Application Research on Deep Convolution Neural Network Based Fault Diagnosis Technology for Traction Converter
Converter is a key component of traction system in electric locomotive. The fault of converter can easily lead to the paralysis of train operation and is one of the most dangerous failures of electric locomotive. In order to avoid poor generalization of feature selection in expert experience and sim...
Saved in:
| Main Authors: | LI Chen, ZHANG Huiyuan, LIU Yong, YANG Weifeng |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2021-01-01
|
| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.05.010 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Dual-Level Intelligent Architecture-Based Method for Coupling Fault Diagnosis of Temperature Sensors in Traction Converters
by: Yunxiao Fu, et al.
Published: (2025-07-01) -
Auxiliary Inverter Over-current Fault Analysis in Integrated Traction Converter System
by: REN Xiaodong, et al.
Published: (2018-01-01) -
A Survey of Fault Diagnosis Technology for Converter
by: WANG Zhihong, et al.
Published: (2014-01-01) -
Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter
by: ZHAN Yanhao, et al.
Published: (2021-01-01) -
Fault Diagnosis Technology for Auxiliary Converter Unit
by: 王佳佳, et al.
Published: (2010-01-01)