Fault Diagnosis of High-Speed Train Traction Converter System Based on Random Forest Algorithm

• Published in: 2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS) pp. 1591 - 1596
• Main Authors: Chen, Xi, Zhang, Lu, Chen, Shaozhi, Zhong, Maiying
• Format: Conference Proceeding
• Language: English
• Published: IEEE 17.05.2024
• Subjects: Fault diagnosis; Feature extraction; Feature selection; Insulated gate bipolar transistors; Inverters; Radio frequency; Random forest; Software packages; Time-frequency analysis; Traction converter system

Traction converter system is a key part of the energy conversion of high-speed trains, and the fault diagnosis of the traction converter system has become crucial with the increasing requirements on its reliability. However, the system operates in a complex environment and is susceptible to the coup...