Prediction-based diagnosis and loss prevention using qualitative multi-scale models

A prototype prediction based intelligent diagnostic system that is capable of integrating qualitative and quantitative process models and operation experience in the form of HAZOP result tables is proposed in this paper. The knowledge base of the system is organized in a hierarchical way following the hierarchy levels of the multi-scale model of the process system. This supports the focusing of the fault detection and loss prevention and thus decomposes the otherwise computationally hard problem. The system is illustrated on the example of a commercial fertilizer granulator drum.