Gas metal arc welding process monitoring and quality evaluation using neural networks
Source abstract
Abstract
To ensure product quality, it is essential to ensure process quality. Thus, early monitoring and detection of process disturbances in welding production lines are of great significance. The present paper introduces a neural network system for process monitoring and quality evaluation in gas metal arc welding. The system is based only on the measured and statistically processed data for welding voltage and short circuiting time. It is a self-organising feature map Kohonen network which can automatically recognise and classify process disturbances occurring during welding.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Welding Techniques and Residual Stresses · Advanced machining processes and optimization · Advanced Machining and Optimization Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Joining Technology, Shandong University of Technology, Jinan, 250061, China
Institute for Joining of Materials, University of Hannover, D–30159, Hannover, Germany
References (5)
Show source-provided references
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