Multi-parameter acoustic emission analysis for fatigue crack evaluation in structural health monitoring

IF 5.6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2025-07-23 DOI:10.1016/j.measurement.2025.118529

Jialin Cui , Xianqiang Qu , Chunwang Lv , Jinbo Du , Hanxu Wang

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引用次数: 0

Abstract

Fatigue crack propagation poses a significant challenge to the service safety and reliability of steel structures. Acoustic Emission (AE) technology, as a real-time and highly sensitive non-destructive monitoring approach, holds great potential for tracking crack evolution. This study systematically examines AE signal evolution across different crack propagation stages through controlled experiments. A multi-parameter cross-correlation analysis is introduced to quantify the interdependencies among key AE parameters, offering a more comprehensive assessment than traditional single-parameter methods. The results reveal that AE amplitude, energy, event count, and duration exhibit distinct variations as cracks grow. Notably, energy, event count, and duration demonstrate strong positive correlations, making them robust indicators for crack propagation pattern recognition. In contrast, rise time and peak count show more scattered distributions, reflecting localized damage characteristics. Additionally, AE signals from surface cracks exhibit higher amplitude and energy than those from deep-embedded cracks, validating the spatial attenuation effect and providing a quantitative basis for crack depth estimation. This study presents a multi-parameter correlation-based AE signal analysis method, enhancing AE-based damage classification and monitoring accuracy. The proposed approach strengthens the theoretical foundation for structural health monitoring (SHM) and fatigue damage early warning, while also contributing to the optimization of non-destructive testing (NDT) techniques in engineering applications.

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结构健康监测中疲劳裂纹评价的多参数声发射分析

疲劳裂纹扩展对钢结构的使用安全性和可靠性提出了重大挑战。声发射（AE）技术作为一种实时、高灵敏度的无损监测方法，在跟踪裂纹演化方面具有很大的潜力。本研究通过控制实验系统地考察了声发射信号在不同裂纹扩展阶段的演化。引入多参数互相关分析来量化关键声发射参数之间的相互依赖关系，比传统的单参数方法提供更全面的评估。结果表明，随着裂纹的扩展，声发射振幅、能量、事件数和持续时间呈现明显的变化。值得注意的是，能量、事件计数和持续时间表现出很强的正相关性，使它们成为裂缝扩展模式识别的稳健指标。相比之下，上升时间和峰值数的分布更加分散，反映了局部损伤的特征。此外，表面裂缝声发射信号的振幅和能量均高于深埋裂缝声发射信号，验证了空间衰减效应，为裂缝深度估计提供了定量依据。提出了一种基于多参数相关性的声发射信号分析方法，提高了基于声发射的损伤分类和监测精度。该方法加强了结构健康监测和疲劳损伤预警的理论基础，同时也有助于工程应用中无损检测技术的优化。

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来源期刊

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.