High-speed Train Intelligent Maintenance Pattern and Edge-computing Perception Model
Peng Sun, Weijiao Zhang, Zhikai Jia · 2021
Aiming at the key requirements for the advanced security risks prevention and the smart-precise maintenance management of high-speed trains, given the EMU (Electric Multiple Units) trains management characteristics such as complex dynamic and static scenarios, business collaboration, and cross-specialty cooperation in conurbation transportation, a “Cloud-Edge-Terminal” architecture of intelligent EMU maintenance, an IoT data collection system, and its maintenance organization patterns are researched; an FSM-based (Finite State Machine based) intelligent maintenance edge-perception model and related state transition definition are proposed; which support big-data analysis and intelligent maintenance decision for EMU. A simulation experiment was performed to verify the efficiency, stability, and availability of the system and method in this paper. It has important significance for railway rolling stocks maintenance and other vertical industries that need intelligent reengineering.