Disaster occurrence prediction system and disaster occurrence prediction method

Abstract

To realize an efficient and low-cost disaster occurrence prediction mechanism using infrasound. The disaster occurrence prediction system is composed of an optical analysis unit and an information processing device, and acquires the time change of vibration intensity for each frequency of optical fiber at measurement points set along an optical fiber attached to a power transmission line by DAS (Distributed Acoustic Sensing), monitors in real time whether there is a feature caused by infrasound in the time change of vibration intensity for each frequency at the measurement point, and outputs information predicting the occurrence of a disaster when the above-mentioned feature is detected.

Description

[Technical field]

[0001] The present invention relates to a disaster occurrence prediction system and a disaster occurrence prediction method. [Background technology]

[0002] Patent Document 1 describes an abnormality detection device that acquires backward Rayleigh scattered light from an OPGW (optical fiber composite overhead ground wire), generates vibration information for a frequency domain including the natural frequency of the optical fiber composite overhead ground wire based on the acquired backward Rayleigh scattered light, and detects abnormalities in power transmission equipment based on the generated vibration information.

[0003] Patent Document 2 describes a tsunami detection device that obtains information about a tsunami using infrasound (infrasound, micro-pressure waves). The tsunami detection device determines whether an earthquake detected by an earthquake detection unit that detects earthquakes is of a predetermined magnitude or greater, measures infrasound, and when an earthquake of a predetermined magnitude or greater is detected, determines whether a tsunami has occurred based on the magnitude of the change in sound pressure of the measured infrasound.

[0004] Non-Patent Document 1 describes micro-pressure oscillation data that is being experimentally observed in a study titled "Research on early detection of tsunamis using observation results of micro-pressure oscillations." [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2023-50257 A [Patent Document 2] JP 2016-8865 A [Non-patent literature]

[0006] [Non-Patent Document 1] "Infrasound Monitoring Network", Japan Weather Association, [online], Internet<URL:https: / / micos-sc.jwa.or.jp / infrasound-net / observed / > ,Retrieved November 1, 2020 Summary of the Invention [Problem to be solved by the invention]

[0007] Infrasound is generated by large-scale physical phenomena that cause disasters such as earthquakes, tsunamis, typhoons, volcanic eruptions, and meteorite falls, and has the property of propagating long distances through the atmosphere. Therefore, it is expected to be used as a remote sensing means to obtain information for disaster prevention from remote locations. In addition, as described in Patent Document 2 and Non-Patent Document 1, development and research on disaster prevention systems that use infrasound is underway.

[0008] However, if one were to try to realize a disaster prevention system using infrasound using the mechanisms described in Patent Document 2 and Non-Patent Document 1, it would be necessary to prepare a large number of expensive tsunami detection devices equipped with seismometers as earthquake sensing units. It would also be necessary to secure installation locations where the tsunami detection devices can be supplied with power to operate them at all times. Furthermore, the installation and maintenance of the tsunami detection devices would require a great deal of effort and cost.

[0009] The present invention has been made in consideration of the above background, and aims to provide a disaster occurrence prediction system and a disaster occurrence prediction method that can efficiently and low-costly realize a disaster occurrence prediction mechanism using infrasound. [Means for solving the problem]

[0010] One of the means for solving the above problem is a disaster occurrence prediction system that utilizes power transmission facilities that are installed over a wide area and is composed of an optical analysis unit and an information processing device, and acquires the time change in vibration intensity for each frequency of the optical fiber at measurement points set along the optical fiber installed along the power transmission line using DAS (Distributed Acoustic Sensing), monitors in real time whether or not there is a phenomenon attributable to infrasound in the time change in vibration intensity for each frequency at the measurement point, and outputs information predicting the occurrence of a disaster if such a phenomenon is detected.

[0011] Other problems and solutions disclosed in the present application will be made clear in the detailed description and drawings. Effect of the Invention

[0012] According to the present invention, a disaster occurrence prediction mechanism using infrasound can be realized efficiently and at low cost. [Brief description of the drawings]

[0013] [Figure 1] FIG. 1 is a diagram showing a schematic configuration of a disaster occurrence prediction system. [Diagram 2] FIG. 1 is a diagram illustrating a mechanism for measuring a vibration state by a DAS. [Diagram 3] 13 is a graph showing the change over time for each frequency of the vibration state at each measurement point. [Figure 4A] FIG. 1 is a diagram showing a main configuration of a disaster occurrence prediction device. [Figure 4B] FIG. 2 is a diagram showing main functions of a disaster occurrence prediction device. [Figure 5A] FIG. 2 is a diagram showing the main configuration of an alarm device. [Figure 5B] FIG. 2 is a diagram showing main functions of the alarm device. [Figure 6] 11 is a flowchart illustrating a disaster occurrence prediction process. [Figure 7] 13 is a flowchart illustrating a disaster occurrence prediction information output process. [Figure 8] 13 is an example of a disaster occurrence prediction information output screen. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, the present invention will be described in detail with reference to the accompanying drawings according to an embodiment of the present invention. At least the following matters will become clear from the description of this specification and the accompanying drawings. In the following description, the letter "S" before a reference numeral means a processing step.

[0015] 1 shows a schematic configuration of a disaster prediction system 1 according to an embodiment of the present invention. The disaster prediction system 1 includes a disaster prediction device 100 provided in a substation 6 or the like, and one or more warning devices 300.

[0016] The disaster prediction device 100 is configured using an information processing device (computer). The disaster prediction device 100 is communicably connected to an alarm device 300 via a communication network 5. The communication network is, for example, a local area network (LAN), a wide area network (WAN), the internet, a power line communication (PLC), a public communication network, a dedicated line, or the like.

[0017] The disaster occurrence prediction device 100 uses an optical fiber 4a of an OPGW4 (optical fiber composite overhead ground wire) installed on the power transmission line 3 as a vibration detection sensor, and acquires the vibration state at each of a plurality of measurement positions (hereinafter referred to as "measurement points") set along the optical fiber 4a by a technique (distributed acoustic sensing (hereinafter referred to as DAS)) that measures the vibration state (vibration intensity, vibration frequency) based on the expansion and contraction of the optical fiber 4a at each of the measurement points. In the DAS, for example, the vibration state at each measurement point is acquired by the principle of a C-OTDR (Coherent detection Optical Time Domain Reflectometer).

[0018] FIG. 2 is a diagram for explaining a mechanism by which the disaster prediction device 100 measures the vibration state at each measurement point by the DAS. As shown in the figure, the disaster prediction device 100 inputs a light pulse (laser pulse, hereinafter also referred to as "incident light") from the end face of the optical fiber 4a, and measures the change speed (≒ stretching frequency) of the phase difference of the backscattered light of the light pulse at each measurement point. The phase difference is estimated from the intensity change caused by the interference between the backscattered lights. Then, the disaster prediction device 100 obtains the vibration frequency (for example, vibration frequency in the range of up to 10 kHz) of the longitudinal wave and transverse wave of the optical fiber 4a at each measurement point based on the measured change speed. Also, the disaster prediction device 100 obtains the vibration intensity (spectral intensity, vibration amplitude) at each measurement point based on the phase difference for each vibration frequency. The disaster prediction device 100 obtains the position of each measurement point (distance from the end face) based on the elapsed time from the time when the incident light is input to the end face to the time when the return light is received.

[0019] The above measurement points are set, for example, at predetermined intervals d(m) along the optical fiber that are shorter than the span of the transmission tower 2 (0(m), d(m), . . . , N(m), N+d(m), N+2d(m)). For example, as shown in Fig. 1, if the predetermined interval d is 5(m) and measurement points are set over a maximum range of 70(km) of the power transmission line 3, approximately 14,000 measurement points will be set along the optical fiber.

[0020] The vibration state of the optical fiber 4a at each measurement point includes the effect of sound (sound pressure) received by the optical fiber 4a from the outside. That is, the optical fiber 4a between adjacent transmission towers 2 (span) is a string with the transmission towers 2 at both ends as fixed ends, and resonates with sound of a specific frequency received from the outside, generating a natural vibration.

[0021] The disaster occurrence prediction device 100 acquires information about infrasound (infrasound, micro-pressure waves) based on the time change in the vibration state at each measurement point (time change in vibration intensity for each frequency). For example, when the speed of sound is 340 (m / s), in order to observe infrasound (20 Hz or less), if the frequency of infrasound is 1 Hz, the length of the power transmission line 3 needs to be 1 / 2 (=170 m) of the wavelength (=340 (m / s) / 1 (Hz)) or more. Many existing power transmission lines 3 meet this condition.

[0022] The disaster occurrence prediction device 100 generates information predicting the occurrence of a disaster (hereinafter referred to as “disaster occurrence prediction information”) based on infrasound observed by the DAS, and transmits the generated disaster occurrence prediction information to the alarm device 300.

[0023] Returning to FIG. 1, the warning device 300 is an information processing device (computer) capable of communicating with the disaster occurrence prediction device 100 via the communication network 5, and is, for example, a personal computer, a smartphone, a tablet, various server devices, a mainframe, etc. The warning device 300 is operated, for example, by a facility of an organization that monitors disasters (such as a disaster prevention center or a facility operated by a city, ward, town, or village). Upon receiving disaster occurrence prediction information sent from the disaster occurrence prediction device 100, the warning device 300 outputs information based on the received disaster occurrence prediction information (display on a display device, audio output from an audio output device, etc.).

[0024] Next, the relationship between infrasound and the time change (time change of vibration intensity for each frequency) of the vibration state (vibration intensity, vibration frequency) of each measurement point acquired by the disaster occurrence predicting device 100 using the DAS will be described.

[0025] FIG. 3 is a graph showing the time change in vibration intensity for each frequency at each measurement point, acquired by the disaster occurrence prediction device 100 using the DAS for the power transmission line 3 extending from Hiroshima Prefecture to Shimane Prefecture when an earthquake (seismic intensity "4") occurred in Hyuga-Nada at around 21:14 on July 22, 2023. The three graphs show the time change in vibration intensity for each frequency of the optical fiber 4a, measured at the measurement points of three adjacent spans (spans with identifiers (hereinafter referred to as "span IDs") "K1", "K2", and "K3") of the power transmission line 3 near Hatsukaichi City, Hiroshima Prefecture. In each graph, time flows from top to bottom on the paper. The shade of color in the figure represents the vibration intensity for each frequency (arbitrary unit) (the lighter the color, the greater the vibration intensity).

[0026] As shown in the figure, vibrations with a frequency of 3 to 4 Hz due to infrasound were observed at all measurement points around 21:15:30. In addition, during the same time period, vibrations due to infrasound were observed over a wide frequency band at the measurement points of each span due to the shaking of the earthquake. When the observation results shown in the figure were compared with the micro-pressure vibration observation data during the same time period at an observation point in the "Infrasound Monitoring Network" described in Non-Patent Document 1 (an observation point installed at the Aki City Fire and Disaster Prevention Center (Aki City, Kochi Prefecture). Hatsukaichi City, Hiroshima Prefecture and Aki City, Kochi Prefecture are located approximately equidistant from the Hyuga-Nada Sea), it was confirmed that the standard deviation of the pressure fluctuations increased for about 10 seconds during the same time period and that the standard deviation of the pressure fluctuations peaked at 21:15:33.

[0027] Here, since the transmission speed of infrasound is almost the same as the speed of sound, when an earthquake occurs, it is observed by the DAS before the tsunami arrives. Therefore, when infrasound is observed by the DAS, it is possible to transmit that fact and information based on the observed infrasound (the predicted arrival of a tsunami, the predicted time of the tsunami's arrival, the scale of the tsunami (wave height, etc.)) to the alarm device 300 installed in the area where a disaster is predicted to occur in advance as disaster occurrence prediction information.

[0028] 4A is a diagram showing the main configuration of the disaster occurrence prediction device 100. As shown in the figure, the disaster occurrence prediction device 100 includes a processor 101, a main storage device 102 (memory), an auxiliary storage device 103 (external storage device), an input device 104, an output device 105, a communication device 106, and an optical analysis unit 107. These are communicatively connected via a bus, a communication cable, or the like. Note that the disaster occurrence prediction device 100 may be realized in whole or in part using virtual information processing resources, such as a virtual server provided by a cloud system.

[0029] The processor 101 is configured using, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), an AI (Artificial Intelligence) chip, etc.

[0030] The main memory device 102 is a memory device used when the processor 101 executes a program, and is, for example, a read only memory (ROM), a random access memory (RAM), or a non-volatile memory (NVRAM (Non Volatile RAM)).

[0031] The auxiliary storage device 103 is a device that stores programs and data, and can be configured, for example, with an SSD (Solid State Drive), a hard disk drive, an optical storage device (CD (Compact Disc), DVD (Digital Versatile Disc), etc.). Programs and data can be read into the auxiliary storage device 103 from other information processing devices equipped with non-transient recording media or non-transient storage devices via a recording medium reading device or a communication device 106. The programs and data stored (memorized) in the auxiliary storage device 103 are read into the main storage device 102 as needed.

[0032] The input device 104 is an interface that accepts input of information from the outside, and is, for example, a keyboard, a mouse, a touch panel, a voice input device, or the like.

[0033] The output device 105 is an interface that outputs various information such as the process progress and the process result to the outside. The output device 105 is, for example, a display device (liquid crystal display (LCD) monitor, etc.) that visualizes the various information, a device that converts the various information into voice (voice output device (speaker, etc.)), and a device that converts the various information into text (printer, etc.). For example, the information processing device 10 may be configured to input and output information to and from other devices via the communication device 106.

[0034] The input device 104 and the output device 105 constitute a user interface that realizes interactive processing with the user (receiving information, providing information, etc.).

[0035] The communication device 106 is a device that realizes communication with other devices via a communication network 5 (such as a local area network (LAN), a wide area network (WAN), the Internet, a public communication network, or a dedicated line). The communication device 106 is a wired or wireless communication interface that realizes communication with other devices via a communication medium, such as a network interface card (NIC), a wireless communication module, or a universal serial bus (USB) module.

[0036] The optical analysis unit 107 is a device that measures the vibration state of a measurement point by DAS, and includes a vibration measurement device using C-OTDR and a signal processing circuit. The optical analysis unit 107 includes a CW (continuous wave) laser light source that generates an optical pulse (laser light) to be input to the end face of the optical fiber 4a, an optical pulse generator, an optical amplifier, optical devices (optical detector, optical interferometer), a signal processing circuit (phase calculation circuit, etc.), etc. The optical analysis unit 107 and the optical fiber 4a are connected, for example, by optically connecting the output part of the laser light source of the optical analysis unit 107 to the connection port (socket) of the core wire of the OPGW provided in the substation. Therefore, the connection does not affect the power system, such as a power outage.

[0037] The disaster prediction device 100 may be implemented with, for example, an operating system, a file system, a DBMS (DataBase Management System) (relational database, NoSQL, etc.), a KVS (Key-Value Store), and the like.

[0038] The various functions of the disaster prediction device 100 are realized by the processor 101 reading and executing a program stored in the main memory device 102, or by the hardware (FPGA, ASIC, AI chip, etc.) that constitutes the disaster prediction device 100. The disaster prediction device 100 stores various information (data), for example, as a table of a database or a file managed by a file system.

[0039] 4B is a block diagram illustrating main functions of the disaster occurrence prediction device 100. As shown in the figure, the disaster occurrence prediction device 100 includes a memory unit 110, a vibration state measurement unit 120, an infrasound detection unit 125, a disaster type identification unit 130, a disaster occurrence prediction information generation unit 132, and a disaster occurrence prediction information transmission unit 135.

[0040] Of the above functions, the storage unit 110 stores vibration state for each measurement point 111, infrasound detection information 112, disaster type information 113, disaster occurrence prediction information 114, facility information 115, and geographic information 116. Of these, the vibration state for each measurement point 111, infrasound detection information 112, disaster type information 113, and disaster occurrence prediction information 114 will be described later. The facility information 115 includes information on the power transmission facility (the correspondence between each measurement point and each span, the type of power transmission facility, the positions (latitude, longitude) of the power transmission facility and the span, etc.). Furthermore, the geographic information 116 includes a map and geographic information on the surrounding area where the power transmission facility is deployed.

[0041] The vibration state measurement unit 120 measures the time change of vibration intensity for each frequency at each measurement point on each span using the DAS, and manages the measurement results as vibration state for each measurement point 111. The vibration state for each measurement point 111 includes, for example, information of the graph exemplified in FIG.

[0042] The infrasound detection unit 125 detects infrasound based on the time change in vibration intensity for each frequency at each measurement point included in the vibration state for each measurement point 111 during the above-mentioned period. The infrasound detection unit 125 detects infrasound by monitoring in real time whether or not there is a feature attributable to infrasound in the time change in vibration intensity for each frequency at each measurement point. The infrasound detection unit 125 detects infrasound by, for example, performing data analysis (background noise removal, signal identification, etc.) on the graph shown in FIG. 3.

[0043] When the infrasound detection unit 125 detects infrasound, it manages information indicating that infrasound has been detected and information based on aspects attributable to infrasound in the time change of vibration intensity for each frequency at the measurement point, as infrasound detection information 112. For example, the infrasound detection unit 125 manages information indicating the date and time when infrasound was detected and information used as the basis for determining that infrasound has been detected (for example, information acquired from the graph shown in FIG. 3) as infrasound detection information 112.

[0044] For example, the infrasound detection unit 125 determines that infrasound has been detected when a vibration intensity of a predetermined magnitude or more is observed in the infrasound frequency band (20 Hz or less) at each measurement point of a predetermined number or more adjacent spans. Also, for example, the infrasound detection unit 125 determines that infrasound has been detected when a vibration of a predetermined magnitude or more is observed over a wide frequency band at each measurement point of a predetermined number or more adjacent spans. Note that the infrasound detection unit 125 may detect infrasound by applying a method or criterion other than those described above to the time change in vibration intensity for each frequency at each measurement point. Also, a plurality of methods and criteria may be combined to increase the detection accuracy.

[0045] When the infrasound detection unit 125 detects infrasound, the disaster type identification unit 130 identifies the type of disaster (earthquake, tsunami, typhoon, volcanic eruption, meteorite fall, etc.) based on information (for example, information obtained from the graph shown in Figure 3) that is the basis for determining that infrasound has been detected, and manages the identified type of disaster as disaster type information 113.

[0046] The disaster occurrence prediction information generating unit 132 generates and manages disaster occurrence prediction information 114 based on the infrasound detection information 112 and the disaster type information 113. The disaster occurrence prediction information 114 includes, for example, information indicating the date and time when infrasound was detected and the span where infrasound was detected, which is obtained from the infrasound detection information 112. The disaster occurrence prediction information 114 also includes, for example, information obtained from the disaster type information 113, such as the type of disaster, information specifying the area where a disaster is predicted to occur, the predicted time when the disaster will occur for each specified area, the predicted scale of the disaster for each specified area, and the area where a disaster is predicted (expected) to occur.

[0047] The disaster occurrence prediction information generating unit 132, for example, identifies the position (latitude, longitude) of the span where infrasound was detected from the facility information 115, and compares the identified position with the geographic information 116 to identify an area where a disaster is predicted to occur. For example, the disaster occurrence prediction information generating unit 132 identifies an area that exists within a predetermined distance from the position of the span where infrasound was detected as an area where a disaster is predicted to occur. Furthermore, the disaster occurrence prediction information generating unit 132 determines the predicted time of disaster occurrence and the scale of the disaster for each area, for example, based on the distance between the identified area and the span where infrasound was detected. Furthermore, the disaster occurrence prediction information generating unit 132 determines the scale based on, for example, vibration intensity acquired from the graph shown in FIG. 3.

[0048] A disaster occurrence prediction information transmission unit 135 shown in the figure transmits the disaster occurrence prediction information 114 generated by the disaster occurrence prediction information generation unit 132 to the alarm device 300 via the communication network 5.

[0049] Fig. 5A is a diagram showing the main configuration of the warning device 300. Each element shown in the figure is basically the same as the element with the same name in the disaster prediction device 100 shown in Fig. 4A, so a description thereof will be omitted.

[0050] 5B is a block diagram illustrating main functions of the warning device 300. As shown in the figure, the warning device 300 has the functions of a storage unit 310, a disaster occurrence prediction information receiving unit 320, and a disaster occurrence prediction information output unit 325.

[0051] Of the above functions, the storage unit 110 stores disaster occurrence prediction information 311 .

[0052] The disaster occurrence prediction information receiving unit 320 receives the disaster occurrence prediction information 114 sent from the disaster occurrence prediction device 100 , and manages the received disaster occurrence prediction information 114 as disaster occurrence prediction information 311 .

[0053] The disaster occurrence prediction information output unit 325 outputs information based on the disaster occurrence prediction information 311 to an output device (a display device, an audio output device (speaker), etc.).

[0054] 6 is a flowchart explaining the process performed by the disaster prediction device 100 (hereinafter referred to as "disaster prediction process S600"). The disaster prediction process S600 will be explained below with reference to FIG. 6. Note that, as a premise for the following explanation, it is assumed that the vibration state measurement unit 120 of the disaster prediction device 100 measures the time change (time change of vibration strength for each frequency) of the vibration state (vibration intensity, vibration frequency) of each measurement point on each span in real time using DAS, and manages the latest vibration state of each measurement point as the vibration state for each measurement point 111.

[0055] As shown in the figure, the infrasound detection unit 125 monitors in real time the change over time of the vibration strength for each frequency at each measurement point based on the vibration state for each measurement point 111 (S611 to S612: No). When the infrasound detection unit 125 detects an aspect attributable to infrasound in the change over time of the vibration strength for each frequency at each measurement point acquired from the vibration state for each measurement point 111 (S612: Yes), it generates and manages infrasound detection information 112 for the detected infrasound (S613).

[0056] Next, the disaster type identification unit 130 identifies the type of disaster based on the information used as the basis for determining that the infrasound detection unit 125 has detected infrasound, and manages the identified type of disaster as disaster type information 113 (S614).

[0057] Next, the disaster occurrence prediction information generating unit 132 generates and manages the disaster occurrence prediction information 114 based on the infrasound detection information 112 and the disaster type information 113 (S615).

[0058] Next, the disaster occurrence prediction information transmission unit 135 transmits the disaster occurrence prediction information 114 generated by the disaster occurrence prediction information generation unit 132 to the alarm device 300 via the communication network 5 (S616). After that, the process returns to S611.

[0059] 7 is a flowchart for explaining the process (hereinafter referred to as "disaster occurrence prediction information output process S700") performed by the warning device 300. The disaster occurrence prediction information output process S700 will be explained below with reference to this figure.

[0060] As shown in the figure, the disaster occurrence prediction information receiving unit 320 waits in real time to receive the disaster occurrence prediction information 114 sent from the disaster occurrence prediction device 100 (S711: No). When the disaster occurrence prediction information receiving unit 320 receives the disaster occurrence prediction information 114 (S711: Yes), it manages the received disaster occurrence prediction information 114 as disaster occurrence prediction information 311 (S712).

[0061] Next, the disaster occurrence prediction information output unit 325 outputs information based on the disaster occurrence prediction information 311 to the output device (S713). After that, the process returns to S711.

[0062] FIG. 8 is an example of a screen (hereinafter referred to as a "disaster occurrence prediction information output screen 800") that is displayed when the disaster occurrence prediction information output unit 325 outputs the above information.

[0063] As shown in the figure, the illustrated disaster occurrence prediction information output screen 800 has a display field 811 for the infrasound detection date and time, a display field 812 for the detection distance, a display field 813 for the disaster type, a display field 814 for the predicted disaster occurrence area, a display field 815 for the predicted disaster occurrence time, and a display field 816 for the disaster scale.

[0064] Among these, the infrasound detection date / time display field 811 displays the date / time when the infrasound detection unit 125 detected infrasound.

[0065] Furthermore, the detection span display field 812 displays the span ID of the span where infrasound was detected.

[0066] Furthermore, in the disaster type display field 813, the contents of the disaster type information 113 (information indicating the type of disaster) are displayed.

[0067] Further, in a display field 814 for predicted disaster occurrence areas, information indicating areas where disasters are predicted to occur is displayed.

[0068] Further, in a display field 815 for the predicted disaster occurrence time, the predicted disaster occurrence time is displayed.

[0069] Furthermore, the scale of the disaster that will occur is displayed in a disaster scale display field 816 .

[0070] As described above, the disaster occurrence prediction system 1 of this embodiment monitors in real time whether or not there is a feature caused by infrasound in the time change (time change of vibration intensity for each frequency) of the vibration state (vibration intensity, vibration frequency) of each measurement point acquired by the DAS, and outputs information predicting the occurrence of a disaster when the above-mentioned feature is detected. In this way, the disaster occurrence prediction system 1 uses existing power transmission facilities to quickly provide information predicting the occurrence of a disaster, so that a mechanism for predicting the occurrence of a disaster using infrasound can be realized efficiently and at low cost.

[0071] In addition, the disaster occurrence prediction system 1 outputs information such as the span where infrasound was observed, the type of disaster, the area where the disaster is predicted to occur, the time when the disaster is predicted to occur, and the scale of the disaster as disaster occurrence prediction information 114, so that useful information can be quickly provided to people in areas where a disaster is predicted to occur.

[0072] The above-described embodiment is for the purpose of facilitating understanding of the present invention, and is not intended to limit the present invention. The present invention may be modified or improved without departing from the spirit of the present invention, and equivalents thereof are also included in the present invention.

[0073] For example, when the infrasound detection unit 125 inputs features extracted by performing image recognition processing on the graph (image) shown in FIG. 3 as explanatory variables, a machine learning model that has been trained to output whether or not infrasound has been detected as a target variable may be used.

[0074] Also, for example, when the disaster type identification unit 130 inputs features extracted by performing image recognition processing on the graph (image) shown in Figure 3 as explanatory variables, a machine learning model that has been trained to output information indicating the type of disaster as a target variable may be used.

[0075] Also, for example, the disaster occurrence prediction device 100 may take into account information provided from other systems (for example, the “infrasound monitoring network” described in Non-Patent Document 1) via a communication network 5 or the like to improve the accuracy of the disaster occurrence prediction information.

[0076] Also, for example, the information provided by the disaster occurrence prediction system 1 may be linked with earthquake alerts and warning information issued by public institutions, etc., and used to identify events and prevent false alarms. For example, since an earthquake usually occurs when infrasound is observed, it is possible to verify the accuracy (credibility) of identifying events when issuing earthquake alerts and warning information. [Explanation of symbols]

[0077] 1. Disaster Prediction System 2. Power transmission tower 3. Power Lines 4. OPGW 4a Optical fiber 100 Disaster Prediction Device 107 Optical Analysis Unit 110 Storage section 111 Vibration state at each measurement point 112 Infrasound Detection Information 113 Disaster type information 114 Disaster Prediction Information 115 Equipment information 116 Geographic information 120 Vibration condition measurement unit 125 Infrasound detector 130 Disaster Type Identification Department 132 Disaster Prediction Information Generation Unit 135 Disaster Prediction Information Transmission Department 300 Alarm device 310 Storage section 320 Disaster Prediction Information Reception Unit 325 Disaster Prediction Information Output Unit S600 Disaster occurrence prediction processing S700 Disaster occurrence prediction information output processing 800 Disaster occurrence forecast information output screen

Claims

1. The optical analysis unit and the information processing device are included. Obtaining a time change in vibration intensity for each frequency of an optical fiber at measurement points set along the optical fiber installed along the power transmission line by a distributed acoustic sensing (DAS); Monitor in real time whether or not there is a change in the vibration intensity for each frequency at the measurement point over time that is attributable to infrasound; When the above-mentioned condition is detected, information predicting the occurrence of a disaster is output. Disaster occurrence prediction system.

2. The disaster occurrence prediction system according to claim 1, Identifying the type of the disaster by performing data analysis on the aspect; outputting information indicating the identified type of disaster; Disaster occurrence prediction system.

3. The disaster occurrence prediction system according to claim 1, storing information indicating a correspondence between the measurement points and the spans of the power transmission line; outputting information indicating a span having the measurement point, the information including a feature attributable to infrasound in the time change of the vibration intensity for each frequency; Disaster occurrence prediction system.

4. The disaster occurrence prediction system according to claim 1, storing information indicating a correspondence between the measurement points and the spans of the power transmission lines, information indicating a location of the spans, and geographic information of the vicinity of the power transmission lines; Identifying a span having the measurement point including a feature attributable to infrasound in the time change of the vibration intensity for each frequency, outputting information predicting the occurrence of a disaster in the area surrounding the identified span; Disaster occurrence prediction system.

5. The disaster occurrence prediction system according to claim 4, determining a time when the disaster is predicted to occur in the surrounding area based on the distance from the identified span, and outputting information indicating the determined time. Disaster occurrence prediction system.

6. The disaster occurrence prediction system according to claim 4, determining a scale of the disaster in the surrounding area based on the distance from the identified span, and outputting information indicating the determined scale. Disaster occurrence prediction system.

7. A disaster occurrence prediction system including an optical analysis unit and an information processing device, The information processing device, acquiring, by a distributed acoustic sensing (DAS), a time change in vibration intensity for each frequency of an optical fiber at measurement points set along the optical fiber installed along the power transmission line; A step of monitoring in real time whether or not there is a change in the vibration intensity for each frequency at the measurement point due to infrasound; and a step of outputting information predicting the occurrence of a disaster when the aforementioned aspect is detected; A disaster occurrence prediction method.

8. The disaster occurrence prediction method according to claim 7, The information processing device, Identifying the type of the disaster by performing data analysis on the aspect; and outputting information indicating the identified type of disaster; The disaster occurrence prediction method further comprises:

9. The disaster occurrence prediction method according to claim 7, The information processing device, storing information indicating a correspondence between the measurement points and the spans of the power transmission line; and outputting information indicating a span having the measurement point, the information including a feature attributable to infrasound in the time change of the vibration intensity for each frequency; The disaster occurrence prediction method further comprises:

10. The disaster occurrence prediction method according to claim 7, storing information indicating a correspondence between the measurement points and the spans of the power transmission lines, information indicating a location of the spans, and geographic information of the vicinity of the power transmission lines; Identifying a span having the measurement point including a feature caused by infrasound in the time change of the vibration intensity for each frequency; and outputting information predicting the occurrence of a disaster in an area surrounding the identified span; The disaster occurrence prediction method further comprises: