Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine

Aiming at the fault diagnosis problem of rolling bearing,a fault diagnosis method of rolling bearing based on local characteristic-scale decomposition(LCD) cross approximate entropy(CAE) and relevance vector machine(RVM) is proposed. Firstly,the bearing vibration signals is decomposed into several i...

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Main Authors: Tan Jingjing, Gao Feng, Zhang Qiantu
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2017-01-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.11.034
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author Tan Jingjing
Gao Feng
Zhang Qiantu
author_facet Tan Jingjing
Gao Feng
Zhang Qiantu
author_sort Tan Jingjing
collection DOAJ
description Aiming at the fault diagnosis problem of rolling bearing,a fault diagnosis method of rolling bearing based on local characteristic-scale decomposition(LCD) cross approximate entropy(CAE) and relevance vector machine(RVM) is proposed. Firstly,the bearing vibration signals is decomposed into several intrinsic scale components(ISC) which with different frequency components. Secondly,some ISCs that contain main fault information are shifted out by the energy analysis criterion and CAE values are calculated as fault feature vectors that could represent the operating conditions of bearings. Finally,the fault feature are put into RVM to identify different faults. The effective of the proposed method is verified by the different fault type and different fault degree of rolling bearing experiment.
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spelling doaj.art-361912e1a42d47708e7d9d816c7fe4612023-05-26T09:46:34ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392017-01-014117317729933448Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector MachineTan JingjingGao FengZhang QiantuAiming at the fault diagnosis problem of rolling bearing,a fault diagnosis method of rolling bearing based on local characteristic-scale decomposition(LCD) cross approximate entropy(CAE) and relevance vector machine(RVM) is proposed. Firstly,the bearing vibration signals is decomposed into several intrinsic scale components(ISC) which with different frequency components. Secondly,some ISCs that contain main fault information are shifted out by the energy analysis criterion and CAE values are calculated as fault feature vectors that could represent the operating conditions of bearings. Finally,the fault feature are put into RVM to identify different faults. The effective of the proposed method is verified by the different fault type and different fault degree of rolling bearing experiment.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.11.034Local characteristic-scale decomposition;Cross approximate entropy;Relevance vector machine;Fault diagnosis;Rolling bearing
spellingShingle Tan Jingjing
Gao Feng
Zhang Qiantu
Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine
Jixie chuandong
Local characteristic-scale decomposition;Cross approximate entropy;Relevance vector machine;Fault diagnosis;Rolling bearing
title Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine
title_full Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine
title_fullStr Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine
title_full_unstemmed Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine
title_short Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine
title_sort fault diagnosis method of bearing based on lcd cross approximate entropy and relevance vector machine
topic Local characteristic-scale decomposition;Cross approximate entropy;Relevance vector machine;Fault diagnosis;Rolling bearing
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.11.034
work_keys_str_mv AT tanjingjing faultdiagnosismethodofbearingbasedonlcdcrossapproximateentropyandrelevancevectormachine
AT gaofeng faultdiagnosismethodofbearingbasedonlcdcrossapproximateentropyandrelevancevectormachine
AT zhangqiantu faultdiagnosismethodofbearingbasedonlcdcrossapproximateentropyandrelevancevectormachine