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Authors

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

DOI:

https://doi.org/10.69717/jaest.v4.i2.81

Keywords:

Lifting schemes, Faults, Motor current signature analysis, Fast Fourier transforms, Diagnostic, Fault diagnosis

Abstract

This work describes a novel and effective application of the adaptive wavelet transformfor the detection of bearing faults on induction motor stator current. This transform is based on athree-step nonlinear lifting scheme: a fixed prediction followed by a space-varying update and a noadditive prediction. This transformation technique is used in a diversity of applications in digitalsignal processing and the transmission or storage of sampled data (notably the compression of thesound, or physical measurements of accuracy). Many faults in induction motor have beenidentified as bearing defects, rotor defects and external defects. Experimental results confirm theutility and the effectiveness of the proposed method for outer raceway fault diagnosis under noload and full load conditions.

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Published

2018-06-10

Issue

Section

Research Paper

How to Cite

A new frequency analysis for diagnosis of bearing defects in induction motors using the adaptive lifting scheme of wavelet transforms. (2018). Journal of Applied Engineering Science & Technology, 4(2), 8. https://doi.org/10.69717/jaest.v4.i2.81

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