title: Multiple incipient sensor faults diagnosis with application to high-speed railway traction devices.
abstract: This paper deals with the problem of incipient fault diagnosis for a class of Lipschitz nonlinear systems with 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. The first subsystem is subject to system disturbances and free from sensor faults, while the second subsystem contains sensor faults but without any system disturbances. Sensor faults in the second subsystem are then formed as actuator faults by using a pseudo-actuator based approach. Since the effects of system disturbances on the residual are completely decoupled, multiple incipient sensor faults can be detected by constructing ToMFIR, and the fault detectability condition is then derived for discriminating the detectable incipient sensor faults. Further, a sliding-mode observers (SMOs) based fault isolation scheme is designed to guarantee accurate isolation of multiple sensor faults. Finally, simulation results conducted on a CRH2 high-speed railway traction device are given to demonstrate the effectiveness of the proposed approach.
authors.affiliation: College of Automation Engineering and Jiangsu Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, PR China.
authors.forename: Yunkai
authors.initials: Y
authors.lastname: Wu
authors.affiliation: College of Automation Engineering and Jiangsu Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, PR China. Electronic address: binjiang@nuaa.edu.cn.
authors.forename: Bin
authors.initials: B
authors.lastname: Jiang
authors.affiliation: College of Automation Engineering and Jiangsu Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, PR China.
authors.forename: Ningyun
authors.initials: N
authors.lastname: Lu
authors.affiliation: School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, PR China.
authors.forename: Hao
authors.initials: H
authors.lastname: Yang
authors.affiliation: College of Automation Engineering and Jiangsu Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, PR China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhou
keywords: High-speed railway traction device; Incipient fault diagnosis; Nonlinear system; Sensor bias; Total measurable fault information residual (ToMFIR)