| 基于信号指纹的地磁异常识别算法 |
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| 引用本文： | 徐鹏深,滕云田,于子叶,王晓美,吴琼,胡星星.基于信号指纹的地磁异常识别算法[J].地震学报,2018,40(1):79-88. |
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| 作者姓名： | 徐鹏深 滕云田 于子叶 王晓美 吴琼 胡星星 |
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| 作者单位： | 1.中国北京 100081 中国地震局地球物理研究所 |
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| 摘 要： | 本文基于信号指纹技术，通过研究短时（<10 min）地磁异常数据识别算法，完成了对地磁干扰信号类型的识别。本文所用信号指纹技术结合了短时傅里叶变换、小波变换、信号二值化、文本相似性哈希等多种数据和文本处理方法，将一定时间内的波形数据转换为一个32位的整型数字，极大地压缩了信号的特征信息，因此在很大程度上减少了后续查找与分类过程中所需处理的数据。利用该算法对河北红山地磁台2016年5月1—3日两套GM4磁通门磁力仪的原始秒数据的计算结果表明，本文算法可以快速准确地识别干扰信号类型，为实现地磁相对观测数据中异常信号的自动提取提供技术支撑。
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| 关 键 词： | 短周期异常 信号指纹 文本相似性哈希 |
| 收稿时间： | 2017-05-25 |
Electromagnetic anomaly identification algorithm based on signal fingerprinting |
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| Institution: | 1.Institute of Geophysics，China Earthquake Administration，Beijing 100081，China2.Liaoning Earthquake Agency，Shenyang 110031，China3.Institute of Geodesy and Geophysics，Chinese Academy of Sciences，Wuhan 430077，China |
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| Abstract: | This paper makes research on recognition algorithm of short-time （<10 min） geomagnetic anomaly data, based on signal fingerprint, to recognize the categories of geomagnetic disturbance signals. The signal fingerprinting used in this study can convert the waveform data for a given period of time into a 32-bit integer, basing on the combination of multiple data and text-processing methods, such as Fourier transform, wavelet transform, signal binarization and MinHash, which greatly compresses the feature information of signals, thus greatly reduces the amount of data to be located and classified in the following research. The experiment uses raw second-scale data of two sets of GM4 fluxgate magnetometers recorded at Hongshan geomagnetic station (LYH) in Longyao city of Hebei Province from 1 to 3 May 2016, and the results indicate that the algorithm in this paper can quickly and accurately recognize categories of interference signals, and provides technical support for automatic abnormal signals extraction of geomagnetic relative record data. |
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