【摘要】 基于流向阵列的高时间分辨率粒子图像测速（TR–PIV）数据库，使用尺度分解和时空相关方法研究了不同类型湍流结构的迁移特性。使用离散小波变换对流向脉动速度进行流向空间分解，发现存在含能最集中的尺度；使用空间条件相位平均方法验证了不同小波系数代表的湍流结构；基于这些小波系数，使用时空互相关方法，得到相关系数随时间延迟的变化曲线，得到不同结构的迁移速度剖面，发现在尾迹区，不同湍流结构的迁移速度与平均速度基本一致，而在对数律区及以下，最大含能尺度结构的迁移速度高于平均速度，且不同结构的迁移速度也不同，随着雷诺数增大，其差值有所区别，但是大小关系未变。更多还原

【Abstract】 The convection features of different types of turbulent structures were studied by scale decomposition and temporal-spatial correlation, based on PIV data of a large field of view and high-resolution captured by four streamwise assembled cameras in the turbulent boundary layer. Discrete wavelet transform was used to decompose the fluctuation velocity along the streamwise direction, and it is found that there are scales with the most concentrated energy. The conditional average method was used to detect the turbulence structures represented by different wavelet coefficients. Based on these wavelet coefficients, the spatial-temporal correlation method was used to obtain the curves of correlation coefficients versus time delay, and the convection velocity profiles of different types of structures were obtained. It is found that the convection velocity of different types of turbulent structures in the wake region is basically consistent with the average velocity, while in the logarithmic region and below, the convection velocities of structures with the most energetic scale is higher than the average velocity, and convection velocity of different types of structures are also different. As the Reynolds number increases, the difference between them varies, but their orders remain unchanged.更多还原