• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2005년도 춘계 종합학술대회 논문집
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• pp.315-319
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• 2005

컴퓨터 시스템의 성능분석을 위하여 페트리 네트 기반 모델이 널리 사용되어 왔으나, 신뢰도와 가용도 분석을 위한 페트리 네트 모델링은 폭넓은 관심을 갖지 못했다. 본 논문에서는 페트리 네트를 이용한 데이터베이스 시스템의 신뢰도 분석과 모델링 기법에 대하여 논의한다. 공유 메모리(Shared Memory), 프로세서, 버스, 데이터베이스(디스크)의 구성요소를 갖는 고장감내형(fault-tolerant) 데이터 베이스 시스템의 신뢰도 분석을 위한 페트리 네트 모델을 개발한다. 각 구성요소에 대한 고장을 고려하며, 데이터베이스 시스템이 동작중일 조건은 데이터베이스가 동작하고 컴퓨터 구성요소인 프로세서, 메모리, 버스가 동작중인 경우로 한다. 각 구성요소는 개별적으로 고장이 날 수 있으며, 시스템이 동작하는 한 복구할 수 있다. 이러한 고장 및 복구 조건을 고려한 시스템의 신뢰도 분석을 페트리 네트의 확장 모델이며 모델링 기능이 풍부한 마르코프 reward 모델을 이용하여 수행한다. Stochastic Reward Net(SRN)이 갖고 있는 variable cardinality, enabling 함수, 시간천이 우선순위 등의 기능을 이용하여 신뢰도 모델을 개발하는 기법을 제시한다.

• 대한기계학회논문집A
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• 제41권11호
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• pp.1055-1064
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• 2017

로켓 모터와 같은 일회성 시스템은 매우 높은 신뢰도를 요구하기 때문에 합리적인 신뢰성 설계 방안이 필요한데 아직 국내에서는 단순히 각 부품별로 안전 계수를 부여하는 설계 방법을 적용해 왔다. 고전적인 신뢰성 해석에서는 한계 상태 함수에 사용되는 변수가 단일 값으로 입력되고 몇 개의 실험 데이터에 대하여 단순히 평균과 표준 편차를 취한 뒤 그 값을 신뢰성 해석에 사용하기 때문에 로켓 모터와 같이 높은 수준의 신뢰도를 요구하는 시스템에서 위험한 결과를 도출할 수 있다. 본 연구에서는 로켓 모터의 체결 볼트와 오링을 대상으로 베이지안 접근법을 활용하여 입력 변수를 통계적으로 추정하고 이를 통한 신뢰성 해석을 수행하였다. 추정된 변수는 확률 분포 형태로 도출되며 신뢰성 해석 결과로 계산되는 실패 확률 역시 분포로 주어지기 때문에 객관적이고 정량적인 설계 기준을 설정할 수 있다.

• 한국산학기술학회논문지
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• 제11권6호
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• pp.1997-2003
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• 2010

평균잔여수명은 공학, 의학, 생존분석, 사회과학 등 많은 분야에서 중요한 역할을 하고 있다. 특히 시스템의 신뢰성연구에서 시스템의 갑작스런 중지는 심각한 문제를 초래하기 때문에, 부품에 대한 평균잔여수명 추정은 매우 중요하다. 그래서 많은 상황변수를 고려한 시뮬레이션 연구가 되어왔다. 본 연구에서는 임의절단(random censoring) 에서 가지 평균잔여수명 추정기법을 소개하고 3가지 와이블 수명분포와 6가지 절단분포의 조합에서 시뮬레이션하였다. 또한 이들의 성과를 편의(bias)와 MSE측면에서 비교 분석하였다.

• 한국전문물리치료학회지
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• 제15권2호
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• pp.20-29
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• 2008

The purpose of this study was to examine the validity and reliability of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)-VA3.0 in patients with hip and knee osteoarthritis (OA). The sample consisted of 301 patients who had received treatments at the physical therapy units of 5 medical institutions in Andong City in june 2006. Questionnaires on the WOMAC were recruited by 12 physical therapists. The internal structure and reliability of the scales were evaluated by means of item-internal consistency (Cronbach's alpha coefficient: ${\alpha}$), item-discriminant validity, and Pearson's relation coefficient. To explore construct validity, we conducted a principal component factor analysis with varimax rotation analysis. The criterion for factor extraction was an eigenvalue >1.0. The average age of the patients was 62.1 years. All WOMAC subscales (pain, stiffness, and physical function) were internally consistent with Cronbach's coefficients of .81, .91, and .80, respectively. The internal consistency reliability of item-each scale were also internally consistent with Cronbach's coefficient of .89 (Pearson's correlation coefficient: .71~.84), .93 (.89~.91), and .96 (.67~.91), respectively. However, high correlation was found among 3 items (.66~.83, .66~.67, and .67~.83), so the item-discriminant validity was low (${\alpha}$ coefficient: .81, .91, .80, respectively). The construct validity by factor analysis was low because it was not consistent With WOMAC-VA3.0. In conclusion, the results reported here confirm the reliability of the WOMAC in patients with OA of the hip and knee. The collection of information on the hip and knee osteoarthritis using this instrument was acceptable to patients. A further prospective multi-center study will be necessary to prove the construct validity.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Nuclear Engineering and Technology
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• 제55권3호
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 하계학술발표대회 논문집
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• pp.3-9
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• 2008

Recently, the plant industries are being activated and plant control systems use various technologies. Because the optimized design for the plants is very important for the reducing of operation and maintenance costs, automatic control systems become more important. Plant control systems consist of the master controller, the plant networks, the programming environment for engineering, monitoring software and the field devices. The control systems should have reliability, availability and safety. Modular architecture of hardware and software makes flexible configuration of the control systems. Each component should have diagnostic functions. It follows industrial standards and makes open systems. Open systems increase accessibility against the data which is distributed in the plants. The controllers including processor and communication modules use the up-to-date technology. They have real time and fault tolerant function by duplicating processors or networks. It also enables to make the distributed control systems. The distributed architecture makes more scalable main control system. Automatic control systems can be operated with better performance. In this paper, we analyzed the requirements of the seawater desalination plants and made some consideration facts for developing the optimized controller. Also we described the design concept of the main controller, which consists of several modules. We should validate and complement the design for the reliability and better performance.

• 대한기계학회논문집A
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• 제33권5호
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• pp.521-528
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• 2009

One of reliability measurements of vehicle is estimated by driving mileage but the reliability of component, such as an hydraulic clutch system, is defined from the number of successful operational cycle. Relationship between these reliability measurement variables(mileage and cycle) should be examined first of all in the reliability estimation of components. Relationship between mileage and cycles is commonly known as linear function. However, the gradient depends on the operational environmental condition. Therefore, estimation of mission profile variable should be done with correlation analysis at the same time. In this paper, we derive mission profile variable of an hydraulic clutch system by field vehicle test and suggest the determination process of durability test parameters of CMC(Clutch Master Cylinder) with mission profile variable.

• 대한기계학회논문집
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• 제19권6호
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• pp.1439-1450
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• 1995

Bellows is a familiar component in piping systems as it provides a relatively simple means of absorbing thermal expansion and providing system flexibility. In routine piping flexibility analysis by finite element methods, bellows is usually considered to be straight pipe runs modified by an appropriate flexibility factor; maximum stresses are evaluated using a corresponding stress concentration factor. The aim of this study is to develop a bellows finite element, which similarly includes more complex shell type deformation patterns. This element also does not require flexibility or stress factors, but evaluates more detailed deformation and stress patterns. The proposed bellows element is a 3-D, 2-noded line element, with three degrees of freedom per node and no bending. It is formulated by including additional 'internal' degrees of freedom to account for the deformation of the bellows corrugation; specifically a quarter toroidal section of the bellows, loaded by axial force, is considered and the shell type deformation of this is include by way of an approximating trigonometric series. The stiffness of each half bellows section may be found by minimising the potential energy of the section for a chosen deformation shape function. An experiment on the flexibility is performed to verify the reliability for bellows finite element.

• Tribology and Lubricants
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• 제39권3호
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• pp.94-101
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• 2023

Automotive wheel bearings are a critical component of vehicles that support their weight and facilitate rotation. Life and stiffness are significant performance characteristics of wheel bearings. Designing wheel bearings involves finding optimal design variables that satisfy both performances. CO₂ emission reduction and fuel efficiency regulations attribute to the recent increase in design requirements for lightweight and compact automotive parts while maintaining performance. However, achieving a design that maintains performance while reducing weight poses challenges, as performance and weight are generally inversely proportional. In this study, we perform design optimization of automotive wheel bearings considering life and stiffness. We develop a program that calculates the basic rated life and modified rated life based on international standards for evaluating the life of wheel bearings. We develop a regression equation using regression analysis to address the time-consuming stiffness analysis during repetitive analysis. We perform ANOVA and main effect analyses to understand the statistical characteristics of the developed regression equation. Furthermore, we verify its reliability by comparing the predicted and test results. We perform design optimization using the developed life prediction program, stiffness regression equation and weight regression equation. We select bearing specifications and geometry as design variables, weight as the cost function, and life and stiffness as constraints. Through design optimization, we investigate the influence of design variables on the cost function and constraints by comparing the initial and optimal design values.