A Lightweight and Efficient Multimodal Feature Fusion Network for Bearing Fault Diagnosis in Industrial Applications

A Lightweight and Efficient Multimodal Feature Fusion Network for Bearing Fault Diagnosis in Industrial Applications

To address the issues of single-structured feature input channels, insufficient feature learning capabilities in noisy environments, and large model parameter sizes in intelligent diagnostic models for mechanical equipment, a lightweight and efficient multimodal feature fusion convolutional neural n...

Full description

Saved in:
Bibliographic Details
Main Authors: Chaoquan Mo, Ke Huang, Wenhan Li, Kaibo Xu
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
mechanical equipment fault diagnosis
parallel time–frequency dual-stream
multimodal feature fusion
convolutional attention mechanism
graphical user interface
Online Access:https://www.mdpi.com/1424-8220/24/22/7139
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/24/22/7139

Similar Items