Phase Sensitive Demodulation Technology And Image Reconstruction In Electrical Capacitance Tomography

High-quality measurements of the flow parameters plays a crucial role in modern industries and the understandings of the complicated physical or chemical mechanisms of the dynamic behaviors of the measurement objects of interest in a multiphase flow system. Owing to the distinct advantages, including non-invasive sensing, low cost, fast response and high safety, electrical capacitance tomography (ECT) is considered as a promising visualization measurement method for the flow parameters in a multiphase flow system.. However, ECT method will face the following challenges such as the weak capacitance signal measurement, the accuracy of data acquisition and the image reconstruction quality, which needs to be further improved. In order to promote the industrial applications, in this dissertation the key issues on the data acquisition and the image reconstruction are investigated to improve the accuracy and speed in the ECT visualization measurement method. The main research contents can be summarized as the follows.(1) In common ECT circuits, the acquired voltage signals should be demodulated by a demodulation circuits consisting of the analog components. However, the analog components are easy to introduce noises. There is a close correlations between the improvement of the signal-to-noise ratio of the whole system and the low pass filters, and thus simultaneously achieving the high-accuracy and high-speed of the data acquisition process is challenging. In this dissertation, in order to improve the precision and the speed of data acquisition in ECT system, the digital quadrature demodulation method is employed to improve the time resolution and the speed of ECT data acquisition. Numerical simulation and experimental results validate the feasibility and effectiveness of the proposed method.(2) A new image reconstruction method is proposed, and ECT image reconstruction task is cast as an optimization problem. A new objective functional that fuses the measurement information form other sensors or the previous observations is proposed. The bilateral total variation regularization method and the higher-order derivative based reference image regularization method are proposed, in which the exploitations of the prior information on the objects of interest can be achieved. A new iteration scheme that integrates the beneficial advantages of the split Bregman method is developed to solve the proposed objective functional. Numerical simulation results indicate that the quality of the images reconstructed by the proposed algorithm is dramatically improved, and thus a promising method is introduced for the solving the inverse problems in ECT image reconstruction.