基于fft的时均速度测量时空图像测速仪的设计与评价

Zhang Zhen, Li Huabao, Zhou Yang, Huang Jian
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引用次数: 3

摘要

时空图像测速(STIV)是一种时间平均速度估计方法,在过去的十年中被用于从微观尺度到大尺度的非侵入式流量测量。它以一条测试线作为审讯区(IA),检测生成的时空图像的纹理方向,确定一维速度。由于STIV在空间分辨率和时间复杂度上都优于大尺度粒子图像测速(Large-Scale Particle Image velocity, LSPIV),因此在河流流量实时监测方面具有很大的潜力。然而,由于其复杂性和不确定性,其实用性仍然受到性能评估和灵敏度分析不足的限制。为了简化纹理方向在空间域的检测,提出了一种基于快速傅里叶变换的FFT-STIV方法,在频域检测幅度谱的方向。然后从测量精度、测量范围和计算复杂度等方面对该方法进行了理论评价。最后,分析了基于滚动喷涂模型(RPM)的图像尺寸、采样率、边缘阈值、校准精度和跟踪条件的敏感性。结果表明,FFT-STIV随机误差可控制在±5%以内,系统误差约为±1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and evaluation of an FFT-based space-time image velocimetry (STIV) for time-averaged velocity measurement
Space-Time Image Velocimetry (STIV) is a time-averaged velocity estimation method, which has been used for nonintrusive flow measurements from micro scale to large scale over the past decade. It takes a testing line as the Interrogation Area (IA), and detects the texture orientation of a generated Space-Time Image to determine the 1D velocity. Since STIV is superior to the Large-Scale Particle Image Velocimetry (LSPIV) in spatial resolution and time complexity, it has great potential in real-time monitoring of river flow. However, its practicality is still limited by the deficiencies of performance evaluation and sensitivity analysis due to its complexity and uncertainty. To simplify the detection of texture orientation in spatial domain, an FFT-STIV method was proposed based on Fast Fourier Transform, which detected the orientation of magnitude spectra in frequency domain. Then, a theoretical evaluation was provided, including measuring accuracy, measuring range and computational complexity. Finally, the sensitivities of image size, sampling rate, edge threshold, calibration accuracy, and tracing condition were analyzed based on a Rolling Painting Model (RPM). Results showed that the random errors of FFT-STIV could be controlled within ± 5%, where the systematic error was about ± 1%.
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