Welding simulator with dual-user configuration

Description

FIELD

The general inventive concepts relate to simulated welding training and, more particularly, to systems for and methods of simulated welding training wherein multiple users can interact simultaneously with distinct simulated environments or within the same simulated environment.

BACKGROUND

Learning how to arc weld traditionally takes many hours of instruction, training, and practice. There are many different types of arc welding and arc welding processes that can be learned. Conventionally, welding has been learned by a student using a real welding system to perform actual welding operations on real metal pieces. Such real-world training can tie up scarce welding resources, use up limited and/or costly welding materials, and present safety concerns. Recently, however, the idea of training using welding simulators has become more popular. For example, training in a virtual reality (VR) welding environment or an augmented reality (AR) welding environment can avoid many of the drawbacks of real-world welding training.

Typically, a welding simulator will interface with external components to support a single user at a time. Thus, there is an unmet need for a welding simulator that can support multiple users simultaneously interacting with distinct simulated environments or within the same simulated environment.

SUMMARY

It is proposed herein to provide a welding simulator that can support multiple users simultaneously interacting with distinct simulated environments or within the same simulated environment.

Accordingly, the general inventive concepts relate to and contemplate systems for and methods of performing simulated welding training, wherein two or more users can simultaneously interact with distinct simulated environments or within the same simulated environment. In this manner, the innovative welding simulator can provide new training opportunities across a broad range of users (e.g., students, instructors, collaborators).

In one exemplary embodiment, a welding simulator comprises a first display associated with a first user; a second display associated with a second user; a first mock welding tool associated with the first user; a second mock welding tool associated with the second user; a first stand operable to hold a first coupon; a second stand operable to hold a second coupon; a first spatial tracker for tracking first movements of the first mock welding tool relative to the first coupon by the first user; a second spatial tracker for tracking second movements of the second mock welding tool relative to the second coupon by the second user; and a housing holding logic comprising a memory storing machine-readable instructions and a processor for executing the instructions to generate a simulated environment; and simultaneously display the simulated environment, including at least one of the first movements and the second movements, on the first display and the second display.

In some exemplary embodiments, the first display is part of a welding helmet. In some exemplary embodiments, the second display is part of a welding helmet.

In some exemplary embodiments, the welding simulator further comprises a third display. In some exemplary embodiments, the third display is mounted on the housing.

In some exemplary embodiments, the welding simulator further comprises a fourth display. In some exemplary embodiments, the fourth display is mounted on the housing.

In some exemplary embodiments, the logic displays the first coupon and the second coupon as the same part. In some exemplary embodiments, a weld path is defined on the part, the first movements correspond to a first traversal of the weld path, and the second movements correspond to a second traversal of the weld path.

In some exemplary embodiments, the logic displays the first coupon and the second coupon as portions of the same assembly.

In one exemplary embodiment, a welding simulator comprises a first display associated with a first user; a second display associated with a second user; a first mock welding tool associated with the first user; a second mock welding tool associated with the second user; a first stand operable to hold a first coupon; a second stand operable to hold a second coupon; a first spatial tracker for tracking first movements of the first mock welding tool relative to the first coupon by the first user; a second spatial tracker for tracking second movements of the second mock welding tool relative to the second coupon by the second user; and a housing holding first logic and second logic, wherein the first logic comprises a first memory storing first machine-readable instructions and a first processor for executing the first machine-readable instructions to generate a first simulated environment; and display the first simulated environment and the first movements on the first display; and wherein the second logic comprises a second memory storing second machine-readable instructions and a second processor for executing the second machine-readable instructions to generate a second simulated environment; and display the second simulated environment and the second movements on the second display.

In some exemplary embodiments, the first display is part of a welding helmet. In some exemplary embodiments, the second display is part of a welding helmet.

In some exemplary embodiments, the welding simulator further comprises a third display. In some exemplary embodiments, the third display is mounted on the housing. In some exemplary embodiments, the first logic causes the first simulated environment and the first movements to be displayed on the third display.

In some exemplary embodiments, the welding simulator further comprises a fourth display. In some exemplary embodiments, the fourth display is mounted on the housing. In some exemplary embodiments, the second logic causes the second simulated environment and the second movements to be displayed on the fourth display.

In some exemplary embodiments, the first logic displays the first coupon as a first part and the second logic displays the second coupon as a second part. In some exemplary embodiments, the first part and the second part are identical. In some exemplary embodiments, the first part and the second part are different portions of an assembly.

Numerous other aspects, advantages, and/or features of the general inventive concepts will become more readily apparent from the following detailed description of exemplary embodiments, from the claims, and from the accompanying drawings being submitted herewith.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example embodiment of a system block diagram of a system providing arc welding training in a real-time virtual reality environment;

FIG. 2 illustrates an example embodiment of a combined simulated welding console and observer display device (ODD) of the system of FIG. 1;

FIG. 3 illustrates an example embodiment of the observer display device (ODD) of FIG. 2;

FIG. 4 illustrates an example embodiment of a front portion of the simulated welding console of FIG. 2 showing a physical welding user interface (WUI);

FIG. 5 illustrates an example embodiment of a mock welding tool (MWT) of the system of FIG. 1;

FIG. 6 illustrates an example embodiment of a table/stand (T/S) of the system of FIG. 1;

FIG. 7A illustrates an example embodiment of a pipe welding coupon (WC) of the system of FIG. 1;

FIG. 7B illustrates the pipe WC of FIG. 7A mounted in an arm of the table/stand (TS) of FIG. 6;

FIG. 8 illustrates various elements of an example embodiment of the spatial tracker (ST) of FIG. 1;

FIG. 9A illustrates an example embodiment of a face-mounted display device (FMDD) of the system of FIG. 1;

FIG. 9B is an illustration of how the FMDD of FIG. 9A is secured on the head of a user;

FIG. 9C illustrates an example embodiment of the FMDD of FIG. 9A mounted within a welding helmet;

FIG. 10 illustrates an example embodiment of a subsystem block diagram of a programmable processor-based subsystem (PPS) of the system of FIG. 1;

FIG. 11 illustrates an example embodiment of a block diagram of a graphics processing unit (GPU) of the PPS of FIG. 10;

FIG. 12 illustrates an example embodiment of a functional block diagram of the system of FIG. 1,

FIG. 13 is a flow chart of an embodiment of a method of training using the virtual reality training system of FIG. 1;

FIGS. 14A-14B illustrate the concept of a welding pixel (wexel) displacement map;

FIG. 15 illustrates an example embodiment of a coupon space and a weld space of a flat welding coupon simulated in the simulator;

FIG. 16 illustrates an example embodiment of a coupon space and a weld space of a corner welding coupon simulated in the simulator;

FIG. 17 illustrates an example embodiment of a coupon space and a weld space of a pipe welding coupon simulated in the simulator;

FIG. 18 illustrates an example embodiment of the pipe welding coupon;

FIGS. 19A-19C illustrate an example embodiment of the concept of a dual-displacement puddle model of the simulator;

FIG. 20 illustrates an example embodiment of a welding console of a multi-user welding simulator.

FIG. 21 illustrates a multi-user welding simulator generating two discrete simulated environments.

FIG. 22 illustrates a multi-user welding simulator generating a common simulated environment.

DESCRIPTION

The general inventive concepts encompass systems for and methods of performing simulated welding training, wherein two or more users can simultaneously interact with distinct simulated environments or within the same simulated environment. In some embodiments, a single welding simulator can generate multiple distinct simulated environments, each of the simulated environments supporting the training of a different user at the same time. In some embodiments, a single welding simulator can generate a simulated environment and manage the simultaneous interactions of multiple different users within the simulated environment.

A virtual reality arc welding (VRAW) system is described herein, as an exemplary embodiment of a welding simulator, to put in context the idea of training in a virtual reality welding environment. Subsequently, a learning management system (LMS) is described herein in the context of collecting data from one or more VRAW systems (or similar virtual reality welding systems) and storing and analyzing the data. The data may be representative of simulated welding operations performed by student welders on the VRAW systems, and analysis of the data may be initiated by a welding instructor, for example, to track student progress and provide proper feedback to a student welder.

Virtual Reality Arc Welding System

An embodiment of the present invention provides one or more virtual reality arc welding (VRAW) systems each having a programmable processor-based subsystem, a spatial tracker operatively connected to the programmable processor-based subsystem, at least one mock welding tool capable of being spatially tracked by the spatial tracker, and at least one display device operatively connected to the programmable processor-based subsystem. The system is capable of simulating, in a virtual reality space, a weld puddle having real-time molten metal fluidity and heat dissipation characteristics. The system is also capable of displaying the simulated weld puddle on the display device in real-time. The real-time molten metal fluidity and heat dissipation characteristics of the simulated weld puddle provide real-time visual feedback to a user of the mock welding tool when displayed, allowing the user to adjust or maintain a welding technique in real-time in response to the real-time visual feedback (i.e., helps the user learn to weld correctly). The displayed weld puddle is representative of a weld puddle that would be formed in the real world based on the user's welding technique and the selected welding process and parameters. By viewing a puddle (e.g., shape, color, slag, size, stacked dimes), a user can modify his technique to make a good weld and determine the type of welding being done. The shape of the puddle is responsive to the movement of the gun or stick. As used herein, the term “real-time” means perceiving and experiencing in time in a simulated environment in the same way that a user would perceive and experience in a real-world welding scenario. Furthermore, the weld puddle is responsive to the effects of the physical environment including gravity, allowing a user to realistically practice welding in various positions including overhead welding and various pipe welding angles (e.g., 1G, 2G, 5G, 6G). The system is further capable of saving data associated with a simulated virtual reality welding session for a user (e.g., a student welder).

FIG. 1 illustrates an example embodiment of a system block diagram of a system 100 providing arc welding training in a real-time simulated (e.g., virtual reality) environment. The system 100 includes a programmable processor-based subsystem (PPS) 110 having processing units and computer memory. The system 100 further includes a spatial tracker (ST) 120 operatively connected to the PPS 110. The system 100 also includes a physical welding user interface (WUI) 130 operatively connected to the PPS 110 and a face-mounted display device (FMDD) 140 operatively connected to the PPS 110 and the ST 120. The system 100 further includes an observer display device (ODD) 150 operatively connected to the PPS 110. The system 100 also includes at least one mock welding tool (MWT) 160 operatively connected to the ST 120 and the PPS 110. The system 100 further includes a table/stand (T/S) 170 and at least one welding coupon (WC) 180 capable of being attached to the T/S 170. In accordance with an alternative embodiment of the present invention, a mock gas bottle (not shown) could be provided to simulate a source of shielding gas having an adjustable flow regulator.

FIG. 2 illustrates an example embodiment of a combined simulated welding console 135 (simulating a welding power source user interface) and observer display device (ODD) 150 of the system 100 of FIG. 1. The physical WUI 130 resides on a front portion of the console 135 and provides knobs, buttons, and a joystick for user selection of various modes and functions. The ODD 150 is attached to a top portion of the console 135. The MWT 160 rests in a holder attached to a side portion of the console 135. Internally, the console 135 holds the PPS 110 and a portion of the ST 120. In accordance with an alternative embodiment, the selection of the modes and functions provided by the WUI 130 may be in the form of a touch-screen display.

FIG. 3 illustrates an example embodiment of the observer display device (ODD) 150 of FIG. 2. In accordance with an embodiment of the present invention, the ODD 150 is a liquid crystal display (LCD) device. Other display devices are possible as well. For example, the ODD 150 may be a touchscreen display, in accordance with another embodiment of the present invention. The ODD 150 receives video (e.g., SVGA format) and display information from the PPS 110.

As shown in FIG. 3, the ODD 150 is capable of displaying a first user scene showing various welding parameters 151 including position, tip to work, weld angle, travel angle, and travel speed. These parameters may be selected and displayed in real time in graphical form and are used to teach proper welding technique. Furthermore, as shown in FIG. 3, the ODD 150 is capable of displaying simulated welding discontinuity states 152 including, for example, improper weld size, poor bead placement, concave bead, excessive convexity, undercut, porosity, incomplete fusion, slag inclusion, excess spatter, overfill, and burnthrough (melt through). Undercut is a groove melted into the base metal adjacent to the weld or weld root and left unfilled by weld metal. Undercut is often due to an incorrect angle of welding. Porosity refers to cavity type discontinuities formed by gas entrapment during solidification often caused by moving the arc too far away from the coupon. Data associated with the parameters and states may be stored on the VRAW system for student welders.

Also, as shown in FIG. 3, the ODD 150 is capable of displaying user selections 153 including menu, actions, visual cues, new coupon, and end pass. These user selections are tied to user buttons on the console 135. As a user makes various selections via, for example, a touchscreen of the ODD 150 or via the physical WUI 130, the displayed characteristics can change to provide selected information and other options to the user. Furthermore, the ODD 150 may display a view seen by a welder wearing the FMDD 140 at the same angular view of the welder or at various different angles, for example, chosen by an instructor. The ODD 150 may be viewed by an instructor and/or students for various training purposes. For example, the view may be rotated around the finished weld allowing visual inspection by an instructor. In accordance with an alternate embodiment of the present invention, video from the system 100 may be sent to a remote location via, for example, the Internet for remote viewing and/or critiquing. Furthermore, audio may be provided, allowing real-time audio communication between a student and a remote instructor.

FIG. 4 illustrates an example embodiment of a front portion of the simulated welding console 135 of FIG. 2 showing a physical welding user interface (WUI) 130. The WUI 130 includes a set of buttons 131 corresponding to the user selections 153 displayed on the ODD 150. The buttons 131 may be colored to correspond to the colors of the user selections 153 displayed on the ODD 150. When one of the buttons 131 is pressed, a signal is sent to the PPS 110 to activate the corresponding function. The WUI 130 also includes a joystick 132 capable of being used by a user to select various parameters and selections displayed on the ODD 150. The WUI 130 further includes a dial or knob 133 for adjusting wire feed speed/amps, and another dial or knob 134 for adjusting volts/trim. The WUI 130 also includes a dial or knob 136 for selecting an arc welding process. In accordance with an embodiment of the present invention, three arc welding processes are selectable including flux cored arc welding (FCAW) including gas-shielded and self-shielded processes; gas metal arc welding (GMAW) including short arc, axial spray, STT, and pulse; and shielded metal arc welding (SMAW) including E6010 and E7010 electrodes. In some embodiments, other arc welding processes, such as gas tungsten arc welding (GTAW), could be supported. The WUI 130 further includes a dial or knob 137 for selecting a welding polarity. In accordance with an embodiment of the present invention, three arc welding polarities are selectable including alternating current (AC), positive direct current (DC+), and negative direct current (DC−).

FIG. 5 illustrates an example embodiment of a mock welding tool (MWT) 160 of the system 100 of FIG. 1. The MWT 160 of FIG. 5 simulates a stick welding tool for plate and pipe welding and includes a holder 161 and a simulated stick electrode 162. A trigger on the MWT 160 is used to communicate a signal to the PPS 110 to activate a selected simulated welding process. The simulated stick electrode 162 includes a tactilely resistive tip 163 to simulate resistive feedback that occurs during, for example, a root pass welding procedure in real-world pipe welding or when welding a plate. If the user moves the simulated stick electrode 162 too far back out of the root, the user will be able to feel or sense the lower resistance, thereby deriving feedback for use in adjusting or maintaining the current welding process.

It is contemplated that the stick welding tool may incorporate an actuator, not shown, that withdraws the simulated stick electrode 162 during the virtual welding process. That is to say that as a user engages in virtual welding activity, the distance between holder 161 and the tip of the simulated stick electrode 162 is reduced to simulate consumption of the electrode. The consumption rate, i.e. withdrawal of the simulated stick electrode 162, may be controlled by the PPS 110 and more specifically by coded instructions executed by the PPS 110. The simulated consumption rate may also depend on the user's technique. It is noteworthy to mention here that as the system 100 facilitates virtual welding with different types of electrodes, the consumption rate or reduction of the simulated stick electrode 162 may change with the welding procedure used and/or setup of the system 100.

Other mock welding tools are possible as well, in accordance with other embodiments of the present invention, including a MWT that simulates a hand-held semi-automatic welding gun having a wire electrode fed through the gun, for example. Furthermore, in accordance with other certain embodiments of the present invention, a real welding tool could be used as the MWT 160 to better simulate the actual feel of the tool in the user's hands, even though, in the system 100, the tool would not be used to actually create a real arc. Also, a mock grinding tool may be provided or otherwise simulated, for use in a simulated grinding mode of the simulator 100. Similarly, a mock cutting tool may be provided or otherwise simulated, for use in a simulated cutting mode of the simulator 100. Furthermore, a mock gas tungsten arc welding (GTAW) torch or filler material may be provided or otherwise simulated for use in the simulator 100.

FIG. 6 illustrates an example embodiment of a table/stand (T/S) 170 of the system 100 of FIG. 1. The T/S 170 includes an adjustable table 171, a stand or base 172, an adjustable arm 173, and a vertical post 174. The table 171, the stand 172, and the arm 173 are each attached to the vertical post 174. The table 171 and the arm 173 are each capable of being manually adjusted upward, downward, and rotationally with respect to the vertical post 174. The arm 173 is used to hold various welding coupons (e.g., pipe welding coupon 175) and a user may rest his/her arm on the table 171 when training. The vertical post 174 is indexed with position information such that a user may know exactly where the arm 173 and the table 171 are vertically positioned on the post 174. This vertical position information may be entered into the system by a user using the WUI 130 and the ODD 150.

In accordance with an alternative embodiment of the present invention, the positions of the table 171 and the arm 173 may be automatically set by the PPS 110 via preprogrammed settings, or via the WUI 130 and/or the ODD 150 as commanded by a user. In such an alternative embodiment, the T/S 170 includes, for example, motors and/or servo-mechanisms, and signal commands from the PPS 110 activate the motors and/or servo-mechanisms. In accordance with a further alternative embodiment of the present invention, the positions of the table 171 and the arm 173 and the type of coupon are detected by the system 100. In this way, a user does not have to manually input the position information via the user interface. In such an alternative embodiment, the T/S 170 includes position and orientation detectors and sends signal commands to the PPS 110 to provide position and orientation information, and the pipe welding coupon 175 includes position detecting sensors (e.g., coiled sensors for detecting magnetic fields). A user is able to see a rendering of the T/S 170 adjust on the ODD 150 as the adjustment parameters are changed, in accordance with an embodiment of the present invention.

FIG. 7A illustrates a pipe welding coupon (WC) 175 as an example embodiment of the welding coupon (WC) 180 of the system 100 of FIG. 1. The pipe WC 175 simulates two six inch diameter pipes 175′ and 175″ placed together to form a root 176 to be welded. The pipe WC 175 includes a connection portion 177 at one end of the pipe WC 175, allowing the pipe WC 175 to be attached in a precise and repeatable manner to the arm 173. FIG. 7B illustrates the pipe WC 175 of FIG. 7A mounted on the arm 173 of the table/stand (TS) 170 of FIG. 6. The precise and repeatable manner in which the pipe WC 175 is capable of being attached to the arm 173 allows for spatial calibration of the pipe WC 175 to be performed only once at the factory. Then, in the field, as long as the system 100 is told the position of the arm 173, the system 100 is able to track the MWT 160 and the FMDD 140 with respect to the pipe WC 175 in a simulated environment. A first portion of the arm 173, to which the WC 175 is attached, is capable of being tilted with respect to a second portion of the arm 173, as shown in FIG. 6. This allows the user to practice pipe welding with the pipe in any of several different orientations and angles.

FIG. 8 illustrates various elements of an example embodiment of the spatial tracker (ST) 120 of FIG. 1. The ST 120 is a magnetic tracker that is capable of operatively interfacing with the PPS 110 of the system 100. The ST 120 includes a magnetic source 121 and source cable, at least one sensor 122 and associated cable, host software on disk 123, a power source 124 and associated cable, USB and RS-232 cables 125, and a processor tracking unit 126. The magnetic source 121 is capable of being operatively connected to the processor tracking unit 126 via a cable. The sensor 122 is capable of being operatively connected to the processor tracking unit 126 via a cable. The power source 124 is capable of being operatively connected to the processor tracking unit 126 via a cable. The processor tracking unit 126 is cable of being operatively connected to the PPS 110 via a cable (e.g., the USB or RS-232 cable 125). The host software on disk 123 is capable of being loaded onto the PPS 110 and allows functional communication between the ST 120 and the PPS 110.

Referring to FIG. 6, the magnetic source 121 of the ST 120 is mounted on the first portion of the arm 173. The magnetic source 121 creates a magnetic field around the source 121, including the space encompassing the pipe WC 175 attached to the arm 173, which establishes a 3D spatial frame of reference. The T/S 170 is largely non-metallic (non-ferric and non-conductive) so as not to distort the magnetic field created by the magnetic source 121. The sensor 122 includes three induction coils orthogonally aligned along three spatial directions. The induction coils of the sensor 122 each measure the strength of the magnetic field in each of the three directions and provide that information to the processor tracking unit 126. As a result, the system 100 is able to determine where any portion of the pipe WC 175 is with respect to the 3D spatial frame of reference established by the magnetic field when the pipe WC 175 is mounted on the arm 173. The sensor 122 may be attached to the MWT 160 or to the FMDD 140, allowing the MWT 160 or the FMDD 140 to be tracked by the ST 120 with respect to the 3D spatial frame of reference in both space and orientation. When two sensors 122 are provided and operatively connected to the processor tracking unit 126, both the MWT 160 and the FMDD 140 may be tracked. In this manner, the system 100 is capable of creating a virtual WC, a virtual MWT, and a virtual T/S in virtual reality space and displaying the virtual WC, the virtual MWT, and the virtual T/S on the FMDD 140 and/or the ODD 150 as the MWT 160 and the FMDD 140 are tracked with respect to the 3D spatial frame of reference.

In accordance with an alternative embodiment of the present invention, the sensor(s) 122 may wirelessly interface to the processor tracking unit 126, and the processor tracking unit 126 may wirelessly interface to the PPS 110. In accordance with other alternative embodiments of the present invention, other types of spatial trackers 120 may be used in the system 100 including, for example, an accelerometer/gyroscope-based tracker, an optical tracker (active or passive), an infrared tracker, an acoustic tracker, a laser tracker, a radio frequency tracker, an inertial tracker, and augmented reality based tracking systems. Other types of trackers may be possible as well, including combinations of any of the aforementioned trackers.

FIG. 9A illustrates an example embodiment of the face-mounted display device 140 (FMDD) of the system 100 of FIG. 1. FIG. 9B is an illustration of how the FMDD 140 of FIG. 9A is secured on the head of a user. FIG. 9C illustrates an example embodiment of the FMDD 140 of FIG. 9A integrated into a welding helmet 900. The FMDD 140 operatively connects to the PPS 110 and the ST 120 either via wired means or wirelessly. A sensor 122 of the ST 120 may be attached to the FMDD 140 or to the welding helmet 900, in accordance with various embodiments of the present invention, allowing the FMDD 140 and/or welding helmet 900 to be tracked with respect to the 3D spatial frame of reference created by the ST 120.

In accordance with an embodiment of the present invention, the FMDD 140 includes two high-contrast SVGA 3D OLED microdisplays capable of delivering fluid full-motion video in the 2D and frame sequential video modes. Video of the virtual reality environment is provided and displayed on the FMDD 140. A zoom (e.g., 2x) mode may be provided, allowing a user to simulate a cheater lens, for example.

The FMDD 140 further includes two earbud speakers 910, allowing the user to hear simulated welding-related and environmental sounds produced by the system 100. The FMDD 140 may operatively interface to the PPS 110 via wired or wireless means, in accordance with various embodiments of the present invention. In accordance with an embodiment of the present invention, the PPS 110 provides stereoscopic video to the FMDD 140, providing enhanced depth perception to the user. In accordance with an alternate embodiment of the present invention, a user is able to use a control on the MWT 160 (e.g., a button or switch) to call up and select menus and display options on the FMDD 140. This may allow the user to easily reset a weld if he makes a mistake, change certain parameters, or back up a little to re-do a portion of a weld bead trajectory, for example.

FIG. 10 illustrates an example embodiment of a subsystem block diagram of the programmable processor-based subsystem (PPS) 110 of the system 100 of FIG. 1. The PPS 110 includes a central processing unit (CPU) 111 and two graphics processing units (GPU) 115, in accordance with an embodiment of the present invention. The two GPUs 115 are programmed to provide virtual reality simulation of a weld puddle (also known as a weld pool) having real-time molten metal fluidity and heat absorption and dissipation characteristics, in accordance with an embodiment of the present invention.

FIG. 11 illustrates an example embodiment of a block diagram of a graphics processing unit (GPU) 115 of the PPS 110 of FIG. 10. Each GPU 115 supports the implementation of data parallel algorithms. In accordance with an embodiment of the present invention, each GPU 115 provides two video outputs 118 and 119 capable of providing two virtual reality views. The two GPUs 115 in the PPS 110 of this example embodiment provide a total of four video outputs. Two of the video outputs may be routed to the FMDD 140, rendering the welder's point of view, and a third video output may be routed to the ODD 150, for example, rendering either the welder's point of view or some other point of view. The remaining fourth video output may be routed to a projector, for example. Both GPUs 115 perform the same welding physics computations but may render the virtual reality environment from the same or different points of view. The GPU 115 includes a compute unified device architecture (CUDA) 116 and a shader 117. The CUDA 116 is the computing engine of the GPU 115 which is accessible to software developers through industry standard programming languages. The CUDA 116 includes parallel cores and is used to run the physics model of the weld puddle simulation described herein. The CPU 111 provides real-time welding input data to the CUDA 116 on the GPU 115. The shader 117 is responsible for drawing and applying all of the visuals of the simulation. Bead and puddle visuals are driven by the state of a wexel displacement map which is described later herein. In accordance with an embodiment of the present invention, the physics model runs and updates at a rate of about 30 times per second.

FIG. 12 illustrates an example embodiment of a functional block diagram of the system 100 of FIG. 1. The various functional blocks of the system 100 as shown in FIG. 12 are implemented largely via software instructions and modules running on the PPS 110. The various functional blocks of the system 100 include a physical interface 1201, torch and clamp models 1202, environment models 1203, sound content functionality 1204, welding sounds 1205, stand/table model 1206, internal architecture functionality 1207, calibration functionality 1208, coupon models 1210, welding physics 1211, internal physics adjustment tool (tweaker) 1212, graphical user interface functionality 1213, graphing functionality 1214, student reports functionality 1215, renderer 1216, bead rendering 1217, 3D textures 1218, visual cues functionality 1219, scoring and tolerance functionality 1220, tolerance editor 1221, and special effects 1222.

The internal architecture functionality 1207 provides the higher level software logistics of the processes of the system 100 including, for example, loading files, holding information, managing threads, turning the physics model on, and triggering menus. The internal architecture functionality 1207 runs on the CPU 111, in accordance with an embodiment of the present invention. Certain real-time inputs to the PPS 110 include arc location, gun position, FMDD or helmet position, gun on/off state, and contact made state (yes/no).

The graphical user interface functionality 1213 allows a user, through the ODD 150 using the joystick 132 of the physical user interface 130, to set up a welding scenario. In accordance with an embodiment of the present invention, the setup of a welding scenario includes selecting a language, entering a user name, selecting a practice plate (i.e., a welding coupon), selecting a welding process (e.g., FCAW, GMAW, SMAW) and associated axial spray, pulse, or short arc methods, selecting a gas type and flow rate, selecting a type of stick electrode (e.g., 6010 or 7018), and selecting a type of flux cored wire (e.g., self-shielded, gas-shielded). The setup of a welding scenario also includes selecting a table height, an arm height, an arm position, and an arm rotation of the T/S 170. The setup of a welding scenario further includes selecting an environment (e.g., a background environment in virtual reality space), setting a wire feed speed, setting a voltage level, setting an amperage, selecting a polarity, and turning particular visual cues on or off.

During a simulated welding scenario, the graphing functionality 1214 gathers user performance parameters and provides the user performance parameters to the graphical user interface functionality 1213 for display in a graphical format (e.g., on the ODD 150). Tracking information from the ST 120 feeds into the graphing functionality 1214. The graphing functionality 1214 includes a simple analysis module (SAM) and a whip/weave analysis module (WWAM). The SAM analyzes user welding parameters including welding travel angle, travel speed, weld angle, position, and tip to work distance by comparing the welding parameters to data stored in bead tables. The WWAM analyzes user whipping parameters including dime spacing, whip time, and puddle time. The WWAM also analyzes user weaving parameters including width of weave, weave spacing, and weave timing. The SAM and WWAM interpret raw input data (e.g., position and orientation data) into functionally usable data for graphing. For each parameter analyzed by the SAM and the WWAM, a tolerance window is defined by parameter limits around an optimum or ideal set point input into bead tables using the tolerance editor 1221, and scoring and tolerance functionality 1220 is performed. Various types of student training data such as, for example, parameter data and scoring data may be stored on the VRAW system.

The tolerance editor 1221 includes a weldometer which approximates material usage, electrical usage, and welding time. Furthermore, when certain parameters are out of tolerance, welding discontinuities (i.e., welding defects) may occur. The state of any welding discontinuities are processed by the graphing functionality 1214 and presented via the graphical user interface functionality 1213 in a graphical format. Such welding discontinuities include improper weld size, poor bead placement, concave bead, excessive convexity, undercut, porosity, incomplete fusion, slag entrapment, overfill, burnthrough, and excessive spatter. In accordance with an embodiment of the present invention, the level or amount of a discontinuity is dependent on how far away a particular user parameter is from the optimum or ideal set point.

Different parameter limits may be pre-defined for different types of users such as, for example, welding novices, welding experts, and persons at a trade show. The scoring and tolerance functionality 1220 provides number scores depending on how close to optimum (ideal) a user is for a particular parameter and depending on the level of discontinuities or defects present in the weld. The optimum values are typically derived from real-world data. Information from the scoring and tolerance functionality 1220 and from the graphics functionality 1214 may be used by the student reports functionality 1215 to create a performance report for an instructor and/or a student.

The system 100 is capable of analyzing and displaying the results of virtual welding activity. By analyzing the results, it is meant that system 100 is capable of determining when during the welding pass and where along the weld joints, the user deviated from the acceptable limits of the welding process. A score may be attributed to the user's performance. In one embodiment, the score may be a function of deviation in position, orientation and speed of the mock welding tool 160 through ranges of tolerances, which may extend from an ideal welding pass to marginal or unacceptable welding activity. Any gradient of ranges may be incorporated into the system 100 as chosen for scoring the user's performance. Scoring may be displayed numerically or alpha-numerically. Additionally, the user's performance may be displayed graphically showing, in time and/or position along the weld joint, how closely the mock welding tool traversed the weld joint. Parameters such as travel angle, work angle, speed, and distance from the weld joint are examples of what may be measured, although any parameters may be analyzed for scoring purposes. The tolerance ranges of the parameters are taken from real-world welding data, thereby providing accurate feedback as to how the user will perform in the real world. In another embodiment, analysis of the defects corresponding to the user's performance may also be incorporated and displayed on the ODD 150. In this embodiment, a graph may be depicted indicating what type of discontinuity resulted from measuring the various parameters monitored during the virtual welding activity. While occlusions may not be visible on the ODD 150, defects may still have occurred as a result of the user's performance, the results of which may still be correspondingly displayed (e.g., graphed). Again, various types of student training data such as, for example, parameter data and scoring data may be stored on the VRAW system.

Visual cues functionality 1219 provides immediate feedback to the user by displaying overlaid colors and indicators on the FMDD 140 and/or the ODD 150. Visual cues are provided for each of the welding parameters 151 including position, tip to work distance, weld angle, travel angle, travel speed, and arc length (e.g., for stick welding) and visually indicate to the user if some aspect of the user's welding technique should be adjusted based on the predefined limits or tolerances. Visual cues may also be provided for whip/weave technique and weld bead “dime” spacing, for example. Visual cues may be set independently or in any desired combination.

Calibration functionality 1208 provides the capability to match up physical components in real-world space (3D frame of reference) with visual components in the simulated environment (e.g., in virtual reality space). Each different type of welding coupon (WC) 180 is calibrated in the factory by mounting the WC 180 to the arm 173 of the T/S 170 and touching the WC 180 at predefined points (indicated by, for example, three dimples on the WC 180) with a calibration stylus operatively connected to the ST 120. The ST 120 reads the magnetic field intensities at the predefined points, provides position information to the PPS 110, and the PPS 110 uses the position information to perform the calibration (i.e., the translation from real-world space to virtual reality space).

Any particular type of WC 180 fits into the arm 173 of the T/S 170 in the same repeatable way to within very tight tolerances. Therefore, once a particular WC type is calibrated, that WC type does not have to be re-calibrated (i.e., calibration of a particular type of WC is a one-time event). WCs 180 of the same type are interchangeable. Calibration ensures that physical feedback perceived by the user during a welding process matches up with what is displayed to the user in virtual reality space, making the simulation seem more real. For example, if the user slides the tip of a MWT 160 around the corner of an actual WC 180, the user will see the tip sliding around the corner of the virtual WC on the FMDD 140 as the user feels the tip sliding around the actual corner. In accordance with an embodiment of the present invention, the MWT 160 is placed in a pre-positioned jig and is calibrated as well, based on the known jig position.

In accordance with an alternative embodiment of the present invention, “smart” coupons are provided, having sensors on, for example, the corners of the coupons. The ST 120 is able to track the corners of a “smart” coupon such that the system 100 continuously knows where the “smart” coupon is in real-world 3D space. In accordance with a further alternative embodiment of the present invention, licensing keys are provided to “unlock” welding coupons. When a particular WC 180 is purchased, a licensing key is provided allowing the user to enter the licensing key into the system 100, unlocking the software associated with that WC 180. In accordance with another embodiment of the present invention, special non-standard welding coupons may be provided based on real-world CAD drawings of parts. Users may be able to train on welding a CAD part even before the part is actually produced in the real world.

Sound content functionality 1204 and welding sounds 1205 provide particular types of welding sounds that change depending on if certain welding parameters are within tolerance or out of tolerance. Sounds are tailored to the various welding processes and parameters. For example, in a MIG spray arc welding process, a crackling sound is provided when the user does not have the MWT 160 positioned correctly, and a hissing sound is provided when the MWT 160 is positioned correctly. In a short arc welding process, a steady crackling or frying sound is provided for proper welding technique, and a hissing sound may be provided when undercutting is occurring. These sounds mimic real-world sounds corresponding to correct and incorrect welding technique.

High fidelity sound content may be taken from real-world recordings of actual welding using a variety of electronic and mechanical means, in accordance with various embodiments of the present invention. In accordance with an embodiment of the present invention, the perceived volume and directionality of sound is modified depending on the position, orientation, and distance of the user's head (assuming the user is wearing a FMDD 140 that is tracked by the ST 120) with respect to the simulated arc between the MWT 160 and the WC 180. Sound may be provided to the user via ear bud speakers 910 in the FMDD 140 or via speakers configured in the console 135 or T/S 170, for example.

Environment models 1203 are provided to provide various background scenes (still and moving) in the simulated environment (e.g., virtual reality space). Such background environments may include, for example, an indoor welding shop, an outdoor race track, a garage, etc. and may include moving cars, people, birds, clouds, and various environmental sounds. The background environment may be interactive, in accordance with an embodiment of the present invention. For example, a user may have to survey a background area, before starting welding, to ensure that the environment is appropriate (e.g., safe) for welding. Torch and clamp models 1202 are provided which model various MWTs 160 including, for example, guns, holders with stick electrodes, etc. in virtual reality space.

Coupon models 1210 are provided which model various WCs 180 including, for example, flat plate coupons, T-joint coupons, butt-joint coupons, groove-weld coupons, and pipe coupons (e.g., 2-inch diameter pipe and 6-inch diameter pipe) in virtual reality space. A stand/table model 1206 is provided which models the various parts of the T/S 170 including an adjustable table 171, a stand 172, an adjustable arm 173, and a vertical post 174 in virtual reality space. A physical interface model 1201 is provided which models the various parts of the welding user interface 130, console 135, and ODD 150 in virtual reality space.

In accordance with an embodiment of the present invention, simulation of a weld puddle or pool in virtual reality space is accomplished where the simulated weld puddle has real-time molten metal fluidity and heat dissipation characteristics. At the heart of the weld puddle simulation is the welding physics functionality 1211 (also known as the physics model) which is run on the GPUs 115, in accordance with an embodiment of the present invention. The welding physics functionality employs a double displacement layer technique to accurately model dynamic fluidity/viscosity, solidity, heat gradient (heat absorption and dissipation), puddle wake, and bead shape.

The welding physics functionality 1211 communicates with the bead rendering functionality 1217 to render a weld bead in all states from the heated molten state to the cooled solidified state. The bead rendering functionality 1217 uses information from the welding physics functionality 1211 (e.g., heat, fluidity, displacement, dime spacing) to accurately and realistically render a weld bead in virtual reality space in real-time. The 3D textures functionality 1218 provides texture maps to the bead rendering functionality 1217 to overlay additional textures (e.g., scorching, slag, grain) onto the simulated weld bead. For example, slag may be shown rendered over a weld bead during and just after a welding process, and then removed to reveal the underlying weld bead. The renderer functionality 1216 is used to render various non-puddle specific characteristics using information from the special effects module 1222 including sparks, spatter, smoke, arc glow, fumes and gases, and certain discontinuities such as, for example, undercut and porosity.

The internal physics adjustment tool 1212 is a tweaking tool that allows various welding physics parameters to be defined, updated, and modified for the various welding processes. In accordance with an embodiment of the present invention, the internal physics adjustment tool 1212 runs on the CPU 111 and the adjusted or updated parameters are downloaded to the GPUs 115. The types of parameters that may be adjusted via the internal physics adjustment tool 1212 include parameters related to welding coupons, process parameters that allow a process to be changed without having to reset a welding coupon (allows for doing a second pass), various global parameters that can be changed without resetting the entire simulation, and other various parameters.

FIG. 13 is a flow chart of an embodiment of a method 1300 of training using the virtual reality training system 100 of FIG. 1. In step 1310, a user moves a mock welding tool with respect to a welding coupon in accordance with a welding technique. In step 1320, a welding simulator (e.g., the system 100) tracks position and orientation of the mock welding tool in three-dimensional space. In step 1330, the user views a display of the welding simulator showing a real-time simulation of the mock welding tool and the welding coupon in a simulated environment (e.g., virtual reality space) as the simulated mock welding tool deposits a simulated weld bead material onto at least one simulated surface of the simulated welding coupon by forming a simulated weld puddle in the vicinity of a simulated arc emitting from said simulated mock welding tool. In step 1340, the user views on the display, real-time molten metal fluidity and heat dissipation characteristics of the simulated weld puddle. In step 1350, the user modifies in real-time, at least one aspect of the welding technique in response to viewing the real-time molten metal fluidity and heat dissipation characteristics of the simulated weld puddle.

The method 1300 illustrates how a user is able to view a weld puddle in virtual reality space and modify his welding technique in response to viewing various characteristics of the simulated weld puddle, including real-time molten metal fluidity (e.g., viscosity) and heat dissipation. The user may also view and respond to other characteristics including real-time puddle wake and dime spacing. Viewing and responding to characteristics of the weld puddle is how most welding operations are actually performed in the real world. The double displacement layer modeling of the welding physics functionality 1211, running on the GPUs 115, allows for such real-time molten metal fluidity and heat dissipation characteristics to be accurately modeled and represented to the user. For example, heat dissipation determines solidification time (i.e., how much time it takes for a wexel to completely solidify).

Furthermore, a user may make a second pass over the weld bead material using the same or a different (e.g., a second) mock welding tool and/or welding process. In such a second pass scenario, the simulation shows the simulated mock welding tool, the welding coupon, and the original simulated weld bead material in virtual reality space as the simulated mock welding tool deposits a second simulated weld bead material merging with the first simulated weld bead material by forming a second simulated weld puddle in the vicinity of a simulated arc emitting from the simulated mock welding tool. Additional subsequent passes using the same or different welding tools or processes may be made in a similar manner. In any second or subsequent pass, the previous weld bead material is merged with the new weld bead material being deposited as a new weld puddle is formed in virtual reality space from the combination of any of the previous weld bead material, the new weld bead material, and possibly the underlying coupon material, in accordance with certain embodiments of the present invention. Such subsequent passes may be needed to make a large fillet or groove weld, performed to repair a weld bead formed by a previous pass, for example, or may include a hot pass and one or more fill and cap passes after a root pass as is done in pipe welding. In accordance with various embodiments of the present invention, weld bead and base material may include mild steel, stainless steel, aluminum, nickel based alloys, or other materials. Again, various types of student training data such as, for example, parameter data and scoring data may be stored on the VRAW system and may be used later with respect to a learning management system (LMS) as described later herein. Other types of student training data may be stored as well such as, for example, student identifying data.

Engine for Modeling

FIGS. 14A-14B illustrate the concept of a welding element (wexel) displacement map 1420, in accordance with an embodiment of the present invention. FIG. 14A shows a side view of a flat welding coupon 1400 having a flat top surface 1410. The welding coupon 1400 exists in the real world as, for example, a plastic part, and also exists in virtual reality space as a simulated welding coupon (e.g., simulating a metal workpiece). FIG. 14B shows a representation of the top surface 1410 of the simulated welding coupon 1400 broken up into a grid or array of welding elements, termed “wexels” forming a wexel map 1420. Each wexel (e.g., wexel 1421) defines a small portion of the surface 1410 of the welding coupon. The wexel map defines the surface resolution. Changeable channel parameter values are assigned to each wexel, allowing values of each wexel to dynamically change in real-time in the simulated environment (e.g., virtual reality weld space) during a simulated welding process. The changeable channel parameter values correspond to the channels Puddle (molten metal fluidity/viscosity displacement), Heat (heat absorption/dissipation), Displacement (solid displacement), and Extra (various extra states, e.g., slag, grain, scorching, virgin metal). These changeable channels are referred to herein as PHED for Puddle, Heat, Extra, and Displacement, respectively.

FIG. 15 illustrates an example embodiment of a coupon space and a weld space of the flat welding coupon 1400 of FIG. 14A simulated in the welding training system 100 of FIG. 1. Points 0, X, Y, and Z define the local 3D coupon space. In general, each coupon type defines the mapping from 3D coupon space to 2D virtual reality weld space. The wexel map 1420 of FIG. 14B is a two-dimensional array of values that map to weld space in virtual reality. A user is to weld from point B to point E as shown in FIG. 15. A trajectory line from point B to point E is shown in both 3D coupon space and 2D weld space in FIG. 15.

Each type of coupon defines the direction of displacement for each location in the wexel map. For the flat welding coupon of FIG. 15, the direction of displacement is the same at all locations in the wexel map (i.e., in the Z-direction). The texture coordinates of the wexel map are shown as S, T (sometimes called U, V) in both 3D coupon space and 2D weld space, in order to clarify the mapping. The wexel map is mapped to and represents the rectangular surface 1410 of the welding coupon 1400.

FIG. 16 illustrates an example embodiment of a coupon space and a weld space of a corner welding coupon 1600 simulated in the system 100. The corner welding coupon 1600 has two surfaces 1610 and 1620 in 3D coupon space that are mapped to 2D weld space as shown in FIG. 16. Again, points 0, X, Y, and Z define the local 3D coupon space. The texture coordinates of the wexel map are shown as S, T in both 3D coupon space and 2D weld space, in order to clarify the mapping. A user is to weld from point B to point E as shown in FIG. 16. A trajectory line from point B to point E is shown in both 3D coupon space and 2D weld space in FIG. 16. However, the direction of displacement is towards the line X′-0′ as shown in the 3D coupon space, towards the opposite corner.

FIG. 17 illustrates an example embodiment of a coupon space and a weld space of a pipe welding coupon 1700 simulated in the system 100. The pipe welding coupon 1700 has a curved surface 1710 in 3D coupon space that is mapped to 2D weld space. Points 0, X, Y, and Z once again define the local 3D coupon space. The texture coordinates of the wexel map are shown as S, T in both 3D coupon space and 2D weld space, in order to clarify the mapping. A user is to weld from point B to point E along a curved trajectory as shown in FIG. 17. A trajectory curve and line from point B to point E is shown in 3D coupon space and 2D weld space, respectively. The direction of displacement is away from the line Y-0 (i.e., away from the center of the pipe). FIG. 18 illustrates an example embodiment of the pipe welding coupon 1700 of FIG. 17. The pipe welding coupon 1700 is made of a non-ferric, non-conductive plastic and simulates two pipe pieces 1701 and 1702 coming together to form a root joint 1703. An attachment piece 1704 for attaching to the arm 173 of the stand 170 is also shown.

In a similar manner that a texture map may be mapped to a rectangular surface area of a geometry, a weldable wexel map may be mapped to a rectangular surface of a welding coupon. Each element of the weldable map is termed a wexel in the same sense that each element of a picture is termed a pixel (a contraction of picture element). A pixel contains channels of information that define a color (e.g., red, green, blue). A wexel contains channels of information (e.g., P, H, E, D) that define a weldable surface in virtual reality space.

In accordance with an embodiment of the present invention, the format of a wexel is summarized as channels PHED (Puddle, Heat, Extra, Displacement) which contains four floating point numbers. The Extra channel is treated as a set of bits which store logical information about the wexel such as, for example, whether or not there is any slag at the wexel location. The Puddle channel stores a displacement value for any liquefied metal at the wexel location. The Displacement channel stores a displacement value for the solidified metal at the wexel location. The Heat channel stores a value giving the magnitude of heat at the wexel location. In this way, the weldable part of the coupon can show displacement due to a welded bead, a shimmering surface “puddle” due to liquid metal, color due to heat, etc. All of these effects are achieved by the vertex and pixel shaders applied to the weldable surface.

In accordance with an embodiment of the present invention, a displacement map and a particle system are used where the particles can interact with each other and collide with the displacement map. The particles are virtual dynamic fluid particles and provide the liquid behavior of the weld puddle but are not rendered directly (i.e., are not visually seen directly). Instead, only the particle effects on the displacement map are visually seen. Heat input to a wexel affects the movement of nearby particles. There are two types of displacement involved in simulating a welding puddle which include Puddle and Displacement. Puddle displacement is “temporary” and only lasts as long as there are particles and heat present. Displacement is “permanent.” Puddle displacement is the liquid metal of the weld which changes rapidly (e.g., shimmers) and can be thought of as being “on top” of the Displacement. The particles overlay a portion of a virtual surface displacement map (i.e., a wexel map). The Displacement represents the permanent solid metal including both the initial base metal and the weld bead that has solidified.

In accordance with an embodiment of the present invention, the simulated welding process in virtual reality space works as follows: Particles stream from the emitter (emitter of the simulated mock welding tool 160) in a thin cone. The particles make first contact with the surface of the simulated welding coupon where the surface is defined by a wexel map. The particles interact with each other and the wexel map and build up in real-time. More heat is added the nearer a wexel is to the emitter. Heat is modeled in dependence on distance from the arc point and the amount of time that heat is input from the arc. Certain visuals (e.g., color) are driven by the heat. A weld puddle is drawn or rendered in virtual reality space for wexels having enough heat. Wherever it is hot enough, the wexel map liquefies, causing the Puddle displacement to “raise up” for those wexel locations. Puddle displacement is determined by sampling the “highest” particles at each wexel location. As the emitter moves on along the weld trajectory, the wexel locations left behind cool. Heat is removed from a wexel location at a particular rate. When a cooling threshold is reached, the wexel map solidifies. As such, the Puddle displacement is gradually converted to Displacement (i.e., a solidified bead). Displacement added is equivalent to Puddle removed such that the overall height does not change. Particle lifetimes are tweaked or adjusted to persist until solidification is complete. Certain particle properties that are modeled in the system 100 include attraction/repulsion, velocity (related to heat), dampening (related to heat dissipation), and direction (related to gravity).

FIGS. 19A-19C illustrate an example embodiment of the concept of a dual-displacement (displacement and particles) puddle model of the system 100. Welding coupons are simulated in a simulated environment (e.g., virtual reality space) having at least one surface. The surfaces of the welding coupon are simulated in virtual reality space as a double displacement layer including a solid displacement layer and a puddle displacement layer. The puddle displacement layer is capable of modifying the solid displacement layer.

As described herein, “puddle” is defined by an area of the wexel map where the Puddle value has been raised up by the presence of particles. The sampling process is represented in FIGS. 19A-19C. A section of a wexel map is shown having seven adjacent wexels. The current Displacement values are represented by un-shaded rectangular bars 1910 of a given height (i.e., a given displacement for each wexel). In FIG. 19A, the particles 1920 are shown as round un-shaded dots colliding with the current Displacement levels and are piled up. In FIG. 19B, the “highest” particle heights 1930 are sampled at each wexel location. In FIG. 19C, the shaded rectangles 1940 show how much Puddle has been added on top of the Displacement as a result of the particles. The weld puddle height is not instantly set to the sampled values since Puddle is added at a particular liquification rate based on Heat. Although not shown in FIGS. 19A-19C, it is possible to visualize the solidification process as the Puddle (shaded rectangles) gradually shrinks and the Displacement (unshaded rectangles) gradually grows from below to exactly take the place of the Puddle. In this manner, real-time molten metal fluidity characteristics are accurately simulated. As a user practices a particular welding process, the user is able to observe the molten metal fluidity characteristics and the heat dissipation characteristics of the weld puddle in real-time in virtual reality space and use this information to adjust or maintain his welding technique.

The number of wexels representing the surface of a welding coupon is fixed. Furthermore, the puddle particles that are generated by the simulation to model fluidity are temporary, as described herein. Therefore, once an initial puddle is generated in virtual reality space during a simulated welding process using the welding training system 100, the number of wexels plus puddle particles tends to remain relatively constant. This is because the number of wexels that are being processed is fixed and the number of puddle particles that exist and are being processed during the welding process tend to remain relatively constant because puddle particles are being created and “destroyed” at a similar rate (i.e., the puddle particles are temporary). Therefore, the processing load of the logic processor-based subsystem 110 remains relatively constant during a simulated welding session.

In accordance with an alternate embodiment of the present invention, puddle particles may be generated within or below the surface of the welding coupon. In such an embodiment, displacement may be modeled as being positive or negative with respect to the original surface displacement of a virgin (i.e., un-welded) coupon. In this manner, puddle particles may not only build up on the surface of a welding coupon, but may also penetrate the welding coupon. However, the number of wexels is still fixed and the puddle particles being created and destroyed is still relatively constant.

In accordance with alternate embodiments of the present invention, instead of modeling particles, a wexel displacement map may be provided having more channels to model the fluidity of the puddle. Or, instead of modeling particles, a dense voxel map may be modeled. Or, instead of a wexel map, only particles may be modeled which are sampled and never go away. Such alternative embodiments may not provide a relatively constant processing load for the system 100, however.

Furthermore, in accordance with an embodiment of the present invention, blowthrough or a keyhole is simulated by taking material away. For example, if a user keeps an arc in the same location for too long, in the real world, the material would burn away causing a hole. Such real-world burnthrough is simulated in the system 100 by wexel decimation techniques. If the amount of heat absorbed by a wexel is determined to be too high by the system 100, that wexel may be flagged or designated as being burned away and rendered as such (e.g., rendered as a hole). Subsequently, however, wexel re-constitution may occur for certain welding process (e.g., pipe welding) where material is added back after being initially burned away. In general, the system 100 simulates wexel decimation (taking material away) and wexel reconstitution (adding material back).

Furthermore, removing material in root-pass welding is properly simulated in the system 100. For example, in the real world, grinding of the root pass may be performed prior to subsequent welding passes. Similarly, the system 100 may simulate a grinding pass that removes material from the virtual weld joint. It will be appreciated that the material removed is modeled as a negative displacement on the wexel map. That is to say that the grinding pass removes material that is modeled by the system 100 resulting in an altered bead contour. Simulation of the grinding pass may be automatic, which is to say that the system 100 removes a predetermined thickness of material, which may be respective to the surface of the root pass weld bead. In an alternate embodiment, an actual grinding tool, or grinder, may be simulated that turns on and off by activation of the mock welding tool 160 or another input device. It is noted that the grinding tool may be simulated to resemble a real-world grinder. In this embodiment, the user maneuvers the grinding tool along the root pass to remove material responsive to the movement thereof. It will be understood that the user may be allowed to remove too much material. In a manner similar to that described above, holes or keyholes, or other defects (described above) may result if the user “grinds away” to much material. Still, hard limits or stops may be implemented, i.e. programmed, to prevent the user from removing too much material or indicate when too much material is being removed.

In addition to the non-visible “puddle” particles described herein, the system 100 also uses three other types of visible particles to represent Arc, Flame, and Spark effects, in accordance with an embodiment of the present invention. These types of particles do not interact with other particles of any type but interact only with the displacement map. While these particles do collide with the simulated weld surface, they do not interact with each other. Only Puddle particles interact with each other, in accordance with an embodiment of the present invention. The physics of the Spark particles is setup such that the Spark particles bounce around and are rendered as glowing dots in the simulated environment (e.g., virtual reality space).

The physics of the Arc particles is setup such that the Arc particles hit the surface of the simulated coupon or weld bead and stay for a while. The Arc particles are rendered as larger dim bluish-white spots in virtual reality space. It takes many such spots superimposed to form any sort of visual image. The end result is a white glowing nimbus with blue edges.

The physics of the Flame particles is modeled to slowly raise upward. The Flame particles are rendered as medium sized dim red-yellow spots. It takes many such spots superimposed to form any sort of visual image. The end result is blobs of orange-red flames with red edges raising upward and fading out. Other types of non-puddle particles may be implemented in the system 100, in accordance with other embodiments of the present invention. For example, smoke particles may be modeled and simulated in a similar manner to flame particles.

The final steps in the simulated visualization are handled by the vertex and pixel shaders provided by the shaders 117 of the GPUs 115. The vertex and pixel shaders apply Puddle and Displacement, as well as surface colors and reflectivity altered due to heat, etc. The Extra (E) channel of the PHED wexel format, as discussed earlier herein, contains all of the extra information used per wexel. In accordance with an embodiment of the present invention, the extra information includes a non virgin bit (true=bead, false=virgin steel), a slag bit, an undercut value (amount of undercut at this wexel where zero equals no undercut), a porosity value (amount of porosity at this wexel where zero equals no porosity), and a bead wake value which encodes the time at which the bead solidifies. There are a set of image maps associated with different coupon visuals including virgin steel, slag, bead, and porosity. These image maps are used both for bump mapping and texture mapping. The amount of blending of these image maps is controlled by the various flags and values described herein.

A bead wake effect is achieved using a 1D image map and a per wexel bead wake value that encodes the time at which a given bit of bead is solidified. Once a hot puddle wexel location is no longer hot enough to be called “puddle,” a time is saved at that location and is called “bead wake.” The end result is that the shader code is able to use the 1D texture map to draw the “ripples” that give a bead its unique appearance which portrays the direction in which the bead was laid down. In accordance with an alternative embodiment of the present invention, the system 100 is capable of simulating, in virtual reality space, and displaying a weld bead having a real-time weld bead wake characteristic resulting from a real-time fluidity-to-solidification transition of the simulated weld puddle, as the simulated weld puddle is moved along a weld trajectory.

Multi-User Configuration

In conventional welding training systems, a single console (e.g., the console 135) is designed to interface with a single work station (e.g., the T/S 170) so that a single user can engage in a simulated welding exercise. Thus, only a single user display (e.g., the FMDD 140) and a single mock welding tool (e.g., the MWT 160) are provided. Likewise, the console need only be interfaced with a single additional display device (e.g., the ODD 150) so that a third-party can observe the user interacting with a simulated environment generated by the console. Conversely, the general inventive concepts encompass welding training systems that support multiple users interacting simultaneously with distinct simulated environments or within the same simulated environment.

A welding training system 2000 (i.e., a welding simulator) according to an example embodiment is shown in FIG. 20. The welding simulator 2000 includes a console 2035 for interfacing with a first table/stand (T/S) 2010 and a second table/stand (T/S) 2015. The first T/S 2010 is associated with a first user, while the second T/S 2015 is associated with a second user. While the T/S 2010 and the T/S 2015 can be the same as the T/S 170 described above, the general inventive concepts are not so limited and can encompass any suitable workstation for interfacing with the welding simulator 2000. Additionally, it will be appreciated that the general inventive concepts are extendable to more than two such workstations.

Likewise, while much of the console 2035 can be similar to the console 135 described above, there are necessary differences. For example, in some embodiments, the console 2035 is interfaced with a first observer display device (ODD) 2020 and a second observer display device (ODD) 2025. In some embodiments, a single observer display device (ODD), operating in a split-screen mode, could be used instead of the ODD 2020 and the ODD 2025. Additionally, the console 2035 is able to interface or otherwise communicate with separate mock welding tools (e.g., the mock welding tool 160) associated with each of the first user and the second user, respectively. Likewise, the console 2035 is able to interface or otherwise communicate with separate displays (e.g., the FMDD 140) associated with each of the first user and the second user, respectively.

In some embodiments, the console 2035 is interfaced with a first spatial tracker (e.g., the ST 120) associated with the first T/S 2010 and a second spatial tracker (e.g., the ST 120) associated with the second T/S 2015. In some embodiments, the console 2035 is interfaced with a single spatial tracker capable of defining a 3D spatial frame of reference that encompasses the relevant work area of both the first T/S 2010 and the second T/S 2015.

In some embodiments, the console 2035 has a single physical welding user interface (WUI) (e.g., the WUI 130) that can be shared by the first user and the second user.

In some embodiments, the console 2035 houses a first programmable processor-based subsystem (PPS) (e.g., the PPS110) associated with the first user and a second programmable processor-based subsystem (PPS) (e.g., the PPS110) associated with the second user. For example, separate motherboards may be installed in the console 2035. In some embodiments, the console 2035 houses a single programmable processor-based subsystem (PPS) (e.g., the PPS110) that is capable of generating either separate distinct simulated environments for the first user and the second user (and processing the respective interactions therewith) or generating a common simulated environment for the first user and the second user (and processing the respective interactions therewith).

The welding training system 2000 supports functionality that conventional welding training systems lack. For example, an instructor can observe the simultaneous welding training of a first student (i.e., the first user) and a second student (i.e., the second user) at the console 2035 via the first ODD 2020 and the second ODD 2025. In this scenario, each student is likely interacting with a distinct simulated environment. The instructor does not have to move from the workstation (e.g., the T/S 2010) of the first student to the workstation (e.g., the T/S 2015) of the second student to observe the performance of both students. Furthermore, in some embodiments, the first student and the second student are performing the same welding exercise (e.g., welding process), which facilitates comparison of the two students by the instructor. This is particularly true if both students begin the simulation at the same time.

As another example, the instructor could use one of the workstations (e.g., the T/S 2015) to demonstrate a welding technique to a student (e.g., the first user) in a common simulated environment. Here, the instructor's welding movements would be observable to the first user via the first user's FMDD. Thus, the welding simulator 2000 allows for simulated “hands on” demonstration by the instructor. Likewise, the instructor could interact with a simulated weld initially performed by the first user, such as to teach a remedial welding (e.g., repair) technique.

In the case of a common simulated environment, two different students could be simultaneously performing simulated welds on parts of a common assembly (shown in the common simulated environment). Again, the activities of both students would be visible to the instructor via the ODDs 2020, 2025 on the console 2035. Likewise, the two students could be taking turns practicing simulated welds that are complementary to one another, such as a root pass and fill pass. Again, the activities of both students would be visible to the instructor via the ODDs 2020, 2025 on the console 2035.

Given the increased flexibility of the welding simulator 2000, one of ordinary skill in the art will recognize many other applications thereof. The functionality of the welding simulator 2000 will be more generally described with reference to FIGS. 21 and 22.

As shown in FIG. 21, a multi-user welding simulator 2100 (e.g., the welding simulator 2000) includes a console 2102 that houses the PPS and other related components. The console 2102 is interfaced with a first workstation 2104 associated with a first user 2106 and a second workstation 2108 associated with a second user 2110. Each of the workstations 2104, 2108 includes those components (e.g., T/S, ST, WC, MWT, FMDD) necessary for the users 2106, 2110 to engage in simulated welding training. The welding simulator 2100 generates a first simulated environment 2112, such as a virtual reality space or an augmented reality space. The welding simulator 2100 also generates a second simulated environment 2114, such as a virtual reality space or an augmented reality space. The first simulated environment 2112 is visible to the first user 2106 but not the second user 2110. Likewise, the second simulated environment 2114 is visible to the second user 2110 but not the first user 2106. The welding simulator 2100 is able to process the simultaneous interactions of the first user 2106 with the first simulated environment 2112 and the second user 2110 with the second simulated environment 2114 in real time.

As shown in FIG. 22, the multi-user welding simulator 2100 can also generate a single (common) simulated environment 2120, such as a virtual reality space or an augmented reality space. The simulated environment 2120 is visible to both the first user 2106 and the second user 2110. The welding simulator 2100 is able to process the simultaneous interactions of the first user 2106 and the second user 2110 with the common simulated environment 2120 in real time.

While the embodiments discussed herein have been related to the systems and methods discussed above, these embodiments are intended to be exemplary and are not intended to limit the applicability of these embodiments to only those discussions set forth herein. The control systems and methodologies discussed herein are equally applicable to, and can be utilized in, systems and methods related to the simulation of arc welding, laser welding, brazing, soldering, plasma cutting, waterjet cutting, laser cutting, and any other systems or methods using similar control methodology, without departing from the spirit and scope of the above discussed inventions. The embodiments and discussions herein can be readily incorporated into any of these systems and methodologies by those of skill in the art.

While the invention has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from its scope. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.

Claims

1. A welding simulator comprising: a first display associated with a first user;a second display associated with a second user;a first mock welding tool associated with the first user;a second mock welding tool associated with the second user;a first stand operable to hold a first coupon;a second stand operable to hold a second coupon;a first spatial tracker for tracking first movements of the first mock welding tool relative to the first coupon by the first user;a second spatial tracker for tracking second movements of the second mock welding tool relative to the second coupon by the second user; anda housing holding logic comprising a memory storing machine-readable instructions and a processor for executing the instructions to: generate a simulated environment; andsimultaneously display the simulated environment, including the first movements and the second movements, on the first display and the second display.
2. The welding simulator of claim 1, wherein the first display is part of a welding helmet.
3. The welding simulator of claim 1, wherein the second display is part of a welding helmet.
4. The welding simulator of claim 1, further comprising a third display.
5. The welding simulator of claim 4, wherein the third display is mounted on the housing.
6. The welding simulator of claim 4, further comprising a fourth display.
7. The welding simulator of claim 6, wherein the fourth display is mounted on the housing.
8. The welding simulator of claim 1, wherein the logic displays the first coupon and the second coupon as a same part.
9. The welding simulator of claim 8, wherein a weld path is defined on the same part, wherein the first movements correspond to a first traversal of the weld path, andwherein the second movements correspond to a second traversal of the weld path.
10. The welding simulator of claim 1, wherein the logic displays the first coupon and the second coupon as portions of the same assembly.
11. A welding simulator comprising: a first display associated with a first user;a second display associated with a second user;a first mock welding tool associated with the first user;a second mock welding tool associated with the second user;a first stand operable to hold a first coupon;a second stand operable to hold a second coupon;a first spatial tracker for tracking first movements of the first mock welding tool relative to the first coupon by the first user;a second spatial tracker for tracking second movements of the second mock welding tool relative to the second coupon by the second user; anda housing holding first logic and second logic,wherein the first logic comprises a first memory storing first machine-readable instructions and a first processor for executing the first machine-readable instructions to: generate a first simulated environment; anddisplay the first simulated environment and the first movements on the first display; andwherein the second logic comprises a second memory storing second machine-readable instructions and a second processor for executing the second machine-readable instructions to: generate a second simulated environment; anddisplay the second simulated environment and the second movements on the second display.
12. The welding simulator of claim 11, wherein the first display is part of a welding helmet.
13. The welding simulator of claim 11, wherein the second display is part of a welding helmet.
14. The welding simulator of claim 11, further comprising a third display.
15. The welding simulator of claim 14, wherein the third display is mounted on the housing.
16. The welding simulator of claim 14, wherein the first logic causes the first simulated environment and the first movements to be displayed on the third display.
17. The welding simulator of claim 16, further comprising a fourth display.
18. The welding simulator of claim 17, wherein the fourth display is mounted on the housing.
19. The welding simulator of claim 17, wherein the second logic causes the second simulated environment and the second movements to be displayed on the fourth display.
20. The welding simulator of claim 11, wherein the first logic displays the first coupon as a first part; and wherein the second logic displays the second coupon as a second part.
21. The welding simulator of claim 20, wherein the first part and the second part are identical.
22. The welding simulator of claim 20, wherein the first part and the second part are different portions of an assembly.

CROSS-REFERENCE TO RELATED APPLICATION

This U.S. patent application claims the benefit of and priority to U.S. provisional patent application Ser. No. 62/659,729 filed on Apr. 19, 2018, the entire disclosure of which is incorporated herein by reference.

US Referenced Citations (478)

Number	Name	Date	Kind
317063	Wittenstrom	May 1885	A
428459	Coffin	May 1890	A
483428	Goppin	Sep 1892	A
1159119	Springer	Nov 1915	A
1286529	Cave	Dec 1918	A
2326944	Holand et al.	Aug 1943	A
2333192	Mobert	Nov 1943	A
D140630	Garibay	Mar 1945	S
D142377	Dunn	Sep 1945	S
D152049	Welch	Dec 1948	S
2681969	Burke	Jun 1954	A
D174208	Abidgaard	Mar 1955	S
2728838	Barnes	Dec 1955	A
D176942	Cross	Feb 1956	S
2894086	Rizer	Jul 1959	A
3035155	Hawk	May 1962	A
3059519	Stanton	Oct 1962	A
3356823	Waters et al.	Dec 1967	A
3555239	Kerth	Jan 1971	A
3562927	Moskowitz	Feb 1971	A
3562928	Schmitt	Feb 1971	A
3621177	McPherson et al.	Nov 1971	A
3654421	Streetman et al.	Apr 1972	A
3690020	McBratnie	Sep 1972	A
3739140	Rotilio	Jun 1973	A
3852917	McKown	Dec 1974	A
3866011	Cole	Feb 1975	A
3867769	Schow et al.	Feb 1975	A
3904845	Minkiewicz	Sep 1975	A
3988913	Metcalfe et al.	Nov 1976	A
D243459	Bliss	Feb 1977	S
4024371	Drake	May 1977	A
4041615	Whitehill	Aug 1977	A
D247421	Driscoll	Mar 1978	S
4124944	Blair	Nov 1978	A
4132014	Schow	Jan 1979	A
4237365	Lambros et al.	Dec 1980	A
4280041	Kiessling et al.	Jul 1981	A
4280137	Ashida et al.	Jul 1981	A
4314125	Nakamura	Feb 1982	A
4354087	Osterlitz	Oct 1982	A
4359622	Dostoomian et al.	Nov 1982	A
4375026	Kearney	Feb 1983	A
4410787	Kremers et al.	Oct 1983	A
4429266	Traadt	Jan 1984	A
4452589	Denison	Jun 1984	A
D275292	Bouman	Aug 1984	S
D277761	Korovin et al.	Feb 1985	S
4525619	Ide et al.	Jun 1985	A
D280329	Bouman	Aug 1985	S
4555614	Morris et al.	Nov 1985	A
4611111	Baheti et al.	Sep 1986	A
4616326	Meier et al.	Oct 1986	A
4629860	Lindborn	Dec 1986	A
4677277	Cook et al.	Jun 1987	A
4680014	Paton et al.	Jul 1987	A
4689021	Vasiliev et al.	Aug 1987	A
4707582	Beyer	Nov 1987	A
4716273	Paton et al.	Dec 1987	A
D297704	Bulow	Sep 1988	S
4812614	Wang et al.	Mar 1989	A
4867685	Brush et al.	Sep 1989	A
4877940	Bangs et al.	Oct 1989	A
4897521	Burr	Jan 1990	A
4907973	Hon	Mar 1990	A
4931018	Herbst et al.	Jun 1990	A
4973814	Kojima	Nov 1990	A
4998050	Nishiyama et al.	Mar 1991	A
5034593	Rice et al.	Jul 1991	A
5061841	Richardson	Oct 1991	A
5089914	Prescott	Feb 1992	A
5192845	Kirmsse et al.	Mar 1993	A
5206472	Myking et al.	Apr 1993	A
5266930	Ichikawa et al.	Nov 1993	A
5283418	Bellows et al.	Feb 1994	A
5285916	Ross	Feb 1994	A
5288968	Cecil	Feb 1994	A
5305183	Teynor	Apr 1994	A
5320538	Baum	Jun 1994	A
5337611	Fleming et al.	Aug 1994	A
5360156	Ishizaka et al.	Nov 1994	A
5360960	Shirk	Nov 1994	A
5362962	Barborak et al.	Nov 1994	A
5370071	Ackermann	Dec 1994	A
D359296	Witherspoon	Jun 1995	S
5424634	Goldfarb et al.	Jun 1995	A
5436638	Bolas et al.	Jul 1995	A
5464957	Kidwell et al.	Nov 1995	A
5465037	Huissoon et al.	Nov 1995	A
D365583	Viken	Dec 1995	S
5493093	Cecil et al.	Feb 1996	A
5547052	Latshaw	Aug 1996	A
5562843	Yasumoto	Oct 1996	A
5662822	Tada et al.	Sep 1997	A
5670071	Tomoyuki et al.	Sep 1997	A
5676503	Lang	Oct 1997	A
5676867	Van Allen	Oct 1997	A
5708253	Bloch et al.	Jan 1998	A
5710405	Solomon et al.	Jan 1998	A
5719369	White et al.	Feb 1998	A
D392534	Degen et al.	Mar 1998	S
5728991	Takada et al.	Mar 1998	A
5751258	Fergason et al.	May 1998	A
D395296	Kaya et al.	Jun 1998	S
5774110	Edelson	Jun 1998	A
D396238	Schmitt	Jul 1998	S
5781258	Debral et al.	Jul 1998	A
5823785	Matherne, Jr.	Oct 1998	A
5835077	Dao et al.	Nov 1998	A
5835277	Hegg	Nov 1998	A
5845053	Watanabe et al.	Dec 1998	A
5877777	Colwell	Mar 1999	A
5963891	Walker et al.	Oct 1999	A
6008470	Zhang et al.	Dec 1999	A
6037948	Liepa	Mar 2000	A
6049059	Kim	Apr 2000	A
6051805	Vaidya et al.	Apr 2000	A
6114645	Burgess	Sep 2000	A
6155475	Ekelof et al.	Dec 2000	A
6155928	Burdick	Dec 2000	A
6230327	Briand et al.	May 2001	B1
6236013	Delzenne et al.	May 2001	B1
6236017	Smartt et al.	May 2001	B1
6242711	Cooper	Jun 2001	B1
6271500	Hirayam et al.	Aug 2001	B1
6301763	Pryor	Oct 2001	B1
6330938	Herve et al.	Dec 2001	B1
6330966	Eissfeller	Dec 2001	B1
6331848	Stove et al.	Dec 2001	B1
D456428	Aronson et al.	Apr 2002	S
6373465	Jolly et al.	Apr 2002	B2
6377011	Ben-Ur	Apr 2002	B1
D456828	Aronson et al.	May 2002	S
6396232	Paa et al.	May 2002	B2
D461383	Blackburn	Aug 2002	S
6427352	Pfeiffer et al.	Aug 2002	B1
6441342	Hsu	Aug 2002	B1
6445964	White et al.	Sep 2002	B1
6492618	Flood et al.	Dec 2002	B1
6506997	Matsuyama	Jan 2003	B2
6552303	Blankenship	Apr 2003	B1
6560029	Dobbie et al.	May 2003	B1
6563489	Latypov et al.	May 2003	B1
6568846	Cote et al.	May 2003	B1
D475726	Suga et al.	Jun 2003	S
6572379	Sears et al.	Jun 2003	B1
6583386	Ivkovich	Jun 2003	B1
6593540	Baker	Jul 2003	B1
6621049	Suzuki	Sep 2003	B2
6624388	Blankenship	Sep 2003	B1
D482171	Vui et al.	Nov 2003	S
6647288	Madill et al.	Nov 2003	B2
6649858	Wakeman	Nov 2003	B2
6655645	Lu et al.	Dec 2003	B1
6660965	Simpson	Dec 2003	B2
6679702	Rau	Jan 2004	B1
6697701	Hillen et al.	Feb 2004	B2
6697770	Nagetgaal	Feb 2004	B1
6703585	Suzuki	Mar 2004	B2
6708385	Lemelson	Mar 2004	B1
6710298	Eriksson	Mar 2004	B2
6710299	Blankenship et al.	Mar 2004	B2
6715502	Rome et al.	Apr 2004	B1
D490347	Meyers	May 2004	S
6730875	Hsu	May 2004	B2
6734393	Friedl et al.	May 2004	B1
6744011	Hu et al.	Jun 2004	B1
6750428	Okamoto et al.	Jun 2004	B2
6765584	Matthias	Jul 2004	B1
6772802	Few	Aug 2004	B2
6788442	Potin et al.	Sep 2004	B1
6795778	Dodge et al.	Sep 2004	B2
6798974	Nakano et al.	Sep 2004	B1
6857553	Hartman et al.	Feb 2005	B1
6858817	Blankenship et al.	Feb 2005	B2
6865926	O'Brien et al.	Mar 2005	B2
D504449	Butchko	Apr 2005	S
6920371	Hillen et al.	Jul 2005	B2
6940039	Blankenship et al.	Sep 2005	B2
6982700	Rosenberg et al.	Jan 2006	B2
7021937	Simpson et al.	Apr 2006	B2
7024342	Waite	Apr 2006	B1
7110859	Shibata et al.	Sep 2006	B2
7126078	Demers et al.	Oct 2006	B2
7132617	Lee et al.	Nov 2006	B2
7170032	Flood	Jan 2007	B2
7194447	Harvey	Mar 2007	B2
7225414	Sharma et al.	May 2007	B1
7233837	Swain et al.	Jun 2007	B2
7247814	Ott	Jul 2007	B2
D555446	Picaza Ibarrondo	Nov 2007	S
7298535	Kuutti	Nov 2007	B2
7315241	Daily et al.	Jan 2008	B1
D561973	Kinsley et al.	Feb 2008	S
7353715	Myers	Apr 2008	B2
7363137	Brant et al.	Apr 2008	B2
7375304	Kainec et al.	May 2008	B2
7381923	Gordon et al.	Jun 2008	B2
7414595	Muffler	Aug 2008	B1
7465230	LeMay et al.	Dec 2008	B2
7474760	Hertzman et al.	Jan 2009	B2
7478108	Townsend et al.	Jan 2009	B2
D587975	Aronson et al.	Mar 2009	S
7487018	Lee et al.	Apr 2009	B2
7516022	Lee et al.	Apr 2009	B2
7580821	Schirm	Aug 2009	B2
D602057	Osicki	Oct 2009	S
7621171	O'Brien	Nov 2009	B2
D606102	Bender et al.	Dec 2009	S
7643890	Hillen et al.	Jan 2010	B1
7687741	Kainec et al.	Mar 2010	B2
D614217	Peters et al.	Apr 2010	S
D615573	Peters et al.	May 2010	S
7817162	Bolick et al.	Oct 2010	B2
7853645	Brown et al.	Dec 2010	B2
D631074	Peters et al.	Jan 2011	S
7874921	Baszucki et al.	Jan 2011	B2
7970172	Hendrickson	Jun 2011	B1
7972129	O'Dononghue	Jul 2011	B2
7991587	Ihn	Aug 2011	B2
8069017	Hallquist	Nov 2011	B2
8224881	Spear et al.	Jul 2012	B1
8248324	Nangle	Aug 2012	B2
8265886	Bisiaux et al.	Sep 2012	B2
8274013	Wallace	Sep 2012	B2
8287522	Moses et al.	Oct 2012	B2
8301286	Babu	Oct 2012	B2
8316462	Becker et al.	Nov 2012	B2
8363048	Gering	Jan 2013	B2
8365603	Lesage et al.	Feb 2013	B2
8512043	Choquet	Aug 2013	B2
8569646	Daniel et al.	Oct 2013	B2
8592723	Davidson et al.	Nov 2013	B2
8657605	Wallace et al.	Feb 2014	B2
8692157	Daniel et al.	Apr 2014	B2
8747116	Zboray et al.	Jun 2014	B2
8777629	Kreindl et al.	Jul 2014	B2
8787051	Chang et al.	Jul 2014	B2
8834168	Peters et al.	Sep 2014	B2
8851896	Wallace et al.	Oct 2014	B2
8911237	Postlewaite et al.	Dec 2014	B2
8915740	Zboray et al.	Dec 2014	B2
RE45398	Wallace	Mar 2015	E
8992226	Leach et al.	Mar 2015	B1
9011154	Dig et al.	Apr 2015	B2
9293056	Zboray et al.	Mar 2016	B2
9293057	Zboray et al.	Mar 2016	B2
9740412	Jung et al.	Aug 2017	B2
9779635	Zboray et al.	Oct 2017	B2
9836987	Postlethwaite et al.	Dec 2017	B2
20010045808	Heitmann et al.	Nov 2001	A1
20010052893	Jolly et al.	Dec 2001	A1
20020032553	Simpson et al.	Mar 2002	A1
20020039138	Edelson et al.	Apr 2002	A1
20020046999	Veikkolainen et al.	Apr 2002	A1
20020005421	Edelson et al.	May 2002	A1
20020050984	Roberts	May 2002	A1
20020085843	Mann	Jul 2002	A1
20020094026	Edelson et al.	Jul 2002	A1
20020098468	Barrett et al.	Jul 2002	A1
20020111557	Madill et al.	Aug 2002	A1
20020132213	Grant et al.	Sep 2002	A1
20020135695	Edelson et al.	Sep 2002	A1
20020175897	Pelosi	Nov 2002	A1
20020178038	Grybas	Nov 2002	A1
20020180761	Edelson	Dec 2002	A1
20030000931	Ueda	Jan 2003	A1
20030002740	Melikian	Jan 2003	A1
20030023592	Modica et al.	Jan 2003	A1
20030025884	Hamana et al.	Feb 2003	A1
20030062354	Ward	Apr 2003	A1
20030075534	Okamoto	Apr 2003	A1
20030106787	Santilli	Jun 2003	A1
20030111451	Blankenship et al.	Jun 2003	A1
20030172032	Choquet	Sep 2003	A1
20030186199	McCool et al.	Oct 2003	A1
20030228560	Seat et al.	Dec 2003	A1
20030234885	Pilu	Dec 2003	A1
20040009462	McElwrath	Jan 2004	A1
20040020907	Zauner et al.	Feb 2004	A1
20040035990	Ackeret	Feb 2004	A1
20040050824	Samler	Mar 2004	A1
20040082373	Cole et al.	Apr 2004	A1
20040088071	Kouno	May 2004	A1
20040140301	Blankenship et al.	Jul 2004	A1
20040167788	Birimisa et al.	Aug 2004	A1
20040181382	Hu	Sep 2004	A1
20050007504	Fergason	Jan 2005	A1
20050017152	Fergason	Jan 2005	A1
20050029326	Henrikson	Feb 2005	A1
20050046584	Breed	Mar 2005	A1
20050050168	Wen et al.	Mar 2005	A1
20050101767	Clapham et al.	May 2005	A1
20050103766	Iizuka et al.	May 2005	A1
20050103767	Kainec et al.	May 2005	A1
20050103768	Ward	May 2005	A1
20050109735	Flood	May 2005	A1
20050128186	Shahoian et al.	Jun 2005	A1
20050133488	Blankenship	Jun 2005	A1
20050159840	Lin et al.	Jul 2005	A1
20050163364	Beck	Jul 2005	A1
20050189336	Ku	Sep 2005	A1
20050199602	Kaddani et al.	Sep 2005	A1
20050230573	Ligertwood	Oct 2005	A1
20050233295	Chiszar et al.	Oct 2005	A1
20050252897	Hsu et al.	Nov 2005	A1
20050255914	McHale et al.	Nov 2005	A1
20050275913	Vesely et al.	Dec 2005	A1
20050275914	Vesely et al.	Dec 2005	A1
20060014130	Weinstein	Jan 2006	A1
20060076321	Maev	Apr 2006	A1
20060136183	Choquet	Jun 2006	A1
20060140502	Tseng et al.	Jun 2006	A1
20060154226	Maxfield	Jul 2006	A1
20060163227	Hillen et al.	Jul 2006	A1
20060163228	Daniel	Jul 2006	A1
20060166174	Rowe	Jul 2006	A1
20060169682	Kainec et al.	Aug 2006	A1
20060173619	Brant et al.	Aug 2006	A1
20060183083	Moran et al.	Aug 2006	A1
20060189260	Sung	Aug 2006	A1
20060207980	Jacovetty et al.	Sep 2006	A1
20060213892	Ott	Sep 2006	A1
20060214924	Kawamoto et al.	Sep 2006	A1
20060226137	Huismann et al.	Oct 2006	A1
20060241432	Herline et al.	Oct 2006	A1
20060252543	Van Noland et al.	Nov 2006	A1
20060258447	Baszucki et al.	Nov 2006	A1
20070034611	Drius et al.	Feb 2007	A1
20070038400	Lee et al.	Feb 2007	A1
20070045488	Shin	Mar 2007	A1
20070060359	Smith	Mar 2007	A1
20070088536	Ishikawa	Apr 2007	A1
20070112889	Cook et al.	May 2007	A1
20070164007	Peters et al.	Jul 2007	A1
20070188606	Atkinson et al.	Aug 2007	A1
20070198117	Wajihuddin	Aug 2007	A1
20070211026	Ohta et al.	Sep 2007	A1
20070221797	Thompson et al.	Sep 2007	A1
20070256503	Wong et al.	Nov 2007	A1
20070264620	Maddix et al.	Nov 2007	A1
20070277611	Portzgen et al.	Dec 2007	A1
20070291035	Vesely et al.	Dec 2007	A1
20080021311	Goldbach	Jan 2008	A1
20080027594	Jump et al.	Jan 2008	A1
20080031774	Magnant et al.	Feb 2008	A1
20080037218	Sharma et al.	Feb 2008	A1
20080038702	Choquet	Feb 2008	A1
20080061049	Mbrecht	Mar 2008	A1
20080078811	Hillen et al.	Apr 2008	A1
20080078812	Peters et al.	Apr 2008	A1
20080107345	Melikian	May 2008	A1
20080117203	Gering	May 2008	A1
20080120075	Wloka	May 2008	A1
20080128398	Schneider	Jun 2008	A1
20080135533	Ertmer et al.	Jun 2008	A1
20080140815	Brant et al.	Jun 2008	A1
20080149686	Daniel et al.	Jun 2008	A1
20080203075	Feldhausen et al.	Aug 2008	A1
20080233550	Solomon	Sep 2008	A1
20080249998	Dettinger et al.	Oct 2008	A1
20080303197	Paquette et al.	Dec 2008	A1
20080314887	Stoger et al.	Dec 2008	A1
20090015585	Klusza	Jan 2009	A1
20090021514	Klusza	Jan 2009	A1
20090045183	Artelsmair et al.	Feb 2009	A1
20090050612	Serruys et al.	Feb 2009	A1
20090057286	Ihara et al.	Mar 2009	A1
20090109128	Nangle	Apr 2009	A1
20090152251	Dantinne et al.	Jun 2009	A1
20090173726	Davidson et al.	Jul 2009	A1
20090184098	Daniel et al.	Jul 2009	A1
20090197228	Afshar et al.	Aug 2009	A1
20090200281	Hampton	Aug 2009	A1
20090200282	Hampton	Aug 2009	A1
20090231423	Becker et al.	Sep 2009	A1
20090257655	Melikian	Oct 2009	A1
20090259444	Dolansky	Oct 2009	A1
20090298024	Batzler et al.	Dec 2009	A1
20090312958	Dai et al.	Dec 2009	A1
20090325699	Delgiannidis	Dec 2009	A1
20100012017	Miller	Jan 2010	A1
20100012637	Jaeger	Jan 2010	A1
20100021051	Melikian	Jan 2010	A1
20100048273	Wallace et al.	Feb 2010	A1
20100062405	Zboray et al.	Mar 2010	A1
20100062406	Zboray et al.	Mar 2010	A1
20100096373	Hillen et al.	Apr 2010	A1
20100121472	Babu et al.	May 2010	A1
20100133247	Mazumder et al.	Jun 2010	A1
20100133250	Sardy et al.	Jun 2010	A1
20100176107	Bong	Jul 2010	A1
20100201803	Melikian	Aug 2010	A1
20100224610	Wallace	Sep 2010	A1
20100276396	Cooper	Nov 2010	A1
20100279771	Block et al.	Nov 2010	A1
20100299101	Shimada et al.	Nov 2010	A1
20100307249	Lesage et al.	Dec 2010	A1
20100314362	Albrecht	Dec 2010	A1
20100326962	Calla et al.	Dec 2010	A1
20110006047	Penrod	Jan 2011	A1
20110048273	Colon	Mar 2011	A1
20110052046	Melikian	Mar 2011	A1
20110060568	Goldfine	Mar 2011	A1
20110062132	Raje et al.	Mar 2011	A1
20110082728	Melikian	Apr 2011	A1
20110091846	Kreindl et al.	Apr 2011	A1
20110114615	Daniel et al.	May 2011	A1
20110116076	Chantry et al.	May 2011	A1
20110117527	Conrardy	May 2011	A1
20110122495	Togashi	May 2011	A1
20110183304	Wallace et al.	Jul 2011	A1
20110187746	Suto	Aug 2011	A1
20110187859	Edelson	Aug 2011	A1
20110218024	Baerlocher	Sep 2011	A1
20110229864	Short et al.	Sep 2011	A1
20110248864	Becker	Oct 2011	A1
20110316516	Schiefermuller et al.	Dec 2011	A1
20120029674	Hida	Feb 2012	A1
20120122062	Yang et al.	May 2012	A1
20120189993	Kindig et al.	Jul 2012	A1
20120291172	Wills et al.	Nov 2012	A1
20120298640	Conrardy et al.	Nov 2012	A1
20130026150	Chantry et al.	Jan 2013	A1
20130040270	Albrecht	Feb 2013	A1
20130049976	Maggiore	Feb 2013	A1
20130075380	Albrech et al.	Mar 2013	A1
20130119040	Suraba	May 2013	A1
20130170259	Chang et al.	Jul 2013	A1
20130182070	Peters et al.	Jul 2013	A1
20130183645	Wallace et al.	Jul 2013	A1
20130189657	Wallace et al.	Jul 2013	A1
20130189658	Peters et al.	Jul 2013	A1
20130198334	Ikenaga et al.	Aug 2013	A1
20130203029	Choquet	Aug 2013	A1
20130206740	Pfeifer et al.	Aug 2013	A1
20130209976	Postlethwaite et al.	Aug 2013	A1
20130230832	Peters	Sep 2013	A1
20130231980	Choquet	Sep 2013	A1
20130252214	Eigart et al.	Sep 2013	A1
20130288211	Patterson et al.	Oct 2013	A1
20130295535	Levy et al.	Nov 2013	A1
20130327747	Dantinne	Dec 2013	A1
20130342678	McAninch et al.	Dec 2013	A1
20140017642	Postlethwaite et al.	Jan 2014	A1
20140038143	Daniel	Feb 2014	A1
20140042136	Daniel	Feb 2014	A1
20140065584	Wallace	Mar 2014	A1
20140134580	Becker	May 2014	A1
20140263224	Becker	Sep 2014	A1
20140272835	Becker	Sep 2014	A1
20140272836	Becker	Sep 2014	A1
20140272837	Becker	Sep 2014	A1
20140272838	Becker	Sep 2014	A1
20140312020	Daniel	Oct 2014	A1
20140346158	Matthews	Nov 2014	A1
20150056584	Boulware et al.	Feb 2015	A1
20150056585	Boulware et al.	Feb 2015	A1
20150056586	Penrod	Feb 2015	A1
20150072323	Postlethwaite et al.	Mar 2015	A1
20150125836	Daniel	May 2015	A1
20150194072	Becker et al.	Jul 2015	A1
20150194073	Becker et al.	Jul 2015	A1
20150235565	Postlethwaite	Aug 2015	A1
20150248846	Postlethwaite et al.	Sep 2015	A1
20150262511	Lin et al.	Sep 2015	A1
20160049085	Beeson	Feb 2016	A1
20160093233	Boulware et al.	Mar 2016	A1
20160125594	Becker et al.	May 2016	A1
20160125763	Becker	May 2016	A1
20160203734	Boulware et al.	Jul 2016	A1
20160203735	Boulware et al.	Jul 2016	A1
20160260261	Hsu	Sep 2016	A1
20160331592	Stewart	Nov 2016	A1
20160343268	Postlethwaite et al.	Nov 2016	A1
20170046977	Becker et al.	Feb 2017	A1
20170053557	Daniel	Feb 2017	A1
20170200384	Albrecht	Jul 2017	A1

Foreign Referenced Citations (129)

Number	Date	Country
2698078	Sep 2011	CA
1665633	Sep 2005	CN
201083660	Jul 2008	CN
201149744	Nov 2008	CN
101406978	Apr 2009	CN
101419755	Apr 2009	CN
201229711	Apr 2009	CN
101571887	Nov 2009	CN
101587659	Nov 2009	CN
101661589	Mar 2010	CN
102053563	May 2011	CN
102202836	Sep 2011	CN
202053009	Nov 2011	CN
202684308	Jan 2013	CN
203503228	Mar 2014	CN
103871279	Jun 2014	CN
106774949	May 2017	CN
28 33 638	Feb 1980	DE
30 46 634	Jan 1984	DE
32 44 307	May 1984	DE
35 22 581	Jan 1987	DE
4037879	Jun 1991	DE
196 15 069	Oct 1997	DE
197 39 720	Oct 1998	DE
19834205	Feb 2000	DE
200 09 543	Aug 2001	DE
10 2005 047 204	Apr 2007	DE
102006048165	Jan 2008	DE
10 2010 038 902	Feb 2012	DE
202012013151	Feb 2015	DE
0008527	Jan 1982	EP
0 108 599	May 1984	EP
0 127 299	Dec 1984	EP
0 145 891	Jun 1985	EP
319623	Oct 1990	EP
0852986	Jul 1998	EP
1 527 852	May 2005	EP
1905533	Apr 2008	EP
2801966	Nov 2014	EP
2 274 736	May 2007	ES
1456780	Mar 1965	FR
2 827 066	Jan 2003	FR
2 926 660	Jul 2009	FR
1 455 972	Nov 1976	GB
1 511 608	May 1978	GB
2 254 172	Sep 1992	GB
2435838	Sep 2007	GB
2 454 232	May 2009	GB
2-224877	Sep 1990	JP
05-329645	Dec 1993	JP
07-047471	Feb 1995	JP
H07214317	Aug 1995	JP
07-232270	Sep 1995	JP
08-505091	Apr 1996	JP
08-150476	Jun 1996	JP
H08221107	Aug 1996	JP
08-132274	May 1998	JP
H1133963	Feb 1999	JP
2000-167666	Jun 2000	JP
2000-237872	Sep 2000	JP
2001-071140	Mar 2001	JP
2002278670	Sep 2002	JP
2003-200372	Jul 2003	JP
2003-326362	Nov 2003	JP
2004025270	Jan 2004	JP
2006-006604	Jan 2006	JP
2006175205	Jul 2006	JP
2006-281270	Oct 2006	JP
2007-290025	Nov 2007	JP
2009-500178	Jan 2009	JP
2009160636	Jul 2009	JP
2010-225129	Oct 2010	JP
2010231792	Oct 2010	JP
2012024867	Feb 2012	JP
2012218058	Nov 2012	JP
100876425	Dec 2008	KR
20090010693	Jan 2009	KR
1020090111556	Oct 2009	KR
20110068544	Jun 2011	KR
527045	Jul 1995	RU
2317183	Feb 2008	RU
2008 108 601	Nov 2009	RU
1038963	Aug 1983	SU
9845078	Oct 1998	WO
0112376	Feb 2001	WO
0143910	Jun 2001	WO
0158400	Aug 2001	WO
2004029549	Apr 2004	WO
2005102230	Nov 2005	WO
2005110658	Nov 2005	WO
2006034571	Apr 2006	WO
2007009131	Jan 2007	WO
2007039278	Apr 2007	WO
2009120921	Jan 2009	WO
2009060231	May 2009	WO
2010020867	Aug 2009	WO
2009149740	Dec 2009	WO
2010000003	Jan 2010	WO
2010020870	Feb 2010	WO
2010044982	Apr 2010	WO
2010091493	Aug 2010	WO
2011017608	Feb 2011	WO
2011041037	Apr 2011	WO
2011045654	Apr 2011	WO
2011058433	May 2011	WO
2011059502	May 2011	WO
2011060350	May 2011	WO
2011067447	Jun 2011	WO
2011088412	Jul 2011	WO
2011097035	Aug 2011	WO
2011150165	Dec 2011	WO
2012016851	Feb 2012	WO
2012082105	Jun 2012	WO
2012137060	Oct 2012	WO
2012143327	Oct 2012	WO
2013014202	Jan 2013	WO
2013-025672	Feb 2013	WO
2013061518	May 2013	WO
2013098567	Jul 2013	WO
2013114189	Aug 2013	WO
2013119749	Aug 2013	WO
2013175079	Nov 2013	WO
2013186413	Dec 2013	WO
2014007830	Jan 2014	WO
2014019045	Feb 2014	WO
2014020386	Feb 2014	WO
2014140720	Sep 2014	WO
2014184710	Nov 2014	WO
2016-137578	Sep 2016	WO

Non-Patent Literature Citations (222)

Entry
Andreas Grahn, “Interactive Simulation of Contrast Fluid using Smoothed Particle Hydrodynamics,” Jan. 1, 2008, Masters Thesis in Computing Science, Umea University, Department of Computing Science, Umea Sweden; 69 pages.
Marcus Vestedund, Simulation and Rendering of a Viscous Fluid using Smoothed Particle Hydrodynamics, Dec. 3, 2004, Master's Thesis in Computing Science, Umea University, Department of Computing Science, Umea Sweden; 46 pages.
M. Muller et al., Point Based Animation of Elastic, Plastic and Melting Objects, Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2004); 11 pages.
Andrew Nealen, “Point-Based Animation of Elastic, Plastic, and Melting Objects,” CG topics, Feb. 2005; 2 pages.
D. Tonnesen, Modeling Liquids and Solids using Thermal Particles, Proceedings of Graphics lnterface'91, pp. 255-262, Calgary, Alberta, 1991.
CUDA Programming Guide Version 1.1, Nov. 29, 2007, 143 pages.
Websters II new college dictionary, 3rd ed., Houghton Mifflin Co., copyright 2005, Boston, MA, p. 1271, definition of Wake, 3 pages.
Da Daito L. et al. “CS Wave: Learning welding motion in a virtual environment” Published in Proceedings of the IIW International Conference, Jul. 10-11, 2008; 19 pages.
CS Wave-Manual, “Virtual Welding Workbench User Manual 3.0” 2007; 25 pages.
Choquet, Claude. “ARC+®: Today's Virtual Reality Solution for Welders”, Published in Proceedings of the IIW International Conference; Jul. 10-11, 2008; 19 pages.
Welding Handbook, Welding Science & Technology, American Welding Society, Ninth Ed., Copyright 2001. Appendix A “Terms and Definitions” 54 pages.
Virtual Welding: A Low Cost Virtual Reality Welder Training System, NSRP RA 07-01—BRP Oral Review Meeting in Charleston, SC at ATI, Mar. 2008; 6 pages.
Dorin Aiteanu, “Virtual and Augmented Reality Supervisor for A New Welding Helmet Dissertation,” Nov. 15, 2005; 154 pages.
Screen Shotof CS Wave Exercise 135.FWPG Root Pass Level 1 https://web.archive.org/web/20081128081858/http:/wave.c-s.fr/images/english/snap_evolution2.Jpg; 1 page.
Screen Shot of CS Wave Control Centre V3.0.0 https://web.archive.org/web/20081128081915/http:/wave.c-s.fr/images/english/snap_evolution4.jpg; 1 page.
Screen Shot of CS Wave Control Centre V3.0.0 https://web.archive.org/web/20081128081817/http:/wave.c-s.fr/mages/english/snap_evolution6.jpg; 1 page.
Da Daito L et al. “CS Wave A Virtual learning tool for the welding motion,” Mar. 14, 2008; 10 pages.
Nordruch, Stefan et al. “Visual Online Monitoring of PGMAW Without a Lighting Unit”, Jan. 2005; 14 pages.
The Evolution of Computer Graphics; Tony Tamasi, NVIDIA, 2008; 36 pages.
VRSim Powering Virtual Reality, www.lincolnelectric.com/en-us/eguipment/lraining-eguipment/Pages/powered-by-'rsim.aspx, 2016, 1 page.
Hillers, B.; Graser, A. “Direct welding arc observation without harsh flicker,” 8 pages, allegedly FABTECH International and AWS welding show, 2007.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00905; 72 pages.
Declaration of Edward Bohnart, Apr. 27, 2016, exhibit to IPR 2016-00905; 23 pages.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00904; 76 pages.
Declaration of Edward Bohnart, Apr. 27, 2016, exhibit to IPR 2016-00904; 22 pages.
Declaration of Axel Graeser, Apr. 17, 2016, exhibit to IPR 2016-00840; 88 pages.
Adams et., “Adaptively Sampled Particle Fluids,” ACM Transactions on Graphics, vol. 26, No. 3, Article 48, Jul. 2007, pp. 48.1-48.7.
ARC+—Archived Press Release from WayBack Machine from Jan. 31, 2008-Apr. 22, 2013, Page, https://web.3rchive.org/web/20121006041803/http://www.123certification.com/en/article_press/index.htm, Jan. 21, 2016, 3 pages.
P. Tschirner et al., Virtual and Augmented Reality for Quality Improvement of Manual Welds National Institute of Standards and Technology, Jan. 2002, Publication 973, 24 pages.
Y. Wang et al., “Impingement of Filler Droplets and Weld Pool During Gas Metal Arc Welding Process” International Journal of Heat and Mass Transfer, Sep. 1999, 14 pages.
Larry Jeffus, “Welding Principles and Applications,” Sixth Edition, 2008, 10 pages.
R.J. Renwick et al., “Experimental Investigation of GTA Weld Pool Oscillations,” Welding Research—Supplement to the Welding Journal, Feb. 1983, 7 pages.
Matt Phar, “GPU Gems 2 Programming Techniques for High-Performance Graphics and General-Purpose Computation,” 2005, 12 pages.
Yaoming, “Applications of Microcomputer in Robot Technology,” Scientific and Technical Documentation Press, Sep. 1987, pp. 360-365.
Thurey et al., “Real-time Breaking Waves for Shallow Water Simulations,” Proceedings of the Pacific Conference on Computer Graphics and Applications, Maui, Hawaii, Oct. 29-Nov. 2, 2007, 8 pages.
Stam, “Stable Fluids,” SIGGRAPH 99 Conference Proceedings, Annual Conference Series, Aug. 1999, 121-128.
Rasmussen et al., “Directable Photorealistic Liquids,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2004), pp. 193-202.
Premoze et al., “Particle-Based Simulation of Fluids,” Eurographics, vol. 22, No. 3 (2003), 10 pages.
O'Brien et al., “Dynamic Simulation of Splashing Fluids,” Proceedings of Computer Animation '95, Apr. 19-21, 1995, in Geneva, Switzerland, pp. 198-205.
Muller et al., “Particle-Based Fluid Simulation for Interactive Applications,” Eurographics/SIGGRAPH Symposium on Computer Animation (2003), pp. 154-159 and 372.
Klinger et al., “Fluid Animation with Dynamic Meshes,” Computer Graphics Proceedings, Annual Conference Series, Jul. 30-Aug. 3, 2006, 820-825.
Kass et al., “Rapid, Stable Fluid Dynamics for Computer Graphics,” Computer Graphics, vol. 24, No. 4, Aug. 1990, pp. 49-57.
Irving et al., “Efficient Simulation of Large Bodies of Water by Coupling Two and ThreeDimensional Techniques,” ACM Transactions on Graphics (TOG), vol. 25, Issue 3, Jul. 2006,pp. 805-811.
Holmberg et al., “Efficient Modeling and Rendering of Turbulent Water over Natural Terrain,” Proceedings of the 2nd International conference on Computer graphics and interactive techniques in Australasia and South East Asia, Singapore, Jun. 15-18, 2004, pp. 15-22.
Goktekin et al., “A Method for Animating Viscoelastic Fluids,” Computer Graphics Proceedings, Annual Conference Series, Aug. 8-12, 2004, pp. 1-6.
Foster et al., “Realistic Animation of Liquids,” Graphical Models and Image Processing, vol. 58, No. 5, Sep. 1996, pp. 471-483.
Foster et al., “Practical Animation of Liquids,” ACM SIGGRAPH, Aug. 12-17, 2001, Los Angeles, CA, pp. 23-30.
Feldman et al., “Fluids in Deforming Meshes,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2005), pp. 255-259.
Feldman et al., “Animating Suspended Particle Explosions,” Computer Graphics Proceedings, Annual Conference Series, Jul. 27-31, 2003, pp. 1-8.
Clausen et al., “Simulating Liquids and Solid-Liquid Interactions with Lagrangian Meshes,” ACM Transactions on Graphics, vol. 32, No. 2, Article 17, Apr. 2013, pp. 17.1-17.15.
SIMFOR / CESOL, “RV-SOLD” Welding Simulator, Technical and Functional Features, 20 pages, date unknown.
Weldplus, Welding Simulator, 2 pages, printed Jan. 14, 2015.
Robert Schoder, “Design and Implementation of a Video Sensor for Closed Loop Control of Back Bead Weld Puddle Width,” Massachusetts, Institute of Technology, Dept. of Mechanical Engineering, May 27, 1983, 64 pages.
Hills and Steele, Jr.; “Data Parallel Algorithms”, Communications of the ACM, Dec. 1986, vol. 29, No. 12, p. 1170.
Nancy C. Porter, J. Allan Cote, Timothy D. Gifford, and Wim Lam, Virtual Reality Welder Training, 29 pages, dated Jul. 14, 2006.
J.Y. (Yosh) Mantinband, Hillel Goldenberg, Llan Kleinberger, Paul Kleinberger, Autosteroscopic, field-sequential display with full freedom of movement OR Let the display were the shutter-glasses, 3ality (Israel) Ltd., 8 pages, 2002.
Fronius, ARS Electronica Linz GMBH, High-speed video technology is applied to research on welding equipment. and the results are visualized in the CAVE, 2 pages, May 18, 1997.
D.K. Aidun and S.A. Martin, “Penetration in Spot GTA Welds during Centrifugation,” Journal of Material Engineering and Performance Volumn 7(5), 4 pages, Oct. 1998—597.
Arc+ simulator; httl://www.123arc.com/en/depliant_ang.pdf; 2 pages, 2000.
Glen Wade, “Human uses of ultrasound: ancient and modern”, Ulrasonics vol. 38, 5 pages, dated 2000.
ASME Definitions, Consumables, Welding Positions, 4 pages, dated Mar. 19, 2001. See http://www.gowelding.com/asme4.htm.
M. Abbas, F. Waeckel, Code Aster (Software) EDF (France), 14 pages, Oct. 2001.
Achim Mahrle, Jurgen Schmidt, “The influence of fluid flow phenomena on the laser beam welding process” International Journal of Heat and Fluid Flow 23, 10 pages, dated 2002.
The Lincoln Electric Company; Checkpoint Production Monitoring brochure; four (4) pages; http://www.lincolnelectric.com/assets/en_US/products/literature/s232.pdf; Publication S2.32; 4 pages, Issue Date Feb. 2012.
WeldWatch Software/Visible Welding; website printout; http://visiblewelding.com/weldwatch-software/; 4 pages; 2015.
Desroches, X.; Code-Aster, Note of use for aclculations of welding; Instruction manual U2.03 booklet: Thermomechincal; Document: U2.03.05; 13 pages, Oct. 1, 2003.
Fast, K. et al., “Virtual Training for Welding”, Mixed and Augmented Reality, 2004, ISMAR 2004, Third IEEE and SM International Symposium on Arlington, VA, 2 pages, Nov. 2-5, 2004.
Cooperative Research Program, Virtual Reality Welder Training, Summary Report SR 0512, 4 pages, Jul. 2005.
Porter, et al., Virtual Reality Training, Paper No. 2005-P19, 14 pages, 2005.
Eduwelding+, Weld Into the Future; Online Welding Seminar—A virtual training environment; 123arc.com; 4 pages, 2005.
Miller Electric MFG Co.; MIG Welding System features weld monitoring software; NewsRoom 2010 (Dialog® File 992); © 2011 Dialog. 2010; http://www.dialogweb.com/cgi/dwclient?reg=133233430487; three (3) pages; printed Mar. 8, 2012.
M. Abida and M. Siddique, Numerical simulation to study the effect of tack welds and root gap on welding deformations and residual stresses of a pipe-flange joint, Faculty of Mechanical Engineering, GIK Institute of Engineering Sciences and Technology, Topi, NWFP, Pakistan, 12 pages, Available on-line Aug. 25, 2005.
Abbas, M. et al. .; Code_Aster; Introduction to Code_Aster; User Manual; Booklet U1.0-: Introduction to Code_Aster; Document: U1.02.00; Version 7.4; 14 pages, Jul. 22, 2005.
Mavrikios D et al, A prototype virtual reality-based demonstrator for immersive and interactive simulation of welding processes, International Journal of Computer Integrated manufacturing, Taylor and Francis, Basingstoke, GB, vol. 19, No. 3, 8 pages, Apr. 1, 2006, pp. 294-300.
Nancy C. Porter, Edison Welding Institute; J. Allan Cote, General Dynamics Electric Boat; Timothy D. Gifford, VRSim; and Wim Lam, FCS Controls; Virtual Reality Welder Trainer, Session 5: Joining Technologies for Naval Applications, 16 pages, earliest date Jul. 14, 2006.
T Borzecki, G. Bruce, Y.S. Han, M. Heinemann, A. Imakita, L. Josefson, W. Nie, D. Olson, F. Roland, and Y. Takeda, 16th International Shop and Offshore Structures Congress: Aug. 20-25, 2006: Southhampton, UK, 49 pages, vol. 2 Specialist Committee V.3 Fabrication Technology Committee Mandate.
Ratnam and Khalid: “Automatic classification of weld defects using simulated data and an MLP neutral network.” Insight vol. 49, No. 3; 6 pages, Mar. 2007.
Wang et al., Study on welder training by means of haptic guidance and virtual reality for arc welding, 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006 ISBN-10: 1424405718, 5 pages, p. 954-958.
CS Wave, The Virtual Welding Trainer, 6 pages, 2007.
asciencetutor.com, A division of Advanced Science and Automation Corp., VWL (Virtual Welding Lab), 2 pages, 2007.
Eric Linholm, John Nickolls, Stuart Oberman, and John Montrym, “NVIDIA Testla: A Unifired Graphics and Computing Architecture”, IEEE Computer Society, 17 pages, 2008.
NSRP ASE, Low-Cost Virtual Realtiy Welder Training System, 1 Page, 2008.
Edison Welding Institute, E-Weld Predictor, 3 pages, 2008.
CS Wave, A Virtual learning tool for welding motion, 10 pages, Mar. 14, 2008.
The Fabricator, Virtually Welding, Training in a virtual environment gives welding students a leg up, 4 pages, Mar. 2008.
N. A. Tech., P/NA.3 Process Modeling and Optimization, 11 pages, Jun. 4, 2008.
FH Joanneum, Fronius—virtual welding, 2 pages, May 12, 2008.
Eduwelding+, Training Activities with arc+ simulator; Weld Into The Future, Online Welding Simulator—A virtual training environment; 123arc.com; 6 pages, May 2008.
ChemWeb.com, Journal of Materials Engineering and Performance (v.7, #5), 3 pgs., printed Sep. 26, 2012.
Choquet, Claude; “ARC+: Today's Virtual Reality Solution for Welders” Internet Pages, 6 pages, Jan. 1, 2008.
Juan Vicenete Rosell Gonzales, “RV-Sold: simulator virtual para la formacion de soldadores”; Deformacion Metalica, Es. vol. 34, No. 301, 14 pages, Jan. 1, 2008.
White et al., Virtual welder training, 2009 IEEE Virtual Reality Conference, 1 page, p. 303, 2009.
Training in a virtual environment gives welding students a leg up, retrieved on Apr. 12, 2010 from: http://www.thefabricator.com/article/arcwelding/virtually-welding, 4 pages.
Sim Welder, Train better welders faster, retrieved on Apr. 12, 2010 from: http://www.simwelder.com.
P. Beatriz Garcia-Allende, Jesus Mirapeix, Olga M. Conde, Adolfo Cobo and Jose M. Lopez-Higuera; Defect Detection in Arc-Welding Processes by Means of the Line-to-Continuum Method and Feature Selection; www.mdpi.com/journal/sensors; 2009; 18 pages; Sensors 2009, 9, 7753-7770; doi; 10.3390/s91007753.
Production Monitoring 2 brochure, four (4) pages, The Lincoln Electric Company, May 2009.
Aiteanu, Dorin, Hillers, Bernd and Graser, Axel “A Step Forward in Manual Welding: Demonstration of Augmented Reality Helmet” Institute of Automation, University of Bremen, Germany, Proceedings of the Second IEEE and ACMInternational Symposium on Mixed and Augmented Reality; 2003; 2 pages.
Bjorn G. Agren; Sensor Integration for Robotic Arc Welding; 1995; vol. 5604C of Dissertalions Abstracts International p. 1123; Dissertation Abs Online (Dialog® File 35): © 2012 ProQuest Info& Learning: http://dialogweb.com/cgi/dwclient?reg=1331233317524; one (1) page; printed Mar. 8, 2012.
J. Hu and Hi Tsai, Heat and mass transfer in gas metal arc welding. Part 1: the arc, found in ScienceDirect, International Journal of Heat and Mass Transfer 50 (2007), 14 pages, 833-846, available online on Oct. 24, 2006 http://www.web.mst.edu/˜tsai/publications/HU-IJHMT-2007-1-60.pdf.
M. Ian Graham, Texture Mapping, Carnegie Mellon University Class 15-462 Computer Graphics, Lecture 10, 53 pages, dated Feb. 13, 2003.
Communication pursuant to Article 94(3) EPC from EP Application No. 19170017.8 dated Apr. 1, 2021.
Communication pursuant to Article 94(3) EPC from EP Application No. 19170161.4 dated Apr. 1, 2021.
Communication pursuant to Article 94(3) EPC from EP Application No. 19170585.4 dated Apr. 14, 2021.
Office Action from U.S. Appl. No. 16/366,324 dated Mar. 26, 2021.
Office Action from U.S. Appl. No. 16/366,300 dated Mar. 26, 2021.
Office Action from U.S. Appl. No. 16/366,378 dated Mar. 30, 2021.
Fujita et al., “Simulation Teaching Materials for the Mastery of Advanced Skills in Welding Torch Operation,” IEICE Technical Report vol. 104, No. 48, Institute of Electronics, Information and Communication Engineers (IEICE), May 7, 2004.
Collins (Lecture 4:Smoothing) (downloaded from: https://web.archive.org/web/20150616212349/http://www.cse.psu.edu/-rtc12/CSE486/lecture04.pdf) (Year: 2015).
IT Media, “Tokyo Game Show 2008: Games aren't just about entertainment,” published Oct. 9, 2008.
Extended European Search Report from Corresponding Application No. EP19170154.9; dated Jul. 8, 2019; pp. 1-7.
Extended European Search Report from Corresponding Application No. EP19170017.8; dated Jul. 8, 2019; pp. 1-7.
Extended European Search Report from Corresponding Application No. EP19170161.4; dated Jul. 9, 2019; pp. 1-8.
Chuansong Wu: “Microcomputer-based welder training simulator”, Computers in Industry, vol. 20, No. 3, Oct. 1992, 5 pages, pp. 321-325, XP000205597, Elsevier Science Publishers, Amsterdam, NL.
ViziTech USA, retrieved on Mar. 27, 2014 from http://vizitechusa.com/, 2 pages.
Guu and Rokhlin ,Technique for Simultaneous Real-Time Measurements of Weld Pool Surface Geometry and Arc Force, 10 pages, Dec. 1992.
William T. Reeves, “Particles Systems—A Technique for Modeling a Class of Fuzzy Objects”, Computer Graphics 17:3 pp. 359-376, 1983, 17 pages.
S.B. Chen, L. Wu, Q. L. Wang and Y. C. Liu, Self-Learning Fuzzy Neural Networks and Computer Vision for Control of Pulsed GTAW, 9 pages, dated May 1997.
Patrick Rodjito, Position tracking and motion prediction using Fuzzy Logic, 81 pages, 2006, Colby College.
D'Huart, Deat, and Lium; Virtual Environment for Training, 6th International Conference, ITS 20002, 6 pages, Jun. 2002.
Konstantinos Nasios (Bsc), Improving Chemical Plant Safety Training Using Virtual Reality, Thesis submitted to the University of Nottingham for the Degree of Doctor of Philosophy, 313 pages, Dec. 2001.
ANSI/A WS D 10.11 MID 10. 11 :2007 Guide for Root Pass Welding of Pipe without Backing Edition: 3rd American Welding Society / Oct. 13, 2006/36 pages ISBN: 0871716445, 6 pages.
M. Jonsson, L. Karlsson, and L-E Lindgren, Simulation of Tack Welding Procedures in Butt Joint Welding of Plates Welding Research Supplement, Oct. 1985, 7 pages.
Isaac Brana Veiga, Simulation of a Work Cell in the IGRIP Program , dated 2006, 50 pages.
Balijepalli, A. and Kesavadas, Haptic Interfaces for Virtual Environment and Teleoperator Systems, Haptics 2003, Department of Mechanical & Aerospace Engineering, State University of New York at Buffalo, NY.
Johannes Hirche, Alexander Ehlert, Stefan Guthe, Michael Doggett, Hardware Accelerated Per-Pixel Displacement Mapping, 8 pages.
Yao et al., ‘Development of a Robot System for Pipe Welding’. 2010 International Conference on Measuring echnology and Mechatronics Automation. Retrieved from the Internet: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5460347&tag=1; pp. 1109-1112, 4 pages.
Steve Mann, Raymond Chun Bing Lo, Kalin Ovtcharov, Shixiang Gu, David Dai, Calvin Ngan, Tao Ai, Realtime HDR (High Dynamic Range) Video for Eyetap Wearable Computers, FPGA-Based Seeing Aids, and Glasseyes (Eyetaps), 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1-6, 6 pages, Apr. 29, 2012.
Kyt Dotson, Augmented Reality Welding Helmet Prototypes How Awsome the Technology Can Get, Sep. 26, 2012, Retrieved from the Internet: URL:http://siliconangle.com/blog/2012/09/26/augmented-reality-welding-helmet-prototypes-how-awesome-the-technology-can-get/,1 page, retrieved on Sep. 26, 2014.
Terrence O'Brien, “Google's Project Glass gets some more details”,Jun. 27, 2012 (Jun. 27, 2012), Retrieved from the Internet: http://www.engadget.com/2012/06/27/googles-project-glass-gets-some-more-details/, 1 page, retrieved on Sep. 26, 2014.
T. Borzecki, G. Bruce, YS. Han, et al., Specialist Committee V.3 Fabrication Technology Committee Mandate, Aug. 20-25, 2006, 49 pages, vol. 2, 16th International Ship and Offshore Structures Congress, Southampton, UK.
G. Wang, P.G. Huang, and Y.M. Zhang: “Numerical Analysis of Metal Transfer in Gas Metal Arc Welding”: Departments of Mechanical Engineering; and Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40506-0108, 10 pages, Dec. 10, 2001.
Echtler et al, “The Intelligent Welding Gun: Augmented Reality for Experimental Vehicle Construction,” Virtual and Augmented Reality Applications in Manufacturing (2003) pp. 1-27.
Teeravarunyou et al, “Computer Based Welding Training System,” International Journal of Industrial Engineering (2009) 16(2): 116-125.
Antonelli et al, “A Semi-Automated Welding Station Exploiting Human-Robot Interaction,” Advanced Manufacturing Systems and Technology (2011) pp. 249-260.
Praxair Technology Inc, “The RealWeld Trainer System: Real Weld Training Under Real Conditions” Brochure (2013) 2 pages.
Xie et al., “A Real-Time Welding Training System Base on Virtual Reality,” Wuhan Onew Technology Co., Lid, IEEE Virtual Reality Conference Mar. 23-27, 2015, Arles France, pp. 309-310.
Lincoln Global, Inc., “VRTEX 360: Virtual Reality Arc Welding Trainer” Brochure (2015) 4 pages.
Wuhan Onew Technology Co Ltd, “ONEW-360 Welding Training Simulator” http://en.onewtech.com/_d276479751.htm as accessed on Jul. 10, 2015, 14 pages.
The Lincoln Electric Company, “VRTEX Virtual Reality Arc Welding Trainer,” http://www.lincolnelectric.com/en-us/equipment/training-equipment/Pages/vrtex.aspx as accessed on Jul. 10, 2015, 3 pages.
Miller Electric Mfg Co, “LiveArc: Welding Performance Management System” Owner's Manual, (Jul. 2014) 64 pages.
Miller Electric Mfg Co, “LiveArc Welding Performance Management System” Brochure, (Dec. 2014) 4 pages.
Bargteil et al., “A Texture Synthesis Method for Liquid Animations,” Eurographics/ ACM SIGGRAPH Symposium on Computer Animation, 2006, pp. 345-351.
Aidun, Daryush K “Influence of simulated high-g on the weld size of Al—Li-Alloy” Acta Astronautica, vol. 48, No. 2-3, pp. 153-156, 2001.
Boss (engineering), Wikipedia, 1 page, printed Feb. 6, 2014.
CS Wave, Product Description, 2 pages, printed Jan. 14, 2015.
EnergynTech Inc.; website printout; http://www.energyntech.com./; Advanced Metals Processing Technology & Flexible Automation for Manufacturing; Virtual Welder; Virtual training system for beginning welders; 2 page; 2014.
EnergynTech Inc.; website printout; http://www.energyntech.com/Zipper.html; Zipper Robot Performing a HiDep Weld; 1 page 2014.
Erden, “Skill Assistance with Robot for Manual Welding”, Marie Curie Intra-European Fellowship, Project No. 297857, 3 pgs., printed Apr. 27, 2015.
EWM Virtual Welding Trainer, 2 pages, printed Jan. 14, 2015.
Fillet weld, Wikipedia, 3 pgs, printed Feb. 6, 2014.
Fronius, Virtual Welding, 8 pages, printed Jan. 14, 2015.
Fronius, Virtual Welding, The Welder Training of the Future, 8 page brochure, 2011.
The Goodheart-Wilcox Co., Inc., Weld Joints and Weld Types, Chaper 6; pp. 57-68; date unknown.
Kemppi ProTrainer, product data, 3 pages, printed Jan. 14, 2015.
Leap Motion, Inc., product information, copyright 2013, 14 pages.
Learning Labs, Inc., Seabery, Soldamatic Augmented Reality Welding Trainers, 4 pgs., printed Mar. 20, 2014.
Lim et al., “Automatic classification of weld defects using simulated data and MLP neural network”, Insight, vol. 49, No. 3, Mar. 2007.
Narayan et al., “Computer Aided Design and Manufacturing,” pp. 3-4, 14-15, 17-18, 92-95, and 99-100, Dec. 31, 2008.
NSRP—Virtual Welding—A Low Cost Virtual Reality Welder Training System—Phase II—Final Report; Feb. 29, 2012; Kenneth Fast, Jerry Jones, Valerie Rhoades; 53 pages.
Seabury Soluciones, SOLDAMATIC Welding Trainer Simulator, 30 pages, printed Jan. 14, 2015.
Terebes; Institute of Automation; University of Bremen; Project Motivation Problems Using Traditional Welding Masks; 2 page ; 2015.
Weld nut, Wikipedia, 2 pgs, printed Feb. 6, 2014.
Bargteil et al., “A Semi-Lagrangian Contouring Method for Fluid Simulation,” ACM Transactions on Graphics, vol. 25, No. 1, Jan. 2006, pp. 19-38.
Chentanez et al., “Liquid Simulation on Lattice-Based Tetrahedral Meshes,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2007), 10 pages.
Chentanez et al., “Simultaneous Coupling of Fluids and Deformable Bodies,” Eurographics/ ACM SIGGRAPH Symposium on Computer Animation, 2006, pp. 83-89.
Russell and Norvig, “Artificial Intelligence: A Modern Approach”, Prentice-Hall (Copyright 1995).
Mechanisms and Mechanical Devices Source Book, Chironis, Neil Sclater, McGraw Hill; 2nd Addition, 1996.
Exhibit B from Declaration of Morgan Lincoln in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, dated Dec. 20, 2016, 5 pages.
Bender Shipbuilding and Repair Co. Virtual Welding—A Low Cost Virtual Reality Welding Training System. Proposal submitted pursuant to MSRP Advanced Shipbuilding Enterprise Research Announcement, Jan. 23, 2008. 28 pages. See also, http://www.nsrp.org/6-PresentationsM/D/020409 Virtual Welding Wilbur.pdf.
Aiteanu, Dorian; and Graser, Axel. “Generation and Rendering of a Virtual Welding Seam in an Augmented Reality Training Environment.” Proceedings of the Sixth IASTED International Conference on Visualization, Imaging and Image Processing, Aug. 28-30, 2006, 8 pages, allegedly Palma de Mallorca, Spain. Ed. J.J. Villaneuva. ACTA Press.
Tschirner, Petra; Hillers, Bernd; and Graser, Axel “A Concept for the Application of Augmented Reality in Manual Gas Metal Arc Welding.” Proceedings of the International Symposium on Mixed and Augmented Reality; 2 pages; 2002.
Penrod, Matt. “New Welder Training Tools.” EWI PowerPoint presentation; 16 pages; allegedly 2008.
Fite-Georgel, Pierre. Is there a Reality in Industrial Augmented Reality? 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR). 10 pages, allegedly 2011.
Hillers, B.; Graser, A. “Real time Arc-Welding Video Observation System.” 62nd International Conference of IIW, Jul. 12-17, 2009, 5 pages, allegedly Singapore 2009.
Advance Program of American Welding Society Programs and Events. Nov. 11-14, 2007. 31 pages. Chicago.
Terebes: examples from http://www.terebes.uni-bremen.de.; 6 pages.
Sandor, Christian; Gudrun Klinker. “PAARTI: Development of an Intelligent Welding Gun for BMW.” PIA2003, 7 pages, Tokyo. 2003.
ARVIKA Forum Vorstellung Projekt PAARI. BMW Group Virtual Reality Center. 4 pages. Nuermberg. 2003.
Sandor, Christian; Klinker, Gudrun. “Lessons Learned in Designing Ubiquitous Augmented Reality User Interfaces.” 21 gages, allegedly from Emerging Technologies of Augmented Reality: Interfaces Eds. Haller, M.; Billinghurst, M.; Thomas, B. Idea Group Inc. 2006.
Impact Welding: examples from current and archived website, trade shows, etc. See, e.g., http://www.impactwelding..com. 53 pages.
http://www.nsrp.org/6-Presentations/WDVirtual_Welder.pdf (Virtual Reality Welder Training, Project No. SI051, Navy ManTech Program, Project Review for ShipTech 2005); 22 pages. Biloxi, MS.
https://app.aws_org/w/r/www/wj/2005/031WJ_2005_03.pdf (AWS Welding Journal, Mar. 2005 (see, e.g., p. 54)).; 114 pages.
https://app.aws.org/conferences/defense/live index.html (AWS Welding in the Defense Industry conference schedule, 2004); 12 pages.
https://app.aws.org/wj/2004/04/052/njc (AWS Virtual Reality Program to Train Welders for Shipbuilding, workshop information, 2004); 7 pages.
https://app.aws.org/wj/2007/11WJ200711.pdf (AWS Welding Journal, Nov. 2007); 240 pages.
American Welding Society, “Vision for Welding Industry;” 41 pages.
Energetics, Inc. “Welding Technology Roadmap,” Sep. 2000, 38 pages.
Aiteanu, Dorian; and Graser, Axel. Computer-Aided Manual Welding Using an Augmented Reality Supervisor Sheet Metal Welding Conference XII, Livonia, MI, May 9-12, 2006, 14 pages.
Hillers, Bemd; Aiteanu, Dorin and Graser, Axel “Augmented Reality—Helmet for the Manual Welding Process,” Institute of Automation, University of Bremen, Germany; 21 pages.
ArcSentry Weld Quality Monitoring System; Native American Technologies, allegedly 2002, 5 pages.
P/NA.3 Process Modelling and Optimization; Native American Technologies, allegedly 2002, 5 pages.
B. Hillers, D. Aitenau, P. Tschimer, M. Park, A. Graser, B. Balazs, L. Schmidt, “Terebes: Welding Helmet with AR Capabilities”, Institute of Automatic University Bremen; Institute of Industrial Engineering and Ergonomics, 10 pages, allegedly 2004.
Sheet Metal Welding Conference Xlr, American Welding Society Detroit Section, May 2006, 11 pages.
Kenneth Fast, Timothy Gifford, Robert Yancey, “Virtual Training for Welding”, Proceedings of the Third IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR 2004); 2 pages.
Amended Answer to Complaint with Exhibit A for Patent Infringement filed by Seabery North America Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, docket No. 44, filed Mar. 1, 2016, in the U.S. District Court for the Northern District of Ohio; 19 pages.
Amended Answer to Complaint with Exhibit A for Patent Infringement filed by Seabery Soluciones SL in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L_ et al., Case No. 1:15-cv-01575-DCN, docket No. 45, filed Mar. 1, 2016 n the U.S. District Court for the Northern District of Ohio; 19 pages.
Reply to Amended Answer to Complaint for Patent Infringement filed by Lincoln Electric Company; Lincoln Global, Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN; docket No. 46, filed Mar. 22, 2016; 5 pages.
Answer for Patent Infringement filed by Lincoln Electric Company, Lincoln Global, Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN; docket No. 47, filed Mar. 22, 2016; 5 pages.
Petition for Inter Partes Review of U.S. Pat. No. 8,747,116; IPR 2016-00749; Apr. 7, 2016; 70 pages.
Petition for Inter Partes Review of U.S. Pat. No. RE45,398; IPR 2016-00840; Apr. 18, 2016; 71 pages.
Petition for Inter Partes Review of U.S. Pat. No. 9,293,056; IPR 2016-00904; May 9, 2016; 91 pages.
Petition for Inter Partes Review of U.S. Pat. No. 9,293,057; IPR 2016-00905; May 9, 2016; 87 pages.
http://www.vrsim.net/history, downloaded Feb. 26, 2016.
Complaint for Patent Infringement in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-av-01575-DCN, docket No. 1, filed Aug. 10, 2015, in the U.S. District Court for the Northern District of Ohio; 81 pages.
Kobayashi, Ishigame, and Kato, Simulator of Manual Metal Arc Welding with Haptic Display (“Kobayashi 2001”), Proc. of the 11th International Conf. on Artificial Reality and Telexistence (ICAT), Dec. 5-7, 2001, pp. 175-178, Tokyo, Japan.
Wahi, Maxwell, and Reaugh, “Finite-Difference Simulation of a Multi-Pass Pipe Weld” (“Wahi”), vol. L, paper 3/1, International Conference on Structural Mechanics in Reactor Technology, San Francisco, CA, Aug. 15-19, 1977.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00749.
Declaration of Edward Bohnert, Apr. 27, 2016, exhibit to IPR 2016-00749.
Swantec corporate web page downloaded Apr. 19, 2016. httpl/www.swantec.com/technology/numerical-simulation/.
Catalina, Stefanescu, Sen, and Kaukler, Interaction Of Porosity with a Planar Solid/Liquid Interface (Catalina),), Metallurgical and Materials Transactions, vol. 35A, May 2004, pp. 1525-1538.
Fletcher Yoder Opinion re RE45398 and U.S. Appl. No. 14/589,317; including appendices; Sep. 9, 2015; 1700 pages.
Kobayashi, Ishigame, and Kato, “Skill Training System of Manual Arc Welding By Means of Face-Shield-Like HMD and Virtual Electrode” (“Kobayashi 2003”), Entertainment Computing, vol. 112 of the International Federation for Information Processing (IFIP), Springer Science + Business Media, New York, copyright 2003, pp. 389-396.
G.E. Moore, No exponential is forever: but Forever can be delayed!: IEEE International Solid-State Circuits Conference, 2003. 19 pages.
“High Performance Computer Architectures_ A Historical Perspective,” downloaded May 5, 2016. http://homepages.inf.ed.ac.uk/cgi/mi/comparch. pl?Paru/perf.html,Paru/perf-f.html,Paru/menu-76.html; 3 pages.
Office Action from U.S. Appl. No. 16/366,324 dated Sep. 28, 2021.
Office Action from U.S. Appl. No. 16/366,300 dated Oct. 1, 2021.
Office Action from U.S. Appl. No. 16/366,378 dated Oct. 18, 2021.
Office Action from U.S. Appl. No. 16/366,378 dated Apr. 1, 2022.
Office Action from CN Application No. 201910308278.8 dated Mar. 1, 2022.
Office Action from CN Application No. 201910308996.5 dated Mar. 3, 2022.
Office Action from CN Application No. 201910308188.9 dated Mar. 16, 2022.
Office Action from U.S. Appl. No. 16/366,300 dated May 10, 2022.

Related Publications (1)

	Number	Date	Country
	20190325782 A1	Oct 2019	US

Provisional Applications (1)

	Number	Date	Country
	62659729	Apr 2018	US

Welding simulator with dual-user configuration

Information

Patent Number

Date Filed

Date Issued

Inventors

Original Assignees

Examiners

Agents

CPC

Field of Search

CPC

International Classifications

Disclaimer

Term Extension

Abstract