流型自适应的归一化方法对Tikhonov正则化算法的改进

电容层析成像的成像数据采用不同的归一化模型,对重建图像的质量有重要影响.针对两相流的典型流型,研究了采用不同的归一化模型时,Tikhonov正则化算法性能与流型及相含率的相关性.仿真采用新的归一化模型与常规的模型处理电容测量值,重建原图像.结果表明,基于单一的归一化模型,不能在各流型分布下都有最好的成像效果.提出了基于流型识别、自动适应流型的归一化方法,新方法提高了Tikhonov正则化算法的性能.

Adaptive Normalization Method for Flow Pattern to Improve Performance of Tikhonov Regularization Algorithm

The imaging data being used for electrical capacitance tomography(ECT) need be normalized and the reconstructed image quality greatly relies on the normalization method.In ECT,the relationship between the images reconstructed by Tikhonov regularization algorithm based on the different normalization models and the two-phrase flow patterns and phase concentrations,was investigated.The images reconstructed with the new normalization models were proposed and compared to those with conventional ones.A conclusion...