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Compressive sensing of full wave field data for structural health monitoring applications

机译:全波场数据的压缩传感,用于结构健康监测应用

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Numerous nondestructive evaluations and structural health monitoring approaches based on guide waves rely on analysis of wave fields recorded through scanning laser Doppler vibrometers (SLDVs) or ultrasonic scanners. The informative content which can be extracted from these inspections is relevant; however, the acquisition process is generally timeconsuming, posing a limit in the applicability of such approaches. To reduce the acquisition time, we use a random sampling scheme based on compressive sensing (CS) to minimize the number of points at which the field is measured. The CS reconstruction performance is mostly influenced by the choice of a proper decomposition basis to exploit the sparsity of the acquired signal. Here, different bases have been tested to recover the guided waves wave field acquired on both an aluminum and a composite plate. Experimental results show that the proposed approach allows a reduction of the measurement locations required for accurate signal recovery to less than 34% of the original sampling grid.
机译:许多基于导波的无损评估和结构健康监测方法都依赖于对通过扫描激光多普勒振动计(SLDV)或超声扫描仪记录的波场的分析。可以从这些检查中提取的信息内容是相关的;然而,获取过程通常很耗时,从而限制了这种方法的适用性。为了减少采集​​时间,我们使用基于压缩感测(CS)的随机采样方案来最小化测量场的点数。 CS重建性能主要受选择适当的分解基础以利用所采集信号的稀疏性影响。在这里,已经测试了不同的基座以恢复在铝和复合板上获得的导波波场。实验结果表明,该方法可以将准确信号恢复所需的测量位置减少到原始采样网格的34%以下。

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