Information processing device, information processing program, and information processing method

Abstract

To provide an information processing device capable of highly accurately estimating the magnitude and the distance from a ground motion observation location to the earthquake center, even when noise is superimposed on the earthquake motion.SOLUTION: An amplitude calculation unit 21 acquires observed digital data Dg(l*) from a ground motion sensor 10 and calculates an amplitude x(l*) caused by the ground motion. A frequency analysis unit 22 calculates frequency characteristics such as a running spectrum PS(l*,f) from the amplitude x(l*). A magnitude estimation unit 24 estimates the magnitude of an earthquake using the frequency characteristics such as the running spectrum PS(l*,f). A distance estimation unit 25 estimates the distance from a ground motion observation location to the earthquake center using the amplitude x(l*) and the magnitude. By means of the frequency analysis unit 22, the magnitude estimation unit 24, and the distance estimation unit 25, the magnitude and the distance to the earthquake center can be highly accurately estimated even when noise is superimposed on the earthquake motion.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a seismometer that estimates magnitude and distance to an epicenter from a time series of observation data observed by a ground motion sensor. [Background technology]

[0002] Seismometers are devices that can immediately estimate damage immediately after an earthquake occurs and prevent further damage. To estimate damage, seismometers must accurately estimate the magnitude and distance to the epicenter.

[0003] As a method for estimating magnitude and distance to the epicenter, Patent Document 1 discloses a method for estimating magnitude and distance to the epicenter from the growth rate of the initial P-wave motion in observation data. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 3695579 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the technology disclosed in Patent Document 1 has the problem that if noise such as vehicle vibrations is superimposed on the initial P-wave motion, the growth rate of the initial P-wave motion cannot be accurately calculated, and the distance to the epicenter and magnitude may not be accurately estimated.

[0006] The present disclosure aims to provide a seismometer that can accurately estimate the distance to the epicenter and magnitude even when noise such as vehicle vibrations is superimposed on the initial P-wave motion. [Means for solving the problem]

[0007] The information processing device according to the present disclosure includes: an amplitude calculation unit that calculates amplitudes caused by ground motion from observation data observed by the ground motion sensor; a frequency analysis unit that calculates frequency characteristics from the amplitude in real time using an autoregressive model; a magnitude estimation unit that estimates the magnitude of the earthquake that caused the ground motion by using the frequency characteristics; Equipped with. [Effects of the Invention]

[0008] The information processing device according to the present disclosure includes a frequency analysis unit, a magnitude estimation unit, and a distance to the epicenter estimation unit, and therefore can provide a device that can correctly estimate the magnitude of an earthquake and the distance to the epicenter even if noise such as vehicle vibrations is superimposed on the initial P wave motion. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram of the first embodiment, showing the system configuration of a seismometer 30. [Figure 2] FIG. 1 is a functional block diagram of an information processing device 20 according to the first embodiment. [Figure 3] FIG. 1 is a diagram of the first embodiment, and is a flowchart showing the operation of the information processing device 20 in the process of estimating the magnitude and the process of estimating the distance to the epicenter. [Figure 4] 10 is a diagram of the first embodiment, and is another flowchart showing the operation of the information processing device 20 in the process of estimating magnitude and the process of estimating distance to the epicenter. FIG. [Figure 5] FIG. 1 is a diagram of the first embodiment, showing the hardware configuration of an information processing device 20. DETAILED DESCRIPTION OF THE INVENTION

[0010] In the description of the embodiments and drawings, the same elements and corresponding elements are denoted by the same reference numerals. The description of elements denoted by the same reference numerals will be omitted or simplified as appropriate. In the following embodiments, the word "unit" may be appropriately read as "circuit," "process," "step," "processing," or "circuitry."

[0011] The symbols used in the first embodiment are summarized below.

[0012] In the descriptions other than Formula 1 to Formula 14, the lowercase letter l of L will be written as l to distinguish it from the number 1. * It is written as follows.

[0013] <Index and data sent and received> (1)l * :l * is a counter that counts up with each sampling. (2) m:m is the index of the AR model. (3) f: f is frequency (Hz). (4)Dg(l * ):Dg(l * ) is the observed digital data. (5)x(l * ):x(l * ) is the amplitude data in physical units. (6)φS m (l * ):φS m (l * ) are the AR coefficients of the AR model (m = 1, , M). (7)σS 2 (l * ):σS j 2 (l * ) is the variance of the estimation error of the amplitude data by the AR model. (8)PS(l * ,f):PS(l * ,f) is the running spectrum by the AR model. (9)fSd(l * ):fSd(l * ) is the dominant frequency. (10) Mag(l * ):Mag(l * ) is an estimate of the magnitude. (11) Dist(l * ):Dist(l *) is an estimate of the distance to the epicenter.

[0014] <internal variable> (1) μS(l * ):μS(l * ) is the mean from the AR model. (2)CS m (l * ):CSm(l * ) is the covariance function from the AR model (m = 0, , M). (3)xS(l * ):xS(l * ) is the estimated value of the amplitude data by the AR model. (4) Q: Q is the number of characteristic roots of the AR model. (5)zS q (l * ):zS q (l * ) is the characteristic root of the AR model (q = 1, ,Q). (6)fS q (l * ):fS q (l * ) is the peak frequency of the running spectrum by the AR model (q=1, ,Q). (7) PS q (l * ):PS q (l * ) is the peak value of the running spectrum by the AR model (q=1, ,Q).

[0015] <parameters> (1) fs: fs is the sampling frequency (Hz) of the observed digital data. (2) Cf: Cf is the physical value conversion coefficient. (3) M: M is the order of the AR model. (4) rS: rS is the forgetting factor of the AR model. It is a coefficient that determines the window size for smoothing the running spectrum. The larger rS, the smaller the window size, resulting in a short-term average. (5) CMa: CMa is a coefficient 1 for calculating the magnitude estimate. (6) CMb: CMb is the coefficient 2 for calculating the magnitude estimate. (7) CDa: CDa is a coefficient 1 for calculating the estimated distance to the epicenter. (8) CDb: CDb is a coefficient 2 used to calculate the estimated distance to the epicenter. (9) CDc: CDc is a coefficient 3 used to calculate the estimated distance to the epicenter. (10) CDd: CDd is a coefficient 4 for calculating the estimated distance to the epicenter. (11) CDe: CDe is a coefficient 5 used to calculate the estimated distance to the epicenter. (12) CDf: CDf is a coefficient 6 used to calculate the estimated distance to the epicenter. (13) CDg: CDg is a coefficient 7 used to calculate the estimated distance to the epicenter.

[0016] Embodiment 1 A seismometer 30 according to a first embodiment will be described with reference to FIGS.

[0017] ***Configuration Description*** 1 is a system configuration diagram of a seismometer 30. The seismometer 30 includes a ground motion sensor 10 and an information processing device 20. The seismometer 30 is capable of communicating with an external device 40 via a network 50.

[0018] 2 is a block diagram of the information processing device 20. The information processing device 20 includes an amplitude calculation unit 21, a frequency analysis unit 22, a dominant frequency calculation unit 23, a magnitude estimation unit 24, and a distance estimation unit 25 as functional elements.

[0019] ***Explanation of Operation*** 3 is a flowchart showing the operation of the information processing device 20 to estimate the magnitude and distance to the epicenter from the time series of observation data observed by the ground motion sensor 10. The operation of the information processing device 20 will be described with reference to FIG. 3. The operation of the information processing device 20 corresponds to an information processing method. The operation of the information processing method corresponds to processing by an information processing program 231, which will be described later. In FIG. 3, the operation of the information processing device 20 is shown as process P201 to process P205. The information processing device 20 estimates the magnitude and distance to the epicenter from the time series of observation data observed by the ground motion sensor 10. -1 Ground motion is acquired as observed digital data from the ground motion sensor 10 at time intervals of . Ground motion is the vibration of the earth, and the vibration of the earth caused by an earthquake is called "earthquake motion." Hereinafter, the reciprocal (fs) -1 is called the sampling interval. At each sampling, the information processing device 20 performs processing to estimate the magnitude of the earthquake that caused the ground motion and the distance from the installation position of the ground motion sensor 10 to the epicenter.

[0020] <Process P201: Calculate the amplitude of the observed data> (1) The amplitude calculation unit 21 receives the digital data Dg(l) of the ground motion observed by the ground motion sensor 10 from the ground motion sensor 10. * ) is obtained. Observation digital data Dg(l * ) is the ground motion. (2) The amplitude calculation unit 21 calculates the amplitude of the acquired observation digital data Dg(l * ) based on the ground motion amplitude data x(l * The amplitude calculation unit 21 calculates the observed digital data Dg(l * ) to obtain the amplitude data x(l * ) is calculated.

number

[0021] <Process P202: Calculate frequency characteristics> The frequency analysis unit 22 uses an autoregressive model to analyze the amplitude data x(l * ) and calculates the frequency characteristics in real time. Specifically, it is as follows. The frequency analysis unit 22 first analyzes the amplitude data x(l * ) time series is smoothed by time averaging. Next, by expressing it as an autoregressive model, the time-averaged running spectrum of the amplitude data is calculated. Hereinafter, the autoregressive model will be referred to as the AR model. The frequency characteristics are the AR coefficient φS of the AR model shown below. m (l * ), the variance of the estimation error of the amplitude data by the AR model, σS 2 (l * ) and the running spectrum PS(l * , f). In other words, the frequency characteristics include the AR coefficient φS of the AR model. m (l * ), the variance of the estimation error of the amplitude data by the AR model, σS 2 (l * ) and the running spectrum PS(l * ,f) are included. (1) The frequency analysis unit 22 calculates the average μS(l * ) is calculated.

number

number

number

number

number

number

[0022] <Process P203: Calculate the dominant frequency> (1) The dominant frequency calculation unit 23 calculates the amplitude data x(l) from the frequency characteristics calculated by the frequency analysis unit 22. * ) and calculate the dominant frequency of the signal. Specifically, the procedure is as follows: The dominant frequency calculation unit 23 solves the M-th order polynomial (characteristic equation) for z in Equation 8, and identifies the solutions whose imaginary parts are 0 or positive as the characteristic roots zS of the AR model. q (l * ) (q is a sequential number, q=1, ,Q).

number

number

number

[0023] <Process P204: Calculate the estimated magnitude> The magnitude estimation unit 24 estimates the magnitude of the earthquake that caused the ground motion by using the frequency characteristics. The magnitude estimation unit 24 estimates the magnitude by using the dominant frequency calculated by the dominant frequency calculation unit 23. Specifically, the process is as follows. The magnitude estimation unit 24 calculates the estimated magnitude value Mag(l * ) is calculated.

number

[0024] <Process P205: Calculate the estimated distance to the epicenter> The distance estimation unit 25 calculates the amplitude data x(l * ) and magnitude Mag(l * ), the distance Dist from the installation position of the ground motion sensor 10 to the epicenter of the earthquake is estimated. In other words, the installation position of the ground motion sensor 10 is the position where the ground motion was observed. Specifically, the distance estimation unit 25 calculates the distance Mag(l) estimated by Equation 11 as follows. * ) to calculate the distance Dist(l * The position where the ground motion is observed is the installation position of the ground motion sensor 10. In the following, "distance to the epicenter" means "the distance from the position where the ground motion is observed to the epicenter." The distance estimation unit 25 estimates the "distance to the epicenter" Dist(l * ) is calculated.

[0025]

number

[0026] The above-described procedure by the information processing device 20 enables highly accurate estimation of the magnitude and the distance to the epicenter.

[0027] Also, at a certain timing (counter) "l * " In Equation 11, Mag(l * ) and Dist(l * The magnitude estimation unit 24 calculates the calculated Dist(l * ) to DistInit. Timing "l * " At some point after "l ** " and amplitude data x(l ** The magnitude estimation unit 24 estimates the timing "l * "DistInit, timing "l ** " amplitude data x(l ** ) to determine the timing ** "The estimated value Mag(l ** ) can be calculated from Equation 13. The left side of Equation 13 is Mag(l ** ) The x(l) on the right side of Equation 13 is x(l ** )

[0028]

number

[0029] By using Equation 13, the timing ** " in Mag(l ** ) can be estimated more accurately.

[0030] <Modification> 4 is a flowchart showing the operation of a modification of Embodiment 1. The modification will be described with reference to FIG.

[0031] <Process P205a> In Figure 3, Mag(l * ) and then use Equation 12 to calculate Mag(l * ) to Dist(l * In the modified example described with reference to FIG. 4, in process P205a, the distance estimation unit 25 calculates Dist(l * ) is calculated by Equation 14. * ) to Dist(l * ), with the coefficients CMa and CMb replaced by CDf and CDg. That is, in process P205a, the distance estimation unit 25 uses the frequency characteristics to estimate the distance from the installation position of the ground motion sensor 10 to the epicenter of the earthquake that caused the ground motion. The distance estimation unit 25 uses the dominant frequency to estimate the distance from the installation position of the ground motion sensor 10 to the epicenter. Specifically, it is as follows.

[0032]

number

[0033] <Process P204a> Next, in process P204a, the magnitude estimation unit 24 estimates the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor 10 to the epicenter. Specifically, the magnitude estimation unit 24 estimates the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor 10 to the epicenter. * ) and Mag(l * ) is calculated. As mentioned above, Dist(l * ) and then calculate its Dist(l * ) to Mag(l * ) may be calculated.

[0034] As described in Equation 13, in the case of FIG. 4, Dist(l * ) to DistInit, and then use Equation 13 to calculate DistInit, x(l ** ) by Mag(l ** ) may be calculated.

[0035] ***Effects of the First Embodiment*** (1) In the first embodiment, the dominant frequency fSd(l * Therefore, even if noise such as vehicle vibrations, which generally have a dominant frequency different from that of seismic motion, is superimposed on the seismic motion, it is possible to estimate the magnitude and distance to the epicenter with high accuracy. (2) In the first embodiment, DistInit, x(l ** ) to Mag(l ** ), which allows for highly accurate magnitude estimates.

[0036] In the first embodiment, the epicenter distance is assumed to be the distance from the installation position of the ground motion sensor 10 to the epicenter, but other embodiments are possible in which the epicenter distance or the shortest distance to the fault is assumed.

[0037] In addition, in Figure 3, Mag(l* ) and calculate this Mag(l * ) in Equation 12 to find Dist(l * ) was calculated. In the modified example shown in FIG. 4, Dist(l * ) and calculate this Dist(l * ) in Equation 12, Mag(l * ) was calculated. However, not limited to these, Mag(l * ) and Dist(l * ) can also be calculated simultaneously.

[0038] The magnitude estimation unit 24 also calculates the running spectrum PS(l * , f) is used in machine learning such as deep learning to obtain the magnitude value Mag(l * ) features may be learned. That is, the magnitude estimation unit 24 calculates the running spectrum PS(l * ,f) and magnitude value Mag(l * ) as training data, and * ,f) and Mag(l * ) and the magnitude estimation unit 24 learns the correspondence between the new PS(l * ,f) for Mag(l * The distance estimation unit 25 determines the determined Mag(l * ) and use Equation 12 to calculate the distance to the epicenter Dist(l * ) can be calculated. This allows for embodiments that provide highly accurate estimates of magnitude and distance to the epicenter. Alternatively, the distance estimation unit 25 may calculate the running spectrum PS(l * ,f) and the estimated distance Dist(l * ) as training data, and * ,f) and Dist(l * ) and the distance estimation unit 25 learns the correspondence between the new PS(l * ,f) for Dist(l *The magnitude estimation unit 24 can calculate the determined Dist(l * ) and use Equation 12 to obtain Mag(l * ) is calculated. Alternatively, Mag(l) can be calculated by the above-mentioned formulas 11 and 14. * ) and Dist(l * ) simultaneously, the configuration is as follows: That is, the magnitude estimation unit 24 calculates the running spectrum PS(l * ,f) and the magnitude value Mag(l * ) and the estimated distance Dist(l * ) as training data, and * ,f) and Mag(l * ) and Dist(l * ) and learn the correspondence. As a result, the magnitude estimation unit 24 calculates a new PS(l * ,f), Mag(l * ) and Dist(l * ) can be calculated simultaneously. This machine learning may be performed by the distance estimation unit 25 instead of the magnitude estimation unit 24. Alternatively, a learning unit including the magnitude estimation unit 24 and the distance estimation unit 25 may perform this machine learning.

[0039] In addition, zS calculated using Equation 8 to Equation 10 q (l * ), fS q (l * ) and PS q (l * ) is equivalent to the dimension reduction of the running spectrum across all frequencies f, so that all or part of these can be used in machine learning such as deep learning to effectively learn the characteristics of the magnitude value, enabling an embodiment to estimate the magnitude and distance to the epicenter with high accuracy.

[0040] In the first embodiment, the amplitude data x(l *) is assumed to be one of the three spatial components, but embodiments are also possible in which multiple spatial components are used simultaneously or in which function values ​​calculated from multiple spatial components are used.

[0041] Furthermore, in the first embodiment, an autoregressive model is used to calculate the running spectrum in the frequency analysis unit 22, but other methods such as FFT (Fast Fourier Transform) are also possible. For example, the frequency analysis unit 22 calculates the frequency characteristics from the amplitude in real time using other methods such as FFT. Then, the distance estimation unit 25 may use the calculated frequency characteristics to estimate the distance from the installation position of the ground motion sensor 10 to the epicenter of the earthquake that caused the ground motion.

[0042] In addition, the estimated magnitude Mag(l * ) the function forms of Equations 11 and 13 for calculating the distance to the epicenter Dist(l * The function form of Equation 12 for calculating ) may be other than this.

[0043] (Hardware Supplement) 5 shows the hardware configuration of the information processing device 20. The information processing device 20 is a computer. The information processing device 20 includes a processor 210. The information processing device 20 includes, as hardware components, the processor 210, a main storage device 220, an auxiliary storage device 230, and a communication interface 240. The processor 210 is connected to other hardware via a signal line 250 and controls the other hardware.

[0044] The information processing device 20 includes an amplitude calculation unit 21, a frequency analysis unit 22, a dominant frequency calculation unit 23, a magnitude estimation unit 24, and a distance-to-epicenter estimation unit 25. These functions are realized by an information processing program 231.

[0045] The processor 210 is a device that executes an information processing program 231. When the processor 210 executes the information processing program 231, the functions of an amplitude calculation unit 21, a frequency analysis unit 22, a dominant frequency calculation unit 23, a magnitude estimation unit 24, and a distance-to-epicenter estimation unit 25 are realized. The processor 210 is an integrated circuit (IC) that performs arithmetic processing.

[0046] A specific example of the main memory device 220 is an SRAM (Static Random Access Memory). The main memory 220 stores the results of calculations performed by the processor 210.

[0047] The auxiliary storage device 230 is a storage device that stores data in a non-volatile manner. A specific example of the auxiliary storage device 230 is a hard disk drive (HDD). The auxiliary storage device 230 may also be a portable recording medium. The auxiliary storage device 230 stores an information processing program 231.

[0048] The communication interface 240 is a communication port that allows the processor 210 to communicate with other devices. The communication interface 240 is connected to a network 50.

[0049] The processor 210 loads the information processing program 231 from the auxiliary storage device 230 into the main storage device 220. The processor 210 reads the loaded information processing program 231 from the main storage device 220 and executes it.

[0050] The information processing program 231 is a program that causes a computer to execute each process, each procedure, or each step, where each "unit" of the information processing device 20 is replaced with a "process," a "procedure," or a "step."

[0051] Furthermore, a method performed by the information processing device 20, which is a computer, executing the information processing program 231 is an information processing method. The information processing program 231 may be provided by being stored in a computer-readable recording medium, or may be provided as a program product. [Explanation of symbols]

[0052] 10 ground motion sensor, 20 information processing device, 21 amplitude calculation unit, 22 frequency analysis unit, 23 dominant frequency calculation unit, 24 magnitude estimation unit, 25 distance estimation unit, 30 seismometer, 40 external device, 50 network, 210 processor, 220 main memory device, 230 auxiliary memory device, 231 information processing program, 240 communication interface, 250 signal line.

Claims

1. an amplitude calculation unit that calculates amplitudes caused by ground motion from observation data observed by the ground motion sensor; a frequency analysis unit that calculates frequency characteristics from the amplitude in real time using an autoregressive model; a dominant frequency calculation unit that calculates a dominant frequency of the amplitude from the frequency characteristics; a magnitude estimation unit that estimates the magnitude of the earthquake that caused the ground motion by using the dominant frequency; a distance estimation unit that estimates a distance from an installation position of the ground motion sensor to the epicenter of the earthquake based on the amplitude and the magnitude; An information processing device comprising:

2. On the computer, an amplitude calculation process for calculating amplitudes caused by ground motion from observation data observed by the ground motion sensor; a frequency analysis process for calculating frequency characteristics from the amplitude in real time using an autoregressive model; a dominant frequency calculation process for calculating a dominant frequency of the amplitude from the frequency characteristics; a magnitude estimation process for estimating the magnitude of the earthquake that caused the ground motion by using the dominant frequency; a distance estimation process for estimating a distance from an installation position of the ground motion sensor to an epicenter of the earthquake based on the amplitude and the magnitude; An information processing program that executes the above.

3. The computer The amplitude caused by ground motion is calculated from the observation data obtained by the ground motion sensor. Calculating frequency characteristics from the amplitude in real time using an autoregressive model; calculating a dominant frequency of the amplitude from the frequency characteristics; using the dominant frequency to estimate the magnitude of the earthquake causing the ground motion; Based on the amplitude and the magnitude, a distance from the installation position of the ground motion sensor to the epicenter of the earthquake is estimated. Information processing methods.

4. an amplitude calculation unit that calculates amplitudes caused by ground motion from observation data observed by the ground motion sensor; a frequency analysis unit that calculates frequency characteristics from the amplitude in real time; a dominant frequency calculation unit that calculates a dominant frequency of the amplitude from the frequency characteristics; a distance estimation unit that estimates the distance from the installation position of the ground motion sensor to the epicenter of the earthquake that causes the ground motion by using the dominant frequency; An information processing device comprising:

5. The frequency analysis unit The information processing apparatus according to claim 4 , wherein the frequency characteristics are calculated in real time from the amplitude using an autoregressive model.

6. the amplitude calculation unit calculates a time series of the amplitude from the time series of the observation data; the frequency analysis unit calculates a running spectrum of the amplitude in the time series as the frequency characteristic using an autoregressive model; The dominant frequency calculation unit determines a frequency corresponding to a maximum peak value of the running spectrum as the dominant frequency fSd, The distance estimation unit estimates the distance Dist by calculating f(fSd, Dist)=0 using an arbitrary function f(fSd, Dist) of the dominant frequency fSd and the distance Dist.

6. The information processing device according to claim 4.

7. the amplitude calculation unit calculates a time series of the amplitude from the time series of the observation data; the frequency analysis unit calculates a running spectrum of the amplitude in the time series as the frequency characteristic using an autoregressive model; The dominant frequency calculation unit determines a frequency corresponding to a maximum peak value of the running spectrum as the dominant frequency fSd, The distance estimation unit estimates the distance Dist by calculating Dist=CDf×log(fSd)+CDg using the dominant frequency fSd, the coefficients CDf and CDg.

6. The information processing device according to claim 4.

8. The information processing device further comprises: a magnitude estimation unit that estimates the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor to the epicenter; The information processing device according to claim 4 or claim 5, comprising:

9. The information processing device further comprises: a magnitude estimation unit that estimates the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor to the epicenter; The information processing device according to claim 6 , comprising:

10. The information processing device further comprises: a magnitude estimation unit that estimates the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor to the epicenter; The information processing device according to claim 7 , comprising:

11. On the computer, an amplitude calculation process for calculating amplitudes caused by ground motion from observation data observed by the ground motion sensor; a frequency analysis process for calculating frequency characteristics from the amplitude in real time; a dominant frequency calculation process for calculating a dominant frequency of the amplitude from the frequency characteristics; a distance estimation process for estimating a distance from an installation position of the ground motion sensor to an epicenter of an earthquake that causes the ground motion by using the dominant frequency; An information processing program that executes the above.

12. The frequency analysis process includes: The information processing program according to claim 11, wherein the frequency characteristics are calculated in real time from the amplitude using an autoregressive model.

13. the amplitude calculation process calculates a time series of the amplitude from a time series of the observation data; the frequency analysis process calculates a running spectrum of the amplitude in the time series as the frequency characteristic using an autoregressive model; The dominant frequency calculation process determines a frequency corresponding to a maximum peak value of the running spectrum as the dominant frequency fSd, The distance estimation process estimates the distance Dist by calculating f(fSd, Dist)=0 using an arbitrary function f(fSd, Dist) of the dominant frequency fSd and the distance Dist.

13. The information processing program according to claim 11 or 12.

14. the amplitude calculation process calculates a time series of the amplitude from a time series of the observation data; the frequency analysis process calculates a running spectrum of the amplitude in the time series as the frequency characteristic using an autoregressive model; The dominant frequency calculation process determines a frequency corresponding to a maximum peak value of the running spectrum as the dominant frequency fSd, The distance estimation process estimates the distance Dist by calculating Dist=CDf×log(fSd)+CDg using the dominant frequency fSd, the coefficients CDf and CDg.

13. The information processing program according to claim 11 or 12.

15. The information processing program The computer further comprises: a magnitude estimation process for estimating the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor to the epicenter; 13. The information processing program according to claim 11, wherein the information processing program executes the following:

16. The information processing program The computer further comprises: a magnitude estimation process for estimating the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor to the epicenter; The information processing program according to claim 13, wherein the information processing program executes the following:

17. The information processing program The computer further comprises: a magnitude estimation process for estimating the magnitude of the earthquake based on the amplitude and the distance from the installation position of the ground motion sensor to the epicenter; 15. The information processing program according to claim 14, which causes the program to execute the following:

18. The computer The amplitude caused by ground motion is calculated from the observation data obtained by the ground motion sensor. Calculating frequency characteristics in real time from the amplitude; calculating a dominant frequency of the amplitude from the frequency characteristics; Using the dominant frequency, a distance from the installation position of the ground motion sensor to the epicenter of the earthquake that caused the ground motion is estimated. Information processing methods.

Images