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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Zernike ultrasonic tomography for fluid velocity imaging based on pipeline intrusive time-of-flight measurements
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Zernike ultrasonic tomography for fluid velocity imaging based on pipeline intrusive time-of-flight measurements

机译:基于管道侵入飞行时间测量的流体速度成像的Zernike超声层析成像

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摘要

In this paper, we propose a novel ultrasonic tomography method for pipeline flow field imaging, based on the Zernike polynomial series. Having intrusive multipath time-offlight ultrasonic measurements (difference in flight time and speed of ultrasound) at the input, we provide at the output tomograms of the fluid velocity components (axial, radial, and orthoradial velocity). Principally, by representing these velocities as Zernike polynomial series, we reduce the tomography problem to an ill-posed problem of finding the coefficients of the series, relying on the acquired ultrasonic measurements. Thereupon, this problem is treated by applying and comparing Tikhonov regularization and quadratically constrained ??? minimization. To enhance the comparative analysis, we additionally introduce sparsity, by employing SVD-based filtering in selecting Zernike polynomials which are to be included in the series. The first approach???Tikhonov regularization without filtering, is used because it is the most suitable method. The performances are quantitatively tested by considering a residual norm and by estimating the flow using the axial velocity tomogram. Finally, the obtained results show the relative residual norm and the error in flow estimation, respectively, ~0.3% and ~1.6% for the less turbulent flow and ~0.5% and ~1.8% for the turbulent flow. Additionally, a qualitative validation is performed by proximate matching of the derived tomograms with a flow physical model.
机译:在本文中,我们基于Zernike多项式级数提出了一种用于管道流场成像的新型超声层析成像方法。在输入处进行侵入式多路径时下超声测量(飞行时间和超声速度的差异),我们在输出时提供流体速度分量(轴向,径向和正交速度)的层析X线照片。原则上,通过将这些速度表示为Zernike多项式级数,我们可以将断层扫描问题简化为依靠所获取的超声测量值来找到级数系数的不适定问题。因此,通过应用和比较Tikhonov正则化和二次约束来解决此问题。最小化。为了增强比较分析,我们还通过在选择要包含在该系列中的Zernike多项式中使用基于SVD的滤波来引入稀疏性。第一种方法是使用没有过滤的Tikhonov正则化,因为它是最合适的方法。通过考虑残留范数并使用轴向速度层析X射线照片估计流量,对性能进行了定量测试。最后,获得的结果显示相对残差范数和流量估计误差,对于较小的湍流,分别为〜0.3%和〜1.6%,对于湍流为〜0.5%和〜1.8%。另外,通过将派生的断层图与流物理模型进行近似匹配来执行定性验证。

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