融合动态演变信息的声学三维温度场重建

Acoustic 3D temperature field reconstruction fused dynamic evolution information

在声学层析成像方法测量锅炉温度场的应用中,温度场重建算法的精度和速度起着重要作用。建立了三维温度场声学重建的动态模型,提出了同时考虑声学测量信息和温度场动态演变信息的动态重建算法。建立了一个融合声学测量信息、温度场的空间约束及动态演化信息的目标函数,在光滑约束法的基础上构建了反映相邻空间像素位置关系的正则矩阵,采用Tikhonov正则化和优化相结合的方法求解目标函数。仿真模拟研究表明,与最小二乘、代数重建法和标准Tikhonov正则化算法等静态重建算法相比,融合动态演变信息的温度场重建算法的重建速度相仿,而重建精度有显著提高并对于测量数据误差具有更好的数值稳定性,为声学温度场重建提供了一种可行性极高的有效方法。

Accuracy and speed of reconstruction algorithm play an important role in the temperature field measurement for a boiler by acoustic tomography. A dynamic model of a 3D temperature field reconstruction by acoustic tomography is established. A dynamic reconstruction algorithm is proposed considering both the acoustic measurement information and the dynamic evolution information of the temperature field. An objective function is built, which fuses the measurement information, space constraint of the temperature field and the dynamic evolution information. A regularization matrix is established based on the smooth constraint method which reflects the positional relationship between spatially adjacent pixels. A method combining Tikhonov regularization and optimization is adopted to solve the function. The numerical simulations show that the reconstruction speed of the algorithm fusing dynamic evolution information is similar to static reconstruction algorithm including the least square method, the algebraic reconstruction technique and the standard Tikhonov regularization algorithm. The image quality and noise immunity of the algorithm fusing dynamic evolution information are better than the results obtained from the static algorithms. An innovative method with high effectiveness is provided for temperature field reconstruction by acoustic.