In this paper, we discuss the usage and implementation of the compressive sensing (CS) for the efficient measurement and analysis of the von Kármán vortices. We consider two different flow fields, the flow fields around a circle and an ellipse. We solve the governing $k-ϵ$ transport equations numerically in order to model the flow fields around these bodies. Using the time series of the drag, $C_D,$ and the lift, $C_L,$ coefficients, and their Fourier spectra, we show that compressive sampling can be effectively used to measure and analyze Von Kármán vortices. We discuss the effects of the number of samples on reconstruction and the benefits of using compressive sampling over the classical Shannon sampling in the flow measurement and analysis where Von Kármán vortices are present. We comment on our findings and indicate their possible usage areas and extensions. Our results can find many important applications including but are not limited to measure, control, and analyze vibrations around coastal and offshore structures, bridges, aerodynamics, and Bose-Einstein condensation, just to name a few.

在本文中，我们将讨论压缩感测（CS）的使用和实现，以有效测量和分析vonKármán涡。我们考虑两个不同的流场，即围绕圆形和椭圆形的流场。我们解决治理$ķ-ϵ$为了数值模拟这些物体周围的流场，需要用数字形式传输方程。使用拖曳的时间序列，$C_d，$ 还有电梯 $C_{\mathrm{大号}}，$系数，以及它们的傅里叶光谱，我们表明压缩采样可以有效地用于测量和分析冯卡门漩涡。我们讨论了采样数量对重建的影响，以及在存在VonKármán涡流的流量测量和分析中，与经典Shannon采样相比，使用压缩采样的好处。我们对我们的发现进行评论，并指出其可能的使用领域和扩展。我们的结果可以找到许多重要的应用，包括但不限于测量，控制和分析沿海和近海结构，桥梁，空气动力学和Bose-Einstein凝结周围的振动，仅举几例。