An identification model for fault detection of reinitializable Discrete-Event Systems

An identification model for fault detection of reinitializable Discrete-Event Systems | 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 An identification model for fault detection of reinitializable Discrete-Event Systems Diego A. Libanio, Gustavo S. Viana, Marcos V. Moreira This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4797407/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 May, 2025 Read the published version in Journal of Control, Automation and Electrical Systems → Version 1 posted 9 You are reading this latest preprint version Abstract Recently, Discrete-Event System (DES) identification techniques with the aim of fault detection have been proposed in the literature. In simple words, identification of DES with the aim of fault detection consists in computing a model which is capable of simulating the observed fault-free behavior generated by the system. Then, a fault is detected when a discrepancy between the evolution of the system and the model estimate is observed. Although several identification models for DES have been proposed in the literature, from the authors’ knowledge, they are capable of correctly simulating the fault-free behavior of reinitializable systems, i.e., systems that always returns to its initial state after completing a task, only in some cases. In this paper, we propose a new identification model that simulates the fault-free behavior generated by reinitializable systems. In addition, a didactic mechatronic plant is used to illustrate the proposed method. Identification Fault detection Discrete-event systems Finite state automata Black-box identification Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 May, 2025 Read the published version in Journal of Control, Automation and Electrical Systems → Version 1 posted Editorial decision: Revision requested 20 Dec, 2024 Reviews received at journal 18 Dec, 2024 Reviewers agreed at journal 13 Nov, 2024 Reviews received at journal 08 Nov, 2024 Reviewers agreed at journal 01 Nov, 2024 Reviewers invited by journal 25 Oct, 2024 Editor assigned by journal 25 Jul, 2024 Submission checks completed at journal 25 Jul, 2024 First submitted to journal 24 Jul, 2024 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4797407","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":337980207,"identity":"c941b1a2-4193-487a-b1a4-188ea1d86a7a","order_by":0,"name":"Diego A. 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