Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy

When the gearbox fails, its vibration signal is unstable and nonlinear. The commonly applied gearbox fault diagnosis methods are almost all based on the single-channel vibration signal analysis,which is easy to cause the loss of fault information,so the practicality in industrial production is limit...

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Main Authors: Fuming Zhou, Jinxing Shen, Xiaoqiang Yang, Wuqiang Liu, Xiaolin Liu
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2021-04-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.04.019
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author Fuming Zhou
Jinxing Shen
Xiaoqiang Yang
Wuqiang Liu
Xiaolin Liu
author_facet Fuming Zhou
Jinxing Shen
Xiaoqiang Yang
Wuqiang Liu
Xiaolin Liu
author_sort Fuming Zhou
collection DOAJ
description When the gearbox fails, its vibration signal is unstable and nonlinear. The commonly applied gearbox fault diagnosis methods are almost all based on the single-channel vibration signal analysis,which is easy to cause the loss of fault information,so the practicality in industrial production is limited. In order to overcome this defect, the multivariate multiscale dispersion entropy is introduced into the gearbox fault diagnosis. Meanwhile, the coarse graining method of it is improved, and improved multivariate multiscale dispersion entropy(IMMDE) is proposed to extract fault information of multi-channel vibration signal of gearbox. Based on this,a new gearbox fault diagnosis method based on ensemble empirical mode decomposition (EEMD),IMMDE and genetic algorithm optimization support vector machine(GA-SVM) is proposed. Through the analysis of experimental data, it can be seen that this method has higher accuracy and stability compared with multivariate multiscale sample entropy(MMSE) and multivariate multiscale fuzzy entropy (MMFE),and has obvious advantages in dealing with short time series.
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institution Kabale University
issn 1004-2539
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publishDate 2021-04-01
publisher Editorial Office of Journal of Mechanical Transmission
record_format Article
series Jixie chuandong
spelling doaj-art-d17c64583a36403da217fee18cd65aa12025-01-10T14:53:43ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392021-04-01451121228813923Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion EntropyFuming ZhouJinxing ShenXiaoqiang YangWuqiang LiuXiaolin LiuWhen the gearbox fails, its vibration signal is unstable and nonlinear. The commonly applied gearbox fault diagnosis methods are almost all based on the single-channel vibration signal analysis,which is easy to cause the loss of fault information,so the practicality in industrial production is limited. In order to overcome this defect, the multivariate multiscale dispersion entropy is introduced into the gearbox fault diagnosis. Meanwhile, the coarse graining method of it is improved, and improved multivariate multiscale dispersion entropy(IMMDE) is proposed to extract fault information of multi-channel vibration signal of gearbox. Based on this,a new gearbox fault diagnosis method based on ensemble empirical mode decomposition (EEMD),IMMDE and genetic algorithm optimization support vector machine(GA-SVM) is proposed. Through the analysis of experimental data, it can be seen that this method has higher accuracy and stability compared with multivariate multiscale sample entropy(MMSE) and multivariate multiscale fuzzy entropy (MMFE),and has obvious advantages in dealing with short time series.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.04.019GearboxFault diagnosisEEMDImproved multivariate multiscale dispersion entropyGA-SVM
spellingShingle Fuming Zhou
Jinxing Shen
Xiaoqiang Yang
Wuqiang Liu
Xiaolin Liu
Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy
Jixie chuandong
Gearbox
Fault diagnosis
EEMD
Improved multivariate multiscale dispersion entropy
GA-SVM
title Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy
title_full Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy
title_fullStr Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy
title_full_unstemmed Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy
title_short Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy
title_sort fault diagnosis of gearbox multi channel vibration signal based on improved multivariate multiscale dispersion entropy
topic Gearbox
Fault diagnosis
EEMD
Improved multivariate multiscale dispersion entropy
GA-SVM
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.04.019
work_keys_str_mv AT fumingzhou faultdiagnosisofgearboxmultichannelvibrationsignalbasedonimprovedmultivariatemultiscaledispersionentropy
AT jinxingshen faultdiagnosisofgearboxmultichannelvibrationsignalbasedonimprovedmultivariatemultiscaledispersionentropy
AT xiaoqiangyang faultdiagnosisofgearboxmultichannelvibrationsignalbasedonimprovedmultivariatemultiscaledispersionentropy
AT wuqiangliu faultdiagnosisofgearboxmultichannelvibrationsignalbasedonimprovedmultivariatemultiscaledispersionentropy
AT xiaolinliu faultdiagnosisofgearboxmultichannelvibrationsignalbasedonimprovedmultivariatemultiscaledispersionentropy