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Study On The Method Of Magnetic Induction Tomography With Uniform Excitation Field

Posted on:2022-12-03Degree:MasterType:Thesis
Country:ChinaCandidate:D P WangFull Text:PDF
GTID:2480306752955979Subject:Computer Software and Application of Computer
Abstract/Summary:PDF Full Text Request
Magnetic Induction Tomography(MIT)technology has the characteristics of noninvasive,non-radiation,and low cost.It is a tomographic imaging technology that can image the object to be measured with electromagnetic characteristics and present the conductivity distribution of the object to be measured,which has great application potential in the fields of industrial detection,medical imaging and other fields.In this paper,the basic working principle of magnetic induction tomography technology and the development status at home and abroad are studied,and the Helmholtz coil that can generate a uniform magnetic field is used as the excitation coil of the new MIT system,the uniform excitation field magnetic induction detection imaging system is designed.The magnetic field strength and uniformity of the excitation magnetic field and the detection effect of the detection system on the measured object are studied through simulation models and hardware experiments.The total variation filter back-projection reconstruction algorithm is used for image reconstruction of the system detection signal,and the detection accuracy of the system on the deep part of the measured object is visually displayed.Firstly,the simulation model of the uniform excitation field magnetic induction detection system based on the Helmholtz coil is established to study the positive problem.At the same time,the simulation model of the traditional magnetic induction tomography detection system is designed,and the detection performance of the uniform excitation field magnetic induction detection system is evaluated by the magnetic field distribution,sensitivity distribution and the change of the detection coil phase data caused by the disturbance.The disturbance model of the measured object is rotated and scanned,and simulation calculation is performed.The obtained phase difference data is analyzed and used for MIT imaging.Secondly,the hardware system of magnetic induction detection with uniform excitation field is designed after completing the calculation and analysis of the simulation model,including the excitation-detection coil,the required circuit design,the measured object-disturbance model,and the rotating platform.In order to analyze the detection performance of the hardware system,the stability experiment is designed to analyze the system detection effect.Thirdly,the total variation filtering back-projection algorithm applied to the MIT system with uniform excitation field is designed based on the mathematical model theory of MIT reconstruction,which combines the filtering back-projection algorithm with the total variation constraint algorithm.The reconstruction data obtained by the model simulation calculation is used for image reconstruction,and the reconstruction image obtained by the original commonly used image algorithm is compared and analyzed.It is proved that the total variation filtering back-projection algorithm proposed in this paper improves the quality of the reconstructed image.Finally,the measured data are obtained through the imaging experiments of the uniform excitation field magnetic induction detection hardware system in this paper.The image is reconstructed by the total variation filter back-projection algorithm,and the reconstructed image results are compared and analyzed with the simulation reconstruction image and the ideal image results,respectively.It is proved that the uniform excitation field magnetic induction detection system proposed in this paper enhances the detection effect on the measured object,and the total variation backprojection algorithm improves the quality of the reconstructed image.
Keywords/Search Tags:Magnetic induction tomography, Uniform magnetic field, Total variation minimization, Back-projection reconstruction
PDF Full Text Request
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