Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS

In order to solve the fault recognition problems caused by a complex signal transfer path,severe noise pollution and the weak fault features,a method for gear based on variational mode decomposition( VMD)and adaptive neuro-fuzzy inference system( ANFIS) is proposed. Firstly,VMD is used to decompose...

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Main Authors: Zheng Xiaoxia, Jia Wenhui, Zhou Guowang, Li Jia
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2018-01-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.03.031
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author Zheng Xiaoxia
Jia Wenhui
Zhou Guowang
Li Jia
author_facet Zheng Xiaoxia
Jia Wenhui
Zhou Guowang
Li Jia
author_sort Zheng Xiaoxia
collection DOAJ
description In order to solve the fault recognition problems caused by a complex signal transfer path,severe noise pollution and the weak fault features,a method for gear based on variational mode decomposition( VMD)and adaptive neuro-fuzzy inference system( ANFIS) is proposed. Firstly,VMD is used to decompose a fault signal into several intrinsic mode functions( IMFs),and introduced the permutation entropy to construct the feature vectors characterizing the modal component information. Then the extracted feature vectors are input into the adaptive neuro-fuzzy inference system to establish the fault diagnosis model. Finally,the model is validated by the vibration signal data of the gears and compared with the support vector machine( SVM) method. The results show that the proposed method has a strong learning ability and it can effectively diagnose the gear fault,improve the accuracy of fault identification. The recognition effect is obviously superior to SVM.
format Article
id doaj-art-d26e0659e04e405e9103c00853150408
institution Kabale University
issn 1004-2539
language zho
publishDate 2018-01-01
publisher Editorial Office of Journal of Mechanical Transmission
record_format Article
series Jixie chuandong
spelling doaj-art-d26e0659e04e405e9103c008531504082025-01-10T14:43:06ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392018-01-014214915429935469Gear Fault Diagnosis based on Variational Mode Decomposition and ANFISZheng XiaoxiaJia WenhuiZhou GuowangLi JiaIn order to solve the fault recognition problems caused by a complex signal transfer path,severe noise pollution and the weak fault features,a method for gear based on variational mode decomposition( VMD)and adaptive neuro-fuzzy inference system( ANFIS) is proposed. Firstly,VMD is used to decompose a fault signal into several intrinsic mode functions( IMFs),and introduced the permutation entropy to construct the feature vectors characterizing the modal component information. Then the extracted feature vectors are input into the adaptive neuro-fuzzy inference system to establish the fault diagnosis model. Finally,the model is validated by the vibration signal data of the gears and compared with the support vector machine( SVM) method. The results show that the proposed method has a strong learning ability and it can effectively diagnose the gear fault,improve the accuracy of fault identification. The recognition effect is obviously superior to SVM.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.03.031Variational mode decompositionAdaptive neuro-fuzzy inference systemGearPermutation entropyFault diagnosis
spellingShingle Zheng Xiaoxia
Jia Wenhui
Zhou Guowang
Li Jia
Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS
Jixie chuandong
Variational mode decomposition
Adaptive neuro-fuzzy inference system
Gear
Permutation entropy
Fault diagnosis
title Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS
title_full Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS
title_fullStr Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS
title_full_unstemmed Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS
title_short Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS
title_sort gear fault diagnosis based on variational mode decomposition and anfis
topic Variational mode decomposition
Adaptive neuro-fuzzy inference system
Gear
Permutation entropy
Fault diagnosis
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.03.031
work_keys_str_mv AT zhengxiaoxia gearfaultdiagnosisbasedonvariationalmodedecompositionandanfis
AT jiawenhui gearfaultdiagnosisbasedonvariationalmodedecompositionandanfis
AT zhouguowang gearfaultdiagnosisbasedonvariationalmodedecompositionandanfis
AT lijia gearfaultdiagnosisbasedonvariationalmodedecompositionandanfis