• Title/Summary/Keyword: Weibull probability distribution

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고장 보고율을 이용한 현장 수명자료 분포의 모수추정

  • Park, Tae-Ung;Kim, Yeong-Bok;Lee, Chang-Hun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.678-685
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    • 2005
  • Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used to estimate parameters of the lifetime distribution when failure reporting probability is known. Secondly, Expectation and Maximization(EM) algorithm is used to estimate the failure reporting probability and parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

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Mathematical modeling of wind power estimation using multiple parameter Weibull distribution

  • Chalamcharla, Seshaiah C.V.;Doraiswamy, Indhumathy D.
    • Wind and Structures
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    • v.23 no.4
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    • pp.351-366
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    • 2016
  • Nowadays, wind energy is the most rapidly developing technology and energy source and it is reusable. Due to its cleanliness and reusability, there have been rapid developments made on transferring the wind energy systems to electric energy systems. Converting the wind energy to electrical energy can be done only with the wind turbines. So installing a wind turbine depends on the wind speed at that location. The expected wind power can be estimated using a perfect probability distribution. In this paper Weibull and Weibull distribution with multiple parameters has been used in deriving the mathematical expression for estimating the wind power. Statistically the parameters of Weibull and Weibull distribution are estimated using the maximum likelihood techniques. We derive a probability distribution for the power output of a wind turbine with given rated wind speeds for the regions where the wind speed histograms present a bimodal pdf and compute the first order moment of this distribution.

Estimating Parameters of Field Lifetime Data Distribution Using the Failure Reporting Probability (고장 보고율을 이용한 현장 수명자료 분포의 모수추정)

  • Kim, Young Bok;Lie, Chang Hoon
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.1
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    • pp.52-60
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    • 2007
  • Estimating parameters of the lifetime distribution is investigated when field failure data are not completelyreported. To take into account the reality and the accuracy of the estimates in such a case, the failure reportingprobability is incorporated in estimating parameters, Firstly, method of maximum likelihood estimate (MLE) isused to estimate parameters of the lifetime distribution when failure reporting probability is known, Secondly,Expectation and Maximization (EM) algorithm is used to estimate the failure reporting probability and parame-ters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both cases,procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simula-tion results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

Estimation of sewer deterioration by Weibull distribution function (와이블 분포함수를 이용한 하수관로 노후도 추정)

  • Kang, Byongjun;Yoo, Soonyu;Park, Kyoohong
    • Journal of Korean Society of Water and Wastewater
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    • v.34 no.4
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    • pp.251-258
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    • 2020
  • Sewer deterioration models are needed to forecast the remaining life expectancy of sewer networks by assessing their conditions. In this study, the serious defect (or condition state 3) occurrence probability, at which sewer rehabilitation program should be implemented, was evaluated using four probability distribution functions such as normal, lognormal, exponential, and Weibull distribution. A sample of 252 km of CCTV-inspected sewer pipe data in city Z was collected in the first place. Then the effective data (284 sewer sections of 8.15 km) with reliable information were extracted and classified into 3 groups considering the sub-catchment area, sewer material, and sewer pipe size. Anderson-Darling test was conducted to select the most fitted probability distribution of sewer defect occurrence as Weibull distribution. The shape parameters (β) and scale parameters (η) of Weibull distribution were estimated from the data set of 3 classified groups, including standard errors, 95% confidence intervals, and log-likelihood values. The plot of probability density function and cumulative distribution function were obtained using the estimated parameter values, which could be used to indicate the quantitative level of risk on occurrence of CS3. It was estimated that sewer data group 1, group 2, and group 3 has CS3 occurrence probability exceeding 50% at 13th-year, 11th-year, and 16th-year after the installation, respectively. For every data groups, the time exceeding the CS3 occurrence probability of 90% was also predicted to be 27th- to 30th-year after the installation.

Approximated Modeling Technique of Weibull Distributed Radar Clutter (Weibull 분포 레이더 클러터의 근사적 모델링 기법)

  • Nam, Chang-Ho;Ra, Sung-Woong
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.23 no.7
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    • pp.822-830
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    • 2012
  • Clutters are all unwanted radar returns to affect on detection of targets. Radar clutter is characterized by amplitude distributions, spectrum, etc. Clutter is modelled with considering these kinds of characteristics. In this paper, a Weibull distribution function approximated by uniform distribution function is suggested. Weibull distribution function is used to model the various clutters. This paper shows that the data generated by the approximated solution of Weibull distribution function satisfy the Weibull probability density function. This paper shows that the data generation time of approximated Weibull distribution function solution is reduced by 20 % compared with the generation time of original Weibull probability density function.

Failure Rate Calculation using the Mixture Weibull Distribution (혼합 와이블 분포를 이용한 고장률 산출 기법에 관한 연구)

  • Chai, Hui-seok;Shin, Joong-woo;Lim, Tae-jin;Kim, Jae-chul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.3
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    • pp.500-506
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    • 2017
  • In 2014, ISO 55000s has been enacted and the power plant asset management is becoming a hot issue for all over the world. The asset management system is being developed as a combination of CBM(Condition Based Maintenance) and RCM(Reliability Centered Maintenance). Therefore, the research on the calculation of the failure rate which is the most basic index of RCM is actively carried out. The failure rate calculation has been going on for a long time, and the most widely used probability distribution is the Weibull distribution. In the Weibull distribution, the failure rate function is determined in three types according to the value of the shape parameter. However, the Weibull distribution has a limitation that it is difficult to apply it when the trend of failure rate changes-such as bathtub curves. In this paper, the failure rate is calculated using the mixture Weibull distribution which can appropriately express the change of the shape of the failure rate. Based on these results, we propose the necessity and validity of applying mixture Weibull distribution.

Analysis of Probability Distribution of Muzzle Velocity for Chrome Plated Barrel (크롬도금 포열의 포구속도 확률분포 특성 분석)

  • Kim, Jaekab;Kim, Jaehoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.24 no.4
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    • pp.401-407
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    • 2021
  • To confirm the change of muzzle velocity and the most suitable probability distribution model of the 155 mm K9 howitzer barrel with chrome plating and changed rifling. Using a statistical program, the muzzle velocity were plotted on a normal distribution, a 2-parameter and 3-parameter Weibull distribution on a probability paper. Also, statistical parameters were estimated and muzzle velocity fitness test and probability of K676 charge were plotted. In both the chrome-plated with standard rifling and changed rifling for K9 barrel, the 2-parameter and 3-parameter Weibull distribution were skewed to the left compared to the normal distribution. It was confirmed that the muzzle velocity of the K9 barrel with chromium-plated is suitable for the normal distribution and 3-parameter Weibull distribution model.

Fracture Probability Properties of Torsion Fatigue of STS304 Steel (STS304강의 비틀림 피로파괴 확률특성)

  • Park, Dae-Hyun;Jeong, Soon-Ug
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.201-206
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    • 2003
  • This study is test for STS304 specimen using bending and torsion state. Rounded specimen and notched specimen including fracture surface investigation was comparatively experimented, fatigue life according to degree of surface finishing was examined. Fatigue fracture probability of notched canilever specimens were predicted by P-S-N curve, median rank and Weibull distribution. And at the relation with the rotational speed and stress, the fatigue life of the test specimen was higher at high speed than low speed If summarize STS304 torsion result of fatigue test, is as following. Fatigue life prediction was available by Weibull statistics distribution, and 50% breakdown probability correlation equation was appeared as following.

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Reliability Estimation of Buried Gas Pipelines in terms of Various Types of Random Variable Distribution

  • Lee Ouk Sub;Kim Dong Hyeok
    • Journal of Mechanical Science and Technology
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    • v.19 no.6
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    • pp.1280-1289
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    • 2005
  • This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

Evaluation of Insulating Reliability in Epoxy Composites using Dielectric Breakdown Data (절연 파괴 데이터를 이용한 에폭시 복합체의 절연 신뢰도 평가)

  • Park, Geon-Ho
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2005.05b
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    • pp.114-118
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    • 2005
  • In this study, the DC dielectric breakdown of epoxy composites used for molding material was experimented and then its data were simulated by Weibull distribution equation. From the analysis of Weibull distribution, it was confirmed that as the allowed breakdown probability was given by 0.1[%], the applied field value needed to be under 21.5[kV/mm].

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