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.
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초록· 키워드
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Since one decade, the detection of HFPD (High frequency Partial Discharge) has been proposed as one of the effective method for the diagnosis of the power component under service in power grids. As a tool for HFPD detection, Metal Foil sensor based on the embedded technology has been commercialized for mainly power cable due to its advantages.
Recently, for the on-site noise discrimination, several PA (Pulse analysis) methods have been reported and the related software, such as Neural Network and Fuzzy, have been proposed to separate the PD (Partial Discharge) signals from the noises since their wave shapes are completely different from each other. On the other hand, the relevant fundamental investigation has not yet clearly made while it is reported that the effectiveness of the current methods based on PA is dependant on the types of sensors. Moreover, regarding the identification of the vital defects introducible into the Power Cable, the direct identification of the nature of defects from the PD signals through Metal Foil coupler has not yet been realized. As a trial for solving above shortcomings, different types of software have been proposed and employed without any convincing probability of identification.
In this regards, our novel algorithm "PA Map" based on the pulse analysis is suggested to identify directly the defects inside the power cable from the HFPD signals which is output of the HFCT and metal foil sensors. This method enables to discriminate the noise and then to make the data analysis related to the PD signals. For the purpose, the HFPD detection and PA (Pulse Analysis) system have been developed and then the effect of noise discrimination has been investigated by use of the artificial defects using real scale mockup. Throughout these works, our system is proved to be capable of separating the small void discharges among the very large noises such as big air corona and ground floating discharges at the on-site as well as of identifying the concerned defects.
Recently, for the on-site noise discrimination, several PA (Pulse analysis) methods have been reported and the related software, such as Neural Network and Fuzzy, have been proposed to separate the PD (Partial Discharge) signals from the noises since their wave shapes are completely different from each other. On the other hand, the relevant fundamental investigation has not yet clearly made while it is reported that the effectiveness of the current methods based on PA is dependant on the types of sensors. Moreover, regarding the identification of the vital defects introducible into the Power Cable, the direct identification of the nature of defects from the PD signals through Metal Foil coupler has not yet been realized. As a trial for solving above shortcomings, different types of software have been proposed and employed without any convincing probability of identification.
In this regards, our novel algorithm "PA Map" based on the pulse analysis is suggested to identify directly the defects inside the power cable from the HFPD signals which is output of the HFCT and metal foil sensors. This method enables to discriminate the noise and then to make the data analysis related to the PD signals. For the purpose, the HFPD detection and PA (Pulse Analysis) system have been developed and then the effect of noise discrimination has been investigated by use of the artificial defects using real scale mockup. Throughout these works, our system is proved to be capable of separating the small void discharges among the very large noises such as big air corona and ground floating discharges at the on-site as well as of identifying the concerned defects.
목차
Abstract
1. 서론
2. 실험 방법
3. 실험결과 및 분석
4. 154㎸ XLPE 전력 케이블 실험
5. 결론
감사의 글
참고문헌
저자소개
참고문헌 (7)
참고문헌 신청
1. [학술지(정기간행물)] - / 2006 / SENSORS AND SENSING USED FOR NON-CONVENTIONAL PD DETECTION
2. [학술지(정기간행물)] - / 2003 / A New Approach to the Dianosis of Solid Insulation Systems Based on PD Signal Inference 19 (2) : 23 ~ 30
3. [학술지(정기간행물)] - / 2003 / Advanced PD Interference in On field Measurements. Part 1 : Noise Rejection 10 (2) : 216 ~ 224
4. [학술지(정기간행물)] - / 2005 / Pulse Preclassification for online PD Noise Suppression based on realtime Pulse Shape Identification
5. [학술지(정기간행물)] - / / Synchronous Three Phase Partial Discharge Detection on Rotating Machines
2. [학술지(정기간행물)] - / 2003 / A New Approach to the Dianosis of Solid Insulation Systems Based on PD Signal Inference 19 (2) : 23 ~ 30
3. [학술지(정기간행물)] - / 2003 / Advanced PD Interference in On field Measurements. Part 1 : Noise Rejection 10 (2) : 216 ~ 224
4. [학술지(정기간행물)] - / 2005 / Pulse Preclassification for online PD Noise Suppression based on realtime Pulse Shape Identification
5. [학술지(정기간행물)] - / / Synchronous Three Phase Partial Discharge Detection on Rotating Machines
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