Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformation

The generalized S transform (GST) can flexibly adjust the change trend of the fundamental window function according to the frequency distribution characteristics and the time-frequency emphasis of vibration signal. Also, this transform can accelerate or slow down the time-band width change along wit...

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Main Authors: Jianhua Cai, Yongliang Xiao
Format: Article
Language:English
Published: JVE International 2017-09-01
Series:Journal of Vibroengineering
Subjects:
Online Access:https://www.jvejournals.com/article/18244
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spelling doaj-9465dbc316d24048ace215472d3ce9f82020-11-24T23:42:34ZengJVE InternationalJournal of Vibroengineering1392-87162538-84602017-09-011964221423010.21595/jve.2017.1824418244Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformationJianhua Cai0Yongliang Xiao1Cooperative Innovation Center for the Construction and Development of Dongting Lake Ecological Economic Zone, Hunan University of Arts and Science, Changde 415000, ChinaSchool of Information Technology and Management, Hunan University of Finance and Economics, Changsha 410205, ChinaThe generalized S transform (GST) can flexibly adjust the change trend of the fundamental window function according to the frequency distribution characteristics and the time-frequency emphasis of vibration signal. Also, this transform can accelerate or slow down the time-band width change along with the frequency, in order to make the amplitude of the fundamental window function present the various nonlinear changes. These features are very constructive significance for signal analysis and processing. A time-frequency analysis method based on the generalized S transformation is introduced to the fault diagnosis of bearing. And the application principle and the steps of method applied in fault diagnosis are given. Simulated signals and the actual bearing fault signals from inner race, outer race and rolling body are processed to verify the validity of the proposed method. Results show that the method can effectively enhance the resolution of vibration signal not only in time domain but also in frequency domain. The fault characteristic frequency can be extracted from the reconstructed signal, and the status of bearing and the fault type of bearing can be obviously distinguished. The presented time-frequency method effectively improves the accuracy of the fault diagnosis of bearings.https://www.jvejournals.com/article/18244generalized S transformtime-frequency analysishigh resolution processingbearing fault diagnosis
collection DOAJ
language English
format Article
sources DOAJ
author Jianhua Cai
Yongliang Xiao
spellingShingle Jianhua Cai
Yongliang Xiao
Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformation
Journal of Vibroengineering
generalized S transform
time-frequency analysis
high resolution processing
bearing fault diagnosis
author_facet Jianhua Cai
Yongliang Xiao
author_sort Jianhua Cai
title Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformation
title_short Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformation
title_full Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformation
title_fullStr Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformation
title_full_unstemmed Time-frequency analysis method of bearing fault diagnosis based on the generalized S transformation
title_sort time-frequency analysis method of bearing fault diagnosis based on the generalized s transformation
publisher JVE International
series Journal of Vibroengineering
issn 1392-8716
2538-8460
publishDate 2017-09-01
description The generalized S transform (GST) can flexibly adjust the change trend of the fundamental window function according to the frequency distribution characteristics and the time-frequency emphasis of vibration signal. Also, this transform can accelerate or slow down the time-band width change along with the frequency, in order to make the amplitude of the fundamental window function present the various nonlinear changes. These features are very constructive significance for signal analysis and processing. A time-frequency analysis method based on the generalized S transformation is introduced to the fault diagnosis of bearing. And the application principle and the steps of method applied in fault diagnosis are given. Simulated signals and the actual bearing fault signals from inner race, outer race and rolling body are processed to verify the validity of the proposed method. Results show that the method can effectively enhance the resolution of vibration signal not only in time domain but also in frequency domain. The fault characteristic frequency can be extracted from the reconstructed signal, and the status of bearing and the fault type of bearing can be obviously distinguished. The presented time-frequency method effectively improves the accuracy of the fault diagnosis of bearings.
topic generalized S transform
time-frequency analysis
high resolution processing
bearing fault diagnosis
url https://www.jvejournals.com/article/18244
work_keys_str_mv AT jianhuacai timefrequencyanalysismethodofbearingfaultdiagnosisbasedonthegeneralizedstransformation
AT yongliangxiao timefrequencyanalysismethodofbearingfaultdiagnosisbasedonthegeneralizedstransformation
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