Advanced SearchSearch Tips
MUSIC-based Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors Using Flux Signal
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
MUSIC-based Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors Using Flux Signal
Youn, Young-Woo; Yi, Sang-Hwa; Hwang, Don-Ha; Sun, Jong-Ho; Kang, Dong-Sik; Kim, Yong-Hwa;
  PDF(new window)
The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.
Broken rotor bar;Induction motor;Fault diagnosis;Spectral analysis;Flux signal;
 Cited by
Robust Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors,;;;;

Journal of Electrical Engineering and Technology, 2014. vol.9. 1, pp.37-44 crossref(new window)
Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network, Computational Intelligence and Neuroscience, 2016, 2016, 1  crossref(new windwow)
Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis, Journal of Sound and Vibration, 2016, 379, 213  crossref(new windwow)
Robust Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors, Journal of Electrical Engineering and Technology, 2014, 9, 1, 37  crossref(new windwow)
Motor Reliability Working Group, "Report of large motor reliability survey of industrial and commercial installation, Part II," IEEE Trans. Ind. Appl., Vol. IA- 21, No. 4, pp. 865-872, July/Aug. 1985. crossref(new window)

W. T. Thomson and M. Fenger, "Current signature analysis to detect induction motor faults," IEEE Ind. Appl. Mag., Vol. 7, No. 4, pp. 26-34, July/Aug. 2001.

J. R. Cameron, W. T. Thomson, and A. B. Dow, "Vibration and current monitoring for detecting airgap eccentricity in large induction motors," Proc. IEE-Electric Power Appl., Vol. 133, No. 3, pp. 155- 163, May 1986. crossref(new window)

R. R. Schoen, T. G. Habetler, F. Kamran, and R. G. Bartfield, "Motor bearing damage detection using stator current monitoring," IEEE Ind. Appl., Vol. 31, No. 6, pp.1274-1279, Nov./Dec. 1995. crossref(new window)

M. J. Devaney, and L. Eren, "Detecting motor bearing faults," IEEE Instrumentation and Measurement Mag., Vol. 7, No. 4, pp. 30-50, Dec. 2004. crossref(new window)

H. Henao, C. Demian, and G.-A. Capolino, "A frequency-domain detection of stator winding faults in induction machines using an external flux sensor," IEEE Ind. Appl. Vol. 39, No. 5, pp. 1272-1279, Sep./ Oct. 2003. crossref(new window)

M. E. H. Benbouzid, M. Vieira, and C. Theys, "Induction motors' faults detection and localization using stator current advanced signal processing techniques," IEEE Trans. Power Electron., Vol. 14, No. 1, pp. 14-22, Jan. 1999. crossref(new window)

S. H. Kia, H. Henao, and G.-A. Capolino, "A highresolution frequency estimation method for threephase induction machine fault detection," IEEE Trans. Ind. Electron., Vol. 54, No. 4, pp. 2305-2314, Aug. 2007. crossref(new window)

I. Ahmed, and M. Ahmed, "Comparison of stator current, axial leakage flux and instantaneous power to detect broken rotor bar faults in induction machines," in Proc. of Power Engineering Conference, pp. 1-6, Dec. 2008.

R. Blasco-Gimenez, G. M. Asher, M. Sumner, and K. J. Bradley, "Performance of FFT-rotor slot harmonic speed detector for sensorless induction motor drives," Proc. IEE-Electric Power Appl., Vol. 143, No. 3, pp. 258-268, May 1996. crossref(new window)

M. H. Hayes, Statistical digital signal processing and modeling: John Wiley & Sons, Inc, 1996.

Don-Ha Hwang et al., "Detection of air-gap eccentricity and broken-rotor bar conditions in a squirrel-cage induction motor using the radial flux sensor," Journal of Applied Physics, Vol. 103, No. 7, pp. 07F131-07F131-3, Apr. 2008. crossref(new window)

M. Kristensson, M. Jansson, and B. Ottersten, "Further results and insights on subspace based sinusoidal frequency estimation," IEEE Trans. Signal Process., Vol. 49, No. 12, pp. 2962-2974, Dec. 2001. crossref(new window)