闪电光电信号的同步观测与闪电类型模式识别  

Simultaneous observations of optical and electrical signals and pattern recognition in lightning flashes classification

作　　者：李鹏[1] 郑毅[1] 张义军[2] 

机构地区：[1]防化研究院,北京102205 [2]中国气象科学研究院,北京100081

出　　处：《强激光与粒子束》2007年第9期1512-1516,共5页High Power Laser and Particle Beams

基　　金：国家科技基础条件平台资助课题(2004DEA71070);科技部科技开发项目"三维闪电探测系统研制"资助课题

摘　　要：利用宽带电场仪和光学纹波探头,对2006年夏季广东省从化地区发生的自然闪电的光电信号进行了同步观测,并对结果进行了统计分析。统计结果表明:闪电光信号脉冲的发生时间和峰值到达时间总是滞后于电信号,并且脉冲上升沿和宽度也比电信号宽;云闪的光信号在上述特征参数的滞后量、上升沿时间和脉宽时间差要比地闪回击放电大。从闪电光电信号时域信号特征的角度,利用BP人工神经网络,对闪电类型进行了模式识别研究。总体识别结果基本上能够满足要求,但是由于云闪放电过程比较复杂,获得的数据较少,所以对云闪识别的效果并不理想。The optical and electrical signals of lightning discharges were measured simultaneously by using the wide - band electric field instrument and the optical ripple detector at Conghua city Guangdong province in summer, 2006. The observation data were analyzed statistically in this paper. The results show that the lightning optical signal is always delayed from the electric signal on onset and peak time, and the optical pulse rises more slowly to the peak and its pulse-width is broader. Using the back propagation artificial neural networks methods, the pattern recognition in lighting flashes chassification was further investigated by optical and electric time series. The results are up to the standard except in-cloud flash ones.

关 键 词：闪电 光电信号 同步观测 统计分析 BP神经网络 模式识别 

分 类 号：P427.3[天文地球—大气科学及气象学] TP183[自动化与计算机技术—控制理论与控制工程]