Implementation of a Power Quality signal classification system using wavelet based energy distribution and neural network

Praveen Sebastian, Pramod Antony Dśa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper presents a classification system based on Wavelet Transform for normal Power Quality disturbances. The parameter used for the classification algorithm was energy distribution of detailed coefficient of Wavelet Transform up to 10 leveles of decomposition. Wavelet Transform parameters are effective in classification of disturbance waveforms. Artificial Neural Network was used for the classification purpose which gave satisfactory results. And the algorithm developed in MATLAB was interfaced with Data Acquisition devices to check its accuracy for online classification purpose.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE International Conference on Power and Advanced Control Engineering, ICPACE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages157-161
Number of pages5
ISBN (Electronic)9781479983704
DOIs
Publication statusPublished - 23-09-2015
Externally publishedYes
EventIEEE International Conference on Power and Advanced Control Engineering, ICPACE 2015 - Bengaluru, India
Duration: 12-08-201514-08-2015

Conference

ConferenceIEEE International Conference on Power and Advanced Control Engineering, ICPACE 2015
CountryIndia
CityBengaluru
Period12-08-1514-08-15

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Energy Engineering and Power Technology

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    Sebastian, P., & Dśa, P. A. (2015). Implementation of a Power Quality signal classification system using wavelet based energy distribution and neural network. In Proceedings of the 2015 IEEE International Conference on Power and Advanced Control Engineering, ICPACE 2015 (pp. 157-161). [7274935] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPACE.2015.7274935