Title :
Fault diagnosis of Rail Vehicle Suspension Systems by using GLRT
Author :
Wei, Xiukun ; Liu, Hai ; Qin, Yong
Author_Institution :
State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
Abstract :
In this paper, we consider fault detection issue for Rail Vehicle Suspension Systems. The faults considered are the secondary vertical damper fault, the vertical spring fault and sensor failure. A Kalman filter is applied to generate the residual for fault detection. When there is a detectable fault, the observer sends an alarm signal if the residual evaluation is larger than a predefined threshold. The effectiveness of the proposed approach is demonstrated by simulation results for several fault scenarios.
Keywords :
Kalman filters; damping; fault diagnosis; light rail systems; observers; sensors; shock absorbers; springs (mechanical); suspensions (mechanical components); GLRT; Kalman filter; alarm signal; fault detection; fault diagnosis; generalized likelihood ratio test; light rail vehicle suspension system; observer; residual evaluation; secondary vertical damper fault; sensor failure; vertical spring fault; Acceleration; Damping; Fault detection; Rail transportation; Springs; Suspensions; Vehicles; GLRT; Light vehicle suspension system; fault diagnosis;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968516
