Denoising and Recognition Method for Weak Acoustic Abnormal Signals in Hot-Wall Hydrogenation Reactors Using DnCNN-CNN

Denoising and Recognition Method for Weak Acoustic Abnormal Signals in Hot-Wall Hydrogenation Reactors Using DnCNN-CNN

Accurate identification of damage in hot-wall hydrogenation reactors is a challenging and costly task. Acoustic Emission (AE) technology is considered a promising approach owing to its high sensitivity to micro-damages. However, during the operation of the hot-wall hydrogenation reactor, high-intens...

Full description

Saved in:
Bibliographic Details
Main Authors: Xueqin Wang, Shilin Xu, Yun Tu, Ying Zhang, Mingguo Peng
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Weak abnormal signals
acoustic emission technology
equipment health monitoring
denoising convolutional neural networks
Online Access:https://ieeexplore.ieee.org/document/11029235/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/11029235/

Similar Items