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Fuzzy Support Vector Machine and Its Application to Mechanical Condition Monitoring.

Authors :
Wang, Jun
Liao, Xiaofeng
Yi, Zhang
Zhang, Zhousuo
Hu, Qiao
He, Zhengjia
Source :
Advances in Neural Networks - ISNN 2005 (9783540259121); 2005, p937-942, 6p
Publication Year :
2005

Abstract

Fuzzy support vector machine (FSVM) is applied in this paper, in order to resolve problem on bringing different loss for classification error to different fault type in mechanical fault diagnosis. Based on basic principle of FSVM, a method of determining numerical value range of fuzzy coefficient is proposed. Classification performance of FSVM is tested and verified by means of simulation data samples. A fuzzy fault classifier is constructed, and applied to condition monitoring of flue-gas turbine set. The results show that fuzzy coefficient can indicate importance degree of data sample, and classification error rate of important data sample can be decreased. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540259121
Database :
Supplemental Index
Journal :
Advances in Neural Networks - ISNN 2005 (9783540259121)
Publication Type :
Book
Accession number :
32862721
Full Text :
https://doi.org/10.1007/11427391_150