关键词: 电容层析成像, 新型类支集神经网络, 划分子网络, 图像重建

Abstract: Aiming at improvement of image reconstruction algorithm in 12-Electrical Capacitance Tomography system，this paper conducts an experimental study on closed containers gas/solid two phase flow，which mainly depend on the stability and the speed of image reconstruction algorithm.To keep the stability of solving process and the computational performance，the image reconstruction algorithm based on a new set of neural network types supported algorithm（NSSN） is first applied to the ECT image reconstruction system.Large-scale training of neural network algorithm puts forward a slow sub-division of the network enhancement.The system uses 12-electrode capacitance tomography system for gas-solid flow tube closure data detection，the use of the improved neural network algorithm for image reconstruction.The obtained experimental results fully show that the image reconstruction method has high precision imaging，computing speed and so on.This method can simplify the use of neural network structure，reducing the size of neurons for image reconstruction of electrical capacitance tomography system and providing a new way of thinking.

Key words: Electrical Capacitance Tomography（ECT）, New Supported Set Network（NSSN）, dividing subnetwork, image reconstruction