In this paper, system identification is coupled with optimization-based damage detection to provide accurate localization of cracks in thin plates, under dynamic loading. Detection relies on exploitation of strain measurements from a network of sensors deployed onto the plate structure. The data-driven approach is based on the detection of discrepancies between healthy and damaged modal strain curvatures, while the model-based method exploits an enriched finite element method coupled to an optimization algorithm to minimize discrepancies between the measured and modelled response of the structure. It is demonstrated, through a series of numerical experiments, that the fusion of data-driven and model-based approaches can be beneficial both in terms of accuracy and localization, as well as in terms of computational requirements.

在本文中，系统识别与基于优化的损伤检测相结合，可以在动态载荷下准确地确定薄板上裂纹的位置。检测依赖于来自部署在板结构上的传感器网络的应变测量结果。数据驱动的方法基于对健康模态曲率曲率和受损模态曲率曲率之间差异的检测，而基于模型的方法则利用了结合优化算法的丰富有限元方法，以使结构的实测响应与模型响应之间的差异最小化。通过一系列数值实验证明，将数据驱动方法与基于模型的方法相融合可以在准确性和本地化方面以及在计算需求方面均是有益的。