S-wave prediction method, prediction system, computer, and computer program for continuously predicting the intensity of S-waves.

Abstract

This invention provides an S-wave prediction method that can continuously predict S-wave intensity at an earlier point in time, even when S-wave intensity gradually increases over time. [Solution] Whenever seismic motion is observed, multiple real-time S-wave intensities are calculated using each of the multiple acceleration 3 components measured at one or more observation points, and the calculated multiple real-time S-wave intensities are sent to a communication network. At an evaluation point where the S-wave intensity is predicted, multiple real-time S-wave intensities are obtained from the communication 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 a multiple predicted S-wave intensity 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 calculated so far, 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, at an observation point, the three components of acceleration of the observed seismic motion or the real-time S-wave intensity are transmitted to a communication network, and at an evaluation point for evaluating the effects of the seismic motion, the predicted S-wave intensity at the evaluation point is continuously predicted at an earlier time based on the real-time S-wave intensity calculated using the three components of acceleration obtained from the communication network, or based on the real-time S-wave intensity obtained from the communication network and distance attenuation. [Background technology]

[0002] Predicting earthquakes is extremely difficult. Therefore, earthquake early warning systems have been proposed that calculate the time of the earthquake, the location of the epicenter, and the magnitude of the earthquake based on seismic motion observation data from numerous seismic observation points immediately after an earthquake occurs, and then notify areas that have not yet been reached of the predicted arrival time and intensity of the main seismic motion based on this information.

[0003] The applicant of this application has already proposed the technologies 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 on the premises of a building or business establishment, to detect P-waves based on the correlation coefficient between the data signals measured by these seismometers, and to predict the intensity of S-waves based on the P-wave data received from the P-wave detection point, and to issue a warning based on this.

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

[0005] [Patent Document 1] Patent No. 6887310 [Patent Document 2] Patent No. 7109120 [Overview of the project] [Problems that the invention aims to solve]

[0006] Currently, the Japan Meteorological Agency (JMA) uses the PLUM method (Propagation of Local Undamped Motion) to obtain information on S-waves expected to reach a given observation point. Unlike the previously used IPF method (Integrated Particle Filter method), the PLUM method predicts seismic intensity based on observed real-time seismic intensity without using the source element, and is considered capable of providing accurate real-time seismic intensity predictions during large earthquakes. A hybrid method combining the IPF and PLUM methods is also in operation.

[0007] The PLUM method cannot predict S-waves at the evaluation point until the S-waves reach the Japan Meteorological Agency's observation point, which is located some distance away. From the evaluation point's perspective, the arrival and intensity of the S-waves are only known when they reach the observation point. For example, if the S-wave velocity is 4 km / s and the observation point is 30 km away from the evaluation point, the margin of error is only about 7 seconds. Furthermore, because the evaluation point uses the S-wave intensity observed at the observation point without attenuation, it may observe an intensity greater than the actual intensity that reaches the target. In addition, although S-waves are observed in real time at the Japan Meteorological Agency's observation points, the data is first transmitted to the agency, processed and incorporated into a telegram, and then distributed, which inevitably means there may be a time lag between the occurrence of an earthquake and the issuance of a report.

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

[0009] This invention provides an S-wave prediction method for continuously predicting the intensity of S-waves that reach an evaluation point during an earthquake. In one embodiment of this method, the real-time S-wave intensity is calculated using the three components of acceleration measured at an observation point for seismic motion, and the calculated real-time S-wave intensity is transmitted to a communication network. At the evaluation point where the S-wave intensity is to be predicted, the real-time S-wave intensity is obtained 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 embodiment, the method includes the steps of: observing seismic motion at one or more observation points among a plurality of observation points capable of observing seismic motion; calculating multiple real-time S-wave intensities 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 vertical direction)) measured at one or more observation points each time seismic motion is observed; and transmitting the calculated multiple real-time S-wave intensities to a communication network. The method further includes the steps of: obtaining multiple real-time S-wave intensities from the communication network at an evaluation point among the plurality of observation points where the S-wave intensity is predicted; and calculating multiple predicted S-wave intensities at the evaluation point based on the obtained multiple real-time S-wave intensities and distance attenuation between the epicenter and the evaluation point. The method further includes the steps of: determining whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensities calculated previously each time one of the multiple predicted S-wave intensities is 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, this method transmits the three components of acceleration measured at the earthquake motion observation points to the communication network. At the evaluation point for predicting the S-wave intensity, the three components of acceleration are acquired from the communication network, and the real-time S-wave intensity is calculated using the acquired three components of acceleration. Based on the real-time S-wave intensity and the distance attenuation, the predicted S-wave intensity is calculated.

[0012] In this aspect, the method includes the steps of observing ground motion at one or more of a plurality of observation points capable of observing ground motion, and transmitting, each time the ground motion is observed, the plurality of three components of acceleration (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the vertical direction)) measured at the one or more observation points to the communication network. The method further includes the steps of acquiring, at an evaluation point for predicting the S-wave intensity among the plurality of observation points, the plurality of three components of acceleration from the communication network, calculating a plurality of real-time S-wave intensities using each of the acquired plurality of three components of acceleration, 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 the distance attenuation between the earthquake source and the evaluation point. The method further includes the steps of, each time each of the plurality of predicted S-wave intensities is calculated, determining whether the calculated predicted S-wave intensity is greater than the maximum value of the plurality of previously calculated predicted S-wave intensities, 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 reaching an evaluation point during an earthquake. In one embodiment, the system comprises a communication network, seismometers located at each of a plurality of observation points capable of observing seismic motion, and a plurality of computers located at each of the plurality of observation points, connected to the seismometers and connected to each other through the communication network. One or more of the computers at the observation points are configured to calculate a plurality of real-time S-wave intensities using each of the plurality of three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the vertical direction)) measured by the seismometer each time the seismometer observes seismic motion, and to send the calculated plurality of real-time S-wave intensities to the communication network. Among the multiple computers, the computer at the evaluation point for predicting S-wave intensity acquires multiple real-time S-wave intensity values ​​from the communication network, calculates multiple predicted S-wave intensity values ​​at the evaluation point based on the acquired real-time S-wave intensity values ​​and the distance attenuation between the epicenter and the evaluation point, and for each of the multiple predicted S-wave intensity values ​​calculated, determines whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensity values ​​calculated so far. If 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.

[0014] In another aspect, the system includes a communication network, seismometers disposed at each of a plurality of observation points capable of observing ground motions, and a plurality of computers disposed at each of the plurality of observation points, connected to the seismometers, and connected to each other through the communication network. One or more computers at the observation points among the plurality of computers are configured to send, to the communication network, a plurality of acceleration three components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the vertical direction)) measured by the seismometer each time the seismometer observes a ground motion. The computer at the evaluation point for predicting the S-wave intensity among the plurality of computers acquires the plurality of acceleration three components from the communication network, calculates a plurality of real-time S-wave intensities using each of the acquired plurality of acceleration three components, calculates a plurality of predicted S-wave intensities at the evaluation point based on the calculated plurality of real-time S-wave intensities and the distance attenuation between the earthquake source and the evaluation point, and each time a plurality of predicted S-wave intensities are calculated, determines whether the calculated predicted S-wave intensity is greater than the maximum value among the plurality of predicted S-wave intensities calculated previously. If the calculated predicted S-wave intensity is greater than the maximum value, it is configured to output the calculated predicted S-wave intensity as the maximum predicted S-wave intensity at the evaluation point.

[0015] In yet another embodiment, the present invention provides a computer that constitutes an S-wave prediction system for continuously predicting the intensity of S-waves reaching an evaluation point during an earthquake. This computer is located at each of a plurality of observation points where seismic motion can be observed, and is connected to a seismometer located at each of the plurality of observation points, and is also connected to each other through a communication network. This 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 vertical direction)) measured by the seismometer, and to transmit the plurality of the plurality of acceleration components or the plurality of real-time S-wave intensities to the communication network. This computer is configured to further acquire multiple three-component acceleration data 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 the distance attenuation between the epicenter and the evaluation point, and, each time one of the multiple predicted S-wave intensities is calculated, determine whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensities calculated so far. 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 embodiment, the present invention provides a computer program for continuously predicting the intensity of S-waves reaching an evaluation point during an earthquake. [Effects of the Invention]

[0017] According to the present invention, at the evaluation point, the three components of acceleration or the intensity of S-waves observed at the closest observation point to the epicenter, which is far from the evaluation point, can be obtained from the communication network. Therefore, the intensity of S-waves at the evaluation point can be determined more quickly compared to conventional methods. Furthermore, at the evaluation point, the intensity of S-waves at the evaluation point can be determined based on the distance attenuation between the epicenter and the evaluation point, allowing for a more accurate prediction of the intensity of the arriving S-waves.

[0018] Furthermore, even in earthquakes where the bedrock ruptures over time, causing the epicenter to shift, or where the S-wave intensity gradually increases at observation points, the S-wave intensity can be predicted continuously and without omission at evaluation points. At evaluation points, the predicted S-wave intensity can be used to promptly issue warnings or shut down equipment such as elevators. [Brief explanation of the drawing]

[0019] [Figure 1] This is a schematic diagram showing an example of the installation of the main system in an S-wave prediction system according to one embodiment of the present invention. [Figure 2] This figure shows an image illustrating the installation of the main system in the S-wave prediction system. [Figure 3A] This block diagram outlines the S-wave prediction system. [Figure 3B] This is a block diagram showing the functions of the data processing unit of the main system. [Figure 4] This is a flowchart of the basic processing in an S-wave prediction system according to one embodiment of the present invention. [Figure 5] This is a flowchart of the process for calculating the real-time S-wave intensity (SOB) at an observation point according to one embodiment of the present invention. [Figure 6] This is a flowchart of the process for calculating the predicted S-wave intensity K at an evaluation point according to one embodiment of the present invention. [Figure 7] This is a flowchart of the basic processing in an S-wave prediction system according to another embodiment of the present invention. [Figure 8] This is a flowchart of the process for calculating the real-time S-wave intensity (SOB) at an evaluation point according to another embodiment of the present invention. [Figure 9] This is a flowchart of the process for calculating the predicted S-wave intensity K at an evaluation point according to another embodiment of the present invention. [Modes for carrying out the invention]

[0020] Embodiments of the present invention will be described in detail below with reference to the drawings. This invention provides an S-wave prediction method and system for continuously predicting the intensity of S-waves (secondary waves) that reach evaluation points during an earthquake. In this system, the three components of acceleration of the seismic motion or real-time S-wave intensity observed at an observation point at the epicenter or a nearby observation point are sent to a communication network, and other observation points (referred to as evaluation points) that predict the S-wave intensity acquire this information from the communication network. As a result, even evaluation points far from the epicenter can obtain the predicted S-wave intensity at the evaluation point before the actual S-waves arrive. 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 components of acceleration acquired from the communication network or to the real-time S-wave intensity acquired from the communication network. Furthermore, 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 can always be obtained. Therefore, at the evaluation point, the S-wave intensity can be predicted continuously and without missing any changes in response to changes in seismic motion.

[0021] [Overview of the S-wave prediction system] Figure 1 is a schematic diagram showing an example of the installation of one observation point in an S-wave prediction system 1 according to one embodiment of the present invention. In the S-wave prediction system 1, three seismometers are installed inside a building or on the premises of a business, and the S-wave intensity can be determined based on the measurement data from these three seismometers, i.e., the three components of acceleration (acceleration x in the east-west direction, acceleration y in the north-south direction, and acceleration z in the vertical direction). In this embodiment, as shown in Figure 1, 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, but it is not limited to this, and the number of seismometers to be installed can be multiple, such as two or four or more. However, when a majority vote decision is made by multiple seismometers for the detection of seismic waves, it is preferable that the number of seismometers be odd.

[0022] In this specification, the S-wave intensity calculated using the three acceleration components measured by a seismometer is referred to as "Real-time S-wave intensity SOB (Seismic Observation)," and the S-wave intensity predicted at an evaluation point is referred to as "Predicted S-wave intensity K." The Real-time S-wave intensity SOB does not necessarily have to be calculated at the observation point where the seismic motion was observed; it may also be calculated at an evaluation point where it is necessary to know the predicted S-wave intensity K, using the three acceleration components measured by a seismometer at the observation point where the seismic motion was observed.

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

[0024] When multiple seismometers are installed, there are no particular restrictions on which seismometer's measurement data to use. For example, by comparing the measurement data of multiple seismometers, the measurement data of the seismometer with an intermediate noise level during normal times can be used. Alternatively, the real-time S-wave intensity SOB (Sum of Bore) calculated using the three acceleration components of each seismometer can be selected based on an intermediate value.

[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. Figure 2 is a diagram showing an installation image of the main system 100 of the S-wave prediction system 1 according to an embodiment of the present invention, and shows the main system 100 installed at points A, B, C, ... Each point where the main system 100 is installed serves as an S-wave observation point and also as an evaluation point for predicting the intensity of the S-waves.

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

[0027] Figure 3A is a block diagram illustrating the S-wave prediction system 1, showing, for example, a configuration in which multiple main systems 100A, 100B, 100C, ..., 100X are connected to each other via a communication network N. In Figure 3A, the main systems installed at points A, B, C, ..., and X are designated as 100A, 100B, 100C, ..., and 100X, respectively. Since these configurations are similar, 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 installed at an appropriate distance apart at a single location. The data measured by the first seismometer 101, the second seismometer 102, and the third seismometer 103 is transmitted to the data processing unit 110. The data processing unit 110 in the main system 100A can be implemented by a general-purpose computer (information processing device) consisting of a CPU, a ROM that holds program instructions that operate on the CPU, and RAM which is the CPU's work area. 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] Figure 3B is a block diagram showing the functions of the data processing unit 110. The data processing unit 110 includes a real-time S-wave intensity (SOB) calculation unit, a real-time S-wave intensity (SOB) determination unit, a predicted S-wave intensity (K) calculation unit, and a maximum predicted S-wave intensity determination unit. The detailed functions of each will be described later. The data processing unit 110 operates in cooperation with the various components connected to the data processing unit 110 as shown in the figure. Furthermore, various control processes in the S-wave prediction system 1 are realized by the CPU (not shown) executing program instructions stored in storage means (not shown) such as ROM or RAM within the data processing unit 110.

[0030] Returning to Figure 3A, the data processing unit 110 is connected to a storage unit 120, such as a hard disk or solid-state drive. The storage unit 120 can store the computer program necessary for the operation of the S-wave prediction system 1, initial data, intermediate processing data, facility information (facility name, location information (latitude, longitude), etc.), 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 or store in the storage unit 120. The computer program necessary for the operation of the S-wave prediction system 1 includes program instructions to cause the computer to execute all the processing steps in the S-wave prediction system described below.

[0031] Furthermore, a communication unit 150 is connected to the data processing unit 110, enabling communication with the outside world via wireless or wired means. The communication unit 150 can transmit data transferred from the data processing unit 110 to main systems 100B, 100C, ..., 100X (other than itself, main system 100A) via an external communication network N. The communication unit 150 can also receive data transmitted from main systems 100B, 100C, ..., 100X (other than itself, main system 100A) via the external communication network N, and transmit the received data to the data processing unit 110. Main system 100A also has a notification unit 130, which can output an alarm according to the predicted S-wave intensity K level as needed.

[0032] (First Embodiment) [Processing in the S-wave prediction system] Next, the processing in the S-wave prediction system 1 according to the first embodiment will be described. The S-wave prediction system 1 can perform seismic motion observation, calculation of real-time S-wave intensity SOB at the epicenter or a nearby observation point, and calculation of predicted S-wave intensity K at an evaluation point based on the real-time S-wave intensity SOB of the generated seismic motion.

[0033] Figure 4 is a flowchart of the processing in the S-wave prediction system 1. Figure 4(a) shows the processing of the observation point main system 100 (for example, main system 100A) which observes seismic motion at or near the epicenter and calculates real-time S-wave intensity SOB, and Figure 4(b) shows the processing of the evaluation point main system 100 (main systems 100B, 100C, ..., 100X) which predicts the intensity of S-waves based on the real-time S-wave intensity SOB transmitted by the main system 100. All of the main systems 100A, 100B, 100C, ..., 100X that constitute the S-wave prediction system 1 can perform the processing shown in Figures 4(a) and 4(b).

[0034] When the main system 100 functions as an S-wave observation device, it can perform the processing shown in Figure 4(a). Specifically, the main system 100 observes seismic motion at or near the epicenter (S4a-2), calculates the real-time S-wave intensity SOB using the measured acceleration 3 components (S4a-3), compares the real-time S-wave intensity SOB with a threshold TH as needed (S4a-4, S4a-5), and then transmits the real-time S-wave intensity SOB to the communication network N (S4a-6).

[0035] In large earthquakes, the bedrock may rupture over time, causing the epicenter to shift. In earthquakes where the epicenter shifts, the observation points that observe S-waves may also shift to other observation points as the epicenter moves. Therefore, in this invention, as the epicenter shifts, real-time S-wave intensity SOB may be calculated at one or more observation points other than the one that initially calculated the real-time S-wave intensity SOB, and these 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 perform the processing shown in Figure 4(b). Specifically, the main system 100 obtains the real-time S-wave intensity SOB from the communication network N (S4b-2), calculates the predicted S-wave intensity K at the evaluation point (S4b-3), and stores the maximum value of the calculated predicted S-wave intensities K as the maximum predicted S-wave intensity K (S4b-4, S4b-5).

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

number

[0038] In this invention, it is preferable to use an average of multiple real-time measurement data obtained by a seismometer at regular time intervals, and this regular time interval is called a "primary interval." By averaging multiple real-time measurement data acquired over one primary interval, rather than using the real-time measurement data from the seismometer itself, it is possible to reduce the variability in real-time S-wave intensity (SOB) that may occur due to data fluctuations when processing real-time measurement data as is, thereby achieving faster and more accurate prediction. From the viewpoint of measurement reliability, the size of one primary interval is preferably 0.05 seconds to 0.2 seconds, but is not limited to this. If the size of the primary interval is small, the number of real-time measurement data to be averaged will be small, and fluctuations in individual real-time measurement data will be more likely to affect the accuracy of the S-wave intensity. On the other hand, if the size of the primary interval is large, the number of real-time measurement data included in the primary interval will be large, which will increase the processing time, and it may take a long time to calculate the S-wave intensity. For example, if the size of the elementary interval is 0.1 seconds and the seismometer's sampling frequency is 100 Hz, the number of real-time measurement data points in one elementary interval is 10. If the size of the elementary interval is 0.05 seconds and the seismometer's sampling frequency is 100 Hz, the number of real-time measurement data points in one elementary interval is 5.

[0039] (Comparison of S-wave intensity at observation point with threshold and data transmission) Returning to Figure 4, if we define SOB0 as the first real-time S-wave intensity SOB observed after the occurrence of seismic motion, it is preferable that the obtained real-time S-wave intensity SOB0 is compared with a predetermined threshold TH in the 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 TH, the real-time S-wave intensity SOB0 is sent to the communication network N. In another embodiment, the real-time S-wave intensity SOB0 may be sent to the communication network N without being compared with the threshold TH.

[0040] The threshold value TH can be determined in advance by the provider or user of the S-wave prediction system 1 and stored in an appropriate location. If no comparison with the threshold value TH is performed, or if the threshold value TH is too small, real-time S-wave intensity SOB will be sent to the network N frequently, which may cause network congestion and hinder the prediction of S-wave intensity at evaluation points. If the threshold value TH is too large, seismic motion that could cause significant damage at evaluation points may be missed, and accurate prediction of 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 obtained from the communication network N. Figure 6 is a flowchart of the process for 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 the real-time S-wave intensity SOB from the communication network N (S6-1). After the occurrence of seismic motion, the main system 100 acquires the real-time S-wave intensity SOB0 of the first S-wave observed at the observation point from the communication network N, and the predicted S-wave intensity calculation unit of the data processing unit 110 uses the real-time S-wave intensity SOB0 to calculate the predicted S-wave intensity K0 at the evaluation point. The predicted S-wave intensity K0 at the evaluation point is calculated using the acquired real-time S-wave intensity SOB0 and based on the distance attenuation between the epicenter and the evaluation point (S6-5). The distance attenuation is calculated using the following distance attenuation formula (2) (S6-4). The distance attenuation formula is predetermined and stored in the memory unit or is pre-programmed.

number

[0043] Here, in order to calculate distance attenuation, information about the epicenter, that is, the distance from the evaluation point to the epicenter, is required. The epicenter information is included in the Japan Meteorological Agency's Earthquake Early Warning (EEW) message. Therefore, if the main system 100 at the evaluation point is able to obtain the EEW (S6-2), distance attenuation can be calculated using the epicenter information included in the EEW.

[0044] If, for any reason, the main system 100 at the evaluation point is unable to acquire the EEW, 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 the predicted S-wave intensity K0 considering distance attenuation. Situations in which EEW cannot be acquired include, for example, when the earthquake is magnitude 3 or less and therefore EEW is not transmitted, or when EEW is transmitted but the main system 100 is unable to receive it for some reason.

[0045] (Acquisition of the next real-time S-wave intensity at the evaluation point and calculation of the maximum predicted S-wave intensity) When the next real-time S-wave intensity SOB1 is observed at the observation point where the initial seismic motion was observed, or at an observation point different from the initial observation point if the epicenter has moved, the main system 100 at the observation point sends 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 Figure 4(b)), and, as with the acquisition of the initial real-time S-wave intensity SOB0, the predicted S-wave intensity (K) calculation unit of the data processing unit 110 calculates the predicted S-wave intensity K1 according to the flow in Figure 6 (S4b-3).

[0046] Next, the main system 100 of the evaluation points compares the predicted S-wave intensity K0 calculated from the first 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 determination unit of the data processing unit 110 (S4b-4). When the newly calculated predicted S-wave intensity K1 is greater than the first predicted S-wave intensity K0, the predicted S-wave intensity K1 is output as the maximum predicted S-wave intensity K at that evaluation point MAX (S4b-4).

[0047] Furthermore, at the observation point where the seismic motion was first observed, or at an observation point different from the previous observation points when the epicenter moves, when a plurality of real-time S-wave intensities SOB2, SOB3, SOB4, ···, SOB M are observed, the main system 100 of the observation point sequentially sends the real-time S-wave intensities SOB greater than the threshold TH, for example, SOB2, SOB4, SOB5, ···, SOB M to the communication network N (in this example, since SOB3 is smaller than the threshold TH, it is not sent to the communication network N). The main system 100 of the evaluation point similarly sequentially acquires the real-time S-wave intensities SOB2, SOB4, SOB5, ···, SOB M from the communication network N, and each time it is acquired, the predicted S-wave intensity (K) calculation unit calculates predicted S-wave intensities K2, K4, K5, ···, K M according to FIG. 6.

[0048] Each time the main system 100 of the evaluation point calculates each of the predicted S-wave intensities K2, K4, K5, ···, K M , the maximum predicted S-wave intensity determination unit compares each of the calculated predicted S-wave intensities K2, K4, K5, ···, K M with the maximum predicted S-wave intensity K MAX which is the maximum value of the predicted S-wave intensity K up to that time (S4b-4), and when the calculated predicted S-wave intensities K2, K4, K5, ···, K M are greater than the maximum predicted S-wave intensity K MAX , that predicted S-wave intensity K is the maximum predicted S-wave intensity K at the evaluation pointMAX It is output as (S4b-5).

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

[0050] (Second embodiment) [Processing in the S-wave prediction system] In the first embodiment, the main system 100, which functions as an S-wave observation device at the observation point, calculates the real-time S-wave intensity SOB based on the three acceleration components of the measured seismic motion and sends the calculated real-time S-wave intensity SOB to the communication network N. The main system 100, which functions as an S-wave intensity prediction device at the evaluation point, obtains 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, which functions as an S-wave observation device at the observation point, sends 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, which functions 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 uses the calculated real-time S-wave intensity SOB to determine the predicted S-wave intensity K. The following will primarily describe the differences from the first embodiment.

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

[0052] The main system 100, which observes seismic motion, can perform the processing shown in Figure 7(a). Specifically, the main system 100 at the observation point measures seismic motion at the epicenter or a nearby observation point (S7a-2) and sends 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 repeatedly sends the three components of acceleration to the communication network N each time it observes seismic motion.

[0053] Meanwhile, the main system 100 at the evaluation point for predicting S-wave intensity can perform the processing shown in Figure 7(b). Specifically, the main system 100 at the evaluation point sequentially acquires multiple acceleration 3 components from the communication network N at an evaluation point far from the epicenter (S7b-2), and uses the acquired acceleration 3 components to calculate the real-time S-wave intensity SOB (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 intensities K as the maximum predicted S-wave intensity K (S7b-5, S7-6).

[0054] Figure 8 is a flowchart of the process for calculating the real-time S-wave intensity (SOB) in the main system 100 of the evaluation point. At the evaluation point, the three acceleration components are acquired from the communication network N (S8-1), and the real-time S-wave intensity (SOB) calculation unit preferably corrects the drift of each of the three acceleration components (S8-2), and the elementary interval mean x is calculated from the drift-corrected data. s , y s , z s This is required (S8-3). SOB is x s , y s , z s Using this, it can be calculated by equation (1) above. 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 acceleration components obtained from the communication network N. Figure 9 is a flowchart of the process for 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 initially observed at the observation point from the communication network N after the occurrence of seismic motion, and calculates the real-time S-wave intensity SOB0 in the real-time S-wave intensity SOB calculation unit of the data processing unit 110 (S9-1). Next, the main system 100 calculates the predicted S-wave intensity K0 at the evaluation point using the predicted S-wave intensity (K) calculation unit of the data processing unit 110. The predicted S-wave intensity K0 at the evaluation point is calculated using the calculated real-time S-wave intensity SOB0 and based on the distance attenuation between the epicenter and the evaluation point (S9-5). The calculation of distance attenuation is the same as in the first embodiment and is performed using equation (2) with the epicenter information included in EEW or the location of the observation point (S9-2, S9-3, S9-4).

[0056] When the next seismic motion is observed at the observation point where the initial seismic motion was observed, or at a different observation point if the epicenter has moved, the main system 100 at the observation point transmits the three acceleration components of that seismic motion to the communication network N. The main system 100 at the evaluation point obtains the next three acceleration components from the communication network N (S7b-2 in Figure 7(b)), calculates the real-time S-wave intensity SOB1 according to the flow in Figure 8, as was done when the first three acceleration components were obtained (S7b-3), and further calculates the predicted S-wave intensity K1 from the real-time S-wave intensity SOB1 (S7b-4).

[0057] The main evaluation system 100 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 determination 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 set to the new maximum predicted S-wave intensity K at that evaluation point. MAX It is output as (S7-6).

[0058] Furthermore, if multiple seismic waves are observed at the observation point where the initial seismic wave was observed, or at a different observation point if 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 these three acceleration components from the communication network N (S7b-2) and records the real-time S-wave intensities SOB2, SOB3, ..., SOB M The following values ​​were calculated (S7b-3), and the real-time S-wave intensities SOB2, SOB3, ..., SOB M Predicted S-wave intensities K2, K3, ..., K M Calculate (S7b-4).

[0059] The main system 100 for evaluation points is based on the predicted S-wave intensities K2, K3, ..., K M Each time a calculation is performed, the calculated predicted S-wave intensities K2, K3, ..., K M And the maximum predicted S-wave intensity K is the maximum value of the predicted S-wave intensity K up to that point. MAX By comparing these (S7b-5), the respective predicted S-wave intensities K2, K3, ..., K were calculated. M However, the maximum predicted S-wave intensity K MAX If it is greater, the predicted S-wave intensity K becomes the new maximum predicted S-wave intensity K at the evaluation point. MAX It will be output as follows.

[0060] In this way, the main evaluation system 100 acquires multiple acceleration 3 components from the communication network N, and uses the acquired acceleration 3 components to calculate the real-time S-wave intensity SOB, from which the maximum predicted S-wave intensity K MAX Therefore, the S-wave prediction system 1 can continuously predict the maximum S-wave intensity that will reach the evaluation point when an earthquake occurs.

Claims

1. An S-wave prediction method that continuously predicts the intensity of S-waves reaching an evaluation point when an earthquake occurs, A step of observing seismic motion at one or more observation points among multiple observation points capable of observing seismic motion, Each time seismic motion is observed, the process involves calculating multiple real-time S-wave intensities 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 vertical direction)) measured at one or more of the aforementioned observation points, and The steps include sending the calculated multiple real-time S-wave intensities to the communication network, The steps include: obtaining multiple real-time S-wave intensities from the communication network at an evaluation point among the multiple observation points for predicting S-wave intensity; and calculating multiple predicted S-wave intensities at the evaluation point based on the obtained real-time S-wave intensities and the distance attenuation between the epicenter and the evaluation point; Each time one of the multiple predicted S-wave intensities is calculated, the step of determining whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensities calculated previously, If 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. A method for predicting S-waves, including the S-wave prediction method.

2. An S-wave prediction method that continuously predicts the intensity of S-waves reaching an evaluation point when an earthquake occurs, A step of observing seismic motion at one or more observation points among multiple observation points capable of observing seismic motion, Each time seismic motion is observed, multiple three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the vertical direction)) measured at one or more observation points are transmitted to the communication network; The steps include obtaining multiple acceleration three components from the communication network at an evaluation point among the multiple observation points for predicting the intensity of the S wave, The steps include calculating multiple real-time S-wave intensities using each of the acquired three acceleration components, A step of calculating a plurality of predicted S-wave intensities at the evaluation point based on the plurality of real-time S-wave intensities calculated and the distance attenuation between the epicenter and the evaluation point, Each time one of the multiple predicted S-wave intensities is calculated, the step of determining whether the calculated predicted S-wave intensity is greater than the maximum value among the multiple predicted S-wave intensities calculated previously, If 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. A method for predicting S-waves, including the S-wave prediction method.

3. The step of sending the calculated multiple real-time S-wave intensities to the communication network is: The calculation includes sending the real-time S-wave intensity to the communication network when the calculated real-time S-wave intensity exceeds a threshold. The S-wave prediction method according to claim 1.

4. The aforementioned distance attenuation is calculated using the epicenter information included in the earthquake early warning issued by the Japan Meteorological Agency when the warning is received, and when the earthquake early warning is not received, it is calculated using the observation point that observed the seismic motion from one or more of the aforementioned observation points as the epicenter. The S-wave prediction method according to claim 1 or claim 2.

5. An S-wave prediction system that continuously predicts the intensity of S-waves reaching an evaluation point when an earthquake occurs, Communication networks and A seismometer placed at each of the multiple observation points capable of observing seismic motion, Multiple computers are placed at each of the aforementioned observation points, connected to the seismometer, and connected to each other through the communication network. Equipped with, One or more of the computers at the observation points among the aforementioned multiple computers are: 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 vertical direction)) measured by the seismometer, and the calculated multiple real-time S-wave intensities are transmitted to the communication network. It is configured in such a way, Of the aforementioned multiple computers, the computer at the evaluation point for predicting the intensity of the S wave is: Multiple real-time S-wave intensities are acquired from the communication network. Based on the acquired multiple real-time S-wave intensities and the distance attenuation between the epicenter and the evaluation point, multiple predicted S-wave intensities at the evaluation point are calculated. Each time one 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 among the multiple predicted S-wave intensities calculated previously. If 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 is configured in such a way. S-wave prediction system.

6. An S-wave prediction system that continuously predicts the intensity of S-waves reaching an evaluation point when an earthquake occurs, Communication networks and A seismometer placed at each of the multiple observation points capable of observing earthquakes, Multiple computers are placed at each of the aforementioned observation points, connected to the seismometer, and connected to each other through the communication network. Equipped with, One or more of the computers at the observation points among the aforementioned multiple computers are: Each time the seismometer detects seismic motion, it transmits multiple three acceleration components (x (acceleration in the east-west direction), y (acceleration in the north-south direction), and z (acceleration in the vertical direction)) measured by the seismometer to the communication network. It is configured in such a way, Of the aforementioned multiple computers, the computer at the evaluation point for predicting the intensity of the S wave is: Multiple three acceleration components are obtained from the communication network, Using each of the acquired three acceleration components, multiple real-time S-wave intensities are calculated. Based on the multiple real-time S-wave intensities calculated and the distance attenuation between the epicenter and the evaluation point, multiple predicted S-wave intensities at the evaluation point are calculated. Each time one 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 among the multiple predicted S-wave intensities calculated previously. If 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 is configured in such a way. S-wave prediction system.

7. The computer at one or more observation points among the aforementioned plurality of computers is: If the calculated real-time S-wave intensity exceeds a threshold, the real-time S-wave intensity is transmitted to the communication network. The S-wave prediction system according to claim 5, configured as described above.

8. The aforementioned distance attenuation is calculated using the epicenter information included in the earthquake early warning issued by the Japan Meteorological Agency when the warning is received, and when the earthquake early warning is not received, it is calculated using the observation point that observed the seismic motion from one or more of the aforementioned observation points as the epicenter. The S-wave prediction system according to claim 5 or claim 6.

9. A computer comprising an S-wave prediction system that continuously predicts the intensity of S-waves reaching an evaluation point when an earthquake occurs, They are placed at each of the multiple observation points capable of observing seismic motion, connected to the seismometers placed at each of the multiple observation points, and connected to each other through a communication network. 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 vertical direction)) measured by the seismometer, multiple real-time S-wave intensities are calculated. Multiple acceleration three components or multiple real-time S-wave intensities are transmitted to the communication network. Multiple acceleration three components or multiple real-time S-wave intensities are acquired from the communication network. Based on the multiple real-time S-wave intensities and the distance attenuation between the epicenter and the evaluation point, multiple predicted S-wave intensities at the evaluation point are calculated. Each time one 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 among the multiple predicted S-wave intensities calculated previously. If 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 is configured in such a way. computer.

10. If the calculated real-time S-wave intensity exceeds a threshold, the real-time S-wave intensity is transmitted to the communication network. The computer according to claim 9, configured in such a way.

11. When an earthquake early warning issued by the Japan Meteorological Agency is received, the distance attenuation is calculated using the epicenter information included in the earthquake early warning. When an earthquake early warning is not received, the distance attenuation is calculated using the observation point that observed the seismic motion among the multiple observation points as the epicenter. The computer according to claim 9.

12. A computer program for continuously predicting the intensity of S-waves reaching an evaluation point during an earthquake, comprising program instructions for causing a computer to execute the method described in claim 1 or claim 2.

Images