Research of the Fault Feature Extraction of Rolling Bearing based on Image Processing

The feature extraction is crucial for fault diagnosis,although the existing feature extraction methods in time domain,frequency domain and time-frequency domain are effective,it is also necessary to find new methods in other domain.On the basis of the characteristic of snow images generated by analy...

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Main Authors: Zhang Qiantu, Fang Liqing
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2015-01-01
Series:Jixie chuandong
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.05.013
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author Zhang Qiantu
Fang Liqing
author_facet Zhang Qiantu
Fang Liqing
author_sort Zhang Qiantu
collection DOAJ
description The feature extraction is crucial for fault diagnosis,although the existing feature extraction methods in time domain,frequency domain and time-frequency domain are effective,it is also necessary to find new methods in other domain.On the basis of the characteristic of snow images generated by analyzing SDP(Symmetrized Dot Pattern)method,a feature extraction method based on image processing are put forward.Firstly,the original vibration signals are transformed into snow images in polar coordinate by SDP method.Then,the shape features of the snow images in different fault pattern of rolling bearing are extracted by using image processing technology,and the characteristic parameters are analyzed.Finally,BP network are created to realize fault pattern recognition.The experimental results show that this method is effective.
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spelling doaj.art-2d756b8110ab41619b5caebbdfff8fbb2023-05-26T09:38:18ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392015-01-0139424529916720Research of the Fault Feature Extraction of Rolling Bearing based on Image ProcessingZhang QiantuFang LiqingThe feature extraction is crucial for fault diagnosis,although the existing feature extraction methods in time domain,frequency domain and time-frequency domain are effective,it is also necessary to find new methods in other domain.On the basis of the characteristic of snow images generated by analyzing SDP(Symmetrized Dot Pattern)method,a feature extraction method based on image processing are put forward.Firstly,the original vibration signals are transformed into snow images in polar coordinate by SDP method.Then,the shape features of the snow images in different fault pattern of rolling bearing are extracted by using image processing technology,and the characteristic parameters are analyzed.Finally,BP network are created to realize fault pattern recognition.The experimental results show that this method is effective.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.05.013
spellingShingle Zhang Qiantu
Fang Liqing
Research of the Fault Feature Extraction of Rolling Bearing based on Image Processing
Jixie chuandong
title Research of the Fault Feature Extraction of Rolling Bearing based on Image Processing
title_full Research of the Fault Feature Extraction of Rolling Bearing based on Image Processing
title_fullStr Research of the Fault Feature Extraction of Rolling Bearing based on Image Processing
title_full_unstemmed Research of the Fault Feature Extraction of Rolling Bearing based on Image Processing
title_short Research of the Fault Feature Extraction of Rolling Bearing based on Image Processing
title_sort research of the fault feature extraction of rolling bearing based on image processing
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.05.013
work_keys_str_mv AT zhangqiantu researchofthefaultfeatureextractionofrollingbearingbasedonimageprocessing
AT fangliqing researchofthefaultfeatureextractionofrollingbearingbasedonimageprocessing