Cargando…
Boosted Convolutional Neural Network Algorithm for the Classification of the Bearing Fault form 1-D Raw Sensor Data
Renewable energy sources are a growing branch of industry. One such source is wind farms, which have significantly increased their number over recent years. Alongside the increased number of turbines, maintenance problems are growing. There is a need for newer and less intrusive predictive maintenan...
Autores principales: | Knap, Paweł, Lalik, Krzysztof, Bałazy, Patryk |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181244/ https://www.ncbi.nlm.nih.gov/pubmed/37177504 http://dx.doi.org/10.3390/s23094295 |
Ejemplares similares
-
Multi-Fault Classification and Diagnosis of Rolling Bearing Based on Improved Convolution Neural Network
por: Zhang, Xiong, et al.
Publicado: (2023) -
An Ensemble Convolutional Neural Networks for Bearing Fault Diagnosis Using Multi-Sensor Data
por: Liu, Yang, et al.
Publicado: (2019) -
Sensor Data-Driven Bearing Fault Diagnosis Based on Deep Convolutional Neural Networks and S-Transform
por: Li, Guoqiang, et al.
Publicado: (2019) -
Application of Convolutional Neural Network in Motor Bearing Fault Diagnosis
por: Zhou, Shuiqin, et al.
Publicado: (2022) -
A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors
por: Toma, Rafia Nishat, et al.
Publicado: (2021)