基于正则化SVD算法的三维温度场声学重建  

Three-Dimensional Temperature Field Reconstruction with Acoustics Based on Regularized SVD Algorithm

作　　者：王然[1] 安连锁[1] 沈国清[1] 张世平[1] 

机构地区：[1]华北电力大学国家火力发电工程技术研究中心,北京102206

出　　处：《计算物理》2015年第2期195-201,共7页Chinese Journal of Computational Physics

基　　金：国家自然科学基金面上项目(11274111);煤的清洁转化与高效利用创新引智基地111计划(B12034);北京高等学校青年英才计划项目(YETP0700);华北电力大学中央高校基本科研业务费专项资金(2014MS10)资助项目

摘　　要：针对电站锅炉炉内三维温度场重建问题,基于声学理论构建数学模型.提出两种基于奇异值分解法(Singular Value Decomposition,SVD)的正则化算法,利用少量声学数据,对炉膛火焰分布的几种典型模型进行仿真重建.采用不同标准差的高斯噪声对两种算法的抗噪声能力进行检验.仿真结果表明,正则化SVD算法可以解决严重不适定的重建问题,重建温度场能够准确反映温度场分布,并且算法具有一定的抗噪声能力.TSVD正则化算法重建速度更快,抗噪声能力更强,适用于燃烧情况复杂的电站锅炉.For reconstruction of three-dimensional temperature field in furnace of power plant boiler, a mathematical model based on acoustic theory was constructed. Two regularization algorithms based on Singular Value Decomposition（ SVD） algorithm were proposed. Three typical temperature fields were simulated. Anti-noise ability of algorithms was tested by Gaussian noise with standard deviations. It indicates that regularized SVD algorithm is able to solve severely ill-posed reconstruction problems. Reconstruction temperature field reflects accurately temperature distributions, and algorithms have good anti-noise ability. TSVD regularization algorithm with faster reconstruction speed and better anti-noise ability is suitable for power plant boiler with complicated combustion.

关 键 词：声学测温 三维温度场 不适定问题 SVD算法 正则化 

分 类 号：O551.2[理学—热学与物质分子运动论]