11 - Operations and Sustainment
ONTOLOGY-BASED SENSOR HEALTH MONITORING: A DYNAMIC ONTOLOGY-BASED FAULT DETECTION AND CLASSIFICATION FOR TIMESERIES DATA
C. Klein¹, E. Arts¹, B. Atanasoaie¹, H. Meyer¹, F. Raddatz¹, Z. Daw, University of Stuttgart, Institute of Aircraft Systems, Germany; ¹German Aerospace Center (DLR), Germany
We present an ontology-based Sensor Health Monitoring method for predictive maintenance, validated on Falcon 2000LX data. By integrating system metadata and simulation models, it detects sensor faults deterministically, enabling uncertainty quantification and expert insight. The approach is scalable to any asset with structured metadata, offering broad relevance beyond aerospace.
DOI: 10.71945/icas2026_0716