earticle

논문검색

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree

초록

영어

T Bayesian network methodology taking place of fault tree analysis used for reliability assessment has gotten lots of attention in recent years. On basis of the current Bayesian network method used for calculating structural importance degree, a new Bayesian network method is raised. This new method can avoid repeat modification of the parameters in the conditional probability tables, and hence the intermediate results computed during inference process can be shared to decrease calculating complexity. The new method is proved to be correct in a mathematic way and a corresponding algorithm named SID_Jointree for realizing this new method is designed, which guarantees the new method can be realized in computer. Finally, the correctness and efficiency of the new method is validated by using two fault tree cases.

목차

Abstract
 1. Introduction
 2. Bayesian Network
  2.1. Definition of Bayesian Network
  2.2. Inference in Bayesian Networks
  2.3. Mapping Fault Trees into Bayesian Networks
 3. Methods for Solving Structural Importance Degree
  3.1. FTA Method
  3.2. Bayesian Network Method
 4. Case Studies
  4.1. A Simple Fault Tree
  4.2. A Fault Tree for a Power Distribution System
 5. Conclusions
 References

저자정보

  • Wang Yao School of Aeronautics, Northwestern Polytechnical University, Xi’an, 710072 PR China)
  • Sun Qin School of Aeronautics, Northwestern Polytechnical University, Xi’an, 710072 PR China)

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.