2026-08-10T23:06:19Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:24793 2026-02-09T07:47:23Z ddc:004 open_access

Using Qualitative Simulation Models for Monitoring and Diagnosis Das, Ankita Koitz-Hristov, Roxane Wotawa, Franz Qualitative Simulation Fault Detection Model-based Diagnosis Monitoring Application Many systems in our daily lives control physical processes, which are parametrized and adapted, such as heating systems in buildings. Faults and non-optimized settings lead to a high energy demand and, therefore, need to be detected as early as possible. Unfortunately, due to specific adaptations, only the basic principles remain the same, but not the concrete implementations, making the use of techniques like machine learning difficult. Therefore, we suggest using abstract models that cover the basic behavior in a way that allows us to reuse the models in different installations. In particular, we discuss the application of qualitative simulation for fault detection and introduce a formal definition of conformance between the results of qualitative simulation and the monitored behavior. We discuss arising difficulties and provide a basis for further research and applications. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ankita Das and Roxane Koitz-Hristov and Franz Wotawa 2025 Is Part Of OASIcs, Volume 136, 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.DX.2025.4 urn:nbn:de:0030-drops-247934 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2025.4 eng https://creativecommons.org/licenses/by/4.0/legalcode