Fault detection and isolation for dynamic non-stationary processes with stationary subspace-based canonical variate analysis-Reference-Cited by-同舟云学术

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Fault detection and isolation for dynamic non-stationary processes with stationary subspace-based canonical variate analysis

Published:2024-08 Issue: Volume:295 Page:120196
ISSN:0009-2509
Container-title:Chemical Engineering Science
language:en
Short-container-title:Chemical Engineering Science

Author:

Ji Hongquan^ORCID,Sheng Nan^ORCID,Liu Huabo^ORCID,Huang Keke

Funder

NSFC

Publisher

Elsevier BV

Reference31 articles.

1. Reconstruction-based contribution for process monitoring;Alcala;Automatica,2009

2. Exponential stationary subspace analysis for stationary feature analytics and adaptive nonstationary process monitoring;Chen;IEEE Trans. Ind. Inform.,2021

3. A machine-learning architecture for sensor fault detection, isolation, and accommodation in digital twins;Darvishi;IEEE Sens. J.,2023

4. Incipient fault detection for dynamic chemical processes based on enhanced CVDA integrated with probability information and fault-sensitive features;Deng;J. Process Control,2022

5. Statistical monitoring of the covariance matrix in multivariate processes: a literature review;Ebadi;J. Qual. Technol.,2022

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