TY - GEN
T1 - Neuro-fuzzy modeling of human welder's response to 3D weld pool surface in GTAW
AU - Liu, Yu Kang
AU - Zhang, Weijie
AU - Zhang, Yu Ming
PY - 2012
Y1 - 2012
N2 - Understanding and modeling of welder response to 3D weld pool surface help develop intelligent welding robotic systems and better train welders. In this paper, a welder's adjustment on the welding current as a response to the 3D weld pool surface as characterized by its width, length, and convexity is studied. A vision sensing system is developed to real-time measure the specular 3D weld pool in gas tungsten arc welding (GTAW). Experiments are designed to produce random changes in the welding speed resulting in fluctuating 3D weld pool surface. Adaptive Neuro Fuzzy Inference System (ANFIS) model is developed for the human welder response in order to correlate the current adjustment to the 3D weld pool surface. To justify the use of the neuro-fuzzy model, linear model has also been fitted and compared. It is found that the proposed ANFIS modeling can derive detailed correlation between the human welder's responses and the weld pool geometry and help better understand the nonlinear response of the human welder to 3D weld pool surfaces.
AB - Understanding and modeling of welder response to 3D weld pool surface help develop intelligent welding robotic systems and better train welders. In this paper, a welder's adjustment on the welding current as a response to the 3D weld pool surface as characterized by its width, length, and convexity is studied. A vision sensing system is developed to real-time measure the specular 3D weld pool in gas tungsten arc welding (GTAW). Experiments are designed to produce random changes in the welding speed resulting in fluctuating 3D weld pool surface. Adaptive Neuro Fuzzy Inference System (ANFIS) model is developed for the human welder response in order to correlate the current adjustment to the 3D weld pool surface. To justify the use of the neuro-fuzzy model, linear model has also been fitted and compared. It is found that the proposed ANFIS modeling can derive detailed correlation between the human welder's responses and the weld pool geometry and help better understand the nonlinear response of the human welder to 3D weld pool surfaces.
KW - 3D weld pool surface
KW - ANFIS
KW - human welder response
KW - neuro-fuzzy modeling
UR - https://www.scopus.com/pages/publications/84864830757
UR - https://www.scopus.com/inward/citedby.url?scp=84864830757&partnerID=8YFLogxK
U2 - 10.1109/ISIE.2012.6237204
DO - 10.1109/ISIE.2012.6237204
M3 - Conference contribution
AN - SCOPUS:84864830757
SN - 9781467301589
T3 - IEEE International Symposium on Industrial Electronics
SP - 875
EP - 880
BT - Proceedings - 2012 IEEE International Symposium on Industrial Electronics, ISIE 2012
T2 - 21st IEEE International Symposium on Industrial Electronics, ISIE 2012
Y2 - 28 May 2012 through 31 May 2012
ER -