Study on real-time measurement of nugget diameter for resistance spot welding using a neuro-fuzzy algorithm

Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510) Pub Date : 2004-05-18 DOI:10.1109/IMTC.2004.1351535

Zhong-qin Lin, Yansong Zhang, Guanlong Chen, Yongbing Li

引用次数: 16

Abstract

Resistance spot welding (RSW) is still the most successful sheet metal joining method in the automobile industry. However, an effective quality evaluation method has not yet been developed. Real-time quality inspection of RSW is necessary in order to deal with all kinds of problems during welding. This paper developed an experimental system using for measuring electrode displacement. Accordingly based on electrode displacement curve proposes a neuro-fuzzy algorithm to inference nugget diameter online. Inference results showed that among the total number of specimens, 88% were successfully inferred within a range of 1.5% error.

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基于神经模糊算法的电阻点焊熔核直径实时测量研究

电阻点焊(RSW)仍然是汽车工业中最成功的钣金连接方法。然而，目前还没有一种有效的质量评价方法。为了及时处理焊接过程中出现的各种问题，对焊丝进行实时质量检测是十分必要的。研制了一种测量电极位移的实验系统。据此，提出了一种基于电极位移曲线的神经模糊在线推断熔核直径的算法。推断结果表明，在样本总数中，88%的样本在1.5%的误差范围内被推断成功。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510)

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