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    基于网格非均匀离散的声学层析温度场测量

    Acoustic Tomography Temperature Measurement Based on Grid Non-uniform Discretization

    • 摘要: 提出了一种基于网格非均匀离散的声学层析算法,定义了离散因子以量化网格单元在空间上的疏密分布特征,并且引入了格林双调和插值算法,对比分析了均匀离散、基于不同离散因子设置的非均匀离散、奇/偶数网格划分等多种离散方式的重建性能。结果表明:在测点较少时非均匀离散可以提高重建结果的精度,并且能更准确地重建温度场的峰值。此外,在重建单峰对称温度场时,奇数网格离散要比偶数网格离散更有优势。

       

      Abstract: An acoustic tomography temperature measurement based on grid non-uniform discretization was proposed, and discretization factors were defined to quantify the sparse and dense distribution characteristics of grid cells in space. After which, Green's biharmonic interpolation algorithm was introduced, while comparisons and analyses were conducted on the reconstruction performance of various discretization methods, including uniform discretization, non-uniform discretization based on different discretization factor settings, and odd/even-numbered grid divisions. Results show that by non-uniform discretization with fewer measurement points, the accuracy of reconstruction results can be improved, and the peak value of temperature field can be reconstructed more accurately. In addition, when reconstructing the single-peak symmetric temperature field, odd-numbered grid discretization is prior to even-numbered grid discretization.

       

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