Cargando…
Bearing Fault Feature Extraction and Fault Diagnosis Method Based on Feature Fusion
Bearing is one of the most important parts of rotating machinery with high failure rate, and its working state directly affects the performance of the entire equipment. Hence, it is of great significance to diagnose bearing faults, which can contribute to guaranteeing running stability and maintenan...
Autores principales: | Zhu, Huibin, He, Zhangming, Wei, Juhui, Wang, Jiongqi, Zhou, Haiyin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038486/ https://www.ncbi.nlm.nih.gov/pubmed/33916563 http://dx.doi.org/10.3390/s21072524 |
Ejemplares similares
-
Bearing Fault Diagnosis Method Based on Improved Singular Value Decomposition Package
por: Zhu, Huibin, et al.
Publicado: (2023) -
Fault Detection Based on Multi-Dimensional KDE and Jensen–Shannon Divergence
por: Wei, Juhui, et al.
Publicado: (2021) -
Fault Identification for a Closed-Loop Control System Based on an Improved Deep Neural Network
por: Sun, Bowen, et al.
Publicado: (2019) -
A Deep Neural Network-Based Feature Fusion for Bearing Fault Diagnosis
por: Hoang, Duy Tang, et al.
Publicado: (2021) -
Research on rolling bearing fault diagnosis based on multi-dimensional feature extraction and evidence fusion theory
por: Li, Jingchao, et al.
Publicado: (2019)