Paper Title:
Multi-Fault Classifier Based on Support Vector Machine and Its Application
| Periodical | Key Engineering Materials (Volumes 293 - 294) |
|---|---|
| Main Theme | Damage Assessment of Structures VI |
| Edited by | W.M. Ostachowicz, J.M. Dulieu-Barton, K.M. Holford, M. Krawczuk and A. Zak |
| Pages | 483-492 |
| DOI | 10.4028/www.scientific.net/KEM.293-294.483 |
| Citation | Zhou Suo Zhang et al., 2005, Key Engineering Materials, 293-294, 483 |
| Online since | September, 2005 |
| Authors | Zhou Suo Zhang, Minghui Shen, Wenzhi Lv, Zheng Jia He |
| Keywords | Machinery Fault Diagnosis, Multi-Fault Classifier, Support Vector Machine (SVM) |
| Price | US$ 28,- |
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Abstract
Aiming at problem on limiting development of machinery fault intelligent diagnosis due to needing many fault data samples, this paper improves a multi-classification algorithm of support vector machine, and a multi-fault classifier based on the algorithm is constructed. Training the multi-fault classifier only needs a small quantity of fault data samples in time domain, and does not need signal preprocessing of extracting signal features. The multi-fault classifier has been applied to fault diagnosis of steam turbine generator, and the results show that it has such simple algorithm, online fault classification and excellent capability of fault classification as advantages.
