A Neuro-fuzzy Approach to Part Fitup Fault Control During Resistance Spot Welding Using Servo Gun

Resistance spot welding (RSW) is widely utilized as a joining technique for automobile industry. However, good weld quality control method has not yet been developed in plant environment when part fitup fault exists. This paper proposed a neuro-fuzzy algorithm to control weld quality by adjusting we...

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Bibliographic Details
Published inAdvances in Natural Computation pp. 1060 - 1068
Main Authors Zhang, Y. S., Chen, G. L
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Exact sciences and technology
Nugget Size
Resistance Spot
Resistance Spot Welding
Weld Nugget
Weld Quality
Fuzzy control
Fuzzy algorithm
Welded joint
Quality control
Automobile industry
Spot welding
Neural network
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ISBN9783540283201
354028320X
3540283234
9783540283232
ISSN0302-9743
1611-3349
DOI10.1007/11539902_135

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Summary:Resistance spot welding (RSW) is widely utilized as a joining technique for automobile industry. However, good weld quality control method has not yet been developed in plant environment when part fitup fault exists. This paper proposed a neuro-fuzzy algorithm to control weld quality by adjusting welding current. An experimental system was developed to measure electrode displacement curve. Accordingly based on electrode displacement curve optimal current for every cycle will be achieved under poor fitup fault condition. Results showed that proposed neuro-fuzzy system is suitable as a weld quality monitoring for resistance spot welding.
ISBN:9783540283201
354028320X
3540283234
9783540283232
ISSN:0302-9743
1611-3349
DOI:10.1007/11539902_135