An Image Reconstruction Algorithm Based on RBF Neural Network for Electrical Capacitance Tomography

Electrical capacitance tomography (ECT) image reconstruction is a typical ill-posed problem. Successful applications of ECT depend greatly on the precision and speed of the image reconstruction algorithms. In this paper, an image reconstruction method based on RBF Neural Network is proposed. Using the measurement data obtained from the ECT simulation software developed, the reconstructed images were obtained. The proposed RBF Neural Network method was verified through typical flow patters image reconstruction. The results show that this method is an effective approach to solve image reconstruction for ECT, which is faster and more accurate compared with the BP neural network.