Inferring sensor placement using critical pairs and satisfiability modulo theory
Publication date
2024-11-26
Document type
Konferenzbeitrag
Author
Organisational unit
Conference
35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024) ; Vienna, Austria ; November 4–7, 2024
Publisher
Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH
Series or journal
Open Access Series in Informatics (OASIcs)
ISSN
Periodical volume
125
Volume (part of multivolume book)
35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)
First page
9:1
Last page
9:19
Peer-reviewed
✅
Part of the university bibliography
✅
Language
English
Keyword
dtec.bw
Abstract
Industrial fault diagnosis exhibits the perennial problem of reasoning with partial and real-valued information. This is mainly due to the fact that in real-world applications, industrial systems are only instrumented insofar, as sensor information is required for their functioning. However, such instrumentation leaves out much information that would be useful for fault diagnosis. This is problematic since consistency-based fault diagnosis uses available information and computes intermediate values within a system description. These values are then used to compare expected normal behaviour to actual observed values. In the past, this was done only for Boolean circuits. Recently, satisfiability modulo non-linear arithmetic (SMT) formulations have been developed that allow the calculation of real values, instead of only Boolean ones. Leveraging those formulations, we in this article present a novel method to infer missing sensor values using an SMT system description and the notion of critical pairs. We show on a running example and also empirically that we can infer novel measurements for five process industrial systems. We conclude that, although SMT calculations accumulate some error, we can infer novel optimal measurements for all systems.
Description
This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
Cite as
Alexander Diedrich, René Heesch, Marco Bozzano, Björn Ludwig, Alessandro Cimatti, and Oliver Niggemann. Inferring Sensor Placement Using Critical Pairs and Satisfiability Modulo Theory. In 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024). Open Access Series in Informatics (OASIcs), Volume 125, pp. 9:1-9:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/OASIcs.DX.2024.9
Version
Published version
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