Cargando…
Fault Diagnosis for Rotating Machinery Using Multiscale Permutation Entropy and Convolutional Neural Networks
In view of the limitations of existing rotating machine fault diagnosis methods in single-scale signal analysis, a fault diagnosis method based on multi-scale permutation entropy (MPE) and multi-channel fusion convolutional neural networks (MCFCNN) is proposed. First, MPE quantitatively analyzes the...
Autores principales: | Li, Hongmei, Huang, Jinying, Yang, Xiwang, Luo, Jia, Zhang, Lidong, Pang, Yu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517452/ https://www.ncbi.nlm.nih.gov/pubmed/33286622 http://dx.doi.org/10.3390/e22080851 |
Ejemplares similares
-
Rotating Machinery Fault Diagnosis Based on Improved Multiscale Amplitude-Aware Permutation Entropy and Multiclass Relevance Vector Machine
por: Chen, Yinsheng, et al.
Publicado: (2019) -
The Optimized Multi-Scale Permutation Entropy and Its Application in Compound Fault Diagnosis of Rotating Machinery
por: Wang, Xianzhi, et al.
Publicado: (2019) -
Composite Multiscale Transition Permutation Entropy-Based Fault Diagnosis of Bearings
por: Guo, Jing, et al.
Publicado: (2022) -
Fault Diagnosis for Rolling Element Bearings Based on Feature Space Reconstruction and Multiscale Permutation Entropy
por: Zhang, Weibo, et al.
Publicado: (2019) -
A Lighted Deep Convolutional Neural Network Based Fault Diagnosis of Rotating Machinery
por: Ma, Shangjun, et al.
Publicado: (2019)