A Rolling Bearing Fault Diagnosis Method Based on Switchable Normalization and a Deep Convolutional Neural Network

A Rolling Bearing Fault Diagnosis Method Based on Switchable Normalization and a Deep Convolutional Neural Network

Aiming to address the problems of a low fault detection rate and poor diagnosis performance under different loads and noise environments, a rolling bearing fault diagnosis method based on switchable normalization and a deep convolutional neural network (SNDCNN) is proposed. The method effectively ex...

Full description

Bibliographic Details
Main Authors: Xiaoyu Han, Yunpeng Cao, Junqi Luan, Ran Ao, Weixing Feng, Shuying Li
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Machines
Subjects:
deep convolutional neural network
fault diagnosis
K-max pooling
rolling bearing
switchable normalization
Online Access:https://www.mdpi.com/2075-1702/11/2/185

Internet

https://www.mdpi.com/2075-1702/11/2/185

Similar Items