Multiway independent component analysis mixture model and mutual information based fault detection and diagnosis approach of multiphase batch processes

Jie Yu; Jingyan Chen; Mudassir M. Rashid

doi:10.1002/aic.14051

Multiway independent component analysis mixture model and mutual information based fault detection and diagnosis approach of multiphase batch processes

AIChE Journal ◽

10.1002/aic.14051 ◽

2013 ◽

Vol 59 (8) ◽

pp. 2761-2779 ◽

Cited By ~ 18

Author(s):

Jie Yu ◽

Jingyan Chen ◽

Mudassir M. Rashid

Keyword(s):

Fault Detection ◽

Mutual Information ◽

Independent Component Analysis ◽

Mixture Model ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Batch Processes ◽

Detection And Diagnosis ◽

Diagnosis Approach

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A Novel Fault Detection and Diagnosis Scheme Based on Independent Component Analysis-Statistical Characteristics: Application on the Tennessee Eastman Benchmark Process

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN ◽

10.1252/jcej.20we045 ◽

2021 ◽

Vol 54 (6) ◽

pp. 304-312

Author(s):

Cheng Zhang ◽

Xiaofang Zheng ◽

Yuan Li

Keyword(s):

Fault Detection ◽

Independent Component Analysis ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Statistical Characteristics ◽

Detection And Diagnosis

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Fault detection and diagnosis based on modified independent component analysis

AIChE Journal ◽

10.1002/aic.10978 ◽

2006 ◽

Vol 52 (10) ◽

pp. 3501-3514 ◽

Cited By ~ 278

Author(s):

Jong-Min Lee ◽

S. Joe Qin ◽

In-Beum Lee

Keyword(s):

Fault Detection ◽

Independent Component Analysis ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Detection And Diagnosis

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The Method of Fault Detection and Diagnosis for Induction Motors Based on Wavelets and Independent Component Analysis

International Journal of Digital Content Technology and its Applications ◽

10.4156/jdcta.vol5.issue9.45 ◽

2011 ◽

Vol 5 (9) ◽

pp. 405-410

Author(s):

Wang Kai ◽

Bai Ming ◽

Cong Lin ◽

Yang Ting ◽

Sun huayu

Keyword(s):

Fault Detection ◽

Independent Component Analysis ◽

Induction Motors ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Detection And Diagnosis

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Fault Detection and Diagnosis of Nonlinear Processes Using Improved Kernel Independent Component Analysis (KICA) and Support Vector Machine (SVM)

Industrial & Engineering Chemistry Research ◽

10.1021/ie071496x ◽

2008 ◽

Vol 47 (18) ◽

pp. 6961-6971 ◽

Cited By ~ 68

Author(s):

Yingwei Zhang

Keyword(s):

Support Vector Machine ◽

Fault Detection ◽

Independent Component Analysis ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Support Vector ◽

Nonlinear Processes ◽

Kernel Independent Component Analysis ◽

Detection And Diagnosis

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Dynamic kernel independent component analysis approach for fault detection and diagnosis

2017 Chinese Automation Congress (CAC) ◽

10.1109/cac.2017.8243137 ◽

2017 ◽

Author(s):

Lin Feng ◽

Rongrong Sun

Keyword(s):

Fault Detection ◽

Independent Component Analysis ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Analysis Approach ◽

Kernel Independent Component Analysis ◽

Detection And Diagnosis

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Retraction of “Fault Detection and Diagnosis of Nonlinear Processes Using Improved Kernel Independent Component Analysis (KICA) and Support Vector Machine (SVM)”

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.9b05805 ◽

2019 ◽

Vol 58 (45) ◽

pp. 20858-20858 ◽

Cited By ~ 1

Author(s):

Yingwei Zhang

Keyword(s):

Support Vector Machine ◽

Fault Detection ◽

Independent Component Analysis ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Support Vector ◽

Nonlinear Processes ◽

Kernel Independent Component Analysis ◽

Detection And Diagnosis

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Dynamic independent component analysis approach for fault detection and diagnosis

Expert Systems with Applications ◽

10.1016/j.eswa.2010.06.101 ◽

2010 ◽

Vol 37 (12) ◽

pp. 8606-8617 ◽

Cited By ~ 49

Author(s):

George Stefatos ◽

A. Ben Hamza

Keyword(s):

Fault Detection ◽

Independent Component Analysis ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Analysis Approach ◽

Detection And Diagnosis

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Fault detection and diagnosis of non-linear non-Gaussian dynamic processes using kernel dynamic independent component analysis

Information Sciences ◽

10.1016/j.ins.2013.06.021 ◽

2014 ◽

Vol 259 ◽

pp. 369-379 ◽

Cited By ~ 86

Author(s):

Jicong Fan ◽

Youqing Wang

Keyword(s):

Fault Detection ◽

Independent Component Analysis ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Independent Component ◽

Dynamic Processes ◽

Non Linear ◽

Detection And Diagnosis ◽

Non Gaussian

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Dynamic process fault detection and diagnosis based on dynamic principal component analysis, dynamic independent component analysis and Bayesian inference

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2015.09.010 ◽

2015 ◽

Vol 148 ◽

pp. 115-127 ◽

Cited By ~ 45

Author(s):

Jian Huang ◽

Xuefeng Yan

Keyword(s):

Principal Component Analysis ◽

Bayesian Inference ◽

Fault Detection ◽

Independent Component Analysis ◽

Dynamic Process ◽

Principal Component ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Dynamic Principal Component Analysis ◽

Detection And Diagnosis

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Global-local based wavelet functional principal component analysis for fault detection and diagnosis in batch processes

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2021.104279 ◽

2021 ◽

Vol 212 ◽

pp. 104279

Author(s):

Jingxiang Liu ◽

Dan Wang ◽

Junghui Chen

Keyword(s):

Principal Component Analysis ◽

Fault Detection ◽

Principal Component ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Functional Principal Component Analysis ◽

Batch Processes ◽

Functional Principal Component ◽

Detection And Diagnosis

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