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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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 |
_version_ |
1725503900267577344 |