지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학위논문
- 저자정보
- 지도교수
- 구자윤
- 발행연도
- 2013
- 저작권
- 한양대학교 논문은 저작권에 의해 보호받습니다.
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The application of the superconducting power apparatus is now being considered as one of the promising tool for enlarging the limited transmission capacity of the traditional electric power apparatus due to the several technical advantages such as reduced size, weight, high efficiency and so on. Therefore, since more than two decades, many research institutes try to improve performance by carrying out experimental investigations related to the reliability of the apparatus under cryogenic temperature. One of them is Partial discharge (PD) detection which is considered as the indication of the insulation state of the apparatus, however, very few reports have been reported based on the results obtained under cryogenic temperature. In this work, 3 different types of artificial defects are put into Liquid Nitrogen in order to produce PD under AC applied voltage: protrusion, floating electrode, and turn to turn. PD signals are detected by use of our specially designed sensor and then its pattern recognition is made based on PRPDA (Phase Resolved PD Analysis) and CAPD (Chaos Analysis of Partial Discharge). Regarding the related recognition rate, NN (Neural Networks) is employed for learning process. Moreover, other patterns from the unknown defects are also put into network for its comparison. On the other hand, difference in recognition rate depending on three methods of NN has been noticed enabling us to deduce their related recognition rate.
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