利用压缩传感技术对vonKármán涡旋的有效传感
Efficient Sensing of the von Kármán Vortices Using Compressive Sensing
摘要：
在本文中，我们讨论了压缩传感（CS）的有效测量和分析的冯卡门涡的使用和实施。我们考虑两种不同的流场，绕圆和椭圆的流场。我们解决的控制$k-ε$输运方程数值模拟这些机构周围的流场。使用时间序列的阻力，$C_D$，和升力，$C_L$，系数，和他们的傅立叶谱，我们表明，压缩采样可以有效地用于测量和分析冯卡门涡。我们讨论了重建的样本数量的影响和使用压缩采样的好处，在经典的香农采样的流量测量和分析，其中冯卡门涡存在。我们评论我们的研究结果，并指出其可能的使用领域和扩展。我们的研究结果可以找到许多重要的应用，包括但不限于测量，控制和分析沿海和海上结构，桥梁，空气动力学和玻色-爱因斯坦凝聚周围的振动，仅举几例。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
