A novel method for multichannel discharge image diagnosis in gas switches based on multi-axis tomography techniques

Abstract

Abstract The discharge channel is a crucial diagnostic tool for identifying the properties of gas switches. However, single-view images cannot easily be used to inherently understand the discharge channel characteristics of trigger electrodes. A reconstruction method of the discharge channel in gas switches is proposed based on a multi-axis tomography technique, which uses very few projections of optical images to reconstruct the location of a multichannel discharge in annular electrodes. In this paper, an algorithm named TVM-OSEM (total variation minimization ordered subsets expectation maximization) is proposed, which can effectively remove artifact noise to improve the reconstruction accuracy of discharge channels. The method is validated against simulations of a radiator with high-density-difference boundary. The calculated discharge channel distribution from one experiment is presented.