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Noninvasive low-cycle fatigue characterization at high depth with photoacoustic eigen-spectrum analysis

机译:利用光声本征谱分析高深度的无创低循环疲劳特性

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摘要

In this work, photoacoustic eigen-spectrum analysis was proposed for noninvasively characterizing the mechanical properties of materials. We theoretically predicted the relationship between the photoacoustic eigen-spectra of cylindrical optical absorbers and their mechanical properties. Experimental measurements of eigen-spectra extracted from photoacoustic coda waves agreed well with the theoretical predictions. We then applied the photoacoustic eigen-spectrum analysis for contactless monitoring of low-cycle fatigue damage. Experiments showed that the photoacoustic eigen-spectra were closely related to the degree of low-cycle fatigue. This study might enhance the contrast of photoacoustic imaging ford mechanical characterization.
机译:在这项工作中,提出了光声本征谱分析,用于非侵入性地表征材料的机械性能。我们从理论上预测了圆柱形光学吸收体的光声本征光谱与其机械性能之间的关系。从光声尾波提取的本征光谱的实验测量与理论预测吻合得很好。然后,我们将光声本征谱分析应用于低周期疲劳损伤的非接触式监测。实验表明,光声本征谱与低周疲劳程度密切相关。这项研究可能会增强光声成像福特机械表征的对比度。

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