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.
초록· 키워드
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This study was carried out for the reliability of PD(Partial Discharge) pattern recognition. For the pattern recognition, the database for PD was established by use of self-designed insulation defects which occur and were mostly critical in GIS(Gas Insulated Switchgear). The acquired database was analyzed to distinguish patterns by means of PRPD(Phase Resolved Partial Discharge) method and stored to the form with to unite the average amplitude of PD pulse and the number of PD pulse as the input data of neural network.
In order to prove the performance of genetic algorithm combined with neural network, the neural networks with trial-and-error method and the neural network with genetic algorithm were trained by same training data and compared to the results of their pattern recognition rate.
As a result, the recognition success rate of defects was 93.2% and the neural network train process by use of trial-and-error method was very time consuming. The recognition success rate of defects, on the other hand, was 100% by applying the genetic algorithm at neural network and it took a relatively short time to find the best solution of parameters for optimization. Especially, it could be possible that the scrupulous parameters were obtained by genetic algorithm.
In order to prove the performance of genetic algorithm combined with neural network, the neural networks with trial-and-error method and the neural network with genetic algorithm were trained by same training data and compared to the results of their pattern recognition rate.
As a result, the recognition success rate of defects was 93.2% and the neural network train process by use of trial-and-error method was very time consuming. The recognition success rate of defects, on the other hand, was 100% by applying the genetic algorithm at neural network and it took a relatively short time to find the best solution of parameters for optimization. Especially, it could be possible that the scrupulous parameters were obtained by genetic algorithm.
목차
Abstract
1. 서론
2. 실험장치 및 모의절연결함
3. 부분방전 패턴분석
4. 부분방전 패턴인식
5. 결론
감사의 글
참고문헌
저자소개
참고문헌 (7)
참고문헌 신청
1. [학술지(정기간행물)] - E. Gulski / 1993 / Neural Network as a Tool for Recognition of Partial Discharges / IEEE Transactions on Electrical Insulation 28 (6) : 984 ~ 1001
2. [학술대회논문] - G. Wu / 2000 / A Neural Network Used for PD Pattern Recognition with Genetic Algorithm / Proceedings of the 6th International Conference on Properties and Application of Dielectric Materials : 451 ~ 454
3. [단행본] - A. Krivda / 1995 / Recognition of Discharge - Discrimination and Classification / Dictorial Thesis of Delft University, Delft Univ. Press
4. [학술대회논문] - S. Kim / 2006 / A Study on the Improvement of PD Pattern Recognition Probability using Combined Neural Network (CNN) Model / International Conference on Condition Monitoring and Diagnosis : PT-114 ~
5. [학술지(정기간행물)] - Y. Lim / 2004 / A Novel Approach for the Pattern Classification of Partial Discharges in Gas-Insulated Switchgear using a Chaotic Theory Combined with Spectral Analysis / Cigre : D1-305 ~
2. [학술대회논문] - G. Wu / 2000 / A Neural Network Used for PD Pattern Recognition with Genetic Algorithm / Proceedings of the 6th International Conference on Properties and Application of Dielectric Materials : 451 ~ 454
3. [단행본] - A. Krivda / 1995 / Recognition of Discharge - Discrimination and Classification / Dictorial Thesis of Delft University, Delft Univ. Press
4. [학술대회논문] - S. Kim / 2006 / A Study on the Improvement of PD Pattern Recognition Probability using Combined Neural Network (CNN) Model / International Conference on Condition Monitoring and Diagnosis : PT-114 ~
5. [학술지(정기간행물)] - Y. Lim / 2004 / A Novel Approach for the Pattern Classification of Partial Discharges in Gas-Insulated Switchgear using a Chaotic Theory Combined with Spectral Analysis / Cigre : D1-305 ~
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