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Quantitative evaluation of orientation-specific damage using elastic waves and probability-based diagnostic imaging

机译:使用弹性波和基于概率的诊断成像对定向损伤的定量评估

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摘要

Different from the damage with relatively smooth boundaries or edges such as a through-thickness hole or delamination which scatters elastic waves omnidirectionally, orientation-specific damage of sizable length in a particular dimension (e.g., a crack or a notch) often exerts strong directivity to elastic wave propagation. As a consequence the damage-scattered waves may not be captured efficiently by sensors at certain locations, posing a challenging issue to elastic-wave-based damage identification. In this study, the influence of damage orientation on Lamb wave propagation was quantitatively scrutinised. Based on the established correlation between damage parameters (location, orientation, shape and size) and extracted signal features, a probability-based diagnostic imaging approach was developed, in conjunction with use of an active sensor network in conformity to a pulse-echo configuration. Relying on enhancive signal features including both the temporal information and signal intensity, this imaging approach is capable of indicating the orientation of individual damage edges clearly and further shape/size of the damage. The effectiveness of the approach was demonstrated by predicting orientation-specific damage cases including a triangular through-thickness hole (through finite element simulation), a through-thickness crack and an L-shape crack (through experiment) in aluminium plates. With the assistance of a two-level synthetic image fusion scheme, all damage cases were visually and quantitatively highlighted in the probability images.
机译:与具有相对光滑的边界或边缘的损坏(例如贯穿厚度的孔或分层结构会全方位分散弹性波)不同,在特定尺寸(例如,裂纹或缺口)中,特定长度的特定于方向的损坏(例如,裂缝或缺口)通常对弹性波传播。结果,损坏散布的波可能无法在某些位置被传感器有效捕获,这给基于弹性波的损坏识别提出了挑战。在这项研究中,对损伤取向对兰姆波传播的影响进行了定量研究。基于损伤参数(位置,方向,形状和大小)与提取的信号特征之间已建立的相关性,结合基于脉冲回波配置的有源传感器网络,开发了基于概率的诊断成像方法。依靠增强的信号特征(包括时间信息和信号强度),这种成像方法能够清楚地指示各个损伤边缘的方向,并进一步指示损伤的形状/大小。通过预测特定方向的损伤情况(包括三角形贯穿厚度的孔(通过有限元模拟),贯穿厚度的裂纹和L形裂纹(通过实验))证明了该方法的有效性。借助两级合成图像融合方案,在概率图像中以视觉和定量方式突出显示了所有损坏情况。

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