Department of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University of Rome, Via Ariosto 25, 00185, Rome, Italy.
Sci Rep. 2023 Mar 8;13(1):3916. doi: 10.1038/s41598-023-30683-z.
The monitoring of the structural health of infrastructures is a very important topic in structural engineering, but unfortunately, there are few established techniques that are applicable in a wide range of situations. In this paper, we present a new method that adapts image analysis tools and methodologies, taken from the field of computer vision, and applies them to the monitoring signals of a railway bridge. We show that our method correctly identifies changes in the structural health of the bridge with very high precision, thus providing a better, simpler, and more general alternative to current methodologies used in the field.
基础设施的结构健康监测是结构工程中一个非常重要的课题，但不幸的是，目前可用的技术很少能够适用于广泛的情况。在本文中，我们提出了一种新的方法，该方法采用了图像处理分析工具和方法，这些工具和方法来自计算机视觉领域，并将其应用于铁路桥梁的监测信号中。我们表明，我们的方法能够非常精确地识别桥梁结构健康状况的变化，从而为该领域当前使用的方法提供了更好、更简单、更通用的替代方案。
