Dynamics Performance Evaluation and Alarm Method of High-speed Train in Service

Dynamics performance is one of the most critical qualities of railway vehicle, which is closely related to the security, reliability. Nowadays, with the long term service of the vehicle, some parameters vary form the nominal values, that is, degradation and failure occur, which will result in the deterioration of the dynamics performance and may even cause accident. But current maintenance decision is mainly based on simple threshold value of single parameter, which is too simple compared with the complexity of the dynamics system. The central principle of our strategy is that the maintenance decision-making power of dynamics-related parts should be given back to dynamics performance itself, and current maintenance system can be reformed and optimized by Condition Based Maintenance. This paper proposes a dynamics performance evaluation and alarm method for high-speed train in service, to assess the vehicle dynamics performance based on service data including detectable factors and regular ones. The former type of factor is mainly composed of wheelset size and circular irregularity parameters, while the wheel profile, spring stiffness and damper damping can be estimated on the basis of the wear and degradation law. The multi-body dynamics model is built up, and various operating conditions are considered. Several dynamics performance indexes are obtained from the calculation results, including kinetic stability, derailment safety, ride comfort, wheel-rail interaction and bogie vibration. And the corresponding alarm and maintenance decision is raised. Finally, an actual case is studied to illustrate the effect of the method. Through this method, vehicle dynamics performance can be assessed considering both the coupled relationship of various factors and multifarious operating conditions from the system global view, which can avoid the weakness of current simple threshold and lead to more reasonable operation management and maintenance decision.