In order to reconstruct complicated temperature fields more accurately by acoustic CT, a reconstruction algorithm based on Markov radial basis function and Tikhonov regular- ization 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 basis 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. Recon- struction results show that the MTR algorithm can reconstruct the hot temperature, especially the hot position accurately. An experiment system for temperature distribution measurement by acoustic CT is developed. The capability of acoustic CT to detect a hot spot created by electric heaters in an experimental silo filled with 1200 kg soybeans is tested by using the MTR algorithm. In the reconstruction temperature field, the hot position can be determined correctly and the temperature error of the hot spot is 1.3%. It is thus clear that the MTR algorithm has a good capacity of reconstructing complex temperature fields, and can be expected to be used in temperature monitoring for actual stored gains.
