Study on weld quality control of resistance spot welding using a neuro-fuzzy algorithm

被引：0

作者：

Zhang, YS ^{[1
]}

Chen, GL ^{[1
]}

Lin, ZQ ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai 200030, Peoples R China

来源：

KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 3, PROCEEDINGS | 2004年 / 3215卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Resistance spot welding (RSW) is widely utilized as a joining technique for automobile industry. However, good weld quality evaluation method has not yet been developed in plant environment. It is necessary to achieve real-time inspection of RSW. This paper proposed a neuro-fuzzy algorithm to predict weld quality online. An experimental system was developed to measure electrode displacement curve. Accordingly based on electrode displacement curve nugget diameter will be inferred. Inference results showed that proposed neuro-fuzzy algorithm is suitable as a weld quality monitoring for resistance spot welding.

引用

页码：544 / 550

页数：7

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