基于少量声波飞行时间数据的温度场重建

Temperature field reconstruction based on a few sound travel-time data

为依据少量声波飞行时间数据较高精度地重建温度场,提出了一种基于径向基函数和奇异值分解的声学CT温度场重建新算法。采用新算法对单峰和双峰温度场模型进行了仿真数据重建,重建结果表明,与高斯函数正则化重建算法、代数重建算法相比,新算法的重建精度有明显改善。采用新算法对实验室内的均匀温度场和加热温度场进行了实测数据重建,重建结果与被测温度场一致,且均匀温度场的重建均方根百分误差仅为0.31%。由于新算法重建速度快、重建精度高、抗干扰能力较强,可望用于复杂温度场的在线重建。

In order to reconstruct temperature field from a few sound travel-time data with high accuracy,a new acoustic temperature field reconstruction algorithm based on radial basic function and singular value decomposition is proposed.Using the new algorithm,single-peak and double-peak temperature field models have been reconstructed.Reconstruction results indicate that the new algorithm has higher accuracy compared with the algorithm based on combination of Gaussian function with regularization and the algorithm using algebraic reconstruction techniques.Using the new algorithm,a uniform temperature field and a non-uniform temperature field generated by an electrical heater in the Lab have been reconstructed.Reconstruction results comply with the real temperature distribution,and the reconstruction percent root-mean-square error of the uniform field is only 0.31%.Since the new algorithm has high accuracy,fast speed and good anti-noise ability,it is expected to be used for complex temperature field reconstruction on-line.