Abstract
An approach to the building of a hierarchical hybrid expert system for the technical diagnosis of chemical plants is presented that utilizes both qualitative and quantitative process knowledge. Evidential intervals are used to make allowances for the inaccuracy of expert estimations, instability of parameters, measurement noise etc. Diagnostic variables are represented as interval numbers. It is shown that such an approach gives a number of advantages over Bayesian and fuzzy set techniques. A procedure for identification of possibly faulty process chains in the first stage of a diagnosis is described using the example of a nitric acid production process. Detailed diagnosis, not treated in this paper, would be applied after candidate process chains are located.
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