• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.219-226
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• 2004

In this paper, we consider two-components system which the lifetimes have a bivariate Weibull distribution with bivariate random censored data. Here the bivariate censoring times are independent of the lifetimes of the components. We obtain estimators and approximated confidence intervals for the reliability of series system based on likelihood function and relative frequency, respectively. Also we present a numerical study.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.17-33
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• 2001

The characteristics of Weibull distribution are investigated as a function of shape parameter. The statistical estimation methods of the shape parameter and statistical comparison methods of two or more shape parameters are studied. Assuming Weibull distribution, statistical analysis of bending-strength data of alumina titanium carbide ceramic matrix composites machined two different methods are performed.

• Journal of applied mathematics & informatics
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• v.42 no.4
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• pp.819-829
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• 2024

This paper delves into an examination of both non-Bayesian and Bayesian estimation techniques for determining the Topp-leone inverse Weibull distribution parameters based on progressive Type-II censoring. The first approach employs expectation maximization (EM) algorithms to derive maximum likelihood estimates for these variables. Subsequently, Bayesian estimators are obtained by utilizing symmetric and asymmetric loss functions such as Squared error and Linex loss functions. The Markov chain Monte Carlo method is invoked to obtain these Bayesian estimates, solidifying their reliability in this framework.

• Journal of Biomedical Engineering Research
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• v.37 no.1
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• pp.21-30
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• 2016

Weibull distribution with two parameters, shape (k) and scale (s) parameters are used to model the fatigue failure analysis due to periodic vortex shedding of the synovial fluid in knee joints. In order to determine the later parameter, a suitable statistical model is required for velocity distribution of synovial fluid flow. Hence, wide applicability of Weibull distribution in life testing and reliability analysis can be applied to describe the probability distribution of synovial fluid flow velocity. In this work, comparisons of three most widely used methods for estimating Weibull parameters are carried out; i.e. the least square estimation method (LSEM), maximum likelihood estimator (MLE) and the method of moment (MOM), to study fatigue failure of bone joint due to periodic vortex shedding of synovial fluid. The performances of these methods are compared through the analysis of computer generated synovial fluidflow velocity distribution in the physiological range. Significant values for the (k) and (s) parameters are obtained by comparing these methods. The criterions such as root mean square error (RMSE), coefficient of determination ($R^2$), maximum error between the cumulative distribution functions (CDFs) or Kolmogorov-Smirnov (K-S) and the chi square tests are used for the comparison of the suitability of these methods. The results show that maximum likelihood method performs well for most of the cases studied and hence recommended.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.159-168
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• 2008

A special field experiment has been carried out from March 2001 to June 2001 at the Changhowon in Kyunggi to investigate a better methodology for the estimation of dry deposition of pollutions applicable in Korea. In this study, dry deposition plate was used to measure of total and water soluble acidic mass fluxes, and CPRI(Coarse Particle Rotary Impactor), CI(Cascade Impactor) were also used to measure ambient concentrations in various particle size ranges. Sehmel-Hodgson model was used to estimate dry depostion velocity and Weibull probability distribution function was applied to get generalized particle size distribution for the size fractioned concentration data sampled by CPRI and CI. Atmospheric dry deposition fluxes of mass and ionic matters estimated by the various techniques(one-step, multi-step, equi-concentration, subdivision for only the coarse particle range, applying Weibull distribution function, etc.) were compared to flux data sampled by DDP. It was found out that the deposition fluxes estimation methodology calculated by the each particle size range devided by particle size distribution characteristics and the rapidly changed points of deposition velocity using Weibull probability distribution function was the most applicable.

• Journal of Energy Engineering
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• v.14 no.2 s.42
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• pp.123-132
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• 2005

An economic feasibility study is performed for the wind power generation with the examination of the wind speed and its distribution at Daekwanryung at which a wind fm is under construction. In this analysis, the distribution of wind speed is the key issue. The wind distribution which is usually expressed in terms of Weibull distribution with shape factor and scale factor needs to be reexamined to find the proper values of them according to the empirical wind speed data. After this kind of analysis is done, annual power generation of wind is calculated. Due to the lack of cost information, we applied EWEA data instead or the actual information from the site. The result would be of use to determine the 'reference price' of wind power under the current system of 'compensating subsidy for renewable power generation'.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.1
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• pp.33-37
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• 2017

This paper describes the modeling of the failure rate estimation technique for applying the asset management technique to electric power facilities. There are many modeling techniques to estimate the failure rate. In this paper, the characteristics of the normal distribution, exponential distribution, weibull distribution, and piecewise linear functions are discussed. When evaluating reliability, the evaluation may be less meaningful if the sample data is insufficient. Therefore, Weibull distribution and piecewise linear function are adopted as the most suitable functions for estimating the failure rate of power facilities and the resulting failure rate function is derived.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2353-2360
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• 2000

Statistical fatigue properties of metallic materials are increasingly required for reliability design purpose. In this study, static and fatigue tests were conducted and the normal, log-normal, two -parameter Weibull distributions at the 5% significance level are compared using the Kolmogorov-Smirnov goodness-of-fit test. Parameter estimation were compared with experimental results using the maximum likelihood method and least square method. It is found that two-parameter Weibull distribution and maximum likelihood method provide a good fit for static and fatigue life data. Therefore, it is applicable to the static and fatigue life analysis of the spheroidal graphite cast iron. The P-S-N curves were evaluated using log-normal distribution, which showed fatigue life behavior very well.

• International Journal of Reliability and Applications
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• v.10 no.1
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• pp.43-57
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• 2009

In this article, we study the reliability equivalence factor of a series system. The failure rates of the system components are functions of time t. we study two cases of non-constat failure rates (i) weibull distribution (ii) linear increasing failure rate distribution. There are two methods are used to improve the given system. Two types of reliability equivalence factors are discussed. Numerical examples are presented to interpret how one can utilize the obtained results.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.130-139
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• 2017

The crop damage caused by strong wind was predicted using the wind speed data available from Korean Meteorological Administration (KMA). Wind speed data measured at 19 automatic weather stations in 2012 were compared with wind data available from the KMA's digital forecast. Linear regression equations were derived using the maximum value of wind speed measurements for the three-hour period prior to a given hour and the digital forecasts at the three-hour interval. Estimates of daily maximum wind speed were obtained from the regression equation finding the greatest value among the maximum wind speed at the three-hour interval. The estimation error for the daily maximum wind speed was expressed using normal distribution and Weibull distribution probability density function. The daily maximum wind speed was compared with the critical wind speed that could cause crop damage to determine the level of stages for wind damage, e.g., "watch" or "warning." Spatial interpolation of the regression coefficient for the maximum wind speed, the standard deviation of the estimation error at the automated weather stations, the parameters of Weibull distribution was performed. These interpolated values at the four synoptic weather stations including Suncheon, Namwon, Imsil, and Jangsu were used to estimate the daily maximum wind speed in 2012. The wind damage risk was determined using the critical wind speed of 10m/s under the assumption that the fruit of a pear variety Mansamgil would begin to drop at 10 m/s. The results indicated that the Weibull distribution was more effective than the normal distribution for the estimation error probability distribution for assessing wind damage risk.