TY - GEN
T1 - Control of human welder's arm movement in manual gas tungsten arc welding (GTAW) process
AU - Huang, Ning
AU - Liu, Yukang
AU - Chen, Shujun
AU - Zhang, Yuming
PY - 2014
Y1 - 2014
N2 - Manual GTAW is commonly used in industry especially for applications which require high weld quality. Unfortunately, skills needed for critical welding operations typically require a long time to develop. In this paper a control system was developed to assist the welder in regulating his/her arm movement (i.e., the welding speed) in real-time. Training experiments are conducted by a human welder, whose movement speed (system output) is accurately tracked by a Leap motion sensor. Visual commands (arrows with both direction and amplitude) are displayed on a monitor, which is used as system input. Modeling trials suggest that Moving Average (MA) models are not sufficient in capturing the human movement dynamics. Auto-Regressive Moving Average (ARMA) models are then identified using Least Squares (LS), and F-test is used to select the model order. Pole placement controller is proposed to control the human welder arm movement. Controller simulation shows that the proposed controller is able to drive the system to desired speed with no static error and acceptable regulating speed. To further demonstrate the effectiveness of the proposed controller, tracking experiments are conducted by a human welder to track various set-points. It is observed that with the proposed pole placement controller, the welder can track the desired speed with acceptable accuracy. The proposed welding speed assistance system may be beneficial to develop the next generation intelligent welding machines.
AB - Manual GTAW is commonly used in industry especially for applications which require high weld quality. Unfortunately, skills needed for critical welding operations typically require a long time to develop. In this paper a control system was developed to assist the welder in regulating his/her arm movement (i.e., the welding speed) in real-time. Training experiments are conducted by a human welder, whose movement speed (system output) is accurately tracked by a Leap motion sensor. Visual commands (arrows with both direction and amplitude) are displayed on a monitor, which is used as system input. Modeling trials suggest that Moving Average (MA) models are not sufficient in capturing the human movement dynamics. Auto-Regressive Moving Average (ARMA) models are then identified using Least Squares (LS), and F-test is used to select the model order. Pole placement controller is proposed to control the human welder arm movement. Controller simulation shows that the proposed controller is able to drive the system to desired speed with no static error and acceptable regulating speed. To further demonstrate the effectiveness of the proposed controller, tracking experiments are conducted by a human welder to track various set-points. It is observed that with the proposed pole placement controller, the welder can track the desired speed with acceptable accuracy. The proposed welding speed assistance system may be beneficial to develop the next generation intelligent welding machines.
UR - http://www.scopus.com/inward/record.url?scp=84906670623&partnerID=8YFLogxK
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U2 - 10.1109/AIM.2014.6878181
DO - 10.1109/AIM.2014.6878181
M3 - Conference contribution
AN - SCOPUS:84906670623
SN - 9781479957361
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 824
EP - 829
BT - AIM 2014 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics
T2 - 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2014
Y2 - 8 July 2014 through 11 July 2014
ER -