Abstract:Seismic precursor data are easily interfered by noise and the data updating speed in a database is slow. To solve this problem, an information extraction and data updating method of a seismic precursor database based on spatial correlation is proposed in this paper. Using a fast Myriad filter, a sliding window is introduced, and window data are selected to participate in the calculation. The calculated results are regarded as the output value of the current window filter, and the data filtering and denoizing of information extraction is realized. In accordance with the preliminary filtering results, the current data are taken as the center, a spatial window is determined, and then related data statistics are horizontally conducted. A sliding time window is selected for each data in the spatial window, and filling repair parameters of the missing data are obtained. A surface weighting function is introduced to smooth the filling repair parameters, and S-transform data are updated according to the smoothed filling repair parameters. Then, the data updating of the earthquake precursor database is realized based on spatial correlation. The experimental results show that the signal-to-noise ratio of the proposed method is high, and the data update time is short. Thus, the method can preliminarily realize the information extraction and data updating of the earthquake precursor database.
