Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO

Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO

Bearing is an important component of mechanical system; any defects of bearing will lead to serious damage for the entire mechanical system. In this paper, Cauchy kernel relevance vector machine with stochastic inertia weight particle swarm optimization algorithm (SIWPSO-CauchyRVM) is proposed to fa...

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Main Authors: Sheng-wei Fei, Yong He
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2015/129361
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spelling doaj-be9b2e994a9f47e295cb0bcc55249fdc2020-11-24T23:03:43ZengHindawi LimitedShock and Vibration1070-96221875-92032015-01-01201510.1155/2015/129361129361Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSOSheng-wei Fei0Yong He1School of Mechanical Engineering, Donghua University, Shanghai 201620, ChinaSchool of Mechanical Engineering, Donghua University, Shanghai 201620, ChinaBearing is an important component of mechanical system; any defects of bearing will lead to serious damage for the entire mechanical system. In this paper, Cauchy kernel relevance vector machine with stochastic inertia weight particle swarm optimization algorithm (SIWPSO-CauchyRVM) is proposed to fault diagnosis for bearing. As the selection of the Cauchy kernel parameter has a certain influence on the diagnosis result of relevance vector machine, stochastic inertia weight PSO is used to select the Cauchy kernel parameter. The relative energies of 16 wavelet coefficients of the forth layer of vibration signal of bearing can be used as the diagnosis features of bearing. The experimental results indicate that fault diagnosis method of bearing based on SIWPSO-CauchyRVM has excellent diagnosis ability.http://dx.doi.org/10.1155/2015/129361
collection DOAJ
language English
format Article
sources DOAJ
author Sheng-wei Fei
Yong He
spellingShingle Sheng-wei Fei
Yong He
Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO
Shock and Vibration
author_facet Sheng-wei Fei
Yong He
author_sort Sheng-wei Fei
title Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO
title_short Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO
title_full Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO
title_fullStr Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO
title_full_unstemmed Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO
title_sort fault diagnosis of bearing based on cauchy kernel relevance vector machine classifier with siwpso
publisher Hindawi Limited
series Shock and Vibration
issn 1070-9622
1875-9203
publishDate 2015-01-01
description Bearing is an important component of mechanical system; any defects of bearing will lead to serious damage for the entire mechanical system. In this paper, Cauchy kernel relevance vector machine with stochastic inertia weight particle swarm optimization algorithm (SIWPSO-CauchyRVM) is proposed to fault diagnosis for bearing. As the selection of the Cauchy kernel parameter has a certain influence on the diagnosis result of relevance vector machine, stochastic inertia weight PSO is used to select the Cauchy kernel parameter. The relative energies of 16 wavelet coefficients of the forth layer of vibration signal of bearing can be used as the diagnosis features of bearing. The experimental results indicate that fault diagnosis method of bearing based on SIWPSO-CauchyRVM has excellent diagnosis ability.
url http://dx.doi.org/10.1155/2015/129361
work_keys_str_mv AT shengweifei faultdiagnosisofbearingbasedoncauchykernelrelevancevectormachineclassifierwithsiwpso
AT yonghe faultdiagnosisofbearingbasedoncauchykernelrelevancevectormachineclassifierwithsiwpso
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