DocumentCode
2313053
Title
Application of support vector machines to sensor fault diagnosis in ESP system
Author
Zheng, Saui-Bo ; Zheng-Zhi Han ; Tang, Hou-Jun ; Zhang, Yong
Author_Institution
Sch. of Electr. & Inf. Eng., Shanghai Jiao Tong Univ., China
Volume
6
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
3334
Abstract
Sensor prediction models in ESP system are constructed with support vector machines (SVMs) regression algorithm. Thus SVMs are used as residual generator via analytical redundancy of the sensors. DAGSVM classification algorithm fulfills sensor fault isolation. The research´s result shows the application of SVMs to sensor fault diagnosis in ESP system is effective and feasible.
Keywords
automobiles; control engineering computing; fault diagnosis; sensors; stability; support vector machines; time-varying systems; ESP system; electronic stability program; residual generator; sensor fault diagnosis; sensor fault isolation; support vector machines regression algorithm; Automotive engineering; Electrostatic precipitators; Fault diagnosis; Mechanical sensors; Redundancy; Safety; Sensor systems; Sensor systems and applications; Stability; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1380354
Filename
1380354
Link To Document