A theory of diagnosis from first principles
Artificial Intelligence
Readings in model-based diagnosis
Readings in model-based diagnosis
Issues of Fault Diagnosis for Dynamic Systems
Issues of Fault Diagnosis for Dynamic Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Possible conflicts: a compilation technique for consistency-based diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An interval-based approach for fault isolation and identification in continuous dynamic systems
Proceedings of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
Computer Methods and Programs in Biomedicine
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A model-based approach for fault diagnosis is proposed, where the fault detection is based on checking the consistency of the Analytical Redundancy Relations (ARRs) using an interval tool. The tool takes into account the uncertainty in the parameters and the measurements using intervals. Faults are explicitly included in the model, which allows for the exploitation of additional information. This information is obtained from partial derivatives computed from the ARRs. The signs in the residuals are used to prune the candidate space when performing the fault diagnosis task. The method is illustrated using a two-tank example, in which these aspects are shown to have an impact on the diagnosis and fault discrimination, since the proposed method goes beyond the structural methods.