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A Model-Based Approach for Monitoring and Diagnosing Digital Twin Discrepancies

Authors Elaheh Hosseinkhani , Martin Leucker , Martin Sachenbacher , Hendrik Streichhahn, Lars B. Vosteen

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Author Details

Elaheh Hosseinkhani
  • Institute for Software Engineering and Programming Languages, Universität zu Lübeck, Germany
Martin Leucker
  • Institute for Software Engineering and Programming Languages, Universität zu Lübeck, Germany
Martin Sachenbacher
  • Institute for Software Engineering and Programming Languages, Universität zu Lübeck, Germany
Hendrik Streichhahn
  • Dräger Safety AG & Co. KGaA., Lübeck, Germany
Lars B. Vosteen
  • Institute for Software Engineering and Programming Languages, Universität zu Lübeck, Germany

Funding

This paper is partially funded by the German Federal Ministry for Economic Affairs and Climate Action, due to a resolution of the German Bundestag, under grant number 01MC22005C.

Acknowledgements

We want to thank Jan-Henrik Metsch for insightful discussions and valuable feedback.

Cite As Get BibTex

Elaheh Hosseinkhani, Martin Leucker, Martin Sachenbacher, Hendrik Streichhahn, and Lars B. Vosteen. A Model-Based Approach for Monitoring and Diagnosing Digital Twin Discrepancies. In 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024). Open Access Series in Informatics (OASIcs), Volume 125, pp. 2:1-2:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/OASIcs.DX.2024.2

Abstract

Recent decades have seen the increasing use of Digital Twins (DTs) - that is, digital models used over the lifetime of a physical product or system for tasks such as predictive maintenance or optimization - in a number of domains such as buildings, manufacturing, or design. DTs face a challenge known as the DT synchronization problem; a DT, often based on machine-learned, or complex simulation models, needs to adequately mirror the physical product or system at all times, as any deviations might affect the quality of predictions or control actions. In this paper, we present a model-based approach that aims to add a level of awareness to DT models by supervising if they are in sync with the physical counterpart. The approach is agnostic to the type of models used in the DT, as long as they are compositional, and based on monitoring critical properties (behavioral or functional aspects) of the system at run-time. In the case violations are detected, it reasons on the DT’s structure to localize and identify parts of the model that cause deviations and need to be adapted. We give a formal description and an implementation of this approach, and illustrate it with an example from building climatisation.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Reliability
Keywords
  • Digital Twins
  • Runtime Verification
  • Diagnosis
  • FDIR
  • TeSSLa

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