Cargando…
Fault diagnosis of anti-friction bearings based on Bi-dimensional ensemble local mean decomposition and optimized dynamic least square support vector machine
In order to ensure the normal operation of rotating equipment, it is very important to quickly and efficiently diagnose the faults of anti-friction bearings. Hereto, fault diagnosis of anti-friction bearings based on Bi-dimensional ensemble local mean decomposition and optimized dynamic least square...
Autores principales: | Xiong, Zhengqiang, Han, Chang, Zhang, Guorong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584940/ https://www.ncbi.nlm.nih.gov/pubmed/37853075 http://dx.doi.org/10.1038/s41598-023-44996-6 |
Ejemplares similares
-
Bearing Fault Diagnosis Using a Particle Swarm Optimization-Least Squares Wavelet Support Vector Machine Classifier
por: Van, Mien, et al.
Publicado: (2020) -
Adaptive filtering
:
fundamentals of least mean squares with MATLAB
por: Poularikas, Alexander D
Publicado: (2015) -
Simulation of Friction Fault of Lightly Loaded Flywheel Bearing Cage and Its Fault Characteristics
por: Chen, Changrui, et al.
Publicado: (2022) -
Bearing Fault Diagnosis Using Piecewise Aggregate Approximation and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise
por: Hu, Lei, et al.
Publicado: (2022) -
Fast Algorithms for Structured Least Squares and Total Least Squares Problems
por: Kalsi, Anoop, et al.
Publicado: (2006)