9527302 Tomsovic This project is aimed at developing an information theoretic approach for assessing power system equipment condition with the goal of improving the overall integrity of the power system. This research is felt to be particularly important in light of concerns with the quality of the nation's civil infrastructure system. In terms of overall power system reliability and security, individual equipment condition plays a critical role. Electric utilities direct significant effort towards detecting accelerated aging and preventing catastrophic equipment failures. Traditional maintenance and condition monitoring schedules were based primarily on manufacturer recommended fixed time intervals. In recent years due to greater economic pressures, utilities have begun, one, to shift towards longer maintenance intervals and two, to load equipment significantly beyond manufacturer ratings. Under normal conditions, there is adequate design margin to allow both reduced maintenance and some overloading. Recent sensor developments offer the ability to further stretch equipment limits by monitoring certain key variables. Unfortunately, the breakdown mechanism of most equipment are only partially understood so that developed methods for early detection of equipment failures are imprecise and unreliable. Broad experience with a particular technique is necessary to overcome this impression and perform effective diagnosis. In addition, most equipment has relatively long expected lifetimes so that there may not be significant failure date to perform meaningful statistical models of failures. Together the above factors, suggest that utilities are following practices with limited knowledge of the long term impacts on system reliability. They may not fully understand the limits to which their equipment can be pushed. Further, they lack the computational framework to include their data and the experience in a workable model. This work focuses on developing an info rmation theoretic framework for modeling the imperfect knowledge of equipment breakdown with the ability to easily incorporate new information as experience is gained. The long term objective is to allow both statistical, process and heuristic data in a model which allows for improved suggestions on maintenance intervals, diagnostic conclusions and reliability evaluation. This project will focus on underlying general principles of power system equipment in developing this model. ***
