Artificial neural networks for real-time fault diagnostics in asynchronous electric drives

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dc.contributor.authorChetat, B.
dc.contributor.authorHoja, J.
dc.date.accessioned2015-09-17T11:19:26Z
dc.date.available2015-09-17T11:19:26Z
dc.date.issued2003
dc.description.abstractThe possibility of developing diagnostic systems for controllable asynchronous electric drives on the basis of neural networks combined in a decision-making system for the identification of various defects and determination of a rational diagnostic sequence is considered. The number of determinable diagnostic variables of the object permitting relatively reliable defect detection under external perturbations is optimizeden_US
dc.identifier.issn10683712
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/2225
dc.language.isoenen_US
dc.publisherRussian Electrical Engineeringen_US
dc.relation.ispartofseriesVolume 74, Issue 12, 2003;PP. 21-26
dc.subjectDecision makingen_US
dc.subjectElectric convertersen_US
dc.subjectFailure analysisen_US
dc.subjectShort circuit currentsen_US
dc.titleArtificial neural networks for real-time fault diagnostics in asynchronous electric drivesen_US
dc.typeArticleen_US

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