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3D Temperature Distribution Reconstruction in Furnace Based on Acoustic Tomography

机译：基于声学断层扫描的炉中的3D温度分布重建

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摘要

3D temperature distribution measurement in a furnace based on acoustic tomography (AT) calculates temperature field through multipath acoustic time-of-flight (TOF) data. In this paper, a new 3D temperature field reconstruction model based on radial basis function approximation with polynomial reproduction (RBF-PR) is proposed for solving the AT inverse problem. In addition, the modified reconstruction method that integrates the advantages of the TSVD and Tikhonov regularization methods is presented to reduce the sensitivity of noise on perturbations with the ill-posed problems and improve the reconstruction quality (RQ). Numerical simulations are implemented to evaluate the effectiveness of the proposed reconstruction method using different 3D temperature distribution models, which include the one-peak symmetry distribution, one-peak asymmetry distribution, and two-peak symmetry distribution. To study the antinoise ability of our method, noises are added to the value of TOF. 3D display of reconstructed temperature fields and reconstruction errors is given. The results indicate that our model can reconstruct the temperature distribution with higher accuracy and better antinoise ability compared with the truncated generalized singular value decomposition (TGSVD). Besides that, the proposed method can determine the hot spot position with higher precision, and the temperature error of the hot spot is lower than the other compared methods.
机译：基于声学断层扫描（AT）的炉中的3D温度分布测量通过多径声学飞行时间（TOF）数据计算温度场。本文提出了一种基于径向基函数近似与多项式再现（RBF-PR）的新的3D温度场重建模型，用于解决逆问题。此外，提出了整合TSVD和Tikhonov正规化方法优势的改进的重建方法，以降低扰动对扰动的敏感性，并提高重建质量（RQ）。实施数值模拟以评估使用不同的3D温度分布模型的所提出的重建方法的有效性，包括单峰对称分布，单峰值不对称分布和两个峰值对称分布。为研究我们方法的抗切征能力，噪声被添加到TOF的值中。给出了重建温度场的3D显示和重建错误。结果表明，与截短的广义奇异值分解（TGSVD）相比，我们的模型可以以更高的准确度和更好的抗切征能力重建温度分布。除此之外，所提出的方法可以以更高的精度确定热点位置，热点的温度误差低于其他比较方法。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第19期|1830965.1-1830965.15|共15页
  • 作者

    Kong Qian; Jiang Genshan; Liu Yuechao; Sun Jianhao;

  • 作者单位

    North China Elect Power Univ Baoding 071003 Peoples R China;

    North China Elect Power Univ Baoding 071003 Peoples R China;

    North China Elect Power Univ Baoding 071003 Peoples R China;

    North China Elect Power Univ Baoding 071003 Peoples R China;

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