Research on Feature Extraction Method of Engine Misfire Fault Based on Signal Sparse Decomposition
Engine vibration signals are easy to be interfered by other noise, causing feature signals that represent its operating status get submerged and further leading to difficulty in engine fault diagnosis. In addition, most of the signals utilized to verify the extraction method are derived from numeric...
Saved in:
| Main Authors: | Canyi Du, Fei Jiang, Kang Ding, Feng Li, Feifei Yu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/6650932 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Bearing Fault Vibration Signal Feature Extraction and Recognition Method Based on EEMD Superresolution Sparse Decomposition
by: Zhang- Jian, et al.
Published: (2022-01-01) -
MISFIRE FAULT DIAGNOSIS OF GASOLINE ENGINES USING THE COSINE MEASURE OF SINGLE-VALUED NEUTROSOPHIC SETS
by: Xiaoqi Wang, et al.
Published: (2016-03-01) -
Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox
by: Jin XU, et al.
Published: (2021-10-01) -
A feature extraction method based on improved resonance sparse decomposition for early faults in rolling bearings
by: SUN Meng, et al.
Published: (2025-06-01) -
Feature extraction using sparse component decomposition for face classification
by: Hamid Reza Shahdoosti
Published: (2023-09-01)