Using ontologies to create logical system descriptions for fault diagnosis
Publication date
2024-10-16
Document type
Konferenzbeitrag
Organisational unit
Conference
29th International Conference on Emerging Technologies and Factory Automation (ETFA 2024) ; Padova, Italy ; September 10–13, 2024
Publisher
IEEE
Book title
2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)
Peer-reviewed
✅
Part of the university bibliography
✅
Language
English
Abstract
With the increasing complexity of highly automated cyber-physical systems (CPS), monitoring their behavior has become crucial. Failures in these systems can be costly, halt production, or even pose risks to human safety. Effective diagnosis depends on understanding the system's components, connections, and the influences among them, knowledge typically provided by experts. However, the shift towards self-diagnosing systems necessitates this knowledge be machine-readable and interpretable. This paper introduces a novel methodology that utilizes an ontology to encode knowledge about cyber-physical systems and systematically generate propositional logical expressions. These expressions can then be evaluated using state-of-the-art diagnostic algorithms to identify failure causes. Our methodology was validated using an established AI benchmark for diagnostics. We constructed an ontology description for the underlying cyber-physical system, deduced influences of system sensors from data, and successfully diagnosed induced failures, demonstrating the efficacy and applicability of our approach.
Version
Published version
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