Single Feature Extraction Method of Bearing Fault Signals Based on Slope Entropy
As an entropy representing the complexity of sequence, slope entropy (SloE) is applied to feature extraction of bearing signal for the first time. With the advantage of slope entropy in feature extraction, the effectiveness of bearing fault signal diagnosis can be verified. Five different kinds of e...
Saved in:
Main Author: | Erna Shi |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2022/6808641 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fault Feature Extraction for Rolling Bearing based on LMD Energy Entropy
by: Xu Le, et al.
Published: (2019-01-01) -
Feature Extraction Strategy with Improved Permutation Entropy and Its Application in Fault Diagnosis of Bearings
by: Fan Jiang, et al.
Published: (2018-01-01) -
Sparse Signal Representations of Bearing Fault Signals for Exhibiting Bearing Fault Features
by: Wei Peng, et al.
Published: (2016-01-01) -
A Fault Feature Extraction Method for Rolling Bearing Based on Intrinsic Time-Scale Decomposition and AR Minimum Entropy Deconvolution
by: Jiakai Ding, et al.
Published: (2021-01-01) -
A New Method of Fault Feature Extraction Based on Hierarchical Dispersion Entropy
by: Peng Chen, et al.
Published: (2021-01-01)