多权值电容归一化方法的研究

基于并联模型且考虑了不同介质满场分布时电容值对测量电容值的影响,提出了一种多权值电容归一化方法,所建模型不仅适用于两相流还适用于两相流以上的多相流。实验结果表明:在包含2种以上介质的多相流图像重建中,使用多权值模型的图像重建精度的均方差为0.0044,明显优于并联模型的0.0322,因此,多权值模型能够提高图像重建算法精度。分析重建图像发现,该模型还能提高物场中心处的灵敏度,使得物场中心处物体的成像误差减小,从而提高重建图像质量。

Research on Multi-weights Normalization Method

A new multi-weights normalization method based on the parallel normalization model is presented,and it considered the influences of the capacitances when the sensor is full of deference permittivity materials for the measured capacitance.The multi-weights model is suitable for two or more phase flow.The experimental results show that the RMSE of the image reconstruction accuracy based on the multi-weights model is 0.0044,better than that of parallel normalization model which is 0.0322 when more than two kinds of medium in the image reconstruction,so the multi-weights model can improve the image reconstruction accuracy effectively.Through the analysis of the reconstruction image show that it also can improve the sensitivity of the center field and reduce the imaging errors,which greatly improving the quality of reconstruction.