A Digital Twin-Based Fault Diagnosis Framework for Bogies of High-Speed Trains

Abstract

To improve the safety of High-speed trains’ operation and reduce the bogie maintenance cost and failure rate, this paper proposes a digital twin-based framework for fault diagnosis of bogies. A digital twin system of the bogie is constructed from seven dimensions. Then a framework for the fault diagnosis of the high-speed train bogie is proposed, in which a multi-layer convolutional neural network is adopted for fault diagnosis.