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바이모달 이산정보에 대한 신뢰성해석 기법 비교

Comparative Study of Reliability Analysis Methods for Discrete Bimodal Information

  • 임우철 (한양대학교 공과대학 미래자동차공학과) ;
  • 장준용 (한양대학교 공과대학 미래자동차공학과) ;
  • 이태희 (한양대학교 공과대학 미래자동차공학과)
  • Lim, Woochul (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.) ;
  • Jang, Junyong (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.) ;
  • Lee, Tae Hee (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.)
  • 투고 : 2012.12.28
  • 심사 : 2013.05.29
  • 발행 : 2013.07.01

초록

응답의 분포는 변수의 분포에 따라 달라진다. 특히 변수의 분포가 두 개 이상의 모드를 가질 때, 대부분 응답의 분포 또한 두 개 이상의 모드를 갖는다. 이런 문제에 대해 기존의 신뢰성해석 기법은 변수를 하나의 모드를 갖는 특정 연속확률분포로 가정하고 신뢰성해석을 수행한다. 하지만 실제 문제에서 변수들은 이산정보이면서 두 개 이상의 모드를 갖는 경우가 많기 때문에 변수의 분포에 대한 가정을 하지 않고 두 개 이상의 모드를 고려한 신뢰성해석을 수행하는 것은 매우 중요하다. 본 연구에서는 두 개 이상의 모드를 갖는 분포를 추정할 수 있는 기법인 아카이케정보척도와 최대엔트로피법칙을 이용하여 신뢰성해석을 수행한다. 수학예제를 통해 두 기법의 특징을 파악하고 몬테카를로 시뮬레이션의 결과와 비교하여 정확도를 검증한다.

The distribution of a response usually depends on the distribution of a variable. When the distribution of a variable has two different modes, the response also follows a distribution with two different modes. In most reliability analysis methods, the number of modes is irrelevant, but not the type of distribution. However, in actual problems, because information is often provided with two or more modes, it is important to estimate the distributions with two or more modes. Recently, some reliability analysis methods have been suggested for bimodal distributions. In this paper, we review some methods such as the Akaike information criterion (AIC) and maximum entropy principle (MEP) and compare them with the Monte Carlo simulation (MCS) using mathematical examples with two different modes.

키워드

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