Research on Armature Structure Optimization of Rail Gun Based on Multiple Linear Regression

Abstract

The armature structure is the key to the electromagnetic orbit emission. In the initial stage of launch, a good initial contact between the armature and the orbit can effectively avoid transition. First, an L16(54) orthogonal table was established in this article to obtain 16 groups of numerical simulation schemes, and the range and variance analyses of numerical results were carried out. The results show that the main factors affecting the peak contact pressure and stress are shoulder thickness and interference. The secondary factors are the tail length, tail tip thickness, and leading foot thickness; second, a machine learning method based on a multiple linear regression normal equation method is adopted to predict its contact state. The prediction error can be controlled within 10%; finally, parametric scanning is carried out on the basis of machine learning and a new method of armature structure optimization is proposed to improve the initial contact state. The optimized armature can greatly reduce its stress peak. This research provides a new method for the armature structure optimization design.