Acoustic Fault Diagnosis Method for Rotating Machinery Based on Collaborative Perception Information Aggregation Guidance Network

Acoustic Fault Diagnosis Method for Rotating Machinery Based on Collaborative Perception Information Aggregation Guidance Network

Abstract The non-contact and directional nature of acoustic fault diagnosis offers a distinct advantage for fault detection in complex environments, ensuring the safe and stable operation of rotating machinery. However, challenges such as complex working conditions and data imbalance significantly h...

Full description

Saved in:
Bibliographic Details
Main Authors: Chaofan Li, Fan Zhang, Qichen Wang, Yufei Han, Tianrui Li, Fei Teng, Cai Yi, Yongmeng Wu
Format: Article
Language:English
Published: Springer 2025-06-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Deep learning
Intelligent fault diagnosis
Acoustic data
Variable working conditions
Anti-imbalanced data
Online Access:https://doi.org/10.1007/s44196-025-00862-z
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1007/s44196-025-00862-z

Similar Items