Research on Real-time Monitoring of Abnormal Seismic Noise  

作　　者：Lin Binhua Jin Xing Liao Shirong Li Jun Huang Linzhu Chen Huifang 

机构地区：[1]Earthquake Administration of Fujian Province,Fuzhou 350003,China [2]Fuzhou University,Fuzhnu 3501-16,China

出　　处：《Earthquake Research in China》2016年第2期224-232,共9页中国地震研究（英文版）

基　　金：sponsored by the National Key Technology R&D Program of China(2009BAK55B00);the Earthquake Industry Research Project(201508012)

摘　　要：The noise data in vertical component records of 85 seismic stations in Fujian Province during 2012 is used as the research object in this paper. The noise data is divided into fiveminute segments to calculate the power spectra. The high reference line and low reference line of station are then identified by drawing a probability density function graph( PDF)using the power spectral probability density function. Moreover, according to the anomalies of PDF graphs in 85 seismic stations,the abnormal noise is divided into four categories: dropped packet, low noise, high noise, and median noise anomalies.Afterwards,four selection methods are found by the high or low noise reference line of the stations,and the system of real-time monitoring of seismic noise is formed by combining the four selection methods. Noise records of 85 seismic stations in Fujian Province in July2013 are selected for verification,and the results show that the anomalous noise-recognition system could reach a 90% success rate at most stations and the effect of selection are very good. Therefore,it could be applied to the seismic noise real-time monitoring in stations.The noise data in vertical component records of 85 seismic stations in Fujian Province during 2012 is used as the research object in this paper. The noise data is divided into five- minute segments to calculate the power spectra. The high reference line and low reference line of station are then identified by drawing a probability density function graph （PDF） using the power spectral probability density function. Moreover, according to the anomalies of PDF graphs in 85 seismic stations, the abnormal noise is divided into four categories： dropped packet, low noise, high noise, and median noise anomalies. Afterwards, four selection methods are found by the high or low noise reference line of the stations, and the system of real-time monitoring of seismic noise is formed by combining the four selection methods. Noise records of 85 seismic stations in Fujian Province in July 2013 are selected for verification, and the results show that the anomalous noise-recognition system could reach a 90 % success rate at most stations and the effect of selection are very good. Therefore, it could be applied to the seismic noise real-time monitoring in stations.

关 键 词：Seismic noise Power spectral density Probability density function Powerspectrum Abnormity Data quality 

分 类 号：P315.6[天文地球—地震学]