Widespread monitoring of bridges is yet rarely employed at a territorial level due to the high costs of monitoring systems. However, the aging of civil infrastructures, combined with the growing traffic demand, poses the need for a simple and automatic tool that helps emergency management. In this paper, an integrated algorithm for the identification of dynamic and dense quasi-static structural features exploiting moving vehicles is proposed. Filtering raw acceleration structural responses, triggered by passing vehicles, enables the identification of modal parameters and curvature influence lines. The procedure can be implemented efficiently as its main computational core consists of convolutions. The definition of a curvature-based damage index leads to accurate localization and quantification of structural anomalies using few sensors. The proposed procedure is tested on three viaducts of the Italian A24 motorway. Moreover, a numerical model is studied to evaluate the potentialities of the strategy for damage localization.

由于监视系统的高昂成本，在区域级别上很少采用对桥梁的广泛监视。但是，民用基础设施的老化以及不断增长的交通需求构成了对一种简单，自动的工具的需求，该工具可用于紧急情况管理。提出了一种基于运动车辆的动态和密集准静态结构特征识别的集成算法。过滤由过往车辆触发的原始​​加速度结构响应，可以识别模态参数和曲率影响线。该程序的主要计算核心由卷积组成，因此可以高效地实现该程序。基于曲率的损伤指数的定义导致使用很少的传感器对结构异常进行准确的定位和量化。拟议的程序在意大利A24高速公路的三个高架桥上进行了测试。此外，研究了一个数值模型来评估损伤定位策略的潜力。