Web based automatic classification of power quality disturbances using the S-transform and a rule based expert system

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The detection and classification of power quality problems are important issues for electronic systems. This paper deals with a new approach for the automatic detection and classification of power quality disturbances through the Internet by combining the S-transform, a rule based expert system and a MATLAB web server. The S-transform is used to obtain the time frequency characteristics of power quality events under noisy conditions, and a set of features is extracted for pattern classification of power quality disturbances. A rule-based expert system is also developed in which the system classifies various power quality disturbances. Finally, a MATLAB web server is used to integrate the graphical and computational process with remote access through the internet. Our test results illustrate the effectiveness and robustness of the proposed method for automatic power quality disturbance classification through the Internet. 1548-7741/

Original languageEnglish
Pages (from-to)2375-2383
Number of pages9
JournalJournal of Information and Computational Science
Volume8
Issue number12
Publication statusPublished - Dec 2011

Fingerprint

knowledge-based system
Power quality
Expert systems
Mathematical transformations
Internet
MATLAB
Servers
Pattern recognition
electronics
event

Keywords

  • MATLAB web server
  • Power quality
  • Rule based expert system
  • S-transform
  • Time-frequency analysis

ASJC Scopus subject areas

  • Information Systems
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics
  • Library and Information Sciences

Cite this

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abstract = "The detection and classification of power quality problems are important issues for electronic systems. This paper deals with a new approach for the automatic detection and classification of power quality disturbances through the Internet by combining the S-transform, a rule based expert system and a MATLAB web server. The S-transform is used to obtain the time frequency characteristics of power quality events under noisy conditions, and a set of features is extracted for pattern classification of power quality disturbances. A rule-based expert system is also developed in which the system classifies various power quality disturbances. Finally, a MATLAB web server is used to integrate the graphical and computational process with remote access through the internet. Our test results illustrate the effectiveness and robustness of the proposed method for automatic power quality disturbance classification through the Internet. 1548-7741/",
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