高压电器2025，Vol.61Issue(9)：8-17,10.DOI:10.13296/j.1001-1609.hva.2025.09.002
基于ELM与MOGWO的真空灭弧室结构优化设计
Optimization Design of Vacuum Interrupter Structure Based on Extreme Learning Machine and MOGWO
摘要
Abstract
Interrupter is the core of vacuum circuit breaker and its electric field distribution is closely related to the internal structure design.In this paper,the influence of the grading shield,the structure of the suspension shield,the distance between the shield and the contact as well as the shape of the contact on the electric field distribution of the interrupter is studied firstly,finding that the electric field strength is concentrated at the end of the suspen-sion shield,the end of the contact and the area between the suspension shield and the contact.In order to improve the electric field distribution of the interrupter further,a method based on the combination of extreme learning ma-chine(ELM)and gray wolf algorithm(MOGWO)is proposed in this paper to optimize the design of important struc-tural parameters of the interrupter,and set up a ELM model with the length L1 above the slope of the suspension shield,the curling radius R of the end,the curling angle θ,the distance L2 between the shield and the contact sur-face,and the curvature radius r of the contact end as the input,and the maximum electric field strength and the elec-tric field uniformity of the sub-regions on both sides of the stationary and moving contacts as the output respective-ly,and the structure of the vacuum interrupter is optimized by the MOGWO algorithm.The optimization results show that when the structural parameters of the vacuum interrupter L1 is 79.9 mm,R is 3.5 mm,θ is 220.0°,L2is 11.13 mm and r is 3.0 mm,the electric field distribution of the vacuum interrupter is significantly improved.关键词
真空灭弧室/电场分布/MOGWO/极限学习机Key words
vacuum interrupter/electric field distribution/MOGWO/extreme learning machine引用本文复制引用
丁璨,王周琳,袁召,刘学良,白耀龙..基于ELM与MOGWO的真空灭弧室结构优化设计[J].高压电器,2025,61(9):8-17,10.基金项目
国家自然科学基金面上项目(52177143).Project Supported by General Program of National Natural Science Foundation of China(52177143). （52177143）
