Overview of fault prognosis for traction systems in high-speed trains: A deep learning perspective

Author:

Zhong KaiORCID,Wang Jiayi,Xu Shuiqing,Cheng Chao,Chen Hongtian

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference85 articles.

1. Data-driven designs of fault detection systems via neural network-aided learning;Chen;IEEE Trans. Neural Netw. Learn. Syst.,2021

2. A single-side neural network-aided canonical correlation analysis with applications to fault diagnosis;Chen;IEEE Trans. Cybern.,2021

3. JITL-MBN: A real-time causality representation learning for sensor fault diagnosis of traction drive system in high-speed trains;Chen;IEEE Trans. Neural Netw. Learn. Syst.,2022

4. A review of fault detection and diagnosis for the traction system in high-speed trains;Chen;IEEE Trans. Intell. Transp. Syst.,2019

5. Edge computing-aided framework of fault detection for traction control systems in high-speed trains;Chen;IEEE Trans. Veh. Technol.,2019

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