An Optimization and Parametric Study of a Schlieren Motion Estimation Method
An Optimization and Parametric Study of a Schlieren Motion Estimation Method
复制标题
DOI：
10.1007/s10494-021-00246-1
复制
发表时间：
2021-02
期刊：
影响因子：
--
通讯作者：
Qian Wang;X. Mei;Yu Wu;C. Zhao
中科院分区：
文献类型：
--
作者：
Qian Wang;X. Mei;Yu Wu;C. Zhao
纹影成像技术具有灵敏度高、灵活性强、使用方便等优点，在湍流和燃烧研究中得到了广泛应用。随着数字成像和图像处理技术的发展，利用时间分辨纹影成像序列反演速度测量成为可能。本文基于射流的高速纹影图像和冲击火焰的瞬态点火过程，对一种新提出的纹影运动估计（SME）算法进行了优化和参数研究。SME算法使用分级非凸性（GNC）计算方案进行优化，该方案通过线性组合凸二次函数和略微非凸的广义Charbonnier函数来采用三阶段策略。推导了Euler-Lagrange方程，同时将罚函数分离，便于变换罚函数。通过参数研究，讨论了权重参数的影响，并通过计算得到了合适的权重参数范围。对SME方法和GNC-SME方法进行了比较，结果表明GNC方法在保持边界的同时，避免了局部发散和过光滑。GNC技术的应用拓宽了权值参数的适用范围。GNC-SME方法具有较好的鲁棒性，使其更适合于各种应用。
Schlieren imaging is a widely used technique for flow visualization in turbulence and combustion investigations due to its high sensitivity, flexibility and easiness in use. With the development of digital imaging and image processing techniques, it is possible to retrieve velocity measurements using time-resolved schlieren imaging sequences. In this paper, an optimization and parametric study has been conducted on a newly proposed schlieren motion estimation (SME) algorithm, based on the high speed schlieren images of a jet flow and the transient ignition process of impinging flames. The SME algorithm is optimized using a graduated non-convexity (GNC) computing scheme, which employs a three stage strategy by linearly combining a convex quadratic function and a slightly non-convex generalized Charbonnier function. The Euler–Lagrange equations have been derived, while the penalty function was separated so that penalty functions can be changed conveniently. Parametric investigations have been conducted to discuss the influence of weight parameters, while the suitable ranges have been obtained after intensive calculations. Comprehensive comparisons have been made between the SME and GNC-SME methods, which indicates that the GNC scheme can preserve the boundary well and avoid local divergence and over-smoothness at the same time. The suitable weight parameter range is also broadened by using the GNC technique. The better robustness of GNC-SME method makes it more adaptive to various applications.