A study on power quality diagnosis system using neural networks

Jin Su Kim, Young Il Kim, Kwang Soon Kim, Gi Ju Park

Research output: Contribution to journalArticle

Abstract

In this paper, we have studied the power quality(PQ) diagnosis system with the two methods for PQ diagnosis. One to Apply a regulation value in compliance with mathematics calculation, and the other Automatic identification using Neural network algorithm. Neural network algorithm is used for an automatic diagnosis of the PQ. The regulation proposed by IEEE 1159 Working group is applied for the precision of the diagnosis. In order to divide accurate segmentation, the algorithm for a computer training used the back propagation out of several neural network algorithms. We have configured the proto-type sample by using Labview and a programmed Neural Networks Algorithm using with C. And arbitrary electric Signal generated by OMICRON Company's CMC 256-6 for an efficiency test.

Original languageEnglish
Pages (from-to)1351-1358
Number of pages8
JournalTransactions of the Korean Institute of Electrical Engineers
Volume56
Issue number8
Publication statusPublished - 2007 Jan 1

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Power quality
Neural networks
Backpropagation
Industry

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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A study on power quality diagnosis system using neural networks. / Kim, Jin Su; Kim, Young Il; Kim, Kwang Soon; Park, Gi Ju.

In: Transactions of the Korean Institute of Electrical Engineers, Vol. 56, No. 8, 01.01.2007, p. 1351-1358.

Research output: Contribution to journalArticle

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