Systems and methods for a weld training system

Information

  • Patent Grant
  • 11127313
  • Patent Number
    11,127,313
  • Date Filed
    Monday, August 13, 2018
    6 years ago
  • Date Issued
    Tuesday, September 21, 2021
    3 years ago
Abstract
Systems and methods for a weld training system are disclosed. An example weld training system includes: a mobile device configured to be attached to a welding accessory using a mount, the mobile device comprising one or more sensors, wherein the mobile device is configured to: gather, via the one or more sensors of the mobile device, information indicative of dynamic position or orientation of the mobile device during a welding procedure; and display, via a display of the mobile device, a welding environment based on the information.
Description
BACKGROUND

The present disclosure relates generally to welding systems, and more particularly, to a mobile device that may be used as a weld training tool for training and/or recruiting purposes.


Welding is a process that has increasingly become utilized in various industries and applications. Such processes may be automated in certain contexts, although a large number of applications continue to exist for manual welding operations. In both cases, such welding operations rely on a variety of types of equipment to ensure the supply of welding consumables (e.g., wire feed, shielding gas, etc.) is provided to the weld in appropriate amounts at the desired time.


In preparation for performing manual welding operations, welding operators may be trained using a weld training system. The weld training system may be designed to train welding operators with the proper techniques for performing various welding operations. Various training methods and systems may be utilized within the weld training systems. However, these training methods and systems are generally large and unwieldy, and may be too expensive to produce and utilize in higher volumes. Accordingly, it may be beneficial to provide for low cost weld training methods and systems that may be readily produced and utilized in higher volumes.


BRIEF DESCRIPTION

In an embodiment, weld training system is provided. The weld training system includes a welding torch configured to perform a welding procedure and a mobile device coupled to the welding torch. The mobile device is configured to detect, via one or more sensors, dynamic position or orientation information of the welding torch during the welding procedure to determine one or more operating parameters of the welding procedure. The mobile device is also configured to display a welding environment based at least in part on the one or more operating parameters.


In another embodiment, a weld training system is provided. The weld training system includes a welding torch configured to perform a simulated welding procedure on a simulated weld joint on an orientation device. The welding training system also includes a mobile device coupled to the welding torch. The mobile device includes a camera configured to detect one or more of a plurality of identifiers disposed on the orientation device. The mobile device also includes a processor configured to determine dynamic position or orientation information of the welding torch based at least in part on the one or more of the plurality of identifiers detected by the camera.


In another embodiment, a non-transitory computer-readable medium storing computer instructions is provided. The computer instructions are configured to perform, via a welding torch of a weld training system, a virtual welding procedure on a simulated weld joint with respect to an orientation device. The orientation device is a simulated work surface. The computer instructions are configured to receive, via one or more sensors disposed with a mobile device coupled to welding torch, dynamic position or orientation information of the welding torch. The computer instructions are configured to determine, via processing circuitry disposed within the mobile device, updated position or orientation information of the welding torch based at least in part on the received position or orientation information. The updated position or orientation information is utilized to determine one or more operating parameters of the virtual welding procedure.





DRAWINGS

These and other features, aspects, and advantages of the present disclosure will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:



FIG. 1 is a block diagram of an embodiment of a weld training system utilizing a mobile device coupled to a welding torch, in accordance with aspects of the present disclosure;



FIG. 2 is an embodiment of the mobile device coupled to the welding torch of FIG. 1, in accordance with aspects of the present disclosure;



FIG. 3 is an embodiment of the mobile device coupled to the welding torch of FIG. 1, where the mobile device is utilized with an orientation device, in accordance with aspects of the present disclosure; and



FIG. 4 is an embodiment of a screen illustrating data corresponding to a simulated, augmented, or virtual reality welding environment, in accordance with aspects of the present disclosure.





DETAILED DESCRIPTION

Embodiments of the systems and methods described herein relate to a weld training system that utilizes a mobile device. In certain embodiments, the mobile device may be coupled to a welding torch of the weld training system, and an operator may engage the welding torch and the mobile device to perform a simulated welding experience for training or recruiting purposes. In particular, the mobile device may be configured to provide sensor feedback information related to the simulated welding experience to the weld training system and/or the operator. For example, one or more sensors disposed within the mobile device may be configured to detect position or orientation information of the welding torch during the simulated welding experience. Further, based on the position or orientation information detected, the mobile device may be configured to display a visual representation of a virtual welding environment on a display of the mobile device or on an external device. In addition, the mobile device may be configured to determine one or more operating parameters of the simulated weld during the simulated welding experience and, in certain embodiments, may display the one or more operating parameters on the display of the mobile device or the external device.


In certain embodiments, the welding torch and the mobile device may be configured to perform the simulated welding experience using an orientation device. For example, the orientation device may be a prefabricated two-dimensional or three-dimensional material having a series of identifiers (e.g., various patterns of dots, textures, raised surfaces, barcodes, QR codes, etc.) that orient the welding torch and guide the operator performing the simulated weld. In some situations, the orientation device may be configured for a particular type or a particular series of simulated welds. In certain embodiments, the mobile device may utilize one or more cameras or optical sensors to detect the identifiers on the orientation device to orient the welding torch while the particular type or series of simulated welds is performed relative to the orientation device.


In certain embodiments, the mobile device of the weld training system may be coupled to a welding torch performing an actual welding procedure (e.g., live welding arc, live-arc mode). In these situations, the weld training system may enable an augmented welding experience configured to enable training using augmented reality simulation. For example, the mobile device may be configured to provide a live video of the welding operator performing an augmented reality weld, live video of a welding arc, live video of a weld puddle, and/or simulated video of a welding operation. Furthermore, in certain embodiments, the mobile device may provide real-time feedback information on relevant process parameters of the augmented welding process that further guides the operator during the augmented welding experience.


In this manner, the operator may engage in a real-time simulated welding experience or a real-time augmented welding experience for training or recruiting purposes via a low cost weld training system. Specifically, the low cost weld training system described herein may be utilized and reproduced in higher volumes. It should be noted that the mobile device may also be configured to provide post-weld feedback providing a summary of the relevant process parameters of the simulated or augmented welding experience, including the operator's actions.


As used herein, the weld training system may include any suitable welding related system, including, but not limited to, a welding training system, a live welding system, a simulated welding system, a virtual reality welding system, a welding training application (e.g., utilized on a mobile device), a welding training system utilized on a gaming platform, and so forth. In certain embodiments, the weld training system may be configured to perform a virtual welding operation, a shielded metal arc welding (SAW) process, a gas-metal arc welding (GMAW) process, a tungsten inert gas (TIG) welding process, a plasma cutting process, or any other type of welding process.



FIG. 1 is a block diagram of an embodiment of a weld training system 10, in accordance with aspects of the present disclosure. As noted above, embodiments of the weld training system 10 include any suitable welding related system, including a welding application executed using the weld training system 10 that enables a simulated or an augmented welding experience. In certain embodiments, the weld training system 10 includes a mobile device 12, which may be any personal mobile device and/or portable mobile device. For example, the mobile device 12 may be a cellular phone (e.g., smart phone, iPhone®, Android® phone, Windows® phone, Blackberry®), a tablet computer, a laptop computer, a personal data assistant (PDA), and so forth. The mobile device 12 may have various sensors (e.g., accelerometers, gyroscopes, cameras, magnetometers, GPS) disposed within a sensor system 14 as described below, a memory to store data and instructions, and a processor configured to receive feedback from the sensors and to execute instructions for the mobile device 12. In some embodiments, the mobile device 12 includes a display screen configured to display information (e.g., graphical simulated welding experience, augmented welding experience, weld parameters) to the operator.


In particular, the illustrated embodiment depicts the mobile device 12 communicatively coupled to a welding torch 24. The mobile device 12 of the weld training system 10 includes one or more processors 16 (or any computing component), memory device(s) 18, storage device(s) 20, and a display 22. The processor(s) 16 may be used to execute software, such as welding software, a welding application, image processing software, sensing device software, and so forth. Moreover, the processor(s) 16 may include one or more microprocessors, such as one or more “general-purpose” microprocessors, one or more special-purpose microprocessors and/or application specific integrated circuits (ASICS), or some combination thereof. For example, the processor(s) 16 may include one or more reduced instruction set (RISC) processors.


The memory 18 may include a volatile memory, such as random access memory (RAM), and/or a nonvolatile memory, such as read-only memory (ROM). The memory device(s) 18 may store a variety of information and may be used for various purposes. For example, the memory device(s) 18 may store processor-executable instructions (e.g., firmware or software) for the processor(s) 16 to execute, such as instructions (e.g., application) for enabling a simulated or augmented welding experience via the mobile device 12 and/or instructions to communicate feedback information from/to the mobile device 12. In addition, a variety of control regimes for various welding processes, along with associated settings and parameters may be stored in the storage device(s) 20 and/or memory device(s) 18, along with code configured to provide a specific output (e.g., initiate wire feed, enable gas flow, capture welding current data, detect short circuit parameters, determine amount of spatter, etc.) during the simulated or augmented welding operation.


The storage device(s) 20 (e.g., nonvolatile storage) may include ROM, flash memory, a hard drive, or any other suitable optical, magnetic, or solid-state storage medium, or a combination thereof. The storage device(s) 20 may store data (e.g., data corresponding to a simulated or an augmented welding operation, video and/or parameter data corresponding to a simulated or augmented welding operation, etc.), instructions (e.g., software or firmware for the welding system, software for the welding application, software to enable communications and/or control with the mobile device 12, etc.), and any other suitable data. As will be appreciated, data that corresponds to the simulated or augmented welding operation may include a video recording of the welding operation, a simulated or augmented video, an orientation and/or a position of system 10 components, a work angle of the welding torch 24 with respect to a simulated or real workpiece, a travel angle of the welding torch 24 with respect to a simulated or real workpiece, a travel speed of the welding torch 24 with respect to a simulated or real workpiece, a distance between components of the system 10, a voltage, a current, a traversed path, a discontinuity analysis, welding device settings, and so forth.


As discussed above, the mobile device 12 comprises the display 22 configured for displaying data and/or screens associated with the simulated or augmented welding process (e.g., to display data generated by welding software), among other things. The display 22 may provide a graphical user interface to a welding operator (e.g., welding instructor, welding student, etc.). For example, the graphical user interface displayed by the display 22 may provide various screens to enable the operator (e.g., welding student, welding gamer, welding trainee, etc.) to perform the simulated or augmented welding task, view real-time feedback of the simulated or augmented welding parameters, view a post-welding summary of the simulated or augmented welding task, view averages and/or results from prior simulated or augmented welding tasks, compare and view final welding scores of one or more welding operators, and so forth. In certain embodiments, the display 22 may be a touch screen display configured to receive touch inputs, and to provide data corresponding to the touch inputs to the mobile device 12. In some embodiments, the display 22 is configured to display information corresponding to sensing device software, and provide a virtual and/or simulated image of the weld being performed, as further described below.


As noted above, the mobile device 12 may include a welding application disposed on the memory device(s) 18 and executed by the processor(s) 16. Further, an operator may engage the welding application via the display 22. For example, the welding application may allow an operator to select from various types or sequences of weld geometries, such as a T, fillet, butt, or other geometry, as well as the orientation of the weld (e.g., flat, horizontal, vertical, overhead). Based on the selected parameters of the simulated weld, the welding application may commence. In certain embodiments, after the operator engages a trigger on the welding torch 24 or the welding process is selected on the display 22, and as the welding torch 24 is moved, the sensor system 14 of the mobile device 12 may gather position and/or orientation information of the welding torch 24 as sensor feedback information. Based on the sensor feedback information, the display may graphically illustrate the welding torch 24 coming into position with respect to a simulated joint within a simulated welding environment.


In certain embodiments, the display 22 may display a menu where the operator 16 is able to specify settings such as the type of welding application, the mode of welding (e.g., simulated mode, live-arc mode, or augmented mode, among other modes), the weld joint geometry, the orientation, the material thickness, the wire feed speed, and the voltage. Another embodiment may permit the operator to pick the weld joint, orientation and material thickness, and the welding application of the mobile device 12 may suggest the wire feed speed and the voltage. The operator may then be able to adjust settings off of a starting point or accept these parameters. Based on travel speed, angles and orientation detected by the sensor system 14, the mobile device 12 may be configured to simulate the weld. As skill improves, the simulated weld by the operator will be at the desired location in the joint and the right width due to travel speed, angle, and orientation.


In certain embodiments, the mobile device 12 may utilize sensor feedback from the sensor system 14 to determine parameters like travel speed, wire location with respect to the joint, torch angles and contact tip or torch to joint/work distance. The processor 16 of the mobile device 12 may execute instructions (e.g., software) to utilize sensor feedback to simulate and display the simulated weld. The software may be available for use with the mobile device 12 through various sources, including, but not limited to, a tangible non-transitory storage media (e.g., flash drive, optical disc, magnetic disc), a network, a website (e.g., a manufacturer website, www.Millerwelds.com), and so forth. In some embodiments, scores and results from simulated welds performed by one or more operators may also be stored (e.g., in the memory 18) or shared.


In particular, the sensor system 14 of the mobile device 12 may include various sensors that sense the movement, position, and/or orientation of the mobile device 12 (and, by extension, the welding torch 24 to which the mobile device 12 is coupled) relative to a reference point or a reference object. For example, the mobile device 12 may have one or more 3D gyroscopes for angle information, one or more 3D accelerometers, one or more proximity sensors, one or more magnetometers, one or more GPS receivers, one or more Bluetooth sensors, other wireless field sensors, or any combination thereof. The mobile device 12 may utilize one or more of these sensors to sense a change in speed of the mobile device 12 in a direction and/or an orientation. Feedback (e.g., signals) from the one or more sensors may be stored in the memory 18 of the mobile device 12 for subsequent retrieval and/or transmission to another mobile device, a computer system, or a network, or any combination thereof. The processor 16 of the mobile device 12 utilizes feedback from the one or more sensors in real-time to simulate and display the simulated welding application on the display 22. In some embodiments, the mobile device 12 may utilize one or more of these sensors exclusively. In certain embodiments, the sensor system 14 of the mobile device includes one or more cameras or optical sensors. In certain embodiments, these cameras or optical sensors may be utilized to identify components within the environment that guide the simulated or augmented welding application, as further described with respect to FIG. 3.


In certain embodiments, one or more 3D accelerometers of the sensor system 14 of the mobile device 12 may generate signals based at least in part on acceleration of the mobile device 12 (and thereby the acceleration of the welding torch 24 coupled to the mobile device 12). The signals generated by the 3D accelerometers may be in units of G (e.g., approximately 9.81 m/s2). The total acceleration of the mobile device 12 may be approximately equal to the gravitational acceleration (e.g., 1 G) plus the acceleration the user imparts to the mobile device 12. The mobile device 12 may separate the gravitational acceleration from user imparted acceleration utilizing signals from the one or more 3D gyroscopes that are from approximately the same time as the signals from the one or more 3D accelerometers.


Further, in certain embodiments, the sensor system 14 includes one or more 3D gyroscopes that may be utilized by the mobile device 12 to determine rotation of the mobile device 12 relative to one or more reference planes. In some embodiments, the one or more 3D gyroscopes may be utilized with the signals from the one or more 3D accelerometers to generate gyroscope enhanced motion data including, but not limited to, Euler angles of the mobile device 12 (e.g., pitch, roll, and yaw), attitude quaternion, rotation matrix, the gravitational component of 3D acceleration, a user acceleration component of 3D acceleration, or rotation rate, or any combination thereof. In some embodiments, the Euler angles of the mobile device 12 determined by the one or more 3D gyroscopes may be in units of radians or degrees.


Further, in certain embodiments, the sensor system 14 may include one or more global positioning system (GPS) receivers configured to report location data of the mobile device 12. Location data includes, but is not limited to, latitude and longitude, magnetic heading relative to magnetic north, true heading relative to true north, course and speed of movement, or altitude, or any combination thereof. As may be appreciated, latitude and longitude may be geographical coordinates using the World Geodetic System (WGS) 84 reference frame. Course data may represent the direction in which the mobile device 12 and/or the welding torch 14 are traveling in units of degrees. Course values are measured in degrees starting at due north and continuing clockwise around the compass. For example, north is 0 degrees, east is 90 degrees, south is 180 degrees, and west is 270 degrees. Speed data may represent the instantaneous speed of the mobile device 12 and/or the welding torch 14, such as in meters per second. This value represents the instantaneous speed of the mobile device 12 and/or the welding torch 14 in the direction of its current heading. The one or more magnetometers may provide compass direction for the mobile device 12 and/or the welding torch 14, such as in units of microteslas.


In certain embodiments, the display 22 may depict the simulated welding environment based on the sensor feedback received from the sensor system 14. For example, the display 22 may darken to display sparks, the arc, and a glowing weld deposit as a simulation of the weld as feedback of technique. A start switch or a trigger on the welding torch 24 or other device such as foot pedal or finger control may be in communication with the mobile device 12. Additionally, or in the alternative, the simulated welding application may be started by touching a start icon on the display 22. Accordingly, after the operator commences the simulated weld, the display 22 may darken to depict the simulated welding experience and environment, and the operator may move the display 22 of the mobile device 12 via the welding torch 24 and watch the simulated formation of the weld for the length of the simulated welding application.


In certain embodiments, instead of a simulated welding environment wherein the entirety of the simulated weld is generated by the simulated welding application, an augmented welding environment wherein live video of a live arc is augmented with other video and/or information may be displayed via the display 22 of the mobile device 12. In such embodiments, the display 22 may depict the augmented welding environment based on the sensor feedback received from the sensor system 14. For example, if an operator selects an augmented welding mode from the display 22, the mobile device 12 may be configured for an augmented reality simulation. As part of this augmented reality simulation, the mobile device 12 may receive and display a live video of a welding operator performing a real weld with a live arc. Further, based on the sensor feedback received from the sensor system 14, the mobile device 12 may integrate a virtual welding environment into the live video of the real welding application. In this manner, the display 22 may generally be transparent to enable the welding operator to view actual objects within the real welding environment; however, a virtual welding environment may be portrayed on portions of the display 22 to also enable the welding operator to view virtual objects superimposed on the actual (i.e., real world) objects captured in the live video. The virtual objects may be any number of figures, symbols, text, or images that may guide the welding operator during the actual welding process.


In certain embodiments, components of the weld training system 10 may be used by the operator (e.g., welding student, trainee, gamer, recruiter, trainer, etc.) to perform simulated or augmented welding operations that provide the user with a simulated or augmented welding like experience. For example, the weld training system 10 may include the welding torch 24 (either as a live-arc torch or dummy torch), a welding power supply 24 (that supplies the welding power during live-arc welding), a welding wire feeder 28 (that supplies welding wire during live-arc welding in certain embodiments), a gas supply 30 (that supplied shielding gas during live-arc welding in certain embodiments), or any combination thereof. It should be noted that in some embodiments, the weld training system 10 may include a gateway 32 to facilitate communication between various components of the weld training system 10. For example, the mobile device 12 may be in wireless communication with the gateway 32 of the weld training system 10, and the gateway 32 may receive and communicate information (e.g., sensor feedback information related to the simulated or augmented welding operation, the simulated or augmented welding parameters, the post-welding summary of the simulated or augmented welding task, etc.) to external components of the welding training system 10, such as a display 34 on a welding helmet 36 or an external display 38. In some embodiments, the welding training system 10 may be coupled via a wired or wireless (e.g., Bluetooth, Wi-Fi, etc.) connection to the welding helmet 36 and/or the external display 38, and may project feedback into the welding helmet 36. In certain embodiments, the external display 38 may be an augmented reality display, which may include optical projection systems, monitors, hand held devices, head-mounted displays, eyeglasses (e.g., glasses that are configured to augment a portion of a person's field of view), etc. Angles, coaching, voice, and other information may be useful for feedback when running the system with the welding helmet 36 on to more closely simulate welding without the helmet darkening.


Further, in certain embodiments, one or more weld training systems 10 may be coupled to a monitoring/analysis system 40. The monitoring/analysis system 40 may gather information from the one or more weld training systems 10, and the monitoring/analysis system 40 may be configured to work off-line or on a network 42 (e.g., Wi-Fi network). The network 42 may communicatively couple the monitoring/analysis system 40 to the cloud storage/services 44. The cloud storage/services 44 may contain information that provide feedback or aid to an instructor or operator performing a welding process. The weld training system 10 also may provide haptic vibration and/or audible feedback to the operator utilizing a database of information for proper technique, travel speed, and distance, among other training variables. The haptic vibration and/or audible feedback may be provided based at least in part on a history of one or more simulated or augmented welds performed by the operator. The cloud storage/services 44 may be coupled to a remote computer 46 that provides or retrieves information from or to the cloud 44.


It should be noted that while aspects of the present embodiments are generally described in the context of weld training systems, features of the present embodiments may be utilized in other types of welding systems, such as those described above.



FIG. 2 is an embodiment of the mobile device 12 coupled to a neck 50 of the welding torch 24 of FIG. 1, in accordance with aspects of the present disclosure. The mobile device 12 may be fixedly or removably mounted on the welding torch 24, such as on the neck 50 of the welding torch 24, via one or more mounting devices 52. It will be appreciated that while illustrated as being coupled to the neck 50 of the welding torch 24, in other embodiments, the one or more mounting devices 52 may be configured to be coupled to other places (e.g., a handle) of the welding torch 24. In the illustrated embodiment, the operator may move either the welding torch 24 or the mobile device 12 in order to engage both the welding torch 24 and the mobile device 12 for the simulated or augmented welding process. In particular, the display 22 of the mobile device 12 may be positioned on the neck 50 such that it generally guides the operator's eyes to look at the welding torch 24 in a desired manner while welding. In certain embodiments, the one or more mounting devices 52 may be moveable with respect to the welding torch 24 in order to allow the operator to slightly move, rotate, tilt, or adjust the position of the mobile device 12 for comfort or ease of operation. In addition, in certain embodiments, the one or more mounting devices 50 may be configured to be removably coupled to the welding torch 24 at their appropriate positions with respect to the welding torch 24 such that, for example, the one or more mounting devices 50 may be removed when the welding torch 24 is not being used for weld training.


As illustrated in FIG. 2, in certain embodiments, the mounting device 52 may include, or be directly coupled to, a shield 54 that is configured to hold the mobile device 22 in place with respect to the welding torch 24 while also protecting the mobile device 12 from welding materials (e.g., spatter) during an actual welding process. In certain embodiments, the shield 54 may be transparent, such that the mobile device 12 (and/or the operator) is not restricted in its field of view during operation. For example, the mobile device 12 may be able to gather information or data (e.g., via a camera that is disposed proximate the shield 54 when the mobile device 122 is held in place by the shield 54) through the transparent shield 54 during the simulated or augmented welding process. Further, the welding torch 24 may include a trigger 53. As described above, the start of the simulated or augmented weld may be initiated via the touch screen display 22 on the mobile device 12, or by depression of the trigger 53 of the welding torch 24, or a combination thereof. In some embodiments, additional triggers or switches may be disposed on the welding torch 24 or on a foot pedal. The triggers and/or switches may communicate via wired or wireless (e.g., Wi-Fi, Bluetooth) connections to initiate start. For example, the operator may engage the trigger 53 on the welding torch 24 to commence a simulated or augmented welding process. In certain embodiments, the mobile device 12 may sense the actuation or release of the trigger 53 through a wired connection through the mounting device 52.


In certain embodiments, the mobile device 12 includes a camera 56 (or other optical sensor) that may be a component of the sensor system 14. In certain embodiments, the camera 56 may be utilized to provide a live video of the actual live arc during an augmented welding process. For example, as noted above, in certain embodiments, the shield 54 may be transparent, and the camera 56 of the mobile device 12 may be configured to gather information or data through the transparent shield 54. Alternatively, or in addition to, in certain embodiments, the camera 56 may be configured to gather information or data through the one or more apertures disposed on the shield 54. In certain embodiments, the camera 56 may be utilized to detect one or more orientation devices 58 during a simulated welding process, as further described with respect to FIG. 3. Although the camera 56 illustrated in FIG. 2 appears to be on a side of the mobile device 12 opposite from an operational end of the welding torch 24 when held in place by the mounting device 52, it will be appreciated that the camera 56 of the mobile device 12 may be functional on both sides of the mobile device 12 such that the camera 56 is capable of collecting video and image data from the operational area around a workpiece (or an orientation device 58) during a live arc welding operation or a simulated or virtual welding operation.



FIG. 3 is an embodiment of the mobile device 12 coupled to the welding torch 24 of FIG. 1, where the mobile device 12 is utilized with an orientation device 58, in accordance with aspects of the present disclosure. The orientation device 58 may be a prefabricated two-dimensional or three-dimensional material having a series of identifiers 60 (e.g., various patterns of dots, lines, curves, grids, recesses, protrusions, geometric shapes, textures, raised surfaces, barcodes, QR codes, etc.). In certain embodiments, the orientation device 58 may be a separate token, a piece of paper, a sheet of plastic, a solid surface, a tag, or the like. The orientation device 58 may be utilized for a simulated welding process, and may be configured to orient the welding torch 24 and guide the operator performing the simulated weld. For example, the orientation device 58 may be a simulated work surface on which the operator may perform a simulated weld joint for a virtual or simulated welding application.


In some embodiments, the sensor system 14 of the mobile device 12 may utilize the camera 56 to detect the identifiers 60 on the orientation device 58. For example, the camera 56 may detect a series of patterns of identifiers 60 that aid the mobile device 12 in determining where the mobile device 12 is positioned relative to a starting point 62 on the orientation device 58, a travel speed of the mobile device 12 (and, by extension, the welding torch 24) relative to the orientation device 58, additional angle information of the mobile device 12 (and, by extension, the welding torch 24) relative to the orientation device 58, and distance of the mobile device 12 (and, by extension, the welding torch 24) to the orientation device 58 for the weld simulation. In some embodiments, the camera 56 may work exclusively without other sensors of the sensor system 14 to provide feedback to the mobile device 12. In other embodiments, the mobile device 12 may utilize the camera 56 and one or more of sensors including, but not limited to one or more 3D accelerometers, one or more proximity sensors, one or more magnetometers, one or more GPS receivers, one or more Bluetooth sensors, other wireless field sensors, or any combination thereof. For example, the camera 56 may determine a position and/or orientation of the mobile device 12 (and, by extension, the welding torch 24) relative to the orientation device 58, and the other sensors may be used to confirm and/or slightly adjust the determined position and/or orientation. In some embodiments, the mobile device 12 may sense (e.g., via a magnetometer) small magnets 64 disposed on the orientation device 58 to determine speed, direction, orientation, and other feedback parameters for the simulated welding process.


In particular, the camera 56 may detect the patterns of the identifiers 60 on the orientation device 58. The identifiers 60 may be unique (e.g., color, geometry, etc.) and disposed in various locations on the orientation device 58 to enable accurate position and/or orientation information for the system 10 (e.g., mobile device 12, welding torch 24, and so forth) relative to the orientation device 58. This unique pattern enables the mobile device 12 to determine parameters of the simulated weld, such as a travel distance, a weld width, a depth, one or more angles, or any combination thereof. The camera 56 may detect the identifiers 60, and may provide this information to the processor 16 of the mobile device 12. The processor 16 may be configured to extract information from the identifiers 60 that orient the welding torch 24 with respect to the simulated weld simulated on the orientation device 58. In turn, the orientation device 58 may guide the operator through the simulated weld. In certain embodiments, the operator may dynamically adjust one or more operating parameters of the simulated welding process based on the detected identifiers (i.e., based on the position or orientation of the welding torch 24 with respect to the simulated weld).


In some embodiments, the one or more sensors in the mobile device 12 are used to help ensure accuracy of the measurements determined via the camera 56. In other embodiments the camera 56 may be used without the identifiers 60 and/or the orientation device 58. That is, the camera 56 may determine the relative movement and/or the relative orientation of the mobile device 12 via utilizing one or more objects in the field of view of the camera 56 as orientation devices. In such situations, the orientation device 58 may not be needed.


In some embodiments, the mobile device 12 may be mounted to a welding torch 24 during an actual welding application to provide angle, position, travel speed, and other sensor information, which may be attributed to the welding torch 24. In other words, when mounted to the welding torch 24, the mobile device 12 may serve similar functionality as a retrofit kit for adding the camera 56, sensors, display 22, processor 16, memory 18, and storage 20 of the mobile device 12 to the welding torch 24, thereby enabling the welding torch 24 to function as a mobile weld training system 10. Further, in such situations, the mobile device 12 and the welding torch 24 may also be configured for an augmented welding application. In certain augmented welding applications, the mobile device 12 may be placed in various areas on the operators hand and/or welding torch 24 to provide feedback without blocking the actual welding process. The camera 56 may also use various filtering means to help track the weld and even display a live feed of the actual weld occurring.


In certain embodiments, the portable weld training system 10 can incorporate a competitive, gaming aspect to the simulated welding experience provided by the mobile device 12, and can provide a welding score to the user based on the received feedback. Further, the mobile device 12 may access the storage within the network 42 or cloud 44 to store and/or retrieve information for each welding operator, such as, for example, user identification information, historical weld information, and/or historical welding scores.



FIG. 4 is an embodiment of a screen 70 illustrating data corresponding to a simulated, augmented, or virtual reality welding environment, such as those generated by the weld training system 10, in accordance with aspects of the present disclosure. The screen 70 may be produced by the weld training software disposed on the mobile device 12, and may be displayed on the display 22, the external display 38, and/or the helmet 36. The screen 70 illustrates parameters that may be graphically displayed to a welding operator before, during, and/or after performing a simulated, augmented, or virtual reality welding operation. For example, the parameters may include a work angle 72, a travel angle 74, a contact tip to work piece distance 76 (e.g., CTWD 76), a welding torch travel speed 78, a proximity of the welding torch 24 in relation to a work piece 80, a welding voltage 82, a welding current 84, a welding torch orientation, a welding torch position, an aim of the welding torch 24, a video replay of the simulation, augmented, or virtual reality welding environment 86, and so forth.


As illustrated, graphically illustrated parameters may include an indication 88 of a current value of a parameter (e.g., while performing a weld training assignment). Furthermore, a graph 90 may show a history of the value of the parameter, and a score 92 may show an overall percentage that corresponds to how much time during the weld training assignment that the welding operator was within a range of acceptable values. As noted above, a video replay 86 of a weld training assignment may be provided on the screen 70. The video replay 86 may show live video of a welding operator performing the simulated or actual weld with either a simulated, augmented, or virtual reality environment superimposed thereon.


In some embodiments, a time 94 during a weld may be selected by a welding operator. By selecting the time 94, the welding operator may view the video replay 86 in conjunction with the welding parameters as they were at the selected time 94 in order to establish a correlation between the welding parameters and the video replay 86. The weld training software may be configured to recreate welding data based at least partly on welding parameter data, to synchronize the video replay 86 with the recreated welding data, and to provide the synchronized video replay 86 and recreated welding data to the display 22, the external display 38, and/or the helmet 36. Further, in some embodiments, a summary of the post-welding data and/or score may be displayed on a summary page 96 for each welding operator 98. It should be noted that in some situations, the screen 70 may display a comparison of total scores for each welding individual 98. Indeed, the weld training system may include or utilize any number of weld training features (e.g., a total welding score) or techniques (e.g., comparing weld training information) previously disclosed in U.S. Patent Application Publication No. 2014/0272837, entitled “MULTI-MODE SOFTWARE AND METHOD FOR A WELDING TRAINING SYSTEM,” filed Mar. 15, 2013, which is hereby incorporated by reference in its entirety for all purposes.


While only certain features of the present embodiments have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the present disclosure.

Claims
  • 1. A weld training system, comprising: a mobile device configured to be attached to a welding accessory using a mount, the mobile device comprising one or more sensors, wherein the mobile device is configured to: gather, via the one or more sensors of the mobile device, information indicative of dynamic position or orientation of the mobile device during a welding procedure; anddisplay, via a display of the mobile device, a welding environment based on the information.
  • 2. The weld training system of claim 1, further comprising a welding torch, the mobile device configured to be communicatively coupled to a welding torch.
  • 3. The weld training system of claim 2, wherein the welding torch is configured to perform a simulated welding procedure on a simulated weld joint on a simulated work surface, and wherein the mobile device is configured to display a simulated welding environment based at least in part on the information.
  • 4. The weld training system of claim 2, wherein the welding torch is configured to perform an actual welding procedure on an actual weld joint with a live arc, and wherein the mobile device is configured to display an augmented welding environment based at least in part on the information.
  • 5. The weld training system of claim 4, wherein the display of the augmented welding environment comprises a live video of actual objects used in the actual welding procedure with one or more virtual objects superimposed on the actual objects.
  • 6. The weld training system of claim 2, wherein the mobile device is configured to receive an indication of actuation or release of a trigger, and to perform a welding simulation in response to detecting the indication of actuation of the trigger.
  • 7. The weld training system of claim 2, wherein the welding torch is configured to perform a simulated welding procedure on a simulated weld joint on a simulated work surface, and wherein the mobile device is configured to display the welding environment as an augmented welding environment.
  • 8. The weld training system of claim 7, wherein the mobile device is configured to display the augmented welding environment as a live video of actual objects used in the actual welding procedure with one or more virtual objects superimposed on the actual objects, the one or more virtual objects comprising at least one of the simulated weld joint or the simulated work surface.
  • 9. The weld training system of claim 1, wherein the weld training system is configured to provide at least one of haptic vibration or audio feedback.
  • 10. The weld training system of claim 1, wherein the one or more sensors comprise a camera.
  • 11. The weld training system of claim 10, wherein the camera is configured to detect an orientation device, the mobile device configured to determine the information based on an image of the orientation device captured by the camera.
  • 12. The weld training system of claim 10, wherein the one or more sensors further include at least one of an accelerometer, a gyroscope, a proximity sensor, a magnetometer, a GPS receiver, or an electromagnetic field sensor, the mobile device configured to determine the information based on a combination of an image captured by the camera and the at least one of the accelerometer, the gyroscope, the proximity sensor, the magnetometer, the GPS receiver, or the electromagnetic field sensor.
  • 13. The weld training system of claim 1, wherein the mobile device is configured to display the simulated welding environment by displaying an entirety of a simulated weld generated by a simulated welding application, including the simulated weld joint, a simulated work surface, and live video of actual objects used in the actual welding procedure with one or more virtual objects superimposed on the actual objects, the one or more virtual objects comprising at least one of the simulated weld joint or the simulated work surface.
  • 14. The weld training system of claim 1, wherein the mobile device is configured to determine an operating parameter based on the information, the operating parameter comprising at least one of: a work angle of a welding torch, a travel angle of the welding torch, a travel speed of the welding torch, a contact tip to work piece distance, a proximity of the welding torch to a weld joint, a welding voltage, a welding current, an orientation of the welding torch, or a position of the welding torch.
  • 15. The weld training system of claim 1, further comprising an orientation device comprising an identifier, wherein a sensor of the mobile device is configured to detect the identifier.
  • 16. The weld training system of claim 15, wherein the mobile device is configured to determine a first position of the mobile device based at least on the detection of the identifier, and wherein the mobile device is configured to determine a second position of the welding torch relative to the orientation device based at least in part on the determined first position of the mobile device and the mounted position.
  • 17. The weld training system of claim 15, wherein the identifier comprises at least one of patterns, dots, lines, curves, grids, recesses, protrusions, geometric shapes, textures, raised surfaces, barcodes, or QR codes.
  • 18. The weld training system of claim 1, wherein the mobile device is configured to implement a gaming application based on the information and the welding procedure.
  • 19. The weld training system of claim 1, wherein the mobile device comprises a storage device and is configured to store at least one of user identification information based on the information, historical weld information based on the information, or historical welding scores based on the information.
  • 20. The weld training system of claim 1, wherein the mobile device is configured to transmit the information to an external device.
  • 21. The weld training system of claim 20, wherein the external device is a device selected from the group consisting of: an external display, a remote computing system, or cloud storage or processing.
  • 22. The weld training system of claim 1, wherein the mobile device is configured to display the welding environment as an augmented welding environment including a live video of actual objects used in the actual welding procedure with one or more virtual objects superimposed on the actual objects, the one or more virtual objects comprising at least one of the simulated weld joint or the simulated work surface.
RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 14/554,693, entitled “SYSTEMS AND METHODS FOR A WELD TRAINING SYSTEM,” and claims priority from and the benefit of U.S. Provisional Patent Application Ser. No. 61/911,321, entitled “TRAINING SYSTEM USING A PORTABLE SMART DEVICE,” filed Dec. 3, 2013. The entireties of U.S. patent application Ser. No. 14/554,693, and U.S. Provisional Patent Application Ser. No. 61/911,321 are incorporated herein by reference.

US Referenced Citations (513)
Number Name Date Kind
1340270 Emil May 1920 A
2045800 Walther Jun 1936 A
2045801 Richter Jun 1936 A
2045802 Walther Jun 1936 A
2333192 Moberg Oct 1942 A
2351910 Blankenbuehler Jun 1944 A
3391691 Young Jul 1968 A
3679865 Jesnitzer Jul 1972 A
3867769 Schow Feb 1975 A
4028522 Chihoski Jun 1977 A
4041615 Whitehill Aug 1977 A
4044377 Bowerman Aug 1977 A
4124944 Blair Nov 1978 A
4132014 Schow Jan 1979 A
4144766 Wehrmeister Mar 1979 A
4224501 Lindbom Sep 1980 A
4253648 Meeks Mar 1981 A
4294440 Severt Oct 1981 A
4375026 Kearney Feb 1983 A
4375165 deSterke Mar 1983 A
4389561 Weman Jun 1983 A
4396945 DiMatteo Aug 1983 A
4412121 Kremers Oct 1983 A
4452589 Denison Jun 1984 A
4459114 Barwick Jul 1984 A
4471207 Hawkes Sep 1984 A
4484059 Lillquist Nov 1984 A
4485683 Bertil Dec 1984 A
4518361 Conway May 1985 A
4541055 Wolfe Sep 1985 A
4555614 Morris Nov 1985 A
4557191 Speicher Dec 1985 A
4577499 Silke Mar 1986 A
4590356 Povlick May 1986 A
4591689 Brown May 1986 A
4594497 Takahashi Jun 1986 A
4595186 Reed Jun 1986 A
4595368 Cole Jun 1986 A
4595820 Richardson Jun 1986 A
4609806 Grabkowski Sep 1986 A
4628176 Kojima Dec 1986 A
4638146 Koyama Jan 1987 A
4641292 Tunnell Feb 1987 A
4677277 Cook Jun 1987 A
4680014 Paton Jul 1987 A
4689021 Vasiliev Aug 1987 A
4716273 Paton Dec 1987 A
4721947 Brown Jan 1988 A
4728768 Cueman Mar 1988 A
4739404 Richardson Apr 1988 A
4767109 Raketich Aug 1988 A
4820901 Peviani Apr 1989 A
4829365 Eichenlaub May 1989 A
4830261 Mello May 1989 A
4867685 Brush Sep 1989 A
4868649 Gaudin Sep 1989 A
4877940 Bangs Oct 1989 A
4881678 Gaudin Nov 1989 A
4920249 McLaughlin Apr 1990 A
4931018 Herbst Jun 1990 A
4937427 McVicker Jun 1990 A
4943702 Richardson Jul 1990 A
4954690 Kensrue Sep 1990 A
4992881 Tomasek Feb 1991 A
4996409 Paton Feb 1991 A
5061841 Richardson Oct 1991 A
5103376 Blonder Apr 1992 A
5185561 Good Feb 1993 A
5208436 Blankenship May 1993 A
5211564 Martinez Aug 1993 A
5231928 Phillips Aug 1993 A
5243265 Matsuura Sep 1993 A
5281921 Novak Jan 1994 A
5283418 Bellows Feb 1994 A
5302799 Kennedy Apr 1994 A
5304774 Durheim Apr 1994 A
5306893 Morris Apr 1994 A
5320538 Baum Jun 1994 A
5343011 Fujii Aug 1994 A
5380978 Pryor Jan 1995 A
5397872 Baker Mar 1995 A
5404181 Hung Apr 1995 A
5426732 Boies Jun 1995 A
5430643 Seraji Jul 1995 A
5448405 Clausen Sep 1995 A
5464957 Kidwell Nov 1995 A
5508757 Chen Apr 1996 A
5514846 Cecil May 1996 A
5517420 Kinsman May 1996 A
5521843 Hashima May 1996 A
5533146 Iwai Jul 1996 A
5543863 Lin Aug 1996 A
5546476 Mitaka Aug 1996 A
5571431 Lantieri Nov 1996 A
5592241 Kita Jan 1997 A
5617335 Hashima Apr 1997 A
5626672 Rossetti May 1997 A
5659479 Duley Aug 1997 A
5668612 Hung Sep 1997 A
5674415 Leong Oct 1997 A
5675229 Thorne Oct 1997 A
5681490 Chang Oct 1997 A
5708253 Bloch Jan 1998 A
5709219 Chen Jan 1998 A
5747042 Choquet May 1998 A
5823785 Matherne, Jr. Oct 1998 A
5832139 Batterman Nov 1998 A
5845053 Watanabe Dec 1998 A
5856844 Batterman Jan 1999 A
5930093 Morrissett Jul 1999 A
5961859 Chou Oct 1999 A
5973677 Gibbons Oct 1999 A
5999909 Rakshit Dec 1999 A
6003052 Yamagata Dec 1999 A
6018729 Zacharia Jan 2000 A
6019359 Fly Feb 2000 A
6024273 Ludewig Feb 2000 A
6033226 Bullen Mar 2000 A
6039494 Pearce Mar 2000 A
6046431 Beattie Apr 2000 A
6046754 Stanek Apr 2000 A
6049059 Kim Apr 2000 A
6051805 Vaidya Apr 2000 A
6101455 Davis Aug 2000 A
6107601 Shimagama Aug 2000 A
6115025 Buxton Sep 2000 A
6130407 Villafuerte Oct 2000 A
6136946 Yao Oct 2000 A
6153848 Nagae Nov 2000 A
6155475 Ekelof Dec 2000 A
6163946 Pryor Dec 2000 A
6226395 Gilliland May 2001 B1
6236017 Smartt May 2001 B1
6242711 Cooper Jun 2001 B1
6271500 Hirayama Aug 2001 B1
6288359 Koch Sep 2001 B1
6290740 Schaefer Sep 2001 B1
6301763 Pryor Oct 2001 B1
6315186 Friedl Nov 2001 B1
6329635 Leong Dec 2001 B1
6337458 Lepeltier Jan 2002 B1
6371765 Wall Apr 2002 B1
6417894 Goff Jul 2002 B1
6441342 Hsu Aug 2002 B1
6445964 White Sep 2002 B1
6469752 Ishikawa Oct 2002 B1
6476354 Jank Nov 2002 B1
6479793 Wittmann Nov 2002 B1
6506997 Matsuyama Jan 2003 B2
6516300 Rakshit Feb 2003 B1
6572379 Sears Jun 2003 B1
6583386 Ivkovich Jun 2003 B1
6596972 Di Novo Jul 2003 B1
6614002 Weber Sep 2003 B2
6621049 Suzuki Sep 2003 B2
6622906 Kushibe Sep 2003 B1
6647288 Madill Nov 2003 B2
6670574 Bates Dec 2003 B1
6697761 Akatsuka Feb 2004 B2
6703585 Suzuki Mar 2004 B2
6710298 Eriksson Mar 2004 B2
6728582 Wallack Apr 2004 B1
6734393 Friedl May 2004 B1
6744011 Hu Jun 2004 B1
6748249 Eromaki Jun 2004 B1
6750428 Okamoto Jun 2004 B2
6753909 Westerman Jun 2004 B1
6768974 Nanjundan Jul 2004 B1
6795068 Marks Sep 2004 B1
6839049 Koizumi Jan 2005 B1
6857553 Hartman Feb 2005 B1
6868726 Lemkin Mar 2005 B2
6910971 Alsenz Jun 2005 B2
6927360 Artelsmair Aug 2005 B2
6937329 Esmiller Aug 2005 B2
6967635 Hung Nov 2005 B2
6977357 Hsu Dec 2005 B2
6995536 Challoner Feb 2006 B2
7015419 Hackl Mar 2006 B2
7025053 Altamirano Apr 2006 B1
7032814 Blankenship Apr 2006 B2
7045742 Feichtinger May 2006 B2
7081888 Cok Jul 2006 B2
7120473 Hawkins Oct 2006 B1
7132617 Lee Nov 2006 B2
7132623 DeMiranda Nov 2006 B2
7150047 Fergason Dec 2006 B2
7173215 Kapoor Feb 2007 B1
7181413 Hadden Feb 2007 B2
7226176 Huang Jun 2007 B1
7261261 Ligertwood Aug 2007 B2
7342210 Fergason Mar 2008 B2
7358458 Daniel Apr 2008 B2
7465230 LeMay Dec 2008 B2
7474760 Hertzman Jan 2009 B2
7523069 Friedl Apr 2009 B1
7564005 Cabanaw Jul 2009 B2
7574172 Clark Aug 2009 B2
7577285 Schwarz Aug 2009 B2
D614217 Peters Apr 2010 S
7698094 Aratani Apr 2010 B2
D615573 Peters May 2010 S
7766213 Henrikson Aug 2010 B2
7789811 Cooper Sep 2010 B2
7813830 Summers Oct 2010 B2
7826984 Sjostrand Nov 2010 B2
7831098 Melikian Nov 2010 B2
7839416 Ebensberger Nov 2010 B2
7845560 Emanuel Dec 2010 B2
D631074 Peters Jan 2011 S
7899618 Ledet Mar 2011 B2
7962967 Becker Jun 2011 B2
8019144 Sugihara Sep 2011 B2
8044942 Leonhard Oct 2011 B1
8046178 Dai Oct 2011 B2
8100694 Portoghese Jan 2012 B2
8110774 Huonker Feb 2012 B2
8235588 Louban Aug 2012 B2
8248324 Nangle Aug 2012 B2
8274013 Wallace Sep 2012 B2
8393519 Allehaux Mar 2013 B2
8406682 Elesseily Mar 2013 B2
8431862 Kachline Apr 2013 B2
8432476 Ashforth Apr 2013 B2
8478382 Burnside Jul 2013 B2
8502866 Becker Aug 2013 B2
8512043 Choquet Aug 2013 B2
8541746 Andres Sep 2013 B2
8657605 Wallace Feb 2014 B2
8681178 Tseng Mar 2014 B1
8686318 Albrecht et al. Apr 2014 B2
8692157 Daniel Apr 2014 B2
8698843 Tseng Apr 2014 B2
8747116 Zboray Jun 2014 B2
8777629 Kreindl Jul 2014 B2
8803908 Van Osten Aug 2014 B2
8834168 Peters Sep 2014 B2
8851896 Wallace Oct 2014 B2
8860760 Chen Oct 2014 B2
8911237 Postlethwaite Dec 2014 B2
8915740 Zboray Dec 2014 B2
8946595 Ishida Feb 2015 B2
8953033 Yamane Feb 2015 B2
8953909 Guckenberger Feb 2015 B2
RE45398 Wallace Mar 2015 E
8987628 Daniel Mar 2015 B2
8990842 Rowley Mar 2015 B2
8992226 Leach Mar 2015 B1
9011154 Kindig Apr 2015 B2
9012802 Daniel Apr 2015 B2
9050678 Daniel Jun 2015 B2
9050679 Daniel Jun 2015 B2
9089921 Daniel Jul 2015 B2
9101994 Albrecht Aug 2015 B2
9196169 Wallace Nov 2015 B2
9218745 Choquet Dec 2015 B2
9230449 Conrardy Jan 2016 B2
9269279 Penrod Feb 2016 B2
9293056 Zboray Mar 2016 B2
9293057 Zboray Mar 2016 B2
9318026 Peters Apr 2016 B2
9330575 Peters May 2016 B2
9336686 Peters May 2016 B2
9402122 Richardson Jul 2016 B2
9573215 Pfeifer Feb 2017 B2
9685099 Boulware Jun 2017 B2
9724787 Becker Aug 2017 B2
9789603 Jacobsen Oct 2017 B2
10427239 Becker Oct 2019 B2
20010026445 Naghi Oct 2001 A1
20010032508 Lemkin Oct 2001 A1
20020043607 Tajima Apr 2002 A1
20020071550 Pletikosa Jun 2002 A1
20020105797 Navid Aug 2002 A1
20020114653 Gatta Aug 2002 A1
20020148745 Chang Oct 2002 A1
20020153354 Norby Oct 2002 A1
20030011673 Eriksson Jan 2003 A1
20030092496 Alsenz May 2003 A1
20030172032 Choquet Sep 2003 A1
20040058703 Eromaki Mar 2004 A1
20040068335 Ferla Apr 2004 A1
20040069754 Bates Apr 2004 A1
20040099648 Hu May 2004 A1
20040175684 Kaasa Sep 2004 A1
20040223148 Takemura Nov 2004 A1
20040227730 Sugihara Nov 2004 A1
20040251910 Smith Dec 2004 A1
20050006363 Hsu Jan 2005 A1
20050012598 Berquist Jan 2005 A1
20050016979 Stein Jan 2005 A1
20050017152 Fergason Jan 2005 A1
20050073506 Durso Apr 2005 A1
20050127052 Spencer Jun 2005 A1
20050133488 Blankenship Jun 2005 A1
20050135682 Abrams Jun 2005 A1
20050179654 Hawkins Aug 2005 A1
20050197115 Clark et al. Sep 2005 A1
20050207102 Russo Sep 2005 A1
20050219206 Schena Oct 2005 A1
20050227635 Hawkins Oct 2005 A1
20050256611 Pretlove Nov 2005 A1
20060010551 Bishop Jan 2006 A1
20060081740 Bellavance Apr 2006 A1
20060136183 Choquet Jun 2006 A1
20060151446 Schneider Jul 2006 A1
20060163228 Daniel Jul 2006 A1
20060173619 Brant Aug 2006 A1
20060212169 Luthardt Sep 2006 A1
20060241432 Herline Oct 2006 A1
20070038400 Lee Feb 2007 A1
20070051711 Kachline Mar 2007 A1
20070056942 Daniel et al. Mar 2007 A1
20070114215 Bill May 2007 A1
20070115202 Kiesenhofer May 2007 A1
20070164006 Burgstaller Jul 2007 A1
20070187378 Karakas Aug 2007 A1
20070188606 Atkinson Aug 2007 A1
20070209586 Ebensberger Sep 2007 A1
20070221636 Monzyk Sep 2007 A1
20070247793 Carnevali Oct 2007 A1
20070248261 Zhou Oct 2007 A1
20070264620 Maddix Nov 2007 A1
20070278196 James Dec 2007 A1
20070291166 Misawa Dec 2007 A1
20080004633 Arata Jan 2008 A1
20080030631 Gallagher Feb 2008 A1
20080038702 Choquet Feb 2008 A1
20080061113 Seki Mar 2008 A9
20080077422 Dooley Mar 2008 A1
20080124698 Ebensberger May 2008 A1
20080128395 Aigner Jun 2008 A1
20080128400 Michels Jun 2008 A1
20080149602 Lenzner Jun 2008 A1
20080149608 Albrecht Jun 2008 A1
20080158502 Becker Jul 2008 A1
20080168290 Jobs Jul 2008 A1
20080169277 Achtner Jul 2008 A1
20080234960 Byington Sep 2008 A1
20080314887 Stoger Dec 2008 A1
20090005728 Weinert Jan 2009 A1
20090057285 Bashore Mar 2009 A1
20090057286 Ihara Mar 2009 A1
20090109128 Nangle Apr 2009 A1
20090146359 Canfield Jun 2009 A1
20090152251 Dantinne Jun 2009 A1
20090161212 Gough Jun 2009 A1
20090173726 Davidson Jul 2009 A1
20090189974 Deering Jul 2009 A1
20090190826 Tate Jul 2009 A1
20090200281 Hampton Aug 2009 A1
20090200282 Hampton Aug 2009 A1
20090230107 Ertmer Sep 2009 A1
20090231423 Becker Sep 2009 A1
20090236325 Gozalbo Sep 2009 A1
20090249606 Diez Oct 2009 A1
20090283021 Wong Nov 2009 A1
20090298024 Batzler Dec 2009 A1
20090313549 Casner et al. Dec 2009 A1
20090323121 Valkenburg Dec 2009 A1
20100020483 Ma Jan 2010 A1
20100048273 Wallace Feb 2010 A1
20100062405 Zboray Mar 2010 A1
20100062406 Zboray Mar 2010 A1
20100088793 Ghisleni Apr 2010 A1
20100123664 Shin May 2010 A1
20100133247 Mazumder Jun 2010 A1
20100145520 Gerio Jun 2010 A1
20100167249 Donncha Jul 2010 A1
20100201803 Melikian Aug 2010 A1
20100207620 Gies Aug 2010 A1
20100224610 Wallace Sep 2010 A1
20100238119 Dubrovsky Sep 2010 A1
20100245273 Hwang Sep 2010 A1
20100283588 Gomez Nov 2010 A1
20100291313 Ling Nov 2010 A1
20100314362 Albrecht Dec 2010 A1
20110000892 Mueller Jan 2011 A1
20110006047 Penrod Jan 2011 A1
20110091846 Kreindl Apr 2011 A1
20110092828 Spohn Apr 2011 A1
20110114615 Daniel May 2011 A1
20110117527 Conrardy May 2011 A1
20110176720 VanOsten Jul 2011 A1
20110183304 Wallace Jul 2011 A1
20110198329 Davidson Aug 2011 A1
20110220616 Mehn Sep 2011 A1
20110220619 Mehn Sep 2011 A1
20110240605 Takayama Oct 2011 A1
20110249090 Moore Oct 2011 A1
20110284508 Miura Nov 2011 A1
20110285290 Griffin Nov 2011 A1
20110286005 Yamamoto Nov 2011 A1
20110290765 Albrecht Dec 2011 A1
20110311297 Giuliano Dec 2011 A1
20110313731 Vock Dec 2011 A1
20120007748 Forgues Jan 2012 A1
20120037600 Katoh Feb 2012 A1
20120048838 Ishida Mar 2012 A1
20120072021 Walser Mar 2012 A1
20120077174 DePaul Mar 2012 A1
20120105476 Tseng May 2012 A1
20120113512 Tsanev May 2012 A1
20120122062 Yang May 2012 A1
20120175834 Hamm Jul 2012 A1
20120180180 Steve Jul 2012 A1
20120188365 Stork Jul 2012 A1
20120189993 Kindig Jul 2012 A1
20120205359 Daniel Aug 2012 A1
20120231894 Nicora Sep 2012 A1
20120248080 Hutchison Oct 2012 A1
20120248083 Garvey Oct 2012 A1
20120291172 Wills Nov 2012 A1
20120298640 Conrardy Nov 2012 A1
20120323496 Burroughs Dec 2012 A1
20130040270 Albrecht Feb 2013 A1
20130064427 Picard et al. Mar 2013 A1
20130081293 Delin Apr 2013 A1
20130119037 Daniel May 2013 A1
20130178952 Wersborg Jul 2013 A1
20130182070 Peters Jul 2013 A1
20130183645 Wallace Jul 2013 A1
20130189656 Zboray Jul 2013 A1
20130189657 Wallace Jul 2013 A1
20130189658 Peters Jul 2013 A1
20130200882 Almalki Aug 2013 A1
20130203029 Choquet Aug 2013 A1
20130206740 Pfeifer Aug 2013 A1
20130206741 Pfeifer Aug 2013 A1
20130209976 Postlethwaite Aug 2013 A1
20130230832 Peters Sep 2013 A1
20130237336 Cottam Sep 2013 A1
20130252214 Choquet Sep 2013 A1
20130256289 Knoener Oct 2013 A1
20130262000 Hutchison Oct 2013 A1
20130264315 Hung Oct 2013 A1
20130264322 Bornemann Oct 2013 A1
20130265416 Enyedy Oct 2013 A1
20130288211 Patterson Oct 2013 A1
20130326842 Pearson Dec 2013 A1
20140008088 Chellew Jan 2014 A1
20140017642 Postlethwaite Jan 2014 A1
20140042135 Daniel Feb 2014 A1
20140042137 Daniel Feb 2014 A1
20140069899 Mehn Mar 2014 A1
20140131337 Williams May 2014 A1
20140134579 Becker May 2014 A1
20140134580 Becker May 2014 A1
20140166631 Rozmarynowski Jun 2014 A1
20140184496 Gribetz Jul 2014 A1
20140220522 Peters Aug 2014 A1
20140234813 Peters Aug 2014 A1
20140263224 Becker Sep 2014 A1
20140263227 Daniel Sep 2014 A1
20140267773 Jeung Sep 2014 A1
20140272835 Becker Sep 2014 A1
20140272836 Becker Sep 2014 A1
20140272837 Becker Sep 2014 A1
20140272838 Becker Sep 2014 A1
20140315167 Kreindl Oct 2014 A1
20140322684 Wallace Oct 2014 A1
20140346158 Matthews Nov 2014 A1
20140346163 Rajagopalan Nov 2014 A1
20140346793 DeStories Nov 2014 A1
20140374396 Luo Dec 2014 A1
20150056584 Boulware Feb 2015 A1
20150056585 Boulware Feb 2015 A1
20150072323 Postlethwaite Mar 2015 A1
20150122781 Albrecht May 2015 A1
20150154884 Salsich Jun 2015 A1
20150170539 Barrera Jun 2015 A1
20150190875 Becker Jul 2015 A1
20150190876 Becker Jul 2015 A1
20150190887 Becker Jul 2015 A1
20150190888 Becker Jul 2015 A1
20150194072 Becker Jul 2015 A1
20150194073 Becker Jul 2015 A1
20150209887 DeLisio Jul 2015 A1
20150235565 Postlethwaite Aug 2015 A1
20150248845 Postlethwaite Sep 2015 A1
20150325153 Albrecht Nov 2015 A1
20150328710 Kachline Nov 2015 A1
20150352653 Albrecht Dec 2015 A1
20150375323 Becker Dec 2015 A1
20150375324 Becker Dec 2015 A1
20150375327 Becker Dec 2015 A1
20150379894 Becker Dec 2015 A1
20160039034 Becker Feb 2016 A1
20160039053 Becker Feb 2016 A1
20160049085 Beeson Feb 2016 A1
20160093233 Boulware Mar 2016 A1
20160125592 Becker May 2016 A1
20160125593 Becker May 2016 A1
20160125594 Becker May 2016 A1
20160125653 Denis May 2016 A1
20160125761 Becker May 2016 A1
20160125762 Becker May 2016 A1
20160125763 Becker May 2016 A1
20160125764 Becker May 2016 A1
20160203734 Boulware Jul 2016 A1
20160203735 Boulware Jul 2016 A1
20160236303 Matthews Aug 2016 A1
20160260261 Hsu Sep 2016 A1
20160267806 Hsu Sep 2016 A1
20160288236 Becker Oct 2016 A1
20160358503 Batzler Dec 2016 A1
20170046974 Becker Feb 2017 A1
20170046975 Becker Feb 2017 A1
20170046976 Becker Feb 2017 A1
20170046977 Becker Feb 2017 A1
20170148352 Becker May 2017 A1
20170165776 Becker Jun 2017 A1
20170169729 Becker Jun 2017 A1
Foreign Referenced Citations (94)
Number Date Country
2311685 Dec 2001 CA
2517874 Dec 2001 CA
2549553 Jul 2004 CA
2554498 Apr 2006 CA
1264822 Aug 2000 CN
100371672 Dec 2004 CN
1841321 Oct 2006 CN
1866317 Nov 2006 CN
1909020 Feb 2007 CN
101218060 Jul 2008 CN
201181527 Jan 2009 CN
101502906 Aug 2009 CN
101770710 Jul 2010 CN
102049595 May 2011 CN
102083580 Jun 2011 CN
102165504 Aug 2011 CN
102165505 Aug 2011 CN
102298858 Dec 2011 CN
202200202 Apr 2012 CN
102441737 May 2012 CN
103035135 Apr 2013 CN
103038804 Apr 2013 CN
202877704 Apr 2013 CN
103071909 May 2013 CN
103143810 Jun 2013 CN
103349558 Oct 2013 CN
103350268 Oct 2013 CN
103392089 Nov 2013 CN
203276641 Nov 2013 CN
103831553 Jun 2014 CN
203778997 Aug 2014 CN
202010011064 Oct 2010 DE
102010038902 Feb 2012 DE
0323277 Jul 1989 EP
0878263 Nov 1998 EP
0963744 Dec 1999 EP
1029306 Aug 2000 EP
1295195 Jun 2001 EP
1573699 Sep 2005 EP
1797545 Jun 2007 EP
1864744 Dec 2007 EP
2022592 Feb 2009 EP
2415560 Feb 2014 EP
3192481 Jul 2017 EP
2438440 Jan 2014 ES
1456780 Jul 1966 FR
2827066 Jan 2003 FR
2454232 May 2009 GB
H11146387 May 1999 JP
2000298427 Oct 2000 JP
2002317557 Oct 2002 JP
2004181493 Jul 2004 JP
2007021542 Feb 2007 JP
2009125790 Jun 2009 JP
100876425 Dec 2008 KR
20110000152 Jan 2011 KR
846203 Jul 1981 SU
972552 Nov 1982 SU
1324050 Jul 1987 SU
1354234 Nov 1987 SU
1489933 Jun 1989 SU
1638145 Mar 1991 SU
9958286 Nov 1999 WO
03019349 Jan 2003 WO
2004057554 Jul 2004 WO
2005102230 Nov 2005 WO
2005110658 Nov 2005 WO
2006004427 Jan 2006 WO
2006034571 Apr 2006 WO
2007009131 Jan 2007 WO
2007044135 Apr 2007 WO
2008076777 Jun 2008 WO
2009022443 Feb 2009 WO
2009053829 Apr 2009 WO
2009060231 May 2009 WO
2009092944 Jul 2009 WO
2009146359 Dec 2009 WO
2010000003 Jan 2010 WO
2010020867 Feb 2010 WO
2010020869 Feb 2010 WO
2010020870 Feb 2010 WO
2010111722 Oct 2010 WO
2011112493 Sep 2011 WO
2011150165 Dec 2011 WO
2012036710 Mar 2012 WO
2012137060 Oct 2012 WO
2013023012 Feb 2013 WO
2013061518 May 2013 WO
2013138831 Sep 2013 WO
2013186413 Dec 2013 WO
2014007830 Jan 2014 WO
2014074296 May 2014 WO
2014074297 May 2014 WO
2014140719 Sep 2014 WO
Non-Patent Literature Citations (134)
Entry
Welding Accessories. Global Specs <retrieved: https://web.archive.org/web/20100809231402/https://www.globalspec.com/learnmore/manufacturing_process_equipment/welding_equipment_supplies/welding_accessories> (Year: 2010).
“Low Cost Virtual Reality Welding Training System,” NSRP Joint Panel Meeting, Apr. 21, 2010, http://www.nsrp.org/6-Presentations/Joint/042110_Low_Cost_Virtual_Reality_Welder_Training_System_Fast.pdf.
“NJC Technology Displayed at ShipTech 2005”, Welding Journal, vol. 84, No. 3, Mar. 2005, p. 54, https://app.aws.org/w/r/www/wj/2005/03/M1_2005_03.pdf.
“Sheet Metal Conference XXII,” Conference Program, American Welding Society, May 2006, Detroit.
“Virtual Reality Program to Train Welders for Shipbuilding”, American Welding Society, Navy Joining Center, https://app.aws.org/wj/2004/04/052/.
“Virtual Reality Welder Training Initiatives: Virtual Welding Lab Pilot,” Paul D. Camp Community College, Advanced Science & Automation Corporation, Northrop Grumman Newport News, Nov. 22, 2006, http://www.nsrp.org/6-Presentations/WD/103106_Virtual_Reality_Welder.pdf.
“Virtual Welding—A Low Cost Virtual Reality Welder Training System”, Interim Status Report # 4, Technology Investment Agreement 2008-600, Feb. 18, 2009, http://www.nsrp.org/3-Key_Deliverables/FY08_Low-Cost_Virtual_Reality_Welder_Trainer/ FY08_Low-Cost_Virtual_Reality_Welder_Trainer-Interim2.pdf.
“Virtual Welding: A Low Cost Virtual Reality Welder Training System,” NSRP ASE, Feb. 19, 2009, http://www.nsrp.org/6-Presentations/WD/020409_Virtual_Welding_Wilbur.pdf.
“Vision for Welding Industry,” American Welding Society, Apr. 22, 1999, http://www.aws.org/library/doclib/vision.pdf.
“Welding in Defense Industry,” American Welding Society conference schedule, 2004. https://app.aws.org/conferences/defense/live_index.html.
“Welding Technology Roadmap,” prepared by Energetics, Inc., Columbia, MD, in cooperation with The American Welding Society and the Edison Welding Institute, Sep. 2000.
123arc.com—“Weld into the future”; 2000.
Advance Program of American Welding Society Programs and Events, Nov. 11-14, 2007, Chicago.
Aiteanu, Dorin, and Axel Graser, “Computer-Aided Manual Welding Using an Augmented Reality Supervisor,” Sheet Metal Welding Conference XII, Livoinia, MI, May 9-12, 2006, pp. 1-14.
Aiteanu, Dorin, et al., “A Step Forward in Manual Welding: Demonstration of Augmented Reality Helmet,” Institute of Automation, University of Bremen, Germany, 2003.
Aiteanu et al., Generation and Rendering of a Virtual Welding Seam in an Augmented Reality Training Envionment, Proceedings of the Sixth IASTED International Conference Visualization, Imaging, and Image Proceeding, Aug. 28-30, 2006, Palma de Mallorca, Spain ISBN Hardcapy: 0-88986-598-1 /CD: 0-88986-600-7 (8 pages).
American Welding Society Forms: typical Procedure Qualification Record and Welding Procedure Specification forms.
American Welding Society's Virtual Welding Trailer to Debut at FABTECH Careers in Welding Trailer Appeals to New Generation of Welders, Miami, Florida, Nov. 3, 2011.
ArcSentry Weld Monitoring System, Version 3, Users Manual, Native American Technologies, Golden, CO, Dec. 10, 1999.
Arvika Forum Vorstellung Projeckt PAARA, BMW Group Virtual Reality Center, Nuernberg, 2003.
Ascension Technology Corporation: Tracking 3D Worlds: http://ascension-tech.com/, Dec. 1996.
Barckhoff, J.R.; “Total Welding Managemet,” American Welding Society, 2005.
Bender Shipbuilding and Repair, Co., “Virtual Welding—A Low Cost Virtual Reality Welder Training System”, Technical Proposal, Jan. 23, 2008.
Byrd, Alex Preston, “Identifying the effects of human factors and training methods on a weld training program” (2014). Graduate Theses and Dissertations. Paper 13991.
Central Welding Supply http://www.welders-direct.com/ Feb. 29, 2000.
Choquet, Claude, ARC+ & ARC PC Welding Simulators: Teach Welders with Virtual Interactive 3D Technologies; Jul. 2010.
Choquet, Claude, ARC+: Today's Virtual Reality Solution for Welders, Jun. 1, 2008.
Cybernetics: Enhancing Human Performance found in the DTIC Review dated Mar. 2001, p. 186/19. See http://www.dtic.mil/dtic/tr/fulltext/u2/a385219.pdf.
Echtler, Florian, Fabian Stuurm, Kay Kindermann, Gudrun Klinker, Joachim Stilla, Jorn Trilk, Hesam Najafi, “The Intelligent Welding Gun: Augmented Reality for Experimental Vehicle Construction,” Virtual and Augmented Reality Applications in Manufacturing, Ong S.K and Nee A.Y.C., eds., Springer Verlag, 2003, pp. 1-27.
Evaluating Two Novel Tactile Feedback Devices, by Thomas Hulin, Phillipp Kremer, Robert Scheibe, Simon Schaetzle and Carsten Preusche presented at the 4th International Conference on Enactive Interfaces, Grenoble, France, Nov. 19-22, 2007.
Fast et al., Virtual Training for Welding, Proceedings of the Third IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR 2004); 0-7695-2191-6/04; 2004.
Fast, Kenneth, Jerry Jones, and Valerie Rhoades; “Virtual Welding—A Low Cost Virtual Reality Welder Training System Phase II,” National Shipbuilding Research Program (NSRP), NSRP ASE Technology Investment Agreement No. 2010-357, Feb. 29, 2012, http://www.nsrp.org/3-RA-Panel_Final_Reports/FY08_Virtual_Welder_Final_Report.pdf.
Fite-Georgel, Pierre; “Is there a Reality in Industrial Augmented Reality?” 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2011.
Fridenfalk et al., Design and Validation of a Universal 6D Seam Tracking System in Robotic Welding Based on Laser Scanning, Industrial Robotics: Programming, Simulation, and Application, ISBN 3-86611-286-6, pp. 702, ARS/pIV, Germany, Dec. 2006, edited by Kin Huat.
Fronius “The Ghost”: http://www.fronius.com/cps/rde/xchg/SID-3202EAB7-AE082518/fronius_interational/hs.xs1/79_15490_ENG_HTML.htm; 2006.
Fronius International GmbH—Focus on Welding—Fronius Virtual Welding; http://www.fronius.com/cps/rde/xchg/SID-99869147-0110E322/fronius_intenational/hs.xsl/79_15490_ENG_HML.htm; 2006.
Fronius Perfect Welding; 06,3082, EN v01 2010 aw05; Virtual Welding—The training method of the future; Feb. 20, 2012.
ftp://www.hitl.washington.edu/pub/scivw/publications/IDS-pdf/HAPTIC1.pdf, (University of Washington): Table 11, Tactile Feedback Actuator Technologies, p. 119, below the table is a. Based on Hasser (1995, 1996).
GAWDA—Welding & Gases Today Online GAWDA Media Blog; Will Games Turn Welding into a Virtual Market? Friday, Dec. 2, 2011; http://www.weldingandgasestoday.org/blogs/Devin-OToole/index.php/ta . . . .
Gundersen, O., et al. “The Use of an Integrated Multiple Neural Network Structure for Simultaneous Prediction of Weld Shape, Mechanical Properties, and Distortion in 6063-T6 and 6082-T6 Aluminum Assemblies”, Mathematical Modelling of Weld Phenomena, vol. 5, Maney Publishing, 2001.
Haptic Feedback for Virtual Reality by Grigore C. Burdea dated 1996.
Hemez, Francois M., Scott W. Doebling, “Uncertainty, Validation of Computer Models an the Myth of Numerical Predictability,” Engineering Analysis Group (ESA-EA), Los Alamos National Laboratory, dated 2004.
Hillers, B, and Axel Graeser, “Direct welding arc observation withouth harsh flicker,” FABTECH International and AWS Welding Show, 2007.
Hillers, B, and Axel Graeser, “Real time Arc-Welding Video Observation System,” 62nd International Conference of IIW, Jul. 12-17, 2009, Singapore, 2009.
Hillers, B., et al.; “TEREBES: Welding Helmet with AR Capabilites,” Institute of Automation, University of Bremen, and Institute of Industrial Engineering and Ergonomics, RWTH Aachen Universty, 2004.
Hillers, Bernd, Dorin Aiteanu, Axel Graser, “Augmented Reality—Helmet for the Manual Welding Process,” Virtual and Augmented Reality Applications in Manufacturing, Institute of Automation, Universtity of Bremen, 2004.
Himperich, Frederick, “Applications in Augmented Reality in the Automotive Industry,” Fachgebiet Augmented Reality, Department of Informatics, Jul. 4, 2007, p. 1-21.
http://www.123arc.com “Simulation and Certification”; 2000.
Image from Sim Welder.com—R-V's Welder Training Goes Virtual, www.rvii.com/PDF/simwelder.pdf; Jan. 2010.
IMPACT Spring 2012 vol. 12, No. 2, Undergraduate Research in Information Technology Engineering, University of Virginia School of Engineering & Applied Science; 2012.
IMPACT Welding: miscellaneous examples from current and archived website, trade shows, etc. See, e.g., http://www.impactwelding.com.
Integrated Microelectromechanical Gyroscopes; Journal of Aerospace Engineering, Apr. 2003 pp. 65-75 (p. 65) by Huikai Xie and Garry K. Fedder.
International Search Report for PCT application No. PCT/US2009/045436, dated Nov. 9, 2009, 3 pgs.
International Search Report for PCT application No. PCT/US2012/050059, dated Nov. 27, 2012, 16 pgs.
International Search Report for PCT application No. PCT/US2013/038371, dated Jul. 31, 2013, 8 pgs.
International Search Report for PCT application No. PCT/US2013/066037, dated Mar. 11, 2014, 10 pgs.
International Search Report for PCT application No. PCT/US2013/066040, dated Mar. 11, 2014, 12 pgs.
International Search Report for PCT application No. PCT/US2014/018107, dated Jun. 2, 2014, 3 pgs.
International Search Report for PCT application No. PCT/US2014/018109, dated Jun. 2, 2014, 4 pgs.
International Search Report for PCT application No. PCT/US2014/018113, dated Jun. 2, 2014, 3pgs.
International Search Report for PCT application No. PCT/US2014/018114, dated Jun. 2, 2014, 4 pgs.
International Search Report for PCT application No. PCT/US2014/065498, dated May 11, 2015, 13 pgs.
International Search Report for PCT application No. PCT/US2014/065506, dated Jun. 26, 2015, 16 pgs.
International Search Report for PCT application No. PCT/US2014/065512, dated Jun. 8, 2015, 17 pgs.
International Search Report for PCT application No. PCT/US2014/065525, dated Jul. 23, 2015, 16 pgs.
International Search Report for PCT application No. PCT/US2014/067951, dated Feb. 24, 2015, 10 pgs.
International Search Report for PCT application No. PCT/US2015/037410, dated Nov. 6, 2015, 10 pgs.
International Search Report for PCT application No. PCT/US2015/037439, dated Nov. 3, 2015, 12 pgs.
International Search Report for PCT application No. PCT/US2015/037440, dated Nov. 3, 2015, 12 pgs.
International Search Report for PCT application No. PCT/US2015/039680, dated Sep. 23, 2015, 12 pgs.
International Search Report from PCT application No. PCT/US2015/043370, dated Dec. 4, 2015, 12 pgs.
International Search Report from PCT application No. PCT/US2015/058563, dated Jan. 29, 2016, 13 pgs.
International Search Report from PCT application No. PCT/US2015/058569, dated Feb. 10, 2016, 12 pgs.
International Search Report from PCT application No. PCT/US2015/058660, dated Feb. 2, 2016, 14 pgs.
International Search Report from PCT application No. PCT/US2015/058666, dated Feb. 1, 2016, 11 pgs.
International Search Report from PCT application No. PCT/US2015/058667, dated Feb. 5, 2016, 14 pgs.
Jo et al., Visualization of Virtual Weld Beads, VRST 2009, Kyoto, Japan, Nov. 18-20, 2009; Electronics and Telecommunications Research Institute (ETRI) ACM 978-1 60558-869-8/09, 0011.
Kiwinakiful; Holographic TV coming 2012 (as seen on BBV); http://www.youtube.com/watch?v=Ux6aD6vE9sk&feature=related, Jul. 2, 2011.
Kooima, Robert; Kinect +3D TV=Virtual Reality; http://www.youtube.com/watch?v=2MX1RinEXUM&feature=related, Feb. 26, 2011.
Leap Motion; https://www.leapmotion.com/, May 2012.
Lincoln Electric VRTEX Virtual Reality Arc Welding Trainer; http://www.lincolnelectric.com/en-us/equipment/training-equipment/pages/vrtex360.aspx; 1999.
MacCormick, John; How does the Kinect work?; http://users.dickinson.edu/˜jmac/selected-talks/kinect.pdf, Dec. 1, 2011.
NAMeS Users Guide, N A Tech Neural Applications, Copyright 1997, 1998, 1999, 2000 Golden, CO (123 pages).
NAMeS, Native American Technologies Weld Measuring Software, Users Guide, 2000.
National Science Foundation—Where Discoveries Begin—Science and Engineering's Most Powerful Statements Are Not Made From Words Alone—Entry Details for NSF International Science & Engineering Visualization Challenge, Public Voting ended on Mar. 9, 2012; Velu the welder by Muralitharan Vengadasalam—Sep. 30, 2011; https://nsf-scivis.skild.com/skild2/NationalScienceFoundation/viewEntryDetail.action?pid . . . .
Native American Technologies, “ArcDirector Weld Controller” web page, http://web.archive.org/web/20020608125127/http://www.natech-inc.com/arcdirector/index.html, published Jun. 8, 2002.
Native American Technologies, “ArcSentry Weld Quality Monitoring System” web page, http://web.archive.org/web/20020608124903/http://www.natech-inc.com/arcsentry1/index.html, published Jun. 8, 2002.
Native American Technologies, “P/NA.3 Process Modelling and Optimization” web pages, http://web.archive.org/web/20020608125619/http://www.natech-inc.com/pna3/index.html, published Jun. 8, 2002.
Native American Technologies, “Process Improvement Products” web page, http://web.archive.org/web/20020608050736/http://www.natech-inc.com/products.html, published Jun. 8, 2002.
Natural Point, Trackir; http://www.naturalpoint.com/trackir/, Dec. 2003.
Numerical Simulation F Arc Welding Process and its Application Dissertation for Ohio State University by Min Hyun Cho, M.S. 2006: See Internet as this document is security protected) ohttps://etd.ohiolink.edu/ap:0:0:APPLICATION_PROCESS=DOWNLOAD_ETD_SUB_DOC_ACCNUM:::F1501_ID:osu11557411 attachment.
NZ Manufacturer Game promotes welding trade careers; http://nzmanufacturer.co.nz/2011/11/gme-promotes-welding-trade-careers/ . . . Compentenz Industry Training; www.competenz.org.nz; Game promotes welding trade careers, Nov. 7, 2011.
OptiTrack: Motion Capture Systems: http://www.naturalpoint.com/optitrack/, Mar. 2005.
Penrod, Matt; “New Welder Training Tools,” EWI PowerPoint presentation, 2008.
PhaseSpace: Optical Motion Capture: http://phasespace.com/, 2009.
Playstation; Move Motion Controller: http://us.playstation.com/ps3/playstation-move/, Mar. 2010.
Polhemus: Innovation in Motion: http://polhemus.com/?page=researchandtechnology, 1992.
Porter et al, EWI-CRP Summary Report SR0512, Jul. 2005—Virtual Reality Welder Training.
Porter, Nancy C., Edison Welding Institute; J. Allan Cote, General Dynamics Electrict Boat; Timothy D. Gifford, VRSim; and Wim Lam, FCS Controls—Virtual Reality Welder Training—Project No. S1051 Navy Man Tech Program; Project Review for Ship Tech 2005,—Mar. 1, 2005, Biloxi, MS, http://www.nsrp.org/6-Presentations/WD/Virtual_Welder.pdf.
Porter, Nancy C., Edison Welding Institute; J.Allan Cote, General Dynamics Electric Boat; Timoty D. Gifford, VRSim; and Wim Lam, FCS Controls—Virtual Reality Welder Training—Session 5; Joining Technologies for Naval Applications; 2007.
Ryu, Jonghyun, Jaehoon Jung, Seojoon Kim, and Seungmoon Choi, “Perceptually Transparent Vibration Rendering Using a Vibration Motor for Haptic Interaction,” 16 IEEE International Conference on Robot & Human Interactive Communication, Jeju, Korea, Aug. 26-29, 2007.
Sandor, Christian, Gudrun Klinker, “PAARTI: Development of an Intelligent Welding Gun for BMW,” PIA 2003, Tokyo, Japan, Technical University of Munich Department of Informatics, Oct. 7, 2003.
Sandor, Christian, Gudrun Klinker; “Lessons Learned in Designing Ubiquitous Augmented Reality User Interfaces,” Emerging Technologies of Augmented Reality Interfaces, Eds. Haller, M, Billinghurst, M., and Thomas, B., Idea Group Inc., 2006.
ShotOfFuel; Wii Head Tracking for 3D, http://www.youtube.com/watch?v=1x5ffF-0Wr4, Mar. 19, 2008.
Stone, R. T., K. Watts, and P. Zhong, “Virtual Reality Integrated Welder Training, Welding Research,” Welding Journal, vol. 90, Jul. 2011, pp. 136-s-141-s, https://app.aws.org/wj/supplement/wj201107_s136.pdf.
TCS News & Events: Press Release: TCS wins the “People Choice” award from National Science Foundation, USA, pp. 1-6; Press Release May 21, 2012; http://www.tsc.com/news_events/press_releases/Pages/TCS_People_Choice_award_Natio . . . .
TeachWELD: Welding Simulator/Hands-On Learning for Welding: http://realityworks.com/products/teachweld-welding-simulator; 2012.
Terebes; miscellaneous examples from http://www.terebes.uni-bremen.de.
The Rutgers Master II—New Design Force-Feedback Glove by Mourad Bouzit, Member, IEEE,Grigore Burdea, Senior Member, IEEE, George Popescu, Member, IEEE, and Rares Bolan, Student Member, found in IEEE/ASME Transactions on Mechatronics, vol. 7, No. 2, Jun. 2002.
Thefabricator.com—Arc Welding Article; Heston, Tim, Virtual welding—Training in a virtual environment gives welding students a leg up—Mar. 11, 2008.
Tschirner, Petra, Hillers, Bernd, and Graeser, Axel; “A Concept for the Application of Augmented Reality in Manual Gas Metal Arc Welding,” Proceedings of the International Symposium on Mixed and Augmented Reality, 2002.
Vicon: Motion Capture Systems: http://vicon.com/, Dec. 1998.
Virtual Reality Training Manual Module 1—Training Overview—A Guide for Gas Metal Arc Welding—EWI 2006.
Welding Journal, American Welding Society, Nov. 2007, https://app.aws.org/wj/2007/11/WJ_2007_11.pdf.
White, S., et al., “Low-Cost Simulated MIG Welding for Advancement in Technical Training,” Virtual Reality, 15, 1, 69-81, Mar. 2011. ISSN:13594338 [Retrieved from EBSCOhost, Jun. 15, 2015].
“SOLDAMATIC: Augmented Training Technology for Welding,” Seabery Augmented Training Technology, Seabery Soluciones, 2011.
Hodgson, et al. “Virtual Reality in the Wild: A Self-Contained and Wearable Simulation System.” IEEE Virtual Reality, Mar. 4-8, 2012, Orange County, CA USA.
Hashimoto, Nobuyoshi et al., “Training System for Manual Arc Welding by Using Mixed Reality: Reduction of Position-Perception Error of Electrode Tip,” Journal of the Japan Society for Precision Engineering, vol. 72, pp. 249-253, 2006.
International Search Report from PCT application No. PCT/US2014/018103, dated Jun. 30, 2014, 13 pgs.
International Search Report from PCT application No. PCT/US2015/058567, dated May 6, 2016, 15 pgs.
International Search Report from PCT application No. PCT/US2015/058664, dated Apr. 25, 2016, 17 pgs.
International Search Report from PCT application No. PCT/US2016/023612, dated Jul. 18, 2016, 11 pgs.
Kobayashi, Kazuhiko et al., “Modified Training System for Manual Arc Welding by Using Mixed Reality and Investigation of Its Effectiveness,” Journal of the Japan Society for Precision Engineering, vol. 70, pp. 941-945, 2004.
Kobayashi, Kazuhiko et al., “Simulator of Manual Metal Arc Welding with Haptic Display,” Chiba University, ICAT 2001, Dec. 2001.
Kobayashi, Kazuhiko et al., “Skill Training System of Manual Arc Welding by Means of Face-Shield HMD and Virtual Electrode,” Chiba University, Japan, R. Nakatsu et al. (eds.), Entertainment Computing, Springer Science+Business Media, New York, 2003.
VRTEX 360 Operator's Manual, Lincoln Electric, Oct. 2012.
VRTEX 360, Lincoln Electric, Dec. 2009.
Weld Training Solutions, REALWELD, The Lincoln Electric Company, Jul. 2015.
Quebec International, May 28, 2008 ‘Video Game’ Technology to Fill Growing Need; http://www.mri.gouv.qc.ca/portail_scripts/actualities/viewnew.sap?NewID=5516.
Canadian Office Action Appln No. 2,961,806 dated Jan. 8, 2018 (3 pgs).
Canadian Office Action Appln No. 2,961,093 dated Mar. 5, 2018 (4 pgs).
Aiteanu, Dorin, “Virtual and Augmented Reality Supervisor for a New Welding Helmet” Nov. 15, 2005, pp. 1-150.
Wenbin Hou, “Discussion on Application of Simulation in Welding Teaching”, Science and Technology Innovation, Nov. 30, 2011, p. 248.
K. Fast, et al., “Virtual Training for Welding”, Third IEEE and ACM International Symposium on Mixed and Augmented Reality, Jan. 24, 2005, pp. 1-2.
Related Publications (1)
Number Date Country
20190005846 A1 Jan 2019 US
Provisional Applications (1)
Number Date Country
61911321 Dec 2013 US
Continuations (1)
Number Date Country
Parent 14554693 Nov 2014 US
Child 16101874 US