Design Of Three-Dimensional Sensor And Image Reconstruction For Electrical Capacitance Tomography

ECT(Electrical Capacitance Tomography) as a process tomography is an important field of research in recent years, extremely rapid development. Electrical capacitance tomography depends on the operating principle of capacitive measurement, electrical capacitance tomography technology has the advantages of high safety, non-invasive detection and wide applicability, based on this, the electrical capacitance tomography has a very wide range of applications. In practical application, is also accompanied by a corresponding problem. The traditional sensor is two-dimensional imaging, only get "slices image", this imaging method has many drawbacks. In the process of fluid transmission, some problems are difficult to directly reflect. ECT imaging sensor sensitivity field distribution is not uniform, the sensitive field distribution by the distribution of measured medium (position and area size) and the difference of two-phase medium permittivity, the formation of "soft field" effect, reduces the accuracy of the reconstructed image. Aiming at the above problems, this dissertation mainly do the following work:1. Understand the technical principle of electrical capacitance tomography, combined with the specific research of this topic, relevant materials for the direct access to three-dimensional electrical capacitance tomography, and points out the necessity of research on direct three-dimensional capacitance tomography system.2. In-depth study of electrical capacitance tomography system components, sensor structure, classification and correlation coefficient of the sensor, the relevant theoretical knowledge of the data acquisition system.3. Through the research on the traditional capacitance tomography sensor, design of a new type of direct 3D ECT sensor, at the same time, improve the existing incentive mode. Experiments show that using the new 3D ECT sensor can not only increase the projection data, but also can effectively improve the measurement accuracy.4. A detailed study of the properties of the "soft field" and analysis of its causes. Constructing particle swarm optimization by setting a priori conditions, in order to make up for the "soft field" effect caused by defects, and used two particle swarm optimization to find the optimal solution for image reconstruction. Through the experiment, two particle swarm optimization algorithm set a priori conditions, comparing the application of new image reconstruction method of the reconstruction results of the algorithm reconstruction results and application of traditional image reconstruction, the quality of the image, the image precision is obviously improved, and overcome the local optimization.