Diagnosis of broken bar fault in induction machines using advanced digital signal processing

International Review of Electrical Engineering

Volumn 5, Issue 4, 2010, Pages 1460-1468

  Braham, A ^a   Lachiri, Z ^a,b  

^a UNIVERSITY OF CARTHAGE   (Tunisia)

^b UNIVERSITY OF TUNIS EL MANAR   (Tunisia)

Author keywords

Broken rotor bar; Fault diagnosis; Induction motor; Power spectrum density estimation

Indexed keywords

EID: 79956190421     PISSN: 18276660     EISSN: 25332244     Source Type: Journal    
DOI: None     Document Type: Article

References (21)

1. A. H. Bonnett, G. S. Soukup, Cause and Analysis of Stator and Rotor Failures in Three-Phase Squirrel-Cage Induction Motors", IEEE Transactions on Industry Applications, vol. 28 n. 4, Jully/August 1992, pp. 921-937.
2. S. Nandi, H. A. Toliyat, Condition monitoring and fault diagnosis of electrical machines-a review", The 34th IEEE INDUSTRY APPLICATIONS Conference Annual Meeting ~IAS~, vol.1, 1999, Phoenix.
3. W. T. Thomson, M. Fenger, Current Signature Analysis to Detect Induction Motor Faults", IEEE Industry Applications Magazine, Jully/August 2001, pp. 26-34.
4. N. M. Elkasabgy, A. R. Eastham, G. E. Dawson, Detection of Broken Bars in The Cage Rotor on an Induction Machine, IEEE Transactions on Industry Applications, vol. 28 n. 1, January/February 1992, pp. 165-171.
5. B. Ayhan, M. Y. chow, M. H. Song, Multiple Discriminant Analysis and Neural-Network-Based Monolith and Partition Fault-Detection Schemes for Broken Rotor Bar in Induction Motors, IEEE Transactions on Industrial Electronics, vol.53 n. 4, August 2006, pp. 1298-1308.
6. A. Bellini, A. Yazidi, F. Filippetti, C. Rossi, G. Capolino, High Frequency Resolution Techniques for Rotor Fault Detection of Induction Machines, IEEE Transactions on Industrial Electronics, vol. 55 n. 12, December 2008, pp. 4200-4209.
7. A. Ordaz-Moreno, R. de Jesus Romero-Troncoso, J. A. Vite-Frias, J. R. Rivera-Gillen, A. Garcia-Perez, Automatic Online Diagnosis Algorithm for Broken-Bar Detection on Induction Motors Based on Discrete Wavelet Transform for FPGA Implementation, IEEE Transactions on Industrial Electronics, vol. 55 n. 5, May 2008, pp. 2193-2202.
8. A. Lebaroud, G. Clerc, Classification of Induction Machine Faults by Optimal Time-Frequency Representations, IEEE Transactions on Industrial Electronics, vol. 55 n. 12, December 2008, pp. 4290-4298.
9. H. Arabaci, O. Bilgin, Neural network classification and diagnosis of broken rotor bar faults by means of short time fourier transform, The International MultiConference of ENGINEERS AND COMPUTER SCIENTISTS ~IMECS~, 2009, Hong Kong.
10. W. T. Thomson, M. Fenger, Case histories of current signature analysis to detect faults in induction motor drives, The IEEE International ELECTRIC MACHINES and DRIVES Conference ~IEMDC~, 2003.
11. M. E. H. Benbouzid, A Review of Induction Motors Signature Analysis as a Medium for Faults Detection, IEEE Transactions on Industrial Electronics, vol. 47 n. 5, October 2000, pp. 984-993.
12. J. Cusidó, L. Romeral, J. A. Ortega, A. Garcia, J. R. Riba, Wavelet and PDD as Fault Detection Techniques, Electric Power Systems Research, vol. 80, 2010, pp. 915-924.
13. G. Niu, A. Widodo, J. D. Son, B. S. Yang, D. H. Hwang, D. S. Kang, Decision-level Fusion Based on Wavelet Decomposition for Induction Motor Fault Diagnosis Using Transient Current Signal, Expert Systems with Applications, vol. 35, October 2008, pp. 918-928.
14. L. Eren, Y. Çekiç, M. J. Devaney, Broken Rotor Bar Detection via Wavelet Packet Decomposition of Motor Current, International Review of Electrical Engineering (IREE), vol. 4 n. 5, October 2009, pp. 844-850.
15. M. H. Hayes, Statistical Digital Signal Processing and Modeling (Wiley, 1996).
16. D. S. Gazzana, L. A. Pereira, D. Fernandas, An Automated System for Incipient Fault Detection and Diagnosis in Induction Motors Based on MCSA, The IEEE International Conference on Industrial Technology ~ICIT~, March 14-17 2010, Vi a del Mar, Chile.
17. L. A. Pereira, D. Fernandas, D. S. Gazzana, F. B. Libano, S. Haffner, Performance evaluation of nonparametric, parametric, and the MUSIC methods to detection of rotor Cage Faults of induction motors, The 32nd Annual Conference on IEEE INDUSTRIAL ELECTRONICS ~IECON~, November 6-10, 2006, Paris, France.
18. P. Stoica, R. L. Moses, Spectral Analysis of Signals (Prentice Hall, 2005).
19. S. H. Kia, H. Henao, G.-A. Capolino, Digital Signal Processing for Induction Machines Diagnosis-A Review, The 33rd Annual Conference of the IEEE INDUSTRIAL ELECTRONICS SOCIETy ~IECON~, November 5-8, 2007, Taipei, Taiwan.
20. F. Castanié, Spectral Analysis: Parametric and Non-Parametric Digital Methods (ISTE Ltd, 2006).
21. Moallem, P.; Dehkordi, B. Mirzaeian; Boroujeni, S. M. Shirvani, Determination of Number of Broken Rotor Bars in Squirrel-Cage Induction Motors Using Wavelet, PCA and Neural Networks, International Review of Electrical Engineering (IREE), vol. 4, issue 2, April 2009, pp. 242-248.