Nonlinear Dynamic Process Monitoring Based on Discriminative Denoising Autoencoder and Canonical Variate Analysis

Modern industrial processes are characterized by increasing complexity, often exhibiting pronounced dynamic behaviors and significant nonlinearity. Addressing these dynamic and nonlinear characteristics is essential for effective process monitoring. However, many existing methods for process monitor...

Full description

Saved in:

Bibliographic Details
Published in:	Actuators Vol. 13; no. 11; p. 440
Main Authors:	Liang, Jun, Liu, Daoguang, Zhan, Yinxiao, Fan, Jiayu
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2024
Subjects:	canonical variate analysis (CVA) Classification Correlation analysis Data processing denoising autoencoder (DAE) Discriminant analysis dynamics Effectiveness Fault diagnosis Feature extraction Methods Monitoring Noise reduction Nonlinear dynamics nonlinear process Nonlinearity process monitoring Redundancy Variables Tennessee United States > US
ISSN:	2076-0825, 2076-0825
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!