| Electrical capacitance tomography(ECT) technique,developed in 1980 s,is a kind of process tomography technique for measuring multi-phase flow in industrial pipeline.ECT has many advantages,such as non-radiation,non-intrusion,simple structure,low cost,easy installation,quick response.At present,it has become the focus of research on process parameters detection at home and abroad.Due to the inverse problem of the ECT image reconstruction technique is ill-conditioned,the further improvement of image reconstruction precision has always been restricted by these bottleneck problems.In 2006,Donoho et al proposed the theory of compressed sensing theory(CS).The theory makes use of the sparsity or compressibility of the signal to carry out a small sampling and achieve the accurate reconstruction of the signal.In order to solve the ill-conditioned problem of the problem of electrical capacitance tomography,the compressed sensing theory is applied to the image reconstruction of electrical capacitance tomography.the main work and results are as follows:(1)According to the characteristic of measuring projection signal of ECT system,the sparse effects of projection signal in different sparse basis spaces are studied.Finally,the discrete Fourier transform is chosen as its sparse basis,which has a better sparsity;(2)The sampling method required by the compressed sensing theory is studied in depth.The author improves the natural sampling method of ECT system and proposes two kinds of random sampling methods to reduce the correlation between the sparse matrix and the observation matrix;(3)Three kinds of signal reconstruction algorithms based on compressed sensing theory are deeply studied.The algorithms are applied in the image reconstruction of electrical capacitance tomography and the simulation experiment is carried out.The results show that the algorithms based on compressed sensing theory can effectively improve the quality of reconstructed image. |
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