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《工程(英文)》 >> 2019年 第5卷 第2期 doi: 10.1016/j.eng.2018.11.027

结构健康监测数据科学与工程研究进展

School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China

收稿日期: 2018-08-01 修回日期: 2018-10-13 录用日期: 2018-11-15 发布日期: 2019-02-28

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摘要

结构健康监测(SHM)是一个多学科交叉领域,涉及利用大量传感器和仪器对结构荷载和响应进行自动感知,然后根据收集到的数据对结构进行健康诊断。由于安装在结构上的 SHM 系统能自动实时地感知、评估和预警结构状态,所以海量数据是 SHM 的一个显著特征。与海量数据处理与分析相关的方法与技术被称为数据科学与工程,其包括数据采集、数据转换、数据管理以及数据处理与挖掘算法。本文旨在简要回顾笔者在 SHM 数据科学与工程方面开展的最新研究,具体涵盖基于压缩采样的数据采集算法、基于深度学习算法的异常数据诊断方法、基于计算机视觉技术的桥梁裂纹识别方法,以及基于机器学习算法的桥梁结构状态评估方法。最后,本文在结语部分对该领域的未来发展趋势进行了展望。

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