Structural Optimization Design of Electromagnetic Repulsion Mechanism Based on BP Neural Network and NSGA-II

The long-stroke electromagnetic repulsion mechanism is subjected to large stresses during the driving phase, and the repulsion disc is prone to fracture due to excessive vibration amplitude up and down. Therefore, it is necessary to reduce the peak stress and vibration amplitude of the repulsion disc, improve the mechanical life, and improve the driving performance without decreasing the motion displacement, but it is not possible to do so at present. To address this problem, this paper takes the 'coil-repulsion disc type' electromagnetic repulsion mechanism as the research object, and builds a simulation model of electromagnetic repulsion mechanism with structural strength and driving performance by using finite element simulation software, and analyzes the effects of four structural parameters, namely, the height of the repulsion disc, the inner diameter of the repulsion disc, the radius of the circular table and the radius of the chamfer, on the displacement and stress distribution of the model. After that, 39 sets of samples were output by BBD experimental design method, which were introduced into the BP neural network prediction model and combined with NSGA-II algorithm to optimize the structure of the electromagnetic repulsion mechanism. The simulation results show that with the repulsion disc height of 14 mm, the repulsion disc inner diameter of 14 mm, the radius of the circular table is 29.78mm and the chamfer radius of 7.06 mm, the peak stress of the repulsion disc of the electromagnetic repulsion mechanism is reduced by 57.83%, the amplitude of the repulsion disc is reduced by 3.24 mm, the peak electromagnetic repulsion force is increased by 7.52 kN and speed at the end of 3ms increased by 9.8%. Under the condition of satisfying the constraints and increasing the overall displacement, the structural strength is increased and the driving performance of the mechanism is ensured to be improved, providing reasonable mechanism parameters for the opening and closing requirements of the fast mechanical switch. (c) 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.