Jang, W.-C. and Kang, M. and Kim, J. and Kim, J.-M. and Nguyen, H.N. (2014) Reliable condition monitoring of an induction motor using a genetic algorithm based method. In: 2014 IEEE Symposium on Computational Intelligence for Engineering Solutions, CIES 2014, 9 December 2014 through 12 December 2014.
Reliable condition monitoring of an induction motor using a genetic algorithm based method.pdf
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Abstract
Condition monitoring is a vital task in the maintenance of industry machines. This paper proposes a reliable condition monitoring method using a genetic algorithm (GA) which selects the most discriminate features by taking a transformation matrix. Experimental results show that the features selected by the GA outperforms original and randomly selected features using the same k-nearest neighbor (k-NN) classifier in terms of convergence rate, the number of features, and classification accuracy. The GA-based feature selection method improves the classification accuracy from 3% to 100% and from 30% to 100% over the original and randomly selected features, respectively. © 2014 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Divisions: | Faculties > Faculty of Control Engineering |
| Identification Number: | 10.1109/CIES.2014.7011828 |
| Uncontrolled Keywords: | Classification (of information); Condition monitoring; Feature extraction; Induction motors; Linear transformations; Motion compensation; Nearest neighbor search; Classification accuracy; Convergence rates; Feature selection methods; K-nearest neighbor classifier; K-nearest neighbors; Transform matrices; Transformation matrices; Genetic algorithms |
| Additional Information: | Conference code: 110167. Language of original document: English. |
| URI: | http://eprints.lqdtu.edu.vn/id/eprint/9998 |
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