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Assessing the Value of Information for long-term structural health monitoring

机译：评估信息的价值，以进行长期结构健康监测

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In the field of Structural Health Monitoring, tests and sensing systems are intended as tools providing diagnoses, which allow the operator of the facility to develop an efficient maintenance plan or to require extraordinary measures on a structure. The effectiveness of these systems depends directly on their capability to guide towards the most optimal decision for the prevailing circumstances, avoiding mistakes and wastes of resources. Though this is well known, most studies only address the accuracy of the information gained from sensors without discussing economic criteria. Other studies evaluate these criteria separately, with only marginal or heuristic connection with the outcomes of the monitoring system. The concept of "Value of Information" (Vol) provides a rational basis to rank measuring systems according to a utility-based metric, which fully includes the decision-making process affected by the monitoring campaign. This framework allows, for example, an explicit assessment of the economical justifiability of adopting a sensor depending on its precision. In this paper we outline the framework for assessing the Vol, as applicable to the ranking of competitive measuring systems. We present the basic concepts involved, highlight issues related to monitoring of civil structures, address the problem of non-linearity of the cost-to-utility mapping, and introduce an approximate Monte Carlo approach suitable for the implementation of time-consuming predictive models.
机译：在结构健康监测领域，测试和传感系统旨在作为提供诊断的工具，使设施的操作员可以制定有效的维护计划或对结构采取特殊措施。这些系统的有效性直接取决于它们针对当前情况做出最佳决策的能力，从而避免错误和资源浪费。尽管这是众所周知的，但大多数研究仅针对从传感器获取的信息的准确性，而没有讨论经济标准。其他研究则单独评估这些标准，仅与监测系统的结果之间存在边际或启发式联系。 “信息价值”（Vol）的概念为根据基于效用的度量对测量系统进行排名提供了合理的基础，该度量完全包括受监视活动影响的决策过程。例如，此框架允许根据传感器的精度对采用传感器的经济合理性进行明确评估。在本文中，我们概述了评估Vol的框架，适用于竞争性测量系统的排名。我们介绍了涉及的基本概念，重点介绍了与监视土木结构有关的问题，解决了成本-效用图的非线性问题，并介绍了适合于实施耗时的预测模型的近似蒙特卡洛方法。

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