A RS APPROACH TO FOUNDING AND MAINTAINING ES KNOWLEDGE BASE FOR FAULT DIAGNOSIS OF POWER TRANSFORMER
Shu Hong · Proceedings of the CSEE · 2002
In order to resolve the bottleneck problem of obtaining complete knowledge of expert system,a Rough Set approach to founding knowledge base of an expert system for transformer fault diagnosis is proposed.From the reduction of decision table defined by history fault data,a series of nodes network rule sets,with suitable belief degree under different reductive levels,are developed by calculating the rough subjection degree of every rule.When the fault information of transformer is given,one can match the information to the rule sets of relative nodes.Even when the data of DGA is imperfect,the diagnosis results are correct.The knowledge base is maintained through reasoning machine and database.A lot of diagnosis examples show that the ES is quite efficient,flexible and fault tolerant.