Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph

There are many unknown abnormal working conditions in industrial production. It is difficult to identify unknown abnormal working conditions because there are few relative sample and experience in this field. To solve this problem, a new identification method combining two-step clustering analysis a...

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Autores principales:	Juan Hong, Jian Qu, Wende Tian, Zhe Cui, Zijian Liu, Yang Lin, Chuankun Li
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	two-step clustering analysis signed directed graph catalytic cracking process abnormal identification Chemical technology TP1-1185 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/374429f5440c4751b5fc8e2d50da4eca
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spelling	oai:doaj.org-article:374429f5440c4751b5fc8e2d50da4eca2021-11-25T18:51:50ZIdentification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph10.3390/pr91120552227-9717https://doaj.org/article/374429f5440c4751b5fc8e2d50da4eca2021-11-01T00:00:00Zhttps://www.mdpi.com/2227-9717/9/11/2055https://doaj.org/toc/2227-9717There are many unknown abnormal working conditions in industrial production. It is difficult to identify unknown abnormal working conditions because there are few relative sample and experience in this field. To solve this problem, a new identification method combining two-step clustering analysis and signed directed graph (TSCA-SDG) is proposed. Firstly, through correlation analysis and R-type clustering analysis, the variables are effectively selected and extracted. Then, a two-step clustering analysis was carried out on the selected variables to obtain the cluster results. Through the establishment of the signed directed graph (SDG) model, the causes of abnormal working conditions and their mutual influence are deduced from the mechanism. The application of the TSCA-SDG method in the catalytic cracking process shows that this method has good performance for abnormal condition identification.Juan HongJian QuWende TianZhe CuiZijian LiuYang LinChuankun LiMDPI AGarticletwo-step clustering analysissigned directed graphcatalytic cracking processabnormal identificationChemical technologyTP1-1185ChemistryQD1-999ENProcesses, Vol 9, Iss 2055, p 2055 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	two-step clustering analysis signed directed graph catalytic cracking process abnormal identification Chemical technology TP1-1185 Chemistry QD1-999
spellingShingle	two-step clustering analysis signed directed graph catalytic cracking process abnormal identification Chemical technology TP1-1185 Chemistry QD1-999 Juan Hong Jian Qu Wende Tian Zhe Cui Zijian Liu Yang Lin Chuankun Li Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph
description	There are many unknown abnormal working conditions in industrial production. It is difficult to identify unknown abnormal working conditions because there are few relative sample and experience in this field. To solve this problem, a new identification method combining two-step clustering analysis and signed directed graph (TSCA-SDG) is proposed. Firstly, through correlation analysis and R-type clustering analysis, the variables are effectively selected and extracted. Then, a two-step clustering analysis was carried out on the selected variables to obtain the cluster results. Through the establishment of the signed directed graph (SDG) model, the causes of abnormal working conditions and their mutual influence are deduced from the mechanism. The application of the TSCA-SDG method in the catalytic cracking process shows that this method has good performance for abnormal condition identification.
format	article
author	Juan Hong Jian Qu Wende Tian Zhe Cui Zijian Liu Yang Lin Chuankun Li
author_facet	Juan Hong Jian Qu Wende Tian Zhe Cui Zijian Liu Yang Lin Chuankun Li
author_sort	Juan Hong
title	Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph
title_short	Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph
title_full	Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph
title_fullStr	Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph
title_full_unstemmed	Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph
title_sort	identification of unknown abnormal conditions in catalytic cracking process based on two-step clustering analysis and signed directed graph
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/374429f5440c4751b5fc8e2d50da4eca
work_keys_str_mv	AT juanhong identificationofunknownabnormalconditionsincatalyticcrackingprocessbasedontwostepclusteringanalysisandsigneddirectedgraph AT jianqu identificationofunknownabnormalconditionsincatalyticcrackingprocessbasedontwostepclusteringanalysisandsigneddirectedgraph AT wendetian identificationofunknownabnormalconditionsincatalyticcrackingprocessbasedontwostepclusteringanalysisandsigneddirectedgraph AT zhecui identificationofunknownabnormalconditionsincatalyticcrackingprocessbasedontwostepclusteringanalysisandsigneddirectedgraph AT zijianliu identificationofunknownabnormalconditionsincatalyticcrackingprocessbasedontwostepclusteringanalysisandsigneddirectedgraph AT yanglin identificationofunknownabnormalconditionsincatalyticcrackingprocessbasedontwostepclusteringanalysisandsigneddirectedgraph AT chuankunli identificationofunknownabnormalconditionsincatalyticcrackingprocessbasedontwostepclusteringanalysisandsigneddirectedgraph
_version_	1718410579084836864

Identification of Unknown Abnormal Conditions in Catalytic Cracking Process Based on Two-Step Clustering Analysis and Signed Directed Graph

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