Detection of induction motor improper bearing lubrication by discrete wavelet transforms (DWT) decomposition

被引：9

作者：

Belkacemi B. ^{[1
]}

Saad S. ^{[1
]}

Ghemari Z. ^{[2
]}

Zaamouche F. ^{[3
]}

Khazzane A. ^{[1
]}

机构：

[1] Laboratoire des Systèmes Electromécaniques (LSELM), Badji Mokhtar-Annaba University

[2] Electrical Engineering Department, University of Mohamed Boudiaf at M’sila, M'sila

[3] Mining Institute, Electromechanical Department, Larbi Tebessi University, Tebessa

来源：

Instrumentation Mesure Metrologie | 2020年 / 19卷 / 05期

关键词：

Discrete wavelet transforms (DWT); Fault diagnosis; Induction motor; Lubrication defects; MATLAB wavelets toolbox;

D O I：

10.18280/i2m.190504

中图分类号：

学科分类号：

摘要：

The present paper deals with healthy and improper bearing lubrication signals analysis using Discrete Wavelet Transform (DWT) enhanced by MATLAB/ Wavelets toolbox analysis. The identification of bearing faults from the time or the frequency domain are difficult due to non stationary vibration signal. Therefore, for more accurate faults information and identification of bearing with lubrication defects (improper or absence of lubrication), the DWT is used. The validation of this procedure is conducted by an experimental setup designed for vibration signal acquisition and the complete analysis is finalized by MATLAB/ Wavelets toolbox. The recorded data used for the validation are the signals of healthy and un-lubricated bearing driven at a rotation speed of 1500 rpm by 0.78 KW three phase induction motor. From the obtained results it can be observed that, for medium speeds DWT decomposition enhanced by MATLAB Wavelets Toolbox procedure is efficient for improper lubricated bearing related faults diagnosis and detection. © 2020 Lavoisier. All rights reserved.

引用

页码：347 / 354

页数：7

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