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DOI: 10.4230/OASIcs.DX.2025.13

Beyond Dynamic Bayesian Networks: Fusing Temporal Logic Monitors with Probabilistic Diagnosis (Short Paper)

Authors: Chetan Kulkarni and Johann Schumann

Published in: OASIcs, Volume 136, 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)

Abstract

Conventional diagnostic systems often fail to account for temporal dynamics - such as duration, frequency, or sequence of events - which are critical for accurate fault assessment. Existing solutions that model time, like Dynamic Bayesian Networks (DBNs), typically suffer from computational complexity and scalability issues. This paper introduces a hybrid diagnostic architecture that integrates a standard Bayesian Networks (BNs) with a powerful temporal reasoner R2U2 (Realizable Responsive Unobtrusive Unit). By decoupling temporal logic from probabilistic inference, our approach allows the specialized R2U2 engine to efficiently process complex time-dependent conditions and provide nuanced inputs to the BNs. The result is a more scalable, flexible, and robust framework for diagnosing failures in systems where temporal behavior is a key factor. The paper will detail this architecture, its generation from system models, and demonstrate its capabilities using a UAV electric powertrain example.

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Chetan Kulkarni and Johann Schumann. Beyond Dynamic Bayesian Networks: Fusing Temporal Logic Monitors with Probabilistic Diagnosis (Short Paper). In 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025). Open Access Series in Informatics (OASIcs), Volume 136, pp. 13:1-13:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kulkarni_et_al:OASIcs.DX.2025.13,
  author =	{Kulkarni, Chetan and Schumann, Johann},
  title =	{{Beyond Dynamic Bayesian Networks: Fusing Temporal Logic Monitors with Probabilistic Diagnosis}},
  booktitle =	{36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)},
  pages =	{13:1--13:17},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-394-2},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{136},
  editor =	{Quinones-Grueiro, Marcos and Biswas, Gautam and Pill, Ingo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2025.13},
  URN =		{urn:nbn:de:0030-drops-248022},
  doi =		{10.4230/OASIcs.DX.2025.13},
  annote =	{Keywords: Bayesian diagnostic network, temporal logic, fault diagnosis, temporal reasoning, probabilistic inference, scalability}
}

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Beyond Dynamic Bayesian Networks: Fusing Temporal Logic Monitors with Probabilistic Diagnosis (Short Paper)

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