强激光与粒子束2024，Vol.36Issue(9)：160-168,9.DOI:10.11884/HPLPB202436.240177
基于神经网络反向模型的系统级电场辐射发射预测
Prediction of system-level electric field radiated emission based on ANN reverse model
刘璐瑶 1金晓 2蔡金良2
作者信息
- 1. 中国工程物理研究院应用电子学研究所,四川绵阳 621999||中国电子科技集团公司第二十九研究所,成都 610036||中国工程物理研究院研究生院,北京 100088
- 2. 中国工程物理研究院应用电子学研究所,四川绵阳 621999||先进激光与高功率微波全国重点实验室,四川绵阳 621900
- 折叠
摘要
Abstract
To address the issue of system-level electromagnetic compatibility,a new method of predicting electromagnetic interference of complex systems based on artificial neural network(ANN)reverse model is proposed in this paper.Firstly,the electric field radiated emission(RE)of single equipment is measured.The training data of system-level RE are obtained by simulation based on the equivalence principle of radiated emission.Frequency,RE and coordinate of each single equipment are selected as the input variables,and the system-level RE is the output variable.A reverse model of the three-layer back-propagation(BP)ANN with Levenberg-Marquardt(LM)algorithm is established by exchanging the input-output variables.The alternative ANN with minimum validation error is searched as the ultimate ANN.The numerical root-finding algorithm(regular-falsi method and conjugate gradient method)are adopted to calculate the RE of multi equipments.The results show that the validation error of this reverse model is significantly improved compared to the traditional three-layer LM-BP ANN.Especially,the ANN reverse model based on conjugate gradient method reduces the validation error from 0.4159%to 0.0997%.This method is independent of complex ANN structures,and improves simulation accuracy with limited training data,which provides a new efficient and feasible solution for electromagnetic compatibility evaluation of electronic information platforms such as ships,satellites,and aircrafts.关键词
神经网络/电磁兼容/辐射发射/数值求解方法/非线性系统Key words
artificial neural network/electromagnetic compatibility/radiated emission/root-finding algorithm/nonlinear system分类
信息技术与安全科学引用本文复制引用
刘璐瑶,金晓,蔡金良..基于神经网络反向模型的系统级电场辐射发射预测[J].强激光与粒子束,2024,36(9):160-168,9.
