Optimization of Sensor Network for Mode Shape Identification of a Reinforced Concrete Building

The design of a vibration-based monitoring system for civil structures requires not only the deployment of accelerometers but also the careful selection of their number and locations to ensure reliable identification of the structural dynamic properties. To this end, an optimization of sensor network (OSN) framework was formulated in previous works, with the objective of accurately identifying modal frequencies. In this paper, a modified framework is proposed and assessed. The objective is the accurate reconstruction of mode shapes, measured by the modal assurance criterion, which replaces modal frequencies as the metric for evaluating the effectiveness of the sensor network design. The proposed framework involves three established sensor placement strategies, namely, the modal kinetic energy (MKE) method, the effective independence (EFI) method, and the information entropy (IE) method. They are compared by applying each method separately within the OSN framework. A retrofitted, four-story reinforced concrete building exhibiting spatial irregularity is considered as case study structure. Comparative results demonstrate that both EFI and IE strategies can achieve high accuracy in mode shape reconstruction using a sparse sensor network, while the MKE approach requires a larger number of sensors to reach a similar result. All analyses are based on numerical simulations and offer a useful basis for the design of actual dynamic tests and experimental validations.