An Improved Lightweight Variant of EfficientNetV2 Coupled With Sensor Fusion and Transfer Learning Techniques for Motor Fault Diagnosis
Author:
Affiliation:
1. School of Automation, Wuxi University, Wuxi, Jiangsu, China
2. School of Automation, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Funder
National Natural Science Foundation of China
“Qing Lan Project” of Jiangsu Universities, the Ministry of Education’s Industry-University Cooperation Collaborative Breeding Program
Innovation and Entrepreneurship Program for Jiangsu University Students
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/6287639/10380310/10552743.pdf?arnumber=10552743
Reference38 articles.
1. Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges
2. Real-time fault detection and process control based on multi-channel sensor data fusion
3. Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion
4. Estimation of Tool Wear and Surface Roughness Development Using Deep Learning and Sensors Fusion
5. Image fusion meets deep learning: A survey and perspective
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