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Power quality disturbances events recognition based on S-transform and probabilistic neural network

  • Harbin Institute of Technology
  • Jilin Institute of Chemical Technology
  • State Grid Corporation of China

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Power quality (PQ) events recognition is the most important research area of power quality control. A novel high performance classification system based on S-transform and probabilistic neural network is proposed in this paper. Firstly, S-transform processes the original PQ signals into a complex matrix named S-matrix. The time and frequency features of disturbances signal are extracted from the S-matrix. Then, the selected subset of features is used as the input vector of the classifier. Finally, the probabilistic neural network classifier is trained and tested by the simulated simples. The simulation results show the effectiveness of the new approach.

Original languageEnglish
Title of host publicationLife System Modeling and Intelligent Computing - Int. Conf. on Life System Modeling and Simulation, LSMS 2010 and Int. Conf. on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010
Pages207-212
Number of pages6
EditionPART 1
DOIs
StatePublished - 2010
Event2010 International Conference on Life System Modeling and Simulation, LSMS 2010 and the 2010 International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010 - Wuxi, China
Duration: 17 Sep 201020 Sep 2010

Publication series

NameCommunications in Computer and Information Science
NumberPART 1
Volume97 CCIS
ISSN (Print)1865-0929

Conference

Conference2010 International Conference on Life System Modeling and Simulation, LSMS 2010 and the 2010 International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010
Country/TerritoryChina
CityWuxi
Period17/09/1020/09/10

Keywords

  • S-transform
  • power quality (PQ)
  • power quality disturbances
  • probabilistic neural network

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