Optimal Design of Electrical Capacitance Tomography Sensor and Improved ART Image Reconstruction Algorithm Based On the Internet of Things

For the problems of low sensitivity, weak signal of high and low frequency and low signal-to-noise ratio in ECT, the mathematical model of the sensor is established. From the aspects of electrostatic field distribution and soft field effect, the influence of the structural parameters of the sensor on the sensor performance is analyzed. According to the influence of the components of the sensor on the sensitivity, the principle of optimal design is put forward. Based on the optimized Landweber image reconstruction algorithm, an ART image reconstruction algorithm with iterative correction is proposed, and the mathematical model of the algorithm is designed. According to constructing the target functional regularization term in the negative problems of electrical capacitance tomography, the iterative process of the modified art algorithm is deduced, and with adaptive step size, the convergence is speeded and accuracy of image reconstruction is improved. The experimental results show that the semi-convergence in the improved algorithm is obviously weakened, and the reconstructed image quality is better than that of the traditional art algorithm.