Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/29033
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dc.coverage.spatialNeuro fuzzy approaches for fault Detection in rotating machinesen_US
dc.date.accessioned2014-11-26T07:58:45Z-
dc.date.available2014-11-26T07:58:45Z-
dc.date.issued2014-11-26-
dc.identifier.urihttp://hdl.handle.net/10603/29033-
dc.description.abstractRotating machines are essential components in most of the newlinemanufacturing and production industries They are exposed to a variety of newlineenvironmental conditions These operating conditions coupled with natural newlineageing cause incipient faults in the machines The most common incipient newlinefaults are winding insulation failure and bearing wear With proper newlinemonitoring scheme if these faults were detected at their early stages the newlinemaintenance cost and down time can be reduced Many of the conventional newlinefault detection methods require the need of an expert to evaluate the machine newlinecondition The development of soft computing techniques in the area of newlinecomputer science motivated the researchers to use these techniques for newlineintelligent problem solving which exhibits the characteristics of human newlineintelligence The soft computing tools like neural networks and fuzzy system newlinehave been used in many engineering applications such as fault identification newlineand control of dynamic systems It is well known that a feed forward neural newlinenetwork is capable of approximating any continuous functions closely The newlineuse of fuzzy logic in control applications has tremendously increased over the newlinelast decades newline newlineen_US
dc.format.extentxxii, 147p.en_US
dc.languageEnglishen_US
dc.relationp136-143.en_US
dc.rightsuniversityen_US
dc.titleNeuro fuzzy approaches for fault Detection in rotating machinesen_US
dc.title.alternativeen_US
dc.creator.researcherDuraisamy Ven_US
dc.subject.keywordRotating machinesen_US
dc.description.notereference p136-143.en_US
dc.contributor.guideDevarajan Nen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Electrical and Electronics Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/09/2005en_US
dc.date.awarded30/09/2005en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Electrical and Electronics Engineering

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02_certificate.pdf5.78 kBAdobe PDFView/Open
03_abstract.pdf11.2 kBAdobe PDFView/Open
04_acknowledgement.pdf6.5 kBAdobe PDFView/Open
05_content.pdf73.96 kBAdobe PDFView/Open
06_chapter1.pdf175.88 kBAdobe PDFView/Open
07_chapter2.pdf235.94 kBAdobe PDFView/Open
08_chapter3.pdf674.55 kBAdobe PDFView/Open
09_chapter4.pdf125.08 kBAdobe PDFView/Open
10_chapter5.pdf25.11 kBAdobe PDFView/Open
11_reference.pdf33.28 kBAdobe PDFView/Open
12_publication.pdf11.91 kBAdobe PDFView/Open
13_vitae.pdf5.68 kBAdobe PDFView/Open


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