Model Transformation from CBM to EPL Rules to Detect Failure Symptoms
| Autor: | Jérémy Bascans, Xavier Lorca, Aurélie Montarnal, Alexandre Sarazin, Sébastien Truptil |
|---|---|
| Přispěvatelé: | APSYS (Blagnac), Centre Génie Industriel (CGI), IMT École nationale supérieure des Mines d'Albi-Carmaux (IMT Mines Albi), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), CEA Tech Languedoc-Roussillon Midi-Pyrénées, CEA Tech en régions (CEA-TECH-Reg), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), CEA Tech Occitanie (DOCC) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Information management
Safety engineering Computer science Maintenance Context (language use) 02 engineering and technology computer.software_genre Model transformation Knowledge base Cost reduction [SPI]Engineering Sciences [physics] Expert systems Model driven architectures 020204 information systems 0202 electrical engineering electronic engineering information engineering Software design business.industry Prognostics and health managements Condition-based maintenance Software architecture Complex event processing (CEP) Monitoring and analysis 020207 software engineering Expert system Periodic maintenance Risk analysis (engineering) Prognostics Intermediate results business computer |
| Zdroj: | MODELSWARD 2020-8th International Conference on Model-Driven Engineering and Software Development MODELSWARD 2020-8th International Conference on Model-Driven Engineering and Software Development, Feb 2020, La Valette, Malta. pp.200-224, ⟨10.1007/978-3-030-67445-8_9⟩ Communications in Computer and Information Science ISBN: 9783030674441 MODELSWARD (Revised Selected Papers) |
| DOI: | 10.1007/978-3-030-67445-8_9⟩ |
| Popis: | International audience; The increasing complexity of modern systems, cost reduction policies and ever increasing safety requirements are bringing new challenges to the maintenance domain. In many fields, periodic maintenance actions become either insufficient or too expensive. In this context, Condition-Based Maintenance (CBM) strategies, and Prognostics and Health Management (PHM) in particular, are offering an interesting alternative by allowing systems to be maintained only when needed. These strategies rely on a constant monitoring and analysis of the systems operating conditions in order to detect and identify a failure when it occurs and even sometimes beforehand.Nowadays, two main approaches are explored to detect failures in PHM solutions: one based on machine learning, the other based on expertise and capitalised system knowledge. This work proposes to combine a Complex Event Processing (CEP), to manage incoming data’s volumetry and velocity, with an Expert System (ES) in charge of exploiting the capitalized knowledge. This paper focuses on the configuration of a CEP from rules contained in a CBM ES using a Model Driven Architecture (MDA). This configuration is a challenge, especially regarding the management of rules with temporal parameters and the need for intermediate results to deal with the rule’s complexity. |
| Databáze: | OpenAIRE |
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