人工智能增强的物联网系统用于评估在驱动条件下的桥梁偏移
Leonardo Iacussi1, Paolo Chiariotti1, Alfredo Cigada1
1Department of Mechanical Engineering, Politecnico di Milano, Via Privata Giuseppe la Masa 1, 20156 Milano, Italy.
Sensors (Basel, Switzerland)
|January 11, 2025
概括
本研究介绍了使用数字MEMS传感器和边缘AI进行桥梁结构健康监测 (SHM) 的成本效益高的方法. 它可以通过对车辆的间接测量来准确预测桥梁倾斜行为,从而提高了SHM的可扩展性.
科学领域:
- 土木工程 土木工程是指土木工程.
- 结构健康监测 结构健康监测
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
背景情况:
- 增加的道路交通挑战了桥梁和大桥的结构完整性.
- 间接结构监测为基础设施评估提供了一个可扩展和经济的解决方案.
- 现有的方法可能缺乏成本效益和广泛适用性.
研究的目的:
- 探索用于间接桥梁结构健康监测 (SHM) 的新型传感策略.
- 将数字MEMS传感器与智能物联网基础设施集成,用于桥梁偏移预测.
- 为了利用边缘人工智能实时分析结构性行为.
主要方法:
- 开发一个实验设置,包括桥梁模型和传感器驾驶的车辆.
- 在车辆的智能传感节点上部署各种桥梁偏移估计模型.
- 利用边缘人工智能功能进行车载数据处理和分析.
主要成果:
- 展示了数据驱动技术在提高低成本传感器性能方面的潜力.
- 通过基于车辆的间接测量,验证了通过评估静态桥梁倾斜形状的可行性.
- 展示了边缘AI在预测桥梁偏移行为的有效性.
结论:
- 使用MEMS传感器和物联网的间接SHM提供了一个具有成本效益和可扩展的方法.
- 边缘人工智能集成增强了用于结构监测的低成本传感器的能力.
- 这种方法对改善桥梁和高架桥的维护和安全具有显著的前景.
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