Tikhonov平滑泛函最小值原理在热成像数据处理中的应用

Q3 Engineering
E. Laneev, N. Chernikova, O. Baaj
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引用次数: 5

摘要

本文研究了一种校正热成像图像的方法。热图的数学处理是基于从被研究物体表面到热源的稳定温度分布作为调和函数的解析延拓。该延拓是通过在矩形截面的圆柱形区域内求解拉普拉斯方程的病态混合问题来实现的。圆柱形区域由任意曲面和平面限定。柯西条件被设定在曲面上——期望函数的边值和它的法向导数。第一类非均匀条件设置在圆柱体的侧面上。这个问题是泊松方程对应的混合问题的逆。本文得到了该问题的近似解,该解相对于柯西数据的误差和边界条件的非均匀性是稳定的。在构造近似解的过程中,将问题简化为第一类Fredholm积分方程,利用最小平滑泛函原理求解。当正则化参数与数据误差匹配时,证明了问题近似解的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of the Minimum Principle of a Tikhonov Smoothing Functional in the Problem of Processing Thermographic Data
The paper considers a method for correcting thermographic images. Mathematical processing of thermograms is based on the analytical continuation of the stationary temperature distribution as a harmonic function from the surface of the object under study to the heat sources. The continuation is performed by solving an ill posed mixed problem for the Laplace equation in a cylindrical region of rectangular cross-section. The cylindrical area is bounded by an arbitrary surface and plane. The Cauchy conditions are set on the surface-the boundary values of the desired function and its normal derivative. Inhomogeneous conditions of the first kind are set on the side faces of the cylinder. The problem is the inverse of the corresponding mixed problem for the Poisson equation. In this paper, an approximate solution of the problem is obtained that is stable with respect to the error in the Cauchy data and inhomogeneity in the boundary conditions. In the course of constructing an approximate solution, the problem is reduced to the Fredholm integral equation of the first kind, which is solved using the minimum smoothing functional principle. The convergence of the approximate solution of the problem is proved when the regularization parameter is matched to the error in the data.
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来源期刊
Advances in Systems Science and Applications
Advances in Systems Science and Applications Engineering-Engineering (all)
CiteScore
1.20
自引率
0.00%
发文量
0
期刊介绍: Advances in Systems Science and Applications (ASSA) is an international peer-reviewed open-source online academic journal. Its scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome. ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public governance, finance, and many others.
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