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- 저자 : 장범찬(Beom-Chan Jang) (검색결과 6 건)
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장범찬(Beom Chan Jang),윤병동(Byeng D.Youn),김희수(Hee Soo Kim),배용채(Yong Chae Bae) 대한기계학회 2015 大韓機械學會論文集A Vol.39 No.6
본 연구에서는 수냉식 발전기 고정자 권선의 건전성 예지 방법에 대해 연구하였다. 권선의 데이터를 흡습 데이터와 정상 데이터로 분류 하였으며 각각의 데이터 군을 다른 방법으로 예측 하였다. 흡습 데이터를 예측하기 위해 픽의 제 2 법칙(Fick’s second law)를 이용하여 건전성 감소 모델링을 하였고 픽의 제 2법칙의 해를 이용하여 흡습 모델식을 만들었다. 정상 데이터는 데이터의 분포가 정규분포를 따른다는 가설을 세운 후 카이제곱 검정을 통해 이를 입증하였다. 예측된 흡습 데이터와 정상 데이터를 이용하여 건전성 인자인 방향성 마할라노비스 거리(Directional mahalanobis distance; DMD)의 예측값을 산출하였고 흡습 권선의 고장 예상시점을 계산했다. In this study, we develop a prognostic method of assessing the stator windings of power generators against water absorption through statistical data analysis and degradation modeling. The 42 windings of the generator are divided into two groups: the absorption and normal groups. A degradation model of a winding is constructed using Fick"s second law to predict the level of absorption. By analyzing data from the normal group, we can determine the distribution of the data of normal windings. The health index of a winding is estimated using the directional Mahalanobis distance (DMD) method. Finally, the probability distributions of the failure time of the windings are determined.
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Fick’s second law 를 이용한 수냉식 발전기 고정자 권선의 건전성 예지
윤병동(Byeng D. Youn),장범찬(Beom-Chan Jang),김희수(Hee-Soo Kim),배용채(Yong-Chae Bae) 한국소음진동공학회 2014 한국소음진동공학회 학술대회논문집 Vol.2014 No.10
Power generator is one of the most important component of electricity generation system to convert mechanical energy to electrical energy. I t designed robustly to maintain high system reliability during operation time. But unexpected failure of the power generator could happen and it cause huge amount of economic and social loss. To keep it from unexpected failure, health prognostics should be carried out In this research, We developed a health prognostic method of stator windings in power generator with statistical data analysis and degradation modeling against water absorption. We divided whole 42 windings into two groups, absorption suspected group and normal group. We built a degradation model of absorption suspected winding using Fick’s second law to predict upcoming absorption data. Through the analysis of data of normal group, we could figure out the distribution of data of normal windings. After that, we can properly predict absorption data of normal windings. With data prediction of two groups, we derived upcoming Directional Mahalanobis Distance (DMD) of absorption suspected winding and time vs DMD curve. Finally we drew the probability distribution of Remaining Useful Life of absorption suspected windings.
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Fick’s second law 를 이용한 수냉식 발전기 고정자 권선의 건전성 예지
윤병동(Byeng D. Youn),장범찬(Beom-Chan Jang),김희수(Hee-Soo Kim),배용채(Yong-Chae Bae) 대한기계학회 2014 대한기계학회 춘추학술대회 Vol.2014 No.11
Power generator is one of the most important component of electricity generation system to convert mechanical energy to electrical energy. It designed robustly to maintain high system reliability during operation time. But unexpected failure of the power generator could happen and it cause huge amount of economic and social loss. To keep it from unexpected failure, health prognostics should be carried out In this research, We developed a health prognostic method of stator windings in power generator with statistical data analysis and degradation modeling against water absorption. We divided whole 42 windings into two groups, absorption suspected group and normal group. We built a degradation model of absorption suspected winding using Fick’s second law to predict upcoming absorption data. Through the analysis of data of normal group, we could figure out the distribution of data of normal windings. After that, we can properly predict absorption data of normal windings. With data prediction of two groups, we derived upcoming Directional Mahalanobis Distance (DMD) of absorption suspected winding and time vs DMD curve. Finally we drew the probability distribution of Remaining Useful Life of absorption suspected windings.
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