Dynamic statistical process monitoring based on online dynamic discriminative feature analysis-Reference-Cited by-同舟云学术

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Dynamic statistical process monitoring based on online dynamic discriminative feature analysis

Published:2021-07 Issue: Volume:103 Page:67-75
ISSN:0959-1524
Container-title:Journal of Process Control
language:en
Short-container-title:Journal of Process Control

Author:

Li Shanzhi,Tong Chudong^ORCID,Chen Yang,Lan Ting

Funder

National Natural Science Foundation of China

Zhejiang Province Public Welfare Technology Application Research Project

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Modelling and Simulation,Control and Systems Engineering

Reference33 articles.

1. Process control practice and education: past, present and future;Bequette;Comput. Chem. Eng.,2019

2. Canonical correlation analysis-based explicit relation discovery for statistical process monitoring;Meng;J. Franklin. Inst.,2020

3. Bridging systems theory and data science: A unifying review of dynamic latent variable analytics and process monitoring;Qin;Annu. Rev. Control,2020

4. Laplacian regularized robust principal component analysis for process monitoring;Xiu;J. Process Control,2020

5. A projective and discriminative dictionary learning for high-dimensional process monitoring with industrial applications;Huang;IEEE Trans. Ind. Inform.,2021

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1. Incipient fault detection for dynamic processes with canonical variate residual statistics analysis;Chemometrics and Intelligent Laboratory Systems;2024-09

2. Modified performance-enhanced PCA for incipient fault detection of dynamic industrial processes;Journal of Process Control;2023-11

3. A Method for Online Monitoring Data Release of Composite Submarine Cable Based on Horizontal Federated Learning;Scalable Computing: Practice and Experience;2023-09-10

4. Hybrid-Order Graph Embedded Distributed Encoder-Decoder for Multiunit Industrial Plant-Wide Process Monitoring;IEEE Transactions on Automation Science and Engineering;2023

5. A supervised multisegment probability density analysis method for incipient fault detection of quality indicator;Journal of Process Control;2022-08

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