• Nuclear Engineering and Technology
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• 제17권2호
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• pp.83-97
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• 1985

GLR (Generalized Likelihood Ratio)방식은 최적상태 변수 추정기인 Kalman-Buchy 필터로부터 발생되는 연속 Innovation들에 대해 통계확률적검사를 수행함으로써 시스템 고장 탐지 및 종류를 판별하게 된다. 그러나, 이러한 종전의 GLR방식은 각 경우마다 특별한 고장 형태를 가정해야 하므로, 모든 가능한 고장 형태를 탐지하는 데 많은 어려움이 있다. 이번 논문에서는 이런 난제를 해결할 한 방법을 제시하였다. 그리고, 가압경수형 원자력발전소 일차측 압력을 조절하는 가압기에 적용시켜 본 결과, 어떤 형태의 고장이든 잘 탐지되고 그 종류도 구별할 수 있음을 보여주었으며, 종전방식에 비해 고장 탐지 및 고장 구별에 필요한 컴퓨터처리 시간도 줄일 수가 있었다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2002년도 춘계학술대회
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• pp.89-95
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• 2002

This paper considers the problem of estimating paramaters of the bivariate exponential distribution with a loaction parameter for a two-component shared parallel system using component data from system-level life test terminated at the time of the prespecified number of system failure. In the system-level life testing, there are three patterns of failure types; 1) both component failed 2) both component censored 3) one is failed and the other is censored. In the third case, we assume that the failure time might be known or unknown. The maximum likelihood estimators are obtained for the case of known/unknown failure time when the other component is censored.

• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.241-250
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• 2020

This study examines the relationship between the attributes of board structure and the likelihood of financial distress for the non-financial sector of an emerging market characterized by concentrated ownership and family-controlled business. The present study utilized panel logistic regression to estimate the relationship between board structure attributes and the likelihood of financial distress. We used Altman Z-Score as a proxy for firm financial distress, as this tool measures the financial distress inversely. The study finds a significant relationship between board size and the likelihood of financial distress. The results show that a one-unit increase in board size would decrease the probability of financial distress by 3.4%. Further, we observe that a greater level of board independence is associated with a lower likelihood of financial distress. A one-unit increase in board independence would decrease the probability of financial distress by 20.4%. We also find a significant positive impact of leverage on the likelihood of financial distress. The present study contributes to the body of literature on board structure attributes and likelihood of financial distress in emerging markets, like Pakistan. Furthermore, the findings would be beneficial for corporate policymakers and investors in formulating corporate financial strategy and predicting business failure.

• Geomechanics and Engineering
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• 제24권3호
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.

• 대한기계학회논문집A
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• 제27권3호
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• pp.416-423
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• 2003

During the last ten years, the need has been increased for reducing maintenance cost for aged equipments and ensuring safety, efficiency and profitability of petrochemical and refinery plants. RBI (Risk Based Inspection) methodology is one of the most promising technologies satisfying the need in the field of integrity management. In this study, a user-friendly software, realRBl for RBI based on the API 581 code was developed. This software has modules for evaluating qualitative and semi-quantitative risk level, analyzing quantitative risks using the potential consequences of a failure of the pressure boundary, and assessing the likelihood of failure. A quantitative analysis was performed for 16 columns in a domestic NCC (Naphtha Cracking Center) plant whose operating time reaches about 12 years. Each column was considered as two equipment parts by dividing into top and bottom. Generic column failure frequencies were adjusted based on likelihood data. After determining release rate, release duration and release mass for each failure scenario, flammable/explosive and toxic consequences were assessed. Current risks for 32 equipment parts were evaluated and risk based prioritization were determined as a final result.

• 한국소음진동공학회논문집
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• 제21권2호
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• pp.146-153
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• 2011

Model based machine condition diagnosis methods are generally using a normal and many failure models which need sufficient data to train the models. However, data, especially for failure modes of interest, is very hard to get in real applications. So their industrial applications are either severely limited or impossible when the failure models cannot be trained. In this paper, continuous hidden Markov model(CHMM) with only a normal model has been suggested as a very promising machine condition diagnosis method which can be easily used for industrial applications. Generally hidden Markov model also uses many pattern models to recognize specific patterns and the recognition results of CHMM show the likelihood trend of models. By observing this likelihood trend of a normal model, it is possible to detect failures. This method has been successively applied to arc weld defect diagnosis. The result shows CHMM's big potential as a machine condition monitoring method.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.571-579
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• 1998

In this paper we propose smooth nonparametric estimator of Mean Residual Life(MRL) based on a complete sample. This estimator is constructed using estimator of cumulative failure rate which is derived as the maximum likelihood estimate of cumulative failure rate in the class of distributions which have piecewise linear failure rate functions between each pair of observations. We derive the asymptotic properties of the our estimator. The proposed estimator is compared with previously known estimator by Monte Carlo study.

• 품질경영학회지
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• 제25권3호
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• pp.51-61
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• 1997

We introduce a method of estimating an unknown failure rate function based on sample data. We estimate failure rate function by a function s from a space of cubic splines constrained to be linear (or constant) in tails using maximum likelihood estimation. The number of knots are determined by Bayesian Information Criterion(BIC). Examples using simulated data are used to illustrate the performance of this method.

• 대한안전경영과학회지
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• 제3권4호
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• pp.65-76
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• 2001

Field data have been recorded as the time to failure or the number of failure of systems. We consider the time to failure and covariate variables in some pre-specified follow-up or warranty period. This paper aims to investigate study on the reliability estimation when some additional field data can be collected within-warranty period or after-warranty period. A various likelihood-based methods are outlined and examined for exponential or Weibull distribution.

• Journal of applied mathematics & informatics
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• 제8권1호
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• pp.243-252
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• 2001

The points of failure of a decomposition process are defined to be the union of the points of failure from two component point processes for software reliability systems. Because sampling from the likelihood function of the decomposition model is difficulty, Gibbs Sampler can be applied in a straightforward manner. A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For model determination, we explored the prequential conditional predictive ordinate criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. A numerical example with a simulated data set is given.