Non-Gaussian chemical process monitoring with adaptively weighted independent component analysis and its applications

Journal of Process Control ◽

10.1016/j.jprocont.2013.09.008 ◽

2013 ◽

Vol 23 (9) ◽

pp. 1320-1331 ◽

Author(s):

Qingchao Jiang ◽

Xuefeng Yan

Keyword(s):

Independent Component Analysis ◽

Process Monitoring ◽

Chemical Process ◽

Component Analysis ◽

Independent Component ◽

Non Gaussian ◽

Chemical Process Monitoring

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Double-Weighted Independent Component Analysis for Non-Gaussian Chemical Process Monitoring

Industrial & Engineering Chemistry Research ◽

10.1021/ie4009666 ◽

2013 ◽

Vol 52 (40) ◽

pp. 14396-14405 ◽

Author(s):

Qingchao Jiang ◽

Xuefeng Yan ◽

Chudong Tong

Keyword(s):

Independent Component Analysis ◽

Process Monitoring ◽

Chemical Process ◽

Component Analysis ◽

Independent Component ◽

Non Gaussian ◽

Chemical Process Monitoring

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Chemical process monitoring and fault diagnosis based on independent component analysis

Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788) ◽

10.1109/wcica.2004.1340933 ◽

2004 ◽

Author(s):

Guo-jin Chen ◽

Jun Liang ◽

Ji-xin Qian

Keyword(s):

Fault Diagnosis ◽

Independent Component Analysis ◽

Process Monitoring ◽

Chemical Process ◽

Component Analysis ◽

Independent Component ◽

Chemical Process Monitoring

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Multimode non-Gaussian process monitoring based on local entropy independent component analysis

The Canadian Journal of Chemical Engineering ◽

10.1002/cjce.22651 ◽

2016 ◽

Vol 95 (2) ◽

pp. 319-330 ◽

Author(s):

Na Zhong ◽

Xiaogang Deng

Keyword(s):

Independent Component Analysis ◽

Gaussian Process ◽

Process Monitoring ◽

Component Analysis ◽

Independent Component ◽

Local Entropy ◽

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Hidden Markov Model Based Adaptive Independent Component Analysis Approach for Complex Chemical Process Monitoring and Fault Detection

Industrial & Engineering Chemistry Research ◽

10.1021/ie300203u ◽

2012 ◽

Vol 51 (15) ◽

pp. 5506-5514 ◽

Author(s):

Mudassir M. Rashid ◽

Jie Yu

Keyword(s):

Fault Detection ◽

Independent Component Analysis ◽

Markov Model ◽

Hidden Markov Model ◽

Process Monitoring ◽

Chemical Process ◽

Hidden Markov ◽

Independent Component ◽

Complex Chemical ◽

Chemical Process Monitoring

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Gaussian and non-Gaussian Double Subspace Statistical Process Monitoring Based on Principal Component Analysis and Independent Component Analysis

Industrial & Engineering Chemistry Research ◽

10.1021/ie5025358 ◽

2015 ◽

Vol 54 (3) ◽

pp. 1015-1027 ◽

Author(s):

Jian Huang ◽

Xuefeng Yan

Keyword(s):

Principal Component Analysis ◽

Independent Component Analysis ◽

Process Monitoring ◽

Principal Component ◽

Component Analysis ◽

Independent Component ◽

Statistical Process ◽

Non Gaussian ◽

Statistical Process Monitoring

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Independent component analysis model utilizing de-mixing information for improved non-Gaussian process monitoring

Computers & Industrial Engineering ◽

10.1016/j.cie.2016.01.021 ◽

2016 ◽

Vol 94 ◽

pp. 188-200 ◽

Author(s):

Bei Wang ◽

Xuefeng Yan ◽

Qingchao Jiang

Keyword(s):

Independent Component Analysis ◽

Gaussian Process ◽

Process Monitoring ◽

Component Analysis ◽

Independent Component ◽

Analysis Model ◽

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Non-Gaussian Industrial Process Monitoring With Probabilistic Independent Component Analysis

IEEE Transactions on Automation Science and Engineering ◽

10.1109/tase.2016.2537373 ◽

2017 ◽

Vol 14 (2) ◽

pp. 1309-1319 ◽

Author(s):

Jinlin Zhu ◽

Zhiqiang Ge ◽

Zhihuan Song

Keyword(s):

Independent Component Analysis ◽

Process Monitoring ◽

Industrial Process ◽

Component Analysis ◽

Independent Component ◽

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Joint Probability Density and Double-Weighted Independent Component Analysis for Multimode Non-Gaussian Process Monitoring

Industrial & Engineering Chemistry Research ◽

10.1021/ie504369x ◽

2014 ◽

Vol 53 (52) ◽

pp. 20168-20176 ◽

Author(s):

Qingchao Jiang ◽

Xuefeng Yan

Keyword(s):

Independent Component Analysis ◽

Gaussian Process ◽

Probability Density ◽

Process Monitoring ◽

Joint Probability ◽

Component Analysis ◽

Independent Component ◽

Non Gaussian ◽

Joint Probability Density

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Ensemble modified independent component analysis for enhanced non-Gaussian process monitoring

Control Engineering Practice ◽

10.1016/j.conengprac.2016.09.014 ◽

2017 ◽

Vol 58 ◽

pp. 34-41 ◽

Author(s):

Chudong Tong ◽

Ting Lan ◽

Xuhua Shi

Keyword(s):

Independent Component Analysis ◽

Gaussian Process ◽

Process Monitoring ◽

Component Analysis ◽

Independent Component ◽

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Independent component analysis-based non-Gaussian process monitoring with preselecting optimal components and support vector data description

International Journal of Production Research ◽

10.1080/00207543.2013.870362 ◽

2013 ◽

Vol 52 (11) ◽

pp. 3273-3286 ◽

Author(s):

Qingchao Jiang ◽

Xuefeng Yan ◽

Zhaomin Lv ◽

Meijin Guo

Keyword(s):

Independent Component Analysis ◽

Gaussian Process ◽

Process Monitoring ◽

Component Analysis ◽

Independent Component ◽

Support Vector ◽

Support Vector Data Description ◽

Vector Data ◽

Data Description ◽

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