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The need for economic, reliable, and effective delivery of electric power has lead to the search for fast, efficient, and effective methods for diagnosing the insulation of high-voltage (HV) equipment in the power industries. The recent dielectric techniques that have been carefully considered by major industries for transformer insulation condition assessment are the recovery voltage method (RVM) and the polarization and depolarization current (PDC) measurement. However, due to the complexity of the transformer insulation structure and various degradation mechanisms under multiple stresses, insulation condition assessment is usually performed by experts with special knowledge and experience. In this paper, an expert system (ES) is developed, which imitates the performance of a human expert, to make the complicated insulation condition assessment procedure accessible to plant maintenance engineers. The structure of the ES is described in detail including knowledge base, inference engine, and human-computer interface. Examples of the application of the ES are also presented to confirm that the system can provide accurate insulation diagnosis.