Image Reconstruction Technology Of Capacitance Tomography System Based On Intelligent Algorithm

Electrical capacitance tomography(Electrical Capacitance Tomography,ECT for short)is an industrial process tomography technique,mainly used to measure and image two-phase flow and multi-phase flow.According to the nature of the different dielectric constants between the phases of the measured substance,this technique can obtain the distribution of the medium in the pipeline by measuring the capacitance value between the electrode pairs arranged around the pipeline and using an appropriate image reconstruction algorithm.Compared with other process tomography detection technologies,ECT has the characteristics of non-invasive,no radiation,low cost,good safety performance and fast imaging speed.Capacitance tomography technology has a wide range of applications in the detection of two-phase flow or multi-phase flow,such as oil exploitation and transportation,fluidized bed gas-solid two-phase concentration distribution visualization and pneumatic transportation.This article focuses on the image reconstruction part of the electrical capacitance tomography system,and proposes an image reconstruction algorithm based on intelligent algorithm.Through the self-built capacitance tomography system experimental environment,the actual imaging effect of the algorithm is compared with the traditional imaging algorithm Analyze and complete the verification of algorithm improvement effect in theory.First,the physical meaning of the sensitive field in the capacitive sensor and the solution process of the sensitivity matrix are described.The 8-electrode capacitive sensor is modeled using COMSOL Multiphysics multiphysics coupling software,and the internal field of the sensor is divided into networks according to the finite element analysis method.,To simulate the three flow patterns to provide a theoretical basis for the construction of the following experimental environment;then the principle of the classic Landweber imaging algorithm is discussed in detail,illustrating the instability of the algorithm on convergence,using genetic The advantages of the algorithm and ant colony algorithm in the global search and searching for the optimal solution have improved the Landweber algorithm;finally,the principle of micro capacitance detection and two basic measurement circuits are introduced.For the capacitive sensor used in this paper,the capacitance measurement and The electrode conversion circuit has built the final experimental environment of capacitance tomography system.Using the experimental environment of the built-up capacitance tomography system,a gas-liquid two-phase flow imaging experiment was carried out.For the three flow types,the traditional Landweber algorithm and the improved algorithm were used to reconstruct the acquired capacitance data and the obtained image was reconstructed.A comparative analysis shows that the improved Landweber algorithm has improved both the accuracy of flow pattern identification and the accuracy of imaging,and the practicability of the improved algorithm is verified.