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Resilience Allocation for Resilient Engineered System Design
윤병동(Byeng D. Youn),후차오(Chao Hu),왕핑펭(Pingfeng Wang),윤정택(Joungtaek Yoon) 제어로봇시스템학회 2011 제어·로봇·시스템학회 논문지 Vol.17 No.11
Most engineered systems are designed with high levels of system redundancies to satisfy required reliability requirements under adverse events, resulting in high systems’ LCCs (Life-Cycle Costs). Recent years have seen a surge of interest and tremendous advance in PHM (Prognostics and Health Management) methods that detect, diagnose, and predict the effects of adverse events. The PHM methods enable proactive maintenance decisions, giving rise to adaptive reliability. In this paper, we present a RAP (Resilience Allocation Problem) whose goal is to allocate reliability and PHM efficiency to components in an engineering context. The optimally allocated reliability and PHM efficiency levels serve as the design specifications for the system RBDO (Reliability-Based Design Optimization) and the system PHM design, which can be used to derive the detailed design of components and PHM units. The RAP is demonstrated using a simplified aircraft control actuator design problem resulting in a highly resilient actuator with optimally allocated reliability, PHM efficiency and redundancy for the given parameter settings.
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.
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.
모듈형 시스템 설계를 위한 플러그인 디지털 해석모델의 통계적 보정 및 검증 기술 최신 동향과 전망
윤병동(Byeng D. Youn),윤헌준(Heonjun Yoon),박정호(Jungho Park),이규석(Guesuk Lee),오현석(Hyunseok Oh) 대한기계학회 2014 대한기계학회 춘추학술대회 Vol.2014 No.11
As engineered products become more complex with a shorter development cycle, many leading conglomerates have introduced the concept of modular system design. With this trend, the role of virtual testing using a computer-aided engineering (CAE) model has increased. However, it is challenging to build a high-fidelity CAE model for plug-in digital analysis of a modular system due to the interactions of modules and joints as well as the complicated nature of the full system. One possible solution is statistical model calibration and validation which can improve and ensure the predictive capability of a CAE model. The purpose of this study is to review the current trends and future directions in model calibration and validation for plug-in digital analysis. Three main areas are focused: (i) correlation metric, (ii) model calibration, and (iii) model validation. This paper attempts to provide insights for adopting an appropriate technique in model calibration and validation for a modular system design.
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.