| 行鸿彦,郑锦程,徐伟,王心怡.基于改进麻雀搜索的雷暴云电荷反演方法[J].电子测量与仪器学报,2024,38(8):79-86 |
| 基于改进麻雀搜索的雷暴云电荷反演方法 |
| Thunderstorm cloud charge inversion method based onimproved sparrow search algorithm |
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| DOI： |
| 中文关键词: 三维大气电场 雷暴云电荷 麻雀搜索算法 电荷反演模型 混合策略改进 |
| 英文关键词:three-dimensional atmospheric electric field thunderstorm cloudscharge sparrow search algorithm electric charge inversion model mixed strategy improvements |
| 基金项目:国家自然科学基金（62171228）项目资助 |
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| Author | Institution |
| Xing Hongyan | 1.School of Electrial and Energy Enginggering,Nantong Institute of Technology, Nantong 226001, China;
2.School of Electronics and Information Engineering, Nanjing University of Information
Science & Technology, Nanjing 210044, China |
| Zheng Jincheng | School of Electronics and Information Engineering, Nanjing University of Information
Science & Technology, Nanjing 210044, China |
| Xu Wei | School of Electronics and Information Engineering, Nanjing University of Information
Science & Technology, Nanjing 210044, China |
| Wang Xinyi | School of Electronics and Information Engineering, Nanjing University of Information
Science & Technology, Nanjing 210044, China |
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| 摘要点击次数: 33 |
| 全文下载次数: 109 |
| 中文摘要: |
| 为解决雷暴云电荷反演方法精度较差、现有电荷反演模型受多站组网观测造成的环境误差影响等问题。在假设雷暴云层等厚模型的基础上，推导雷暴云电荷反演所需非线性方程组，建立基于三维大气电场的雷暴云电荷反演模型，通过正弦混沌映射函数优化麻雀搜索算法（SSA）种群初始化方式，提高种群分布的非线性，使用莱维飞行（Levy）函数和反向学习策略优化算法发现者的位置更新方式，提出一种基于改进麻雀搜索算法（ISSA）的雷暴云电荷反演方法。利用三维大气电场仪对地面电场数据进行观测并分析电场特征，使用混合策略改进的SSA算法反演雷暴云充电模型参数。实验结果表明，使用三维大气电场仪观测所得数据进行反演，能够有效消除多站组网观测造成的误差，对比SSA，改进后的ISSA算法反演所得雷暴云两秒相邻电荷量的偏差率均在1%左右，适应度值最低达到5.38，能较为精确的反演雷暴云电荷参数，为研究其充放电过程提供一定参考。 |
| 英文摘要: |
| In order to solve the problems of poor accuracy of the charge inversion method for thunderstorm clouds and the influence of the existing charge inversion model by the environmental error caused by multi-station network observation, a nonlinear equation system is derived to establish a charge inversion model based on the three-dimensional atmospheric electric field. On the basis of the assumption of equal thickness model of thunderstorm clouds, a set of nonlinear equations required for the charge inversion of thunderstorm clouds is derived, and a three-dimensional atmospheric electric field-based charge inversion model of thunderstorm clouds is established. The population initialisation of the sparrow search algorithm (SSA) is optimised by the sinusoidal chaotic mapping function to improve the nonlinearity of the distribution of the populations, and the Levy function and the inverse learning strategy are used to optimise the position updating of the algorithm’s discoverer way, a thunderstorm cloud charge inversion method based on improved sparrow search algorithm (ISSA) is proposed. A 3D atmospheric electric field instrument is used to observe the ground electric field data and analyse the electric field characteristics, and the improved SSA algorithm using the hybrid strategy is used to invert the thunderstorm cloud charging model parameters. The experimental results show that the inversion of the data obtained from the three-dimensional atmospheric electric field instrument (3DAEF) can effectively eliminate the errors caused by the multi-station network observation. Compared with the SSA, the deviation rate of the two-second neighboring charges of the thunderstorm cloud obtained by the improved ISSA algorithm is around 1%, and the fitness value reaches as low as 5.38, which is able to accurately invert the charging parameters of the thunderstorm cloud, and provide a certain reference to the study of its charging and discharging process. |
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