Comparison Of Digital And Analog Demodulation Filtering Methods In Electrical Tomography System

Electrical Tomography(ET)is one of the process tomography technologies,which is often used in the parameter detection work of multiphase flow,and has gradually developed into a mature measurement method.Electrical tomography system is mainly composed of three parts,namely sensor system,data acquisition system and image reconstruction system,among which the data acquisition system plays a connecting role.With the development of science and technology,higher requirements are put forward for the real-time measurement speed and the accuracy of measurement results.More accurate and stable data acquisition system is the basis of high quality and high precision multiphase flow detection.In the data acquisition system,the design of filter and demodulator is the most important part,so this thesis carries on the comparison study of digital and analog demodulation filtering methods of electrical tomography system.The main research content of this thesis is as follows:The working principle of ET data acquisition system is introduced,and the demodulation methods and filtering methods commonly used in ET data acquisition system are compared and analyzed.In view of the limitations of traditional filtering methods,a piecewise Kalman smoothing algorithm is proposed,which combines the standard Kalman filtering algorithm with the RTS smoothing algorithm.By piecewise smoothing,it not only improves the accuracy,but also ensures the real-time performance.By analyzing the influence of random noise on the results of digital orthogonal demodulation,a digital orthogonal demodulation method combined with filter is proposed,which can improve the anti-noise ability of digital orthogonal demodulation technology.The design scheme of ET data acquisition system was developed,and the experimental platform of ET data acquisition system was built.The effectiveness and superiority of the proposed method are verified by the simulation results in multiple scenarios of the simulation platform and the experimental results of the built hardware platform,and the feasibility of the method in the actual industrial process is verified.