Most model-based diagnosis systems, such as GDE and Sherlock, have concerned discrete, static systems such as logic circuits and use simple constraint propagation to detect inconsistencies. However, sophisticated systems such as QSIM and QPE have been developed for qualitative modeling and simulation of continuous dynamic systems. We present an integration of these two lines of research as implemented in a system called QDOCS for multiple-fault diagnosis of continuous dynamic systems using QSIM models. The main contributions of the algorithm include a method for propagating dependencies while solving a general constraint satisfaction problem and a method for verifying the consistency of a behavior with a model across time. Through systematic experiments on two realistic engineering systems, we demonstrate that QDOCS demonstrates the best balance of generality, accuracy, and efficiency among competing methods.

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In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pp. 965-970, Portland, OR, August 1996.

@InProceedings{subramanian:aaai96, title={Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes}, author={Siddarth Subramanian and Raymond J. Mooney}, booktitle={Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96)}, month={August}, address={Portland, OR}, key={diagnosis QDOCS QSIM MBD}, pages={965-970}, url="http://www.cs.utexas.edu/users/ai-lab?subramanian:aaai96", year={1996} }