Induction motors airgap-eccentricity detection through the discrete wavelet transform of the apparent power signal under non-stationary operating conditions

K Yahia; A J M Cardoso; A Ghoggal; S E Zouzou

doi:10.1016/j.isatra.2013.12.002

Induction motors airgap-eccentricity detection through the discrete wavelet transform of the apparent power signal under non-stationary operating conditions

ISA Trans. 2014 Mar;53(2):603-11. doi: 10.1016/j.isatra.2013.12.002. Epub 2014 Jan 23.

Authors

K Yahia¹, A J M Cardoso², A Ghoggal³, S E Zouzou⁴

Affiliations

¹ Laboratoire de Génie Energétique et Matériaux, LGEM. B.P. 145 R.P., 07000 Biskra, Algerie; CISE - Electromechatronic Systems Research Centre, University of Beira Interior, Convento de Santo António, P-6201-001 Covilhã, Portugal. Electronic address: kd_yahia@yahoo.fr.
² CISE - Electromechatronic Systems Research Centre, University of Beira Interior, Convento de Santo António, P-6201-001 Covilhã, Portugal. Electronic address: ajmcardoso@ieee.org.
³ Laboratoire de Génie Electrique, LGEB. B.P. 145 R.P., 07000 Biskra, Algerie. Electronic address: ghoetudes@yahoo.fr.
⁴ Laboratoire de Génie Electrique, LGEB. B.P. 145 R.P., 07000 Biskra, Algerie. Electronic address: zouzou_s@hotmail.com.

PMID: 24461376
DOI: 10.1016/j.isatra.2013.12.002

Abstract

Fast Fourier transform (FFT) analysis has been successfully used for fault diagnosis in induction machines. However, this method does not always provide good results for the cases of load torque, speed and voltages variation, leading to a variation of the motor-slip and the consequent FFT problems that appear due to the non-stationary nature of the involved signals. In this paper, the discrete wavelet transform (DWT) of the apparent-power signal for the airgap-eccentricity fault detection in three-phase induction motors is presented in order to overcome the above FFT problems. The proposed method is based on the decomposition of the apparent-power signal from which wavelet approximation and detail coefficients are extracted. The energy evaluation of a known bandwidth permits to define a fault severity factor (FSF). Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method presented even for the case of load torque variations.

Keywords: Airgap-eccentricity fault detection; Apparent-power; Discrete wavelet transform (DWT); Induction motors (IMs); Load torque variation.