结构健康监测
工程类
建筑工程
计算机科学
深度学习
管道运输
土木工程
系统工程
数据科学
人工智能
机械工程
结构工程
作者
U. M. N. Jayawickrema,H.M.C.M. Herath,N. K. Hettiarachchi,Harsha Sooriyaarachchi,Jayantha Epaarachchi
出处
期刊:Measurement
[Elsevier]
日期:2022-06-25
卷期号:199: 111543-111543
被引量:64
标识
DOI:10.1016/j.measurement.2022.111543
摘要
Structural health monitoring (SHM) systems in civil engineering structures have been a growing focus of research and practice. Over the last few decades, optical fibre sensor (OFS) technology has advanced rapidly, and various types of OFS technologies have found practical uses in civil engineering. Due to recent advances in optical sensors and data-driven solutions, the SHM systems are gaining prominence. Because of its superior ability to detect damage and flaws in civil engineering structures, deep learning (DL) gradually gained substantial attention among researchers in recent years. The main goal of this paper is to review the most recent publications in SHM related to bridges, buildings, and pipelines using emerging OFS and DL-based applications, and to provide readers with an overall knowledge and understanding of various SHM applications. Finally, current research trends and future research needs have been identified.
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