• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Applications of Bayesian networks in complex system reliability.
【24h】

Applications of Bayesian networks in complex system reliability.

机译：贝叶斯网络在复杂系统可靠性中的应用。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Estimating system reliability is an important and challenging problem for system engineers. System reliability may be defined as the probability that a system will perform its intended functions during a specified period of time under stated conditions. Current approaches for reliability analysis use specialized networks, each of which is designed for a specific system. This assumption of specialized networks presupposes that the BN is built by an expert who has "adequate" knowledge about the behavior of the system. However, finding a system expert may not be possible at times for every system under consideration. The number of system experts is limited and finding one is usually difficult and costly.;This dissertation introduces a methodology for reliability estimation, sensitivity analysis, and fault diagnosis in complex systems. A complex system is any system with a large number of interacting components and typically includes various subsystems. First, to solve the problem of reliability estimation in complex systems, the methodology introduced in this dissertation uses Bayesian networks (BN), which is a probabilistic approach that is used to model and predict the behavior of a system based on observed stochastic events. Second, this dissertation introduces a holistic method for automated construction of the BN model for estimating reliability in complex systems. Third, as suggested by the previous studies, this dissertation provides a new algorithm for sensitivity analysis of complex systems using BN. Fourth, this dissertation also introduces an algorithm for efficient fault diagnosis in complex systems using BN with heuristics to reduce the time to diagnose the unprecedented changes in the complex system reliability.;In addition to these, this dissertation presents a case study on estimating grid system reliability with the use of BN. Due to the size and complexity of grid systems, traditional methods for system reliability estimation cannot be used. In this case study, the methodology for reliability estimation is applied to the grid systems and effectively used in estimating grid systems' reliability. In order to validate the results and demonstrate the performance of these new methodologies, this dissertation presents a real-life application.
机译：对于系统工程师来说，估计系统可靠性是一个重要且具有挑战性的问题。系统可靠性可以定义为系统在规定条件下在指定时间段内执行其预期功能的概率。当前的可靠性分析方法使用专门的网络，每种网络都是为特定系统设计的。专门网络的这种假设前提是BN是由对系统行为具有“足够”知识的专家构建的。但是，有时可能无法为正在考虑的每个系统寻找系统专家。系统专家的数量有限，通常很难找到专家，而且成本很高。;本文介绍了一种用于复杂系统可靠性评估，灵敏度分析和故障诊断的方法。复杂的系统是具有大量交互组件的任何系统，通常包括各种子系统。首先，为了解决复杂系统中的可靠性估计问题，本文引入的方法是使用贝叶斯网络（BN），这是一种概率方法，用于基于观察到的随机事件对系统的行为进行建模和预测。其次，本文介绍了一种用于自动构建BN模型的整体方法，用于估计复杂系统中的可靠性。第三，如先前的研究所建议的那样，本文为使用BN的复杂系统的灵敏度分析提供了一种新的算法。第四，本文还引入了一种启发式算法，利用BN算法在复杂系统中进行有效的故障诊断，以减少诊断复杂系统可靠性空前变化的时间。此外，本文还提供了一个估计网格系统的案例研究。使用BN的可靠性。由于网格系统的大小和复杂性，无法使用传统的系统可靠性估计方法。在本案例研究中，可靠性估计的方法应用于网格系统，并有效地用于估计网格系统的可靠性。为了验证结果并证明这些新方法的性能，本文提出了一种实际应用。

著录项

  • 作者

    Doguc, Ozge.;

  • 作者单位

    Stevens Institute of Technology.;

  • 授予单位 Stevens Institute of Technology.;
  • 学科 Engineering System Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 410 p.
  • 总页数 410
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号