System for characterizing manual welding operations

Information

  • Patent Grant
  • 10522055
  • Patent Number
    10,522,055
  • Date Filed
    Thursday, June 13, 2019
    5 years ago
  • Date Issued
    Tuesday, December 31, 2019
    4 years ago
Abstract
A system for characterizing manual welding exercises and providing valuable training to welders that includes components for generating, capturing, and processing data. The data generating component further includes a fixture, workpiece, at least one calibration devices each having at least two point markers integral therewith, and a welding tool. The data capturing component further includes an imaging system for capturing images of the point markers and the data processing component is operative to receive information from the data capturing component and perform various position and orientation calculations.
Description
BACKGROUND OF THE INVENTION

The described invention relates in general to a system for characterizing manual welding operations, and more specifically to a system for providing useful information to a welding trainee by capturing, processing, and presenting in a viewable format, data generated by the welding trainee in manually executing an actual weld in real time.


The manufacturing industry's desire for efficient and economical welder training has been a well documented topic over the past decade as the realization of a severe shortage of skilled welders is becoming alarmingly evident in today's factories, shipyards, and construction sites. A rapidly retiring workforce combined with the slow pace of traditional instructor-based welder training has been the impetus for the development of more effective training technologies. Innovations which allow for the accelerated training of the manual dexterity skills specific to welding, along with the expeditious indoctrination of arc welding fundamentals are becoming a necessity. The characterization and training system disclosed herein addresses this vital need for improved welder training and enables the monitoring of manual welding processes to ensure the processes are within permissible limits necessary to meet industry-wide quality requirements. To date, the majority of welding processes are performed manually, yet the field is lacking practical commercially available tools to track the performance of these manual processes. Thus, there is an ongoing need for an effective system for training welders to properly execute various types of welds under various conditions.


SUMMARY OF THE INVENTION

The following provides a summary of certain exemplary embodiments of the present invention. This summary is not an extensive overview and is not intended to identify key or critical aspects or elements of the present invention or to delineate its scope.


In accordance with one aspect of the present invention, a system for characterizing manual and/or semiautomatic welding operations and exercises is provided. This system includes a data generating component; a data capturing component; and a data processing component. The data generating component further includes a fixture, wherein the geometric characteristics of the fixture are predetermined; a workpiece adapted to be mounted on the fixture, wherein the workpiece includes at least one joint to be welded, and wherein the vector extending along the joint to be welded defines an operation path; at least one calibration device, wherein each calibration device further includes at least two point markers integral therewith, and wherein the geometric relationship between the point markers and the operation path is predetermined; and a welding tool, wherein the welding tool is operative to form a weld at the joint to be welded, wherein the welding tool defines a tool point and a tool vector, and wherein the welding tool further includes a target attached to the welding tool, wherein the target further includes a plurality of point markers mounted thereon in a predetermined pattern, and wherein the predetermined pattern of point markers is operative to define a rigid body. The data capturing component further includes an imaging system for capturing images of the point markers. The data processing component is operative to receive information from the data capturing component and then calculate the position and orientation of the operation path relative to the three-dimensional space viewable by the imaging system; the position of the tool point and orientation of the tool vector relative to the rigid body; and the position of the tool point and orientation of the tool vector relative to the operation path.


In accordance with another aspect of the present invention, a system for characterizing manual and/or semiautomatic welding operations and exercises is also provided. This system includes a data generating component; a data capturing component; and a data processing component. The data generating component further includes a fixture, wherein the geometric characteristics of the fixture are predetermined; a workpiece adapted to be mounted on the fixture, wherein the workpiece includes at least one joint to be welded, and wherein the vector extending along the joint to be welded defines an operation path; at least one calibration device, wherein each calibration device further includes at least two point markers integral therewith, and wherein the geometric relationship between the point markers and the operation path is predetermined; and a welding tool, wherein the welding tool is operative to form a weld at the joint to be welded, wherein the welding tool defines a tool point and a tool vector, and wherein the welding tool further includes a target attached to the welding tool, wherein the target further includes a plurality of point markers mounted thereon in a predetermined pattern, and wherein the predetermined pattern of point markers is operative to define a rigid body. The data capturing component further includes an imaging system for capturing images of the point markers and the imaging system further includes a plurality of digital cameras. At least one band-pass filter is incorporated into the optical sequence for each of the plurality of digital cameras for permitting light from only the wavelengths which are reflected or emitted from the point markers for improving image signal-to-noise ratio. The data processing component is operative to receive information from the data capturing component and then calculate the position and orientation of the operation path relative to the three-dimensional space viewable by the imaging system; the position of the tool point and orientation of the tool vector relative to the rigid body; and the position of the tool point and orientation of the tool vector relative to the operation path.


Additional features and aspects of the present invention will become apparent to those of ordinary skill in the art upon reading and understanding the following detailed description of the exemplary embodiments. As will be appreciated by the skilled artisan, further embodiments of the invention are possible without departing from the scope and spirit of the invention. Accordingly, the drawings and associated descriptions are to be regarded as illustrative and not restrictive in nature.





BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated into and form a part of the specification, schematically illustrate one or more exemplary embodiments of the invention and, together with the general description given above and detailed description given below, serve to explain the principles of the invention, and wherein:



FIG. 1 is a flow chart illustrating the flow of information through the data processing and visualization component of an exemplary embodiment of the present invention;



FIG. 2 provides an isometric view of a portable or semi-portable system for characterizing manual welding operations, in accordance with an exemplary embodiment of the present invention;



FIG. 3 provides an isometric view of the flat assembly of the system of FIG. 2;



FIG. 4 provides an isometric view of the horizontal assembly of the system of FIG. 2;



FIG. 5 provides an isometric view of the vertical assembly of the system of FIG. 2;



FIG. 6 illustrates the placement of two point markers on the flat assembly of FIG. 2;



FIG. 7 illustrates an exemplary workpiece operation path;



FIG. 8 illustrates the placement of two active or passive point markers on an exemplary workpiece for determining a workpiece operation path;



FIG. 9 is a flowchart detailing the process steps involved in an exemplary embodiment of a first calibration component of the present invention;



FIG. 10 illustrates the welding tool of an exemplary embodiment of this invention showing the placement of the point markers used to define the rigid body;



FIG. 11 illustrates the welding tool of an exemplary embodiment of this invention showing the placement of the point markers used to define the tool vector and the rigid body; and



FIG. 12 is a flowchart detailing the process steps involved in an exemplary embodiment of a second calibration component of the present invention.





DETAILED DESCRIPTION OF THE INVENTION

Exemplary embodiments of the present invention are now described with reference to the Figures. Reference numerals are used throughout the detailed description to refer to the various elements and structures. In other instances, well-known structures and devices are shown in block diagram form for purposes of simplifying the description. Although the following detailed description contains many specifics for the purposes of illustration, a person of ordinary skill in the art will appreciate that many variations and alterations to the following details are within the scope of the invention. Accordingly, the following embodiments of the invention are set forth without any loss of generality to, and without imposing limitations upon, the claimed invention.


The present invention relates to an advanced system for observing and characterizing manual welding exercises and operations. This system is particularly useful for welding instruction and welder training that provides an affordable tool for measuring manual welding technique and comparing that technique with established procedures. The training applications of this invention include: (i) screening applicant skill levels; (ii) assessing trainee progress over time; (iii) providing real-time coaching to reduce training time and costs; and (iv) periodically re-testing welder skill levels with quantifiable results. Processing monitoring and quality control applications include: (i) identification of deviations from preferred conditions in real time; (ii) documenting and tracking compliance with procedures over time; (iii) capturing in-process data for statistical process control purposes (e.g., heat input measurements); and (iv) identifying welders needing additional training. The system of the present invention provides the unique benefit of enabling the determination of compliance with various accepted welding procedures.


The present invention, in various exemplary embodiments, measures torch motion and gathers process data during welding exercises using a single or multiple camera tracking system based on point cloud image analysis. This invention is applicable to a wide range of processes including, but not necessarily limited to, GMAW, FCAW, SMAW, GTAW, and cutting. The invention is expandable to a range of work-piece configurations, including large sizes, various joint type, pipe, plate, and complex shapes. Measured parameters include work angle, travel angle, tool standoff, travel speed, bead placement, weave, voltage, current, wire feed speed, and arc length. The training component of the present invention may be pre-populated with specific welding procedures or it may be customized by an instructor. Data is automatically saved and recorded, a post-weld analysis scores performance, and progress is tracked over time. This system may be used throughout an entire welding training program and may include both in-helmet and on-screen feedback. With reference now to the Figures, one or more specific embodiments of this invention shall be described in greater detail.


As shown in FIG. 1, in an exemplary embodiment of the present invention, the basic flow of information through data generating component 100, data capturing component 200, and data processing (and visualization) component 300 of weld characterization system 10 occurs in six basic steps: (1) image capture 110; (2) image processing 112; (3) input of arc weld data 210, such as known or preferred weld parameters; (4) data processing 212; (5) data storage 214; and (5) data display 310. Image capture step 110 includes capturing images of target 98 (which typically includes at least two point markers located in a fixed geometric relationship to one another) with one or more off-the shelf high-speed-vision cameras, where the output aspect typically includes creating of an image file at over 100 frames per second. The input aspect of image processing step 112 includes frame-by-frame point cloud analysis of a rigid body that includes three or more point markets (i.e., the calibrated target). Upon recognition of a known rigid body, position and orientation are calculated relative to the camera origin and the “trained” rigid body orientation. Capturing and comparing the images from two or more cameras allows for a substantially accurate determination of the rigid body position and orientation in three-dimensional space. Images are typically processed at a rate of more than 10 times per second. The output aspect of image processing step 112 includes creation of a data array that includes x-axis, y-axis, and z-axis positional data and roll, pitch, and yaw orientation data, as well as time stamps and software flags. The text file may be streamed or sent at a desired frequency. The input aspect of data processing step 212 includes raw positional and orientation data typically requested at a predetermined rate, while the output aspect includes transforming this raw data into useful welding parameters with algorithms specific to a selected process and joint type. The input aspect of data storage step 214 includes storing welding trial data as a *.dat file, while the output aspect includes saving the data for review and tracking, saving the date for review on a monitor at a later time, and/or reviewing the progress of the student at a later time. Student progress may include total practice time, total arc time, total arc starts, and individual parameter-specific performance over time. The input aspect of data display step 310 includes welding trial data that further includes work angle, travel angle, tool standoff, travel speed, bead placement, weave, voltage, current, wire-feed speed, while the output aspect involves data that may viewed on a monitor, in-helmet display, heads-up display, or combinations thereof, wherein parameters are plotted on a time-based axis and compared to upper and lower thresholds or preferred variations, such as those trained by recording the motions of an expert welder. Current and voltage may be measured in conjunction with travel speed to determine heat input and the welding process parameters may be used to estimate arc length. Position data may be transformed into weld start position, weld stop position, weld length, weld sequence, welding progression, or combinations thereof and current and voltage may be measured in conjunction with travel speed to determine heat input.



FIGS. 2-5 provide illustrative views of weld characterization system 10 in accordance with an exemplary embodiment the present invention. As shown in FIG. 2, portable training stand 20 includes a substantially flat base 22 for contact with a floor or other horizontal substrate, rigid vertical support column 24, camera or imaging device support 26, and rack and pinion assembly 31 for adjusting the height of imaging device support 26. In most embodiments, weld characterization system 10 is intended to be portable or at least moveable from one location to another, therefore the overall footprint of base 22 is relatively small to permit maximum flexibility with regard to installation and use. As shown in FIG. 2-6, weld characterization system 10 may be used for training exercises that include flat, horizontally or vertically oriented workpieces. In the exemplary embodiments shown in the Figures, training stand 20 is depicted as a unitary or integrated structure that is capable of supporting the other components of system. In other embodiments, stand 20 is absent and the various components of the system are supported by whatever suitable structural or supportive means may be available. Thus, within the context of this invention, “stand” 20 is defined as any single structure or, alternately, multiple structures that are capable of supporting the components of weld characterization system 10.


With to FIGS. 2-3, certain welding exercises will utilize a flat assembly 30, which is slidably attached to vertical support column 24 by collar 34, which slides upward or downward on support column 24. Collar 34 is further supported on column 24 by rack and pinion 31, which includes shaft 32 for moving rack and pinion assembly 31 upward or downward on support column 24. Flat assembly 30 includes training platform 38, which is supported by one or more brackets (not visible). In some embodiments, a shield 42 is attached to training platform 38 for protecting the surface of support column 24 from heat damage. Training platform 38 further includes at least one clamp 44 for securing weld position-specific fixture/jig 46 to the surface of the training platform. The structural configuration or general characteristics of weld position-specific jig 46 are variable based on the type of weld process that is the subject of a particular welding exercise, and in FIGS. 2-3, fixture 46 is configured for a fillet weld exercise. In the exemplary embodiment shown in FIGS. 2-3, first 48 and second 50 structural components of weld position-specific fixture 46 are set at right angles to one another. Position-specific fixture 46 may include one or more pegs 47 for facilitating proper placement of a weld coupon on the fixture. The characteristics of any weld coupon (workpiece) 54 used with system 10 are variable based on the type of manual welding process that is the subject of a particular training exercise and in the exemplary embodiment shown in the FIGS. 7-8, first 56 and second 58 portions of weld coupon 54 are also set at right angles to one another. With reference to FIGS. 4-5, certain other welding exercises will utilize a horizontal assembly 30 (see FIG. 4) or a vertical assembly 30 (see FIG. 5). In FIG. 4, horizontal assembly 30 supports butt fixture 46, which holds workpiece 54 in the proper position for a butt weld exercise. In FIG. 5, vertical assembly 30 supports vertical fixture 46, which holds workpiece 54 in the proper position for a lap weld exercise.


Data processing component 300 of the present invention typically includes at least one computer for receiving and analyzing information captured by the data capturing component 200, which itself includes at least one digital camera contained in a protective housing. During operation of weld characterization system 10, this computer is typically running software that includes a training regimen module, an image processing and rigid body analysis module, and a data processing module. The training regimen module includes a variety of weld types and a series of acceptable welding process parameters associated with creating each weld type. Any number of known or AWS weld joint types and the acceptable parameters associated with these weld joint types may be included in the training regimen module, which is accessed and configured by a course instructor prior to the beginning of a training exercise. The weld process and/or type selected by the instructor determine which weld process-specific fixture, calibration device, and weld coupon are used for any given training exercise. The object recognition module is operative to train the system to recognize a known rigid body target 98 (which includes two or more point markers) and for then to use target 98 to calculate positional and orientation data for welding gun 90 as an actual manual weld is completed by a trainee. The data processing module compares the information in the training regimen module to the information processed by the object recognition module and outputs the comparative data to a display device such as a monitor or head-up display. The monitor allows the trainee to visualize the processed data in real time and the visualized data is operative to provide the trainee with useful feedback regarding the characteristics and quality of the weld. The visual interface of weld characterization system 10 may include a variety of features related to the input of information, login, setup, calibration, practice, analysis, and progress tracking. The analysis screen typically displays the welding parameters found in the training regimen module, including (but not limited to) work angle, travel angle, tool standoff, travel speed, bead placement, weave, voltage, current, wire-feed speed, and arc length. Multiple display variations are possible with the present invention.


In most, if not all instances, weld characterization system 10 will be subjected to a series of calibration steps/processes prior to use. Some of the aspects of the system calibration will typically be performed by the manufacturer of system 10 prior to delivery to a customer and other aspects of the system calibration will typically be performed by the user of weld characterization system 10 prior to any welding training exercises. System calibration typically involves two related and integral calibration processes: (i) determining the three-dimensional position and orientation of the operation path to be created on a workpiece for each joint/position combination to be used in various welding training exercises; and (ii) determining the three-dimensional position and orientation of the welding tool by calculating the relationship between a plurality of reflective (passive) or light emitting (active) point markers located on target 98 and at least two key points represented by point markers located on the welding tool 90.


The first calibration aspect of this invention typically involves the calibration of the welding operation with respect to the global coordinate system, i.e., relative to the other structural components of weld characterization system 10 and the three-dimensional space occupied thereby. Prior to tracking/characterizing a manual welding exercise, the global coordinates of each desired operation path (i.e., vector) on any given workpiece will be determined. In most embodiments, this is a factory-executed calibration process that will include corresponding configuration files stored on data processing component 200. To obtain the desired vectors, a calibration device containing active or passive markers may be inserted on at least two locating markers in each of the three possible platform positions (i.e., flat, horizontal, and vertical). FIGS. 6-8 illustrate this calibration step in one possible platform position. Joint-specific fixture 46 includes first and second structural components 48 (horizontal) and 50 (vertical), respectively. Weld coupon or workpiece 54 includes first and second portions 56 (horizontal) and 58 (vertical), respectively. Workpiece operation path 59 extends from point X to point Y and is shown in broken line in FIG. 7. Locating point markers 530 and 532 are placed as shown in FIG. 6 (and FIG. 8) and the location of each marker is obtained using data capturing component 100, which in this embodiment utilizes Optitrack Tracking Tools (NaturalPoint, Inc.) or a similar commercially available or proprietary hardware/software system that provides three-dimensional marker and six degrees of freedom object motion tracking in real time. Such technologies typically utilize reflective and/or light emitting point markers arranged in predetermined patterns to create point clouds that are interpreted by system imaging hardware and system software as “rigid bodies”, although other suitable methodologies are compatible with this invention.


In the calibration process represented by the flowchart of FIG. 9, table 38 is fixed into position i (0,1,2) at step 280; a calibration device is placed on locating pins at step 282; all marker positions are captured at step 284; coordinates for the locator positions are calculated at step 286; coordinates for the fillet operation path are calculated at step 288 and stored at 290; coordinates for the lap operation path are calculated at step 292 and stored at 294; and coordinates for the groove operation path are calculated at step 296 and stored at 298. All coordinates are calculated relative to the three dimensional space viewable by data capturing component 200.


In one embodiment of this invention, the position and orientation of the work-piece is calibrated through the application of two or more passive or active point markers to a calibration device that is placed at a known translational and rotational offset to a fixture that holds the work-piece at a known translational and rotational offset. In another embodiment of this invention, the position and orientation of the work-piece is calibrated through the application of two or more passive or active point markers to a fixture that holds the work-piece at a known translational and rotational offset. In still other embodiments, the workpiece is non-linear, and the position and orientation thereof may be mapped using a calibration tool with two or more passive or active point markers and stored for later use. The position and orientation of the work-piece operation path may undergo a pre-determined translational and rotational offset from its original calibration plane based on the sequence steps in the overall work operation.


Important tool manipulation parameters such as position, orientation, velocity, acceleration, and spatial relationship to the work-piece operation path may be determined from the analysis of consecutive tool positions and orientations over time and the various work-piece operation paths described above. Tool manipulation parameters may be compared with pre-determined preferred values to determine deviations from known and preferred procedures. Tool manipulation parameters may also combined with other manufacturing process parameters to determine deviations from preferred procedures and these deviations may be used for assessing skill level, providing feedback for training, assessing progress toward a skill goal, or for quality control purposes. Recorded motion parameters relative to the workpiece operation path may be aggregated from multiple operations for statistical process control purposes. Deviations from preferred procedures may be aggregated from multiple operations for statistical process control purposes. Important tool manipulation parameters and tool positions and orientations with respect to the workpiece operation path may also be recorded for establishing a signature of an experienced operator's motions to be used as a baseline for assessing compliance with preferred procedures.


The second calibration aspect typically involves the calibration of welding tool 90 with respect to target 98. “Welding” tool 90 is typically a welding torch or gun or SMAW electrode holder, but may also be any number of other implements including a soldering iron, cutting torch, forming tool, material removal tool, paint gun, or wrench. With reference to FIGS. 10-11, welding gun/tool 90 includes tool point 91, nozzle 92, body 94, trigger 96, and target 98. Tool calibration device 93, which includes two integrated active or passive point markers in the A and B positions (see FIG. 11) is attached to or inserted into nozzle 92. A rigid body point cloud (i.e., a “rigid body”) is constructed by attaching active or passive point markers 502, 504, and 506 (and additional point markers) to the upper surface of target 98 (other placements are possible). Target 98 may include a power input if the point markers used are active and require a power source. Data capturing component 200 uses Optitrack Tracking Tools (NaturalPoint, Inc.) or similar hardware/software to locate the rigid body and point markers 522 (A) and 520 (B), which represent the location of tool vector 524. These positions can be extracted from the software of system 10 and the relationship between point markers A and B and the rigid body can be calculated.


In the calibration process represented by the flowchart of FIG. 12, weld nozzle 92 and the contact tube are removed at step 250; the calibration device is inserted into body 94 at step 252; weld tool 90 is placed in the working envelope and rigid body 500 (designated as “S” in FIG. 11) and point markers A and B are captured by data capturing component 100; the relationships between A and S and B and S are calculated at step 256; relationship data for As is stored at 258; and relationship data for Bs is stored at 260.


In one embodiment of this invention, calibration of the tool point and tool vector is performed through the application of two or more passive or active point markers to the calibration device at locations along the tool vector with a known offset to the tool point. In another embodiment, calibration of the tool point and tool vector is performed by inserting the tool into a calibration block of known position and orientation relative to the work-piece. With regard to the rigid body defined by the point markers (e.g., 502, 504, 506), in one embodiment, the passive or active point markers are affixed to the tool in in a multi-faceted manner so that a wide range of rotation and orientation changes can be accommodated within the field of view of the imaging system. In another embodiment, the passive or active point markers are affixed to the tool in a spherical manner so that a wide range of rotation and orientation changes can be accommodated within the field of view of the imaging system. In still another embodiment, the passive or active point markers are affixed to the tool in a ring shape so that a wide range of rotation and orientation changes can be accommodated within the field of view of the imaging system.


Numerous additional useful features may be incorporated into the present invention. For example, for purposes of image filtering, band-pass or high-pass filters may be incorporated into the optical sequence for each of the plurality of digital cameras in data capturing component 200 for permitting light from only the wavelengths which are reflected or emitted from the point markers to improve image signal-to-noise ratio. Spurious data may be rejected by analyzing only image information obtained from within a dynamic region of interest having a limited offset from a previously known rigid-body locality. This dynamic region of interest may be incorporated into or otherwise predefined (i.e., preprogrammed as a box or region of width x and height y and centered on known positions of target 98) within the field of view of each digital camera such that image information is only processed from this predefined region. The region of interest will change as the rigid body moves and is therefore based on previously known locations of the rigid body. This approach allows the imaging system to view only pixels within the dynamic region of interest when searching for point markers while disregarding or blocking pixels in the larger image frame that are not included in the dynamic region of interest. Decreased processing time is a benefit of this aspect of the invention.


While the present invention has been illustrated by the description of exemplary embodiments thereof, and while the embodiments have been described in certain detail, it is not the intention of the Applicant to restrict or in any way limit the scope of the appended claims to such detail. Additional advantages and modifications will readily appear to those skilled in the art. Therefore, the invention in its broader aspects is not limited to any of the specific details, representative devices and methods, and/or illustrative examples shown and described. Accordingly, departures may be made from such details without departing from the spirit or scope of the applicant's general inventive concept.

Claims
  • 1. A method of characterizing a manual welding operation, the method comprising: providing a plurality of welding parameters for a manual welding operation;providing a workpiece to be welded by the manual welding operation;providing a calibration tool, the calibration tool including a plurality of first point markers;providing a welding tool, the welding tool including a plurality of second point markers arranged in a predetermined pattern;placing the workpiece on a weld platform;placing the calibration tool on the weld platform;capturing at least one image of the first point markers of the calibration tool on the weld platform;processing the at least one image of the first point markers on the calibration tool to determine a position and orientation of an operational path for the manual welding operation based on at least one of the welding parameters;manually welding the workpiece with the welding tool;capturing a plurality of images of the second point markers on the welding tool during the manual welding operation;processing the plurality of images of the second point markers on the welding tool to determine a position and orientation of the welding tool; anddetermining a plurality of characteristics of the manual welding operation based on the position and orientation of the operational path and the position and orientation of the welding tool,wherein the characteristics are selected from the group consisting of: a welding tool work angle, a welding tool travel angle, a welding tool travel speed, a bead placement, and a welding tool standoff distance.
  • 2. The method of claim 1, wherein the weld platform includes a plurality of pins for removably attaching the calibration tool to the weld platform.
  • 3. The method of claim 1, wherein the weld platform includes a plurality of clamps to secure the workpiece to the weld platform.
  • 4. The method of claim 1, wherein the weld platform is connected to a stand.
  • 5. The method of claim 4, further comprising displaying the characteristics on a monitor, wherein the monitor is coupled to the stand.
  • 6. The method of claim 4, wherein the stand includes a vertical support.
  • 7. The method of claim 6, wherein an angle of the weld platform relative to the vertical support is adjustable.
  • 8. The method of claim 6, wherein a height of the weld platform relative to the vertical support is adjustable.
  • 9. The method of claim 4, wherein an optical camera system is coupled to the stand, the optical camera system comprising a plurality of spatially-separated cameras, and wherein the optical camera system is operable to capture images containing at least one of the first point markers and the second point markers.
  • 10. The method of claim 1, wherein the calibration tool is in physical contact with the workpiece on the weld platform.
  • 11. The method of claim 1, wherein the second point markers are active point markers.
  • 12. The method of claim 1, wherein the second point markers are light-emitting point markers.
  • 13. The method of claim 1, further comprising comparing each of the welding tool work angle, the welding tool travel angle, the welding tool travel speed, the bead placement, and the welding tool standoff distance to a corresponding predetermined lower threshold value and a corresponding predetermined upper threshold value.
  • 14. The method of claim 13, further comprising calculating a performance score for the manual welding operation based on the comparison of at least one of the welding tool work angle, the welding tool travel angle, the welding tool travel speed, the bead placement, and the welding tool standoff distance to the corresponding predetermined lower threshold value and the corresponding predetermined upper threshold value.
  • 15. The method of claim 1, further comprising comparing each of the welding tool work angle, the welding tool travel angle, the welding tool travel speed, the bead placement, and the welding tool standoff distance to a corresponding predetermined preferred value.
  • 16. The method of claim 15, further comprising calculating a performance score for the manual welding operation based on the comparison of at least one of the welding tool work angle, the welding tool travel angle, the welding tool travel speed, the bead placement, and the welding tool standoff distance to the corresponding predetermined preferred value.
  • 17. The method of claim 1, wherein the welding tool includes more than three of the second point markers, and wherein the predetermined pattern has no axis of symmetry.
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is being filed as a continuation application of U.S. patent application Ser. No. 16/021,576 filed on Jun. 28, 2018, which is a divisional application of U.S. patent application Ser. No. 15/077,532 filed on Mar. 22, 2016, now U.S. Pat. No. 10,068,495 issued on Sep. 4, 2018, which is a continuation of both U.S. patent application Ser. No. 14/293,700 filed on Jun. 2, 2014, now U.S. Pat. No. 9,773,429 issued on Sep. 26, 2017, and U.S. patent application Ser. No. 14/293,826 filed on Jun. 2, 2014, now abandoned, each of which is a continuation-in-part of U.S. patent application Ser. No. 13/543,240 filed on Jul. 6, 2012, now U.S. Pat. No. 9,221,117 issued on Dec. 29, 2015, which is a continuation-in-part of both U.S. patent application Ser. No. 12/966,570 filed on Dec. 13, 2010, now U.S. Pat. No. 9,230,449 issued on Jan. 5, 2016 (which itself is a continuation-in-part of U.S. patent application Ser. No. 12/499,687 filed on Jul. 8, 2009, now abandoned) and U.S. patent application Ser. No. 12/499,687 filed on Jul. 8, 2009, now abandoned, the entire disclosures of which are incorporated herein by reference.

US Referenced Citations (459)
Number Name Date Kind
317063 Wittenstrom May 1885 A
428459 Coffin May 1890 A
483428 Goppin Sep 1892 A
1159119 Springer Nov 1915 A
1286529 Cave Dec 1918 A
2326944 Holand et al. Aug 1943 A
2333192 Mobert Nov 1943 A
D140630 Garibay Mar 1945 S
D142377 Dunn Sep 1945 S
D152049 Welch Dec 1948 S
2681969 Burke Jun 1954 A
D174208 Abidgaard Mar 1955 S
2728838 Barnes Dec 1955 A
D176942 Cross Feb 1956 S
2894086 Rizer Jul 1959 A
3035155 Hawk May 1962 A
3059519 Stanton Oct 1962 A
3356823 Waters et al. Dec 1967 A
3555239 Kerth Jan 1971 A
3562927 Moskowitz Feb 1971 A
3562928 Schmitt Feb 1971 A
3621177 McPherson et al. Nov 1971 A
3654421 Streetman et al. Apr 1972 A
3690020 McBratnie Sep 1972 A
3739140 Rotilio Jun 1973 A
3852917 McKown Dec 1974 A
3866011 Cole Feb 1975 A
3867769 Schow et al. Feb 1975 A
3904845 Minkiewicz Sep 1975 A
3988913 Metcalfe et al. Nov 1976 A
D243459 Bliss Feb 1977 S
4024371 Drake May 1977 A
4041615 Whitehill Aug 1977 A
D247421 Driscoll Mar 1978 S
4124944 Blair Nov 1978 A
4132014 Schow Jan 1979 A
4237365 Lambros et al. Dec 1980 A
4280041 Kiessling et al. Jul 1981 A
4280137 Ashida et al. Jul 1981 A
4314125 Nakamura Feb 1982 A
4354087 Osterlitz Oct 1982 A
4359622 Dostoomian et al. Nov 1982 A
4375026 Kearney Feb 1983 A
4410787 Kremers et al. Oct 1983 A
4429266 Traadt Jan 1984 A
4452589 Denison Jun 1984 A
D275292 Bouman Aug 1984 S
D277761 Korovin et al. Feb 1985 S
4525619 Ide et al. Jun 1985 A
D280329 Bouman Aug 1985 S
4555614 Morris et al. Nov 1985 A
4611111 Baheti et al. Sep 1986 A
4616326 Meier et al. Oct 1986 A
4629860 Lindborn Dec 1986 A
4677277 Cook et al. Jun 1987 A
4680014 Paton et al. Jul 1987 A
4689021 Vasiliev et al. Aug 1987 A
4707582 Beyer Nov 1987 A
4716273 Paton et al. Dec 1987 A
D297704 Bulow Sep 1988 S
4812614 Wang et al. Mar 1989 A
4867685 Brush et al. Sep 1989 A
4877940 Bangs et al. Oct 1989 A
4897521 Burr Jan 1990 A
4907973 Hon Mar 1990 A
4931018 Herbst et al. Jun 1990 A
4973814 Kojima Nov 1990 A
4998050 Nishiyama et al. Mar 1991 A
5034593 Rice et al. Jul 1991 A
5061841 Richardson Oct 1991 A
5089914 Prescott Feb 1992 A
5192845 Kirmsse et al. Mar 1993 A
5206472 Myking et al. Apr 1993 A
5266930 Ichikawa et al. Nov 1993 A
5283418 Bellows et al. Feb 1994 A
5285916 Ross Feb 1994 A
5288968 Cecil Feb 1994 A
5305183 Teynor Apr 1994 A
5320538 Baum Jun 1994 A
5337611 Fleming et al. Aug 1994 A
5360156 Ishizaka et al. Nov 1994 A
5360960 Shirk Nov 1994 A
5362962 Barborak et al. Nov 1994 A
5370071 Ackermann Dec 1994 A
D359296 Witherspoon Jun 1995 S
5424634 Goldfarb et al. Jun 1995 A
5436638 Bolas et al. Jul 1995 A
5464957 Kidwell et al. Nov 1995 A
5465037 Huissoon et al. Nov 1995 A
D365583 Viken Dec 1995 S
5493093 Cecil et al. Feb 1996 A
5547052 Latshaw Aug 1996 A
5562843 Yasumoto Oct 1996 A
5662822 Tada et al. Sep 1997 A
5670071 Tomoyuki et al. Sep 1997 A
5676503 Lang Oct 1997 A
5676867 Van Allen Oct 1997 A
5708253 Bloch et al. Jan 1998 A
5710405 Solomon et al. Jan 1998 A
5719369 White et al. Feb 1998 A
D392534 Degen et al. Mar 1998 S
5728991 Takada et al. Mar 1998 A
5751258 Fergason et al. May 1998 A
D395296 Kaya et al. Jun 1998 S
5774110 Edelson Jun 1998 A
D396238 Schmitt Jul 1998 S
5781258 Debral et al. Jul 1998 A
5823785 Matherne, Jr. Oct 1998 A
5835077 Dao et al. Nov 1998 A
5835277 Hegg Nov 1998 A
5845053 Watanabe et al. Dec 1998 A
5877777 Colwell Mar 1999 A
5963891 Walker et al. Oct 1999 A
6008470 Zhang et al. Dec 1999 A
6037948 Liepa Mar 2000 A
6049059 Kim Apr 2000 A
6051805 Vaidya et al. Apr 2000 A
6114645 Burgess Sep 2000 A
6155475 Ekelof et al. Dec 2000 A
6155928 Burdick Dec 2000 A
6230327 Briand et al. May 2001 B1
6236013 Delzenne et al. May 2001 B1
6236017 Smartt et al. May 2001 B1
6242711 Cooper Jun 2001 B1
6271500 Hirayam et al. Aug 2001 B1
6301763 Pryor Oct 2001 B1
6330938 Herve et al. Dec 2001 B1
6330966 Eissfeller Dec 2001 B1
6331848 Stove et al. Dec 2001 B1
D456428 Aronson et al. Apr 2002 S
6373465 Jolly et al. Apr 2002 B2
6377011 Ben-Ur Apr 2002 B1
D456828 Aronson et al. May 2002 S
6396232 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 Apr 2003 B1
6560029 Dobbie et al. May 2003 B1
6563489 Latypov et al. May 2003 B1
6568846 Cote et al. May 2003 B1
D475726 Suga et al. Jun 2003 S
6572379 Sears et al. Jun 2003 B1
6583386 Ivkovich Jun 2003 B1
6593540 Baker Jul 2003 B1
6621049 Suzuki Sep 2003 B2
6624388 Blankenship Sep 2003 B1
D482171 Vui et al. Nov 2003 S
6647288 Madill et al. Nov 2003 B2
6649858 Wakeman Nov 2003 B2
6655645 Lu et al. Dec 2003 B1
6660965 Simpson Dec 2003 B2
6679702 Rau Jan 2004 B1
6697701 Hillen et al. Feb 2004 B2
6697770 Nagetgaal Feb 2004 B1
6703585 Suzuki Mar 2004 B2
6708385 Lemelson Mar 2004 B1
6710298 Eriksson Mar 2004 B2
6710299 Blankenship et al. Mar 2004 B2
6715502 Rome et al. Apr 2004 B1
D490347 Meyers May 2004 S
6730875 Hsu May 2004 B2
6734393 Friedl et al. May 2004 B1
6744011 Hu et al. Jun 2004 B1
6750428 Okamoto et al. Jun 2004 B2
6765584 Matthias Jul 2004 B1
6772802 Few Aug 2004 B2
6788442 Potin et al. Sep 2004 B1
6795778 Dodge et al. Sep 2004 B2
6798974 Nakano et al. Sep 2004 B1
6857553 Hartman et al. Feb 2005 B1
6858817 Blankenship et al. Feb 2005 B2
6865926 O'Brien et al. Mar 2005 B2
D504449 Butchko Apr 2005 S
6920371 Hillen et al. Jul 2005 B2
6940039 Blankenship et al. Sep 2005 B2
6982700 Rosenberg et al. Jan 2006 B2
7021937 Simpson et al. Apr 2006 B2
7024342 Waite Apr 2006 B1
7110859 Shibata et al. Sep 2006 B2
7126078 Demers et al. Oct 2006 B2
7132617 Lee et al. Nov 2006 B2
7170032 Flood Jan 2007 B2
7194447 Harvey Mar 2007 B2
7233837 Swain et al. Jun 2007 B2
7247814 Ott Jul 2007 B2
D555446 Picaza Ibarrondo Nov 2007 S
7298535 Kuutti Nov 2007 B2
7315241 Daily et al. Jan 2008 B1
D561973 Kinsley et al. Feb 2008 S
7353715 Myers Apr 2008 B2
7363137 Brant et al. Apr 2008 B2
7375304 Kainec et al. May 2008 B2
7381923 Gordon et al. Jun 2008 B2
7414595 Muffler Aug 2008 B1
7465230 Lemay et al. Dec 2008 B2
7474760 Hertzman et al. Jan 2009 B2
7478108 Townsend et al. Jan 2009 B2
D587975 Aronson et al. Mar 2009 S
7487018 Lee et al. Apr 2009 B2
7516022 Lee et al. Apr 2009 B2
7580821 Schirm Aug 2009 B2
D602057 Osicki Oct 2009 S
7621171 O'Brien Nov 2009 B2
D606102 Bender et al. Dec 2009 S
7643890 Hillen et al. Jan 2010 B1
7687741 Kainec et al. Mar 2010 B2
D614217 Peters et al. Apr 2010 S
D615573 Peters et al. May 2010 S
7817162 Bolick et al. Oct 2010 B2
7853645 Brown et al. Dec 2010 B2
D631074 Peters et al. Jan 2011 S
7874921 Baszucki et al. Jan 2011 B2
7970172 Hendrickson Jun 2011 B1
7972129 O'Dononghue Jul 2011 B2
7991587 Ihn Aug 2011 B2
8069017 Hallquist Nov 2011 B2
8224881 Spear et al. Jul 2012 B1
8248324 Nangle Aug 2012 B2
8265886 Bisiaux et al. Sep 2012 B2
8274013 Wallace Sep 2012 B2
8287522 Moses et al. Oct 2012 B2
8301286 Babu Oct 2012 B2
8316462 Becker et al. Nov 2012 B2
8363048 Gering Jan 2013 B2
8365603 Lesage et al. Feb 2013 B2
8512043 Choquet Aug 2013 B2
8569646 Daniel et al. Oct 2013 B2
8592723 Davidson et al. Nov 2013 B2
8657605 Wallace et al. Feb 2014 B2
8692157 Daniel et al. Apr 2014 B2
8747116 Zboray et al. Jun 2014 B2
8777629 Kreindl et al. Jul 2014 B2
8787051 Chang et al. Jul 2014 B2
8834168 Peters et al. Sep 2014 B2
8851896 Wallace et al. Oct 2014 B2
8911237 Postlewaite et al. Dec 2014 B2
8915740 Zboray et al. Dec 2014 B2
RE45398 Wallace Mar 2015 E
8992226 Leach et al. Mar 2015 B1
9011154 Kindig et al. Apr 2015 B2
9293056 Zboray et al. Mar 2016 B2
9293057 Zboray et al. Mar 2016 B2
9779635 Zboray et al. Oct 2017 B2
9836987 Postlethwaite et al. Dec 2017 B2
20010045808 Heitmann et al. Nov 2001 A1
20010052893 Jolly et al. Dec 2001 A1
20020032553 Simpson et al. Mar 2002 A1
20020039138 Edelson et al. Apr 2002 A1
20020046999 Veikkolainen et al. Apr 2002 A1
20020005421 Edelson et al. May 2002 A1
20020050984 Roberts May 2002 A1
20020085843 Mann Jul 2002 A1
20020094026 Edelson et al. Jul 2002 A1
20020098468 Barrett et al. Jul 2002 A1
20020111557 Madill et al. Aug 2002 A1
20020132213 Grant et al. Sep 2002 A1
20020135695 Edelson et al. Sep 2002 A1
20020175897 Pelosi Nov 2002 A1
20020178038 Grybas Nov 2002 A1
20020180761 Edelson Dec 2002 A1
20030000931 Ueda et al. Jan 2003 A1
20030002740 Melikian Jan 2003 A1
20030023592 Modica et al. Jan 2003 A1
20030025884 Hamana et al. Feb 2003 A1
20030062354 Ward Apr 2003 A1
20030075534 Okamoto Apr 2003 A1
20030106787 Santilli Jun 2003 A1
20030111451 Blankenship et al. Jun 2003 A1
20030172032 Choquet Sep 2003 A1
20030186199 McCool et al. Oct 2003 A1
20030228560 Seat et al. Dec 2003 A1
20030234885 Pilu Dec 2003 A1
20040009462 McElwrath Jan 2004 A1
20040020907 Zauner et al. Feb 2004 A1
20040035990 Ackeret Feb 2004 A1
20040050824 Samler Mar 2004 A1
20040088071 Kouno May 2004 A1
20040140301 Blankenship et al. Jul 2004 A1
20040167788 Birimisa et al. Aug 2004 A1
20040181382 Hu Sep 2004 A1
20050007504 Fergason Jan 2005 A1
20050017152 Fergason Jan 2005 A1
20050029326 Henrikson Feb 2005 A1
20050046584 Breed Mar 2005 A1
20050050168 Wen et al. Mar 2005 A1
20050101767 Clapham et al. May 2005 A1
20050103766 Iizuka et al. May 2005 A1
20050103767 Kainec et al. May 2005 A1
20050103768 Ward May 2005 A1
20050109735 Flood May 2005 A1
20050128186 Shahoian et al. Jun 2005 A1
20050133488 Blankenship Jun 2005 A1
20050159840 Lin et al. Jul 2005 A1
20050163364 Beck Jul 2005 A1
20050189336 Ku Sep 2005 A1
20050199602 Kaddani et al. Sep 2005 A1
20050230573 Ligertwood Oct 2005 A1
20050233295 Chiszar et al. Oct 2005 A1
20050252897 Hsu et al. Nov 2005 A1
20050275913 Vesely et al. Dec 2005 A1
20050275914 Vesely et al. Dec 2005 A1
20060014130 Weinstein Jan 2006 A1
20060076321 Maev Apr 2006 A1
20060136183 Choquet Jun 2006 A1
20060140502 Tseng et al. Jun 2006 A1
20060154226 Maxfield Jul 2006 A1
20060163227 Hillen et al. Jul 2006 A1
20060163228 Daniel Jul 2006 A1
20060166174 Rowe Jul 2006 A1
20060169682 Kainec et al. Aug 2006 A1
20060173619 Brant et al. Aug 2006 A1
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
20070164007 Peters et al. Jul 2007 A1
20070188606 Atkinson et al. Aug 2007 A1
20070198117 Wajihuddin Aug 2007 A1
20070211026 Ohta et al. Sep 2007 A1
20070221797 Thompson et al. Sep 2007 A1
20070256503 Wong et al. Nov 2007 A1
20070264620 Maddix et al. Nov 2007 A1
20070277611 Portzgen et al. Dec 2007 A1
20070291035 Vesely et al. Dec 2007 A1
20080021311 Goldbach Jan 2008 A1
20080027594 Jump et al. Jan 2008 A1
20080031774 Magnant et al. Feb 2008 A1
20080038702 Choquet Feb 2008 A1
20080061049 Albrecht Mar 2008 A1
20080078811 Hillen et al. Apr 2008 A1
20080078812 Peters et al. Apr 2008 A1
20080107345 Melikian May 2008 A1
20080117203 Gering May 2008 A1
20080120075 Wloka May 2008 A1
20080128398 Schneider Jun 2008 A1
20080135533 Ertmer et al. Jun 2008 A1
20080140815 Brant et al. Jun 2008 A1
20080149686 Daniel et al. Jun 2008 A1
20080203075 Feldhausen et al. Aug 2008 A1
20080233550 Solomon Sep 2008 A1
20080249998 Dettinger et al. Oct 2008 A1
20080303197 Paquette et al. Dec 2008 A1
20080314887 Stoger et al. Dec 2008 A1
20090015585 Klusza Jan 2009 A1
20090021514 Klusza Jan 2009 A1
20090045183 Artelsmair et al. Feb 2009 A1
20090050612 Serruys et al. Feb 2009 A1
20090057286 Ihara et al. Mar 2009 A1
20090109128 Nangle Apr 2009 A1
20090152251 Dantinne et al. Jun 2009 A1
20090173726 Davidson et al. Jul 2009 A1
20090184098 Daniel et al. Jul 2009 A1
20090197228 Afshar et al. Aug 2009 A1
20090200281 Hampton Aug 2009 A1
20090200282 Hampton Aug 2009 A1
20090231423 Becker et al. Sep 2009 A1
20090257655 Melikian Oct 2009 A1
20090259444 Dolansky et al. Oct 2009 A1
20090298024 Batzler et al. Dec 2009 A1
20090312958 Dai et al. Dec 2009 A1
20090325699 Delgiannidis Dec 2009 A1
20100012017 Miller Jan 2010 A1
20100012637 Jaeger Jan 2010 A1
20100021051 Melikian Jan 2010 A1
20100048273 Wallace et al. Feb 2010 A1
20100062405 Zboray et al. Mar 2010 A1
20100062406 Zboray et al. Mar 2010 A1
20100096373 Hillen et al. Apr 2010 A1
20100121472 Babu et al. May 2010 A1
20100133247 Mazumder et al. Jun 2010 A1
20100133250 Sardy et al. Jun 2010 A1
20100176107 Bong Jul 2010 A1
20100201803 Melikian Aug 2010 A1
20100224610 Wallace Sep 2010 A1
20100276396 Cooper Nov 2010 A1
20100299101 Shimada et al. Nov 2010 A1
20100307249 Lesage et al. Dec 2010 A1
20100314362 Albrecht Dec 2010 A1
20100326962 Calla et al. Dec 2010 A1
20110006047 Penrod Jan 2011 A1
20110048273 Colon Mar 2011 A1
20110052046 Melikian Mar 2011 A1
20110060568 Goldfine Mar 2011 A1
20110082728 Melikian Apr 2011 A1
20110091846 Kreindl et al. Apr 2011 A1
20110114615 Daniel et al. May 2011 A1
20110116076 Chantry et al. May 2011 A1
20110117527 Conrardy May 2011 A1
20110122495 Togashi May 2011 A1
20110183304 Wallace et al. Jul 2011 A1
20110187746 Suto 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
20120122062 Yang et al. May 2012 A1
20120189993 Kindig et al. Jul 2012 A1
20120291172 Wills et al. Nov 2012 A1
20120298640 Conrardy et al. Nov 2012 A1
20130026150 Chantry et al. Jan 2013 A1
20130040270 Albrecht Feb 2013 A1
20130049976 Maggiore Feb 2013 A1
20130075380 Albrech et al. Mar 2013 A1
20130119040 Suraba et al. 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 et al. Aug 2013 A1
20130209976 Postlethwaite et al. Aug 2013 A1
20130230832 Peters et al. Sep 2013 A1
20130231980 Choquet Sep 2013 A1
20130252214 Eigart et al. Sep 2013 A1
20130288211 Patterson et al. Oct 2013 A1
20130327747 Dantinne Dec 2013 A1
20130342678 McAninch et al. Dec 2013 A1
20140017642 Postlethwaite et al. Jan 2014 A1
20140038143 Daniel Feb 2014 A1
20140042136 Daniel Feb 2014 A1
20140065584 Wallace et al. Mar 2014 A1
20140134580 Becker May 2014 A1
20140263224 Becker Sep 2014 A1
20140272835 Becker Sep 2014 A1
20140272836 Becker Sep 2014 A1
20140272837 Becker Sep 2014 A1
20140272838 Becker Sep 2014 A1
20140312020 Daniel Oct 2014 A1
20140346158 Matthews Nov 2014 A1
20150056584 Boulware et al. Feb 2015 A1
20150056585 Boulware et al. Feb 2015 A1
20150056586 Penrod Feb 2015 A1
20150072323 Postlethwaite et al. Mar 2015 A1
20150125836 Daniel May 2015 A1
20150194073 Becker et al. Jul 2015 A1
20150235565 Postlethwaite et al. Aug 2015 A1
20150248846 Postlethwaite et al. Sep 2015 A1
20160093233 Boulware et al. Mar 2016 A1
20160125763 Becker May 2016 A1
20160203734 Boulware et al. Jul 2016 A1
20160203735 Boulware et al. Jul 2016 A1
20160260261 Hsu Sep 2016 A1
20160331592 Stewart Nov 2016 A1
20160343268 Postlethwaite et al. Nov 2016 A1
20170053557 Daniel Feb 2017 A1
Foreign Referenced Citations (122)
Number Date Country
2698078 Sep 2011 CA
1665633 Sep 2005 CN
201083660 Jul 2008 CN
201149744 Nov 2008 CN
101406978 Apr 2009 CN
101419755 Apr 2009 CN
201229711 Apr 2009 CN
101571887 Nov 2009 CN
101587659 Nov 2009 CN
101661589 Mar 2010 CN
102053563 May 2011 CN
102202836 Sep 2011 CN
202053009 Nov 2011 CN
202684308 Jan 2013 CN
203503228 Mar 2014 CN
103871279 Jun 2014 CN
28 33 638 Feb 1980 DE
30 46 634 Jan 1984 DE
32 44 307 May 1984 DE
35 22 581 Jan 1987 DE
4037879 Jun 1991 DE
196 15 069 Oct 1997 DE
197 39 720 Oct 1998 DE
19834205 Feb 2000 DE
200 09 543 Aug 2001 DE
10 2005 047 204 Apr 2007 DE
102006048165 Jan 2008 DE
10 2010 038 902 Feb 2012 DE
202012013151 Feb 2015 DE
0008527 Jan 1982 EP
0 108 599 May 1984 EP
0 127 299 Dec 1984 EP
0 145 891 Jun 1985 EP
319623 Oct 1990 EP
0852986 Jul 1998 EP
1 527 852 May 2005 EP
1905533 Apr 2008 EP
2 274 736 May 2007 ES
1456780 Mar 1965 FR
2 827 066 Jan 2003 FR
2 926 660 Jul 2009 FR
1 455 972 Nov 1976 GB
1 511 608 May 1978 GB
2 254 172 Sep 1992 GB
2435838 Sep 2007 GB
2 454 232 May 2009 GB
2-224877 Sep 1990 JP
05-329645 Dec 1993 JP
07-047471 Feb 1995 JP
07-232270 Sep 1995 JP
08-505091 Apr 1996 JP
08-150476 Jun 1996 JP
H08221107 Aug 1996 JP
08-132274 May 1998 JP
2000-167666 Jun 2000 JP
2000-237872 Sep 2000 JP
2001-071140 Mar 2001 JP
2002278670 Sep 2002 JP
2003-200372 Jul 2003 JP
2003-326362 Nov 2003 JP
2004025270 Jan 2004 JP
2006-006604 Jan 2006 JP
2006175205 Jul 2006 JP
2006-281270 Oct 2006 JP
2007-290025 Nov 2007 JP
2009-500178 Jan 2009 JP
2009160636 Jul 2009 JP
2010231792 Oct 2010 JP
2012024867 Feb 2012 JP
2012218058 Nov 2012 JP
100876425 Dec 2008 KR
20090010693 Jan 2009 KR
1020090111556 Oct 2009 KR
20110068544 Jun 2011 KR
527045 Jul 1995 RU
2317183 Feb 2008 RU
2008 108 601 Nov 2009 RU
1038963 Aug 1983 SU
9845078 Oct 1998 WO
0112376 Feb 2001 WO
0143910 Jun 2001 WO
0158400 Aug 2001 WO
2004029549 Apr 2004 WO
2005102230 Nov 2005 WO
2005110658 Nov 2005 WO
2006034571 Apr 2006 WO
2007009131 Jan 2007 WO
2007039278 Apr 2007 WO
2009120921 Jan 2009 WO
2009060231 May 2009 WO
2010020867 Aug 2009 WO
2009149740 Dec 2009 WO
2010000003 Jan 2010 WO
2010020870 Feb 2010 WO
2010044982 Apr 2010 WO
2010091493 Aug 2010 WO
2011017608 Feb 2011 WO
2011041037 Apr 2011 WO
2011045654 Apr 2011 WO
2011058433 May 2011 WO
2011059502 May 2011 WO
2011060350 May 2011 WO
2011067447 Jun 2011 WO
2011088412 Jul 2011 WO
2011097035 Aug 2011 WO
2012016851 Feb 2012 WO
2012082105 Jun 2012 WO
2012137060 Oct 2012 WO
2012143327 Oct 2012 WO
2013014202 Jan 2013 WO
2013-025672 Feb 2013 WO
2013061518 May 2013 WO
2013114189 Aug 2013 WO
2013119749 Aug 2013 WO
2013175079 Nov 2013 WO
2013186413 Dec 2013 WO
2014007830 Jan 2014 WO
2014019045 Feb 2014 WO
2014020386 Feb 2014 WO
2014140720 Sep 2014 WO
2014184710 Nov 2014 WO
2016-137578 Sep 2016 WO
Non-Patent Literature Citations (282)
Entry
SIMFOR / CESOL, “RV-SOLD” Welding Simulator, Technical and Functional Features, 20 pages, date unknown.
International Search Report and Written Opinion from PCT/IB2009/006605 dated Feb. 12, 2010.
Robert Schoder, “Design and Implementation of a Video Sensor for Closed Loop Control of Back Bead Weld Puddle Width,” Massachusetts, Institute of Technology, Dept. of Mechanical Engineering, May 27, 1983, 64 pages.
Hills and Steele, Jr.; “Data Parallel Algorithms”, Communications of the ACM, Dec. 1986, vol. 29, No. 12, p. 1170.
Nancy C. Porter, J. Allan Cote, Timothy D. Gifford, and Wim Lam, Virtual Reality Welder Training, 29 pages, dated Jul. 14, 2006.
J.Y. (YOSH) Mantinband, Hillel Goldenberg, Llan Kleinberger, Paul Kleinberger, Autosteroscopic, field—sequential display with full freedom of movement OR Let the display were the shutter-glasses, 3ality (Israel) Ltd., 8 pages, 2002.
Fronius, ARS Electronica Linz GMBH, High-speed video technology is applied to research on welding equipment, and the results are visualized in the CAVE, 2 pages, May 18, 1997.
D.K. Aidun and S.A. Martin, “Penetration in Spot GTA Welds during Centrifugation,” Journal of Material Engineering and Performance vol. 7(5), 4 pages, Oct. 1998—597.
Arc+ simulator; httl://www.123arc.com/en/depliant_ang.pdf; 2 pages, 2000.
Glen Wade, “Human uses of ultrasound: ancient and modern”, Ulrasonics vol. 38, 5 pages, dated 2000.
ASME Definitions, Consumables, Welding Positions, 4 pages, dated Mar. 19, 2001. See http://www.gowelding.com/asme4.htm.
M. Abbas, F. Waeckel, Code Aster (Software) EDF (France), 14 pages, Oct. 2001.
Achim Mahrle, Jurgen Schmidt, “The influence of fluid flow phenomena on the laser beam welding process”; International Journal of Heat and Fluid Flow 23, 10 pages, dated 2002.
The Lincoln Electric Company; CheckPoint Production Monitoring brochure; four (4) pages; http://www.lincolnelectric.com/assets/en_US/products/literature/s232.pdf; Publication S2.32; 4 pages, Issue Date Feb. 2012.
International Search Report and Written Opinion from PCT/US10/60129 dated Feb. 10, 2011.
Desroches, X.; Code-Aster, Note of use for aclculations of welding; Instruction manual U2.03 booklet: Thermomechincal; Document: U2.03.05; 13 pages, Oct. 1, 2003.
Fast, K. et al., “Virtual Training for Welding”, Mixed and Augmented Reality, 2004, ISMAR 2004, Third IEEE and SM International Symposium on Arlington, VA, 2 pages, Nov. 2-5, 2004.
Cooperative Research Program, Virtual Reality Welder Training, Summary Report SR 0512, 4 pages, Jul. 2005.
Porter, et al., Virtual Reality Training, Paper No. 2005-P19, 14 pages, 2005.
Eduwelding+, Weld Into the Future; Online Welding Seminar—A virtual training environment; 123arc.com; 4 pages, 2005.
Miller Electric MFG Co.; MIG Welding System features weld monitoring software; NewsRoom 2010 (Dialog® File 992); © 2011 Dialog. 2010; http://www.dialogweb.com/cgi/dwclient?reg=133233430487; three (3) pages; printed Mar. 8, 2012.
M. Abida and M. Siddique, Numerical simulation to study the effect of tack welds and root gap on welding deformations and residual stresses of a pipe-flange joint, Faculty of Mechanical Engineering, GIK Institute of Engineering Sciences and Technology, Topi, NWFP, Pakistan, 12 pages, Available on-line Aug. 25, 2005.
Abbas, M. et al. .; Code_Aster; Introduction to Code_Aster; User Manual; Booklet U1.0-: Introduction to Code_Aster; Document: U1.02.00; Version 7.4; 14 pagess, Jul. 22, 2005.
Mavrikios D et al, A prototype virtual reality-based demonstrator for immersive and interactive simulation of welding processes, International Journal of Computer Integrated manufacturing, Taylor and Francis, Basingstoke, GB, vol. 19, No. 3, 8 pages, Apr. 1, 2006, pp. 294-300.
Nancy C. Porter, Edison Welding Institute; J. Allan Cote, General Dynamics Electric Boat; Timothy D. Gifford, VRSim; and WIM LAM, FCS Controls; Virtual Reality Welder Trainer, Session 5: Joining Technologies for Naval Applications, 16 pages, earliest date Jul. 14, 2006.
T Borzecki, G. Bruce, Y.S. Han, M. Heinemann, A. Imakita, L. Josefson, W. Nie, D. Olson, F. Roland, and Y. Takeda, 16th International Shop and Offshore Structures Congress: Aug. 20-25, 2006: Southhampton, UK, 49 pages, vol. 2 Specialist Committee V.3 Fabrication Technology Committee Mandate.
Ratnam and Khalid: “Automatic classification of weld defects using simulated data and an MLP neutral network.” Insight vol. 49, No. 3; 6 pages, Mar. 2007.
Wang et al., Study on welder training by means of haptic guidance and virtual reality for arc welding, 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006 ISBN-10: 1424405718, 5 pages, p. 954-958.
CS Wave, The Virtual Welding Trainer, 6 pages, 2007.
asciencetutor.com, A division of Advanced Science and Automation Corp., VWL (Virtual Welding Lab), 2 pages, 2007.
Eric Linholm, John Nickolls, Stuart Oberman, and John Montrym, “NVIDIA Testla: A Unifired Graphics and Computing Architecture”, IEEE Computer Society, 17 pages, 2008.
NSRP ASE, Low-Cost Virtual Realtiy Welder Training System, 1 Page, 2008.
Edison Welding Institute, E-Weld Predictor, 3 pages, 2008.
CS Wave, A Virtual learning tool for welding motion, 10 pages, Mar. 14, 2008.
The Fabricator, Virtually Welding, Training in a virtual environment gives welding students a leg up, 4 pages, Mar. 2008.
N. A. Tech., P/NA.3 Process Modeling and Optimization, 11 pages, Jun. 4, 2008.
FH Joanneum, Fronius—virtual welding, 2 pages, May 12, 2008.
Eduwelding+, Training Activities with arc+ simulator; Weld Into the Future, Online Welding Simulator—A virtual training environment; 123arc.com; 6 pages, May 2008.
ChemWeb.com, Journal of Materials Engineering and Performance (v.7, #5), 3 pgs., printed Sep. 26, 2012.
Choquet, Claude; “ARC+: Today's Virtual Reality Solution for Welders” Internet Page, 6 pages, Jan. 1, 2008.
Juan Vicenete Rosell Gonzales, “RV-Sold: simulator virtual para la formacion de soldadores”; Deformacion Metalica, Es. vol. 34, No. 301, 14 pages, Jan. 1, 2008.
White et al., Virtual welder training, 2009 IEEE Virtual Reality Conference, 1 page, p. 303, 2009.
Training in a virtual environment gives welding students a leg up, retrieved on Apr. 12, 2010 from: http://www.thefabricator.com/article/arcwelding/virtually-welding, 4 pages.
Sim Welder, Train better welders faster, retrieved on Apr. 12, 2010 from: http://www.simwelder.com.
P. Beatriz Garcia-Allende, Jesus Mirapeix, Olga M. Conde, Adolfo Cobo and Jose M. Lopez-Higuera; Defect Detection in Arc-Welding Processes by Means of the Line-to-Continuum Method and Feature Selection; www.mdpi.com/joumal/sensors; 2009; 18 pages; Sensors 2009, 9, 7753-7770; doi; 10.3390/s91007753.
Production Monitoring 2 brochure, four (4) pages, The Lincoln Electric Company, May 2009.
International Search Report and Written Opinion from PCT/IB10/02913 dated Apr. 19, 2011.
Bjorn G. 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.
J. Hu and Hi Tsai, Heat and mass transfer in gas metal arc welding. Part 1: the arc, found in ScienceDirect, International Journal of Heat and Mass Transfer 50 (2007), 14 pages, 833-846, available online on Oct. 24, 2006 http://www.web.mst.edu/˜tsai/publications/HU-IJHMT-2007-1-60.pdf.
M. Ian Graham, Texture Mapping, Carnegie Mellon University Class 15-462 Computer Graphics, Lecture 10, 53 pages, dated Feb. 13, 2003.
Summons to attend oral proceedings pursuant to Rule 115(1) EPC from EP Application No. 15732934.3 dated Jun. 26, 2019.
Andreas Grahn, “Interactive Simulation of Contrast Fluid using Smoothed Particle Hydrodynamics,” Jan. 1, 2008, Masters Thesis in Computing Science, Umea University, Department of Computing Science, Umea Sweden; 69 pages.
Marcus Vesterlund, “Simulation and Rendering of a Viscous Fluid using Smoothed Particle Hydrodynamics,” Dec. 3, 2004, Master's Thesis in Computing Science, Umea University, Department of Computing Science, Umea Sweden; 46 pages.
M. Muller,, et al., “Point Based Animation of Elastic, Plastic and Melting Objects,” Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2004); 11 pages.
Andrew Nealen, “Point-Based Animation of Elastic, Plastic, and Melting Objects,” CG topics, Feb. 2005; 2 pages.
D. Tonnesen, Modeling Liquids and Solids using Thermal Particles, Proceedings of Graphics Interface'91, pp. 255-262, Calgary, Alberta, 1991.
CUDA Programming Guide Version 1.1, Nov. 29, 2007, 143 pages.
Websters II new college dictionary, 3rd ed., Houghton Mifflin Co., copyright 2005, Boston, MA, p. 1271, definition of Wake, 3 pages.
Da Dalto L, et al. “CS Wave: Learning welding motion in a virtual environment” Published in Proceedings of the IIW International Conference, Jul. 10-11, 2008; 19 pages.
CS Wave-Manual, “Virtual Welding Workbench User Manual 3.0” 2007; 25 pages.
Choquet, Claude. “ARC+®: Today's Virtual Reality Solution for Welders”, Published in Proceedings of the IIW International Conference; Jul. 10-11, 2008; 19 pages.
Welding Handbook, Welding Science & Technology, American Welding Society, Ninth Ed., Copyright 2001. Appendix A Terms and Definitions 54 pages.
Virtual Welding: A Low Cost Virtual Reality Welder Training System, NSRP RA 07-01—BRP Oral Review Meeting in Charleston, SC at ATI, Mar. 2008; 6 pages.
Dorin Aiteanu, “Virtual and Augmented Reality Supervisor for a New Welding Helmet Dissertation,” Nov. 15, 2005; 154 pages.
Screen 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/mages/english/snap_evolution6.jpg; 1 page.
Da Dalto L, et al. “CS Wave a Virtual learning tool for the welding motion,” Mar. 14, 2008; 10 pages.
Nordruch, Stefan, et al. “Visual Online Monitoring of PGMAW Without a Lighting Unit”, Jan. 2005; 14 pages.
The Evolution of Computer Graphics; Tony Tamasi, NVIDIA, 2008; 36 pages.
VRSim Powering Virtual Reality, www.lincolnelectric.com/en-us/eguipment/Iraining-eguipment/Pages/powered-by-'rsim.aspx, 2016, 1 page.
Hillers, B.; Graser, A. “Direct welding arc observation without harsh flicker,” 8 pages, allegedly FABTECH International and AWS welding show, 2007.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00905; 72 pages.
Declaration of Edward Bohnart, Apr. 27, 2016, exhibit to IPR 2016-00905; 23 pages.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00904; 76 pages.
Declaration of Edward Bohnart, Apr. 27, 2016, exhibit to IPR 2016-00904; 22 pages.
Declaration of Axel Graeser, Apr. 17, 2016, exhibit to IPR 2016-00840; 88 pages.
International Search Report and Written Opinion from PCT/IB2014/002346 dated Feb. 24, 2015.
ARC+—Archived Press Release from WayBack Machine from Jan. 31, 2008-Apr. 22, 2013, Page, https://web.3rchive.org/web/20121006041803/http://www.123certification.com/en/article_press/index.htm, Jan. 21, 2016, 3 pages.
P. Tschirner et al., “Virtual and Augmented Reality for Quality Improvement of Manual Welds” National Institute of Standards and Technology, Jan. 2002, Publication 973, 24 pages.
Y. Wang et al., “Impingement of Filler Droplets and Weld Pool During Gas Metal Arc Welding Process” International Journal of Heat and Mass Transfer, Sep. 1999, 14 pages.
Larry Jeffus, “Welding Principles and Applications,” Sixth Edition, 2008, 10 pages.
R.J. Renwick et al., “Experimental Investigation of GTA Weld Pool Oscillations,” Welding Research—Supplement to the Welding Journal, Feb. 1983, 7 pages.
Matt Phar, “GPU Gems 2 Programming Techniques for High-Performance Graphics and General-Purpose Computation,” 2005, 12 pages.
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.
International Search Report and Written Opinion from PCT/IB2015/000777 dated Sep. 21, 2015.
International Search Report and Written Opinion from PCT/IB2015/000814 dated Nov. 5, 2015.
International Search Report and Written Opinion from PCT/IB2015/001711 dated Jan. 4, 2016.
International Preliminary Report on Patentability from PCT/IB2014/001796 dated Mar. 15, 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.
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.
International Preliminary Report on Patentability from PCT/IB2015/001084 dated Jan. 26, 2017.
Extended European Search Report from EP Application No. 10860823.3 dated Jun. 6, 2017.
Communication Pursuant to Article 94(3) EPC in EP Application No. 13753204.0 dated Mar. 9, 2017.
Office action from U.S. Appl. No. 12/499,687 dated Oct. 16, 2012.
Office action from U.S. Appl. No. 12/499,687 dated Jun. 26, 2013.
Notice of Allowance from U.S. Appl. No. 12/966,570 dated Apr. 29, 2014.
Corrected Notice of Allowance from U.S. Appl. No. 12/966,570 dated Feb. 23, 2015.
Russell and Norvig, “Artificial Intelligence: A Modern Approach”, Prentice-Hall (Copyright 1995).
Mechanisms and Mechanical Devices Source Book, Chironis, Neil Sclater, McGraw Hill; 2nd Addition, 1996.
International Search Report and Written Opinion from PCT/US12/45776 dated Oct. 1, 2012.
Bender Shipbuilding and Repair Co. Virtual Welding—A Low Cost Virtual Reality Welding Training System. Proposal submitted pursuant to MSRP Advanced Shipbuilding Enterprise Research Announcement, Jan. 23, 2008. 28 pages, See also, http://www.nsrp.org/6- PresentationsM/D/020409 Virtual Welding Wilbur.pdf.
Aiteanu, Dorian; and Graser, Axel. “Generation and Rendering of a Virtual Welding Seam in an Augmented Reality Training Environment.” Proceedings of the Sixth IASTED International Conference on Visualization, Imaging and Image Processing, Aug. 28-30, 2006, 8 pages, allegedly Palma de Mallorca, Spain. Ed. J.J. Villaneuva. ACTA Press.
Tschirner, Petra; Hillers, Bernd; and Graser, Axel “A Concept for the Application of Augmented Reality in Manual Gas Metal Arc Welding.” Proceedings of the International Symposium on Mixed and Augmented Reality; 2 pages; 2002.
Penrod, Matt. “New Welder Training Tools.” EWI PowerPoint presentation; 16 pages; allegedly 2008.
Fite-Georgel, Pierre. “Is there a Reality in Industrial Augmented Reality?” 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR). 10 pages, allegedly 2011.
Hillers, B.; Graser, A. “Real time Arc-Welding Video Observation System.” 62nd International Conference of IIW, Jul. 12-17, 2009, 5 pages, allegedly Singapore 2009.
Advance Program of American Welding Society Programs and Events. Nov. 11-14, 2007. 31 pages. Chicago.
TEREBES: examples from http://www.terebes.uni-bremen.de.; 6 pages.
Sandor, Christian; Gudrun Klinker. “PAARTI: Development of an Intelligent Welding Gun for BMW.” PIA2003, 7 pages, Tokyo. 2003.
ARVIKA Forum Vorstellung Projekt PAARI. BMW Group Virtual Reality Center. 4 pages. Nuermberg. 2003.
Sandor, Christian; Klinker, Gudrun. “Lessons Learned in Designing Ubiquitous Augmented Reality User Interfaces.” 21 gages, allegedly from Emerging Technologies of Augmented Reality: Interfaces Eds. Haller, M.; Billinghurst, M.; Thomas, B. Idea Group Inc. 2006.
Impact Welding: examples from current and archived website, trade shows, etc. See, e.g., http://www.impactwelding.com. 53 pages.
http://www.nsrp.org/6-Presentations/WDVirtual_Welder.pdf (Virtual Reality Welder Training, Project No. SI051, Navy ManTech Program, Project Review for ShipTech 2005); 22 pages. Biloxi, MS.
https://app.aws_org/w/r/www/wj/2005/031WJ_2005_03.pdf (AWS Welding Journal, Mar. 2005 (see, e.g., p. 54)).; 114 pages.
https://app.aws.org/conferences/defense/live index.html (AWS Welding in the Defense Industry conference schedule, 2004); 12 pages.
https://app.aws.org/wj/2004/04/052/njc (AWS Virtual Reality Program to Train Welders for Shipbuilding, workshop information, 2004); 7 pages.
https://app.aws.org/wj/2007/11WJ200711.pdf (AWS Welding Journal, Nov. 2007); 240 pages.
American Welding Society, “Vision for Welding Industry;” 41 pages.
Energetics, Inc. “Welding Technology Roadmap,” Sep. 2000, 38 pages.
Aiteanu, Dorian; and Graser, Axel. Computer-Aided Manual Welding Using an Augmented Reality Supervisor Sheet Metal Welding Conference XII, Livonia, MI, May 9-12, 2006, 14 pages.
Hillers, Bernd; Aiteanu, Dorin and Graser, Axel “Augmented Reality—Helmet for the Manual Welding Process,” Institute of Automation, University of Bremen, Germany; 21 pages.
Aiteanu, Dorin, Hillers, Bernd and Graser, Axel “A Step Forward in Manual Welding: Demonstration of Augmented Reality Helmet” Institute of Automation, University of Bremen, Germany, Proceedings of the Second IEEE and 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.
B. Hillers, D. Aitenau, P. Tschimer, M. Park, A. Graser, B. Balazs, L. Schmidt, “TEREBES: Welding Helmet with AR Capabilities”, Institute of Automatic University Bremen; Institute of Industrial Engineering and Ergonomics, 10 pages, allegedly 2004.
Sheet Metal Welding Conference Xlr, American Welding Society Detroit Section, May 2006, 11 pages.
Kenneth Fast, Timothy Gifford, Robert Yancey, “Virtual Training for Welding”, Proceedings of the Third IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR 2004); 2 pages.
Amended Answer to Complaint with Exhibit A for Patent Infringement filed by Seabery North America Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN, docket No. 44, filed Mar. 1, 2016, in the U.S. District Court for the Northern District of Ohio; 19 pages.
Amended Answer to Complaint with Exhibit A for Patent Infringement filed by Seabery Soluciones SL in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L_ et al., Case No. 1:15-cv-01575-DCN, docket No. 45, filed Mar. 1, 2016 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 Company; Lincoln Global, Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN; docket No. 46, filed Mar. 22, 2016; 5 pages.
Answer for Patent Infringement filed by Lincoln Electric Company, Lincoln Global, Inc. in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-cv-01575-DCN; docket No. 47, filed Mar. 22, 2016; 5 pages.
Petition for Inter Partes Review of U.S. Pat. No. 8,747,116; IPR 2016-00749; Apr. 7, 2016; 70 pages.
Petition for Inter Partes Review of U.S. Pat. No. RE45,398; IPR 2016-00840; Apr. 18, 2016; 71 pages.
Petition for Inter Partes Review of U.S. Pat. No. 9,293,056; IPR 2016-00904; May 9, 2016; 91 pages.
Petition for Inter Partes Review of U.S. Pat. No. 9,293,057; IPR 2016-00905; May 9, 2016; 87 pages.
http://www.vrsim.net/history, downloaded Feb. 26, 2016.
Complaint for Patent Infringement in Lincoln Electric Co. et al. v. Seabery Soluciones, S.L. et al., Case No. 1:15-av-01575-DCN, docket No. 1, filed Aug. 10, 2015, in the U.S. District Court for the Northern District of Ohio; 81 pages.
Kobayashi, Ishigame, and Kato, “Simulator of Manual Metal Arc Welding with Haptic Display” (“Kobayashi 2001”), Proc. of the 11th International Conf. on Artificial Reality and Telexistence (ICAT), Dec. 5-7, 2001, pp. 175-178, Tokyo, Japan.
Wahi, Maxwell, and Reaugh, “Finite-Difference Simulation of a Multi-Pass Pipe Weld” (“Wahi”), vol. L, paper 3/1, International Conference on Structural Mechanics in Reactor Technology, San Francisco, CA, Aug. 15-19, 1977.
Declaration of Dr. Michael Zyda, May 3, 2016, exhibit to IPR 2016-00749.
Declaration of Edward Bohnert, Apr. 27, 2016, exhibit to IPR 2016-00749.
Swantec corporate web page downloaded Apr. 19, 2016. httpl/www.swantec.com/technology/numerical-simulation/.
Catalina, Stefanescu, Sen, and Kaukler, Interaction of Porosity with a Planar Solid/Liquid Interface(Catalina),), Metallurgical and Materials Transactions, vol. 35A, May 2004, pp. 1525-1538.
Fletcher Yoder Opinion re RE45398 and U.S Appl. No. 14/589,317; including appendices; Sep. 9, 2015; 1700 pages.
Kobayashi, Ishigame, and Kato, “Skill Training System of Manual Arc Welding by Means of Face-Shield-Like HMD and Virtual Electrode” (“Kobayashi 2003”), Entertainment Computing, vol. 112 of the International Federation for Information Processing (IFIP), Springer Science + Business Media, New York, copyright 2003, pp. 389-396.
G.E. Moore, No exponential is forever: but Forever can be delayed!: IEEE International Solid-State Circuits Conference, 2003. 19 pages.
“High Performance Computer Architectures_ A Historical Perspective,” downloaded May 5, 2016. http://homepages.inf.ed.ac.uk/cgi/mi/comparch. pl?Paru/perf.html,Paru/perf-f.html,Paru/menu-76.html; 3 pages.
Chuansong Wu: “Microcomputer-based welder training simulator”, Computers in Industry, vol. 20, No. 3, Oct. 1992, 5 pages, pp. 321-325, XP000205597, Elsevier Science Publishers, Amsterdam, NL.
ViziTech USA, retrieved on Mar. 27, 2014 from http://vizitechusa.com/, 2 pages.
Guu and Rokhlin ,Technique for Simultaneous Real-Time Measurements of Weld Pool Surface Geometry and Arc Force, 10 pages, Dec. 1992.
William T. Reeves, “Particles Systems—A Technique for Modeling a Class of Fuzzy Objects”, Computer Graphics 17:3 pp. 359-376, 1983, 17 pages.
S.B. Chen, L. Wu, Q. L. Wang and Y. C. Liu, Self-Learning Fuzzy Neural Networks and Computer Vision for Control of Pulsed GTAW, 9 pages, dated May 1997.
Patrick Rodjito, Position tracking and motion prediction using Fuzzy Logic, 81 pages, 2006, Colby College.
D'Huart, Deat, and Lium; Virtual Environment for Training, 6th International Conference, ITS 20002, 6 pages, Jun. 2002.
Konstantinos Nasios (Bsc), Improving Chemical Plant Safety Training Using Virtual Reality, Thesis submitted to the University of Nottingham for the Degree of Doctor of Philosophy, 313 pages, Dec. 2001.
ANSI/A WS D 10.11 MID 10. 11 :2007 Guide for Root Pass Welding of Pipe without Backing Edition: 3rd American Welding Society / Oct. 13, 2006/36 pages ISBN: 0871716445, 6 pages.
M. Jonsson, L. Karlsson, and L-E Lindgren, Simulation of Tack Welding Procedures in Butt Joint Welding of Plates Welding Research Supplement, Oct. 1985, 7 pages.
Isaac Brana Veiga, Simulation of a Work Cell in the IGRIP Program, dated 2006, 50 pages.
Balijepalli, A. and Kesavadas, Haptic Interfaces for Virtual Environment and Teleoperator Systems, Haptics 2003, Department of Mechanical & Aerospace Engineering, State University of New York at Buffalo, NY.
Johannes Hirche, Alexander Ehlert, Stefan Guthe, Michael Doggett, Hardware Accelerated Per-Pixel Displacement Mapping, 8 pages.
Yao et al., ‘Development of a Robot System for Pipe Welding’. 2010 International Conference on Measuring 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.
Steve Mann, Raymond Chun Bing Lo, Kalin Ovtcharov, Shixiang Gu, David Dai, Calvin Ngan, Tao 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.
KYT Dotson, Augmented Reality Welding Helmet Prototypes How Awsome the Technology Can Get, Sep. 26, 2012, Retrieved from the Internet: URL:http://siliconangle.com/blog/2012/09/26/augmented-reality-welding-helmet-prototypes-how-awesome-the-technology-can-get/,1 page, retrieved on Sep. 26, 2014.
Terrence O'Brien, “Google's Project Glass gets some more details”,Jun. 27, 2012 (Jun. 27, 2012), Retrieved from the Internet: http://www.engadget.com/2012/06/27/googles-project-glass-gets-some-more-details/, 1 page, retrieved on Sep. 26, 2014.
T. Borzecki, G. Bruce, YS. Han, et al., Specialist Committee V.3 Fabrication Technology Committee Mandate, Aug. 20-25, 2006, 49 pages, vol. 2, 16th International Ship and Offshore Structures Congress, Southampton, UK.
G. Wang, P.G. Huang, and Y.M. Zhang: “Numerical Analysis of Metal Transfer in Gas Metal Arc Welding”: Departments of Mechanical Engineering; and Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40506-0108, 10 pages, Dec. 10, 2001.
Echtler et al, “17 The Intelligent Welding Gun: Augmented Reality for Experimental Vehicle Construction,” Virtual and Augmented Reality Applications in Manufacturing (2003) pp. 1-27.
Teeravarunyou et al, “Computer Based Welding Training System,” International Journal of Industrial Engineering (2009) 16(2): 116-125.
Antonelli et al, “A Semi-Automated Welding Station Exploiting Human-Robot Interaction,” Advanced Manufacturing Systems and Technology (2011) pp. 249-260.
Praxair Technology Inc, “The RealWeld Trainer System: Real Weld Training Under Real Conditions” Brochure (2013) 2 pages.
Xie et al., “A Real-Time Welding Training System Base on Virtual Reality,” Wuhan Onew Technology Co., Lid, IEEE Virtual Reality Conference 2015, Mar. 23-27, Arles France, pp. 309-310.
Lincoln Global, Inc., “VRTEX 360: Virtual Reality Arc Welding Trainer” Brochure (2015) 4 pages.
Wuhan Onew Technology Co Ltd, “ONEW-360 Welding Training Simulator” http://en.onewtech.com/_d276479751.htm as accessed on Jul. 10, 2015, 14 pages.
The Lincoln Electric Company, “VRTEX Virtual Reality Arc Welding Trainer,” http://www.lincolnelectric.com/en-us/equipment/training-equipment/Pages/vrtex.aspx as accessed on Jul. 10, 2015, 3 pages.
Miller Electric Mfg Co, “LiveArc: Welding Performance Management System” Owner's Manual, (Jul. 2014) 64 pages.
Miller Electric Mfg Co, “LiveArc Welding Performance Management System” Brochure, (Dec. 2014) 4 pages.
Office action from U.S. Appl. No. 12/499,687 dated Mar. 6, 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.
Office action from U.S. Appl. No. 13/543,240 dated Nov. 14, 2014.
Office action from U.S. Appl. No. 14/444,173 dated Mar. 18, 2015.
Notice of Allowance from U.S. Appl. No. 13/543,240 dated Jun. 3, 2015.
Notice of Allowance from U.S. Appl. No. 14/444,173 dated Jun. 24, 2015.
Office action from U.S. Appl. No. 15/077,481 dated May 23, 2016.
Notice of Allowance from U.S. Appl. No. 15/077,481 dated Aug. 10, 2016.
Notice of Allowance from U.S. Appl. No. 15/077,481 dated Feb. 3, 2017.
Office Action from U.S. Appl. No. 14/190,812 dated Nov. 9, 2016.
Office Action from U.S. Appl. No. 14/190,812 dated Feb. 23, 2017.
Office Action from U.S. Appl. No. 15/077,532 dated Dec. 29, 2017.
Office Action from U.S. Appl. No. 14/293,700 dated Dec. 28, 2016.
Notice of Allowance from U.S. Appl. No. 14/293,700 dated May 10, 2017.
Office Action from U.S. Appl. No. 14/293,826 dated Dec. 30, 2016.
Office Action from U.S. Appl. No. 14/293,826 dated Jul. 21, 2017.
Office Action from U.S. Appl. No. 14/526,914 dated Feb. 3, 2017.
Office Action from U.S. Appl. No. 14/526,914 dated Jun. 6, 2017.
Office Action from U.S. Appl. No. 14/552,739 dated Feb. 17, 2017.
Office Action from U.S. Appl. No. 14/615,637 dated Apr. 27, 2017.
Office Action from JP Application No. 2016-569029 dated Jun. 11, 2019.
Office Action from U.S. Appl. No. 14/827,657 dated May 26, 2017.
Office Action from U.S. Appl. No. 14/827,657 dated Jan. 16, 2018.
Office Action from U.S. Appl. No. 15/228,524 dated Feb. 5, 2018.
Office Action from Chinese Application No. 201280075678.5 dated Jul. 5, 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.
Office Action from Chinese Application No. 201480025359.2 dated Sep. 26, 2016.
Office Action from Chinese Application No. 201480025614.3 dated Nov. 28, 2016.
Office Action from Chinese Application No. 201480025359.2 dated Feb. 28, 2017.
Office Action from Chinese Application No. 201380076368.X dated Mar. 1, 2017.
Office Action from Chinese Application No. 201480025614.3 dated Jun. 9, 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 on Rejection in CN Application No. 201380047141.2 dated Sep. 7, 2017.
Office Action from U.S. Appl. No. 14/829,161 dated Jul. 28, 2017.
Notification of Reason for Refusal from KR Application No. 10-2015-7002697 dated Sep. 25, 2017.
Communication Pursuant to Article 94(3) EPC in EP Application No. 14732357.0 dated Feb. 12, 2018.
Office Action in JP Application No. 2015-562352 dated Feb. 6, 2018.
Office Action in JP Application No. 2015-562353 dated Feb. 6, 2018.
Office Action in JP Application No. 2015-562354 dated Feb. 6, 2018.
Office Action in JP Application No. 2015-562355 dated Feb. 6, 2018.
Office Action in CN Application No. 201710087175.4 dated Feb. 1, 2018.
Bargteil et al., “A Texture Synthesis Method for Liquid Animations,” Eurographics/ ACM SIGGRAPH Symposium on Computer Animation, 2006, pp. 345-351.
Aidun, Daryush K “Influence of simulated high-g on the weld size of Al—Li-Alloy” Acta Astronautica, vol. 48, No. 2-3, pp. 153-156, 2001.
Boss (engineering), Wikipedia, 1 page, printed Feb. 6, 2014.
CS Wave, Product Description, 2 pages, printed Jan. 14, 2015.
EnergynTech Inc.; website printout; http://www.energyntech.com./; Advanced Metals Processing Technology & Flexible Automation for Manufacturing; Virtual Welder; Virtual training system for beginning welders; 2 page; 2014.
EnergynTech Inc.; website printout; http://www.energyntech.com/Zipper.html; Zipper Robot Performing a HiDep Weld; 1 page 2014.
Erden, “Skill Assistance with Robot for Manual Welding”, Marie Curie Intra-European Fellowship, Project No. 297857, 3 pgs., printed Apr. 27, 2015.
EWM Virtual Welding Trainer, 2 pages, printed Jan. 14, 2015.
Fillet weld, Wikipedia, 3 pgs, printed Feb. 6, 2014.
Fronius, Virtual Welding, 8 pages, printed Jan. 14, 2015.
Fronius, Virtual Welding, The Welder Training of the Future, 8 page brochure, 2011.
The Goodheart-Wilcox Co., Inc., Weld Joints and Weld Types, Chaper 6; pp. 57-68; date unknown.
Kemppi ProTrainer, product data, 3 pages, printed Jan. 14, 2015.
Leap Motion, Inc., product information, copyright 2013, 14 pages.
Learning Labs, Inc., Seabery, Soldamatic Augmented Reality Welding Trainers, 4 pgs., printed Mar. 20, 2014.
Lim et al., “Automatic classification of weld defects using simulated data and MLP neural network”, Insight, vol. 49, No. 3, Mar. 2007.
Narayan et al., “Computer Aided Design and Manufacturing,” pp. 3-4, 14-15, 17-18, 92-95, and 99-100, Dec. 31, 2008.
NISRP—Virtual Welding—A Low Cost Virtual Reality Welder Training System—Phase II—Final Report; Feb. 29, 2012; Kenneth Fast, Jerry Jones, Valerie Rhoades; 53 pages.
Seabury Soluciones, SOLDAMATIC Welding Trainer Simulator, 30 pages, printed Jan. 14, 2015.
Terebes; Institute of Automation; University of Bremen; Project Motivation Problems Using Traditional Welding Masks; 2 page ; 2015.
Weld nut, Wikipedia, 2 pgs, printed Feb. 6, 2014.
Weldplus, Welding Simulator, 2 pages, printed Jan. 14, 2015.
WeldWatch Software/Visible Welding; website printout; http://visiblewelding.com/weldwatch-software/; 4 pages; 2015.
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.
Adams et., “Adaptively Sampled Particle Fluids,” ACM Transactions on Graphics, vol. 26, No. 3, Article 48, Jul. 2007, pp. 48.1-48.7.
Notice of Allowance from U.S. Appl. No. 15/077,532 dated Mar. 28, 2018.
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 ThreeDimensional 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, 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 '95, Apr. 19-21, 1995, in 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, 121-128.
Thurey et al., “Real-time Breaking Waves for Shallow Water Simulations,” Proceedings of the Pacific Conference on Computer Graphics and Applications, Maui, Hawaii, Oct. 29-Nov. 2, 2007, 8 pages.
Yaoming, “Applications of Microcomputer in Robot Technology,” Scientific and Technical Documentation Press, Sep. 1987, pp. 360-365.
Communication pursuant to Article 94(3) EPC from EP Application No. 15732934.3 dated Apr. 24, 2018.
Communication pursuant to Article 94(3) EPC from EP Application No. 15731664.7 dated Jul. 13, 2018.
Office Action from KR Application No. 10-2015-7003281 dated Aug. 13, 2018.
Office Action from CN Application No. 201580021822.0 dated Aug. 30, 2018.
Communication pursuant to Article 94(3) EPC from EP Application No. 10860823.3 dated Aug. 30, 2018.
Office Action from KR Application No. 10-2015-7003281 dated Feb. 22, 2019.
Notification of Reasons for Refusal from JP Application No. 2016-569042 dated Feb. 26, 2019.
First Office Action from CN Application No. 201710868734.5 dated Mar. 22, 2019.
Office Action from U.S. Appl. No. 16/021,576 dated Nov. 1, 2018.
Notice of Allowance from U.S. Appl. No. 16/021,576 dated Feb. 20, 2019.
Second Office Action from CN Application No. 201710868734.5 dated May 22, 2019.
Related Publications (1)
Number Date Country
20190295442 A1 Sep 2019 US
Divisions (2)
Number Date Country
Parent 15077532 Mar 2016 US
Child 16021576 US
Parent 15077532 Mar 2016 US
Child 16021576 US
Continuations (5)
Number Date Country
Parent 16021576 Jun 2018 US
Child 16439959 US
Parent 14293700 Jun 2014 US
Child 15077532 US
Parent 16021576 Jun 2018 US
Child 16439959 US
Parent 14293826 Jun 2014 US
Child 15077532 US
Parent 12499687 Jul 2009 US
Child 12966570 Dec 2010 US
Continuation in Parts (8)
Number Date Country
Parent 13543240 Jul 2012 US
Child 14293700 US
Parent 12966570 Dec 2010 US
Child 13543240 US
Parent 12499687 Jul 2009 US
Child 12966570 US
Parent 12499687 Jul 2009 US
Child 12966570 Dec 2010 US
Parent 16439959 US
Child 12966570 Dec 2010 US
Parent 13543240 Jul 2012 US
Child 14293826 US
Parent 12966570 Dec 2010 US
Child 13543240 US
Parent 12499687 Jul 2009 US
Child 12966570 US