NDLI: Application of neural network combined with improved algorithm in distorted waveform analysis

Content Provider	IEEE Xplore Digital Library
Author	Wei Liao Hua Wang Pu Han
Copyright Year	2010
Description	Author affiliation: Hebei University of Engineering, Handan 056038, China (Wei Liao; Hua Wang) \|\| North China Electric Power University, Baoding 071003, China (Pu Han)
Abstract	The issue of power quality has attracted considerable attention from utilities and customers due to fast development of power system industry. It is vital to ensure power quality by means of advanced technology which can monitor, locate and classify disturbances with measurement approaches and instruments. A novel approach for the power quality disturbances detection and investigation using wavelet transform and neural network is proposed. The wavelet transform technology provides an effective means for analysis of non-stationarity and transient signal in terms of shifted and scaled versions. The detection and localization processes are a series of convolution and decimation processes at each corresponding scale, which provide feature vectors as input variables for neural network designed for disturbance pattern recognition. The wavelet network combines advantages of wavelet transformation for purposes of feature extraction and with the characteristic decision capabilities of neural network. In process of training phase, the evolutionary algorithm is used to complete the network parameters adjustment. The processing phase performs waveform recognition and the output of the processing phase is the type of the disturbances. The simulation results show that the proposed method has the ability of recognizing and classifying different power disturbance types efficiently.
Starting Page	2525
Ending Page	2528
File Size	188932
Page Count	4
File Format	PDF
ISBN	9781424451814
DOI	10.1109/CCDC.2010.5498767
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Instruments wavelet transform Wavelet analysis neural network evolutionary algorithm Power system measurements Power measurement Power quality disturbance Neural networks Power quality feature extraction Power system analysis computing Distortion measurement Monitoring pattern recognition
Content Type	Text
Resource Type	Article

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