Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/60954
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dc.contributor.authorChen, S.-
dc.contributor.authorZivanovic, R.-
dc.date.issued2010-
dc.identifier.citationMeasurement, 2010; 43(7):887-900-
dc.identifier.issn0263-2241-
dc.identifier.issn1873-412X-
dc.identifier.urihttp://hdl.handle.net/2440/60954-
dc.description.abstractThe limitation of data window length in induction machine broken rotor bar diagnostics is a real challenge in practice. Sideband frequencies which are used as broken rotor bar indicators are very close to the fundamental frequency and have low magnitude. Traditional spectral analysis approach such as Discrete Fourier Transform (DFT) can be inaccurate in these conditions due to its inherent drawbacks such as the requirement of long data window for high resolution and the side lobe leakage in frequency domain. In this paper, a high-resolution spectral analysis technique, Prony Analysis (PA), is proposed for broken rotor bar detection in induction machines. The method is described and demonstrated in detail, validated by experimental data, and compared with DFT. Results clearly indicate the advantages of PA over DFT in terms of maintaining a high resolution with a much shorter window and a better frequency estimate accuracy with the same window length. © 2010 Elsevier Ltd. All rights reserved.-
dc.description.statementofresponsibilityShuo Chen and Rastko Živanović-
dc.language.isoen-
dc.publisherElsevier Sci Ltd-
dc.rightsCopyright © 2010 Elsevier Ltd. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.measurement.2010.03.006-
dc.subjectInduction machine-
dc.subjectBroken rotor bar-
dc.subjectProny-
dc.subjectFrequency estimation-
dc.titleEstimation of frequency components in stator current for the detection of broken rotor bars in induction machines-
dc.typeJournal article-
dc.identifier.doi10.1016/j.measurement.2010.03.006-
pubs.publication-statusPublished-
Appears in Collections:Aurora harvest
Electrical and Electronic Engineering publications

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