A review on acoustic emission-based damage detection and quantitative assessment of civil engineering structures in recent years

定量评估 结构健康监测 风险分析(工程) 计算机科学 工程类 风险评估 分级(工程) 法律工程学 民用基础设施 建筑工程 损失和损坏 Boosting(机器学习) 新兴技术 稳健性(进化) 声发射 选择(遗传算法)
作者
Junfang Wang,Kai-Xin Lin,Jian‐Fu Lin,Haijun Zhou
出处
期刊:Structural Health Monitoring-an International Journal [SAGE Publishing]
被引量:3
标识
DOI:10.1177/14759217261422381
摘要

Acoustic emission (AE), as a highly sensitive structural health monitoring technology, has been widely applied to the damage detection of engineering structures. This paper systematically reviews the research progress of AE-based damage detection methods in civil engineering based on the literature mostly in the past 10 years. This review focuses on three types of AE-based damage detection methods for the engineering structures made of three commonly seen materials and having four different damage problems. Specifically, the detection methods are classified into three categories, including AE feature-based methods, waveform-based methods, and intelligent methods using AE physical models or data-driven models. They are further divided into nine subcategories of approaches for detailed analyses. The involved engineering structures are classified according to different materials and different damage problems for providing a cross-understanding of “methods—materials types—damage types” relationship. It is very challenging for AE-based monitoring technology to realize quantitative assessment, although proven to be an effective way for detecting damage existence. Therefore, the quantitative assessment approaches among the AE-based detection methods are explored in detail, which take advantage of explicit features or implicit relationships for grading the stages of damage development and quantifying damage severities. In responding to the limitations undermining the application of AE in civil engineering, possible solutions and future trends are provided and discussed. Through in-depth analyses of the methodological innovation and applications of the AE-based methods in damage initiation identification, damage expansion tracking, and damage quantification, this study potentially provides support for appropriate method selection and technical breakthrough of the challenges, thereby boosting the applicability of AE technology to engineering structures and reducing the engineering safety risks caused by damage development.
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