An industrial process monitoring scheme with moving window slow feature analysis

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.728 ◽

2020 ◽

Vol 53 (2) ◽

pp. 11996-12001

Author(s):

Li Zhu ◽

Zhe Li ◽

Junghui Chen

Keyword(s):

Process Monitoring ◽

Industrial Process ◽

Feature Analysis ◽

Moving Window ◽

Monitoring Scheme ◽

Slow Feature Analysis

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Multistep Dynamic Slow Feature Analysis for Industrial Process Monitoring

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2020.3004681 ◽

2020 ◽

Vol 69 (12) ◽

pp. 9535-9548 ◽

Author(s):

Xin Ma ◽

Yabin Si ◽

Zeyi Yuan ◽

Yihao Qin ◽

Youqing Wang

Keyword(s):

Process Monitoring ◽

Industrial Process ◽

Feature Analysis ◽

Slow Feature Analysis

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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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Multivariate statistical modelling and monitoring for nonstationary industrial process with slow feature analysis and temporal working pattern partition

10.1109/ccdc52312.2021.9601744 ◽

2021 ◽

Author(s):

Xiaoyu Zou ◽

Jie Pan

Keyword(s):

Industrial Process ◽

Statistical Modelling ◽

Feature Analysis ◽

Multivariate Statistical ◽

Slow Feature Analysis

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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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A Novel Auto-regressive Dynamic Slow Feature Analysis Method for Dynamic chemical Process Monitoring

Chemical Engineering Science ◽

10.1016/j.ces.2021.117236 ◽

2021 ◽

pp. 117236

Author(s):

Yuemei Xu ◽

Mingxing Jia ◽

Zhizhong Mao

Keyword(s):

Process Monitoring ◽

Chemical Process ◽

Feature Analysis ◽

Analysis Method ◽

Slow Feature Analysis ◽

Auto Regressive ◽

Chemical Process Monitoring

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Towards Interpretable Process Monitoring: Slow Feature Analysis Aided Autoencoder for Spatiotemporal Process Feature Learning

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2021.3127284 ◽

2021 ◽

pp. 1-1

Author(s):

Shipeng Li ◽

Jiaxiang Luo ◽

Yueming Hu

Keyword(s):

Process Monitoring ◽

Feature Learning ◽

Feature Analysis ◽

Slow Feature Analysis ◽

Spatiotemporal Process

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A novel quality-related process monitoring based on multi-block slow feature analysis of mutual information-index

10.1109/ccdc52312.2021.9601843 ◽

2021 ◽

Author(s):

Yang Yinghua ◽

Kang Weiqi ◽

Liu Xiaozhi

Keyword(s):

Mutual Information ◽

Process Monitoring ◽

Feature Analysis ◽

Information Index ◽

Slow Feature Analysis ◽

Related Process

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Comprehensive process decomposition for closed-loop process monitoring with quality-relevant slow feature analysis

Journal of Process Control ◽

10.1016/j.jprocont.2019.04.001 ◽

2019 ◽

Vol 77 ◽

pp. 141-154 ◽

Author(s):

Yan Qin ◽

Chunhui Zhao

Keyword(s):

Process Monitoring ◽

Closed Loop ◽

Feature Analysis ◽

Slow Feature Analysis ◽

Process Decomposition

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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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