Sparse Signal Representations of Bearing Fault Signals for Exhibiting Bearing Fault Features
Sparse signal representations attract much attention in the community of signal processing because only a few coefficients are required to represent a signal and these coefficients make the signal understandable. For bearing faults’ diagnosis, bearing faults signals collected from transducers are of...
Saved in:
Main Authors: | Wei Peng, Dong Wang, Changqing Shen, Dongni Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2016-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2016/1835127 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation
by: Jianming Ding, et al.
Published: (2019-01-01) -
A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation
by: Xing Yuan, et al.
Published: (2022-01-01) -
Single Feature Extraction Method of Bearing Fault Signals Based on Slope Entropy
by: Erna Shi
Published: (2022-01-01) -
Adaptive Morphological Feature Extraction and Support Vector Regressive Classification for Bearing Fault Diagnosis
by: Jun Shuai, et al.
Published: (2017-01-01) -
Bearing Fault Diagnosis Based on Multilayer Domain Adaptation
by: Bingru Yang, et al.
Published: (2020-01-01)