The management of existing civil infrastructure is challenging due to evolving functional requirements, aging and climate change. Civil infrastructure often has hidden reserve capacity because of conservative approaches used in design and during construction. Information collected through sensor measurements has the potential to improve knowledge of structural behavior, leading to better decisions related to asset management. In this situation, the design of the monitoring system is an important task since it directly affects the quality of the information that is collected. Design of optimal measurement systems depends on the choice of behavior-model parameters to identify using monitoring data and non-parametric uncertainty sources. A model that contains a representation of these parameters as variables is called a model class. Selection of the most appropriate model class is often difficult prior to acquisition of information regarding the structural behavior, and this leads to suboptimal sensor placement. This study presents strategies to efficiently design measurement systems when multiple model classes are plausible. This methodology supports the selection of a sensor configuration that provides significant information gain for each model class using a minimum number of sensors. A full-scale bridge, The Powder Mill Bridge (USA), and an illustrative beam example are used to compare methodologies. A modification of the hierarchical algorithm for sensor placement has led to design of configurations that have fewer sensors than previously proposed strategies without compromising information gain.

由于功能要求不断变化，老化和气候变化，现有民用基础设施的管理面临挑战。由于在设计和施工过程中采用保守的方法，民用基础设施通常具有隐藏的后备能力。通过传感器测量收集的信息有可能提高对结构行为的了解，从而导致与资产管理相关的更好的决策。在这种情况下，监视系统的设计是一项重要任务，因为它直接影响所收集信息的质量。最佳测量系统的设计取决于行为模型参数的选择，以使用监控数据和非参数不确定性源进行识别。包含这些参数作为变量的表示的模型称为模型类。在获取有关结构行为的信息之前，通常很难选择最合适的模型类别，这会导致传感器放置不理想。这项研究提出了在合理的多个模型类别下有效设计测量系统的策略。该方法论支持选择传感器配置，该传感器配置使用最少数量的传感器即可为每个模型类别提供显着的信息增益。一个全尺寸的桥梁，The Powder Mill Bridge（USA）和一个说明性的梁示例用于比较方法。传感器放置的分层算法的修改已导致配置的配置比以前提出的策略具有更少的传感器，而不会损害信息增益。