THE METHODOLOGY FOR KNOWLEDGE-BASE COMPRESSION AND ROBUST DIAGNOSIS -APPLICATION TO A STEAM BOILER PLANT

The new diagnosis approach, which is based on SDG to we the advantages of SDG and covers the problems that conventional SDG-based methods ca nnot handle, is employed for robust diagnosis. Two compression methods are suggested to prevent the drawbacks of the approach which a very l arge knowledge base gives in large-scale processes. The clustering of measured variables and the system decomposition enables minimization, easy construction and maintenance of the knowledge base and flexible d iagnosis throughout the operational change of the process. To show the advantages of the proposed methods, the fault diagnosis system for a steam boiler plant, ENDS (ENergy Diagnosis System) was developed using the expert system shell G2. In the case study, the size of the diagno stic rules is reduced to 0.75% of that of the case without compression , and the system is verified to give fast and robust diagnosis results for the real system. (C) 1997 Elsevier Science Ltd.