Detection and Isolation of Multiple Incipient Sensor Faults with Application to High-Speed Railway Traction Motors

This paper addresses the problem of incipient fault detection and isolation for a class of Lipschitz nonlinear systems with multiple sensor biases and explores further results of total measurable fault information residual (ToMFIR). Firstly, state and output transformations are introduced to transform the original system into two subsystems. Since the effects of system disturbances on the residuals are completely decoupled, the incipient faults in the second subsystem can be detected by constructing ToMFIR. Further, sliding-mode observers (SMOs) based fault isolation scheme is designed to guarantee the isolation of multiple sensor faults even if they occur at the same time, which is the main contribution of this paper. Finally, application results conducted on a CRH2 high-speed railway traction motor are given to illustrate the effectiveness of the proposed approach.