A Robust Data-driven Fault Detection Framework for Traction Dual Rectifiers
Author:
Affiliation:
1. Southwest Jiaotong University,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle,Chengdu,China
2. Aalborg University,AAU Energy,Aalborg,Denmark
Funder
National Natural Science Foundation of China
China Scholarship Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10567049/10567050/10567256.pdf?arnumber=10567256
Reference12 articles.
1. Fuzzy Observer-Based Control for the Traction Dual Rectifiers in High-Speed Train
2. A Voltage-Based Hierarchical Diagnosis Approach for Open-Circuit Fault of Two-Level Traction Converters
3. An Open-Switch Fault Diagnosis Method for Single-Phase PWM Rectifier Using a Model-Based Approach in High-Speed Railway Electrical Traction Drive System
4. A High-Accuracy-Light-AI Data-Driven Diagnosis Method for Open-Circuit Faults in Single-Phase PWM Rectifiers
5. VWM-DCRNN: A Method of Combining Signal Processing With Deep Learning for Fault Diagnosis in Single-Phase PWM Rectifier
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