MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM

Aiming at the fact that the fault diagnosis performance of relevance vector machine(RVM) in motor bearing highly depends on the parameters selection, a motor bearing fault diagnosis method based on RVM optimized by fruit fly optimization algorithm with reverse cognition(RCFOA) was proposed. In order...

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Main Author: WANG HanZhang
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2019-01-01
Series:Jixie qiangdu
Subjects:
Online Access:http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.04.008
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author WANG HanZhang
author_facet WANG HanZhang
author_sort WANG HanZhang
collection DOAJ
description Aiming at the fact that the fault diagnosis performance of relevance vector machine(RVM) in motor bearing highly depends on the parameters selection, a motor bearing fault diagnosis method based on RVM optimized by fruit fly optimization algorithm with reverse cognition(RCFOA) was proposed. In order to improve search ability of FOA, reverse cognition strategy was introduced and improved the original FOA algorithm. Use the RCFOA to optimize RVM parameters can effectively improve the classification performance of RVM. Different fault type and different fault degree of motor bearing fault diagnosis experiment results show that the RCFOA can obtain better parameter when compared with some other methods, improved the fault diagnosis accuracy of RVM and can applied to fault diagnosis efficiently.
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spelling doaj.art-4686b47b88474ba5828a16ca039921062025-01-15T02:29:39ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-014181482030605456MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHMWANG HanZhangAiming at the fact that the fault diagnosis performance of relevance vector machine(RVM) in motor bearing highly depends on the parameters selection, a motor bearing fault diagnosis method based on RVM optimized by fruit fly optimization algorithm with reverse cognition(RCFOA) was proposed. In order to improve search ability of FOA, reverse cognition strategy was introduced and improved the original FOA algorithm. Use the RCFOA to optimize RVM parameters can effectively improve the classification performance of RVM. Different fault type and different fault degree of motor bearing fault diagnosis experiment results show that the RCFOA can obtain better parameter when compared with some other methods, improved the fault diagnosis accuracy of RVM and can applied to fault diagnosis efficiently.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.04.008Fruit fly optimization algorithmReverse cognitionRelevance vector machineFault diagnosisBearing
spellingShingle WANG HanZhang
MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
Jixie qiangdu
Fruit fly optimization algorithm
Reverse cognition
Relevance vector machine
Fault diagnosis
Bearing
title MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
title_full MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
title_fullStr MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
title_full_unstemmed MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
title_short MOTOR BEARING FAULT DIAGNOSIS BASED ON RELEVANCE VECTOR MACHINE OPTIMIZE BY IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
title_sort motor bearing fault diagnosis based on relevance vector machine optimize by improved fruit fly optimization algorithm
topic Fruit fly optimization algorithm
Reverse cognition
Relevance vector machine
Fault diagnosis
Bearing
url http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.04.008
work_keys_str_mv AT wanghanzhang motorbearingfaultdiagnosisbasedonrelevancevectormachineoptimizebyimprovedfruitflyoptimizationalgorithm