A review on structural health monitoring: past to present

被引:11
|
作者
Katam, Rakesh [1 ]
Pasupuleti, Venkata Dilip Kumar [1 ]
Kalapatapu, Prafulla [2 ]
机构
[1] Mahindra Univ, Ecole Cent Sch Engn, Dept Civil Engn, Hyderabad 500043, Telangana, India
[2] Mahindra Univ, Ecole Cent Sch Engn, Dept Comp Sci Engn, ,, Hyderabad 500043, Telangana, India
关键词
Vibration-based SHM; Damage detection; Structural degradation; Frequency domain; Time domain; Digital twinning; Artificial intelligence; Machine learning; Deep learning; BEAM-LIKE STRUCTURES; DAMAGE DETECTION; CRACK IDENTIFICATION; UPDATING MODELS; NEURAL-NETWORK; VIBRATION; FREQUENCY; SENSITIVITY; BRIDGE; DOMAIN;
D O I
10.1007/s41062-023-01217-3
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The field of structural health monitoring (SHM) has gained significant attention from academia and industry, particularly in the realm of damage detection. This approach allows continuous monitoring of the structural integrity of systems and structures throughout their operational lifespan, leading to reduced dependence on periodic inspections and lower maintenance costs. Importantly, this method enables the assessment of structural degradation without causing actual damage to the structure itself. Over the past four decades, various evaluation methods for SHM have been developed, with concrete buildings benefiting greatly from their implementation. Among these methods, vibration-based techniques provide a quick and efficient way to assess the overall health of a structure. Specifically, frequency-based techniques are commonly employed within the vibrations-based SHM (VBSHM) framework, although extracting these parameters through algorithm development can be a complex and time-consuming task. This research aims to review VBSHM with a focus on modal parameters, exploring both traditional and modern methodologies to enhance the accuracy of structural assessment. Additionally, the study highlights the current limitations of research in this field and identifies available studies for further exploration.
引用
收藏
页数:20
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