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Fault Feature-Extraction Method of Aviation Bearing Based on Maximum Correlation Re’nyi Entropy and Phase-Space Reconstruction Technology
- Source :
- Entropy, Vol 24, Iss 10, p 1459 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- To address the difficulty of extracting the features of composite-fault signals under a low signal-to-noise ratio and complex noise conditions, a feature-extraction method based on phase-space reconstruction and maximum correlation Re’nyi entropy deconvolution is proposed. Using the Re’nyi entropy as the performance index, which allows for a favorable trade-off between sporadic noise stability and fault sensitivity, the noise-suppression and decomposition characteristics of singular-value decomposition are fully utilized and integrated into the feature extraction of composite-fault signals by the maximum correlation Re’nyi entropy deconvolution. Verification based on simulation, experimental data, and a bench test proves that the proposed method is superior to the existing methods regarding the extraction of composite-fault signal features.
Details
- Language :
- English
- ISSN :
- 10994300
- Volume :
- 24
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Entropy
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.99a12f922de4667a038f381d59de7fe
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/e24101459