Cargando…
An Effective Bearing Fault Diagnosis Technique via Local Robust Principal Component Analysis and Multi-Scale Permutation Entropy
The acquired bearing fault signal usually reveals nonlinear and non-stationary nature. Moreover, in the actual environment, some other interference components and strong background noise are unavoidable, which lead to the fault feature signal being weak. Considering the above issues, an effective be...
Autores principales: | Ge, Mao, Lv, Yong, Zhang, Yi, Yi, Cancan, Ma, Yubo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514291/ http://dx.doi.org/10.3390/e21100959 |
Ejemplares similares
-
Optimized Adaptive Local Iterative Filtering Algorithm Based on Permutation Entropy for Rolling Bearing Fault Diagnosis
por: Lv, Yong, et al.
Publicado: (2018) -
A Joint Fault Diagnosis Scheme Based on Tensor Nuclear Norm Canonical Polyadic Decomposition and Multi-Scale Permutation Entropy for Gears
por: Ge, Mao, et al.
Publicado: (2018) -
Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis
por: Yasir, Muhammad Naveed, et al.
Publicado: (2018) -
A Rolling Bearing Fault Classification Scheme Based on k-Optimized Adaptive Local Iterative Filtering and Improved Multiscale Permutation Entropy
por: Zhang, Yi, et al.
Publicado: (2021) -
A Novel Demodulation Analysis Technique for Bearing Fault Diagnosis via Energy Separation and Local Low-Rank Matrix Approximation
por: Lv, Yong, et al.
Publicado: (2019)