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Hilbert Transform based Fuzzy Expert System for Diagnosing and Classifying Power Quality Disturbances

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
P. Kalyana Sundaram, R. Neela

Kalyana P Sundaram and R Neela. Hilbert Transform based Fuzzy Expert System for Diagnosing and Classifying Power Quality Disturbances. International Journal of Computer Applications 142(3):48-55, May 2016. BibTeX

	author = {P. Kalyana Sundaram and R. Neela},
	title = {Hilbert Transform based Fuzzy Expert System for Diagnosing and Classifying Power Quality Disturbances},
	journal = {International Journal of Computer Applications},
	issue_date = {May 2016},
	volume = {142},
	number = {3},
	month = {May},
	year = {2016},
	issn = {0975-8887},
	pages = {48-55},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2016909729},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This paper presents a new technique for diagnosis and classification of power quality disturbances. The proposed method applies Hilbert transform to analyze the distorted voltage waveforms and then extract their features. The distorted voltage waveforms are generated by Matlab simulink on the test system. The extracted input features such as standard deviation and variances are given as inputs to the fuzzy-expert system that uses some rules to classify the Power Quality disturbances. Fuzzy classifier has been constructed to classify both the single and combined form power quality disturbances. The results clearly show that the proposed method has the ability to diagnosize and classify Power Quality problems. The results obtained by the proposed method are validated by comparing them against Hilbert Transform based neural classifiers.


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Power quality, Power quality disturbances, Hilbert transforms, Fuzzy-expert system.