State assessment and preventive diagnosis of power transformers: a knowledge-based approach

This paper presents a knowledge-based system, called ASTRA, for state assessment and preventive diagnosis of power transformers. The main goal of ASTRA is to support novices or non-expert operators to make the first decisions about the state of a transformer and to single out cases in which expert consultation is needed. ASTRA can also provide suggestions about appropriate interventions, along with indications about their urgency. ASTRA features a novel distributed knowledge-based architecture, where independent specialists cooperate to reach a global result. Each specialist has autonomous reasoning capabilities and is able to perform a set of specific casks. Uncertainty affecting both data and domain knowledge is explicitly represented and propagated during the reasoning process, from data collection to the presentation of the final results to the user. The conclusions reached by ASTRA are presented to the user in an intuitive graphical form and are supported, on request, by explanations.