In this paper, we make a statistical analysis of the fault information of the underground fluid instruments of 12 models in China from January 2021 to May 2022 based on the Pearson correlation coefficient, and compare...In this paper, we make a statistical analysis of the fault information of the underground fluid instruments of 12 models in China from January 2021 to May 2022 based on the Pearson correlation coefficient, and compare the fault statistics of the meteorological three-element instruments of 3 models during the study period. The results show that:(1) The numbers of faults of the underground fluid instruments of 12models with different service times are basically positively correlated with the numbers of the corresponding instruments, with good consistency. Moreover, the automatic observation instruments(8models) with more than 30 units are significantly correlated at a 0.05 significance level(95% confidence level). Even at a 0.01 significance level(99% confidence level), there are 7 models(7/8) with significant correlation.(2) The positive and negative correlations between the monthly average number of faults and the corresponding service times of the underground fluid instruments of 12 models with different service times are random, and there are 9 models(75%) with no significant correlation at a 0.05 significance level(95% confidence level), while 12 models(100%) with no significant correlation at a 0.01significance level(99% confidence level).(3) The monthly average numbers of faults of the underground fluid instruments of 12 models are basically 0.02-0.05 times/(unit·month), and the overall fault frequency is low.(4) The fault statistics results of the meteorological three-element instruments of 3 models are consistent with the characteristics of the underground fluid instruments of 12 models. In general,there is no significant correlation between the fault frequency and the service time of underground fluid instruments.(5) The results of this paper demonstrate that the service time of underground fluid instruments cannot be taken as the main reason for whether to update the instruments. Similarly, the fault frequency of the instruments cannot be taken as the main reason for the service life of the instruments in the process of formulating the service life standards of underground fluid instruments.展开更多
nonlinear magnitude frequency equation has been derived in this paper on the assumption that all seismicity systems hold fractal characteristics, and according to the differences of relevant coefficients in the equati...nonlinear magnitude frequency equation has been derived in this paper on the assumption that all seismicity systems hold fractal characteristics, and according to the differences of relevant coefficients in the equation, seis-micity systems are classified into two types: type I, the whole earthquake activity is controlled by only one great unified system; type II, the whole earthquake activity is controlled by more than one great system. One type of seismicity system may convert to the other type, generally. For example, a type I system will change to a type II system prior to the occurrence of a strong earthquake in North China. This change can be regarded as an index for earthquake trend estimation. In addition, the difference between b value in nonlinear magnitude frequency equation and that in linear equation and the term dΔM related to the coefficients of nonlinear terms obtained in this paper are proved to be a pair of available parameters for medium short term earthquake prediction.展开更多
基金supported by the Science Project for Earthquake Resilience of China Earthquake Administration(XH22020YA).
文摘In this paper, we make a statistical analysis of the fault information of the underground fluid instruments of 12 models in China from January 2021 to May 2022 based on the Pearson correlation coefficient, and compare the fault statistics of the meteorological three-element instruments of 3 models during the study period. The results show that:(1) The numbers of faults of the underground fluid instruments of 12models with different service times are basically positively correlated with the numbers of the corresponding instruments, with good consistency. Moreover, the automatic observation instruments(8models) with more than 30 units are significantly correlated at a 0.05 significance level(95% confidence level). Even at a 0.01 significance level(99% confidence level), there are 7 models(7/8) with significant correlation.(2) The positive and negative correlations between the monthly average number of faults and the corresponding service times of the underground fluid instruments of 12 models with different service times are random, and there are 9 models(75%) with no significant correlation at a 0.05 significance level(95% confidence level), while 12 models(100%) with no significant correlation at a 0.01significance level(99% confidence level).(3) The monthly average numbers of faults of the underground fluid instruments of 12 models are basically 0.02-0.05 times/(unit·month), and the overall fault frequency is low.(4) The fault statistics results of the meteorological three-element instruments of 3 models are consistent with the characteristics of the underground fluid instruments of 12 models. In general,there is no significant correlation between the fault frequency and the service time of underground fluid instruments.(5) The results of this paper demonstrate that the service time of underground fluid instruments cannot be taken as the main reason for whether to update the instruments. Similarly, the fault frequency of the instruments cannot be taken as the main reason for the service life of the instruments in the process of formulating the service life standards of underground fluid instruments.
文摘nonlinear magnitude frequency equation has been derived in this paper on the assumption that all seismicity systems hold fractal characteristics, and according to the differences of relevant coefficients in the equation, seis-micity systems are classified into two types: type I, the whole earthquake activity is controlled by only one great unified system; type II, the whole earthquake activity is controlled by more than one great system. One type of seismicity system may convert to the other type, generally. For example, a type I system will change to a type II system prior to the occurrence of a strong earthquake in North China. This change can be regarded as an index for earthquake trend estimation. In addition, the difference between b value in nonlinear magnitude frequency equation and that in linear equation and the term dΔM related to the coefficients of nonlinear terms obtained in this paper are proved to be a pair of available parameters for medium short term earthquake prediction.