Cargando…
Tool Wear Condition Monitoring by Combining Variational Mode Decomposition and Ensemble Learning
Most online tool condition monitoring (TCM) methods easily cause machining interference. To solve this problem, we propose a method based on the analysis of the spindle motor current signal of a machine tool. Firstly, cutting experiments under multi-conditions were carried out at a Fanuc vertical ma...
Autores principales: | Yuan, Jun, Liu, Libing, Yang, Zeqing, Zhang, Yanrui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663253/ https://www.ncbi.nlm.nih.gov/pubmed/33121086 http://dx.doi.org/10.3390/s20216113 |
Ejemplares similares
-
Ensemble streamflow forecasting based on variational mode decomposition and long short term memory
por: Sun, Xiaomei, et al.
Publicado: (2022) -
Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition
por: Chang, Kang-Ming
Publicado: (2010) -
Tool Wear Condition Monitoring Method Based on Deep Learning with Force Signals
por: Zhang, Yaping, et al.
Publicado: (2023) -
Combination of variational mode decomposition and coherent factor for ultrasound computer tomography
por: Wang, Shanshan, et al.
Publicado: (2022) -
A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition
por: Zhao, Zhidong, et al.
Publicado: (2013)