Modeling Of Electrical Resistance Tomography

Process Tomography is a new technique developed in the past ten years, which can be widely used in many industrial areas such as oil fields, chemical engineering, power plants and steel factories. Electrical Resistance Tomography (ERT) is one of the firstly developed process tomography systems because of its simple sensor structure, low cost, good security and non-intrusive manner. It is prospective while applied to industries.The research work of ERT involves calculation and measurement. The calculation includes the positive and inverse problem to solve the electromagnetic field. Good software and simulation environment are important to the research and design work of ERT system. The author established the simulation software, made it convenient to set the parameters of the resistance sensor with circular and square pipe, flow pattern, solve the forward problem and reconstruct the image.In present dissertation, the model of ERT was established, the method to deduce the system equation using Finite Element Method (FEM) was discussed, and the process of calculating the voltage, resistance and sensitivity matrix through numerical computation was also introduces.Because during the process of positive problem solution, errors are unavoidable, so the evaluation of the results were carried out through data and diagram, also the influence to the results caused by the change of parameters was analyzed. It was indicated that the calculated results of positive problem have relatively small error and are acceptable, the change of the size of electrodes influences the calculated results slightly, and the increase of mesh grid is helpful to improve the precision of calculation.In inverse problem of ERT, the Linear Back Projection algorithm based on sensitivity field is used to reconstruct the qualitative image. Assume that the change of conductance is slight, so the sensitivity can be approximatelyregarded as unchanged, then images may be arrived using sensitivity matrix. Besides, the entropic thresholding method is applied to improve the quality of image.