Abstract
In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a new combined method based on genetic algorithm(GA) and modified Newton-Raphson(mNR) algorithm via two-step approach for the solution of the static EIT inverse problem. In the first step, each mesh is classified into three mesh groups: target, background, and temporary groups. The mNR algorithm can be used to determine the region of group. In the second step, the values of these resistivities are determined using genetic algorithm. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved compared to that of the mNR algorithm at the expense of increased computational burden.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Control, Automation and Systems Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
