DocumentCode :
1539392
Title :
Neurofuzzy model-based weld fusion state estimation
Author :
Kovacevic, Radovan ; Zhang, Yu M.
Author_Institution :
Welding Res. & Dev. Lab., Kentucky Univ., Lexington, KY, USA
Volume :
17
Issue :
2
fYear :
1997
fDate :
4/1/1997 12:00:00 AM
Firstpage :
30
Lastpage :
42
Abstract :
Proper fusion is crucial in generating a sound weld. Successful control of the fusion state requires accurate measurements of both the topside and back-side bead widths. A top-side sensor-based system is preferred so that the sensor can be attached to and moved with the torch. Thus, the system must be capable of estimating the back-side bead width with high accuracy. Because skilled human operators can estimate the fusion state from the observed weld pool, a neurofuzzy system is developed to infer the backside bead width from the pool geometry in this work. It is found that the back-side bead width can be estimated with satisfactory accuracy by the identified neurofuzzy model. Thus, accurate feedback of the fusion state can be provided for its control
Keywords :
arc welding; computer vision; fuzzy control; fuzzy systems; knowledge based systems; neurocontrollers; real-time systems; state estimation; state feedback; back-side bead widths; computer vision; feedback; model-based state estimation; neurofuzzy system; pool geometry; real time system; sensor-based system; weld fusion; weld pool width control; Acoustic sensors; Control systems; Fusion power generation; Geometry; Humans; Neurofeedback; Sensor systems; Solids; State estimation; Welding;
fLanguage :
English
Journal_Title :
Control Systems, IEEE
Publisher :
ieee
ISSN :
1066-033X
Type :
jour
DOI :
10.1109/37.581293
Filename :
581293
Link To Document :
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