Computer diagnostics of resistance spot welding based on Hamming neural network

The article deals with utilizing the method of qualitative assessment of welding zone dynamic resistance based on a Hamming neural network to increase versatility and reliability of computer diagnostics for resistance spot welding. We propose a mechanism for encoding information on dynamic resistanc...

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Bibliographic Details
Published in:Journal of physics. Conference series 2019-10, Vol.1333 (4), p.42015
Main Authors: Klimov, V S, Klimov, A S, Mkrtychev, S V
Format: Article
Language:English
Subjects:
Algorithms
Error analysis
Hamming neural networks
Network reliability
Neural networks
Physics
Resistance spot welding
Welded joints
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Summary:The article deals with utilizing the method of qualitative assessment of welding zone dynamic resistance based on a Hamming neural network to increase versatility and reliability of computer diagnostics for resistance spot welding. We propose a mechanism for encoding information on dynamic resistance into bipolar signals required for the neural network tuning and operation. The algorithm of welding diagnostics was developed and implemented with specialized software. The results of the neural network training and testing are presented. As the analysis shows, the relative error in predicting destruction force does not exceed 10%. The approach proposed in this article complies with the requirements of ISO 9000:2015 standard for continuous monitoring and documentation of each welded connection and allows for increased accuracy of computer diagnostics of welds.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1333/4/042015