Study And Application Of Electrical Capacitance Tomography System

Electrical capacitance tomography(ECT)based on capacitance sensing array isa kind of process tomography (PT). It has the advantages of being non-intrusive,fast in response and low in cost. It can acquire visible 2D/3D distributioninformation of closed pipeline or vessel. The visible technique is of a greatdeveloping potential in industrial process parameter measurement .Although ECT technique has achieved great progress in the recent twenty years,and various performance indexes have been improved. But this falls short of actualapplications in industrial processes, many foundational researches need also to bedone in the future.In this thesis, the author studied mainly three aspects, i.e. optimum design ofstructure parameter of capacitance sensing array electrode, reconstruction algorithmand hardware design of ECT system. The following achievements have beenobtained:1 The development of the simulation software package of ECT systemThe simulation software package of ECT system based on Matlab has beendeveloped, which can be used in 2D/3D simulation according to demands. Itincludes forward problem and inverse problem. The 2D/3D models of 8-electrode,12-electrode and 16-electrod can be constructed automatically in solving forwardproblem. To counter different model, the dissection and finite element computationcan be done. The 2D/3D sensitivity distribution (map) of ECT sensors can beobtained. The inverse problem is called as reconstruction algorithms, which includeback projection method and active filter back projection method improved by author,and moreover, the simulation of images reconstruction is performed using RBFneural network and SVM method2 The optimum design of structure parameter of sensing array electrodeThe sensing filed in ECT system is called as ' soft-filed ' , which isinhomogeneous,'ill posed' ,nonlinear and mainly relies on the structure parameterof array electrode. The sensitivity distribution is calculated by using the 2D finiteelement method (FEM). The effect of the number and the structure parameters ofarray electrode on the field uniformity are analyzed . A set of optimum parametersof sensing array electrode based on this method is obtained .In order to study ECTsensor in detail, a 3D capacitance model based on the FEM has been developed.Four-node tetrahedron elements are used for 3D meshing, six-node pentahedronelements which are made up of four-node tetrahedron elements are used as imageconstruction elements, in this way an linear interpolation function can be used inthis method. The effect of medium distribution in the axial direction is analyzed byusing calculating results of sensitivity distribution, and 3D simulation results aregiven.3 The presentation of the active filter back projection methodBased on inhomogenous of sensitivity distribution distribution the active filterback projection method is presented by improving filter back projection method.Simulation results show that the new method is superior to the classical filter backprojection method4 The applying the RBF neural network to the image reconstructionThe ECT is a typical nonlinear mapping problem, and the mapping model isdifficult to be described analytically. A neural network offers a general frameworkfor representing nonlinear function mapping from several input variables to severaloutput variables. In fact the image reconstruction based on neural network isprovided with nonlinear mapping from sampling capacitance data to pixel values.The RBF neural network provided a good properties of approximation, classifyand convergence. There is a liner relationship between network weight value andoutput value. It has no local minimum problem, and it is an optimization networkcompared with other forward networks. The applying the RBF neural network to thereconstruction is studied5 The investigating image reconstruction based on Support VectorMachine(SVM)The capacitance tomography is a typical small samples and nonlinear mappingproblem. Support vector machines (SVM) is based on the special small samplestheory with strong generalization ability, and is selected as an optimal theory forsmall samples classify problem.The ECT image reconstruction algorithms based on C-SVM is proposed. In thispaper a novel training method is proposed to improve the efficiency of C-SVMclassifier by selecting active penalty parameters;an image reconstruction algorithmbased on C-SVM is proposed by using four-layers neural network for three-phaseflow. The 3D image reconstruction algorithm is implemented by simulation.6 Hardware design of ECT systemAn ECT system is designed and developed successfully. The embeddedtechnique and CAN bus are applied in the design. The system possesses the stability,flexibility,expansibility and can reconstruct relatively good images.