Cargando…
Hybrid Data Fusion DBN for Intelligent Fault Diagnosis of Vehicle Reducers
Given its importance, fault diagnosis has attracted considerable attention in the literature, and several machine learning methods have been proposed to discover the characteristics of different aspects in fault diagnosis. In this paper, we propose a Hybrid Deep Belief Network (HDBN) learning model...
Autores principales: | Zhang, Tianfan, Li, Zhe, Deng, Zhenghong, Hu, Bin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603551/ https://www.ncbi.nlm.nih.gov/pubmed/31159290 http://dx.doi.org/10.3390/s19112504 |
Ejemplares similares
-
An AVMD-DBN-ELM Model for Bearing Fault Diagnosis
por: Lei, Xue, et al.
Publicado: (2022) -
Fault Diagnosis Method for Industrial Robots Based on DBN Joint Information Fusion Technology
por: Jiao, Jian, et al.
Publicado: (2022) -
Application of DBN and GWO-SVM in analog circuit fault diagnosis
por: Su, Xiyuan, et al.
Publicado: (2021) -
Adaptive Diagnosis for Fault Tolerant Data Fusion Based on α-Rényi Divergence Strategy for Vehicle Localization
por: Makkawi, Khoder, et al.
Publicado: (2021) -
Sensor Fault Detection and Signal Restoration in Intelligent Vehicles
por: Byun, Yeun-Sub, et al.
Publicado: (2019)