A new frequency analysis for diagnosis of bearing defects in induction motors using the adaptive lifting scheme of wavelet transforms

  • Wafa Bentrah Electrical Engineering Department, Université de Biskra, B.P. 145 R.P. 07000, Biskra
  • Salim Sbaa Electronic Engineering Department, Université de Biskra, B.P. 145 R.P. 07000, Biskra
  • Nadjiba Terki Electrical Engineering Department, Université de Biskra, B.P. 145 R.P. 07000, Biskra
  • Noureddine Bessous Electrical Engineering Department, Université de El-Oued, 39000 El-Oued

Abstract

This work describes a novel and effective application of the adaptive wavelet transform for the detection of bearing faults on induction motor stator current. This transform is based on a three-step nonlinear lifting scheme: a fixed prediction followed by a space-varying update and a no additive prediction. This transformation technique is used in a diversity of applications in digital signal processing and the transmission or storage of sampled data (notably the compression of the sound, or physical measurements of accuracy). Many faults in induction motor have been identified as bearing defects, rotor defects and external defects. Experimental results confirm the utility and the effectiveness of the proposed method for outer raceway fault diagnosis under no load and full load conditions.

Published
2018-06-10
How to Cite
BENTRAH, Wafa et al. A new frequency analysis for diagnosis of bearing defects in induction motors using the adaptive lifting scheme of wavelet transforms. Journal of Applied Engineering Science & Technology, [S.l.], v. 4, n. 2, p. 109-116, june 2018. ISSN 2571-9815. Available at: <http://revues.univ-biskra.dz/index.php/jaest/article/view/3884>. Date accessed: 20 aug. 2018.
Section
Section A: Electrical, Electronics and Automatic Engineering

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