A 1.5D Spectral Kurtosis-Guided TQWT Method and Its Application in Bearing Fault Detection
Bearings are the key parts of rotating machinery, and their operation status is related to the operation safety of the whole equipment. Vibration signals often contain periodic impulse components which can reflect the fault state of bearings. However, due to the interference of signal transmission p...
Saved in:
Main Authors: | Xiong Zhang, Ming Zhang, Shuting Wan, Rujiang Hao, Yuling He, Xiaolong Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2021/5554981 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Spectrum Detection Approach for Bearing Fault Signal Based on Spectral Kurtosis
by: Yunfeng Li, et al.
Published: (2017-01-01) -
Multistage Fault Feature Extraction of Consistent Optimization for Rolling Bearings Based on Correlated Kurtosis
by: Long Zhang, et al.
Published: (2020-01-01) -
A Novel Method for Extracting Maximum Kurtosis Component and Its Applications in Rolling Bearing Fault Diagnosis
by: Yonggang Xu, et al.
Published: (2019-01-01) -
An Adaptive Spectral Kurtosis Method Based on Optimal Filter
by: Yanli Yang, et al.
Published: (2017-01-01) -
Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing
by: Xiaolong Wang, et al.
Published: (2020-01-01)