Risk function based fuzzy judge SVM algorithm and its application

Author

Zhai, Yongjie ; Li, Ruixin ; Wang, Dongfeng ; Han, Pu

Author_Institution

Power Eng. Dept., North China Electr. Power Univ., Baoding, China

Volume

3

fYear

2003

fDate

5-8 Oct. 2003

Firstpage

2406

Abstract

The concept of risk is introduced and a fuzzy judge based SVM (FJ-SVM) is put forward. Fuzzy theory is applied to improve the algorithm of SVM, the judge probability for fault is increased and diagnosis is more sensitive to fault. So the probability of mistaking fault for nature is decreased and the slight fault of facility can be identified correctly and timely. It is very important for improving the security of facility in the process. In this paper, the diagnosis example of working status in turbine axletree and the classification results are given to prove the feasibility of this algorithm. The algorithm of fuzzy samples based SVM (FS-SVM) is compared with FJ-SVM to indicate the rationality of FJ-SVM.

Keywords

fault diagnosis; fuzzy set theory; pattern classification; risk analysis; security; support vector machines; FJ-SVM; classification; fault diagnosis; fault judge property; fuzzy judge SVM algorithm; fuzzy theory; risk function; security; support vector machine; turbine axeltree; Fault diagnosis; Hydrogen; Machine learning algorithms; Power engineering; Quadratic programming; Risk management; Security; Support vector machine classification; Support vector machines; Turbines;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2003. IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-7952-7

Type

conf

DOI

10.1109/ICSMC.2003.1244244

Filename

1244244