Dynamic time-frequency analysis method for transient signal in power system network

Baoqun Zhao; Yuanyang Wang

doi:10.1117/12.806339

9 October 2008 Dynamic time-frequency analysis method for transient signal in power system network

Baoqun Zhao, Yuanyang Wang

Proceedings Volume 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment; 712803 (2008) https://doi.org/10.1117/12.806339
Event: Seventh International Symposium on Instrumentation and Control Technology, 2008, Beijing, China

Abstract

To improve the performance of power quality (PQ) disturbances classification, a novel approach using wavelet neural network is proposed. The wavelet transform can accurately localizes signal characteristics in time-frequency domains The wavelet transform is utilized to extract feature vectors of different PQ disturbances. These feature vectors then are applied to the neural network for training and disturbance pattern classification. By comparing with classic neural network, it is concluded that the proposed neural network has better data driven learning and local interconnections performance. The research results between the proposed method and the other existing method are discussed and the proposed method can provide accurate classification results. The simulation results demonstrate the proposed method gives a new way for identification and classification of power quality disturbances.

Citation Download Citation

Baoqun Zhao and Yuanyang Wang "Dynamic time-frequency analysis method for transient signal in power system network", Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 712803 (9 October 2008); https://doi.org/10.1117/12.806339

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