Rolling Bearing Fault Diagnosis Using Multi-Sensor Data Fusion Based on 1D-CNN Model

Rolling Bearing Fault Diagnosis Using Multi-Sensor Data Fusion Based on 1D-CNN Model

To satisfy the requirements of the end-to-end fault diagnosis of rolling bearings, a hybrid model, based on optimal SWD and 1D-CNN, with the layer of multi-sensor data fusion, is proposed in this paper. Firstly, the BAS optimal algorithm is adopted to obtain the optimal parameters of SWD. After that...

Full description

Bibliographic Details
Main Authors: Hongwei Wang, Wenlei Sun, Li He, Jianxing Zhou
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Entropy
Subjects:
end-to-end fault diagnosis of rolling bearings
data fusion
swarm decomposition
convolutional neural network
Online Access:https://www.mdpi.com/1099-4300/24/5/573

Internet

https://www.mdpi.com/1099-4300/24/5/573

Similar Items