Electron Beam Current Distribution Parameter Modelling

The electron beam (EB) technological processes like EB welding, EB additive technologies, etc. depend strongly on the characteristics of the electron beam, generated by the electron gun of each EB installation. The 3D EB radial and angular current distributions, defined for each transverse cross-section of the beam and different process parameters, determine the beam profile and are used to determine the invariant characteristics of the beam quality - brightness and emittance. There are several approaches for EB characterization, which generally can be divided into two big groups: i) assuming Gaussian distribution of the beam current density and ii) without this assumption. In this paper a tomographic technique for reconstruction of a two-dimensional object image from a set of its one-dimensional projections at different scanning angles is implemented for the estimation of 3D radial EB current distribution based on experimental measurements. There the Fourier transformation from real to frequency space and the consequent two-dimensional inverse Fourier transformation permit to reconstruct the beam cross-section current density image with their asymmetry features. This paper presents results from the empirical modelling of the radial standard deviation of the electron beam current distribution –and the, depending on the electron beam process parameters –electron beam focusing current, the electron beam current, Venelt voltage and the electron beam focus position. The electron beam installation, used for the experimental investigation is 2 kW and can be used for electron beam welding, EB additive melting, EB evaporation and EB surface modification. The characterization of the electron beam is one of the necessary conditions for the transfer of technologies from one equipment to another, as well as for the comparison of the quality of different electron beam facilities (guns). Keywords - Electron beam, Radial Current Density Distributions, Tomographic Approach, Regression Model