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DC Field | Value | Language |
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dc.contributor.author | Samaga, R. | - |
dc.contributor.author | Vittal, K.P. | - |
dc.date.accessioned | 2020-03-30T09:58:40Z | - |
dc.date.available | 2020-03-30T09:58:40Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | 2011 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2011, 2011, Vol., , pp.115-119 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/7224 | - |
dc.description.abstract | Non invasive fault detection unit for an induction motor has become an integral part of industrial drives. As the current is the primary quantity to get affected by the non uniform air gap flux, Motor Current Signature Analysis is preferred as compared to vibration analysis for mixed eccentricity fault detection in an induction motor. In this paper, Power Spectral Density analysis is performed on the stator current data samples obtained from modeling and simulation of the induction motor. An Eccentricity Severity Factor is defined and is shown that this factor increases with increase of air gap eccentricity in the machine. Hence it can be used as a measure to assess the degree of eccentricity in the machine. � 2011 IEEE. | en_US |
dc.title | Air gap mixed eccentricity severity detection in an induction motor | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
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