基于小波分析的地面大气电场观测数据处理技术研究

Processing technology of surface atmospheric electric field observations based on wavelet analysis

摘要:

使用南京信息工程大学实验场的AMEO340电场仪一年观测试验资料,将大气电场仪采样序列数据经快速傅里叶变换,得到序列的功率谱,对晴天和伴有闪电天气的地面大气电场数据进行小波函数为sym5的7层分解,某种程度上降低了地面大气电场数据波形的重叠度。通过对伴有闪电天气的地面大气电场数据进行小波7层分解,地面大气电场信号的低频部分不仅突出显示出地面大气电场值的主要变化趋势,而且能清晰地分辨出闪电过程中较强的正负地闪次数,为利用地面大气电场强度值的变化特征进行闪电预警提供了更有效的信息。

关键词:电场数据;小波分析;时频特性

Abstract:

Using one year ground atmospheric electric filed data by the AMEO340 installed in Nanjing University of Information Science and Technology,this paper calculates the ground atmospheric electric field sampling series by the fast Fourier transform in order to get power spectrum of the ground atmospheric electric field series.The ground atmospheric electric field data of sunny and lightning days are analyzed with seven-layer decomposition of the sym5 wavelet function,which decreases the overlapping degree of ground atmosphere electric field data waveform to some extent.The ground atmospheric electric field signals of lightning days are decomposed by the seven-layer decomposition.The low-frequency component of the ground atmospheric electric field signals not only can highlight its main change trend,but also can clearly identify the number of strong positive and negative ground flashes.So it can supply more effective information for the lightning nowcasting by using the characteristics of the ground atmospheric electric field singnals.

Key words:electric field data;wavelet analysis;time-frequency features