• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.05a
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• pp.53-62
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• 2002

Condition monitoring plays a vital role since it sustains reliable operation of industrial plants and machinery in the pursuit of economic whole life operation. In order to achieve this goal, it is needed to monitor various parameters of mechanical system such as vibration, wear, temperature and etc., and finally to diagnosis the root causes of any possible abnormal machine condition. In this work, a machine failure caused by mechanical looseness was experimentally simulated and on-line measurement of the vibration, wear and temperature were simultaneously measured. For the quantitative analyses of machine wear, several statistical parameters of the wear particle size distribution were obtained through the center moment method of the Weibull distribution function, and they were compared to vibrational characteristics. Results showed that the wear and vibrational characteristics did not reveal a strong correlation each other in a loosely supported proceeding bearing.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.7 s.238
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• pp.921-929
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• 2005

This paper presents an accelerated life test for burnout of tungsten filament of incandescent lamp. From failure analyses of field samples, it is shown that their root causes are local heating or hot spots in the filament caused by tungsten evaporation and wire sag. Finite element analysis is performed to evaluate the effect of vibration and impact for burnout, but any points of stress concentration or structural weakness are not found in the sample. To estimate the burnout life of lamp, an accelerated life test is planned by using quality function deployment and fractional factorial design, where voltage, vibration, and temperature are selected as accelerating variables. We assumed that Weibull lifetime distribution and a generalized linear model of life-stress relationship hold through goodness of fit test and test for common shape parameter of the distribution. Using accelerated life testing software, we estimated the common shape parameter of Weibull distribution, life-stress relationship, and accelerating factor.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.9
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• pp.628-633
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• 1999

Degradation diagnosis of XLPE insulated URD cables was accomplished through out new method, which was to be analyzed by non-electrical experiments and synthesized by degradation points. To supplement this method, It was also carried out using several electrical analyses. Tan$\delta$ had commonly a different tendency by means oftemperature and frequency and also appeared higher at the outer part rather than innerpart of insulator. PD-q increased generally in proportion to the applied voltage andshowed regular patterns in relation to the thickness of insulator. Breakdown voltageswere measured and breakdown lifetimes were predicted appling for Weibull distribution function. As a result, breakdown lifetime in failure cables was shorter up to$\fraction one-third$ times than that in general cables. It was very available to estimate cable degradation using above method, but it needs further study on XLPE insulated URD cables in order to improve reliability.

• Composites Research
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• v.16 no.6
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• pp.1-9
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• 2003

In this paper, probabilistic failure analysis based on Weibull distribution function is proposed to predict the fiber strength of composite pressure vessel. And, experimental tests were performed using fiber strand specimens, unidirectional laminate specimens and composite pressure vessels to confirm the volumetric size effect on the fiber strength. As an analytical method, the Weibull weakest link model and the sequential multi-step failure model are considered and mutually compared. The volumetric size effect shows the clearly observed tendency towards fiber strength degradation with increasing stressed volume. Good agreement of fiber strength distribution was shown between test data and predicted results for unidirectional laminate and hoop ply in pressure vessel. The site effect on fiber strength depends on material and processing factors, the reduction of fiber strength due to the stressed volume shows different values according to the variation of material and processing conditions.

• Journal of Power System Engineering
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• v.4 no.2
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• pp.40-45
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• 2000

Some engineering materials are often known to have considerable spatial variation in their resisting strength and other properties. The objective of this study is to investigate the averaging effect and the applicability of extremal statistic for the statistical size effect. In the present study, it is assumed that the material property is a stationary random process in space. The theoretical autocorrelation function of the material strength are discussed for several correlation lengths. And, in order to investigate the statistical size effect, the material properties was simulated by using the non-Gaussian random process method. The material properties were plotted on the Weibull probability papers. The main results are summarized as follows: The autocorrelation function of the material properties are almost independent of the averaging length. The variance decreases with increasing the averaging length. As correlation length is smaller, the slope is larger. And also, it was found that Weibull statistics based on the weakest-link model could not explain the spatial variation of material properties with respect to the size effect satisfactory.

• Journal of Korean Society of Forest Science
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• v.101 no.4
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• pp.599-605
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• 2012

The purpose of this study is to estimate diameter distribution, volume per hectare, and carbon stock for Quercus variabilis stand. 354 Quercus variabilis stands were selected on the basis of age and structure, the data and samples for these stands are collected. For the prediction of diameter distribution, Weibull model was applied and for the estimation of the parameters, a simplified method-of-moments was applied. To verify the accuracy of estimates, models were developed using 80% of the total data and validation was done on the remaining 20%. For the verification of the model, the fitness index, the root mean square error, and Kolmogorov-Smirnov statistics were used. The fitness index of the site index, height, and volume equation estimated from verification procedure were 0.967, 0.727, and 0.988 respectively and the root mean square error were 2.763, 1.817, and 0.007 respectively. The Kolmogorov-Smirnov test applied to Weibull function resulted in 75%. From the models developed in this research, the estimated volume and above-ground carbon stock were derived as $188.69m^3/ha$, 90.30 tC/ha when site index and stem number of 50-years-old Quercus variabilis stand show 14 and 697 respectively. The results obtained from this study may provide useful information about the growth of broad-leaf species and prediction of carbon stock for Quercus variabilis stand.

• Journal of the Chungcheong Mathematical Society
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• v.26 no.3
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• pp.441-451
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• 2013

In this paper, we derive recurrence relations for moments of lower generalized order statistics within a class of doubly truncated distributions. Inverse Weibull, exponentiated Weibull, power function, exponentiated Pareto, exponentiated gamma, generalized exponential, exponentiated log-logistic, generalized inverse Weibull, extended type I generalized logistic, logistic and Gumble distributions are given as illustrative examples. Further, recurrence relations for moments of order statistics and lower record values are obtained as special cases of the lower generalized order statistics, also two theorems for characterizing the general form of distribution based on single moments of lower generalized order statistics are given.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.476-484
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• 2006

The failure prediction and preventive maintenance for the equipment of nuclear power plant area using reliability-centered maintenance have been grown. On the other hand, the maintenance for power distribution system consists of time-based maintenance mainly. In this paper, the new maintenance algorithms for power distribution system are developed considering reliability indices. First of all, Time-varying failure rates are extracted from data accumulated at KEPCO using exponential distribution function and weibull distribution function. Next, based on the extracted failure rate, reliability for real power distribution system is evaluated for applying the effective maintenance algorithm which is the analytic method deciding the maintenance point of time and searching the feeder affecting the specific customer. Also the algorithm deciding the maintenance priority order are presented based on sensitivity analysis and equipment investment plan are analyzed through the presented algorithm at real power distribution system.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.199-207
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• 2001

The failure rate functions between successive failures are of concatenated form. We allow the parameters of failure rate function change after a certain failure and its fixing. We confine out attention to a model wherein the interfailure times are described by its failure rate function. We suggest an adaptive failure rate function with a change-point under the assumption that interfailure times are record value statistics from a Weibull distribution. The proposed model will be applied through a practical example of software failure data.