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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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  1/2017 - 7

 HIGHLY CITED PAPER 

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 in 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: 765 | Views: 1,721

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
SCOPUS ID: 85014214831

Abstract
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Full text preview
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

[1] J. M. Picazo-Rodenas, J. Antonino-Daviu, V. Climente-Alarcon, "Combination of Noninvasive Approaches for General Assessment of Induction Motors," IEEE Transactions on Industry Applications, vol. 51, no. 3, pp. 2172-2180, 2015.
[CrossRef] [Web of Science Times Cited 42]


[2] F. Kulic, D. Matic, B. Dumnic, V. Vasic, "Optimal Fuzzy Controller Tuned by TV-PSO for Induction Motor Speed Control," Advances in Electrical and Computer Engineering, vol. 11, no. 1, pp. 49-54, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 11]


[3] V. Ghorbanian, J. Faiz, "A survey on time and frequency characteristics of induction motors with broken rotor bars in line-start and inverter-fed modes," Mechanical Systems and Signal Processing, vol. 54-55, pp. 427-456, 2015.
[CrossRef] [Web of Science Times Cited 47]


[4] S. Nandi, "Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review," IEEE Transactions on Energy Conversion, vol. 20, no. 4, 2005.
[CrossRef] [Web of Science Times Cited 1217]


[5] M. R. Mehrjou, N. Mariun, N. Misron, M. A. M. Radzi, "A survey of broken rotor bar detection using PT and HT in squirrel cage electrical machine," in Proc. IEEE Student Conference on Research and Development, Kuala Lumpur, Malaysia, 13-14 Dec. 2015, pp. 506 - 510.
[CrossRef]


[6] M. E. H. Benbouzid, G. B. Kliman, "What Stator Current Processing-Based Technique to Use for Induction Motor Rotor Faults Diagnosis?," IEEE Transactions on Energy Conversion, vol. 18, no. 2, pp. 238 - 244, 2003.
[CrossRef] [Web of Science Times Cited 303]


[7] R. Puche-Panadero, M. Pineda-Sanchez, M. Riera-Guasp, J. Roger-Folc, E. Hurtado-Perez and J. Perez-Cruz, "Improved resolution of the MCSA method via Hilbert transform, enabling the diagnosis of rotor asymmetries at very low slip," IEEE Transactions on Energy Conversion, vol. 24, no. 1, pp. 52-59, 2009.
[CrossRef] [Web of Science Times Cited 165]


[8] D. Matic, F. Kulic, M. Pineda-Sanchez, I. Kamenko, "Support vector machine classifier for diagnosis in electrical machines: Application to broken bar," Expert Systems with Applications, vol. 39, no. 10, pp. 8681-8689, 2012.
[CrossRef] [Web of Science Times Cited 48]


[9] R. Gopinath, C. S. Kumar, K. I. Ramachandran, V. Upendranath, P. V. R. Sai-Kiran, "Intelligent fault diagnosis of synchronous generators," Expert Systems With Applications, vol. 45, pp. 142-149, 2016.
[CrossRef] [Web of Science Times Cited 16]


[10] F. D. Samirmi, W. Tang, Q. Wu, "Fuzzy Ontology Reasoning for Power Transformer Fault Diagnosis," Advances in Electrical and Computer Engineering, vol. 15, no. 4, pp. 107-114, 2015.
[CrossRef] [Full Text] [Web of Science Times Cited 7]


[11] T. Senguler, E. Karatoprak, S. Seker, "A New MLP Approach for the Detection of the Incipient Bearing Damage," Advances in Electrical and Computer Engineering, vol. 10, no. 3, pp. 34-39, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 9]


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


[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.
[CrossRef] [Web of Science Times Cited 33]


[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.
[CrossRef] [Web of Science Times Cited 99]


[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.
[CrossRef] [Web of Science Times Cited 79]


[16] C. Concari, G. Franceschini, C. Tassoni, A. Toscani, "Validation of a Faulted Rotor Induction Machine Model With an Insightful Geometrical Interpretation of Physical Quantities", IEEE Transactions on Industrial Electronics, vol. 60, no. 9, pp. 4074-4083, 2013.
[CrossRef] [Web of Science Times Cited 17]


[17] Y. H. Kim, Y. W Youn, D. H. Hwang, J. H. Sun, D. S. Kang, "High-Resolution Parameter Estimation Method to Identify Broken Rotor Bar Faults in Induction Motors," IEEE Transactions on Industrial Electronics, vol. 60, no. 9, pp. 4103-4117, 2013.
[CrossRef] [Web of Science Times Cited 100]


[18] V. Climente-Alarcon, J. A. Antonino-Daviu, F. Vedreno-Santos, R. Puche-Panadero, "Vibration Transient Detection of Broken Rotor Bars by PSH Sidebands," IEEE Transactions on Industry Applications, vol. 49, no. 6, pp. 2576-2582, 2013.
[CrossRef] [Web of Science Times Cited 45]


[19] A. Sapena-Bano, M. Pineda-Sanchez, R. Puche-Panadero, J. Martinez-Roman, D. Matic, "Fault Diagnosis of Rotating Electrical Machines in Transient Regime Using a Single Stator Current’s FFT," IEEE Transactions on instrumentation and measurement, vol. 64, no. 11, pp. 3137-3146, 2015.
[CrossRef] [Web of Science Times Cited 57]


[20] M. Pineda-Sanchez, J. Perez-Cruz, J. Roger-Folch, M. Riera-Guasp, A. Sapena-Bano, R. Puche-Panadero, „Diagnosis of Induction Motor Faults using a DSP and Advanced Demodulation Techniques", in Proc. 9th IEEE SDEMPED, Valencia, Spain, 27-30, Aug.2013, pp.69-76.
[CrossRef]


[21] S. Biswal, J. D. George, G. R Sabareesh, "Fault Size Estimation Using Vibration Signatures in a Wind Turbine Test-rig", Procedia Engineering, vol. 144, pp. 305-311, 2016.
[CrossRef] [Web of Science Times Cited 6]


[22] M. Amarnath, I. R. P. Krishna, "Local fault detection in helical gears via vibration and acoustic signals using EMD based statistical parameter analysis", Measurement, vol. 58, pp. 154-164, 2014.
[CrossRef] [Web of Science Times Cited 49]


[23] Z. Kanovic, D. Matic, Z. Jelicic, M. Rapaic, B. Jakovljevic, M. Kapetina, „Induction Motor Broken Rotor Bar Detection Using Vibration Analysis - A Case Study," in Proc. 9th IEEE SDEMPED, Valencia, Spain, 27-30, Aug. 2013, pp.64-68.
[CrossRef]


[24] J. Obuchowski, R. Zimroz, A. Wylomanska, "Blind equalization using combined skewness-kurtosis criterion for gearbox vibration enhancement," Measurement, vol. 88, pp. 34-44, 2016.
[CrossRef] [Web of Science Times Cited 17]


[25] D. Matic, Z. Kanovic, D. Reljic, F. Kulic, D. Oros, V. Vasic, "Broken Bar Detection Using Current Analysis - A Case Study," in Proc. 9th IEEE SDEMPED, Valencia, Spain, 27-30, Aug. 2013, pp. 407-411.
[CrossRef]


[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 8]




References Weight

Web of Science® Citations for all references: 2,384 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 88 ACR
SCOPUS® Average Citations per reference: 0

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 2021-02-28 03:51 in 158 seconds.




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