基于降维处理的快速EMT图像重建算法

Fast electromagnetic tomography image reconstruction algorithm based on dimensionality reduction

电磁层析成像技术(EMT)具有非侵入、响应速度快、成本低等优点,在工业过程监测和多相流测量等领域有广泛的应用前景。该文针对电磁层析成像逆问题的病态性,提出了1种非迭代的、基于灵敏度矩阵降维的EMT图像重建算法,应用核主成分分析(KPCA)方法对灵敏度矩阵进行降维,有效降低了算法计算复杂度,同时降低了灵敏度矩阵的病态程度。为验证该算法的有效性,将该算法应用于平面EMT金属探伤,并将其与传统的线性反投影算法和Landweber迭代法进行比较。仿真和实验结果表明,该算法的成像质量远高于线性反投影算法,与Landweber迭代法相近,且该算法的计算耗时仅为Landweber迭代法的20%左右。

Electromagnetic tomography(EMT),which has the advantages of noninvasiveness,fast response and low cost,has the potential for extensive use in industrial process monitoring,multiphase flow measurement and other fields.To cope with the ill-conditioning of the inverse problem of EMT,a non-iterative EMT image reconstruction algorithm based on sensitivity matrix dimensionality reduction is proposed.Kernel principal component analysis(KPCA)is used to reduce the dimensionality of the sensitivity matrix,which effectively reduces the computational complexity of the algorithm and reduces the ill-conditioning of the sensitivity matrix.To verify its effectiveness,the proposed algorithm is applied to planar EMT metal flaw detection,and is compared with the traditional linear back projection(LBP)algorithm and the Landweber iteration method.Simulation and experimental results show that the imaging quality of the proposed algorithm is much higher than that of the LBP algorithm and is similar to that of the Landweber iteration method,and the calculation time of the proposed algorithm is only about 20%of that of the Landweber iteration method.