A regularized SVD algorithm based method for reconstructing the three-dimensional temperature field of a 660 MW coal-fired heating furnace furnace is proposed to address the problems of large reconstruction errors and long reconstruction time in existing methods for recon-structing the three-dimensional temperature field in the furnace.Based on the principle of extracting feature points from two-dimensional ima-ges of human vision,extract feature points from three-dimensional images of temperature fields;Using wavelet transform method to calculate the endpoints of sub line segments and obtain feature point matching results;The acoustic temperature measurement method and the ray ima-ging theory are used to reconstruct the distribution form of the acoustic wave propagation velocity.The acoustic measurement system model is built by using the regularization SVD algorithm to modify the acoustic wave flight value.Combining the feature point matching results and the symmetry axis,realized the three-dimensional temperature field reconstruction of the coal powder heating furnace furnace of the 660 MW unit.The experimental results show that the minimum AER,MER,and RMSE of the proposed method are 4.11,0.98,and 1.21,respectively,and the reconstruction time remains within 0.6 seconds.The reconstruction error is small,the reconstruction consumption time is short,the noise resistance is strong,and the temperature field reconstruction effect is good.
关键词
燃烧温度/正则化SVD算法/特征点提取/三维温度场重建/小波变换
Key words
combustion temperature/regularization SVD algorithm/feature point extraction/reconstruction of three-dimensional temperature field/wavelet
万方数据