| 小波分析在雷击大气电场波形去噪分析中的应用 |
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| 引用本文： | 李振亚,肖稳安,张其林,白筱璐,马忠安.小波分析在雷击大气电场波形去噪分析中的应用[J].气象科学,2014,34(3):282-287. |
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| 作者姓名： | 李振亚 肖稳安 张其林 白筱璐 马忠安 |
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| 作者单位： | 南京信息工程大学 气象灾害省部共建教育部重点实验室, 南京 210044;南京信息工程大学 大气物理学院, 南京 210044;南京信息工程大学 气象灾害省部共建教育部重点实验室, 南京 210044;南京信息工程大学 大气物理学院, 南京 210044;南京信息工程大学 气象灾害省部共建教育部重点实验室, 南京 210044;南京信息工程大学 大气物理学院, 南京 210044;南京信息工程大学 气象灾害省部共建教育部重点实验室, 南京 210044;南京信息工程大学 大气物理学院, 南京 210044;普洱市气象局 防雷中心, 云南普洱 665000 |
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| 基金项目： | 公益性行业（气象）科研专项（GYHY200806014） |
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| 摘 要： | 雷击时大气电场信号中混杂的噪声信号影响对真实大气电场信号的分析、提取和使用。文中通过计算仿真信号和去噪前后真实电场信号的均方误差,分析选取不同的小波函数、阈值法和小波分解层数对去噪效果产生的影响。考虑雷击时大气电场信号的信噪比,选用sym5小波和db5小波与minimaxi和rigrsure阈值法结合,且对小波的分解层数选用6~7层,进行大气电场波形的去噪处理,其去噪效果比较理想。最后,将该方法用于实际雷击大气电场波形数据的去噪处理,对雷击时电场波形的突变性检测中,在20个样本中有14个在首次雷击前1.5~2 h具有突变过程,占70%,这为将大气电场仪资料引入其他气象参数预报模型提供了切入点。
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| 关 键 词： | 大气电场波 均方误差 小波分析降噪 阈值法 突变性检测 |
| 收稿时间： | 2012/9/13 0:00:00 |
| 修稿时间： | 2012/11/7 0:00:00 |
Wavelet analysis application in lightning atmospheric electric field waveform de-noising research |
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| LI Zheny,XIAO Wenan,ZHANG Qilin,BAI Xiaolu and MA Zhongan.Wavelet analysis application in lightning atmospheric electric field waveform de-noising research[J].Scientia Meteorologica Sinica,2014,34(3):282-287. |
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| Authors: | LI Zheny XIAO Wenan ZHANG Qilin BAI Xiaolu and MA Zhongan |
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| Affiliation: | Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China;College of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China;College of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China;College of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China;College of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China;Lightning Protection Center of Puer Meteorological Bureau, Yunnan Puer 665000, China |
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| Abstract: | Noise signals mixed in the atmospheric electric field signals when lightning happens should be estimated before analysis, extraction and use of real atmospheric electric field signals. By calculating the mean square errors between simulated signals and real atmospheric electric field signals before and after de-noising,this paper tried to analyse the de-noising effect of different wavelet function, threshold method and wavelet decomposition level. Considering ratio of lightning atmospheric electric field signal to noise signal, selecting sym5 and db5 wavelet, combined with minimaxi and rigrsure threshold method as well as 6-7 wavelet decomposition level, a quite good de-noising effect was found out. Finally, the method is applied in de-noising the atmospheric electric field waveform data of real lightning strikes. In addition, better results in mutation detection have been got. |
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| Keywords: | Atmospheric electric field wave Mean square error Wavelet analysis of de-nosing Threshold method Mutation detection |
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