Computational intelligent Techniques for power transformer fault identification and classification using DGA
| dc.contributor.guide | Rajaram, M | en_US |
| dc.coverage.spatial | Information and Communication Engineering | en_US |
| dc.creator.researcher | Indra, Getzy David | en_US |
| dc.date.accessioned | 2014-09-08T10:05:49Z | |
| dc.date.available | 2014-09-08T10:05:49Z | |
| dc.date.awarded | 30-10-2012 | en_US |
| dc.date.completed | 01-10-2012 | en_US |
| dc.date.issued | 2014-09-08 | |
| dc.date.registered | n.d. | en_US |
| dc.description.abstract | This research is a proposed methodology for diagnosing the faults newlinethat occur in a Power Transformer by analyzing the Dissolved Gas Analysis newlineDGA data taken from the oil immersed transformers The various intelligent newlinetechniques used for diagnosing the faults include Fuzzy Logic and Artificial newlineNeural Networks along with multi classifier systems and principal component newlineAnalysis The diagnosis of various faults is carried out using DGA with newlineInternational Electrotechnical Commission IEC Institute of Electrical and newlineElectronic Engineers IEEE standards which occur due to the thermal and newlineelectrical stresses inside the transformer oil A study of the literature related newlineto the area of research, spanning approximately 47 years showed that the newlinelimitations in decision making have improved year after year by way of newlinesubstituting new methods by the researchers newline newline | en_US |
| dc.description.note | reference p.166-175 | en_US |
| dc.format.accompanyingmaterial | None | en_US |
| dc.format.dimensions | 23cm. | en_US |
| dc.format.extent | xvii, 177p. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10603/24751 | |
| dc.language | English | en_US |
| dc.publisher.institution | Faculty of Information and Communication Engineering | en_US |
| dc.publisher.place | Chennai | en_US |
| dc.publisher.university | Anna University | en_US |
| dc.relation | - | en_US |
| dc.rights | university | en_US |
| dc.source.university | University | en_US |
| dc.subject.keyword | Dissolved Gas Analysis | en_US |
| dc.subject.keyword | Information and Communication engineering | en_US |
| dc.subject.keyword | Institute of Electrical and Electronic Engineers | en_US |
| dc.subject.keyword | International Electrotechnical Commission | en_US |
| dc.title | Computational intelligent Techniques for power transformer fault identification and classification using DGA | en_US |
| dc.title.alternative | - | en_US |
| dc.type.degree | Ph.D. | en_US |
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