Batch Process Monitoring Based on Multiway Global Preserving Kernel Slow Feature Analysis

IEEE Access ◽

10.1109/access.2017.2672780 ◽

2017 ◽

Vol 5 ◽

pp. 2696-2710 ◽

Author(s):

Hanyuan Zhang ◽

Xuemin Tian ◽

Xiaogang Deng

Keyword(s):

Process Monitoring ◽

Batch Process ◽

Feature Analysis ◽

Slow Feature Analysis ◽

Batch Process Monitoring

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Batch process monitoring based on batch dynamic Kernel slow feature analysis

2017 29th Chinese Control And Decision Conference (CCDC) ◽

10.1109/ccdc.2017.7979339 ◽

2017 ◽

Author(s):

Zhang Hanyuan ◽

Tian Xuemin

Keyword(s):

Process Monitoring ◽

Batch Process ◽

Feature Analysis ◽

Slow Feature Analysis ◽

Batch Process Monitoring

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Slow-Feature-Analysis-Based Batch Process Monitoring With Comprehensive Interpretation of Operation Condition Deviation and Dynamic Anomaly

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2018.2853603 ◽

2019 ◽

Vol 66 (5) ◽

pp. 3773-3783 ◽

Author(s):

Shumei Zhang ◽

Chunhui Zhao

Keyword(s):

Process Monitoring ◽

Batch Process ◽

Feature Analysis ◽

Operation Condition ◽

Slow Feature Analysis ◽

Batch Process Monitoring

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Efficient batch process monitoring based on random nonlinear feature analysis

The Canadian Journal of Chemical Engineering ◽

10.1002/cjce.24260 ◽

2021 ◽

Author(s):

Xiaogang Deng ◽

Kunyu Du

Keyword(s):

Process Monitoring ◽

Batch Process ◽

Feature Analysis ◽

Batch Process Monitoring ◽

Nonlinear Feature

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Decentralized dynamic process monitoring based on manifold regularized slow feature analysis

Journal of Process Control ◽

10.1016/j.jprocont.2020.12.006 ◽

2021 ◽

Vol 98 ◽

pp. 79-91

Author(s):

Xue Xu ◽

Jinliang Ding

Keyword(s):

Process Monitoring ◽

Dynamic Process ◽

Feature Analysis ◽

Slow Feature Analysis

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Quality‐relevant dynamic process monitoring based on mutual information multiblock slow feature analysis

Journal of Chemometrics ◽

10.1002/cem.3110 ◽

2019 ◽

Vol 33 (4) ◽

pp. e3110 ◽

Author(s):

Haiyong Zheng ◽

Qingchao Jiang ◽

Xuefeng Yan

Keyword(s):

Mutual Information ◽

Process Monitoring ◽

Dynamic Process ◽

Feature Analysis ◽

Slow Feature Analysis

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Batch process monitoring in the original measurement's space

Journal of Process Control ◽

10.1016/j.jprocont.2010.03.006 ◽

2010 ◽

Vol 20 (6) ◽

pp. 716-725 ◽

Author(s):

Carlos R. Alvarez ◽

Adriana Brandolin ◽

Mabel C. Sánchez

Keyword(s):

Process Monitoring ◽

Batch Process ◽

Batch Process Monitoring

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Feature extraction for batch process monitoring and fault detection via simultaneous data scaling and training of tensor based models

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2018.09.613 ◽

2018 ◽

Vol 51 (24) ◽

pp. 433-440 ◽

Author(s):

Carlos A. Muñoz ◽

Dries Telen ◽

Philippe Nimmegeers ◽

Jan Van Impe

Keyword(s):

Feature Extraction ◽

Fault Detection ◽

Process Monitoring ◽

Batch Process ◽

Batch Process Monitoring ◽

Data Scaling ◽

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Wavelet functional principal component analysis for batch process monitoring

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2019.103897 ◽

2020 ◽

Vol 196 ◽

pp. 103897 ◽

Author(s):

Jingxiang Liu ◽

Junghui Chen ◽

Dan Wang

Keyword(s):

Principal Component Analysis ◽

Process Monitoring ◽

Principal Component ◽

Batch Process ◽

Component Analysis ◽

Functional Principal Component Analysis ◽

Batch Process Monitoring ◽

Functional Principal Component

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Tensor Global-Local Preserving Projections for Batch Process Monitoring

Industrial & Engineering Chemistry Research ◽

10.1021/ie403973w ◽

2014 ◽

Vol 53 (24) ◽

pp. 10166-10176 ◽

Author(s):

Lijia Luo ◽

Shiyi Bao ◽

Zengliang Gao ◽

Jingqi Yuan

Keyword(s):

Process Monitoring ◽

Batch Process ◽

Batch Process Monitoring

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Distributed dynamic process monitoring based on dynamic slow feature analysis with minimal redundancy maximal relevance

Control Engineering Practice ◽

10.1016/j.conengprac.2020.104627 ◽

2020 ◽

Vol 104 ◽

pp. 104627

Author(s):

Kai Zhong ◽

Dewei Ma ◽

Min Han

Keyword(s):

Process Monitoring ◽

Dynamic Process ◽

Feature Analysis ◽

Slow Feature Analysis ◽

Minimal Redundancy ◽

Maximal Relevance

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