Cargando…
A Two-Stage, Intelligent Bearing-Fault-Diagnosis Method Using Order-Tracking and a One-Dimensional Convolutional Neural Network with Variable Speeds
When performing fault diagnosis tasks on bearings, the change of any bearing’s rotation speed will cause the frequency spectrum of bearing fault characteristics to be blurred. This makes it difficult to extract stable fault features based on manual or intelligent methods, resulting in a decrease in...
Autores principales: | Ji, Mengyu, Peng, Gaoliang, He, Jun, Liu, Shaohui, Chen, Zhao, Li, Sijue |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863739/ https://www.ncbi.nlm.nih.gov/pubmed/33498161 http://dx.doi.org/10.3390/s21030675 |
Ejemplares similares
-
Application of a new one-dimensional deep convolutional neural network for intelligent fault diagnosis of rolling bearings
por: Xie, Shenglong, et al.
Publicado: (2020) -
An Anti-UAV Long-Term Tracking Method with Hybrid Attention Mechanism and Hierarchical Discriminator
por: Cheng, Feng, et al.
Publicado: (2022) -
Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain
por: Hakim, Mohammed, et al.
Publicado: (2022) -
Bearing Fault Diagnosis under Variable Speed Using Convolutional Neural Networks and the Stochastic Diagonal Levenberg-Marquardt Algorithm
por: Tra, Viet, et al.
Publicado: (2017) -
WDA: An Improved Wasserstein Distance-Based Transfer Learning Fault Diagnosis Method
por: Zhu, Zhiyu, et al.
Publicado: (2021)