An Ill-Conditioned Optimization Method and Relaxation Strategy of Landweber for EMT System Based on TMR

The sensitivity distribution of the electromagnetic tomography (EMT) system based on tunneling magnetoresistance (TMR) is quite different from the traditional coil measurement EMT system due to the change of detection sensor. The sensitivity of the TMRs-EMT system is higher only near the TMR sensors but lower at other locations in the region of interest, which results in a more serious ill-conditioned problem of image reconstruction. Focusing on the ill-conditioned problem, the Landweber algorithm is optimized by using an appropriate weight and an appropriate relaxation strategy in this article. By verifying the consistency of variation of the spectral radius of the iterative matrix and variation of condition number for the Landweber method, a new weight matrix is introduced for the general Landweber method to reduce the condition number. On this basis, an optimal relaxation factor is determined based on the principle of minimizing the spectral radius of the newly derived iterative matrix. By comparing the imaging results of the new method with the Landweber with a relaxation factor of 1, it can be seen that the average correlation coefficient with the new approach for the five models used in this article is 0.8466, which is much higher than 0.7633 of the Landweber with a relaxation factor of 1. Meanwhile, the proposed method has a faster imaging speed. The convergence analysis of the two methods shows that the new relaxation factor determination strategy can overcome the semiconvergence problem of Landweber.

[1]  Qian Wang,et al.  Weighting Algorithm and Relaxation Strategies of the Landweber Method for Image Reconstruction , 2018, Mathematical Problems in Engineering.

[2]  Chao Wang,et al.  Investigation of Spatial Resolution of Electrical Capacitance Tomography Based on Coupling Simulation , 2020, IEEE Transactions on Instrumentation and Measurement.

[3]  C Wang,et al.  Comparison of sensitivity matrix calculation methods for EMT system based on TMR for permeability detection , 2018, Journal of Physics: Conference Series.

[4]  Yair Censor,et al.  Component averaging: An efficient iterative parallel algorithm for large and sparse unstructured problems , 2001, Parallel Comput..

[5]  Mimi Faisyalini Ramli,et al.  Adaptive Selection of Relaxation Factor in Landweber Iterative Algorithm , 2017, IEEE Sensors Journal.

[6]  Ming Jiang,et al.  Development of iterative algorithms for image reconstruction , 2002 .

[7]  Chao Wang,et al.  An Ill-posed Optimization Method and Relaxation Strategy of Landweber for EMT System Based on TMR , 2020, 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[8]  Chao Wang,et al.  A pre-iteration method for the inverse problem in electrical impedance tomography , 2004, IEEE Transactions on Instrumentation and Measurement.

[9]  L. Landweber An iteration formula for Fredholm integral equations of the first kind , 1951 .

[10]  Jiamin Ye,et al.  A sparsity reconstruction algorithm for electrical capacitance tomography based on modified Landweber iteration , 2014 .

[11]  Ziqiang Cui,et al.  A novel EMT system based on TMR sensors for reconstruction of permeability distribution , 2018, Measurement Science and Technology.

[12]  Per Christian Hansen,et al.  Semi-convergence and relaxation parameters for a class of SIRT algorithms , 2010 .

[13]  Wuqiang Yang,et al.  An image-reconstruction algorithm based on Landweber's iteration method for electrical-capacitance tomography , 1999 .

[14]  Wen Zhang,et al.  Convergence of General Nonstationary Iterative Methods for Solving Singular Linear Equations , 2011, SIAM J. Matrix Anal. Appl..

[15]  Chao Wang,et al.  ECT image reconstruction based on alternating direction approximate newton algorithm , 2018, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[16]  Per Christian Hansen,et al.  Semiconvergence and Relaxation Parameters for Projected SIRT Algorithms , 2012, SIAM J. Sci. Comput..

[17]  Wuqiang Yang,et al.  Optimization of an iterative image reconstruction algorithm for electrical capacitance tomography , 1999 .

[18]  Kwang Youn Kim,et al.  Modified iterative Landweber method in electrical capacitance tomography , 2006 .

[19]  Ming Jiang,et al.  Convergence results of Landweber iterations for linear systems , 2014 .

[20]  Per Christian Hansen,et al.  AIR Tools - A MATLAB package of algebraic iterative reconstruction methods , 2012, J. Comput. Appl. Math..

[21]  姜明,et al.  Necessary and Sufficient Convergence Conditions for Algebraic Image Reconstruction Algorithms , 2007 .

[22]  Philippe A. Tanguy,et al.  ERT algorithms for quantitative concentration measurement of multiphase flows , 2008 .

[23]  Yang Wang,et al.  High-Density Large-Scale TMR Sensor Array for Magnetic Field Imaging , 2019, IEEE Transactions on Instrumentation and Measurement.