Fault detection of rail vehicle suspension system based on CPCA

The suspension system plays a crucial role of the rail vehicles. The fault detection of the suspension system is an effective way to ensure the security of the safe, stable operation of rail vehicles. This paper concerns the fault detection issue of rail vehicle suspension systems with the consensus principle components analysis (CPCA). The signal information used in the fault detection is obtained from the SIMPACK and MATLAB co-simulation environment. In this paper, two typical primary spring and damper fault with coefficient reduction of 5% and 25% are detected successfully using CPCA. Compared with DPCA, the simulation results show that the CPCA method can detect smaller fault with faster response speed.