S-wave prediction method, prediction system, computer, and computer program for continuously predicting S-wave intensity

Abstract

To provide an S-wave prediction method capable of continuously predicting S-wave intensity at an earlier point in time even when the S-wave intensity gradually increases with the lapse of time. [Solution] Each time seismic motion is observed, multiple real-time S-wave intensities are calculated using each of the three acceleration components measured at one or more observation points, the calculated multiple real-time S-wave intensities are sent to a communications network, and at an evaluation point where the S-wave intensity is predicted, the multiple real-time S-wave intensities are obtained from the communications network, and multiple predicted S-wave intensities at the evaluation point are calculated based on the obtained multiple real-time S-wave intensities and distance attenuation. Each time each of the multiple predicted S-wave intensities is calculated, it is determined whether the calculated predicted S-wave intensity is greater than the maximum value of the multiple predicted S-wave intensities previously calculated, and if the calculated predicted S-wave intensity is greater than the maximum value, the calculated S-wave intensity is output as the maximum predicted S-wave intensity at the evaluation point.

Description

[Technical field]

[0001] The present invention relates to a technology for predicting the intensity of seismic motion, and more specifically, to a technology in which an observation point transmits the three acceleration components or real-time S-wave intensity of observed seismic motion to a communication network, and at an evaluation point where the impact of seismic motion is evaluated, the predicted S-wave intensity at the evaluation point is continuously predicted at an earlier point in time based on the real-time S-wave intensity calculated using the three acceleration components obtained from the communication network, or the real-time S-wave intensity obtained from the communication network and distance attenuation. [Background technology]

[0002] It is extremely difficult to predict the occurrence of an earthquake. For this reason, earthquake early warning systems have been proposed that calculate the time of occurrence, epicenter location, and magnitude of an earthquake based on observational information of seismic motion observed at many seismological observation points immediately after the occurrence of an earthquake, and then notify areas that have not yet reached the earthquake of the predicted arrival time and intensity of the main shock based on this information.

[0003] The applicant of the present application has already proposed the techniques disclosed in Patent Document 1 and Patent Document 2. The earthquake warning system disclosed in Patent Document 1 is configured to install three or more seismometers within the premises of a building or business, detect and determine P-waves based on a correlation coefficient between data signals measured by these seismometers, predict the strength of S-waves based on the P-wave data received from the P-wave detection point, and issue an alert based on this.

[0004] The earthquake motion detection and prediction system disclosed in Patent Document 2 is configured to detect P-waves that generate pre-tremors, and to predict S-waves that generate primary motion based on the detected P-waves. This system has a P-wave detection device, which calculates a standard deviation using real-time measurement data when an earthquake occurs, and compares it with a threshold value calculated from real-time measurement data under normal conditions to determine whether a P-wave has been detected. This system also has an S-wave prediction device that predicts S-waves based on the P-waves. This system makes it possible to quickly and accurately detect P-waves that generate pre-tremors. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 6887310 [Patent Document 2] Patent No. 7109120 Summary of the Invention [Problem to be solved by the invention]

[0006] Currently, the Japan Meteorological Agency uses the PLUM (Propagation of Local Undamped Motion) method to obtain information on S-waves that are expected to reach a certain observation point. The PLUM method differs from the previously used IPF (Integrated Particle Filter) method in that it predicts seismic intensity based on observed real-time seismic intensity without using any hypocenter factors, and is said to be able to make appropriate seismic intensity predictions in real time when a major earthquake occurs. A hybrid method combining the IPF and PLUM methods is also in use.

[0007] In the PLUM method, the S-waves cannot be predicted at the point where the intensity of the S-waves is evaluated (evaluation point) until the S-waves reach the Japan Meteorological Agency's observation point, which is located away from the evaluation point. From the viewpoint of the evaluation point, the arrival and intensity of the S-waves are only known when the S-waves reach the observation point. For example, if the speed of the S-waves is 4km / s and the observation point is located 30km away from the evaluation point, the grace period is only about 7 seconds. In addition, since the evaluation point uses the S-wave intensity observed at the observation point without attenuation, it may observe an intensity greater than the intensity that actually arrives. Furthermore, although the Japan Meteorological Agency's observation point observes S-waves in real time, the data is first sent to the Japan Meteorological Agency, where it is processed to be incorporated into a telegram before being distributed, so there is inevitably a risk of a time lag occurring between the occurrence of the earthquake and the issuance of the alert.

[0008] The present invention aims to provide an S-wave prediction method and an S-wave prediction system that can continuously predict S-wave intensity close to the actual intensity at an earlier point in time at an evaluation point distant from the observation point where seismic motion was observed, even when the S-wave intensity gradually increases over time. [Means for solving the problem]

[0009] The present invention provides an S-wave prediction method for continuously predicting the intensity of S-waves that reach an evaluation point when an earthquake occurs. In one embodiment of this method, real-time S-wave intensity is calculated using three acceleration components measured at an observation point of seismic motion, and the calculated real-time S-wave intensity is sent to a communication network. At the evaluation point where the S-wave intensity is predicted, the real-time S-wave intensity is acquired from the communication network, and the predicted S-wave intensity is calculated based on the real-time S-wave intensity and distance attenuation.

[0010] In this aspect, the method includes the steps of observing seismic motion at one or more of a plurality of observation points at which seismic motion can be observed, calculating a plurality of real-time S-wave intensities using each of a plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured at the one or more observation points each time seismic motion is observed, and transmitting the calculated plurality of real-time S-wave intensities to a communication network. The method further includes the steps of acquiring a plurality of real-time S-wave intensities from the communication network at an evaluation point at which the intensity of an S-wave is predicted among the plurality of observation points, and calculating a plurality of predicted S-wave intensities at the evaluation point based on the acquired plurality of real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point. The method further includes the steps of determining, each time each of the plurality of predicted S-wave intensities is calculated, whether the calculated predicted S-wave intensity is greater than the maximum value among the plurality of predicted S-wave intensities previously calculated, and, if the calculated predicted S-wave intensity is greater than the maximum value, outputting the calculated S-wave intensity as the maximum predicted S-wave intensity at the evaluation point.

[0011] In another aspect, the method includes transmitting three acceleration components measured at an observation point of seismic motion to a communication network. At an evaluation point where S-wave intensity is predicted, the three acceleration components are acquired from the communication network, real-time S-wave intensity is calculated using the acquired three acceleration components, and predicted S-wave intensity is calculated based on the real-time S-wave intensity and distance attenuation.

[0012] In this aspect, the method includes the steps of observing seismic motion at one or more of a plurality of observation points at which seismic motion can be observed, and transmitting a plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured at the one or more observation points to a communication network each time seismic motion is observed. The method further includes the steps of acquiring a plurality of three acceleration components from the communication network at an evaluation point at which S-wave intensity is predicted among the plurality of observation points, calculating a plurality of real-time S-wave intensities using each of the acquired plurality of three acceleration components, and calculating a plurality of predicted S-wave intensities at the evaluation point based on the calculated plurality of real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point. The method further includes the steps of determining, each time each of the plurality of predicted S-wave intensities is calculated, whether the calculated predicted S-wave intensity is greater than the maximum value among the plurality of predicted S-wave intensities previously calculated, and, if the calculated predicted S-wave intensity is greater than the maximum value, outputting the calculated predicted S-wave intensity as the maximum predicted S-wave intensity at the evaluation point.

[0013] The present invention further provides an S-wave prediction system that continuously predicts the intensity of S-waves that reach an evaluation point when an earthquake occurs. In one embodiment, the system includes a communication network, a seismometer disposed at each of a plurality of observation points that can observe seismic motion, and a plurality of computers disposed at each of the plurality of observation points, connected to the seismometer, and connected to each other through the communication network. One of the plurality of computers or a computer at each of the observation points is configured to calculate a plurality of real-time S-wave intensities using each of a plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured by the seismometer each time the seismometer observes seismic motion, and to transmit the calculated real-time S-wave intensities to the communication network. Among the multiple computers, a computer at the evaluation point that predicts the intensity of S waves is configured to acquire multiple real-time S-wave intensities from a communication network, calculate multiple predicted S-wave intensities at the evaluation point based on the acquired multiple real-time S-wave intensities and the distance attenuation between the epicenter and the evaluation point, and each time it calculates each of the multiple predicted S-wave intensities, determine whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensities previously calculated, and if the calculated predicted S-wave intensity is greater than the maximum value, output the calculated predicted S-wave intensity as the maximum predicted S-wave intensity at the evaluation point.

[0014] In another aspect, the system includes a communication network, a seismometer disposed at each of a plurality of observation points capable of observing seismic motion, and a plurality of computers disposed at each of the plurality of observation points and connected to the seismometer and connected to each other through the communication network. One of the plurality of computers or a computer at each of the observation points is configured to transmit a plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured by the seismometer to the communication network each time the seismometer observes seismic motion. Among the multiple computers, a computer at an evaluation point which predicts the intensity of S-waves is configured to acquire multiple three components of acceleration from a communications network, calculate multiple real-time S-wave intensities using each of the acquired multiple three components of acceleration, calculate multiple predicted S-wave intensities at the evaluation point based on the calculated multiple real-time S-wave intensities and the distance attenuation between the epicenter and the evaluation point, and each time it calculates each of the multiple predicted S-wave intensities, determine whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensities previously calculated, and if the calculated predicted S-wave intensity is greater than the maximum value, output the calculated predicted S-wave intensity as the maximum predicted S-wave intensity at the evaluation point.

[0015] In yet another aspect, the present invention provides a computer constituting an S-wave prediction system that continuously predicts the intensity of S-waves that reach an evaluation point when an earthquake occurs. The computer is disposed at each of a plurality of observation points that can observe seismic motion, and is connected to a seismometer disposed at each of the plurality of observation points, and is also connected to each other through a communication network. The computer is configured to calculate a plurality of real-time S-wave intensities using each of a plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured by the seismometer, and to transmit a plurality of the three acceleration components or a plurality of real-time S-wave intensities to the communication network. The computer is further configured to acquire multiple three acceleration components or multiple real-time S-wave intensities from a communication network, calculate multiple predicted S-wave intensities at the evaluation point based on the multiple real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point, and each time it calculates each of the multiple predicted S-wave intensities, determine whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensities previously calculated, and if the calculated predicted S-wave intensity is greater than the maximum value, output the calculated predicted S-wave intensity as the maximum predicted S-wave intensity at the evaluation point.

[0016] In yet another aspect, the present invention provides a computer program for continuously predicting the intensity of S waves arriving at an evaluation point when an earthquake occurs. Effect of the Invention

[0017] According to the present invention, the intensity of the three acceleration components or S-waves observed at the observation point closest to the epicenter away from the evaluation point can be obtained from the communication network at the evaluation point, so that the intensity of the S-waves at the evaluation point can be known more quickly than with conventional methods. Also, the intensity of the S-waves at the evaluation point can be calculated based on the distance attenuation between the epicenter and the evaluation point, so that the intensity of the arriving S-waves can be predicted more accurately.

[0018] Furthermore, even in earthquakes where the epicenter moves over time due to rock destruction or the strength of S-waves at the observation point gradually increases, it is possible to predict the strength of S-waves at the evaluation point continuously and without missing any changes. At the evaluation point, the predicted strength of S-waves can be used to issue warnings and stop equipment such as elevators early on. [Brief description of the drawings]

[0019] [Figure 1] FIG. 1 is a schematic diagram showing an example of installation of a main system in an S wave prediction system according to one embodiment of the present invention. [Diagram 2] This is a diagram showing an image of the installation of the main system in the S wave prediction system. [Figure 3A] FIG. 1 is a block diagram showing an overview of an S wave prediction system. [Figure 3B] FIG. 2 is a block diagram showing the functions of a data processing unit of the main system. [Figure 4] 1 is a flowchart of basic processing in an S wave prediction system according to one embodiment of the present invention. [Diagram 5] 1 is a flowchart of a process for calculating real-time S-wave intensity SOB at an observation point according to one embodiment of the present invention. [Figure 6] 1 is a flowchart of a process for calculating predicted S-wave intensity K at an evaluation point according to one embodiment of the present invention. [Figure 7] 13 is a flowchart showing basic processing in an S wave prediction system according to another embodiment of the present invention. [Figure 8] 13 is a flowchart of a process for calculating real-time S-wave intensity SOB at an evaluation point according to another embodiment of the present invention. [Figure 9] 13 is a flowchart of a process for calculating predicted S-wave intensity K at an evaluation point according to another embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The present invention provides an S-wave prediction method and an S-wave prediction system for continuously predicting the intensity of S-waves (secondary waves) that arrive at an evaluation point when an earthquake occurs. In this system, the three acceleration components or real-time S-wave intensity of seismic motion observed at the observation point of the seismic source or an observation point nearby the seismic source are sent to a communication network, and the information is acquired from the communication network at other observation points (referred to as evaluation points) that predict the intensity of S-waves. This makes it possible to obtain the predicted S-wave intensity at the evaluation point before the actual S-wave arrives, even at evaluation points far from the seismic source. At the evaluation point, a more accurate predicted S-wave intensity can be calculated by applying distance attenuation to the real-time S-wave intensity calculated using the three acceleration components acquired from the communication network or the real-time S-wave intensity acquired from the communication network. In addition, even when the seismic motion observed at the observation point changes significantly, the maximum value of the predicted S-wave intensity at the evaluation point is always obtained, so that the S-wave intensity can be predicted at the evaluation point continuously and without missing any changes in response to the change in seismic motion.

[0021] [Outline of the S-wave prediction system] FIG. 1 is a schematic diagram showing an example of installation of one observation point in an S-wave prediction system 1 according to an embodiment of the present invention. In the S-wave prediction system 1, three seismometers are installed in a building or on the premises of a business establishment, and S-wave intensity can be obtained based on measurement data from these three seismometers, i.e., three acceleration components (acceleration x in the east-west direction, acceleration y in the north-south direction, and acceleration z in the up-down direction). In this embodiment, an example is shown in which three seismometers, consisting of a first seismometer 101, a second seismometer 102, and a third seismometer 103, are installed as shown in FIG. 1, but the present invention is not limited to this, and the number of seismometers installed may be two or four or more as long as it is more than one. However, when a majority vote is performed using multiple seismometers to detect seismic waves, it is preferable that the number of seismometers is an odd number.

[0022] In this specification, the S-wave intensity calculated using the three components of acceleration measured by a seismometer is referred to as "real-time S-wave intensity SOB (Seismic Observation)," and the intensity of the S-wave predicted at the evaluation point is referred to as "predicted S-wave intensity K." Real-time S-wave intensity SOB does not necessarily have to be calculated at the observation point where the seismic motion is observed, and may be calculated at the evaluation point where the predicted S-wave intensity K needs to be known, using the three components of acceleration measured by a seismometer at the observation point where the seismic motion is observed.

[0023] In this embodiment, an example is shown in which the first seismometer 101 and the second seismometer 102 are installed inside a building, and the third seismometer 103 is installed on the site to which the building belongs, but the installation method is not limited to this. However, it is preferable that the three seismometers are installed at a certain distance apart on the site to which the building belongs (including inside the building). If the seismometers are placed close to each other, for example, the vibrations of a truck traveling on a nearby road may be measured by the multiple seismometers, which may interfere with seismic wave detection. The appropriate distance between the seismometers is appropriately set depending on the building and site to which the seismometers are installed, but is expected to be, for example, about 30 m to 100 m.

[0024] When multiple seismometers are installed, there is no particular restriction on which seismometer's measurement data should be used. For example, the measurement data from multiple seismometers can be compared, and the measurement data from the seismometer with the middle noise level during normal times can be used. Alternatively, the real-time S-wave intensity SOB with the middle value can be used among the real-time S-wave intensity SOBs calculated using the three acceleration components of each seismometer.

[0025] In the S-wave prediction system 1, the first seismometer 101, the second seismometer 102, the third seismometer 103, and the system that processes the data measured by these seismometers are referred to as the main system 100. Fig. 2 is a diagram showing an installation image of the main system 100 of the S-wave prediction system 1 according to the embodiment of the present invention, and shows a state in which the main system 100 is installed at points A, B, C, .... Each point where the main system 100 is installed is an observation point for S-waves and also an evaluation point for predicting the intensity of S-waves.

[0026] In the S-wave prediction system 1 of this embodiment, the main systems 100 are arranged in various locations as described above, and each main system 100 is configured to be able to communicate with each other via a communication network. Therefore, the main system 100 that observes seismic motion is configured to be able to transmit information on the observed seismic motion to the other main systems 100. At this time, each main system 100 can calculate real-time S-wave intensity SOB using measurement data measured by the three seismometers 101, 102, and 103, making it possible to quickly obtain highly accurate S-wave intensity.

[0027] Fig. 3A is a block diagram showing an overview of the S-wave prediction system 1, and shows, for example, a state in which multiple main systems 100A, 100B, 100C, ..., 100X are connected to one another via a communication network N. In Fig. 3A, main systems installed at points A, B, C, ..., and X are designated as 100A, 100B, 100C, ..., and 100X, respectively. These systems have similar configurations, so only one main system 100A will be described here.

[0028] The main system 100A used in the S-wave prediction system 1 has a first seismometer 101, a second seismometer 102, and a third seismometer 103 that are installed at an appropriate distance apart at one point. Data measured by the first seismometer 101, the second seismometer 102, and the third seismometer 103 are transmitted to a data processing unit 110. The data processing unit 110 in the main system 100A can be realized by a general-purpose computer (information processing device) that includes a CPU, a ROM that holds program instructions that run on the CPU, and a RAM that is a work area for the CPU. The data measured by the first seismometer 101, the second seismometer 102, and the third seismometer 103 is processed by the data processing unit 110.

[0029] 3B is a block diagram showing the functions of the data processing unit 110. The data processing unit 110 has a real-time S-wave intensity (SOB) calculation unit, a real-time S-wave intensity (SOB) judgment unit, a predicted S-wave intensity (K) calculation unit, and a maximum predicted S-wave intensity judgment unit. The detailed functions of each unit will be described later. The data processing unit 110 operates in cooperation with each component connected to the data processing unit 110 shown in the figure. In addition, various control processes in the S-wave prediction system 1 are realized by a CPU (not shown) executing program instructions stored and held in a storage means (not shown) such as a ROM or RAM in the data processing unit 110.

[0030] Returning to FIG. 3A, the data processing unit 110 is connected to a storage unit 120 such as a hard disk or a solid state drive. The storage unit 120 can store computer programs necessary for the operation of the S-wave prediction system 1, initial data, data at the time of intermediate processing, facility information (facility name, location information (latitude, longitude), etc.), and site information (average fault depth, ground amplification, fault depth, etc.), and the data processing unit 110 can arbitrarily access the storage unit 120 to retrieve various data from the storage unit 120 or store them in the storage unit 120. The computer programs necessary for the operation of the S-wave prediction system 1 include program instructions for causing a computer to execute all the steps of processing in the S-wave prediction system described below.

[0031] The data processing unit 110 is also connected to a communication unit 150 that enables wireless or wired communication with the outside. The communication unit 150 is capable of transmitting data transferred from the data processing unit 110 to the main systems 100B, 100C, ..., 100X other than the main system 100A via an external communication network N. The communication unit 150 is also capable of receiving data transmitted from the main systems 100B, 100C, ..., 100X other than the main system 100A via the external communication network N, and transmitting the received data to the data processing unit 110. The main system 100A further includes an alarm unit 130, which can output an alarm according to the level of the predicted S-wave intensity K as necessary.

[0032] (First embodiment) [Processing in S-wave prediction system] Next, a description will be given of the processing in the S-wave prediction system 1 according to the first embodiment. The S-wave prediction system 1 can observe earthquake motion, calculate real-time S-wave intensity SOB at the epicenter or an observation point nearby, and calculate predicted S-wave intensity K at an evaluation point based on the real-time S-wave intensity SOB of the earthquake motion that has occurred.

[0033] Fig. 4 is a diagram showing a flowchart of processing in the S-wave prediction system 1. Fig. 4(a) shows processing of a main system 100 (e.g., main system 100A) at an observation point that observes seismic motion at or near the epicenter and calculates real-time S-wave intensity SOB, among the multiple main systems 100, and Fig. 4(b) shows processing of a main system 100 (main systems 100B, 100C, ..., 100X) at an evaluation point that predicts S-wave intensity based on the real-time S-wave intensity SOB sent by the main system 100. All of the main systems 100A, 100B, 100C, ..., 100X constituting the S-wave prediction system 1 can execute the processing of Fig. 4(a) and Fig. 4(b).

[0034] When functioning as an S-wave observation device, the main system 100 can execute the process of Fig. 4(a). That is, the main system 100 observes seismic motion at the epicenter or an observation point nearby (S4a-2), calculates real-time S-wave intensity SOB using the three acceleration components measured (S4a-3), compares the real-time S-wave intensity SOB with a threshold value TH as necessary (S4a-4, S4a-5), and transmits the real-time S-wave intensity SOB to the communication network N (S4a-6).

[0035] In a huge earthquake, the bedrock may break over time, and the epicenter may move. In the case of an earthquake in which the epicenter moves, the observation point for observing the S-waves may also move to another observation point as the epicenter moves. Therefore, in the present invention, as the epicenter moves, the real-time S-wave intensity SOB may be calculated at one or more observation points other than the observation point at which the initial real-time S-wave intensity SOB was calculated, and the real-time S-wave intensity SOB may be transmitted from these observation points to the communication network N.

[0036] When the main system 100 functions as an S-wave intensity prediction device, it can execute the process of Fig. 4(b). That is, the main system 100 acquires real-time S-wave intensity SOB from the communication network N (S4b-2), calculates predicted S-wave intensity K at the evaluation point (S4b-3), and stores the maximum value of the calculated predicted S-wave intensity K as the maximum predicted S-wave intensity K (S4b-4, S4b-5).

[0037] (Calculation of real-time S-wave intensity at observation points) 5 is a flowchart of the process of calculating real-time S-wave intensity SOB in the main system 100 at the observation point of seismic motion. When seismic motion is observed in the main system 100 at or near the epicenter, the main system 100 calculates real-time S-wave intensity SOB by the real-time S-wave intensity (SOB) calculation section of the data processing section 110 using data measured by the seismometers 101, 102, 103 (S5-1). The real-time S-wave intensity SOB can be calculated using three acceleration components (acceleration x in the east-west direction, acceleration y in the north-south direction, and acceleration z in the up-down direction) measured by the seismometers 101, 102, 103. More preferably, the three acceleration component data x, y, z are each drift-corrected (S5-2), and the elementary section average value x is calculated from the drift-corrected data. s , y s , z s is obtained (S5-3). Drift correction can be performed by a method known to those skilled in the art. The real-time S-wave intensity SOB is calculated as x s , y s , z s Using this, it can be calculated using the following formula (1) (S5-4).

number

[0038] Here, in the present invention, it is preferable to use a plurality of real-time measurement data measured by a seismometer by averaging them at a certain time interval, and the certain time interval is called a "primary interval." By averaging and handling a plurality of real-time measurement data acquired over one elementary interval, rather than the real-time measurement data of the seismometer itself, it is possible to reduce the variation in real-time S-wave intensity SOB that may occur due to data fluctuations when the real-time measurement data is processed as is, and to realize high-speed and high-precision prediction. From the viewpoint of measurement reliability, the size of one elementary interval is preferably 0.05 seconds to 0.2 seconds, but is not limited thereto. If the size of the elementary interval is small, the number of real-time measurement data to be averaged is small, and fluctuations in each real-time measurement data are more likely to affect the accuracy of the S-wave intensity. On the other hand, if the size of the elementary interval is large, the number of real-time measurement data included in the elementary interval is large, which increases the processing time, and may result in a long calculation time for the S-wave intensity. For example, if the size of the elementary interval is 0.1 seconds and the sampling frequency of the seismometer is 100 Hz, the number of real-time measurement data in one elementary interval is 10, and if the size of the elementary interval is 0.05 seconds and the sampling frequency of the seismometer is 100 Hz, the number of real-time measurement data in one elementary interval is 5.

[0039] (Comparison of S-wave intensity at observation points with thresholds and data transmission) Returning to Fig. 4, if the real-time S-wave intensity SOB observed first after the occurrence of seismic motion is taken as SOB0, the determined real-time S-wave intensity SOB0 is preferably compared with a predetermined threshold value TH in a real-time S-wave intensity (SOB) determination unit of the data processing unit 110 (S4a-4). If the real-time S-wave intensity SOB0 is greater than the threshold value TH, the real-time S-wave intensity SOB0 is transmitted to the communication network N. In another embodiment, the real-time S-wave intensity SOB0 may be transmitted to the communication network N without being compared with the threshold value TH.

[0040] The threshold value TH can be appropriately determined in advance by the provider or user of the S-wave prediction system 1 and stored in an appropriate location. If comparison with the threshold value TH is not performed or if the threshold value TH is too small, the real-time S-wave intensity SOB is frequently sent to the network N, which may cause network congestion and hinder prediction of the S-wave intensity at the evaluation point. If the threshold value TH is too large, seismic motion that may cause serious damage at the evaluation point may be overlooked, and appropriate prediction of the S-wave intensity may not be possible.

[0041] (Acquisition of real-time S-wave intensity at evaluation points and calculation of predicted S-wave intensity) The main system 100 at the evaluation point where the S-wave intensity should be predicted can calculate the predicted S-wave intensity K using the real-time S-wave intensity SOB acquired from the communication network N. Figure 6 is a flowchart of the process of calculating the predicted S-wave intensity K in the main system 100 at the evaluation point.

[0042] The main system 100 at the evaluation point acquires real-time S-wave intensity SOB from the communication network N (S6-1). The main system 100 acquires real-time S-wave intensity SOB0 of the S-wave first observed at the observation point after the occurrence of seismic motion from the communication network N, and calculates the predicted S-wave intensity K0 at the evaluation point using the real-time S-wave intensity SOB0 in the predicted S-wave intensity calculation section of the data processing section 110. The predicted S-wave intensity K0 at the evaluation point is calculated based on the distance attenuation between the epicenter and the evaluation point using the acquired real-time S-wave intensity SOB0 (S6-5). The distance attenuation is calculated using the following distance attenuation formula (2) (S6-4). The distance attenuation formula is determined in advance and stored in the memory section, or is incorporated in the program in advance.

number

[0043] Here, to calculate the attenuation over distance, information on the epicenter, i.e., information on the distance from the evaluation point to the epicenter, is required. The information on the epicenter is included in the telegram of the Earthquake Early Warning (EEW) from the Japan Meteorological Agency. Therefore, if the main system 100 at the evaluation point can obtain the EEW (S6-2), the attenuation over distance can be calculated using the information on the epicenter included in the EEW.

[0044] If the main system 100 at the evaluation point is unable to acquire the EEW for some reason, the main system 100 acquires the position of the observation point (S6-3). Distance attenuation is calculated assuming that the epicenter is below the main system 100 that observed the SOB used. This allows the evaluation point to immediately calculate a predicted S-wave intensity K0 that takes distance attenuation into account. Possible cases in which the EEW cannot be acquired include, for example, when the earthquake is of seismic intensity 3 or less and therefore the EEW is not transmitted, or when the EEW is transmitted but the main system 100 is unable to receive it for some reason.

[0045] (Obtaining the next real-time S-wave intensity at the evaluation point and calculating the maximum predicted S-wave intensity) When the next real-time S-wave intensity SOB1 is observed at the observation point where the seismic motion was first observed, or at an observation point other than the first observation point if the epicenter has moved, the main system 100 at the observation point transmits the real-time S-wave intensity SOB1 to the communication network N. The main system 100 at the evaluation point acquires the real-time S-wave intensity SOB1 from the communication network N (S4b-2 in FIG. 4(b)), and calculates the predicted S-wave intensity K1 according to the flow in FIG. 6 by the predicted S-wave intensity (K) calculation unit of the data processing unit 110, in the same way as when the first real-time S-wave intensity SOB0 was acquired (S4b-3).

[0046] The main system 100 of the evaluation point then compares the predicted S-wave intensity K0 calculated from the initial real-time S-wave intensity SOB0 with the predicted S-wave intensity K1 calculated from the newly acquired real-time S-wave intensity SOB1 by the maximum predicted S-wave intensity judgment unit of the data processing unit 110 (S4b-4). If the newly calculated predicted S-wave intensity K1 is greater than the initial predicted S-wave intensity K0, the predicted S-wave intensity K1 is determined to be greater than the maximum predicted S-wave intensity K0 at the evaluation point. MAX (S4b-4).

[0047] In addition, multiple real-time S-wave intensities SOB2, SOB3, SOB4, ..., SOB at the observation point where the earthquake motion was first observed, or at a different observation point if the epicenter has moved. M is observed, the main system 100 of the observation point detects the real-time S-wave intensity SOB, for example, SOB2, SOB4, SOB5, . . . , SOB M are sequentially transmitted to the communication network N (in this example, SOB3 is not transmitted to the communication network N because it is smaller than the threshold value TH). The main system 100 of the evaluation point similarly transmits the real-time S-wave intensities SOB2, SOB4, SOB5, . . . , SOB M are sequentially acquired, and each time they are acquired, the predicted S wave intensity (K) calculation unit calculates the predicted S wave intensity K2, K4, K5, ..., K according to Figure 6. M Calculate.

[0048] The main system 100 of the evaluation point is the predicted S-wave intensity K2, K4, K5, ..., K M Each time the maximum predicted S-wave intensity is calculated, the maximum predicted S-wave intensity judgment unit calculates the predicted S-wave intensity K2, K4, K5, ..., K M and the maximum predicted S-wave intensity K, which is the maximum value of the predicted S-wave intensity K up to that point. MAX The calculated predicted S-wave intensities K2, K4, K5, ..., K M However, the maximum predicted S-wave intensity K MAX If it is greater than the maximum predicted S-wave intensity K at the evaluation point,MAX (S4b-5).

[0049] In this way, the main system 100 of the evaluation point acquires a plurality of real-time S wave intensity SOBs from the communication network N, and calculates the maximum predicted S wave intensity K using the acquired real-time S wave intensity SOBs. MAX Therefore, the S-wave prediction system 1 can continuously predict the maximum value of the S-wave intensity that will reach the evaluation point when an earthquake occurs.

[0050] Second embodiment [Processing in S-wave prediction system] In the first embodiment, the main system 100 functioning as an S-wave observation device at the observation point calculates a real-time S-wave intensity SOB based on the three acceleration components of the measured seismic motion, and transmits the calculated real-time S-wave intensity SOB to the communication network N. Also, the main system 100 functioning as an S-wave intensity prediction device at the evaluation point acquires the real-time S-wave intensity SOB from the communication network N, and calculates the predicted S-wave intensity K using the real-time S-wave intensity SOB. In contrast, in the second embodiment, the main system 100 functioning as an S-wave observation device at the observation point transmits the three acceleration components of the observed seismic motion to the communication network N, and does not calculate the real-time S-wave intensity SOB. On the other hand, the main system 100 functioning as an S-wave intensity prediction device at the evaluation point receives the three acceleration components of the seismic motion from the communication network N, calculates the real-time S-wave intensity SOB, and obtains the predicted S-wave intensity K using the calculated real-time S-wave intensity SOB. In the following, differences from the first embodiment will be mainly described.

[0051] Figure 7 is a flowchart of basic processing in an S wave prediction system according to the second embodiment of the present invention, Figure 8 is a flowchart of processing for calculating real-time S wave intensity SOB at an evaluation point, and Figure 9 is a flowchart of processing for calculating predicted S wave intensity K at an evaluation point.

[0052] The main system 100 that observes seismic motion can execute the process of Fig. 7(a). That is, the main system 100 at the observation point measures seismic motion at the epicenter or an observation point nearby (S7a-2) and transmits the measured three components of acceleration to the communication network N (S7a-3). This main system 100 does not calculate real-time S-wave intensity SOB. The main system 100 repeats transmitting the three components of acceleration to the communication network N every time it observes seismic motion.

[0053] On the other hand, the main system 100 at the evaluation point where the S-wave intensity is predicted can execute the process of Fig. 7(b). That is, the main system 100 at the evaluation point sequentially acquires a plurality of acceleration three components from the communication network N at the evaluation point away from the epicenter (S7b-2), and calculates the real-time S-wave intensity SOB using the acquired acceleration three components (S7b-3). Next, the main system 100 at the evaluation point calculates the predicted S-wave intensity K using the real-time S-wave intensity SOB (S7b-4), and sets the maximum value of the calculated predicted S-wave intensity K as the maximum predicted S-wave intensity K (S7b-5, S7-6).

[0054] 8 is a flowchart of the process of calculating the real-time S-wave intensity SOB in the main system 100 at the evaluation point. At the evaluation point, three acceleration components are acquired from the communication network N (S8-1), and the three acceleration components are preferably drift-corrected by the real-time S-wave intensity (SOB) calculation unit (S8-2), and the raw section average value x s , y s , z s is required (S8-3). SOB is x s , y s , z s Using this, it can be obtained by the above-mentioned formula (1). The main system 100 at the evaluation point where the S-wave intensity should be predicted can calculate the predicted S-wave intensity K using the real-time S-wave intensity SOB calculated using the three components of acceleration acquired from the communication network N. Figure 9 is a flowchart of the process of calculating the predicted S-wave intensity K in the main system 100 at the evaluation point.

[0055] The main system 100 at the evaluation point acquires the three acceleration components first observed at the observation point after the occurrence of earthquake motion from the communication network N, and calculates the real-time S-wave intensity SOB0 in the real-time S-wave intensity SOB calculation section of the data processing section 110 (S9-1). Next, the main system 100 calculates the predicted S-wave intensity K0 at the evaluation point by the predicted S-wave intensity (K) calculation section of the data processing section 110. The predicted S-wave intensity K0 at the evaluation point is calculated based on the distance attenuation between the epicenter and the evaluation point using the calculated real-time S-wave intensity SOB0 (S9-5). The distance attenuation calculation is performed in the same manner as in the first embodiment, using the epicenter information included in the EEW or the position of the observation point, and using formula (2) (S9-2, S9-3, S9-4).

[0056] When the next earthquake motion is observed at the observation point where the first earthquake motion was observed, or at an observation point other than the first observation point if the epicenter has moved, the main system 100 at the observation point transmits the three acceleration components of that earthquake motion to the communication network N. The main system 100 at the evaluation point acquires the next three acceleration components from the communication network N (S7b-2 in FIG. 7(b)), calculates real-time S-wave intensity SOB1 according to the flow in FIG. 8 in the same way as when the first three acceleration components were acquired (S7b-3), and further calculates predicted S-wave intensity K1 from the real-time S-wave intensity SOB1 (S7b-4).

[0057] The main system 100 of the evaluation point then compares the predicted S-wave intensity K0 calculated from the initial SOB0 with the predicted S-wave intensity K1 calculated from the newly acquired SOB1 by the maximum predicted S-wave intensity judgment unit of the data processing unit 110 (S7b-5). If the newly calculated predicted S-wave intensity K1 is greater than the predicted S-wave intensity K0, the predicted S-wave intensity K1 is determined to be the new maximum predicted S-wave intensity K0 at the evaluation point. MAX (S7-6).

[0058] Furthermore, when multiple earthquake motions are observed at the observation point where the earthquake motion was first observed, or at an observation point other than the previous observation point when the epicenter has moved, the main system 100 at the observation point transmits the three acceleration components to the communication network N each time. The main system 100 at the evaluation point sequentially acquires the three acceleration components from the communication network N (S7b-2) and outputs the real-time S-wave intensities SOB2, SOB3, ..., SOB M Calculate the real-time S-wave intensity SOB2, SOB3, ..., SOB M Predicted S-wave intensities K2, K3, ..., K M Calculate (S7b-4).

[0059] The main system 100 of the evaluation point predicts the S-wave intensities K2, K3, . . . , K M Each time the predicted S-wave intensities K2, K3, ..., K M and the maximum predicted S-wave intensity K, which is the maximum value of the predicted S-wave intensity K up to that point. MAX The calculated predicted S-wave intensities K2, K3, . . ., K M However, the maximum predicted S-wave intensity K MAX If it is greater than 1, the predicted S-wave intensity K is the new maximum predicted S-wave intensity K at the evaluation point. MAX will be output as:

[0060] In this way, the main system 100 of the evaluation point acquires a plurality of acceleration three components from the communication network N, and calculates the maximum predicted S wave intensity K from the real-time S wave intensity SOB calculated using the acquired acceleration three components. MAX Therefore, the S-wave prediction system 1 can continuously predict the maximum value of the S-wave intensity that will reach the evaluation point when an earthquake occurs.

Claims

1. An S-wave prediction method for continuously predicting the intensity of S-waves arriving at an evaluation point when an earthquake occurs, comprising: Observing seismic motion at one or more observation points among a plurality of observation points at which seismic motion can be observed; calculating multiple real-time S-wave intensities using multiple three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured at the one or multiple observation points each time a seismic motion is observed; transmitting the calculated real-time S-wave intensities to a communication network; acquiring a plurality of real-time S-wave intensities from the communication network at an evaluation point among the plurality of observation points for which an S-wave intensity is to be predicted, and calculating a plurality of predicted S-wave intensities at the evaluation point based on the acquired plurality of real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point; a step of determining whether or not each of the plurality of predicted S-wave intensities is greater than a maximum value among the plurality of predicted S-wave intensities previously calculated, for each calculation of the plurality of predicted S-wave intensities; If the calculated predicted S-wave intensity is greater than the maximum value, outputting the calculated predicted S-wave intensity as a maximum predicted S-wave intensity at the evaluation point. The S wave prediction method includes:

2. An S-wave prediction method for continuously predicting the intensity of S-waves arriving at an evaluation point when an earthquake occurs, comprising: Observing seismic motion at one or more observation points among a plurality of observation points at which seismic motion can be observed; transmitting a plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured at the one or more observation points to a communication network each time a seismic motion is observed; acquiring a plurality of the three components of acceleration from the communication network at an evaluation point at which an intensity of an S wave is predicted among the plurality of observation points; Calculating a plurality of real-time S-wave intensities using each of the acquired plurality of the three acceleration components; Calculating a plurality of predicted S-wave intensities at the evaluation point based on the calculated plurality of real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point; a step of determining whether or not each of the plurality of predicted S-wave intensities is greater than a maximum value among the plurality of predicted S-wave intensities previously calculated, for each calculation of the plurality of predicted S-wave intensities; If the calculated predicted S-wave intensity is greater than the maximum value, outputting the calculated predicted S-wave intensity as a maximum predicted S-wave intensity at the evaluation point. The S wave prediction method includes:

3. The step of transmitting the calculated real-time S-wave intensities to a communication network includes: If the calculated real-time S-wave intensity exceeds a threshold value, transmitting the real-time S-wave intensity to the communication network. The S wave prediction method according to claim 1 .

4. When an emergency earthquake warning issued by the Japan Meteorological Agency is received, the distance attenuation is calculated using information on the epicenter contained in the emergency earthquake warning, and when an emergency earthquake warning is not received, the distance attenuation is calculated using, as the epicenter, an observation point that observed the seismic motion among the one or more observation points. The S wave prediction method according to claim 1 or 2.

5. An S-wave prediction system that continuously predicts the intensity of S-waves that reach an evaluation point when an earthquake occurs, A communication network; A seismometer disposed at each of a plurality of observation points capable of observing seismic motion; a plurality of computers that are disposed at each of the plurality of observation points, connected to the seismometers, and connected to each other through the communication network; Equipped with One or more computers at the observation points among the plurality of computers, Each time the seismometer observes seismic motion, multiple real-time S-wave intensities are calculated using each of the multiple three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured by the seismometer, and the multiple calculated real-time S-wave intensities are sent to the communication network. It is configured as follows: Among the plurality of computers, a computer at an evaluation point for predicting the intensity of an S wave is Obtaining a plurality of the real-time S-wave intensities from the communication network; Calculating a plurality of predicted S-wave intensities at the evaluation point based on the acquired plurality of real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point; Each time the plurality of predicted S-wave intensities are calculated, it is determined whether the calculated predicted S-wave intensity is greater than a maximum value among the plurality of predicted S-wave intensities previously calculated; When the calculated predicted S-wave intensity is greater than the maximum value, the calculated predicted S-wave intensity is output as the maximum predicted S-wave intensity at the evaluation point. It was configured as follows: S wave prediction system.

6. An S-wave prediction system that continuously predicts the intensity of S-waves that reach an evaluation point when an earthquake occurs, A communication network; A seismometer disposed at each of a plurality of observation points capable of observing earthquakes; a plurality of computers that are disposed at each of the plurality of observation points, connected to the seismometers, and connected to each other through the communication network; Equipped with One or more computers at the observation points among the plurality of computers, Each time the seismometer observes a seismic movement, it transmits a plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured by the seismometer to the communication network. It is configured as follows: Among the plurality of computers, a computer at an evaluation point for predicting the intensity of an S wave is acquiring a plurality of the three acceleration components from the communication network; Calculating a plurality of real-time S-wave intensities using each of the acquired plurality of the three acceleration components; Calculating a plurality of predicted S-wave intensities at the evaluation point based on the calculated plurality of real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point; Each time the plurality of predicted S-wave intensities are calculated, it is determined whether the calculated predicted S-wave intensity is greater than a maximum value among the plurality of predicted S-wave intensities previously calculated; When the calculated predicted S-wave intensity is greater than the maximum value, the calculated predicted S-wave intensity is output as the maximum predicted S-wave intensity at the evaluation point. It was configured as follows: S wave prediction system.

7. One of the plurality of computers or the computer at a plurality of observation points, When the calculated real-time S-wave intensity exceeds a threshold value, the real-time S-wave intensity is transmitted to the communication network. The S wave prediction system according to claim 5 ,

8. When an emergency earthquake warning issued by the Japan Meteorological Agency is received, the distance attenuation is calculated using information on the epicenter contained in the emergency earthquake warning, and when an emergency earthquake warning is not received, the distance attenuation is calculated using, as the epicenter, an observation point that observed the seismic motion among the one or more observation points. The S wave prediction system according to claim 5 or 6.

9. A computer constituting an S-wave prediction system that continuously predicts the intensity of S-waves that arrive at an evaluation point when an earthquake occurs, comprising: the seismometers are arranged at a plurality of observation points capable of observing seismic motion, the seismometers are connected to the respective observation points, and the seismometers are connected to each other through a communication network; A plurality of real-time S-wave intensities are calculated using each of the three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the up-down direction)) measured by the seismometer; Sending a plurality of the three acceleration components or a plurality of real-time S-wave intensities to a communication network; Acquiring a plurality of the three acceleration components or a plurality of real-time S-wave intensities from a communication network; Calculating a plurality of predicted S-wave intensities at the evaluation point based on the plurality of real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point; Each time the plurality of predicted S-wave intensities are calculated, it is determined whether the calculated predicted S-wave intensity is greater than a maximum value among the plurality of predicted S-wave intensities previously calculated; When the calculated predicted S-wave intensity is greater than the maximum value, the calculated predicted S-wave intensity is output as the maximum predicted S-wave intensity at the evaluation point. It was configured as follows: computer.

10. When the calculated real-time S-wave intensity exceeds a threshold value, the real-time S-wave intensity is transmitted to the communication network. A computer according to claim 9, configured to

11. When an emergency earthquake warning issued by the Japan Meteorological Agency is received, the distance attenuation is calculated using information on the epicenter contained in the emergency earthquake warning, and when an emergency earthquake warning is not received, the distance attenuation is calculated using an observation point that observed the seismic motion among the plurality of observation points as the epicenter. The computer of claim 9.

12. A computer program for continuously predicting the intensity of S waves arriving at an evaluation point when an earthquake occurs, comprising program instructions for causing a computer to execute the method according to claim 1 or 2.

Images