The present invention pertains to systems for emulating a virtual welding environment, and more particularly to virtual welding environments that emulate the welding of a boss weld joint in real time and the setup thereof.
For decades companies have been teaching welding skills. Traditionally, welding has been taught in a real world setting, that is to say that welding has been taught by actually striking an arc with an electrode on a piece of metal. Instructors, skilled in the art, oversee the training process making corrections in some cases as the trainee performs a weld. By instruction and repetition, a new trainee learns how to weld using one or more processes. However, costs are incurred with every weld performed, which varies depending on the welding process being taught.
In more recent times, cost saving systems for training welders have been employed. Some systems incorporate a motion analyzer. The analyzer includes a physical model of a weldment, a mock electrode, and sensing means that track movement of the mock electrode. A report is generated that indicates to what extent the electrode tip traveled outside an acceptable range of motion. More advanced systems incorporate the use of virtual reality, which simulates manipulation of a mock electrode in a virtual setting. Similarly, these systems track position and orientation. Such systems teach only muscle memory, but cannot teach the more advanced welding skills required of a skilled welder.
The embodiments of the present invention pertain to a simulator for facilitating virtual welding activity, including but not limited to the following elements: a logic processor based subsystem operable to execute coded instructions for generating an interactive welding environment that emulates welding setup and activity (including any tie-in operation(s)) on a boss weld joint, such as an interface between a section of virtual pipe and a virtual flat plate defining at least one virtual weld joint; a displaying means operatively connected to the logic processor based subsystem for visually depicting the interactive welding environment, wherein the displaying means depicts the virtual weld joint; a pendant or hand-held input device for performing setup and virtual welding activity on the at least one virtual weld joint in real time; and, one or more sensors adapted to track movement of the input device in real time for communicating data about the movement of the input device to the logic processor based subsystem. The input device will emulate controls for input selection for virtual reality welding. The logic processor based subsystem may further include restricting controls or interactions based on a user to enhance learning objectives. The logic processor based subsystem may optionally include teaching interaction or reactions based on visual, audible, physical changes to ensure that the user can properly setup a welding environment or can effect error recovery. The logic processor based subsystem often will include virtual calculators or tables that allow input and provide an output based on entered values. The logic processor based subsystem may also include intelligent agent-enabled results based on incorrect setup parameters or combination of parameters. The logic processor based subsystem may also include intelligent agent-enabled input to identify the proper setup parameters or combination of parameters which should have been entered by the user. The simulator may also include visual, audio or physical indicators of the setup parameters or combination of parameters. A camera-based system may be optionally added to track a path of a weld, including any stops and starts along said path. The camera system may include path-following and path-determinative systems based upon a fuzzy logic controller-based system. The simulator's logic processor based subsystem may include multiple levels for a user, each level adapted to the skill level, learning pace and learning style of the user and artificial intelligence based fault instruction in order to test a user's ability to detect, correct and recover from problems. Multi-language capabilities are also an optional aspect of the invention.
Referring now to the drawings wherein the showings are for purposes of illustrating embodiments of the invention only and not for purposes of limiting the same,
In generating an interactive virtual welding environment 15, simulator 10 emulates one or more welding processes for a plurality of weld joints in different welding positions, and additionally emulates the effects of different kinds of electrodes for the plurality of joint configurations. In one particular embodiment, simulator 10 generates an interactive virtual welding environment 15 that emulates welding of a boss weld joint such as typically encountered during pipe welding and/or welding of open root joints.
As used herein, “boss weld joint” generally refers to the welding interface between a first work piece and a second work piece, wherein at least one of the work pieces will typically have a round, contoured, or angled portion. As a result, at least a portion of the welding interface will typically be non-linear. In some embodiments, one of the work pieces will have a tab, flange, protrusion, or the like (i.e., a “boss”) that forms part of the welding interface. For example, a weld nut may include a boss portion that facilitates welding the weld nut to another work piece or surface. Such a boss, however, is not required to fall within the definition of “boss weld joint” as used herein. For example, the interface between a round pipe abutting a flat plate or the interface between two sections of pipe are also examples of a boss weld joint. For purposes of further describing the general inventive concepts, the boss joint welding process will generally be described herein in the context of welding a pipe to a flat plate.
The system is capable of simulating a weld puddle having real-time molten metal fluidity and heat dissipation characteristics. The simulator 10 is also capable of modeling how virtual welding activity affects the weld joint, e.g., the underlying base material. Illustratively, simulator 10 may emulate welding a root pass and a hot pass, as well as subsequent filler and cap passes, each with characteristics paralleling real-world scenarios. Each subsequent pass may weld significantly different from that of the previous pass as a result of changes in the base material made during the previous pass and/or as a result of a differently selected electrode. Real-time feedback of the puddle modeling allows the end user 12 to observe the virtual welding process on the display 200 and adjust or maintain his/her technique as the virtual weld is being performed. Examples of the kinds of virtual indicators observed may include: flow of the weld puddle, shimmer of molten puddle, changes in color during puddle solidification, freeze rate of the puddle, color gradients of heat dissipation, sound, bead formation, weave pattern, formation of slag, undercut, porosity, spatter, slag entrapment, overfill, blowthrough, and occlusions to name a few. It is to be realized that the puddle characteristics are dependent upon, that is to say responsive to, the end user's 12 movement of the input device 155. In this manner, the displayed weld puddle is representative of a real-world weld puddle formed in real-time based on the selected welding process and on the end user's 12 welding technique. Furthermore, “wagon tracks” is the visual trail of weld defects and slag left behind in the toes of the root pass made during boss joint (e.g., pipe) welding using the SMAW process. The second pass in the boss joint welding, called the hot pass, must be hot enough to remelt the wagon tracks so they are eliminated in the final weldment. Also, wagon tracks may be removed by a grinding process. Such wagon tracks and elimination of the wagon tracks are properly simulated in the simulator 10 described herein, in accordance with an embodiment of the present invention.
With continued reference to
With reference now to
Input Device
With reference now to
Illustratively, mock welding tool 160 simulates a stick welding tool for pipe welding and includes a holder 161 and a simulated stick electrode 162 extending therefrom. The simulated stick electrode 162 may include a tactilely resistive tip 163 to simulate resistive feedback that occurs during welding in a real-world setting. If the end user 12 moves the simulated stick electrode 162 too far back out of the root (described in detail below), the end user 12 will be able to feel or sense the reduced 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 end user 12 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 stick electrode 162, may be controlled by the logic processor-based subsystem 110 and more specifically by coded instructions executed by the logic processor-based subsystem 110. The simulated consumption rate may also depend on the end user's 12 technique. It is noteworthy to mention here that as simulator 10 facilitates virtual welding with different types of electrodes, the consumption rate or reduction of the stick electrode 162 may change with the welding procedure used and/or setup of the simulator 10.
The actuator of the mock welding tool 160 may be electrically driven. Power for engaging the actuator may come from the simulator 10, from an external power source or from internal battery power. In one embodiment, the actuator may be an electromotive device, such as an electric motor. Still, any type of actuator or form of motive force may be used including, but not limited to, electromagnetic actuators, pneumatic actuators, mechanical or spring-loaded actuators, in any combination thereof.
As indicated above, the mock welding tool 160 may work in conjunction with the spatial tracker for interacting with the simulator 10. In particular, the position and/or orientation of mock welding tool 160 may be monitored and tracked by the spatial tracker 120 in real time. Data representing the position and orientation may therefore be communicated to the logic processor-based subsystem 110 and modified or converted for use as required for interacting with the virtual welding environment 15.
Spatial Tracker
Referencing
The magnetic source 121 creates a magnetic field, or envelope, surrounding the source 121 defining a three dimensional space within which end user 12 activity may be tracked for interacting with the simulator 10. The envelope establishes a spatial frame of reference. Objects used within the envelope, e.g., mock welding tool 160 and coupon stand (described below), may be comprised of non-metallic, i.e., non-ferric and non-conductive, material so as not to distort the magnetic field created by the magnetic source 121. Each sensor 122 may include multiple induction coils aligned in crossing spatial directions, which may be substantially orthogonally aligned. The induction coils measure the strength of the magnetic field in each of the three directions providing information to the processor tracking unit 126. In one embodiment at least one sensor 122 is attached to the mock welding tool 160 allowing the mock welding tool 160 to be tracked with respect to the spatial frame of reference in both position and orientation. More specifically, the induction coils may be mounted in the tip of the electrode 162. In this way, simulator 10 is able to determine where within the three dimensional envelope the mock welding tool 160 is positioned. Additional sensors 122 may be provided and operatively attached to the one or more displaying devices 200. Accordingly, simulator 10 may use sensor data to change the view seen by the end user 12 responsive to the end user's 12 movements. As such, the simulator 10 captures and tracks the end user's 12 activity in the real world for translation into the virtual welding environment 15.
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 logic processor-based subsystem 110. In accordance with other alternative embodiments of the present invention, other types of spatial trackers 120 may be used in the simulator 10 including, for example, an accelerometer/gyroscope-based tracker, an optical tracker, an infrared tracker, an acoustic tracker, a laser tracker, a radio frequency tracker, an inertial tracker, an active or passive optical tracker, and augmented reality based tracking Still, other types of trackers may be used without departing from the intended scope of coverage of the general inventive concepts.
Displaying Device
With reference now to
The face mounted display device 140 operatively connects to the logic processor-based subsystem 110 and the spatial tracker 120 via wired or wireless means. A sensor 122 of the spatial tracker 120 may be attached to the face mounted display device 140 or to the welding helmet 900 thereby allowing the face mounted display device 140 to be tracked with respect to the 3D spatial frame of reference created by the spatial tracker 120. In this way, movement of the welding helmet 900 responsively alters the image seen by the end user 12 in a three dimensional virtual reality setting. The face mounted display device 140 may also function to call up and display menu items similar to that of observer display device 150, as subsequently described. In this manner, an end user is therefore able to use a control on the mock welding tool 160 (e.g., a button or switch) to activate and select options from the menu. This may allow the user to easily reset a weld if he makes a mistake, change certain parameters, or back up to re-do a portion of a weld bead trajectory, for example.
The face mounted display device 140 may further include speakers 910, allowing the user to hear simulated welding-related and environmental sounds produced by the simulator 10. Sound content functionality and welding sounds 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 mock welding tool 160 positioned correctly, and a hissing sound is provided when the mock welding tool 160 is positioned correctly. In a short arc welding process, a hissing sound is provided when undercutting is occurring. These sounds mimic real world sounds corresponding to correct and incorrect welding techniques.
High fidelity sound content may be taken from real world recordings of actual welding using a variety of electronic and mechanical means. The perceived volume and direction of the sound is modified depending on the position, orientation, and distance of the end user's head, i.e., the face mounted display device 140, with respect to the simulated arc between the mock welding tool 160 and the welding coupon 175. Sound may be provided to the user via speakers 910, which may be earbud speakers or any other type of speakers or sound generating device, mounted in the face mounted display device 140 or alternatively mounted in the console 135 and/or stand 170. Still, any manner of presenting sound to the end user 12 while engaging in virtual welding activity may be chosen. It is also noted here that other types of sound information may be communicated through the speakers 910. Examples include verbal instructions from the instructor user 12b, in either real time or via prerecorded messages. Prerecorded messages may be automatically triggered by particular virtual welding activity. Real time instructions may be generated on site or from a remote location. Still, any type of message or instruction may be conveyed to end user 12.
Console
With reference now to
The graphical user interface functionality 1213 (see
Accordingly, displaying device 200 reflects activity corresponding to the end user selections 153 including menu, actions, visual cues, new coupon set up, and scoring. These user selections may be tied to user buttons on the console 135. As a user makes various selections via displaying device 200, the displayed characteristics can change to provide selected information and other options to the user. However, the displaying device 200, which may be an observer display device 150, may have another function, which is to display virtual images seen by the end user 12 during operation of the simulator 10, i.e., while engaging in virtual welding activity. Displaying device 200 may be set up to view the same image as seen by the end user 12. Alternatively, displaying device 200 may also be used to display a different view, or different perspective of the virtual welding activity.
In one embodiment, displaying device 150, 200 may be used to play back virtual welding activity stored electronically on data storage devices 300, shown in
Referencing
Displaying device 200 may also be used to display tutorial information used to train an end user 12. Examples of tutorial information may include instructions, which may be displayed graphically as depicted by video or pictures. Additionally, instructions may be written or presented in audio format, mentioned above. Such information may be stored and maintained on the data storage devices 300. In one embodiment, simulator 10 is capable of displaying virtual welding scenes showing various welding parameters 151 including position, tip to work, weld angle, travel angle, and travel speed, termed herein as visual cues.
In one embodiment, remote communications may be used to provide virtual instruction by offsite personnel, i.e., remote users, working from similarly or dissimilarly constructed devices, i.e., simulators. Portraying a virtual welding process may be accomplished via a network connection including but not limited to the internet, LANs, and other means of data transmission. Data representing a particular weld (including performance variables) may be sent to another system capable of displaying the virtual image and/or weld data. It should be noted that the transmitted data is sufficiently detailed for allowing remote user(s) to analyze the welder's performance. Data sent to a remote system may be used to generate a virtual welding environment thereby recreating a particular welding process. Still, any way of communicating performance data or virtual welding activity to another device may be implemented without departing from the intended scope of coverage of the embodiments of the subject invention.
Welding Coupon
With reference now to
The dimensions of welding coupons 175 may vary. For cylindrical pipe, the range of inside diameters may extend from 1½ inches (inside diameter) to 18 inches (inside diameter). In one particular embodiment, the range of inside diameters may exceed 18 inches. In another embodiment, arcuate pipe segments may have a characteristic radius in the range extending from 1½ inches (inside diameter) up to and exceeding 18 inches (inside diameter). Furthermore, it is to be construed that any inside diameter of welding coupon 175 may be utilized, both those smaller than 1½ inches and those exceeding 18 inches. In a practical sense, any size of welding coupon 175 can be used as long as the welding coupon 175, or a portion of the welding coupon 175, fits within the envelope generated by the spatial tracker 120. Flat plate may extend up to and exceed 18 inches in length as well. Still, it is to be understood that the upper dimensional limits of a welding coupon 175 are constrained only by the size and strength of the sensing field generated by the spatial tracker 120 and its ability to be positioned respective of the welding coupon 175. All such variations are to be construed as falling within the scope of coverage of the embodiments of the subject invention.
In one embodiment, the welding coupon 175 includes a pipe 2000 or pipe section interfaced with a plate 2002 that is flat, planar, or the like. In this manner, the welding coupon 175 can emulate a pipe-on-plate weld, as a type of boss weld (see
In one embodiment, the pipe 2000 and the plate 2002 interface to form a fillet joint (see
In one embodiment, a lower section 2020 of the pipe 2000 includes a beveled or grooved section to form a groove joint (see
When welding certain weld joints, such as the fillet joint of
In one embodiment, a tie-in operation 2300 (e.g., as shown in
As the user prepares to begin a second weld pass 2326, it is important that the second weld pass 2326 is tied-in to the first weld pass 2308. Accordingly, the user positions the mock welding tool 2010 to begin welding at a third point 2320 on the weld path 2004 that at least partially overlaps the second point 2306 on the weld path 2004 where the first weld pass 2308 ended (see
The first weld pass 2308 and the second weld pass 2326, which are tied-in to one another, form the fillet joint weld between the pipe 2000 and the plate 2002.
As mentioned above, the welding coupon 175 may be constructed from a material that does not interfere with the spatial tracker 120. For spatial trackers generating a magnetic field, the welding coupon 175 may be constructed from non-ferrous and non-conductive material. However, any type of material may be chosen that is suitable for use with the type of spatial tracker 120 or other sensors selected.
Referencing
An alternative embodiment of the subject invention is contemplated wherein the positions of the table 171 and the arm 173 are automatically adjusted responsive to selections made during set up of the simulator 10. In this embodiment, selections made via the welding user interface 130 may be communicated to the logic processor-based subsystem 110. Actuators and feedback sensors employed by the stand 170 may be controlled by the logic processor-based subsystem 110 for positioning the welding coupon 175 without physically moving the arm 173 or the table 171. In one embodiment, the actuators and feedback sensors may comprise electrically driven servomotors. However, any locomotive device may be used to automatically adjust the position of the stand 170 as chosen with sound engineering judgment. In this manner, the process of setting up the welding coupon 175 is automated and does not require manual adjustment by the end user 12.
Another embodiment of the subject invention includes the use of intelligence devices used in conjunction with the welding coupon 175, termed herein as “smart” coupons 175. In this embodiment, the welding coupon 175 includes a device having information about that particular welding coupon 175 that may be sensed by the stand 170. In particular, the arm 173 may include detectors that read data stored on or within the device located on the welding coupon 175. Examples may include the use of digital data encoded on a sensor, e.g., micro-electronic device, that may be read wirelessly when brought into proximity of the detectors. Other examples may include the use of passive devices like bar coding. Still any manner of intelligently communicating information about the welding coupon 175 to the logic processor-based subsystem 110 may be chosen with sound engineering judgment.
The data stored on the welding coupon 175 may automatically indicate, to the simulator 10, the kind of welding coupon 175 that has been inserted in the stand 170. For example, a 2-inch pipe coupon may include information related to its diameter. Alternatively, a flat plate coupon may include information that indicates the kind of weld joint included on the coupon, e.g., a groove weld joint or a butt weld joint, as well as its physical dimensions. In this manner, information about the welding coupon 175 may be used to automate that portion of the setup of the simulator 10 related to selecting and installing a welding coupon 175.
Calibration functionality 1208 (see
Any part of the same type of welding coupon 175, accordingly, fits into the arm 173 of the stand 170 in the same repeatable way to within very tight tolerances. Therefore, once a particular type welding coupon 175 is calibrated, repeated calibration of similar coupons is not necessary, i.e., calibration of a particular type of welding coupon 175 is a one-time event. Stated differently, welding coupons 175 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 mock welding tool 160 around the corner of an actual welding coupon 175, the user will see the tip sliding around the corner of the virtual welding coupon on the displaying device 200 as the user feels the tip sliding around the actual corner. In accordance with an embodiment of the present invention, the mock welding tool 160 may also be placed in a pre-positioned jig and calibrated in a similar manner, based on the known jig position.
In accordance with another embodiment of the subject invention, “smart” coupons may include sensors that allow the simulator 10 to track the pre-defined calibration point, or corners of the “smart” coupon. The sensors may be mounted on the welding coupon 175 at the precise location of the predefined calibration points. However, any manner of communicating calibration data to the simulator 10 may be chosen. Accordingly, the simulator 10 continuously knows where the “smart” coupon is in real world 3D space. Furthermore, licensing keys may be provided to “unlock” welding coupons 175. When a particular welding coupon 175 is purchased, a licensing key may be provided that allows the end user 12a, 12b to enter the licensing key into the simulator 10, unlocking the software associated with that particular welding coupon 175. In an alternative embodiment, special nonstandard welding coupons may be made or otherwise provided based on real-world CAD drawings of parts.
With reference now to
With reference to
The internal architecture functionality 1207 provides the higher level software logistics of the processes of the simulator 10 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 logic processor-based subsystem 110 include arc location, gun position, face-mounted display device or helmet position, gun on/off state, and contact made state (yes/no).
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 observer display device 150). Tracking information from the spatial tracker 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 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. In one embodiment, the SAM, the WWAM, and/or some other module is used to track, graph, or otherwise account for tie-in operations, as described herein. For each parameter analyzed by the SAM, the WWAM, and/or other related module, 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.
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 fillet size, poor bead placement, improper tie-in, concave bead, excessive convexity, undercut, porosity, incomplete fusion, slag entrapment, and excess 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 provide 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. 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.
Visual cues functionality 1219 provide immediate feedback to the user by displaying overlaid colors and indicators on the face mounted display device 140 and/or the observer display device 150. Visual cues are provided for each of the welding parameters 151 including position, tip to work, weld angle, travel angle, and travel speed 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, weld bead “dime” spacing, and proper tie-in technique, for example.
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 (a.k.a., the physics model) which may be executed 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, and is described in more detail herein with respect to
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. 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 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.
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 many welding operations are actually performed in the real world. The double displacement layer modeling of the welding physics functionality 1211 run 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, welding electrode, 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 (as a form of tie-in) 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 performed to repair a weld bead formed by a previous pass, for example, or may include a heat pass and one or more gap closing passes after a root pass as is done in pipe welding. In accordance with various embodiments of the present invention, base and weld bead material may be simulated to include mild steel, stainless steel, and aluminum.
As noted above, the merging of multiple weld passes is termed a “tie-in.” The second or subsequent weld pass may be performed parallel to and at least partially on top of a first or prior weld pass. Another type of tie-in is when a weld pass is interrupted or otherwise halted prior to traversing the complete weld path. Thereafter, the user starts a new weld pass on the weld path, wherein the new weld pass overlaps or is otherwise interfaced with the pre-existing weld pass. Thus, a proper tie-in involves correctly merging the two or more weld passes making up the weld along the weld path.
In accordance with an embodiment of the present invention, welding with stainless steel materials is simulated in a real-time virtual environment. The base metal appearance is simulated to provide a realistic representation of a stainless steel weldment. Simulation of the visual effect is provided to change the visual spectrum of light to accommodate the coloration of the arc. Realistic sound is also simulated based on proper work distance, ignition, and speed. The arc puddle appearance and deposition appearance are simulated based on the heat affected zone and the torch movement. Simulation of dross or broken particles of aluminum oxide or aluminum nitride films, which can be scattered throughout the weld bead, is provided. Calculations related to the heating and cooling affected zones are tailored for stainless steel welding. Discontinuity operations related to spatter are provided to more closely and accurately simulate the appearance of stainless steel GMAW welding.
In accordance with an embodiment of the present invention, welding with aluminum materials is simulated in a real-time virtual environment. The bead wake is simulated to closely match the appearance of the aluminum welding to that seen in the real world. The base metal appearance is simulated to represent a realistic representation of an aluminum weldment. Simulation of the visual effect is provided to change the visual spectrum of light to accommodate the coloration of the arc. A calculation of lighting is provided to create reflectivity. Calculations related to the heating and cooling affected zones are tailored for aluminum welding. Simulation of oxidation is provided to create a realistic “cleaning action.” Realistic sound is also simulated based on proper work distance, ignition, and speed. The arc puddle appearance and deposition appearance are simulated based on the heat affected zone and the torch movement. The appearance of the aluminum wire is simulated in the GMAW torch to provide a realistic and proper appearance.
In accordance with an embodiment of the present invention, GTAW welding is simulated in a real-time virtual environment. Simulation of operational parameters for GTAW welding are provided including, but not limited to, flow rate, pulsing frequency, pulse width, arc voltage control, AC balance, and output frequency control. Visual representation of the puddle “splash” or dipping technique and melt off of the welding consumable are also simulated. Furthermore, representations of autogenous (no filler metal) and GTAW with filler metal welding operations in the welding puddle are rendered visually and audibly. Implementation of additional filler metal variations may be simulated including, but not limited to, carbon steel, stainless steel, aluminum, and Chrome Moly. A selectable implementation of an external foot pedal may be provided for operation while welding.
Engine for Modeling
Each type of coupon defines the direction of displacement for each location in the wexel map. For the flat welding coupon of
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 simulator 10 include attraction/repulsion, velocity (related to heat), dampening (related to heat dissipation), and direction (related to gravity).
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
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 simulator 10, 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, 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 simulator 10 by wexel decimation techniques. If the amount of heat absorbed by a wexel is determined to be too high by the simulator 10, 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 simulator 10 simulates wexel decimation (taking material away) and wexel reconstitution (adding material back).
Furthermore, removing material in root-pass welding is properly simulated in the simulator 10. For example, in the real world, grinding of the root pass may be performed prior to subsequent welding passes. Similarly, simulator 10 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 simulator 10 resulting in an altered bead contour. Simulation of the grinding pass may be automatic, which is to say that the simulator 10 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 to much material or indicate when too much material is being removed.
In addition to the non-visible “puddle” particles described herein, the simulator 10 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 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 simulator 10, 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 simulator 10 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.
In accordance with an alternative embodiment of the present invention, the simulator 10 is capable of teaching a user how to troubleshoot a welding machine. For example, a troubleshooting mode of the system may train a user to make sure he sets up the system correctly (e.g., correct gas flow rate, correct power cord connected). In accordance with another alternate embodiment of the present invention, the simulator 10 is capable of recording and playing back a welding session (or at least a portion of a welding session, for example, N frames). A track ball may be provided to scroll through frames of video, allowing a user or instructor to critique a welding session. Playback may be provided at selectable speeds as well (e.g., full speed, half speed, quarter speed). In accordance with an embodiment of the present invention, a split-screen playback may be provided, allowing two welding sessions to be viewed side-by-side, for example, on the observer display device 150. For example, a “good” welding session may be viewed next to a “poor” welding session for comparison purposes.
Automated welding is also an aspect of the present invention. One illustrative example of automated welding is orbital welding, which is often used for the joining of tubes or pipes of various types of materials. For example, a TIG (GTAW) welding torch may be used to orbit around the pipes to be welded together by an automated mechanical system.
While the above discussion has focused on the virtual reality simulation of various welding processes, including orbital welding, embodiments of the invention are not limited to that aspect and includes teaching and feedback aspects of the actual setup and performance characteristics associated with welds made in accordance with a user-defined setup. As discussed above, GTAW/GMAW welding requires training to ensure that the operator understands the controls which are available for the practice of a welding process, for example, an orbital welding process. There is a misconception that automation associated with orbital welding systems eliminates the need for training, since the machine is doing the welding. Automated orbital welding requires training to ensure the operator understands welding, and all of the unique setup and implementation skills for controlling TIG beads. This includes error correction, larger diameter pipe welding, the utilization of remote cameras, and proper error assessment and correction.
Training programs offer inconsistent or insufficient coverage of teaching a good weld situation, a bad weld situation, and the mechanisms to perform, react to, or correct each. Instructors for this type of niche solution are hard to find with sufficient background and/or industry knowledge and experience. Only through quality training taught by certified instructors can operators of welding equipment gain the complex skills needed to meet the strict acceptance criteria in today's welding environment. Additionally, on large circumference projects with long weld joints (which may include one or more tie-ins), the difficulty of maintaining attention and focus represents a significant problem.
In the GTAW process, an electric arc is maintained between the non-consumable tungsten electrode and the work piece. The electrode supports the heat of the arc and the metal of the work piece melts and forms the weld puddle. The molten metal of the work piece and the electrode must be protected against oxygen in the atmosphere, thereby typically employing an inert gas such as argon as the shielding gas. If the addition of a filler metal is used, the filler wire can be fed to the weld puddle, where it melts due to the energy delivered by the electric arc. In accordance with one embodiment of the invention, a virtual reality welding system is provided that incorporates technology related to viewing a GTAW/GMAW automated welding operation, using a pendant (actual or virtual) or remote control as it relates to automated welding, identifying welding discontinuities based upon chosen welding parameter combinations, and correcting operator selections and combinations of parameters through the use of user screens to understand the interaction of various parameters and their impact on weld quality with proper terminology and visual elements related to automated welding.
By implementing welding (e.g., orbital GTAW) training in a virtual environment, a number of issues may be addressed. For example, industry and experience in the welding process may be based on the knowledge of the development company and therefore is consistent and updated to the latest technology and standards available, which is easily done by software upgrade in a virtual environment. The instructor becomes a facilitator to the program and does not need to be an expert in the welding process. Additional training aids, such as path following cues or visual overlays, improve transfer of training in a virtual environment. Welding equipment, that can become outdated, does not need to be purchased. The virtual reality system can be used in a one-on-one training environment or a classroom type of setting.
The use of a virtual framework allows multiple pendants to be simulated with one training device. In implementing a welding (e.g., orbital GTAW) process in virtual reality, a pendant can be made as a physical device or as a virtual pendant. With the physical device, the student is able to interact with the controls and get the “feel” for the control. With a virtual pendant, where the controls are available and interacted with on a touch screen, the user can easily choose a variety of pendants for control, whether they are customized or company dependant. A virtual pendant also allows for different types of controls or levels to be enabled for use by the student depending on learning levels or controls available based on their industry level (mirroring field work experience). Unlike traditional training, randomized faults (e.g., wire nesting) can be implemented that provide the user a more detailed and complete experience without damage to the equipment or time-consuming setup.
Part of the learning interaction is the understanding of proper welding parameters based on the joint, preparation, material type, etc. In accordance with an embodiment, in virtual reality, theory enabled screens can be enabled to prompt a user with knowledge as to the proper choice to make. Additional screens or tables can be enabled to prompt a user with knowledge of what to input, but can also be enabled when a wrong choice is selected to highlight what was chosen and why it was incorrect, with the proper selections identified. This type of intelligent agent can ensure that the student does not perform incorrectly and become frustrated by the end result, positive reinforcement and learning being the key. An embodiment of the invention will also allow for the system or instructor to quiz user's knowledge and adapt the training curriculum and testing to the individual user's blind spots. An embodiment of the present invention employs artificial intelligence (AI) and a learning management system (LMS) to help with instruction in needed areas, reinforce knowledge, and provide learning assistance.
Setup parameters may include, but are not limited to: inert gas (e.g., Argon, Helium); arc ignition; welding current (e.g., pulsed vs. unpulsed); downslope functionality to avoid crate ring at the end of the weld; torch rotation travel speed; wire feed characteristics (e.g., pulsed waveforms); wire diameter selection; arc voltage; distance between electrode and work piece; welding oscillation control; remote control; cooling characteristics of the generally integrated closed-loop water cooling circuit; and weld cycle programming (often with four axes), etc.
Inspection and review of the weld is another aspect to the learning process. The student can view the weld and identify what is correct or wrong and, based on these choices, receive a score to identify whether they were right and further receive input on what is right or wrong based on industry standards. This can be enhanced further to identify how to correct these situations. For instance, with the correct amperage and speed (identified), the weld may be a good weld based on a particular industry standard.
As described above, a physical teach pendant or a hand-held control device for input selection in virtual reality welding may be provided. Alternatively, a virtual teach pendant device for control input selection for virtual reality welding may be provided. Interactions with the handheld or virtual device that are student learning level or industry role dependant can be enabled on the device. Restricting controls or interactions based on the user may be provided to enhance learning objectives or reinforce industry role interactions, in accordance with an embodiment.
Teaching interaction or reactions based on visual, audible, or physical changes may be provided to ensure the user knows the proper set-up or error recovery. Also, teaching interaction or reactions based on visual, audible, or physical changes may be provided to ensure the user knows the proper changes in controls needed based on environmental or weld specific changes being made. Virtual calculators or tables may be enabled that allow input and provide an output based on values entered. Intelligent agent enabled results based on incorrect set-up parameters or choices may be provided to reinforce correct industry standards. Furthermore, intelligent agent enabled input to identify what the proper controls input should have been may be provided, based on the current visual, audio, or physical indicators. In accordance with an embodiment, the simulation of camera based systems may be provided along with the creation of path following and path determinative systems based upon a fuzzy logic controller based system. For example, multiple renderings may be provided by simulating two camera views such that the camera views may be moved during the simulation. In accordance with an embodiment, an alarm may sound when the desired path is deviated from, based on the fuzzy logic, for example. Visualization of a simulated TIG weld puddle may be provided via pixel sizes that are small enough to provided proper visualization of the TIG weld puddle. Simulation of the magnification of the simulated TIG weld puddle may also be provided, for better visualization by the user.
Multiple levels of experience for the user that adapt to the skill level, learning pace and learning style of the user (LMS compatible) may be provided. Artificial intelligence (AI) based fault induction may also be provided in order to test the user's ability to detect, correct, and recover from problems. The simulation of unsafe conditions, machine setup, and materials defects may be provided. Also, a multilanguage capable system may be provided, allowing for harmonization of training for a global marketplace, in accordance with an embodiment. An embodiment of the present invention may provide a virtual simulation environment allowing two or more users (multi-man) to create a virtual weld, such as in certain orbital welding scenarios.
In summary, disclosed is a real-time virtual reality welding system including 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 virtual reality space, a weld puddle having real-time molten metal fluidity and heat dissipation characteristics. The system is further capable of displaying the simulated weld puddle on the display device in real-time.
The invention has been described herein with reference to the disclosed embodiments. Obviously, modifications and alterations will occur to others upon a reading and understanding of this specification. It is intended to include all such modifications and alterations insofar as they come within the scope of the appended claims or the equivalence thereof.
The present application is being filed as a non-provisional patent application claiming priority under 35 U.S.C. §119(e) from, and any other benefit of, U.S. Provisional Patent Application No. 61/940,221 filed on Feb. 14, 2014, the entire disclosure of which is herein incorporated by reference. Each of the following commonly-assigned co-pending U.S. patent applications is incorporated by reference herein in its entirety: (1) U.S. patent application Ser. No. 12/501,257, filed on Jul. 10, 2009 and entitled System And Method Providing Arc Welding Training In A Real-Time Simulated Virtual Reality Environment Using Real-Time Weld Puddle Feedback; (2) U.S. patent application Ser. No. 12/501,263, filed on Jul. 10, 2009 and entitled Virtual Reality Pipe Welding Simulator; (3) U.S. patent application Ser. No. 12/504,870, filed on Jul. 17, 2009 and entitled Welding Simulator; (4) U.S. patent application Ser. No. 13/081,725, filed on Apr. 7, 2011 and entitled Virtual Testing And Inspection Of A Virtual Weldment; (5) U.S. patent application Ser. No. 13/364,489, filed on Feb. 2, 2012 and entitled Virtual Welding System; and (6) U.S. patent application Ser. No. 13/545,058, filed on Jul. 10, 2012 and entitled Virtual Reality Pipe Welding Simulator And Setup.
Number | Name | Date | Kind |
---|---|---|---|
317063 | Wittenstrom | May 1885 | A |
428459 | Coffin | May 1890 | A |
483428 | Goppin | Sep 1892 | A |
1159119 | Springer | Nov 1915 | A |
1288529 | De Does | 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 |
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 |
4611111 | Baheti et al. | Sep 1986 | A |
4616326 | Meier et al. | Oct 1986 | A |
4629860 | Lindbom | 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 | 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 | 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 | 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 | Dabral et al. | Jul 1998 | A |
5823785 | Matherne | 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 | May 2001 | B1 |
6236017 | Smartt et al. | May 2001 | B1 |
6242711 | Cooper | Jun 2001 | B1 |
6271500 | Hirayama 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 | Haanpaa 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 et al. | 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 et al. | Jul 2003 | B1 |
6621049 | Suzuki | Sep 2003 | B2 |
6624388 | Blankenship et al. | 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 |
6708835 | 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 |
6857533 | 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 |
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 |
7487018 | Afshar et al. | Feb 2009 | B2 |
D587975 | Aronson et al. | Mar 2009 | S |
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'Donoghue | 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 |
8860760 | Chen et al. | Oct 2014 | B2 |
8911237 | Postlethwaite 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 | Kindig et al. | Apr 2015 | B2 |
9293056 | Zboray | Mar 2016 | B2 |
9293057 | Zboray | Mar 2016 | B2 |
20010045808 | Hietmann 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 |
20020050984 | Roberts | May 2002 | A1 |
20020054211 | Edelson et al. | May 2002 | A1 |
20020085843 | Mann | Jul 2002 | A1 |
20020094026 | Edelson | Jul 2002 | A1 |
20020111557 | Madill et al. | Aug 2002 | A1 |
20020135695 | Edelson et al. | Sep 2002 | A1 |
20020175897 | Pelosi | Nov 2002 | A1 |
20020180761 | Edelson et al. | Dec 2002 | A1 |
20030000931 | Ueda et al. | Jan 2003 | A1 |
20030002740 | Melikian | Jan 2003 | A1 |
20030023592 | Modica et al. | Jan 2003 | A1 |
20030025884 | Hamana et al. | Feb 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 |
20040020907 | Zauner et al. | Feb 2004 | A1 |
20040035990 | Ackeret | Feb 2004 | A1 |
20040050824 | Samler | Mar 2004 | A1 |
20040088071 | Kouno | May 2004 | A1 |
20040140301 | Blankenship et al. | Jul 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 |
20050109735 | Flood | May 2005 | A1 |
20050128186 | Shahoian et al. | Jun 2005 | A1 |
20050133488 | Blankenship et al. | 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 |
20050252897 | Hsu 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 |
20060166174 | Rowe | Jul 2006 | A1 |
20060169682 | Kainec et al. | Aug 2006 | A1 |
20060173619 | Brant 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 |
20070088536 | Ishikawa | Apr 2007 | A1 |
20070112889 | Cook et al. | May 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 |
20080038702 | Choquet | Feb 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 | 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 et al. | Oct 2009 | A1 |
20090298024 | Batzler | Dec 2009 | A1 |
20090312958 | Dai | 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 | Feb 2010 | A1 |
20100062405 | Zboray et al. | Mar 2010 | A1 |
20100062406 | Zboray | 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 |
20100299101 | Shimada et al. | Nov 2010 | A1 |
20100307249 | Lesage et al. | Dec 2010 | A1 |
20100314362 | Albrecht | Dec 2010 | A1 |
20110006047 | Penrod | Jan 2011 | A1 |
20110048273 | Colon | Mar 2011 | A1 |
20110052046 | Melikian | Mar 2011 | A1 |
20110060568 | Goldfine | Mar 2011 | A1 |
20110082728 | Melikian | Apr 2011 | A1 |
20110091846 | Kreindl | 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 | Jul 2011 | A1 |
20110187746 | Suto et al. | Aug 2011 | A1 |
20110187859 | Edelson | Aug 2011 | A1 |
20110229864 | Short et al. | Sep 2011 | A1 |
20110248864 | Becker | Oct 2011 | A1 |
20110316516 | Schiefermuller et al. | Dec 2011 | A1 |
20120189993 | Kindig | Jul 2012 | A1 |
20120291172 | Wills et al. | Nov 2012 | A1 |
20120298640 | Conrardy | Nov 2012 | A1 |
20130026150 | Chantry | 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 |
20130203029 | Choquet | Aug 2013 | A1 |
20130206740 | Pfeifer | Aug 2013 | A1 |
20130209976 | Postlethwaite | Aug 2013 | A1 |
20130230832 | Peters | Sep 2013 | A1 |
20130231980 | Elgart et al. | Sep 2013 | A1 |
20130252214 | Choquet | Sep 2013 | A1 |
20130288211 | Patterson et al. | Oct 2013 | A1 |
20130327747 | Dantinne | Dec 2013 | A1 |
20130342678 | McAninch et al. | Dec 2013 | A1 |
20140038143 | Daniel | Feb 2014 | A1 |
20140042136 | Daniel et al. | Feb 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 |
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 | Mar 2015 | A1 |
20150125836 | Daniel | May 2015 | A1 |
20150194073 | Becker | Jul 2015 | A1 |
20150248845 | Postlethwaite | Sep 2015 | A1 |
20160093233 | Boulware | Mar 2016 | A1 |
20160203734 | Boulware | Jul 2016 | A1 |
20160203735 | Boulware | Jul 2016 | A1 |
20160260261 | Hsu | Sep 2016 | A1 |
20160331592 | Stewart | Nov 2016 | A1 |
20160343268 | Postlethwaite | Nov 2016 | A1 |
20170053557 | Daniel | Feb 2017 | A1 |
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 |
102083580 | Jun 2011 | CN |
102202836 | Sep 2011 | CN |
202053009 | Nov 2011 | CN |
202684308 | Jan 2013 | CN |
203503228 | Mar 2014 | CN |
103871279 | Jun 2014 | CN |
2833638 | Feb 1980 | DE |
3046634 | Jan 1984 | DE |
3244307 | May 1984 | DE |
3522581 | Jan 1987 | DE |
4037879 | Jun 1991 | DE |
19615069 | Oct 1997 | DE |
19739720 | Oct 1998 | DE |
19834205 | Feb 2000 | DE |
20009543 | Aug 2001 | DE |
102005047204 | Apr 2007 | DE |
102006048165 | Jan 2008 | DE |
102010038902 | Feb 2012 | DE |
0008527 | Mar 1980 | EP |
108599 | May 1984 | EP |
127299 | Dec 1984 | EP |
145891 | Jun 1985 | EP |
319623 | Oct 1990 | EP |
852986 | Jul 1998 | EP |
1527852 | May 2005 | EP |
1905533 | Apr 2008 | EP |
2274736 | May 2007 | ES |
1456780 | Mar 1965 | FR |
2827066 | Jan 2003 | FR |
2926660 | Jul 2009 | FR |
1455972 | Nov 1976 | GB |
1511608 | May 1978 | GB |
2254172 | Sep 1992 | GB |
2435838 | Sep 2007 | GB |
2454232 | May 2009 | GB |
02-224877 | Sep 1990 | JP |
05-329645 | Dec 1993 | JP |
07-047471 | Feb 1995 | JP |
07-232270 | Sep 1995 | JP |
08-505091 | Apr 1996 | JP |
08-150476 | Jun 1996 | JP |
08-132274 | May 1998 | JP |
2000-167666 | Jun 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 |
2006006604 | Jan 2006 | JP |
2006-281270 | Oct 2006 | JP |
2007290025 | Nov 2007 | JP |
2009500178 | Jan 2009 | JP |
2009160636 | Jul 2009 | JP |
2012024867 | Feb 2012 | JP |
20090010693 | Jan 2009 | KR |
527045 | Jul 1995 | RU |
2317183 | Feb 2008 | RU |
2008108601 | Nov 2009 | RU |
10388963 | Aug 1983 | SU |
1998045078 | Oct 1998 | WO |
200112376 | Feb 2001 | WO |
2001043910 | Jun 2001 | WO |
2001058400 | Aug 2001 | WO |
2004029549 | Apr 2004 | WO |
2005102230 | Nov 2005 | WO |
2005110658 | Nov 2005 | WO |
2006034571 | Apr 2006 | WO |
2007039278 | Apr 2007 | WO |
2009060231 | May 2009 | WO |
2009120921 | Oct 2009 | WO |
2009149740 | Dec 2009 | WO |
2010000003 | Jan 2010 | WO |
2010044982 | Apr 2010 | WO |
2010091493 | Aug 2010 | WO |
2011045654 | Apr 2011 | WO |
2011058433 | May 2011 | WO |
2011059502 | May 2011 | WO |
2011067447 | Jun 2011 | WO |
2011097035 | Aug 2011 | WO |
2012016851 | Feb 2012 | WO |
2012082105 | Jun 2012 | WO |
2012143327 | Oct 2012 | WO |
2013014202 | Jan 2013 | WO |
2013061518 | May 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 |
Entry |
---|
International Preliminary Report on Patentability from PCT/IB20141001796 dated Mar. 15, 2016. |
Office action from U.S. Appl. No. 15/077,481 dated May 23, 2016. |
Response from U.S. Appl. No. 15/077,481 dated Jun. 23, 2016. |
Office Action from Chinese Application No. 201280075678.5 dated Jul. 5, 2016. |
Notice of Allowance from U.S. Appl. No. 15/077,481 dated Aug. 10, 2016. |
Office Action from Chinese Application No. 201480027306.4 dated Aug. 3, 2016. |
Office Action from Chinese Application No. 201380017661.9 dated Aug. 22, 2016. |
International Preliminary Report on Patentability from PCT/IB2015/000161 dated Aug. 25, 2016. |
International Preliminary Report on Patentability from PCT/IB2015/000257 dated Sep. 15, 2016. |
Office Action from Chinese Application No. 201480025359.2 dated Sep. 26, 2016. |
Office Action from U.S. Appl. No. 14/190,812 dated Nov. 9, 2016. |
Office Action from Chinese Application No. 201480025614.3 dated Nov. 28, 2016. |
Office Action from U.S. Appl. No. 14/293,700 dated Dec. 28, 2016. |
Office Action from U.S. Appl. No. 14/293,826 dated Dec. 30, 2016. |
Adams et al., “Adaptively Sampled Particle Fluids,” ACM Transactions on Graphics, vol. 26, No. 3, Article 48, Jul. 2007, pp. 48.1-48.7. |
Bargteil et al., “A Texture Synthesis Method for Liquid Animations,” Eurographics/ ACM SIGGRAPH Symposium on computer Animation, 2006, pp. 345-351. |
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. |
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. |
Feldman et al., “Animating Suspended Particle Explosions,” Computer Graphics Proceedings, Annual Conference Series, Jul. 27-31, 2003, pp. 1-8. |
Feldman et al., “Fluids in Deforming Meshes,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 2005, pp. 255-259. |
Foster et al., “Practical Animation of Liquids,” ACM SIGGRAPH, Aug. 12-17, 2001, Los Angeles, CA, pp. 23-30. |
Foster et al., “Realistic Animation of Liquids,” Graphical Models and Image Processing, vol. 58, No. 5, Sep. 1996, pp. 471-483. |
Goktekin et al., “A Method for Animating Viscoelastic Fluids,” Computer Graphics Proceedings, Annual Conference Series, Aug. 8-12, 2004, pp. 1-6. |
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. |
Irving et al., “Efficient Simulation of Large Bodies of Water by Coupling Two and Three Dimensional Techniques,” ACM Transactions on Graphics (TOG), vol. 25, Issue 3, Jul. 2006, pp. 805-811. |
Kass et al., “Rapid, Stable Fluid Dynamics for Computer Graphics,” Computer Graphics, vol. 24, No. 4, Aug. 1990, pp. 49-57. |
Klinger et al., “Fluid Animation with Dynamic Meshes,” Computer Graphics Proceedings, Annual Conference Series, Jul. 30-Aug. 3, 2006, pp. 820-825. |
Muller et al., “Particle-Based Fluid Simulation for Interactive Applications,” Eurographics/SIGGRAPH Symposium on computer Animation (2003), pp. 154-159 and 372. |
O'Brien et al., “Dynamic Simulation of Splashing Fluids,” Proceedings of Computer Animation, Apr. 19-21, 1995, Geneva, Switzerland, pp. 198-205. |
Premoze et al., “Particle-Based Simulation of Fluids,” EUROGRAPHICS, vol. 22, No. 3, 2003, 10 pages. |
Rasmussen et al., “Directable Photorealistic Liquids,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 2004, pp. 193-202. |
Stam, “Stable Fluids,” SIGGRAPH 99 Conference Proceedings, Annual Conference Series, Aug. 1999, pp. 121-128. |
Thurey et al., “Real-time Breaking Waves for Shallow Water Simulations,” Proceedings of the Pacific Conference on computer Graphics and Applications, Maui, HI Oct. 29-Nov. 2, 2007, 8 pages. |
Grahn et al., “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. |
Vesterlund et al., “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. |
Muller et al., “Point Based Animation of Elastic, Plastic and Melting Objects,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2004), 11 pages. |
Nealen, “Point-Based Animation of Elastic, Plastic, and Melting Objects,” CG topics, Feb. 2005, 2 pages. |
Tonnesen, “Modeling Liquids and Solids using Thermal Particles,” Proceedings of Graphics Interface 1991, 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 Dalto 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, “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. |
Aiteanu, “Virtual and Augmented Reality Supervisor for a New Welding Helmet,” Dissertation Nov. 15, 2005, 154 pages. |
Screen Shot of 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/images/english/snap—evolution6.jpg, 1 page. |
Da Dalto et al. “CS Wave A Virtual learning tool for the welding motion,” Mar. 14, 2008, 10 pages. |
Nordruch et al., “Visual Online Monitoring of PGMAW Without a Lighting Unit,” Jan. 2005, 14 pages. |
Tamasi, “The Evolution of Computer Graphics,” NVIDIA, 2008, 36 pages. |
VRSim Powering Virtual Reality, www.lincolnelectric.com/en-us/eguipment/Iraining-eguipment/Pages/powered-by-'rsim.aspx, 2016, 1 page. |
Hillers et al., “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. |
Arc+—Archived Press Release from WayBack Machine from Jan. 31, 2008-Apr. 22, 2013, https://web.3rchive.org/web/20121006041803/http://www.123certification.com/en/article—press/index.htm, downloaded on Jan. 21, 2016, 3 pages. |
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. |
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. |
Jeffus, “Welding Principles and Applications,” Sixth Edition, 2008, 10 pages. |
Renwick et al., “Experimental Investigation of GTA Weld Pool Oscillations,” Welding Research—Supplement to the Welding Journal, Feb. 1983, 7 pages. |
Phar, “GPU Gems 2 Programming Techniques for High-Performance Graphics and General-Purpose Computation,” 2005, 12 pages. |
Notice of Allowance from U.S. Appl. No. 15/077,481 dated Feb. 3, 2017. |
Office Action from U.S. Appl. No. 14/526,914 dated Feb. 3, 2017. |
International Preliminary Report on Patentability from PCT/IB2015/000158 dated Jan. 26, 2017. |
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. |
International Search Report and Written Opinion from PCT/IB2015/000777 dated Dec. 15, 2016. |
International Search Report and Written Opinion from PCT/IB2015/000814 dated Dec. 15, 2016. |
“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. |
Aiteanu et al., “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 et al., “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, “New Welder Training Tools,” EWI PowerPoint presentation, 16 pages, allegedly 2008. |
Fite-Georgel, “Is there a Reality in Industrial Augmented Reality?” 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 10 pages, allegedly 2011. |
Hillers et al., “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 et al., “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, Nuernberg, 2003. |
Sandor et al., “Lessons Learned in Designing Ubiquitous Augmented Reality User Interfaces,” 21 pages, 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 et al., “Computer-Aided Manual Welding Using an Augmented Reality Supervisor,” Sheet Metal Welding conference XII, Livonia, MI, May 9-12, 2006, 14 pages. |
Hillers et al., “Augmented Reality—Helmet for the Manual Welding Process,” Institute of Automation, University of Bremen, Germany, 21 pages. |
Aiteanu et al., “A Step Forward in Manual Welding: Demonstration of Augmented Reality Helmet” Institute of Automation, University of Bremen, Germany, Proceedings of the Second IEEE and ACM International Symposium on Mixed and Augmented Reality; 2003, 2 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. |
Hillers et al., “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 XII, American Welding Society Detroit Section, May 2006, 11 pages. |
Fast et al., “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 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, doc. 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 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, doc. No. 45, filed Mar. 1, 2016, in 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 Co., Lincoln Global, Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, doc. No. 46, filed Mar. 22, 2016, in the U.S. District Court for the Northern District of Ohio, 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, doc No. 47, filed Mar. 22, 2016, in the U.S. District Court for the Northern District of Ohio, 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, 10:04:37 pm. |
Complaint for Patent Infringement in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-av-01575-DCN, doc. No. 1, filed Aug. 10, 2015, in the U.S. District Court for the Northern District of Ohio, 81 pages. |
Kobayashi et al., “Simulator of Manual Metal Arc Welding with Haptic Display,” Proc. of the 11th International Conf. on Artificial Reality and Telexistence (ICAT), Dec. 5-7, 2001, pp. 175-178, Tokyo, Japan. |
Wahi et al., “Finite-Difference Simulation of a Multi-Pass Pipe Weld,” 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, http://www.swantec.com/technology/numerical-simulation/. |
Catalina et al., “Interaction of Porosity with a Planar Solid/Liquid Interface,” Metallurgical and Materials Transactions, vol. 35A, May 2004, pp. 1525-1538. |
Fletcher Yoder Opinion re RE45398 and U.S. Appl. No. 14/589,317, Sep. 9, 2015, 41 pages. |
Kobayashi et al., “Skill Training System of Manual Arc Welding by Means of Face-Shield-Like HMD and Virtual Electrode,” 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. |
International Preliminary Report on Patentability from PCT/IB2015/001084 dated Jan. 26, 2017. |
Office Action from U.S. Appl. No. 14/190,812 dated Feb. 23, 2017. |
Office Action from U.S. Appl. No. 14/552,739 dated Feb. 17, 2017. |
Juan Vicenete Rosell Gonzales, “RV-Sold: simulator virtual para la formacion de soldadores”; Deformacion Metalica, Es. vol. 34, No. 301 Jan. 1, 2008. |
Graham, Texture Mapping, Carnegie Mellon University Class 15-462 Computer Graphics, Lecture 10, 53 pages, dated Feb. 13, 2003. |
Guu et al.,Technique for Simultaneous Real-Time Measurements of Weld Pool Surface Geometry and Arc Force, Welding Research Supplement—pp. 473-482, Dec. 1992. |
Hillis et al.; “Data Parallel Algorithms”, Communications of the ACM, Dec. 1986, vol. 29, No. 12, p. 1170. |
Response to Office Action dated Nov. 14, 2014 from U.S. Appl. No. 13/543,240 dated Mar. 13, 2015. |
Hirche et al., Hardware Accelerated Per-Pixel Displacement Mapping, 8 pages, 2004. |
Hu et al., 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. |
Aidun, Influence of Simulated High-g on the Weld Size of Al—Li Alloy, Acta Astronautica, vol. 48, No. 2-3, pp. 153-156, 2001. |
Jonsson et al., Simulation of Tack Welding Procedures in Butt Joint Welding of Plates Welding Research Supplement, Oct. 1985, pp. 296-302. |
Kemppi ProTrainer, product data, 3 pages, printed Jan. 14, 2015. |
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. |
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. |
Wade, Human uses of ultrasound: ancient and modern Department of Electrical and Computer Engineering, University of California at Santa Barbara 93106, USA. Ultrasonics (Impact Factor: 1.81). Apr. 2000; 38(1-8):1-5. |
Production Monitoring 2 brochure, four (4) pages, The Lincoln Electric Company, May 2009. |
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; Issue Date Feb. 2012. |
Lincoln Electric, VRTEX Virtual Reality Arc Welding Trainer, 9 pgs. Printed Feb. 2, 2014. |
Lincoln Electric, Vrtex 360 Virtual Reality Arc Welding Trainer, 4 pgs., Oct. 2014. |
Linholm et al., “NVIDIA Testla: A Unifired Graphics and Computing Architecture”, IEEE Computer Society, 2008. |
Mahrle et al., “The influence of fluid flow phenomena on the laser beam welding process”, Intl. J. of Heat and Fluid Flow, 23, pp. 288-297 (2002). |
Mann et al., 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. |
Yosh Mantinband et al., Autosteroscopic, field-sequential display with full freedom of movement OR Let the display were the shutter-glasses, yosh@3ality.com, (Israel) Ltd., 8 pages, 2002. |
Mavrikios 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, Apr. 1, 2006, pp. 294-300. |
Mechanisms and Mechanical Devices Sourcebook, Chironis, McGraw Hill, Neil Sclater, 2nd Ed. 1996. |
Miller Electric Mfg. Co., “LiveArc Welding Performance Management System”, 4 pg. brochure, Dec. 2014. |
Miller Electric, Owner's Manual, Live Arc, Welding Performance Management System, Owners's Manual—OM-267 357A; 64 pgs., Jul. 2014. |
Miller Electric Mgf. Co.; MIG Welding System features weld monitoring software; NewsRoom 2010 (Dialog® File 992); © 2011 Dialog. 2010; http://www.dialogweb.com/cgi/dwclient?reg=1331233430487; three (3) pages; printed Mar. 8, 2012. |
N. A. Tech., P/NA.3 Process Modeling and Optimization, 11 pages, Jun. 4, 2008. |
NSRP ASE, Low-Cost Virtual Reality Welder Training System, 1 Page, 2008. |
NVIDIA Tesla: A Unified Graphics and Computing Architecture, IEEE Computer Society 0272-1732, Mar.-Apr. 2008. |
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. |
Porter et al., Virtual Reality Training, Paper No. 2005-P19, 14 pages, 2005. |
Porter et al., Virtual Reality Welder Training, 29 pages, dated Jul. 14, 2006. |
Porter, Virtual Reality Welder Trainer, Session 5: Joining Technologies for Naval Applications: earliest date Jul. 14, 2006 (http://weayback.archive.org), Edision Welding Institute; J. Allan Cote, General Dynamics Electric Boat; Timothy D. Gifford, VRSim, and Wim Lam, FCS Controls. |
Praxair, “The RealWeld Trainer System”, two page brochure, 2013. |
Ratnam et al., “Automatic classification of weld defects using simulated data and an MLP neutral network.” Insight vol. 49, No. 3; Mar. 2007. |
Reeves, “Particles Systems—A Technique for Modeling a Class of Fuzzy Objects”, Computer Graphics 17:3 pp. 359-376, 1983, 17 pages. |
Rodjito, Position tracking and motion prediction using Fuzzy Logic, 81 pages, 2006, Colby College, Honors Theses, Paper 520. |
Russell et al., “Artificial Intelligence: A Modern Approach”, Prentice-Hall (Copyright 1995). |
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. |
Seabury Soluciones, SOLDAMATIC Welding Trainer Simulator, 30 pages, printed Jan. 14, 2015. |
SIMFOR / CESOL, “RV-SOLD” Welding Simulator, Technical and Functional Features, 20 pages., no date available. |
Sim Welder, Train better welders faster, retrieved on Apr. 12, 2010 from: http://www.simwelder.com. |
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. |
Teeravarunyou et al., “Computer Based Welding Training System”, Intl J of Industrial Engineering, 16 (2), pp. 116-125 (2009). |
Veiga, Simulation of a Work Cell in the IGRIP Program, dated 2006, 50 pages. |
ViziTech USA, Changing the Way America Learns, retrieved on Mar. 27, 2014 from http://vizitechusa.com/, 2 pages. |
International Search Report and Written Opinion from PCT/IB2015/000777 dated Sep. 21, 2015. |
International Search Report and Written Opinion from PCT/IB2015/001711 dated Jan. 4, 2016. |
Narayan et al., “Computer Aided Design and Manufacturing,” pp. 3-4, 14-15, 17-18, 92-95, and 99-100, Dec. 31, 2008. |
Office Action from Chinese Application No. 201480025359.2 dated Feb. 28, 2017. |
Office Action from Chinese Application No. 201380076368.X dated Mar. 1, 2017. |
Yaoming, “Applications of Microcomputer in Robot Technology,” Scientific and Technical Documentation Press, Sep. 1987, pp. 360-365. |
Notice of Allowance from U.S. Appl. No. 14/293,700 dated May 10, 2017. |
Xie et al., “A Real-Time Welding Training System Base on Virtual Reality,” Wuhan Onew Technology Co., Lid, IEEE Virtual Reality Conference 2015, Mar. 23-27, Arles France, pp. 309-310. |
Office Action from U.S. Appl. No. 14/526,914 dated Jun. 6, 2017. |
Office Action from U.S. Appl. No. 14/827,657 dated May 26, 2017. |
Extended European Search Report from EP Application No. 10860823.3 dated Jun. 6, 2017. |
Office Action from U.S. Appl. No. 14/293,826 dated Jul. 21, 2017. |
Office Action from Chinese Application No. 201480025614.3 dated Jun. 9, 2017. |
Notice of Allowance from U.S. Appl. No. 13/543,240 dated Sep. 3, 2015. |
International Search Report and Written Opinion from PCT/IB2009/006605 dated Feb. 12, 2010. |
International Search Report and Written Opinion from PCT/IB10/02913 dated Apr. 19, 2011. |
International Search Report and Written Opinion from PCT/IB2014/002346 dated Feb. 24, 2015. |
International Search Report and Written Opinion from PCT/IB2015/000161 dated Jun. 8, 2015. |
International Search Report and Written Opinion from PCT/IB2015/000257 dated Jul. 3, 2015. |
Notice of Allowance from U.S. Appl. No. 13/543,240 dated Jun. 3, 2015. |
16th International Ship and Offshore Structures Congress : Aug. 20-25, 2006; Southhampton, U.K. vol. 2 Specialist Committee V.3 Fabrication Technology Committee Mandate: T. Borzecki, G. Bruce, Y.S. Han, M. Heinermann, A. Imakita, L. Josefson, W. Nie, D. Olsen, F. Roland and Y. Takeda. Naval Ship Design, ABS Papers 2006. |
Abbas et al., Code Aster (Software) EDF (France), 29 pages, Oct. 2001. |
Abbas et al.; Code—Aster; Introduction to Code—Aster; User Manual; Booklet U1.0-: Introduction to Code—Aster; Document: U1.02.00; Version 7.4; Jul. 22, 2005. |
Abid, et al., “Numerical Simulation to study the effect of tack welds and root gap on welding deformations and residual stresses of a pipe flange joint” Intl. J. of Pressure Vessels and Piping, 82, pp. 860-871 (2005). |
Abida et al., 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. |
Agren; Sensor Integration for Robotic Arc Welding; 1995; vol. 5604C of Dissertations Abstracts International p. 1123; Dissertation Abs Online (Dialog® File 35): © 2012 ProQuest Info& Learning: http://dialogweb.com/cgi/dwclient?req=1331233317524; one (1) page; printed Mar. 8, 2012. |
Aidun et al., “Penetration in Spot GTA Welds during Centrifugation,” Journal of Materials Engineering and Performance vol. 7(5) Oct. 1998—597-600. |
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. |
Antonelli et al., “A Semi-Automated Welding Station Exploiting Human-robot Interaction”, Dept. of Production Systems and Economics, pp. 249-260, 2011. |
Arc+ simulator; 2 pgs., http://www.123arc.com/en/depliant—ang.pdf; 2000. |
asciencetutor.com, A division of Advanced Science and Automation Corp., VWL (Virtual Welding Lab), 2 pages, 2007. |
ASME Definitions, Consumables, Welding Positions, dated Mar. 19, 2001. See http://www.gowelding.com/wp/asme4.htm. |
B. Virtual Reality Welder Trainer, Session 5, joining Technologies for Naval Applications, earliest date Jul. 14, 2006 (Nancy Porter of EWI). |
Balijepalli et al., “A Haptic Based Virtual Grinding Tool”, Haptic Interfaces for Virtual Environment and Teleoperator Systems, Haptics 2003, 7-.,Department of Mechanical & Aerospace Engineering, State University of New York at Buffalo, NY. |
Borzecki 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. |
Boss (engineering), Wikipedia, 1 page, printed Feb. 6, 2014. |
ChemWeb.com, Journal of Materials Engineering and Performance (v.7, #5), 3 pgs., printed Sep. 26, 2012. |
Chen et al., Self-Learning Fuzzy Neural Networks and Computer Vision for Control of Pulsed GTAW, Welding Research Supplement, pp. 201-209, dated May 1997. |
Choquet; “Arc+: Today's Virtual Reality Solution for Welders” Internet Page, Jan. 1, 2008, 6 pages. |
Code Aster (Software) EDF (France), Oct. 2001. |
Cooperative Research Program, Virtual Reality Welder Training, Summary Report SR 0512, 4 pages, Jul. 2005. |
CS Wave, The Virtual Welding Trainer, 6 pages, 2007. |
CS Wave, A Virtual learning tool for welding motion, 10 pages, Mar. 14, 2008. |
CS Wave, Product Description, 2 pages, printed Jan. 14, 2015. |
Desroches.; Code-Aster, Note of use for calculations of welding; Instruction manual U2.03 booklet: Thermomechanical; Document: U2.03.05; Oct. 1, 2003. |
D'huart et al.; Virtual Environment for Training: An Art of Enhancing Reality, 6th International Conference, ITS 20002, Biarritz, France and San Sebastian, Spain, 6 pages, Jun. 2002. |
Dotson, Augmented Reality Welding Helmet Prototypes How Awesome 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. |
Echtler et al., “The Intelligent Welding Gun: Augmented Reality of Experimental Vehicle Construction”, Virtual and Augmented Reality Applications in Manufacturing, 17, pp. 1-27, Springer Verlag, 2003. |
Edison Welding Institute, E-Weld Predictor, 3 pages, 2008. |
Eduwelding+, Weld Into the Future; Online Welding Seminar—A virtual training environment; 123arc.com; 4 pages, 2005. |
Eduwelding+, Training Activities with arc+ simulator; Weld Into The Future, Online Welding Simulator—A virtual training environment; 123arc.com; 6 pages, May 2008. |
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. |
The Fabricator, Virtually Welding, Training in a virtual environment gives welding students a leg up, 4 pages, Mar. 2008. |
Fast et al., “Virtual Training for Welding”, Mixed and Augmented Reality, 2004, ISMAR 2004, Third IEEE and CM International Symposium on Arlington, VA, Nov. 2-5, 2004. |
Fillet weld, Wikipedia, 3 pgs. Printed Feb. 6, 2014. |
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. |
Fronius, Virtual Welding, 8 pages, printed Jan. 14, 2015. |
Joanneum, Fronius—virtual welding, 2 pages, May 12, 2008. |
Fronius, Virtual Welding/The Welder Training of the Future!, 8 page brochure, 2011. |
Garcia-Allende et al.; Defect Detection in Arc-Welding Processes by Means of the Line-to-Continuum Method and Feature Selection; www.mdpi.comijournal/sensors; Sensors 2009, 9, 7753-7770; doi; 10.3390/s91007753. |
International Search Report and Written Opinion from PCT/US10/60129 dated Feb. 10, 2011. |
International Search Report and Written Opinion from PCT/US12/45776 dated Oct. 1, 2012. |
Office Action from U.S. Appl. No. 12/499,687 dated Oct. 16, 2012. |
“Numerical Analysis of Metal Transfer in Gas Metal Arc Welding,” G. Wang, P.G. Huang, and Y.M. Zhang. Departments of Mechanical and Electrical Engineering. University of Kentucky, Dec. 10, 2001. |
Numerical Analysis of Metal Transfer in Gas Metal Arc Welding Under Modified Pulsed Current Conditions, G. Wang, P.G. Huang, and Y.M. Zhang. Metallurgical and Materials Transactions B, vol. 35B, Oct. 2004, pp. 857-866. |
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, p. 954-958. |
Weld nut, Wikipedia, 2 pgs. Printed Feb. 6, 2014. |
Weldplus, Welding Simulator, 2 pages, printed Jan. 14, 2015. |
White et al., Virtual welder trainer, 2009 IEEE Virtual Reality Conference, p. 303, 2009. |
Chuansong Wu: “Microcomputer-based welder training simulator”, Computers in Industry, vol. 20, No. 3, Oct. 1992, pp. 321-325, XP000205597, Elsevier Science Publishers, Amsterdam, NL. |
Wuhan Onew Technology Co., Ltd., “Onew Virtual Simulation Expert”, 16 pgs., printed Apr. 16, 2015. |
Yao et al., ‘Development of a Robot System for Pipe Welding’. 2010 International Conference on Measuring Technology and Mechatronics Automation. Retrieved from the Internet: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5460347&tag=1; pp. 1109-1112, 4 pages. |
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. |
Terebes; Institute of Automation; University of Bremen; Project Motivation Problems Using Traditional Welding Masks; 2 page; 2015. |
WeldWatch Software/Visible Welding; website printout; http://visiblewelding.com/weldwatch-software/4 pages; 2015. |
Products/Visible Welding; Weldwatch Video Monitoring System; website prinout http://visible welding.com/products; 4 pages; 2015. |
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. |
Corrected Notice of Allowance from U.S. Appl. No. 12/966,570 dated Feb. 23, 2015. |
Office Action from U.S. Appl. No. 14/444,173 dated Mar. 18, 2015. |
Response to Office Action dated Mar. 18, 2015 from U.S. Appl. No. 14/444,173 dated Jun. 11, 2015. |
Notice of Allowance from U.S. Appl. No. 14/444,173 dated Jun. 24, 2015. |
Response from U.S. Appl. No. 12/499,687 dated Apr. 10, 2013. |
Office Action from U.S. Appl. No. 12/499,687 dated Jun. 26, 2013. |
Response from U.S. Appl. No. 12/499,687 dated Nov. 25, 2013. |
Office Action from U.S. Appl. No. 12/499,687 dated Mar. 6, 2014. |
Response from U.S. Appl. No. 12/499,687 dated Sep. 5, 2014. |
Office Action from U.S. Appl. No. 12/499,687 dated Nov. 6, 2014. |
Office Action from U.S. Appl. No. 12/966,570 dated May 8, 2013. |
Response from U.S. Appl. No. 12/966,570 dated Oct. 8, 2013. |
Notice of Allowance from U.S. Appl. No. 12/966,570 dated Apr. 29, 2014. |
Office Action from U.S. Appl. No. 13/543,240 dated Nov. 14, 2014. |
International Search Report and Written Opinion from PCT/IB2015/000814 dated Nov. 5, 2015. |
Office Action from U.S. Appl. No. 14/829,161 dated Jul. 28, 2017. |
Office Action in CN Application No. 201480012861.X dated Jul. 18, 2017. |
Office Action in CN Application No. 201610179195.X dated Jul. 19, 2017. |
Office Action in CN Application No. 201480025985.1 dated Aug. 10, 2017. |
Decision of Rejection in CN Application No. 201380047141.2 dated Sep. 7, 2017. |
Number | Date | Country | |
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20150235565 A1 | Aug 2015 | US |
Number | Date | Country | |
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61940221 | Feb 2014 | US |