scholarly journals Motion Signal Processing for a Remote Gas Metal Arc Welding Application

Robotics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 30
Author(s):  
Lucas Christoph Ebel ◽  
Patrick Zuther ◽  
Jochen Maass ◽  
Shahram Sheikhi
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Evaluation System ◽  
Gas Metal Arc Welding ◽  
Hand Movement ◽  
Skilled Worker ◽  
Robot Controller ◽  
Motion Signal ◽  
Metal Arc Welding ◽  
Tool Trajectory

This article covers the signal processing for a human–robot remote controlled welding application. For this purpose, a test and evaluation system is under development. It allows a skilled worker to weld in real time without being exposed to the associated physical stress and hazards. The torch movement of the welder in typical welding tasks is recorded by a stereoscopic sensor system. Due to a mismatch between the speed of the acquisition and the query rate for data by the robot control system, a prediction has to be developed. It should generate a suitable tool trajectory from the acquired data, which has to be a C 2 -continuous function. For this purpose, based on a frequency analysis, a Kalman-Filter in combination with a disturbance observer is applied. It reproduces the hand movement with sufficient accuracy and lag-free. The required algorithm is put under test on a real-time operating system based on Linux and Preempt_RT in connection to a KRC4 robot controller. By using this setup, the welding results in a plane are of good quality and the robot movement coincides with the manual movement sufficiently.

An Evaluation System of Pulsed GMAW Process

2013 ◽  
Vol 483 ◽  
pp. 599-602
Author(s):  
Ying Gao ◽  
Jing Hua Han ◽  
Li Yan Lou ◽  
Huan Li
Keyword(s):  
Arc Welding ◽  
Evaluation System ◽  
High Speed ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Electric Signal ◽  
Characteristic Parameters ◽  
Display Module ◽  
Metal Arc Welding ◽  
Labview Platform

A process evaluation system for pulsed gas metal arc welding (GMAW-P) based on the LabVIEW platform has been developed. This system is comprised of two modules, a simultaneous display module and a data analysis module. Using these modules, the system can not only provide a comprehensive direct viewing display of the welding electric signal and high speed camera photo, but also can analyze the characteristic parameters of the welding process. The results show that the system works properly.

Droplet Tracking in Double-Electrode GMAW

2011 ◽  
Vol 418-420 ◽  
pp. 1180-1183
Author(s):  
Zhen Zhou Wang ◽  
Yang Yu ◽  
Shu Jun Chen ◽  
Yu Ming Zhang
Keyword(s):  
Real Time ◽  
Gas Metal Arc Welding ◽  
Metal Transfer ◽  
Least Square ◽  
Experimental Results ◽  
Original Position ◽  
Tracking Accuracy ◽  
Tracking Method ◽  
Metal Arc Welding ◽  
Double Electrode

Controlled metal transfer in gas metal arc welding (GMAW) and its modifications including the double-electrode GMAW implies controllable heat and mass inputs and better assured weld quality. To understand, analyze, and control the metal transfer process, the droplet should be monitored in real time. Due to the fast development and transfer of the droplet, the monitoring speed is a key. A tracking method that takes advantage of results from previous images to speed the processing is advantageous. In this paper, Kalman Filter tracking and Least Square Match tracking algorithms are developed to track a droplet in the innovative double-electrode GMAW after its original position is identified. Experimental results showed that the Kalman Filtering algorithm is not suitable for this application due to the limited life span of each droplet. Instead, the Least Square Match algorithm is effective in tracking a droplet if a universal droplet template can be found and defined. However, there are no universal templates suitable for all the droplets. Hence, a real time template updating and LSM tracking method is proposed to track the droplet effectively. Experimental results verified its tracking accuracy.

Real-time sensing of gas metal arc welding process – A literature review and analysis

2021 ◽  
Vol 70 ◽  
pp. 452-469
Author(s):  
Yongchao Cheng ◽  
Rui Yu ◽  
Quan Zhou ◽  
Heming Chen ◽  
Wei Yuan ◽  
...  
Keyword(s):  
Literature Review ◽  
Real Time ◽  
Arc Welding ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Metal Arc Welding ◽  
Arc Welding Process

Virtual Reality Welder Training

2006 ◽  
Vol 22 (03) ◽  
pp. 126-138 ◽  
Author(s):  
Nancy C. Porter ◽  
J. Allan Cote ◽  
Timothy D. Gifford ◽  
Wim Lam
Keyword(s):  
Neural Network ◽  
Virtual Reality ◽  
Real Time ◽  
Arc Welding ◽  
Gas Metal Arc Welding ◽  
Travel Speed ◽  
Virtual Reality Technology ◽  
Metal Arc Welding ◽  
Welding Torch

Based on the orientation and travel speed of a welding torch, virtual reality technology simulates gas metal arc welding in near-real time using a neural network.

Investigation on arc light intensity in gas metal arc welding. Part 2: Application to weld seam tracking

1997 ◽  
Vol 211 (5) ◽  
pp. 355-363 ◽  
Author(s):  
C D Yoo ◽  
H-K Sunwoo ◽  
K-I Koh
Keyword(s):  
Signal Processing ◽  
Light Intensity ◽  
Arc Welding ◽  
Weld Seam ◽  
Gas Metal Arc Welding ◽  
Welding Current ◽  
Seam Tracking ◽  
Processing Methods ◽  
Metal Arc Welding ◽  
Signal Processing Methods

The arc sensor has been widely used to detect the weld seam by monitoring welding current or voltage variation during weaving in gas metal arc welding (GMAW). In this work, the arc light intensity and welding resistance are utilized as the seam tracking sensor. Signal characteristics of the arc light intensity and welding resistance are compared when argon and CO2 gas are used for shielding. The performance of signal processing methods such as the least squares and integration methods is evaluated experimentally. It is found that the arc light intensity provides higher quality signals than welding resistance with CO2 gas. While both signal processing methods demonstrate almost equal seam tracking capabilities, the integration method appears to be more efficient because of the short computation time.

scholarly journals Digitalized Evaluation of Welder Skill by using Cyclogram Characteristics

2019 ◽  
Vol 269 ◽  
pp. 07004
Author(s):  
Seamkong Kuoch ◽  
Eakkachai Warinsiriruk ◽  
Sutep Joy-A-Ka
Keyword(s):  
Signal Processing ◽  
Evaluation Method ◽  
Physical Simulation ◽  
Gas Metal Arc Welding ◽  
Hand Movement ◽  
Welding Process ◽  
Welding Current ◽  
High Sensitivity ◽  
Weld Quality ◽  
Robot Welding

This paper proposes a new evaluation method for welder skill in Gas Metal Arc Welding (GMAW) process in term of studying the natural hand-movement that affect the signal processing. Weld quality of GMAW generally depends on welder skill to maintain the uniform of hand movement. Therefore, the welder skill is considered as the critical point to maintain the weld quality. Hence, welding current and voltage signal could be an alternative way for monitoring and assessing the skill of welder based on the signal variation of the welding process. This research defines in two stages, first is the physical-simulation using robot welding Fanuc Arc Mate 100iB and monitoring the signal using Cyclogram technique. Second is comparing the Cyclogram characteristic of robot welding and manual welder. By using the data acquired, the characteristic of Cyclogram was analyzed by varying Torch angle change (W1) and Torch-height change (W2) to investigate the signal processing. Furthermore, the data of current and voltage were generated as a quantitative method to determine the size of Cyclogram. The results show that the method capable of differentiating the two beginner welders compare to the robot welding performance based area of Cyclogram characteristic. Finally, the Cyclogram could be a novel tool for monitoring and evaluating the welder skill with high sensitivity to detect hand motion.

Virtual Reality Welder Training

2005 ◽  
Author(s):  
Nancy C. Porter ◽  
J. Allan Cote ◽  
Timothy D. Gifford ◽  
Wim Lam
Keyword(s):  
Neural Network ◽  
Virtual Reality ◽  
Real Time ◽  
Arc Welding ◽  
Gas Metal Arc Welding ◽  
Travel Speed ◽  
Virtual Reality Technology ◽  
Metal Arc Welding ◽  
Welding Torch

Based on the orientation and travel speed of a welding torch, virtual reality technology simulates gas metal arc welding in near-real time using a neural network.

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