An ontology model for intelligent tools applied to transformer condition evaluation

Numerous tests are applied to power and instrument transformers during their life cycle in order to evaluate their condition. The results of part of these tests are analyzed through simple comparison to thresholds established in well-accepted standards, but some require expertise to infer about the transformer condition. Researchers often suggest the use of intelligent techniques to interpret results of some transformer tests or to combine information from several analyses with monitoring devices. This paper proposes an ontology model to be used in applications of artificial intelligence techniques to transformer condition assessment, aiming to facilitate the communication and integration of separate modules.