Fault diagnosis of regenerative water heater based-on multi-class support vector machines

Authors:
Lei Wang;Rui-Qing Zhang
Affiliations:
Thermal Power Engineering Department, Shenyang Institute of Engineering, Shenyang, Liaoning, China;Thermal Power Engineering Department, Shenyang Institute of Engineering, Shenyang, Liaoning, China
Venue:
ICNC'09 Proceedings of the 5th international conference on Natural computation
Year:
2009

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Abstract

The main idea of multi-class support vector machines (SVMs) is described. a multi-class model for regenerative water heater fault diagnosis is presented combining the fuzzy logic and SVMs. The typical faults set of regenerative water heater is built after thoroughly analyzing the relationships between performance parameters and faults. Finally, the model is inspected and verified by an example in a regenerative water heater of the turbine unit, the result of diagnosis shows that it is simple and practical; it can identify the regenerative water heater faults effectively.