Diagnostic reasoning based on structure and behavior
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
A theory of diagnosis from first principles
Artificial Intelligence
A correction to the algorithm in Reiter's theory of diagnosis
Artificial Intelligence
Model-based, multiple fault diagnosis of time-varying, continuous physical devices
Proceedings of the sixth conference on Artificial intelligence applications
Modeling digital circuits for troubleshooting
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Qualitative multiple-fault diagnosis of continuous dynamic systems using behavioral modes
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Modeling uncertain temporal evolutions in model-based diagnosis
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
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We present a new approach to model-based monitoring and diagnosis of dynamic systems. The presented DIAMON algorithm uses hierarchical models to monitor and diagnose dynamic systems. DIAMON is based on the integration of teleological parameter-based monitoring models and repair-oriented device-based diagnosis models. It combines consistency-based diagnosis with model-based monitoring and uses an extension of the QSIM-language for the representation of qualitative system models. Furthermore, DIAMON is able to detect and localize a broad range of nonpermanent faults and thus extends traditional diagnosis which exclusively deals with permanent faulty behavior. The operation of DIAMON will be demonstrated on a real-world example in a multiple-faults scenario.