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作 者:王宵宵 周骛[1,2] 王芳婷 唐欣然 蔡小舒 Wang Xiaoxiao;Zhou Wu;Wang Fangting;Tang Xinran;Cai Xiaoshu(School of Energy cmd Power Eitgineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai Key Laboratory of Multiphase Flow and Heat Transfer for Potoer Engineering,Shanghai 200093,China)
机构地区:[1]上海理工大学能源与动力工程学院,上海200093 [2]上海市动力工程多相流动与传热重点实验室,上海200093
出 处:《光学学报》2021年第19期160-166,共7页Acta Optica Sinica
基 金:国家科技重大专项(2017-V-0016-0069);国家自然科学基金(51576130)。
摘 要:提出将离焦成像与粒子轨迹测速相结合,分别针对直线型和曲线型粒子轨迹,构建了离焦特征参数σ的识别算法,形成了用于三维速度测量的离焦粒子轨迹测速(DPSV)方法。该方法基于粒子图像离焦特征参数σ沿运动轨迹线的线性变化假设,通过拟合粒子图像的灰度分布来识别σ,从而获得粒子深度信息。在直线轨迹拟合的基础上,进一步采用圆弧拟合处理湍流实验中常见的弯曲轨迹图像。形成了相应的图像处理流程,并采用仿真图像验证了参数识别的准确性,在本文实验装置的噪声水平下相对误差为9.4%左右。采用LED光源和5μm孔径光阑组成的发光点进行模拟实验,验证了深度位置z与σ的线性关系。最后,将DPSV技术应用于射流流场,得到了三维速度分布。Particle streak velocimetry based on defocused imaging is proposed to measure three-dimensional(3 D) velocity by recognizing defocusing parameter σ of straight and curve trajectories, called defocused particle streak velocimetry(DPSV). Assuming that σ varies linearly along the trajectory, it can be recognized by the surface fitting of the gray value distribution of particle images, and thereby the depth information of particles is estimated. Based on the linear fitting of straight trajectory, the arc fitting is proposed for the processing of images with curve trajectories, which are commonly captured in turbulent flow by PSV. The relevant image processing algorithm is developed and its correctness in the parameter recognition is validated by synthetic images. The results show that the relative error is about 9.4% in the presence of the noise from the experimental device in this paper. The linear relationship between σ and particle depth z is verified by experiments using an LED light and a diaphragm of 5 μm. Finally, the DPSV technique is applied to a jet flow field and its 3 D velocity distribution is presented.
关 键 词:测量 粒子轨迹测速 弯曲轨迹 离焦成像 三维速度 灰度分布
分 类 号:TH815[机械工程—仪器科学与技术]
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