Fast electromagnetic tomography image reconstruction algorithm based on dimensionality reduction
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 sensi-tivity 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)algo-rithm 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.
electromagnetic tomographyimage reconstruction algorithmdata dimensionality reduc-tionkernel principal component analysisill-conditioning
万方数据
维普
