DocumentCode :
1612572
Title :
Online fault diagnosis for hydraulic disc brake system using feature extracted from model and an SVM classifier
Author :
Rui Lian ; Zhengguo Xu ; Jiangang Lu
Author_Institution :
Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou, China
fYear :
2013
Firstpage :
228
Lastpage :
232
Abstract :
This paper describes an online diagnosis approach for leakage and oil contamination faults in hydraulic disc brake system using feature extracted from model and an SVM classifier. A feature signal, which can reflect both faults directly, is derived from the mechanism model of hydraulic cylinder. Feature parameters extracted from the feature signal are related to the magnitude and the category of the faults. An SVM classifier is used to isolate the two kinds of faults. After identifying the fault category, the fault magnitude can be estimated based on the relationship between the fault magnitude and the feature parameter. Simulation results show that this method fulfills the function of online fault diagnosis effectively.
Keywords :
brakes; contamination; fault diagnosis; feature extraction; hydraulic systems; leak detection; mechanical engineering computing; signal classification; support vector machines; SVM classifier; fault category identification; fault magnitude; feature extraction; feature signal; hydraulic cylinder; hydraulic disc brake system; leakage faults; oil contamination faults; online diagnosis approach; online fault diagnosis; Circuit faults; Contamination; Fault detection; Fault diagnosis; Feature extraction; Integrated circuit modeling; Support vector machines; SVM classifier; feature; hydraulic disc brake system; leakage; oil contamination; online fault diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chinese Automation Congress (CAC), 2013
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-0332-0
Type :
conf
DOI :
10.1109/CAC.2013.6775733
Filename :
6775733
Link To Document :
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