Concurrent Quality-Relevant Canonical Correlation Analysis for Nonlinear Continuous Process Decomposition and Monitoring-Reference-Cited by-同舟云学术

Concurrent Quality-Relevant Canonical Correlation Analysis for Nonlinear Continuous Process Decomposition and Monitoring

Published:2020-04-14 Issue:18 Volume:59 Page:8757-8768
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Peng Xin¹^ORCID,Li Zhi¹,Zhong Weimin¹²^ORCID,Qian Feng¹^ORCID,Tian Ying³

Affiliation:

1. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, China

2. Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai, China

3. School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China

Funder

Ministry of Education of the People's Republic of China

Science and Technology Commission of Shanghai Municipality

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.0c00895

Reference41 articles.

1. A Variable-Correlation-Based Sparse Modeling Method for Industrial Process Monitoring

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

3. Concurrent Monitoring Strategy for Static and Dynamic Deviations Based on Selective Ensemble Learning Using Slow Feature Analysis

4. Distributed partial least squares based residual generation for statistical process monitoring

5. Online Performance Monitoring and Modeling Paradigm Based on Just-in-Time Learning and Extreme Learning Machine for a Non-Gaussian Chemical Process

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Novel Distributed Process Monitoring Framework of VAE-Enhanced with Deep Neural Network;Neural Processing Letters;2024-03-20

2. Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey;Processes;2024-01-24

3. Performance-Driven Fault Detection for Uncertain Takagi–Sugeno Fuzzy Feedback Control Systems;IEEE Transactions on Fuzzy Systems;2023-12

4. KPCA-CCA-Based Quality-Related Fault Detection and Diagnosis Method for Nonlinear Process Monitoring;IEEE Transactions on Industrial Informatics;2023-05

5. Performance-Based Fault Detection for Model-Free Automatic Control Systems;2022 China Automation Congress (CAC);2022-11-25