Cargando…
A Hydraulic Pump Fault Diagnosis Method Based on the Modified Ensemble Empirical Mode Decomposition and Wavelet Kernel Extreme Learning Machine Methods
To address the problem that the faults in axial piston pumps are complex and difficult to effectively diagnose, an integrated hydraulic pump fault diagnosis method based on the modified ensemble empirical mode decomposition (MEEMD), autoregressive (AR) spectrum energy, and wavelet kernel extreme lea...
Autores principales: | Li, Zhenbao, Jiang, Wanlu, Zhang, Sheng, Sun, Yu, Zhang, Shuqing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068089/ https://www.ncbi.nlm.nih.gov/pubmed/33917254 http://dx.doi.org/10.3390/s21082599 |
Ejemplares similares
-
Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition
por: Lei, Yaguo, et al.
Publicado: (2013) -
A Compound Fault Diagnosis for Rolling Bearings Method Based on Blind Source Separation and Ensemble Empirical Mode Decomposition
por: Wang, Huaqing, et al.
Publicado: (2014) -
Fault Feature Extraction of Hydraulic Pumps Based on Symplectic Geometry Mode Decomposition and Power Spectral Entropy
por: Zheng, Zhi, et al.
Publicado: (2019) -
Noise Eliminated Ensemble Empirical Mode Decomposition Scalogram Analysis for Rotating Machinery Fault Diagnosis
por: Faysal, Atik, et al.
Publicado: (2021) -
A Comprehensive Fault Diagnosis Method for Rolling Bearings Based on Refined Composite Multiscale Dispersion Entropy and Fast Ensemble Empirical Mode Decomposition
por: Zhang, Weibo, et al.
Publicado: (2019)