统计分析K/N (G) 系统的依赖性竞争性故障组件,受贝尔-胡加德·科普拉的影响,以及逐渐混合的审查数据
Yanjie Shi1, Zaizai Yan1, Xiuyun Peng1
1Science College, Inner Mongolia University of Technology, Hohhot 010051, PR China.
Heliyon
|February 5, 2025
概括
这项研究引入了一种新的统计方法,用于使用Gumbel-Hougard Copula分析具有依赖失效的复杂系统. 与传统方法相比,建议的贝叶斯方法提供了更好的可靠性估计.
科学领域:
- 工程 工程师 工程师 工程师
- 统计 统计 统计 统计
- 可靠性工程可靠性工程
背景情况:
- 复杂的系统往往包括多个组件与依赖的故障机制.
- 建模这些依赖关系对于准确的系统可靠性评估至关重要.
- 甘贝尔 - 霍加德 (GH) 偶数是建模这种依赖关系的合适工具.
研究的目的:
- 为具有依赖性故障机制的系统开发逐步混合的审查测试.
- 用边际推理 (IFM) 和贝叶斯方法估计模型参数和系统可靠性.
- 将拟议的贝叶斯方法与传统的IFM方法的性能进行比较.
主要方法:
- 为具有依赖故障机制的系统开发逐步混合的审查测试.
- 应用边际推理 (IFM) 方法进行参数和可靠性估计.
- 使用大都市-哈斯廷斯 (MH) 和吉布斯采样实施贝叶斯估计方法.
- 在非信息先验下,证明条件后密度对形状参数的日志.
主要成果:
- 贝叶斯估计方法,利用MH和吉布斯采样,已成功实施.
- 边缘韦布尔分布的形状参数的条件后密度被证明是日志.
- 蒙特卡洛模拟表明,贝叶斯的方法优于传统的IFM方法.
- 开发的模型和方法通过对现实数据的应用来验证.
结论:
- 建议的贝叶斯方法为具有依赖失败的复杂系统提供了更准确和可靠的估计.
- 该研究成功地应用了先进的统计技术来增强系统可靠性分析.
- 这些发现对复杂的工程系统的维护和风险评估具有实际意义.
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