An Analysis Method of Principal Components of Power Quality Based on Fast S-transform
To handle the problems in power quality analysis such as a large amount of calculation for S-transform, requiring setting feature parameters to the support vector machine classification, etc, it proposed a new approach which combined the fast S-transform (FST) algorithm with the principal component...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2013-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2095-3631.2013.06.008 |
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| Summary: | To handle the problems in power quality analysis such as a large amount of calculation for S-transform, requiring setting feature parameters to the support vector machine classification, etc, it proposed a new approach which combined the fast S-transform (FST) algorithm with the principal component analysis (PCA) to classify the power quality disturbances. Firstly, the module coefficients of several voltage disturbances were extracted from FST domain. Then, PCA was applied to descend dimension and extract the main feature components and the projection matrix was obtained accordingly. Finally, the voltage signals were projected and classified by the nearest neighbor classifier. The simulation results show that the feature components of the FST module coefficients for voltage disturbances are focused on low-frequency band, so that the algorithm has the advantages of high accuracy, short runtime and somewhat anti-interference ability. Furthermore, It is a good choice to deal with PQDs via real-time identification. |
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| ISSN: | 2096-5427 |