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Integral analysis and optimization of monitoring and inspection in aging structures: a Bayesian network approach

老化结构监测和检查的整体分析和优化：贝叶斯网络方法

基本信息

批准号：
229790985
负责人：
Professor Dr. Daniel Straub
金额：
--
依托单位：
Professur für Risikoanalyse und Zuverlässigkeit
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2012
资助国家：
德国
起止时间：
2011-12-31 至 2017-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/229790985?language=en
关键词：
Integral analysis optimization monitoring inspection

项目摘要

Significant research resources have been invested into the development of monitoring systems for aging engineering systems. At the same time, only limited efforts have been directed towards developing models and methods to quantitatively assess the information gained with these systems and to quantify the benefit of these monitoring systems. Quantitative models for understanding and assessing the effect of monitoring systems are lacking, in particular when considering combinations of several monitoring systems and inspection techniques. To develop and investigate such models is the goal of this project. These shall enable a better understanding of the impact of monitoring systems on the reliability and shall allow to quantify the Value of Information obtained from these systems. The research will employ physically-based probabilistic models of the deteriorating engineering structures and the monitoring and inspection systems. With few exceptions, this approach to assess the effect of monitoring has not been pursued; a main reason being the difficulties in the modeling and the associated large computational efforts. The recently introduced Bayesian network approach to stochastic modeling of deterioration offers unique possibilities to address these challenges. Initial results for individual structural components are promising. Therefore, this research project aims at developing methods to assess the effect of monitoring combined with inspection on the reliability of deteriorating structures, using physically-based models implemented in a Bayesian network model framework. To ensure the feasibility of the project, it will focus on offshore steel structures subject to fatigue, for which structural and deterioration models are readily available. However, the results of the project will be transferable to other types of structures and deterioration mechanisms. In addition, a major expected outcome of the project is didactic: The models needed for quantitatively assessing the impact of monitoring and inspection in an integral way will not least facilitate a better understanding and communication of which information monitoring systems must provide to be effective. Given the economic importance of deterioration in infrastructure and engineering systems and given the significant amount of resources spent on developing and implementing monitoring systems, the potential impact of this research is considerable.

大量的研究资源已经投入到老化工程系统的监测系统的开发中。与此同时，在开发模型和方法以定量评估这些系统所获得的信息和量化这些监测系统的效益方面所做的努力有限。缺乏理解和评估监测系统效果的定量模型，特别是在考虑几种监测系统和视察技术的组合时。开发和研究这样的模型是本项目的目标。这些应能够更好地理解监控系统对可靠性的影响，并允许量化从这些系统中获得的信息的价值。该研究将采用基于物理的概率模型的恶化工程结构和监测和检查系统。除了少数例外，这种评估监测效果的方法一直没有被采用;主要原因是建模困难和相关的大量计算工作。最近推出的贝叶斯网络方法，恶化的随机建模提供了独特的可能性，以解决这些挑战。单个结构部件的初步结果是有希望的。因此，本研究项目的目的是开发方法，以评估监测与检查相结合的退化结构的可靠性的影响，使用基于物理的模型实施的贝叶斯网络模型框架。为了确保项目的可行性，它将重点关注易受疲劳影响的海上钢结构，其结构和劣化模型随时可用。然而，该项目的结果将转移到其他类型的结构和退化机制。此外，该项目的一个主要预期成果是教学性的：以综合方式定量评估监测和视察影响所需的模型将有助于更好地了解和交流监测系统必须提供哪些信息才能有效。鉴于基础设施和工程系统恶化的经济重要性，并鉴于开发和实施监测系统所花费的大量资源，这项研究的潜在影响是相当大的。