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Inversion algorithm for Lamb-wave-based depth characterization of acoustic emission sources in plate-like structures

机译:板状结构中声发射源的羊波基深度表征的反演算法

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摘要

An inversion algorithm (termed AEDep) is proposed for estimating the depth of acoustic emission (AE) sources in plate-like structural components. The work is motivated by the need for characterizing early-stage fatigue crack growth in such components. The algorithm achieves depth estimation by automatically extracting the depth-dependent amplitude ratio between the fundamental Lamb modes which comprise the AE signals. A finite element model is designed to study the frequency-dependent forward problem of Lamb wave motion due to a given source, from which the relation between source depth and amplitude ratio is established. Elastodynamic theory is used to validate the model in the frequency domain, as well as to derive a sensor tuning factor which may be incorporated into the solution. The proposed algorithm was tested on two plate-like specimens: a 6061-T6 aluminum plate and a 2025-T6 aluminum aircraft fuselage panel. Validation of the algorithm was achieved by generating controlled AE sources at various depths along the edges of the specimens, in the form of Hsu-Nielsen pencil lead breaks. Good agreement was found in the aluminum plate between the true and estimated source depths. A slight decrease in accuracy was found in the fuselage panel between the true values and their estimations. However, both experimental cases demonstrated the ability to distinguish between sources originating near the mid-plane of a plate-like structure from those near the surface. Lastly, the fast computation of the inversion algorithm shows strong potential for real-time monitoring applications.
机译:提出了一种反演算法(称为AEDEP),用于估计板状结构部件中的声学发射(AE)源的深度。这种作品是有必要在这些组分中表征早期疲劳裂纹生长的需要。该算法通过自动提取包括AE信号的基本羊肉模式之间的深度依赖性幅度比来实现深度估计。设计有限元模型,用于研究由于给定源的频率依赖性前向问题,从中建立了源深度和幅度比之间的关系。弹性动力学理论用于验证频域中的模型,以及导出可以结合到解决方案中的传感器调谐因子。该算法在两种平板样本上进行了测试:6061-T6铝板和2025-T6铝制飞机机身面板。通过在沿着样本边缘的各种深度处产生受控AE源来实现算法的验证,以Hsu-nielsen铅笔铅断裂的形式。在真实和估计的源深度之间的铝板中发现了良好的一致性。在真实值与其估计之间的机身面板中发现了精度略微降低。然而,两种实验情况都证明了能够区分源自板状结构靠近表面靠近表面附近的源的来源。最后,反演算法的快速计算显示了实时监控应用的强大潜力。

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