Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope Spectrum

According to modulation characteristics of rotating machinery fault vibration signals and limitation of the traditional envelope spectrum analysis needs to rely on experience for determining the parameters of band- pass filter,a fault diagnosis method for rotating machinery based on maximum correlat...

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Main Authors: Zhong Xianyou, Zhao Chunghua, Chen Baojia, Tian Hongliang
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2015-01-01
Series:Jixie chuandong
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.07.028
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author Zhong Xianyou
Zhao Chunghua
Chen Baojia
Tian Hongliang
author_facet Zhong Xianyou
Zhao Chunghua
Chen Baojia
Tian Hongliang
author_sort Zhong Xianyou
collection DOAJ
description According to modulation characteristics of rotating machinery fault vibration signals and limitation of the traditional envelope spectrum analysis needs to rely on experience for determining the parameters of band- pass filter,a fault diagnosis method for rotating machinery based on maximum correlated kurtosis deconvolution( MCKD) and envelope spectrum is proposed. Firstly,by using MCKD,the noise in the rotating machinery vibration signal is reduced,then the envelope spectrum is obtained by Hilbert transform to identify the fault,simulation signal analysis and engineering applications demonstrated the effectiveness of the method.
format Article
id doaj-art-a0bdc999b56e4729b1d034884db609e5
institution Kabale University
issn 1004-2539
language zho
publishDate 2015-01-01
publisher Editorial Office of Journal of Mechanical Transmission
record_format Article
series Jixie chuandong
spelling doaj-art-a0bdc999b56e4729b1d034884db609e52025-01-10T14:06:03ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392015-01-013911311729918058Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope SpectrumZhong XianyouZhao ChunghuaChen BaojiaTian HongliangAccording to modulation characteristics of rotating machinery fault vibration signals and limitation of the traditional envelope spectrum analysis needs to rely on experience for determining the parameters of band- pass filter,a fault diagnosis method for rotating machinery based on maximum correlated kurtosis deconvolution( MCKD) and envelope spectrum is proposed. Firstly,by using MCKD,the noise in the rotating machinery vibration signal is reduced,then the envelope spectrum is obtained by Hilbert transform to identify the fault,simulation signal analysis and engineering applications demonstrated the effectiveness of the method.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.07.028
spellingShingle Zhong Xianyou
Zhao Chunghua
Chen Baojia
Tian Hongliang
Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope Spectrum
Jixie chuandong
title Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope Spectrum
title_full Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope Spectrum
title_fullStr Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope Spectrum
title_full_unstemmed Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope Spectrum
title_short Fault Diagnosis Method of Rotating Machinery based on Maximum Correlation Kurtosis Deconvolution and Envelope Spectrum
title_sort fault diagnosis method of rotating machinery based on maximum correlation kurtosis deconvolution and envelope spectrum
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.07.028
work_keys_str_mv AT zhongxianyou faultdiagnosismethodofrotatingmachinerybasedonmaximumcorrelationkurtosisdeconvolutionandenvelopespectrum
AT zhaochunghua faultdiagnosismethodofrotatingmachinerybasedonmaximumcorrelationkurtosisdeconvolutionandenvelopespectrum
AT chenbaojia faultdiagnosismethodofrotatingmachinerybasedonmaximumcorrelationkurtosisdeconvolutionandenvelopespectrum
AT tianhongliang faultdiagnosismethodofrotatingmachinerybasedonmaximumcorrelationkurtosisdeconvolutionandenvelopespectrum