2022
DOI: 10.3390/s22207973
|View full text |Cite
|
Sign up to set email alerts
|

A Fast Sparse Decomposition Based on the Teager Energy Operator in Extraction of Weak Fault Signals

Abstract: In order to diagnose an incipient fault in rotating machinery under complicated conditions, a fast sparse decomposition based on the Teager energy operator (TEO) is proposed in this paper. In this proposed method, firstly, the TEO is employed to enhance the envelope of the impulses, which is more sensitive to frequency and can eliminate the low-frequency harmonic component and noise; secondly, a smoothing filtering algorithm was adopted to suppress the noise in the TEO envelope; thirdly, the fault signal was r… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2025
2025

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 19 publications
0
1
0
Order By: Relevance
“…In [20], a method based on maximum correlated Kurtosis deconvolution (MCKD) is proposed for extracting subtle bearing faults. Meng et al [21] combines EMD with kurtosis for bearing fault diagnosis, and in [22], generalized S-transform and sparse decomposition are utilized for fault diagnosis under variable operating conditions. The methods described in the above-mentioned literature have all achieved signal denoising and fault diagnosis, yielding favorable experimental results.…”
Section: Signal Reconstruction Methods Based On Tkeo and Ssa-vmdmentioning
confidence: 99%
“…In [20], a method based on maximum correlated Kurtosis deconvolution (MCKD) is proposed for extracting subtle bearing faults. Meng et al [21] combines EMD with kurtosis for bearing fault diagnosis, and in [22], generalized S-transform and sparse decomposition are utilized for fault diagnosis under variable operating conditions. The methods described in the above-mentioned literature have all achieved signal denoising and fault diagnosis, yielding favorable experimental results.…”
Section: Signal Reconstruction Methods Based On Tkeo and Ssa-vmdmentioning
confidence: 99%