Research on health management of rail transit traction system based on big data

Reducing costs and increasing efficiency through intelligent operation and maintenance (IOM) is one of the most important ways to improve the sustainable development of China's urban rail transit. The rapid development of artificial intelligence and big data technology has facilitated the development of intelligent operation and health management of rail transit vehicles. This paper proposes a health management scheme for key components of the traction system based on big data such as traction system equipment operating status data, online fault information, historical fault data, and component failure mechanism experimental data. The scheme describes the construction method of the traction system health management platform, and elaborates the fault prediction model and health management scheme for key components of the traction system, including the inverter, traction motor, high-speed circuit breaker, support capacitor, and cooling fan, so as to provide technical support for intelligent operation and maintenance of railway vehicle traction system.