Reliability Analysis for Industrial Systems with Interdependency

具有相互依赖性的工业系统的可靠性分析

• 批准号: 9908035
• 负责人: Paul Kvam
• 金额: $ 11.07万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-15 至 2002-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9908035&HistoricalAwards=false
• 关键词: Reliability; Analysis; Industrial; Systems; Interdependency

This grant supports research for the development of statistical models for interdependent systems. Specific systems under investigation are those for which the failure of a component within the system affects the reliability of the remaining components. The main goal of this research is to characterize this dependence statistically, using as few assumptions as needed about the component lifetime distributions. Several tools are used to identify the dynamic nature of a system, including reliability estimation, correspondent reliability uncertainty measurement, and statistical tests for interdependence. The load share model, first derived in textile engineering to describe the failure of individual fibers within a bundle, is used as a basis for characterizing component interdependencies. Statistical tests for load sharing rules include a test to see if the load-sharing environment exists, and a test of whether the system stress causes components to fail at an increasing rate as other components fail. Component classes of interest (e.g., those with increasing failure rate) corresponding to specific applications are emphasized in this research project. Applications of the statistical methods are designed for various industries. The research is motivated by problems in the nuclear industry where components in a power plant can suffer decreased reliability if nearby components are degraded or failed. In the field of software reliability, the time until a program bug is found in the software depends on what other bugs exist in the software. Methods derived here can help in the estimation of dynamic software reliability problems like this one. Other examples include materials testing. Metal fatigue, for example, is often characterized by crack growth. In a given specimen, several cracks can exist in the material, but the largest one inherits most of the applied stress, and thus will grow at a faster rate than the other cracks. This provides a platform for extending the load-share model to degradation models in materials engineering.

该补助金支持为相互依赖的系统开发统计模型的研究。 正在调查的特定系统是指系统内某个部件的故障会影响其余部件的可靠性的系统。 本研究的主要目标是统计特性，这种依赖性，使用尽可能少的假设需要的组件寿命分布。几种工具被用来识别系统的动态性质，包括可靠性估计，相应的可靠性不确定性测量，和统计测试的相互依赖性。 负荷分配模型，首先来自纺织工程，以描述一束内的单个纤维的故障，被用作表征组件的相互依赖性的基础。 负载共享规则的统计测试包括一个测试，以查看负载共享环境是否存在，以及一个测试，以确定系统压力是否会导致组件在其他组件失败时以更高的速度失败。 感兴趣的组件类（例如，故障率增加的那些）对应于特定应用的。 统计方法的应用是为各个行业设计的。这项研究的动机是核工业中的问题，如果附近的组件退化或失效，发电厂中的组件可能会降低可靠性。 在软件可靠性领域，直到在软件中发现程序错误的时间取决于软件中存在的其他错误。 这里导出的方法可以帮助在估计动态软件可靠性问题，如这一个。其他例子包括材料测试。 例如，金属疲劳通常以裂纹扩展为特征。 在给定的试样中，材料中可能存在多个裂纹，但最大的一个继承了大部分施加的应力，因此将以比其他裂纹更快的速度增长。这为将载荷分担模型扩展到材料工程中的退化模型提供了一个平台。