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Weakness Monitors for Fail-Aware Systems

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Formal Modeling and Analysis of Timed Systems (FORMATS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12288))

Abstract

Fail-awareness is the ability of a system to detect an upcoming failure before it actually happens. In this paper, we propose a weakness monitoring approach for observing a complex system during its operation, identifying possible degradation of its behavior, and finally raising an alarm in case of an estimated upcoming failure before the system actually goes out of its specification. Our procedure uses online linear regression to monitor trends over time – it is used to optimize the system service. We evaluate our approach on three case studies from the automotive and avionics domains.

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Notes

  1. 1.

    Perfectly periodic sampling is not required for our approach, but we use it to simplify the presentation of the procedure.

  2. 2.

    The specification of the sensor defines the safety threshold to be equal to \(2.2^{\circ }\) or \(3^{\circ }\) depending on the model of the sensor. We set this tolerance to a much lower limit for the purpose of evaluation.

  3. 3.

    The parameters of the injected anomaly y(t) have been selected in order to fit it to the short period of time in which the data have been collected. In practice, the anomaly might evolve at a different time scale but the handling approach remains the same.

  4. 4.

    We refer to the cited papers for the definition of STL syntax and semantics.

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Acknowledgements

We would like to thank Brno University of Technology for their comments and the measured data used in the motor weakness monitoring use case. The data were measured on a testbench located in the premises of Brno University of Technology, Central European Institute of Technology, with the motor which was developed during ENIAC-JU project MotorBrain (nr. 270693).

We would like to thank also the anonymous reviewers for their comments on the earlier drafts of the paper.

We acknowledge the support of ECSEL project Autodrive (nr. 7953297) and FFG national project IoT4CPS.

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Authors and Affiliations

  1. AIT Austrian Institute of Technology, Vienna, Austria

    Stefan Jakšić, Cristinel Mateis & Dejan Ničković

  2. Infineon Technologies Austria AG, Villach, Austria

    Wolfgang Granig & Horst Lewitschnig

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  1. Wolfgang Granig
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  2. Stefan Jakšić
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  4. Cristinel Mateis
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  5. Dejan Ničković
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Correspondence to Dejan Ničković .

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Editors and Affiliations

  1. Inria, Université de Rennes, Rennes, France

    Nathalie Bertrand

  2. Radboud University, Nijmegen, The Netherlands

    Nils Jansen

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Granig, W., Jakšić, S., Lewitschnig, H., Mateis, C., Ničković, D. (2020). Weakness Monitors for Fail-Aware Systems. In: Bertrand, N., Jansen, N. (eds) Formal Modeling and Analysis of Timed Systems. FORMATS 2020. Lecture Notes in Computer Science(), vol 12288. Springer, Cham. https://doi.org/10.1007/978-3-030-57628-8_17

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  • DOI: https://doi.org/10.1007/978-3-030-57628-8_17

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