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| Application in Power Quality Analysis Based on Multifractal Detrended Fluctuation Analysis and Improved Decision Tree |
| ZHANG Shu-qing1,ZHANG Yun1,LIU Hai-tao1,HU Hao2,LI Hua3,YAO Yu-yong3,LIU Yong3,WANG Tao3 |
1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Institute of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China
3. Tangshan Power Supply Company of North Hebei Electric Power Co. Ltd, Tangshan, Hebei 063000, China |
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Abstract Six common power quality signals are analyzed by multi-fractal and trend fluctuation analysis, which proves that the power quality signal has multiple fractal features. Based on this, a power quality feature extraction method based on multi-fractal detrended wave analysis is proposed. Multi-fractal spectrum parameters (hqmax、αmin、α0) and signal energy E are selected as feature vector matrix, combined with improved decision tree classification for power quality. Analysis and identification. The method is compared with DTCWT, HHT and EEMD. The results show that the proposed method shows better recognition results and provides a new idea for feature extraction of power quality signals.
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Received: 15 November 2019
Published: 20 April 2021
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2021, Vol. 42 
