대한전자공학회:학술대회논문집 (Proceedings of the IEEK Conference)
- 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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- Pages.371-375
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- 2004
An Application of Support Vector Machines for Fault Diagnosis
- Hai Pham Minh (Dept of Automation in mining and petrolium, University of mining) ;
- Phuong Tu Minh (Faculty of information technology, Posts & Telecom. Institute of Technology)
- 발행 : 2004.08.01
초록
Fault diagnosis is one of the most studied problems in process engineering. Recently, great research interest has been devoted to approaches that use classification methods to detect faults. This paper presents an application of a newly developed classification method - support vector machines - for fault diagnosis in an industrial case. A real set of operation data of a motor pump was used to train and test the support vector machines. The experiment results show that the support vector machines give higher correct detection rate of faults in comparison to rule-based diagnostics. In addition, the studied method can work with fewer training instances, what is important for online diagnostics.