Lightweight structural health monitoring and safety evaluation: Review and case studies

结构健康监测 结构工程 可靠性工程 法律工程学 工程类 计算机科学 建筑工程
作者
Dan Li,Bo Li,Tengyi Wang,Jian Zhang
出处
期刊:Advances in Structural Engineering [SAGE Publishing]
卷期号:28 (12): 2157-2179 被引量:12
标识
DOI:10.1177/13694332251325043
摘要

Structural health monitoring (SHM) has proven effective in early damage detection and in facilitating structural condition assessment. Conventional SHM systems feature comprehensive sensing for large infrastructures, such as long-span bridges and high-rise buildings. However, the high cost of these systems limits their feasibility for small to medium-sized structures. Inspired by lightweight design principle from the automotive industry, lightweight monitoring offers a promising complementary approach to conventional SHM. This paper provides an overview of the concepts, techniques, methodologies, and applications of lightweight monitoring for SHM. For sensing devices, non-contact, wireless, and robotic sensing are explored for their potential to enable fast and convenient data acquisition. For monitoring scheme, the concept of targeted sensing is introduced as an alternative to comprehensive sensing, focusing on the monitoring of critical structural behaviors using purpose-built devices. Additionally, the development of cloud-edge-end collaborative framework enables optimized deployment of computing resources for SHM. With regard to data analysis, the paper examines methods for data preprocessing, data fusion, and structural evaluation, with particular emphasis on artificial intelligence-driven approaches that enable fast and automatic analysis. Finally, this paper offers insights into the future of lightweight monitoring in SHM. By organizing and clearly identifying SHM techniques suitable for lightweight monitoring practices, this review serves as a practical guide for advancing the adoption of lightweight SHM and provides a foundation for further innovation in this field.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刘铠瑜发布了新的文献求助10
2秒前
挖掘机应助飲啖茶采纳,获得200
3秒前
moon发布了新的文献求助10
4秒前
完美世界应助久顾南川采纳,获得10
4秒前
6秒前
英俊的铭应助常烁采纳,获得10
6秒前
6秒前
陈好完成签到,获得积分10
6秒前
6秒前
粮仓发布了新的文献求助40
8秒前
9秒前
10秒前
orixero应助Jodie采纳,获得30
10秒前
10秒前
11秒前
SciGPT应助可可西里采纳,获得10
11秒前
11秒前
华仔应助moon采纳,获得10
12秒前
13秒前
hahaha关注了科研通微信公众号
14秒前
春树爱学术完成签到,获得积分10
14秒前
冰葬会议发布了新的文献求助20
15秒前
大福麻薯完成签到,获得积分10
15秒前
16秒前
Trailblazer发布了新的文献求助10
16秒前
17秒前
IiIIIIiiIIIIii完成签到,获得积分20
18秒前
Owen应助冷傲的绿草采纳,获得10
18秒前
18秒前
Kao应助小马采纳,获得10
18秒前
酷波er应助guo采纳,获得20
18秒前
手抓饼啊发布了新的文献求助10
19秒前
19秒前
19秒前
开朗绿蓉完成签到,获得积分10
19秒前
20秒前
21秒前
CYJ发布了新的文献求助10
21秒前
21秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7256078
求助须知:如何正确求助?哪些是违规求助? 8878179
关于积分的说明 18750358
捐赠科研通 6936307
什么是DOI,文献DOI怎么找? 3200684
关于科研通互助平台的介绍 2374963
邀请新用户注册赠送积分活动 2176253