Detection of Induction Motor Improper Bearing Lubrication by Discrete Wavelet Transforms (DWT) Decomposition

Immunotechnology : an international journal of immunological engineering Pub Date : 2020-11-15 DOI:10.18280/i2m.190504

Bellal Belkacemi, S. Saad, Z. Ghemari, F. Zaamouche, Adel Khazzane

{"title":"Detection of Induction Motor Improper Bearing Lubrication by Discrete Wavelet Transforms (DWT) Decomposition","authors":"Bellal Belkacemi, S. Saad, Z. Ghemari, F. Zaamouche, Adel Khazzane","doi":"10.18280/i2m.190504","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":79497,"journal":{"name":"Immunotechnology : an international journal of immunological engineering","volume":"19 1","pages":"347-354"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Immunotechnology : an international journal of immunological engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18280/i2m.190504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 6

Abstract

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.

查看原文本刊更多论文

基于离散小波变换(DWT)分解的感应电机轴承润滑不良检测

本文利用MATLAB/小波工具箱增强的离散小波变换(DWT)分析轴承健康和不良润滑信号。由于轴承振动信号的非平稳性，难以从时域或频域识别轴承故障。因此，为了更准确的故障信息和识别具有润滑缺陷(不正确或缺乏润滑)的轴承，使用DWT。通过设计用于振动信号采集的实验装置对该方法进行了验证，并通过MATLAB/小波工具箱完成了完整的分析。用于验证的记录数据是由0.78 KW三相感应电动机以1500 rpm的转速驱动的健康和未润滑轴承的信号。结果表明，在中速工况下，基于MATLAB小波工具箱的DWT分解对轴承非正常润滑相关故障的诊断和检测是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Immunotechnology : an international journal of immunological engineering

自引率

0.00%

发文量