NDLI: Dynamic feature extraction of power disturbance signal based on time-frequency technology

Content Provider	IEEE Xplore Digital Library
Author	Wang Yuguo Zhao Wei Xie Yan
Copyright Year	2009
Description	Author affiliation: Hebei University of Engineering, Handan 056038, China (Wang Yuguo; Zhao Wei; Xie Yan)
Abstract	The growing concern for power quality issues from both utilities and power users is generated by proliferation of power electronic devices and nonlinear loads in power system network. Therefore, the techniques for power quality monitoring and power disturbance mitigation are capturing increasing attention. A novel approach for the power quality disturbances recognition using wavelet transform and neural network is proposed. The wavelet transform is used to complete feature extraction and can accurately localizes the characteristics of transient signal both in time and frequency domains. These feature vectors are input variables for neural network training and the neural network structure is designed for disturbance pattern recognition. Therefore, the wavelet network combines advantages of wavelet transformation for purposes of feature extraction and selection with the characteristic decision capabilities of neural network approaches. During the training process, the wavelet network learns adequate decision functions and arbitrarily complex decision regions defined by the weight coefficients. The simulation results demonstrate the proposed method gives a new way for signal analysis and pattern recognition of power quality disturbances.
Starting Page	2300
Ending Page	2303
File Size	97887
Page Count	4
File Format	PDF
ISBN	9781424427222
DOI	10.1109/CCDC.2009.5192777
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Power system dynamics wavelet transform Time frequency analysis Power electronics Pattern recognition Nonlinear dynamical systems training algorithm neural network Power quality disturbance Power quality Neural networks feature extraction Feature extraction Power generation pattern recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in