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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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FEATURED ARTICLE

Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
Issue 4/2016

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2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  1/2017 - 7

Vibration Based Broken Bar Detection in Induction Machine for Low Load Conditions

MATIC, D. See more information about MATIC, D. on SCOPUS See more information about MATIC, D. on IEEExplore See more information about MATIC, D. on Web of Science, KANOVIC, Z. See more information about KANOVIC, Z. on SCOPUS See more information about KANOVIC, Z. on SCOPUS See more information about KANOVIC, Z. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,535 KB) | Citation | Downloads: 148 | Views: 208

Author keywords
motor, bar, vibration, fault, detection

References keywords
diagnosis(11), induction(10), rotor(8), detection(8), broken(8), fault(7), sanchez(6), pineda(6), motor(6), vibration(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-02-28
Volume 17, Issue 1, Year 2017, On page(s): 49 - 54
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.01007
Web of Science Accession Number: 000396335900007

Abstract
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A new method for broken bar detection, based on vibration signal analysis, is presented in this paper. While there are several methods for broken bar detection at low slip based on the current signal analysis, detection based on vibration signals attracts much less attention. In the current paper, detection of the broken bar was conducted by observing fault frequency content of the modulus of the analytical vibration signal. A broken bar feature is extracted from low frequency range even for low slip conditions. Although this method is successfully used for broken bar detection based on current signal analysis, it is important to verify the method when vibration signal is measured. Procedure is verified in a real industrial environment for induction motor of 3.15 MW.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Full Text] [Web of Science Times Cited 9] [SCOPUS Times Cited 9]


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[CrossRef] [SCOPUS Times Cited 2]


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[CrossRef] [Web of Science Times Cited 205] [SCOPUS Times Cited 293]


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[12] H. Saavedra, J. R. Riba, L. Romeral, "Detection of Inter-turn Faults in Five-Phase Permanent Magnet Synchronous Motors," Advances in Electrical and Computer Engineering, vol. 14, no. 4, pp. 49-54, 2014.
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[13] M. Pineda-Sanchez, M. Riera-Guasp, J. Roger-Folch, J. A. Antonino-Daviu, J. Perez-Cruz, R. Puche-Panadero, "Diagnosis of Induction Motor Faults in Time-Varying Conditions Using the Polynomial-Phase Transform of the Current," IEEE Transactions on Industrial Electronics, vol. 58, no. 4, pp. 1428-1439, 2011.
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[14] J. Pons-Llinares, J. A. Antonino-Daviu, M. Riera-Guasp, M. Pineda-Sanchez, V. Climente-Alarcon, "Induction Motor Diagnosis Based on a Transient Current Analytic Wavelet Transform via Frequency B-Splines," IEEE Transactions on Industrial Electronics, vol. 58, no. 5, pp. 1530-1544, 2011.
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[15] V. Choqueuse, M. E. H. Benbouzid, Y. Amirat, S. Turri, "Diagnosis of three-phase electrical machines using multidimensional demodulation techniques," IEEE Transactions on Industrial Electronics, vol. 59, no. 4, pp. 2014-2023, 2012.
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[26] D. Reljic, D. Jerkan, D. Marcetic, Dj. Oros, "Broken Bar Fault Detection in IM Operating Under No-load Condition," Advances in Electrical and Computer Engineering, vol. 16, no. 4, pp. 63-70, 2016.
[CrossRef] [Full Text] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]




References Weight

Web of Science® Citations for all references: 1,317 TCR
SCOPUS® Citations for all references: 1,746 TCR

Web of Science® Average Citations per reference: 49 ACR
SCOPUS® Average Citations per reference: 65 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-06-27 00:12 in 186 seconds.




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