Convolutional Neural Network-Based Online Stator Inter-Turn Faults Detection for Line-Connected Induction Motors
Author:
Affiliation:
1. Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK, Canada
2. Faculty of Electrical Engineering, Shahid Abbaspour School of Engineering, Shahid Beheshti University, Tehran, Iran
Funder
Natural Science and Engineering Research Council of Canada's Discovery
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/28/10535351/10423188.pdf?arnumber=10423188
Reference43 articles.
1. A Study on Electric Energy Consumption of Manufacturing Companies in the German Industry with the Focus on Electric Drives
2. Fundamentals of a motor thermal model and its applications in motor protection
3. Induction Motors Fault Diagnosis Using Finite Element Method: A Review
4. Stator and rotor turn‐to‐turn fault detection in wound rotor induction machines based on the air‐gap magnetic field distortion
5. Reliable Detection of Stator Interturn Faults of Very Low Severity Level in Induction Motors
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