Application of the Extended $k$nn Method to Resistance Spot Welding Process Identification and the Benefits of Process Information

Author:

Koskimaki H.J.,Laurinen P.,Haapalainen E.,Tuovinen L.,Roning J.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Screening out potentially defective products in micro-transformer production by intelligently integrating mechanical and electronic signals;Engineering Applications of Artificial Intelligence;2023-11

2. Machine learning for intelligent welding and manufacturing systems: research progress and perspective review;The International Journal of Advanced Manufacturing Technology;2022-11-19

3. Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding;Journal of Intelligent Manufacturing;2022-03-02

4. A Novel Real-Time Wear Detection System for the Secondary Circuit of Resistance Welding Guns;Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics;2022

5. A Novel Method for the Real-time Force Losses Detection in Servo Welding Guns;Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics;2021

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