Hybrid Prognostics Model for Life Cycle Management of High Speed Train

Abstract

As the volumes of service of subways and high-speed Electric Multiple Units (EMU) trains have significantly grown in recent years, the life cycle maintenance operation plan for these newly delivered rail vehicles becomes critical. Emerging structural health monitoring (SHM) technologies are introduced to revolutionize the operational procedures for the maintenance of these rail vehicles. To ensure the train safety during the whole lifetime of operation, an effective operation concept to integrate the on-train/online SHM systems with the existing scheduled maintenance procedures is crucially in demand. High-speed EMU trains are obligated with their maintenance schedules before they are delivered to passenger transportation services. The vision of a complete train lifecycle management model will involve multiple tiers in data collection, data distribution and information dissemination, data networking, big data storage and processing, and operational decision management and control