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Resilient Fault Diagnosis Under imperfect observations–A Need for Industry 4.0 Era

IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1279-1288页

作者： Alejandro White Ali Karimoddini Mohammad Karimadini IEEE Vehicle Technology Directorate CCDC Army Research LaboratoryAberdeen Proving GroundMD 21005 USA Department of Electrical and Computer Engineering North Carolina Agricultural and Technical State UniversityGreensboroNC 27411 USA Department of Electrical Engineering Arak University of TechnologyArak ***Iran

In smart industrial systems,in many cases,a fault can be captured as an event to represent the distinct nature of subsequent ***-based fault diagnosis techniques are capable model-based methods for diagnosing faults from a sequence of observable events executed by the system under *** event-based diagnosis techniques rely on perfect observations of observable ***,in practice,it is common to miss an observable event due to a problem in sensorreadings or communication/transmission *** paper develops a fault diagnosis tool,referred to as diagnoser,which can robustly detect,locate,and isolate occurred *** developed diagnoser is resilient against missed observations.A missed observation is detected from its successive sequence of *** detecting a missed observation,the developed diagnoser automatically resets and then,asynchronously resumes the diagnosis *** is achieved solely based on postreset/activation observations and without interrupting the performance of the system under *** concepts of asynchronous detectability and asynchronous diagnosability are *** is shown that if asynchronous detectability and asynchronous diagnosability hold,the proposed diagnoser is capable of diagnosing occurred faults under imperfect *** proposed technique is applied to diagnose faults in a manufacturing *** examples are provided to explain the details of the proposed *** result paves the way towards fostering resilient cyber-physical systems in Industry4.0 context.

关键词： Cyber-physical systems discrete event systems fault diagnosis imperfect communication imperfect observation Industry 4.0 resilience

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