Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling Bearing

In order to detect the early weak faults of rolling bearings effectively,a method of adaptive stochastic resonance based on variational mode decomposition( VMD) is proposed. Firstly,the fault vibration signal of rolling bearing VMD is decomposed into finite Intrinsic Mode Functions( IMF),IMF compone...

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Main Authors: Wang Zhixia, Guo Li, Cheng Qianqian
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.1004.2539.2018.04.029
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author Wang Zhixia
Guo Li
Cheng Qianqian
author_facet Wang Zhixia
Guo Li
Cheng Qianqian
author_sort Wang Zhixia
collection DOAJ
description In order to detect the early weak faults of rolling bearings effectively,a method of adaptive stochastic resonance based on variational mode decomposition( VMD) is proposed. Firstly,the fault vibration signal of rolling bearing VMD is decomposed into finite Intrinsic Mode Functions( IMF),IMF components containing fault feature are selected and reconstructed. The reconstructed signal is inputted into the stochastic resonance system,and the system structure parameters are optimized by the quantum particle swarm algorithm with the objective function of the improved weighted kurtosisso as to get the best resonance output,thus realizing the signal de-noising and enhance the fault feature. Finally the fault feature frequency is extracted by the autocorrelation envelope spectrum of output signal. The validity and advantages of the proposed method are proved by the analysis of the measured data.
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spelling doaj.art-df7d6ce829da4a4e9ca99a1c319dacaa2025-01-10T14:42:48ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392018-01-014214414929936309Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling BearingWang ZhixiaGuo LiCheng QianqianIn order to detect the early weak faults of rolling bearings effectively,a method of adaptive stochastic resonance based on variational mode decomposition( VMD) is proposed. Firstly,the fault vibration signal of rolling bearing VMD is decomposed into finite Intrinsic Mode Functions( IMF),IMF components containing fault feature are selected and reconstructed. The reconstructed signal is inputted into the stochastic resonance system,and the system structure parameters are optimized by the quantum particle swarm algorithm with the objective function of the improved weighted kurtosisso as to get the best resonance output,thus realizing the signal de-noising and enhance the fault feature. Finally the fault feature frequency is extracted by the autocorrelation envelope spectrum of output signal. The validity and advantages of the proposed method are proved by the analysis of the measured data.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.04.029VMDAdaptive stochastic resonanceRolling bearing early fault detectionCharacteristic frequency
spellingShingle Wang Zhixia
Guo Li
Cheng Qianqian
Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling Bearing
Jixie chuandong
VMD
Adaptive stochastic resonance
Rolling bearing early fault detection
Characteristic frequency
title Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling Bearing
title_full Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling Bearing
title_fullStr Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling Bearing
title_full_unstemmed Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling Bearing
title_short Application of Bistable Stochastic Resonance based on VMD in Early Fault Detection of Rolling Bearing
title_sort application of bistable stochastic resonance based on vmd in early fault detection of rolling bearing
topic VMD
Adaptive stochastic resonance
Rolling bearing early fault detection
Characteristic frequency
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.04.029
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AT guoli applicationofbistablestochasticresonancebasedonvmdinearlyfaultdetectionofrollingbearing
AT chengqianqian applicationofbistablestochasticresonancebasedonvmdinearlyfaultdetectionofrollingbearing