Broken Rotor Bar Fault Diagnosis in Induction Motors using Resampling Based Order Tracking Analysis Method
Abstract
Induction motors are the most popular motors used in the industry because of their simple structure, steadfast operation, and high efficiency. Unexpected failures of these motors reduce the production capacity while increasing the maintenance and expenditure cost. So condition monitoring motors and troubleshooting methods are highly necessary for the electrical motors. In this proposed study, the effect of broken rotor bar faults on motor current signal in three-phased motors was examined under stationary and non-stationary conditions. The proposed method contains clear information about the fault under both operation conditions.
References
- S. Nandi, H. A. Toliyat, X. Li, Condition monitoring and fault diagnosis of electrical motors, IEEE Transactions on Energy Conversion, Volume:20, Issue:4, pp:719-729, Dec. 2005.
- M. M. Tezcan, A. I. Çanakoğlu, Finite element study of induction motorshaving broken rotor bar faults, 5. International Advanced Technologies Symposium, Karabük, 2009.
- I. Aydın, The using of data mining and soft computing techniques in fault diagnosis, Fırat University Graduate School of Naturel and Applied Sciences, Master thesis, 2006.
- M. L. Sin, W. L. Soong, N. Ertuğrul, Induction machine on-line condition monitoring and fault diagnosis, University of Adelaide, 2003.
- C. C. Yeh, A. S. Ahmed, R. J. Povinelli, D. M. Ionel, A reconfigurable motor for experimental emulation of stator winding interturn and broken bar faults in polyphase induction machine, IEEE Transactions on Energy Conversion, Volume: 23, Issue:4, Dec. 2008.
- M. Akar, Detection of rotor bar faults in field oriented controlled induction motors, Journal of Power Electronics, Volume:12, Issue:6, pp:982-991, Nov. 2012.
- M. Akar , Mechanical fault diagnosis in the permanent magnet synchronos motor with artifical intelligence techniques, Sakarya University Institute of Science, PhD. Thesis, Sakarya, 2009.
- H. Arabacı, O. Bilgin, Detection of rotor bar faults by using stator current envelope, Proceedings of the World Congress on Engineering 2011, Volume:II, pp:1432-1435, London, U.K, 2011.
- S. Chen, Induction machine broken rotor bar diagnostics using prony analysis, School of Electrical & Electronic Engineering, University of Adelaide, Master’s Thesis, Adelaide, Australia, 2008.
- R. Supangat, Online condition monitoring and detection of stator and rotor faults in induction motors, University of Adelaide, PhD Thesis, Adelaide, Australia, 2008.
- N. Mehala, R. Dahiya, Rotor faults detection in induction motor by wavelet analysis, International Journal of Engineering Science and Technology, Volume:1, Issue:3, pp:90-99, 2009.
- C. Costa, M. Kashiwagi, M. H. Mathias, Rotor failure detection of induction motors by wavelet transform and Fourier transform in non-stationary condition, Case Studies in Mechanical Systems and Signal Processing, Volume:1, pp:15–26, 2015.
- M. Bayrak, A. Küçüker, A power based algorithm design for detection of broken rotor bars faults in three phase induction motors, Journal of the Faculty of Engineering and Architecture of Gazi University, Volume:21, Issue:2, pp:303-311, 2016.
- M. Akar, İ. Çankaya, Broken rotor bar fault detection in inverter-fed squirrel cage induction motors using stator current analysis and fuzzy logic, Turk J Elec. Eng & Comp. Sci, Volume:20, Issue:1, 2012.
- P. Shi, Z. Chen, Y. Vagapov, Z. Zouaoui, A new diagnosis of broken rotor bar fault extent in three phase squirrel cage induction motor, Mechanical Systems and Signal Processing, Volume:42, pp:388-403, 2014.
- 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, Volume:54-55, pp:427-456, 2015.
- M. O. Mustafa, G. Nikolakopoulos, T. Gustafsson, D. Kominiak, A fault detection scheme based on minimum identified uncertainty bounds violation for broken rotor bars in induction motors, Control Engineering Practice, Volume:48, pp:63-77, 2016.
- S. Ergin, A. Uzuntaş, M. B. Gülmezoğlu, Detection of stator, bearing and rotor faults in induction motors, Procedia Engineering Volume:30,pp:1103 – 1109, 2012.
- M. G. Armaki ,R. Roshanfekr, A new approach for fault detection of broken rotor bars in induction motor based on support vector machine, Proceedings of ICEE (Electrical Engineering), 18th Iranian Conference on , May 2010.
- G. B. Kliman, R.A. Koegl, J. Stein, R.D. Endicott, M.W. Madden, Noninvasive detection of broken rotor bars in operating induction motors, IEEE Transactions on Energy Conversion, Volume:3, Issue:4, pp:873–879, 1988.
- K. Wang, Vibration monitoring on electrical machine using vold-kalman filter order tracking, Master’s Thesis, Mechanical and Aeronautical Engineering, University of Pretoria, 2008.
- J. R. Blough, Adaptive resampling-transforming from the time to the angle domain, IMAC-XXIV:Conference & Exposition on Structural Dynamics, 2006.
- T. Doğruer, The detection of rotor bar broken fault in asynchronous motor drived by inverter, Gaziosmanpaşa University Graduate School of Naturel and Applied Sciences, Master’s Thesis, 2012.
- T. Doğruer, M. Akar, İndüksiyon motorlarında durağan olmayan çalışma şartlarında kırık rotor çubuğu arızasının tespiti, EEB2016 Elektrik-Elektronik ve Bilgisayar Sempozyumu, Tokat, Mayıs 2016.
Year 2016,
Volume: 5 , 111 - 125, 07.11.2016
Abstract
References
- S. Nandi, H. A. Toliyat, X. Li, Condition monitoring and fault diagnosis of electrical motors, IEEE Transactions on Energy Conversion, Volume:20, Issue:4, pp:719-729, Dec. 2005.
- M. M. Tezcan, A. I. Çanakoğlu, Finite element study of induction motorshaving broken rotor bar faults, 5. International Advanced Technologies Symposium, Karabük, 2009.
- I. Aydın, The using of data mining and soft computing techniques in fault diagnosis, Fırat University Graduate School of Naturel and Applied Sciences, Master thesis, 2006.
- M. L. Sin, W. L. Soong, N. Ertuğrul, Induction machine on-line condition monitoring and fault diagnosis, University of Adelaide, 2003.
- C. C. Yeh, A. S. Ahmed, R. J. Povinelli, D. M. Ionel, A reconfigurable motor for experimental emulation of stator winding interturn and broken bar faults in polyphase induction machine, IEEE Transactions on Energy Conversion, Volume: 23, Issue:4, Dec. 2008.
- M. Akar, Detection of rotor bar faults in field oriented controlled induction motors, Journal of Power Electronics, Volume:12, Issue:6, pp:982-991, Nov. 2012.
- M. Akar , Mechanical fault diagnosis in the permanent magnet synchronos motor with artifical intelligence techniques, Sakarya University Institute of Science, PhD. Thesis, Sakarya, 2009.
- H. Arabacı, O. Bilgin, Detection of rotor bar faults by using stator current envelope, Proceedings of the World Congress on Engineering 2011, Volume:II, pp:1432-1435, London, U.K, 2011.
- S. Chen, Induction machine broken rotor bar diagnostics using prony analysis, School of Electrical & Electronic Engineering, University of Adelaide, Master’s Thesis, Adelaide, Australia, 2008.
- R. Supangat, Online condition monitoring and detection of stator and rotor faults in induction motors, University of Adelaide, PhD Thesis, Adelaide, Australia, 2008.
- N. Mehala, R. Dahiya, Rotor faults detection in induction motor by wavelet analysis, International Journal of Engineering Science and Technology, Volume:1, Issue:3, pp:90-99, 2009.
- C. Costa, M. Kashiwagi, M. H. Mathias, Rotor failure detection of induction motors by wavelet transform and Fourier transform in non-stationary condition, Case Studies in Mechanical Systems and Signal Processing, Volume:1, pp:15–26, 2015.
- M. Bayrak, A. Küçüker, A power based algorithm design for detection of broken rotor bars faults in three phase induction motors, Journal of the Faculty of Engineering and Architecture of Gazi University, Volume:21, Issue:2, pp:303-311, 2016.
- M. Akar, İ. Çankaya, Broken rotor bar fault detection in inverter-fed squirrel cage induction motors using stator current analysis and fuzzy logic, Turk J Elec. Eng & Comp. Sci, Volume:20, Issue:1, 2012.
- P. Shi, Z. Chen, Y. Vagapov, Z. Zouaoui, A new diagnosis of broken rotor bar fault extent in three phase squirrel cage induction motor, Mechanical Systems and Signal Processing, Volume:42, pp:388-403, 2014.
- 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, Volume:54-55, pp:427-456, 2015.
- M. O. Mustafa, G. Nikolakopoulos, T. Gustafsson, D. Kominiak, A fault detection scheme based on minimum identified uncertainty bounds violation for broken rotor bars in induction motors, Control Engineering Practice, Volume:48, pp:63-77, 2016.
- S. Ergin, A. Uzuntaş, M. B. Gülmezoğlu, Detection of stator, bearing and rotor faults in induction motors, Procedia Engineering Volume:30,pp:1103 – 1109, 2012.
- M. G. Armaki ,R. Roshanfekr, A new approach for fault detection of broken rotor bars in induction motor based on support vector machine, Proceedings of ICEE (Electrical Engineering), 18th Iranian Conference on , May 2010.
- G. B. Kliman, R.A. Koegl, J. Stein, R.D. Endicott, M.W. Madden, Noninvasive detection of broken rotor bars in operating induction motors, IEEE Transactions on Energy Conversion, Volume:3, Issue:4, pp:873–879, 1988.
- K. Wang, Vibration monitoring on electrical machine using vold-kalman filter order tracking, Master’s Thesis, Mechanical and Aeronautical Engineering, University of Pretoria, 2008.
- J. R. Blough, Adaptive resampling-transforming from the time to the angle domain, IMAC-XXIV:Conference & Exposition on Structural Dynamics, 2006.
- T. Doğruer, The detection of rotor bar broken fault in asynchronous motor drived by inverter, Gaziosmanpaşa University Graduate School of Naturel and Applied Sciences, Master’s Thesis, 2012.
- T. Doğruer, M. Akar, İndüksiyon motorlarında durağan olmayan çalışma şartlarında kırık rotor çubuğu arızasının tespiti, EEB2016 Elektrik-Elektronik ve Bilgisayar Sempozyumu, Tokat, Mayıs 2016.
There are 24 citations in total.
Details
| Journal Section | Articles |
|---|---|
| Authors | |
| Publication Date | November 7, 2016 |
| Published in Issue | Year 2016 Volume: 5 |
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