• 한국도로학회논문집
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• 제18권4호
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• pp.63-68
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• 2016

PURPOSES : The nonlinear model of fatigue cracking is typically used for determining the maintenance period. However, this requires that the model parameters be known. In this study, the particle filter (PF) method was used to determine various statistical parameters such as the mean and standard deviation values for the nonlinear model of fatigue cracking. METHODS : The PF method was used to determine various statistical parameters for the nonlinear model of fatigue cracking, such as the mean and standard deviation. RESULTS : On comparing the values obtained using the PF method and the least square (LS) method, it was found that PF method was suitable for determining the statistical parameters to be used in the nonlinear model of fatigue cracking. CONCLUSIONS : The values obtained using the PF method were as accurate as those obtained using the LS method. Furthermore, reliability design can be applied because the statistical parameters of mean and standard deviation can be obtained through the PF method.

• Corrosion Science and Technology
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• 제7권5호
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• pp.296-299
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• 2008

High order statistical parameters were evaluated using the electrochemical noise data collected during corrosion of type 430 stainless steel coupled to a inert, platinum electrode in 3.5% NaCl solution. High order statistical parameters are shown to predict uniform corrosion properly. However, Localization index, skewness of current, kurtosis and skewness of potential are capable of predicting pitting corrosion only when the transients are large with long life time. Of the high order statistical parameters evaluated, kurtosis of current is found to be the most sensitive parameter for detecting uniform and pitting corrosion.

• 한국음향학회지
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• 제8권1호
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• pp.5-12
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• 1989

RMS, Kurtosis, Crest factor, Probability of exceedance와 Probability density function 등의 통계적 파라미터를 선정하여 베어링의 사용조건과 결함진전에 따른 변화특성을 조사하였다. 이를 위해 4볼 시험기에서 하중, 회전수 및 시간을 변화시키면서 실험하여 진동신호를 수집하고, 이를 A/D변환시킨 후 디지털 필터링하여 주파수 대역별 통계적 파라미터 값을 계산하였다. 실험결과, 하중이나 회전수와 같은 운전조건이 변화하는 경우 RMS의 값은 운전조건 변화에 따라 변하지만 Kurtosis 등의 통계적 파라미터들은 운전조건과 무관하게 steady한 결과를 나타내었다. 또한 통계적 파라미터와 시간과의 상관관계에 대한 실험으로부터 통계적 파라미터들을 결함의 진전 상태를 나타내는 파라미터로 사용할 수 있음을 확인하였으며, 따라서 파손방지를 위한 예측지표로서 이들 통계적 파라미터를 이용할 수 있을것으로 판단되었다.

• Structural Engineering and Mechanics
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• 제69권4호
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• pp.361-369
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• 2019

The determination of Paris' law parameters based on crack growth experiments is an important procedure of fatigue life assessment. However, it is a challenging task because it involves various sources of uncertainty. This paper proposes a novel probabilistic method, termed the S-N Paris law (SNPL) method, to quantify the uncertainties underlying the Paris' law parameters, by finding the best estimates of their statistical parameters from the S-N curve data using a Bayesian approach. Through a series of steps, the SNPL method determines the statistical parameters (e.g., mean and standard deviation) of the Paris' law parameters that will maximize the likelihood of observing the given S-N data. Because the SNPL method is based on a Bayesian approach, the prior statistical parameters can be updated when additional S-N test data are available. Thus, information on the Paris' law parameters can be obtained with greater reliability. The proposed method is tested by applying it to S-N curves of 40H steel and 20G steel, and the corresponding analysis results are in good agreement with the experimental observations.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.49-56
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• 1999

This paper present a study on the application of sound pressure and vibration signals to detect the presence of defects in a rolling element bearing using a statistical analysis method. The well established statistical parameters such as the crest factor and the distribution of moments including kurtosis and skewless are utilized in this study. In addition, other statistical parameters derived from the beta distribution function are also used. A comparison study on the performance of the different types of parameter used is also performed. The statistical analysis is used because of its simplicity and quick computation. Under ideal conditions, the statistical method can be used to identify the different types of defect present in the bearing. In addition, the results also reveal that there is no significant advantages in using the beta function parameters when compared to using kurtosis and the crest factor for detecting and identifying defects in rolling element bearings from both sound and vibration signals.

• Journal of Advanced Marine Engineering and Technology
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• 제24권4호
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• pp.405-413
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• 2000

This paper present study on the application of sound pressure and vibration signals to detect the presence of defects in a rolling element bearing using a statistical analysis method. The well established statistical parameters such as the crest factor and the distribution of moments including kurtosis and skew are utilized in this study. In addition, other statistical parameters derived from the beta distribution function are also used. A comparison study on the performance of the different types of parameter used is also performed. The statistical analysis is used because of its simplicity and quick computation. Under ideal conditions, the statistical method can be used to identify the different types of defect present in the bearing. In addition, the results also reveal that there is no significant advantages in using the beta function parameters when compared to using kurtosis and the crest factor for detecting and identifying defects in rolling element bearings from both sound and vibration signals.

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.185-191
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• 1997

Bayesian estimation of multinomial and Poisson parameters under starshped restriction is considered. Most Bayesian estimations in order restricted statistical inference require the high-dimensional integration which is very difficult to evaluate. Monte Carlo integration and Gibbs sampling are among alternative methods. The Bayesian estimation considered in this paper requires only evaluation of incomplete beta functions which are extensively tabulated.

• Journal of the Korean Statistical Society
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• 제32권1호
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• pp.1-10
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• 2003

We consider obtaining graphical summaries of uncertainty in estimates of parameters in nonlinear models. A nonlinear constrained optimization algorithm is developed for likelihood based confidence intervals for the functions of parameters in the model The results are applied to the problem of finding significance levels in nonlinear models.

• Journal of the Korean Statistical Society
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• 제30권2호
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• pp.179-192
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• 2001

When a statistical model has a hierarchical structure such as multilayer perceptrons in neural networks or Gaussian mixture density representation, the model includes distribution with unidentifiable parameters when the structure becomes redundant. Since the exact structure is unknown, we need to carry out statistical estimation or learning of parameters in such a model. From the geometrical point of view, distributions specified by unidentifiable parameters become a singular point in the parameter space. The problem has been remarked in many statistical models, and strange behaviors of the likelihood ratio statistics, when the null hypothesis is at a singular point, have been analyzed so far. The present paper studies asymptotic behaviors of the maximum likelihood estimator and the Bayesian predictive estimator, by using a simple cone model, and show that they are completely different from regular statistical models where the Cramer-Rao paradigm holds. At singularities, the Fisher information metric degenerates, implying that the cramer-Rao paradigm does no more hold, and that he classical model selection theory such as AIC and MDL cannot be applied. This paper is a first step to establish a new theory for analyzing the accuracy of estimation or learning at around singularities.

• 대한기계학회논문집A
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• 제33권12호
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• pp.1449-1454
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• 2009

The performance variation of a multibody system is affected by a variation of various design variables of the system. And the effects of design variable variations on the performance variation must be considered in design of a multibody system. Accordingly, a variation analysis of a multibody system needs to be conducted in design of a multibody system. For a variation analysis of a performance, population mean and variance which are called statistical parameters of design variables are needed. However, an evaluation of statistical parameters of design variables is impossible in many practical cases. Therefore, an estimation of statistical parameters of the performance based on sample mean and variance which are called statistic of design variables is needed. In this paper, the variation analysis method for a multibody system based on design variable samples was proposed. And, using the proposed method, a variation analysis of the vehicle ride comfort based on sample statistic of design variables was conducted.