Research And Design Of ECT Data Acquisition System Based On DSP And FPGA

Electrical Capacitance Tomography(ECT)is a widely used multi-phase flow detection technology,which is mainly able to provide closed pipe or container internal visual information,it has many advantages,such as simple structure,non intrusive,fast response,high security,and so on,and is the research hotspot of process tomography(PT).However,there are still some areas that need to be improved in the practical application of electrical capacitance tomography,the research focus is also focused on the measurement of small capacitance and image reconstruction algorithm,so,the research of data acquisition system and filtering algorithm is of great significance.This paper uses the ECT data acquisition system based on DSP and FPGA as the research object,mainly focuses on the data acquisition and processing of the traditional ECT data acquisition system using DSP or FPGA single device,and uses the wired transmission mode to transmit data.This paper presents an ECT data acquisition system based on DSP and FPGA,which can be used for wireless transmission,in addition,research and design the organizational structure.The main work of this paper is as follows:Firstly,this paper briefly introduces the electrical capacitance tomography system and its research status at home and abroad,and introduces the components of the system,including sensor,data acquisition system,imaging system.An ECT data acquisition based on DSP and FPGA is proposed.Secondly,the related technology used in this system is introduced.The system uses FPGA as a digital filter and phase sensitive demodulation module,DSP as a control module,uses Bluetooth wireless transmission,and has carried on the system hardware design and software design.Finally,several common digital filtering algorithms in ECT system are studied in order to achieve better filtering denoising effect.An adaptive filtering algorithm based on wavelet transform is proposed,and the algorithm is implemented by Matlab software.Simulation analysis shows that this filtering algorithm can achieve better filtering effect.