Title :
Online measurement of weld fusion state using weld pool image and neurofuzzy model
Author :
Kovacevic, Radovan ; Zhang, Yu M.
Author_Institution :
Center for Robotics & Manuf. Syst., Kentucky Univ., Lexington, KY, USA
Abstract :
Proper fusion is crucial in generating a sound weld. Successful control of the fusion state requires accurate measurements of both the top-side and back-side bead widths. A top-side sensor based system is preferred so the sensor can be attached to and move with the torch. Thus, the system must be capable of estimating the back-side bead width using top-side parameters. Because skilled human operators can estimate the fusion state through observation of the weld pool, in this work a neurofuzzy system is developed to infer the back-side bead width from the pool geometry. It is found that the back-side bead width can be estimated with high accuracy by the identified neurofuzzy model. Thus, accurate feedback of the fusion state can be provided for controlling the fusion state
Keywords :
arc welding; computer vision; feedback; fuzzy control; fuzzy neural nets; identification; image recognition; multivariable control systems; real-time systems; arc welding; bead widths; feedback; fuzzy control; identification; image processing; multivariable control system; neurofuzzy model; online measurement; pool geometry; weld fusion state control; weld pool image; Acoustic sensors; Control systems; Geometry; Humans; MIMO; Neurofeedback; Sensor systems; State estimation; State feedback; Welding;
Conference_Titel :
Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-2978-3
DOI :
10.1109/ISIC.1996.556219