Weak feature extraction for early wear of connecting rod bearings under transient conditions
As we all know, it is difficult to extract weak feature for early wear of connecting rod bearings under transient conditions. In order to solve the problem, a method of extracting wear features for connecting rod bearings based on variational modal decomposition (VMD) adaptive noise reduction and co...
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doaj-1fc5c5f3133f40d9a585bdf7176a76c82020-11-25T04:09:46ZengJVE InternationalJournal of Vibroengineering1392-87162538-84602020-11-012271559157010.21595/jve.2019.2035220352Weak feature extraction for early wear of connecting rod bearings under transient conditionsGang Ren0Jide Jia1Jianmin Mei2Automobile NCO School, Army Military Transportation University, Bengbu, ChinaState Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, ChinaProjection Equipment Support Department, Army Military Transportation University, Tianjin, ChinaAs we all know, it is difficult to extract weak feature for early wear of connecting rod bearings under transient conditions. In order to solve the problem, a method of extracting wear features for connecting rod bearings based on variational modal decomposition (VMD) adaptive noise reduction and computational order tracking (COT) was proposed. Firstly, the vibration signals of internal combustion engine block under transient operating conditions were collected, and the signals were reordered to satisfy the order tracking condition. Then, interpolation and fitting techniques were used to map the signal from the time domain space to the angular domain space. Next, the VMD was used to decompose the angular domain signal into multiple modal components, and the autocorrelation function (ACF) was used to denoise the modal components adaptively. Finally, the signal was reconstructed to conduct COT analysis, and the wear features of connecting rod bearing were extracted by average COT spectrum. The simulation analysis and the simulation experiment of the connecting rod bearing fault show that the proposed method is effective, and the weak features for early wear of connecting rod bearing of internal combustion engine are extracted.https://www.jvejournals.com/article/20352variational mode decompositionadaptive de-noisingcomputational order trackingfeature extraction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gang Ren Jide Jia Jianmin Mei |
spellingShingle |
Gang Ren Jide Jia Jianmin Mei Weak feature extraction for early wear of connecting rod bearings under transient conditions Journal of Vibroengineering variational mode decomposition adaptive de-noising computational order tracking feature extraction |
author_facet |
Gang Ren Jide Jia Jianmin Mei |
author_sort |
Gang Ren |
title |
Weak feature extraction for early wear of connecting rod bearings under transient conditions |
title_short |
Weak feature extraction for early wear of connecting rod bearings under transient conditions |
title_full |
Weak feature extraction for early wear of connecting rod bearings under transient conditions |
title_fullStr |
Weak feature extraction for early wear of connecting rod bearings under transient conditions |
title_full_unstemmed |
Weak feature extraction for early wear of connecting rod bearings under transient conditions |
title_sort |
weak feature extraction for early wear of connecting rod bearings under transient conditions |
publisher |
JVE International |
series |
Journal of Vibroengineering |
issn |
1392-8716 2538-8460 |
publishDate |
2020-11-01 |
description |
As we all know, it is difficult to extract weak feature for early wear of connecting rod bearings under transient conditions. In order to solve the problem, a method of extracting wear features for connecting rod bearings based on variational modal decomposition (VMD) adaptive noise reduction and computational order tracking (COT) was proposed. Firstly, the vibration signals of internal combustion engine block under transient operating conditions were collected, and the signals were reordered to satisfy the order tracking condition. Then, interpolation and fitting techniques were used to map the signal from the time domain space to the angular domain space. Next, the VMD was used to decompose the angular domain signal into multiple modal components, and the autocorrelation function (ACF) was used to denoise the modal components adaptively. Finally, the signal was reconstructed to conduct COT analysis, and the wear features of connecting rod bearing were extracted by average COT spectrum. The simulation analysis and the simulation experiment of the connecting rod bearing fault show that the proposed method is effective, and the weak features for early wear of connecting rod bearing of internal combustion engine are extracted. |
topic |
variational mode decomposition adaptive de-noising computational order tracking feature extraction |
url |
https://www.jvejournals.com/article/20352 |
work_keys_str_mv |
AT gangren weakfeatureextractionforearlywearofconnectingrodbearingsundertransientconditions AT jidejia weakfeatureextractionforearlywearofconnectingrodbearingsundertransientconditions AT jianminmei weakfeatureextractionforearlywearofconnectingrodbearingsundertransientconditions |
_version_ |
1724421821604823040 |