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

  • 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.

     

    Abstract: 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.

     

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