中文摘要：

电的电容断层摄影术(ECT ) 是瞄准基于测量电容设想固体 / 气体的二阶段的流动的代表性的介电常数分发和阶段分发的一种非侵略的成像技术。解决非线性、提出病的反的问题：ECT 系统的图象重建，这份报纸基于神经网络与适应小浪相结合的改进光线的基础功能(RBF ) 建议了一个新图象重建方法图象改进。第一，一个改进 RBF 网络被使用建立在重建图象象素和测量的电容价值之间的印射的模型。为更好的图象质量，然后，适应小浪图象改进技术强烈地被分析并且学习，它属于一个空间频率分析方法并且对图象合适提高特征。通过多水平小浪分解，从 RBF 网络生产的图象的边点能基于每个亚乐队的邻居性质是坚定的；在空间频率领域的噪音分发能基于统计特征被估计；在那以后，自我适应的边改进获得能被构造。最后，图象与调整小浪系数被重建。在这份报纸，传送平台的一个 12 电极 ECT 系统和灵魂被建立验证这个图象重建算法。试验性的结果证明那种适应小浪图象改进技术有效地实现了边察觉和图象改进，和改进 RBF 网络和适应小浪图象改进混血儿算法极大地改进了固体 / 气体的二阶段的流动的重建的图象的质量[研磨的煤(PC )/air ] 。

英文摘要：

Electrical capacitance tomography（ECT） is a non-invasive imaging technique that aims at visualizing the cross-sectional permittivity distribution and phase distribution of solid/gas two-phase flow based on the measured capacitance.To solve the nonlinear and ill-posed inverse problem：image reconstruction of ECT system,this paper proposed a new image reconstruction method based on improved radial basis function（RBF） neural network combined with adaptive wavelet image enhancement.Firstly,an improved RBF network was applied to establish the mapping model between the reconstruction image pixels and the capacitance values measured.Then,for better image quality,adaptive wavelet image enhancement technique was emphatically analyzed and studied,which belongs to a space-frequency analysis method and is suitable for image feature-enhanced.Through multi-level wavelet decomposition,edge points of the image produced from RBF network can be determined based on the neighborhood property of each sub-band;noise distribution in the space-frequency domain can be estimated based on statistical characteristics;after that a self-adaptive edge enhancement gain can be constructed.Finally,the image is reconstructed with adjusting wavelet coefficients.In this paper,a 12-electrode ECT system and a pneumatic conveying platform were built up to verify this image reconstruction algorithm.Experimental results demonstrated that adaptive wavelet image enhancement technique effectively implemented edge detection and image enhancement,and the improved RBF network and adaptive wavelet image enhancement hybrid algorithm greatly improved the quality of reconstructed image of solid/gas two-phase flow [pulverized coal（PC）/air].