Study on the Preprocessing Method of Rolling Bearing Signal based on LFK and Entropy Difference Spectrum Criterion
Aiming at the problem that the fault feature of rolling bearing can be easily overwhelmed by random noise,a novel denoising method on the basis of local characteristic- scale decomposition and Fast Kurtogram( LFK) is presented. Firstly,the signal is decomposed by local characteristic- scale decompos...
Saved in:
| Main Authors: | Yu He, Li Hongru, Sun Jian, Xu Baohua |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2016-01-01
|
| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.12.007 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD
by: XIE Guizhong, et al.
Published: (2025-08-01) -
Identification of Optimal Demodulation Frequency Band and Its Application in Fault Diagnosis of Rolling Element Bearings
by: Bingyan CHEN, et al.
Published: (2019-09-01) -
BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY
by: CHEN HuiHong
Published: (2019-01-01) -
Fault Feature Extraction for Rolling Bearing based on LMD Energy Entropy
by: Xu Le, et al.
Published: (2019-01-01) -
Performance Degradation Evaluation of Rolling Bearing based on Improved Fuzzy Entropy and Grey Relation
by: Li Cheng, et al.
Published: (2022-01-01)