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논문 기본 정보

자료유형
학술저널
저자정보
Lee, Jong-Yong (Ingenium college of liberal arts, KwangWoon University) Lee, Chul (Department of Mechatronics, Inhatechnical Collage)
저널정보
(사)국제문화기술진흥원 The International journal of advanced culture technology The International journal of advanced culture technology 제4권 제2호
발행연도
2016.1
수록면
47 - 56 (10page)

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In transformer cooling systems, oil temperature is controlled through the use of a blower and oil pump. For this paper, set-point algorithms, a reset algorithm and control algorithms of the cooling system were developed by neural networks and fuzzy logics. The oil inlet temperature was set by a $2{\times}2{\times}1$ neural network, and the oil temperature difference was set by a $2{\times}3{\times}1$ neural network. Inputs used for these neural networks were the transformer operating ratio and the air inlet temperature. The inlet set temperature was reset by a fuzzy logic based on the transformer operating ratio and the oil outlet temperature. A blower was used to control the inlet oil temperature while the oil pump was used to control the oil temperature difference by fuzzy logics. In order to analysis the performance of these algorithms, the initial start-up test and the step change test were performed by using the dynamic model of a transformer cooling system. Test results showed that algorithms developed for this study were effective in controlling the oil temperature of a transformer cooling system.

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