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基于截断奇异值分解的三维火焰温度场重建研究
引用本文:黄群星,刘冬,王飞,严建华,池涌,岑可法.基于截断奇异值分解的三维火焰温度场重建研究[J].物理学报,2007,56(11):6742-6748.
作者姓名:黄群星  刘冬  王飞  严建华  池涌  岑可法
作者单位:浙江大学能源清洁利用国家重点实验室,杭州,310027
基金项目:国家自然科学基金;国家自然科学基金;教育部长江学者和创新团队发展计划
摘    要:利用CCD摄像机得到的火焰辐射能图像进行炉膛三维火焰温度场重建,但温度重建矩阵方程是一个不适定方程组,从而重建问题是一个不适定问题.应用截断奇异值分解(truncated singular value decomposition,TSVD)的正则化方法对该不适定方程组进行求解,并且采用了L曲线法对正则化参数进行选取.结合重建算例,采用奇异值分解(singular value decomposition,SVD)与离散Picard条件对这个不适定问题进行了分析.重建结果表明,在不同的模拟测量误差下,TSVD能够成功得到合理的解,重建温度场较好的再现了原始假设温度场的特征.

关 键 词:温度场重建  不适定问题  截断奇异值分解  离散Picard条件
文章编号:1000-3290/2007/56(11)/6742-07
收稿时间:1/9/2007 12:00:00 AM
修稿时间:2007-01-09

Study on three-dimensional flame temperature distribution reconstruction based on truncated singular value decomposition
Huang Qun-Xing,Liu Dong,Wang Fei,Yan Jian-Hua,Chi Yong,Cen Ke-Fa.Study on three-dimensional flame temperature distribution reconstruction based on truncated singular value decomposition[J].Acta Physica Sinica,2007,56(11):6742-6748.
Authors:Huang Qun-Xing  Liu Dong  Wang Fei  Yan Jian-Hua  Chi Yong  Cen Ke-Fa
Institution:Zhejiang University State Key Laboratory of Clean Energy Utilization,Hangzhou 310027,China
Abstract:Three-dimensional flame temperature distribution reconstruction in furnace according to the flame radiative energy images captured by CCD cameras was studied. Temperature reconstruction matrix equation is an ill-posed linear system of equations and the reconstruction problem is an ill-posed problem. Truncated singular value decomposition method (TSVD) was introduced to deal with the ill-posed matrix equation and L-curve method was adopted to choose regularization parameter. Singular value decomposition (SVD) and discrete Picard condition were used to analyze the ill-posed characteristics of the reconstruction problem carefully. The results show that reasonable solutions can be obtained by TSVD and the reconstructed temperature distribution can reproduce the feature of the assumed temperature distribution.
Keywords:temperature distribution  ill-posed problem  TSVD  discrete Picard condition
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