A New Method for Identifying Broken Rotor Bars in Squirrel Cage Induction Motor Based on Particle Swarm Optimization Method
Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteristic frequency components of faylted rotor will be detected by minimizing a fitness function using pso. Supply frequency and side band frequencies and their amplitudes can be estimated by the proposed method. The proposed method is applied to a faulty motor with one and two broken bars in different loading condition. Experimental results prove that the proposed method is effective and applicable.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1070839Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1585
 Bulent Ayhan, Mo-Yuen Chow, Myun-Hung Song, "Multiple Signature Processing-Based Fault Detection Schemes for Broken Bar in Induction Motors," IEEE Trans. Energy Conversion, vol.20, No.2, June 2005
 William T. Thosmson, Mark Fenger, "Current Signature Analysis to Detect Induction motor Faults," IEEE Industry Application Magazine, July/August 2001
 Guillermo A.Jimenez, Alfredo O.Munoz, "Fault detection in induction motors using Hilbert and Wavelet transforms," Springer-Verlag 2006
 Zhengping Zhang, Zhen Ren, "A Novel Detection Method of Motor Broken Rotor Bars on Wavelet Ridge," IEEE Trans. Energy Conversion, vol.18, No.3, Sep.2003
 Bin Lu, Manish Paghda, "Induction Motor Fault Diagnosis Using Wavelet Analysis of One-Cycle Average Power," IEEE 2008
 Bulent Ayhan, Mo-Yuen Chow, "Multiple Discriminant Analysis and Neural-Network-Based Monolith and Partition Fault- Detection Schemes for Broken Bar in Induction Motors," IEEE Trans. Industrial Electronics, vol.53, No.4, AUGUST 2006
 J. Kennedy and R. Eberhart, "Particle swarm optimization," in Proc.IEEE Int. Conf. Neural Netw., vol. 4, Nov. 1995, pp. 1942- 1948.
 J. Kennedy and R. Mendes, "Neighborhood topologies in fullyinformed and best-of-neighborhood particle swarms," Proc. of the IEEE International Workshop, pp. 45-50, June 2003.
 R. Eberhart and Y. Shi, "Particle swarm optimization: developments, applications and resources," in Proc. Cong. Evol. Comput, Vol. 1, pp. 81-86, 2001.
 A.Raei, V.Rashtchi, " Accurate identification of parameters, in winding function model of induction motor, using genetic algorithm", SICE 2002 August 5-7,Osaka