基于有限元仿真和微分进化算法的电场测量仪支架优化

首先通过实验分析研究了测量仪支架结构、环境湿度、支架材质对工频电场测量误差的影响；然后通过有限元仿真计算软件搭建了高压输电线路测量仿真模型，对高压工频电场环境及测量仪支架介入后的畸变电场进行仿真计算，并利用大量仿真结果建立了基于BP神经网络的电场测量误差预测模型；最后采用分子微分进化算法以测量误差最小化为目标对测量支架结构参数进行优化求解。研究结果表明，所优化设计得到的新型电场测量仪支架可有效减小测量误差和增强对湿度环境的适应性。

Optimization Design of Electric Field Measuring Instrument Holder Based on Finite Element Simulation and Differential Evolution Algorithm

In view of the problem that the field measurement results of high voltage power frequency electric field are susceptible to environmental humidity and often have large errors， in order to enhance the adaptability of electric field measurement equipment to the environment and reduce the field measurement error， this paper studies the influence of measuring instrument holder structure， environmental humidity and holder material on the measurement error under power frequency electric field through experimental analysis. The simulation model of high voltage transmission line is built by finite element simulation software， and the distortion electric field after the intervention of the high voltage power frequency electric field and the measuring instrument holder is simulated. Based on a large number of simulation results， an electric field measurement error prediction model based on BP neural network is established. Finally， molecular differential evolution algorithm is used to optimize the structural parameters of the measuring instrument holder with the object of minimizing the measurement error. The research results show that the new electric field measuring instrument holder obtained by the design of optimization can effectively reduce the measurement error and enhance the adaptability to the humidity environment.