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Model Transformation from CBM to EPL Rules to Detect Failure Symptoms

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Model-Driven Engineering and Software Development (MODELSWARD 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1361))

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Abstract

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.

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Notes

  1. 1.

    http://www.espertech.com/.

  2. 2.

    https://docs.wso2.com/display/CEP300/Siddhi+Language+Specification.

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Authors and Affiliations

  1. APSYS, 36 Rue Raymond Grimaud, 31700, Blagnac, France

    Alexandre Sarazin & Jérémy Bascans

  2. IMT Mines Albi, Centre de Génie Industriel, Allée des Sciences, 81000, Albi, France

    Alexandre Sarazin, Aurélie Montarnal & Xavier Lorca

  3. CEA, CEA Tech Occitanie, 51 Rue de l’Innovation, 31670, Labège, France

    Sebastien Truptil

Authors
  1. Alexandre Sarazin
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  2. Sebastien Truptil
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  3. Aurélie Montarnal
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  4. Jérémy Bascans
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  5. Xavier Lorca
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Corresponding authors

Correspondence to Alexandre Sarazin , Sebastien Truptil , Aurélie Montarnal , Jérémy Bascans or Xavier Lorca .

Editor information

Editors and Affiliations

  1. Siège du Groupe ESEO, Angers Cedex 02, France

    Slimane Hammoudi

  2. University of Twente, Enschede, The Netherlands

    Luís Ferreira Pires

  3. Malina Software Corp., Nepean, ON, Canada

    Bran Selić

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Sarazin, A., Truptil, S., Montarnal, A., Bascans, J., Lorca, X. (2021). Model Transformation from CBM to EPL Rules to Detect Failure Symptoms. In: Hammoudi, S., Pires, L.F., Selić, B. (eds) Model-Driven Engineering and Software Development. MODELSWARD 2020. Communications in Computer and Information Science, vol 1361. Springer, Cham. https://doi.org/10.1007/978-3-030-67445-8_9

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  • DOI: https://doi.org/10.1007/978-3-030-67445-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67444-1

  • Online ISBN: 978-3-030-67445-8

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