<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>Sharif University of Technology</PublisherName>
				<JournalTitle>Scientia Iranica</JournalTitle>
				<Issn>1026-3098</Issn>
				<Volume>15</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2008</Year>
					<Month>04</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>New Wavelet-Based Approach for Internal Fault Current Identication in Power Transformers</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage></FirstPage>
			<LastPage></LastPage>
			<ELocationID EIdType="pii">2964</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>H.</FirstName>
					<LastName>Monsef</LastName>
<Affiliation>Department of Electrical Engineering,University of Tehran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2009</Year>
					<Month>05</Month>
					<Day>30</Day>
				</PubDate>
			</History>
		<Abstract>This paper demonstrates a novel approach for the dierential protection of power transformers.
This method uses the Wavelet Transform (WT) and the Adaptive Network-based Fuzzy Inference
System (ANFIS) to detect a fault current from an inrush current. The proposed method has
been designed, based on the dierences between the amplitudes of wavelet transform coecients
in a special band of frequency that is caused by faults and inrush currents. The performance of
this algorithm has been simulated and tested under dierent conditions of the switching on of
power transformers, using the PSCAD/EMTDC environment software.</Abstract>
<ArchiveCopySource DocType="pdf">https://scientiairanica.sharif.edu/article_2964_b30a76c9bb0b466e32ead8eab8c54faa.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
