Multi-block principal component analysis based on variable weight information and its application to multivariate process monitoring-Reference-Cited by-同舟云学术

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Multi-block principal component analysis based on variable weight information and its application to multivariate process monitoring

Published:2017-11-20 Issue:5 Volume:96 Page:1127-1141
ISSN:0008-4034
Container-title:The Canadian Journal of Chemical Engineering
language:en
Short-container-title:Can. J. Chem. Eng.

Author:

Wang Lei¹,Deng Xiaogang¹

Affiliation:

1. College of Information and Control Engineering; China University of Petroleum; Qingdao 266580 China

Funder

National Natural Science Foundation of China

China University of Petroleum, Beijing

Fundamental Research Funds for the Central Universities, China

Natural Science Foundation of Shandong Province

Publisher

Wiley

Subject

General Chemical Engineering

Reference42 articles.

1. Review of Recent Research on Data-Based Process Monitoring

2. Fault detection of large-scale process control system with higher-order statistical and interpretative structural model

3. Statistical process monitoring with integration of data projection and one-class classification

4. Fault diagnosis using kNN reconstruction on MRI variables

5. A Review on Basic Data-Driven Approaches for Industrial Process Monitoring

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1. Output related fault detection and diagnosis based on multi block modified orthogonal Broyden-Fletcher-Goldfarb-Shanno algorithm;Neurocomputing;2024-11

2. Canonical variate residual analysis for industrial processes fault detection;The Canadian Journal of Chemical Engineering;2024-07-09

3. Nonlinear predictable feature learning with explanatory reasoning for complicated industrial system fault diagnosis;Knowledge-Based Systems;2024-02

4. Development of a Multi-block Modified Independent Component Analysis based Process Monitoring Strategy;Arabian Journal for Science and Engineering;2023-07-05

5. Nonparametric manifold learning approach for improved process monitoring;The Canadian Journal of Chemical Engineering;2021-03-25

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