声学CT复杂温度场重建研究

为提高声学CT复杂温度场重建能力,提出一种利用Markov径向基函数逼近和Tikhonov正则化的温度场重建算法,简称MTR算法。该算法首先用Markov径向基函数的线性组合,逼近介质中的复杂声速场分布,然后利用介质中多路径声波传播时间和Tikhonov正则化法,求解声速场分布,进而利用声速与温度的关系获得温度分布。对单热点、三热点和五热点温度场模型进行了仿真重建,结果表明MTR算法热点定位精度高,重建误差小。开发了声学CT温度场重建实验系统,用电加热器在内装1200 kg大豆的实验粮仓中形成热点,MTR重建结果能正确反映热点位置,热点温度重建误差1.3%。可见,MTR算法复杂温度场重建能力强,可望用于实际储粮温度分布监测。 

Research on complicated temperature field reconstruction based on acoustic CT

In order to reconstruct complicated temperature fields more accurately by acoustic CT,a new reconstruction algorithm based on Markov radial basis function and Tikhonov regularization is proposed and named as MTR algorithm. With the algorithm,the acoustic velocity field in a medium is approximated by a liner combination of Markov radial basic functions,the acoustic travel-times over multi-paths and the Tikhonov regulation are used to reconstruct the acoustic velocity distribution,and then the temperature distribution is calculated by using the relationship between acoustic velocity and temperature.The temperature field models with one hot spot,three hot spots and five hot spots are reconstructed by using simulation data.Reconstruction results show that MTR algorithm can reconstruct the hot spot temperature,especially the hot spot position accurately.An experiment system for temperature distribution measurement by acoustic tomography is developed.The capability of acoustic tomography to detect a hot spot created by electric heaters in an experimental silo filled with 1200 kg soybeans is tested by using MTR algorithm.In the reconstruction temperature field,the hot spot position can be determined accurately and the temperature error of the hot spot is 1.3%.It is thus clear that MTR algorithm has a good capacity for reconstructing complex temperature fields, and can be expected to be used in temperature monitoring for actual stored gains.