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An Explicable Neighboring-Pixel Reconstruction Algorithm for Temperature Distribution by Acoustic Tomography

Author

Listed:
  • Qirong Qiu

    (School of Mathematics and Physics, North China Electric Power University, Beijing 102206, China)

  • Wanting Zhou

    (School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
    National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing 100190, China)

  • Qing Zhao

    (School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)

  • Shi Liu

    (Ningbo Image Probing Measurement Technology Co., Ltd., Ningbo 315211, China)

Abstract

Acoustic process tomography is a powerful tool for monitoring multiphase flow and combustion. However, its capability of revealing details of the interrogation zone is restricted by the ill-posed and rank deficiency problems. In each projection, a probing sound beam only passes the pixels along its propagation path, resulting in a large number of zero-valued elements in the measurement matrix. This is more pronounced as the resolution of the imaging zone becomes gradually finer, which is detrimental to image reconstruction. In this study, a mathematically explicable reconstruction algorithm of regularization is proposed by assigning each zero-valued pixel with a combination of the values of the neighboring pixels, ruled by the appropriate regularization factors. The formula to determine the regularization factors is also derived. Simulations are carried out to verify this new approach, and some representative cases are presented. As a result, the ambiguity of the inverse process is removed, and the accuracy of the image reconstruction is significantly improved. The results show the robustness of the algorithm and certain advantages over the standard Tikhonov regularization formula.

Suggested Citation

  • Qirong Qiu & Wanting Zhou & Qing Zhao & Shi Liu, 2022. "An Explicable Neighboring-Pixel Reconstruction Algorithm for Temperature Distribution by Acoustic Tomography," Energies, MDPI, vol. 15(9), pages 1-16, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3118-:d:801408
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    References listed on IDEAS

    as
    1. Yuhui Wu & Xinzhi Zhou & Li Zhao & Chenlong Dong & Hailin Wang, 2021. "A Method for Reconstruction of Boiler Combustion Temperature Field Based on Acoustic Tomography," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-11, September.
    2. Qian Kong & Genshan Jiang & Yuechao Liu & Jianhao Sun, 2019. "3D Temperature Distribution Reconstruction in Furnace Based on Acoustic Tomography," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-15, September.
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