Welding quality analysis and prediction based on deep learning
Author:
Affiliation:
1. Wuhan University of Technology,Department of Mechanical Engineering,Wuhan,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9699991/9699993/09700080.pdf?arnumber=9700080
Reference7 articles.
1. Deep features based on a DCNN model for classifying imbalanced weld flaw types
2. Penetration quality prediction of asymmetrical fillet root welding based on optimized BP neural network
3. Use of modified electrode caps for surface quality welds in resistance spot welding;wojciech;Journal of Manufacturing Processes,2016
4. Resistance variations during spot welding;roberts;Welding Journal,1951
5. Adaptive resistance spot welding method that reduces the shunting effect
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2. Challenges for Predictive Quality in Multi-stage Manufacturing: Insights from Literature Review;Proceedings of the 3rd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things;2023-12-04
3. Low-Voltage Electrical Product Quality Problem-Solving Based on Improved Deep Structured Semantic Model;2023 IEEE 19th International Conference on Automation Science and Engineering (CASE);2023-08-26
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