Title :
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
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;
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
DOI :
10.1109/ICMLC.2010.26
