• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1758-1764
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• 2012

A large number of wire rope has been used in various inderstiries as Cranes and Elevators from expanding the scale of the industrial market. But now, the management of wire rope is used as manually operated by rope replacement from over time or after the accident.It is caused to major accidents as well as economic losses and personal injury. Therefore its time to need periodic fault diagnosis of wire rope or supply of real-time monitoring system. Currently, there are several methods has been reported for fault diagnosis method of the wire rope, to find out the feature point from extracting method is becoming more common compared to time wave and model-based system. This method has implemented a deterministic modeling like the observer and neural network through considering the state of the system as a deterministic signal. However, the out-put of real system has probability characteristics, and if it is used as a current method on this system, the performance will be decreased at the real time. And if the random noise is occurred from unstable measure/experiment environment in wire rope system, diagnostic criterion becomes unclear and accuracy of diagnosis becomes blurred. Thus, more sophisticated techniques are required rather than deterministic fault diagnosis algorithm. In this paper, we developed the fault diagnosis of the wire rope using probability density estimation techniques algorithm. At first, The steady-state wire rope fault signal detection is defined as the probability model through probability distribution estimate. Wire rope defects signal is detected by a hall sensor in real-time, it is estimated by proposed probability estimation algorithm. we judge whether wire rope has defection or not using the error value from comparing two probability distribution.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.48-57
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• 1999

Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.169-184
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• 2003

In the IS-95 packet service system, the radio channels are generally classified into the dedicated and the common traffic channels. In this paper, a common traffic channel access method is proposed for the COMA packet service system to enhance the radio resource utilization while guaranteeing QoS to the users. The proposed method is based on the permission probability for the common traffic channel user. To derive permission probability, optimization models are developed for two different QoS constraints. Approximation methods are also developed.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.471-483
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• 1998

The influence of observations on the misclassification probability in multiple discriminant analysis under the equal covariance assumption is investigated by the local influence method. Under an appropriate perturbation we can get information about influential observations and outliers by studying the curvatures and the associated direction vectors of the perturbation-formed surface of the misclassification probability. We show that the influence function method gives essentially the same information as the direction vector of the maximum slope. An illustrative example is given for the effectiveness of the local influence method.

• Korean Journal of Metals and Materials
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• v.46 no.9
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• pp.554-562
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• 2008

The distribution and prediction interval for the misorientation angle of grain boundary at which $Cr_2N$ was precipitated during heating at $900^{\circ}C$ for $10^4$ sec were newly estimated, and followed by the estimation of mathematical and median rank methods. The probability density function of the misorientation angle can be estimated by a statistical analysis. And then the ($1-{\alpha}$)100% prediction interval of misorientation angle obtained by the estimated probability density function. If the estimated probability density function was symmetric then a prediction interval for the misorientation angle could be derived by the estimated probability density function. In the case of non-symmetric probability density function, the prediction interval could be obtained from the cumulative distribution function of the estimated probability density function. In this paper, 95, 99 and 99.73% prediction interval obtained by probability density function method and cumulative distribution function method and compared with the former results by median rank regression or mathematical method.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1269-1286
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• 2017

This paper presents a newly developed resonance self-shielding method based on Tone's method in $APOLLO3^{(R)}$ for fast and thermal reactor calculations. The new method is based on simplified models, the narrow resonance approximation for the slowing down source and Tone's approximation for group collision probability matrix. It utilizes mathematical probability tables as quadrature formulas in calculating effective cross-sections. Numerical results for the ZPPR drawer calculations in 1,968 groups show that, in the case of the double-column fuel drawer, Tone's method gives equivalent precision to the subgroup method while markedly reducing the total number of collision probability matrix calculations and hence the central processing unit time. In the case of a single-column fuel drawer with the presence of a uranium metal material, Tone's method obtains less precise results than those of the subgroup method due to less precise heterogeneous-homogeneous equivalence. The same options are also applied to PWR UOX, MOX, and Gd cells using the SHEM 361-group library, with the objective of analyzing whether this energy mesh might be suitable for the application of this methodology to thermal systems. The numerical results show that comparable precision is reached with both Tone's and the subgroup methods, with the satisfactory representation of intrapellet spatial effects.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.39-46
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• 2012

The objectives of this study is intended to analyze stresses using the boundary element method and probability analysis for agricultural structure. Loads and material properties are an important factor when analyzing the structure. Until now, designing structure, loads and material properties are applied deterministic value. However, load and material properties involve uncertainties due to those change probabilistic and deterministic methods could not consider uncertainties. To solve these problems, the reliability analysis based on probability properties scheme was developed. Reliability analysis is easy to approach to analysis frame structure, however it has limitation when solving plane stress strain problems a kind of agricultural structures. The BEM (Boundary Element Method) is able to analysis plane strain problems by boundary conditions. Thus, this study applied boundary element method to analysis plane strain problem, load and material properties as a probabilistic value to calculate the analytical model using Monte Carlo simulations were developed.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.321-327
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• 2011

Bootstrap methods is the computer-based resampling method that estimates the standard errors and confidence intervals of summary statistics using the plug-in principle for assessing the accuracy or uncertainty of statistical estimates, and the BCa method among the Bootstrap methods is known much superior to other Bootstrap methods in respect of the standards of statistical validation. Therefore this study suggests the method of the representation and treatment of uncertainty in flood risk assessment and water resources planning from the construction and application of rainfall frequency analysis model considersing the uncertainty based on the nonparametric BCa method among the Bootstrap methods for the assessement of the estimation of probability rainfall and the effect of uncertainty considering the uncertainty of the parameter estimation of probability in the rainfall frequency analysis that is the most fundamental in flood risk assessement and water resources planning.

• Architectural research
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• v.3 no.1
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• pp.71-80
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• 2001

It is quite difficult to calculate the collapse probability of a system such as statically indeterminate structure that has many possible modes or paths to complete failure and the problem has remained essentially unsolved. A structure is synthesized by several components or elements and its capacity to resist the given loads is a function of the capacity of the individual element. Thus it is reasonable to assess the probability of failure of the system based upon those of its elements. This paper proposes an efficient technique to directly assess the reliability of a complex structural system from the reliabilities of its components or elements. The theory for the calculation of the probability of a structural system is presented. The target requirements of the method and the fundamental assumptions governing the method are clearly stated. A portal frame and two trusses are selected to demonstrate the efficiency of the method by comparing the results obtained from the proposed method to those from the existing methods in the literature.