At present, most of the high-speed train power supply equipment operation and maintenance business follows the traditional management model, which has the following characteristics: First, there are many planned maintenance, periodic maintenance, fault repair, and less online detection and status maintenance; second, the maintenance work generally adopts manual work, and the manual supervision method is less efficient; third, success or failure is judged only based on fault indicators, and the maintenance process data is not precise enough; fourth, there is a lack of big data system platforms and intelligent applications for monitoring, intelligent processing, analyzing operating status trends and intelligent fault diagnosis of traction power supply equipment.