ToMFIR-based incipient fault detection and estimation for high-speed rail vehicle suspension system

High requirements on safety and reliability of the high-speed railway vehicle suspension (HRVS) system demand accurate detection and estimation of various incipient faults as early as possible under closed-loop control configurations. Firstly, a dynamic model of the suspension system for a three-car CRH2 multiple unit is set up, under which the external disturbances (i.e., track irregularities) and the actuator faults are further modeled. Then, an improved total measurable fault information residual (ToMFIR) based fault detection and estimation method is proposed, in which the restriction on fault type in the original method is removed. Finally, the obtained theoretical results are applied to a CRH2 HRVS simulation system. Results show that the proposed method can detect and estimate several frequent incipient faults effectively, outperforming the conventional observer-based or output residual-based fault detection and estimation methods. (C) 2015 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.