Variable time delay based Granger causality approach integrated with dynamic coupling analysis for root cause diagnosis in chemical processes

Variable time delay based Granger causality approach integrated with dynamic coupling analysis for root cause diagnosis in chemical processes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Variable time delay based Granger causality approach integrated with dynamic coupling analysis for root cause diagnosis in chemical processes Yuting Li, Xu Yang, Jian Huang, Jingjing Gao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3716643/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 May, 2024 Read the published version in Korean Journal of Chemical Engineering → Version 1 posted 4 You are reading this latest preprint version Abstract Due to the dynamic characteristics of chemical industry systems, the time delay tends to be variable, which leads to changes in coupling intensity. This is contrary to the assumptions in causal analysis, where the time delay and coupling are typically assumed to be fixed. In this article, a new causal analysis framework that integrates Granger causality with dynamic coupling analysis based on variable time delay is proposed, which not only fully considers the variable time delay in dynamic processes, but also studies the dynamic change of coupling intensity. Firstly, the moving window is used to explore real-time variations in average mutual information to obtain the variable time delay. Then by further analyzing the normal data, the dynamic coupling relationship caused by continuous changes in time delay is distinguished. On this basis, the extended Granger causality and convergent cross mapping are integrated to relax their assumptions of fixed time delay and coupling. Finally, the direction of fault propagation is guided by the results of causal analysis. The effectiveness of proposed mothed is demonstrated by chemical industry case studies. Variable time delay Dynamics coupling analysis Root cause diagnosis Fault propagation path identification Dynamics chemical industry processes Full Text Cite Share Download PDF Status: Published Journal Publication published 16 May, 2024 Read the published version in Korean Journal of Chemical Engineering → Version 1 posted Reviewers agreed at journal 08 Jan, 2024 Reviewers invited by journal 08 Jan, 2024 Editor assigned by journal 07 Dec, 2023 First submitted to journal 05 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3716643","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265997899,"identity":"f13ab407-0416-49d4-b610-b5622f311b60","order_by":0,"name":"Yuting Li","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0000-7063-4576","institution":"University of Science and Technology Beijing","correspondingAuthor":true,"prefix":"","firstName":"Yuting","middleName":"","lastName":"Li","suffix":""},{"id":265997900,"identity":"4130721f-7c19-47a6-ac71-fddbd9ebf6a7","order_by":1,"name":"Xu Yang","email":"","orcid":"","institution":"University of Science and Technology Beijing","correspondingAuthor":false,"prefix":"","firstName":"Xu","middleName":"","lastName":"Yang","suffix":""},{"id":265997901,"identity":"6d2d3d88-c927-4afb-b059-341f12282e95","order_by":2,"name":"Jian Huang","email":"","orcid":"","institution":"University of Science and Technology Beijing","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Huang","suffix":""},{"id":265997902,"identity":"777a5f7b-3121-4d15-b38c-e7fa6eafb6de","order_by":3,"name":"Jingjing Gao","email":"","orcid":"","institution":"University of Science and Technology Beijing","correspondingAuthor":false,"prefix":"","firstName":"Jingjing","middleName":"","lastName":"Gao","suffix":""}],"badges":[],"createdAt":"2023-12-06 19:26:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3716643/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3716643/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11814-024-00180-8","type":"published","date":"2024-05-17T01:04:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59060829,"identity":"7895b473-22f7-4c0e-9088-e96c074fd068","added_by":"auto","created_at":"2024-06-26 01:04:59","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1991932,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3716643/v1_covered_609cf4d4-f0c7-4437-ba06-297db3e02532.pdf"}],"financialInterests":"","formattedTitle":"Variable time delay based Granger causality approach integrated with dynamic coupling analysis for root cause diagnosis in chemical processes","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"korean-journal-of-chemical-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"kjce","sideBox":"Learn more about [Korean Journal of Chemical Engineering](http://link.springer.com/journal/11814)","snPcode":"11814","submissionUrl":"https://www.editorialmanager.com/kjce/default2.aspx","title":"Korean Journal of Chemical Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Subscription","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Variable time delay, Dynamics coupling analysis, Root cause diagnosis, Fault propagation path identification, Dynamics chemical industry processes","lastPublishedDoi":"10.21203/rs.3.rs-3716643/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3716643/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Due to the dynamic characteristics of chemical industry systems, the time delay tends to be variable, which leads to changes in coupling intensity. 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