Artificial Intelligence
Automatica (Journal of IFAC)
Introduction to Physical System Dynamics
Introduction to Physical System Dynamics
Model-based monitoring of dynamic systems
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Combined qualitative-quantitative steady-state diagnosis of continuous-valued systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Proceedings of the 1999 ACM symposium on Applied computing
Process algebras for systems diagnosis
Artificial Intelligence
Sliding Mode Model Semantics and Simulation for Hybrid Systems
Hybrid Systems V
Series of Abstractions for Hybrid Automata
HSCC '02 Proceedings of the 5th International Workshop on Hybrid Systems: Computation and Control
Model-based diagnosis in the real world: lessons learned and challenges remaining
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
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Diagnosis of dynamic physical systems is complex and requires close interaction of monitoring, fault generation and refinement, and prediction. We establish a methodology for model-based diagnosis of continuous systems in a qualitative reasoning framework. A temporal causal model capturing dynamic system behavior identifies faults from deviant measurements and predicts future system behavior expressed as signatures, i.e., qualitative magnitude changes and higher order time-derivative effects. A comparison of the transient characteristics of the observed variables with the predicted effects helps refine initial fault hypotheses. This allows for quick fault isolation, and circumvents difficulties that arise when interactions caused by feedback and dependent faults. This methodology has been successfully applied to the secondary cooling loop of fast breeder reactors.