【作者】 张轶鹏；

【导师】 乔晓林；

【作者基本信息】 哈尔滨工业大学 ， 信息与通信工程， 2010， 硕士

【摘要】 强震前存在地震电磁疑似异常现象已被大量强震震例所证实,分析地震电磁疑似异常已经成为地震短临预测的有效手段。伴随着国际地震电磁卫星的迅速发展,研究地震电磁特征提取方法,统计分析地震电磁疑似异常,对地震短临预测及我国自主研发电磁卫星都具有重要意义。论文基于法国DEMETER卫星的数据和资料,采用电磁波传播分析和极化分析方法,对截止频率下方出现的类似平面波辐射的地震电磁疑似异常进行了提取,并进行了如下几方面的研究:本文首先研究了电磁波极化概念,对完全极化波和非完全极化波的概念和分析方法进行了阐述,为采用SVD技术深入分析了在电离层高度截止频率下电磁辐射的极化特性和波传播特性。通过特征分析确定了电磁时频幅度和极化度等参数的分割门限,通过门限检测方法将几千个数据文件的数量降低到几百个。其次,论文研究了C均值聚类方法、ISODATA算法和形态学区域生长等目标分割算法,通过理论分析各种算法的优缺点,最终确定采用形态学区域生长算法。该方法运算速度快,适用于大数据量的检测。实验结果表明,该方法可以有效提取地震电磁异常信号,并具有较高的执行效率。最后,论文对2006年全年8700个数据文件采用本文算法进行了检测,并对提取出来的地震电磁疑似异常信息与地震事件进行了统计分析,研究了地震电磁疑似异常发生的经纬度、时间、极化、传播方向等特征参数与地震事件的相关性,为地震电磁前兆分析提供了科学合理的统计结果。论文成果不仅提供了可靠的地震电磁疑似异常检测方法,对于从海量数据中提取少量有用信息而言,也提供了研究典范。更多还原

【Abstract】 It has been proved by a lot of seismic cases that the seismo-electromagnetic abnormal phenomena occur before the strong earthquakes. The seismo-electromagnetic precursors have been considered as an effective means of the short-term and imminent earthquake prediction. At the same time, accompanying with the swift development of the internationalseimo-electromagnetic satellites, it is important for imminent earthquake prediction and our own seimo-electromagnetic satellites to carry out research on processing method for seimo-electromagnetic data on the DEMETER spacecraft.By using the data and documents of the satellite DEMETER, take the methods of analysis of electromagnetic wave propagation and polarization, we extract seismo-electromagnetic abnormal phenomena, which is similar to the plane-wave radiation, under the cut-off frequency, the following specific research:Firstly, the concept of Electromagnetic wave polarization was introduced, include the concept and the analysis methods of completely polarized wave and non-fully polarized wave, and the polarization features as well as the propagation features of electromagnetic radiation under the cut-off frequency in ionosphere use the SVD(Singular value decomposition) technology. The segmentation threshold of electromagnetic spectrum as well as the polarization were determined by the feature analysis, for reduce the amount of data.Secondly, the C-mean algorithm、ISODATA(Iterative Selforganizing Data Analysis Techniques Algorithm) algorithm and the region growing on Morphological were introduced, we finally take region growing on Morphological because for its speed. Experimental results show that this method can effectively extract abnormal seismic electromagnetic signals and implementation of high efficiency.Finally, we use this algorithm detected 8700 data files collected in 2006, then Statistical Analysis the relationship between the seismo-electromagnetic abnormal phenomena and seismic events,. We also statistical analysis the relationship between Latitude and longitude, time, polarization, propagation direction of characteristic parameters of abnormal phenomena and seismic events, for the reason science.The result of article provide a detect method of seismo-electromagnetic abnormal phenomena, and it is also a good model how to extract a little information from mass data files.更多还原