A FAULT DIAGNOSIS METHOD BASED ON SUPPORT VECTOR MACHINE OPTIMIZED BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
In order to improve diagnosis accuracy of support vector machine（SVM） in mechanical fault diagnosis, fruit fly optimization algorithm was improved and a fault diagnosis method based on SVM optimized by improved FOA was proposed. In improved FOA（IFOA）, history location information was introduced when...
| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Strength
2019-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.011 |
| Summary: | In order to improve diagnosis accuracy of support vector machine（SVM） in mechanical fault diagnosis, fruit fly optimization algorithm was improved and a fault diagnosis method based on SVM optimized by improved FOA was proposed. In improved FOA（IFOA）, history location information was introduced when fruit fly update its location, thus improved diversity of fruit fly group and the ability of jump out local optimum and better parameters of SVM can be obtained and classification performance of SVM was improved. Gear fault diagnosis experiment results validated that IFOA improved the identification accuracy of SVM and has a certain superiority when compared with some other methods. |
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| ISSN: | 1001-9669 |