SVM-Based Multiclass Cost-sensitive Classification with Reject Option for Fault Diagnosis of Steam Turbine Generator

Author

Zou, Chao ; Zheng, En-hui ; Xu, Hong-Wei ; Chen, Le

Author_Institution

Coll. of Mechatron. Eng., China Jiliang Univ., Hangzhou, China

fYear

2010

fDate

9-11 Feb. 2010

Firstpage

66

Lastpage

70

Abstract

The steam turbine generator faults not only damage the generator itself, but also cause outages and loss of profits, for this reason, many researchers work on the fault diagnosis. But misdiagnosing may also lead to serious losses. In order to improve the diagnosis reliability and reduce the loss caused by misdiagnosis, in this paper, cost integrated multiclass SVM with reject option (CIMC-SVM) is proposed. Experimental results show that CIMC-SVM is able to improve the diagnosis reliability and minimize the average cost.

Keywords

cost reduction; fault diagnosis; fault tolerance; losses; profitability; steam turbines; support vector machines; turbogenerators; SVM based multiclass cost-sensitive classification; average cost; cost integrated multiclass SVM; diagnosis reliability; fault diagnosis; misdiagnosis loss; outage loss; profit loss; reject option; steam turbine generator; Costs; Fault diagnosis; Machine learning; Nuclear power generation; Power generation; Rotors; Support vector machine classification; Support vector machines; Turbines; Voting; SVM; cost-sensitive; fault diagnosis; multiclass; reject option;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Computing (ICMLC), 2010 Second International Conference on

Conference_Location

Bangalore

Print_ISBN

978-1-4244-6006-9

Electronic_ISBN

978-1-4244-6007-6

Type

conf

DOI

10.1109/ICMLC.2010.26

Filename

5460768