Faculty of Engineering, Lusófona University, Campo Grande 376, 1749-024 Lisboa, Portugal.
CERIS, Instituto Superior Técnico, University of Lisbon, Rovisco Pais, 1049-001 Lisboa, Portugal.
Sensors (Basel). 2022 Nov 4;22(21):8483. doi: 10.3390/s22218483.
The broad availability and low cost of smartphones have justified their use for structural health monitoring (SHM) of bridges. This paper presents a smartphone application called App4SHM, as a customized SHM process for damage detection. App4SHM interrogates the phone's internal accelerometer to measure accelerations, estimates the natural frequencies, and compares them with a reference data set through a machine learning algorithm properly trained to detect damage in almost real time. The application is tested on data sets from a laboratory beam structure and two twin post-tensioned concrete bridges. The results show that App4SHM retrieves the natural frequencies with reliable precision and performs accurate damage detection, promising to be a low-cost solution for long-term SHM. It can also be used in the context of scheduled bridge inspections or to assess bridges' condition after catastrophic events.
智能手机的广泛可用性和低成本使其成为桥梁结构健康监测 (SHM) 的理想选择。本文提出了一种名为 App4SHM 的智能手机应用程序，作为一种定制的 SHM 损伤检测方法。App4SHM 通过内部加速度计测量加速度，通过经过适当训练的机器学习算法估算自然频率，并将其与参考数据集进行比较，从而实现几乎实时的损伤检测。该应用程序在实验室梁结构和两座双后张预应力混凝土桥梁的数据集上进行了测试。结果表明，App4SHM 可以可靠地精确地获取自然频率，并进行准确的损伤检测，有望成为一种低成本的长期 SHM 解决方案。它还可以用于计划中的桥梁检查或评估灾难性事件后桥梁的状况。
