Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD
Vibration signals of rolling element bearings during operation are always very complex, random strongly and broadband. Adaptive Local Iterative Filtering Decomposition (ALIFD) can overcome the smoothness and adaptive flaws of Iterative Filtering Decomposition (IFD), but it is so susceptible to rando...
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doaj-9c87818030254fae88935eb66bfe00b82020-11-25T02:20:55ZengJVE InternationalJournal of Vibroengineering1392-87162538-84602020-05-0122355656510.21595/jve.2019.2088320883Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFDLei Zhao0Yongxiang Zhang1Danchen Zhu2Naval University of Engineering, Wuhan, 430033, ChinaNaval University of Engineering, Wuhan, 430033, ChinaNaval University of Engineering, Wuhan, 430033, ChinaVibration signals of rolling element bearings during operation are always very complex, random strongly and broadband. Adaptive Local Iterative Filtering Decomposition (ALIFD) can overcome the smoothness and adaptive flaws of Iterative Filtering Decomposition (IFD), but it is so susceptible to random noise that it’s less effective. Here, spatial correlation was proposed. Firstly, the signal was denoised by spatial correlation and decomposed into several modes by ALIFD. Finally, the envelope demodulation was analyzed to extract fault feature. The simulating signal analysis and bearing fault simulator show that this method can be available for separating different frequencies of bearing fault vibration signals.https://www.jvejournals.com/article/20883rolling element bearingspatial correlationalifdfault diagnosis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lei Zhao Yongxiang Zhang Danchen Zhu |
spellingShingle |
Lei Zhao Yongxiang Zhang Danchen Zhu Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD Journal of Vibroengineering rolling element bearing spatial correlation alifd fault diagnosis |
author_facet |
Lei Zhao Yongxiang Zhang Danchen Zhu |
author_sort |
Lei Zhao |
title |
Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD |
title_short |
Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD |
title_full |
Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD |
title_fullStr |
Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD |
title_full_unstemmed |
Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD |
title_sort |
rolling element bearing weak fault diagnosis based on spatial correlation and alifd |
publisher |
JVE International |
series |
Journal of Vibroengineering |
issn |
1392-8716 2538-8460 |
publishDate |
2020-05-01 |
description |
Vibration signals of rolling element bearings during operation are always very complex, random strongly and broadband. Adaptive Local Iterative Filtering Decomposition (ALIFD) can overcome the smoothness and adaptive flaws of Iterative Filtering Decomposition (IFD), but it is so susceptible to random noise that it’s less effective. Here, spatial correlation was proposed. Firstly, the signal was denoised by spatial correlation and decomposed into several modes by ALIFD. Finally, the envelope demodulation was analyzed to extract fault feature. The simulating signal analysis and bearing fault simulator show that this method can be available for separating different frequencies of bearing fault vibration signals. |
topic |
rolling element bearing spatial correlation alifd fault diagnosis |
url |
https://www.jvejournals.com/article/20883 |
work_keys_str_mv |
AT leizhao rollingelementbearingweakfaultdiagnosisbasedonspatialcorrelationandalifd AT yongxiangzhang rollingelementbearingweakfaultdiagnosisbasedonspatialcorrelationandalifd AT danchenzhu rollingelementbearingweakfaultdiagnosisbasedonspatialcorrelationandalifd |
_version_ |
1724868929223917568 |