DocumentCode :
2893525
Title :
Harmonic analysis approach based on wavelet transform and neural network
Author :
Maofa, Gong ; Xiaocong, Liu ; Longqing, Chai ; Liming, Gong ; Guoliang, Li
Author_Institution :
Coll. of Inf. & Electr. Eng., Shandong Univ. of Sci. &Technol., Qingdao, China
fYear :
2011
fDate :
6-9 July 2011
Firstpage :
574
Lastpage :
576
Abstract :
The paper presents a new approach based on wavelet and neural network for the estimation of harmonic components in the power system. This proposed method preprocesses the signal using wavelet analysis to get feature extraction of signals. Then it analyses and calculates the feature vector by the artificial neural network (ANN), and the harmonic components of the current can be got. The combination of wavelet and ANN make up for each other´s deficiencies and it can solve the frequency aliasing effectively. The structure of this method and the specific algorithm are presented. The simulation model is also built and the results show that the harmonic components can be detected at real time with high precision.
Keywords :
feature extraction; harmonic analysis; neural nets; power system harmonics; wavelet transforms; artificial neural network; feature extraction; feature vector; frequency aliasing; harmonic analysis; harmonic components estimation; power system harmonics; wavelet transform; Estimation; Harmonic analysis; Power system harmonics; Wavelet analysis; Wavelet packets; Harmonic Analysis; Neural Network; Wavelet Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on
Conference_Location :
Weihai, Shandong
Print_ISBN :
978-1-4577-0364-5
Type :
conf
DOI :
10.1109/DRPT.2011.5993958
Filename :
5993958
Link To Document :
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