Fault detection of urban rail vehicle suspension system based on acceleration measurements

This paper concerns the fault detection issue of urban rail vehicle suspension systems. The underlying vehicle system are equipped with only accelerator sensors in the four corners of the carbody, the front and trail bodgie, respectively. A mathematical model is developed for the considered vehicle suspension system. The faults considered are the vertical damper fault and vertical spring fault. A Kalman filter is applied to generate the residual and its change is detected by using the GLRT method for fault detection. When there is a detectable fault, the detector sends an alarm signal if the residual evaluation is larger than a predefined threshold. By using the professional multi-body simulation tool, SIMPACK, the effectiveness of the proposed approach is demonstrated by simulation results for several fault scenarios.