Decoupling of Demagnetization Characteristics to Improve the Turn-to-Turn Fault Detection in PMSM Using Machine Learning Methods
Author:
Affiliation:
1. Nanyang Technological University, SG,Rolls-Royce@NTU Corporate Lab.
2. Rolls-Royce Electrical, SG
3. School of EEE, Nanyang Technological University, SG
Funder
National Research Foundation (NRF)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10311571/10311610/10312485.pdf?arnumber=10312485
Reference17 articles.
1. Incipient Fault Detection in Stator Windings of an Induction Motor Using Stockwell Transform and SVM
2. Neural Network-Based Diagnostic Tool for Detecting Stator Inter-Turn Faults in Line Start Permanent Magnet Synchronous Motors
3. Robustness Optimization of Model Predictive Current Control for PMSM Drives Considering Dynamic Response Influence
4. Influence of Introducing the Rotor MMF Harmonic on Torque Performance of Spoke Type Permanent Magnet Motor With FSCW
5. Multiscale Kernel-Based Residual CNN for Estimation of Inter-Turn Short Circuit Fault in PMSM
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