The Recognized Criteria And Methods Research On Earthquakes And Explosions Identification

In this paper, we reviewed and summarized the research on earthquakes and explosions identification, studied the rapid identification criteria between earthquakes and explosions and multiple characteristics recognition by using pattern recognition methods and matrix decision-making algorithm (MDA). We applied the results of this study to the development of Decision Support System for Recognizing Earthquakes and Explosions system, whose abbreviation is DSSREE, our research builded the three core modules of feature extraction, pattern recognition and decision-making in this system. In addition, we also studied the criteria of wavelet packet, defined and selected the criteria of energy ratios, which are used effectively to identify earthquakes and explosions.1. In order to meet the need of quickly indentifying, we examined5criteria:the first motion polarity of P wave, ratio of first P amplitude and S maximum amplitude Pc/Sm, ratio of P maximum amplitude and S maximum amplitude Pm/Sm, ratio of P maximum amplitude over duration Pm/Tc, ratio of S maximum amplitude over duration Sm/Tc. We defined the rules for first motion polarity criterion and calculated the optimal threshold and the correct recognition rate of single criterion. Among which the Pm/Sm has a best result for classification, the rate of correct recognition rate reaches to92%, the result of first motion polarity and Pc/Sm are followed by, with correct identification rate91%and84%. The results show that the rule we defined for the first motion is effective and these three criteria can reflect the essential difference between earthquakes and explosions, as discrimination indexes in this region on low-magnitude events are more reliable. The Pm/Tc and Sm/Tc criteria related with duration are not very effective for classification in this region, may be influenced by the attenuation law of small magnitude events.2. Combined with the minimum distance method, the ICHAM method, Fisher method of pattern recognition on multi-features recognition, results indicated that the correct recognition rate of Fisher for C-test with5features and3features is97%and 93%, U-test is93%and97%, all the results are higher than the highest correct recognition rate of single criterion; the result of ICHAM is second,3features are better than5features of C-test; the result of minimum distance method is worst, Only three features of the C test result is higher than the maximum correct recognition rate of single criterion; all the results indicated that selected suitable features can improve the correct recognition rate of these3methods. By comparing can be seen, Fisher method is more satisfactory and has a better prospects for application in discrimination.3. By introducing MDA method we identified and tested all events. The rate of correct recognition reaches to97%for C test and93%for U test with5features, this results are consistent with Fisher method which is the best effective one among the3pattern recognition methods; The changes of correct recognition rate among choosing any4of the5criteria show that the first P motion and Pm/Sm play important roles in recognition; Finally we choose4features to make comprehensive decision by discarding Pm/Tc or Pm/Tc, the correct recognition rate of C test and U test is97%and100%. All the results indicated that MDA can be effectively applied to earthquakes and explosions discrimination.4. Based on Wavelet packet transform, we advanced and defined the P/S energy ratios, the results of which show a better application in earthquakes and explosions discrimination.35P/S energy ratios are selected can be applied in practice, through analyzing these35better used P/S energy ratios, we obtained that:the main energy of P concentrate on low-frequency, with nodes [4,2]、[4,3]、[4,6]、[4,7], The corresponding bands are3.125Hz-6.25Hz and9.375Hz-12.5Hz; the main energy of S concentrate on high-frequency, with nodes [4,9] to [4,15], The corresponding bands are14.0625Hz-25Hz; All of these show that the difference between low-frequency of P-wave and high-frequency of S of explosion is greater than earthquake, As a supplement of Wavelet packet criteria, we also extracted the P/P and S/S energy ratios, eventually we selected5P/P energy ratios and15S/S energy ratios for application, the results of which are further supported the conclusion of the P/S energy ratios. The results of energy criteria show that we can extract effective criteria for the identification of earthquakes and explosions through wavelet packet transform. 5. The research on feature extraction, pattern recognition methods, decision-making methods in this paper played a supporting role and are builded the three main modules for DSSREE system. Simultaneously, DSSREE system played the role of practical application for our research in this paper.Rapid, accurate identification of earthquakes and explosions is the requirements of verification emergency. The rapid identification criteria measured in this paper can reflect the essential difference between earthquakes and explosions; Multi-feature recognition using pattern recognition methods and decision-making method can effectively improve the correct recognition rate; Through Wavelet packet transform of the waveform, the different time-frequency characteristics of earthquakes and explosions can be reflected, the energy ratio criteria we defined and extracted can effectively identify the earthquakes and explosions in this region. The results of this article has provided technical support for the DSSREE system, which is designed for rapid and accurate identification of the earthquake and explosions, also have important implications for the preparation of the earthquake catalog、seismic studies and underground nuclear test monitoring.