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Statistical Health Reasoning of Water-Cooled Power Generator Stator Bars Against Moisture Absorption
Youn, Byeng D.,Kyung Min Park,Chao Hu,Joung Taek Yoon,Hee Soo Kim,Beom Chan Jang,Yong Chae Bae IEEE 2015 IEEE transactions on energy conversion Vol.30 No.4
<P>The power generator is typically maintained with a time- or usage-based strategy, which could result in a substantial waste of remaining useful life, high maintenance cost, and low plant availability. Recently, the field of prognostics and health management offers diagnostic and prognostic techniques to precisely assess the health condition and robustly predict the remaining useful life (RUL) of an engineered system, with an aim to address the aforementioned deficiencies. This paper explores a smart health reasoning system to assess the health condition of power generator stator bars against moisture absorption based on the statistical analysis of the capacitance measurements on bar insulators. In particular, a relative health measure, namely the directional Mahalanobis distance, is proposed to quantify the health condition of a stator bar. The smart health reasoning system is validated using five years' field data from seven generators, each of which contains 42 turns.</P>
저널베어링 상태 진단을 위한 최적의 데이터 분석 기준 설정
윤병동(Byeng D. Youn),정준하(Joonha Jung),전병철(Byungchul Jeon),김연환(Yeon-Whan Kim),배용채(Yong-Chae Bae) 한국소음진동공학회 2014 한국소음진동공학회 학술대회논문집 Vol.2014 No.10
Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.
불인지 불확실성을 고려한 CAE 해석 모델의 예측 정확도 개선
윤병동(Byeng D. Youn),유민지(Minji Yoo),이규석(Guesuk Lee),손혜정(Hyejeong Son),오현석(Hyunseok Oh) 대한기계학회 2015 대한기계학회 춘추학술대회 Vol.2015 No.11
In the design of passenger vehicles in the automotive industry, virtual testing is widely used. However, building a highly-predictive CAE model is still challenging. In this paper, to build a highly-predictive CAE model, several issues in statistical model validation approach are studied with an example of the steering column in cockpit modules: (1) selecting unknown input variables, (2) calibrating unknown parameters, and finally (3) checking the validity of CAE model using area metric based hypothesis testing. It is expected that the study helps to enhance the predictive capability of CAE models.