Disaster information acquisition device and disaster information acquisition system

Abstract

To provide a disaster information acquisition device and a disaster information acquisition system that can acquire plural pieces of disaster information with a simple structure.SOLUTION: The disaster information acquisition device of the present invention includes: a vibration meter which can detect a vibration in a set position; and a data processor for acquiring disaster information of the set position from the result of output of the vibration meter. The data processor includes two or more among a wind rate calculation unit for calculating the estimated value of the wind rate at the set position on the basis of the result of output of the vibration meter; a rainfall intensity calculation unit for calculating the estimated value of the rainfall intensity of the set position from the result of output of the vibration meter; and a sediment disaster detection unit for detecting generation of a sediment disaster in the set position and around the set position from the result of output of the vibration meter.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a disaster information acquisition device and a disaster information acquisition system. [Background technology]

[0002] Regional disaster (hazard) information is generally measured using different sensors for each type of hazard. In Japan, for example, information on earthquakes is collected by the Japan Meteorological Agency's seismic intensity measurement network and the National Research Institute for Earth Science and Disaster Prevention's strong earthquake observation network (K-NET, KiK-net), information on strong winds and heavy rain is collected by the Japan Meteorological Agency's regional weather observation system (Automated Meteorological Data Acquisition System, AMeDAS), and information on the occurrence of landslides is collected by wire sensors installed and managed by the Ministry of Land, Infrastructure, Transport and Tourism and local governments. These information is used to prevent secondary disasters and for evacuation in the event of a disaster. Summary of the Invention [Problem to be solved by the invention]

[0003] However, as mentioned above, when measurements are taken at different locations for each type of disaster, countermeasures tend to be taken separately, which means that comprehensive measures cannot be taken when multiple disasters occur.In addition, measurements are taken using different types of measurement means for each disaster to be detected, and the measurement networks are owned individually by the relevant ministries and agencies, local governments, etc., so installation costs and maintenance costs tend to be high.

[0004] Furthermore, since the equipment using conventional measuring means is owned by different people, the structure of the equipment related to the measuring means is complicated, and the equipment is therefore expensive, it is not easy to install new equipment or change its location, etc. Therefore, it has been difficult to respond by pinpointing various disaster information for a relatively small area, for example.

[0005] The present disclosure aims to provide a disaster information acquisition device and a disaster information acquisition system that are capable of acquiring multiple pieces of disaster information with a simple structure. [Means for solving the problem]

[0006] In order to achieve the above object, a disaster information acquisition device according to a first aspect of the present disclosure includes a vibrometer capable of detecting vibrations at an installation location, and a data processing unit for acquiring disaster information at the installation location from the output results of the vibrometer, wherein the data processing unit includes two or more of: a wind speed calculation unit that calculates an estimated value of wind speed at the installation location from the output results of the vibrometer; a rainfall intensity calculation unit that calculates an estimated value of rainfall intensity at the installation location from the output results of the vibrometer; and a landslide detection unit that detects the occurrence of a landslide at the installation location and around the installation location from the output results of the vibrometer.

[0007] The disaster information acquisition device described above can acquire two or more pieces of disaster information, namely information on strong winds, information on heavy rain, and information on the occurrence of landslides, with a single device. This makes it easier to take comprehensive measures even when multiple disasters occur.

[0008] A disaster information acquisition device according to a second aspect of the present disclosure is the disaster information acquisition device according to the first aspect of the present disclosure, wherein the data processing unit further includes an earthquake detection unit that detects an earthquake at the installation location from the output result of the vibrometer.

[0009] In the disaster information acquisition device described above, in addition to two or more pieces of information on strong winds, heavy rain, and the occurrence of landslides, it is possible to acquire information on earthquakes using a single device.

[0010] A disaster information acquisition device according to a third aspect of the present disclosure is the disaster information acquisition device according to the first or second aspect of the present disclosure, wherein the vibration meter includes a first vibration meter installed on a structure disposed in an air fluid, and the wind speed calculation unit calculates an estimated value of the wind speed at the installation location using a regression model shown in the following equation (1) in which the output result detected by the first vibration meter is used as an explanatory variable.

number

[0011] In the disaster information acquisition device as described above, the wind speed can be detected from the output result of the vibrometer without using a dedicated measuring means.

[0012] A disaster information acquisition device according to a fourth aspect of the present disclosure is the disaster information acquisition device according to the first or second aspect of the present disclosure, wherein the wind speed calculation unit calculates an estimated value of the wind speed at the installation location from an amplitude value in a predetermined frequency range of a Fourier spectrum obtained by Fourier transforming the output result detected by the vibration meter.

[0013] In the disaster information acquisition device as described above, the wind speed can be detected from the output result of the vibrometer without using a dedicated measuring means.

[0014] A disaster information acquisition device according to a fifth aspect of the present disclosure is the disaster information acquisition device according to the third or fourth aspect of the present disclosure, wherein the vibrometer further includes a second vibrometer installed on the ground, and the wind speed calculation unit includes a first vibration determination unit that compares the amplitude value of a Fourier spectrum obtained by Fourier transforming the output result of the first vibrometer with the amplitude value of a Fourier spectrum obtained by Fourier transforming the output result of the second vibrometer and detects whether the difference is equal to or greater than a first threshold, and calculates an estimated value of the wind speed at the installation location from the output result of the first vibrometer when the first vibration determination unit detects a difference equal to or greater than the first threshold.

[0015] In the disaster information acquisition device as described above, vibrations caused by wind can be accurately determined.

[0016] A disaster information acquisition device according to a sixth aspect of the present disclosure is the disaster information acquisition device according to the third or fourth aspect of the present disclosure, wherein the wind speed calculation unit includes a second vibration determination unit that detects whether the duration of vibration detected by the first vibration meter is equal to or greater than a second threshold, and calculates an estimated value of the wind speed at the installation location from the output result of the first vibration meter when the second vibration determination unit detects a duration equal to or greater than the second threshold.

[0017] In the disaster information acquisition device as described above, vibrations caused by wind can be accurately determined.

[0018] A disaster information acquisition device according to a seventh aspect of the present disclosure is the disaster information acquisition device according to the sixth aspect of the present disclosure, wherein the second vibration determination unit determines the duration using at least one of Trifunac's cumulative power method and Jennings' envelope function method.

[0019] In the disaster information acquisition device as described above, the duration of vibration can be accurately determined.

[0020] A disaster information acquisition device according to an eighth aspect of the present disclosure is the disaster information acquisition device according to the first or second aspect of the present disclosure, wherein the rainfall intensity calculation unit calculates an estimated value of rainfall intensity at the installation location from the amplitude of the time history of the output result detected by the vibration meter.

[0021] In the disaster information acquisition device as described above, it is possible to detect rainfall intensity from the output result of the vibration meter without using a dedicated measuring means.

[0022] A disaster information acquisition device according to a ninth aspect of the present disclosure is the disaster information acquisition device according to the first or second aspect of the present disclosure, wherein the rainfall intensity calculation unit calculates an estimate of rainfall intensity at the installation location from an amplitude value in a predetermined frequency range of a Fourier spectrum obtained by Fourier transforming the output result detected by the vibration meter.

[0023] In the disaster information acquisition device as described above, it is possible to detect rainfall intensity from the output result of the vibration meter without using a dedicated measuring means.

[0024] A disaster information acquisition device according to a tenth aspect of the present disclosure is the disaster information acquisition device according to the first or second aspect of the present disclosure, wherein the landslide detection unit detects the occurrence of a landslide at the installation location and the vicinity of the installation location from the number of times the output result detected by the vibration meter exceeds a third threshold within a unit time.

[0025] In the disaster information acquisition device as described above, it is possible to detect the occurrence of a landslide disaster from the output results of the vibrometer without using a dedicated measuring means.

[0026] A disaster information acquisition device according to an eleventh aspect of the present disclosure is a disaster information acquisition device according to any one of the first, second and tenth aspects of the present disclosure, wherein the landslide detection unit includes a high-pass filter that extracts vibration components of frequencies equal to or higher than a predetermined frequency from the output results detected by the vibration meter, and detects the occurrence of a landslide at the installation position and the vicinity of the installation position from the vibration components extracted by the high-pass filter.

[0027] The disaster information acquisition device as described above can accurately determine vibrations caused by the occurrence of a landslide disaster.

[0028] A disaster information acquisition device according to a twelfth aspect of the present disclosure is a disaster information acquisition device according to any of the first, second, tenth, and eleventh aspects of the present disclosure, wherein the landslide detection unit is provided with a fitting unit that fits a curve represented by a Gaussian function to a Fourier spectrum obtained by Fourier transforming the output result of the vibrometer and detects the difference, and detects the occurrence of a landslide at the installation position and around the installation position based on the difference.

[0029] The disaster information acquisition device described above can detect the occurrence of a landslide disaster from the output results of the vibration meter without using a dedicated measuring device, and can also detect landslides that occur at locations distant from the installation location of the vibration meter.

[0030] A disaster information acquisition system according to a thirteenth aspect of the present disclosure includes a vibrometer connected to a communication network and capable of detecting vibrations at an installation location, and a data processing unit capable of acquiring output results of the vibrometer via the communication network and for acquiring disaster information at the installation location from the output results of the vibrometer, wherein the data processing unit includes two or more of: a wind speed calculation unit that calculates an estimated wind speed at the installation location from the output results of the vibrometer; a rainfall intensity calculation unit that calculates an estimated rainfall intensity at the installation location from the output results of the vibrometer; and a landslide detection unit that detects the occurrence of a landslide at the installation location and around the installation location from the output results of the vibrometer.

[0031] The disaster information acquisition system described above can acquire two or more disaster information items, such as information on strong winds, information on heavy rain, and information on the occurrence of landslides, in a single system. This makes it easier to respond comprehensively even when a complex disaster occurs. [Effects of the Invention]

[0032] According to the disaster information acquisition device and disaster information acquisition system of the present disclosure, it is not necessary to prepare multiple measuring means, and it is possible to acquire multiple pieces of disaster information with a simple structure. [Brief explanation of the drawings]

[0033] [Figure 1] 1 is a functional block diagram illustrating an example of a disaster information acquisition device according to an embodiment of the present disclosure. [Figure 2] 2 is a graph showing the relationship between the maximum acceleration detected by the first vibrometer shown in FIG. 1 and the wind speed. [Figure 3] 2 is a graph showing the relationship between RMS acceleration detected by the first vibrometer shown in FIG. 1 and wind speed. [Figure 4] 2 is a graph showing Fourier spectra obtained by Fourier transforming the output results detected by the first and second vibrometers shown in FIG. 1 for each of three directional components. [Figure 5] 1 is a graph showing the results of measuring the duration of vibrations caused by earthquakes and winds using Trifunac's cumulative power method. [Figure 6] 1 is a graph showing the results of measuring the duration of earthquake vibrations and the duration of wind vibrations using Jennings' envelope function method. [Figure 7] 4 is a graph showing the relationship between the acceleration detected by the second vibrometer shown in FIG. 1 and the intensity of rainfall. [Figure 8] 2 is a graph showing Fourier spectra obtained by Fourier transform of the output results of the second vibrometer shown in FIG. 1 observed while changing the rainfall intensity. [Figure 9] 10 is a graph showing the relationship between the amplitude value of the Fourier spectrum obtained by Fourier transforming the output result detected by the second vibrometer shown in FIG. 1 and the rainfall intensity. [Figure 10] 2 is a graph showing an example of an acceleration waveform detected by the vibrometer shown in FIG. 1. [Figure 11] 10 is a graph showing another example of an acceleration waveform detected by the vibrometer shown in FIG. 1 and the relationship between the acceleration waveform and the pulse density. [Figure 12] 11(C) and the acceleration waveform caused by an earthquake. [Figure 13]After applying a high-pass filter to the acceleration waveform detected by the vibrometer and the acceleration waveform caused by the earthquake, a graph similar to that in Figure 12 was generated. [Figure 14] This is a graph showing the Fourier spectra of the vibrations caused by a landslide detected by two different vibrometers. DETAILED DESCRIPTION OF THE INVENTION

[0034] Hereinafter, each embodiment for carrying out the present disclosure will be described with reference to the drawings. Note that the scope necessary for the explanation to achieve the object of the present disclosure will be schematically shown below, and the scope necessary for explaining the relevant parts of the present disclosure will be mainly explained, and the parts for which explanation is omitted will be considered to be publicly known technologies.

[0035] <Overall configuration of the device> 1 is a functional block diagram illustrating an example of a disaster information acquisition device according to an embodiment of the present disclosure. As shown in FIG. 1, the disaster information acquisition device 1 according to this embodiment includes at least a vibration meter 10 capable of detecting vibrations at a specific installation location, and a data processing unit 20 for acquiring disaster information for the installation location from the output result of the vibration meter 10.

[0036] The vibrometer 10 can be installed at any desired location where disaster information is desired to be acquired, and can be configured with a means capable of measuring vibrations occurring at this installation location in three dimensional directions (e.g., X, Y, and Z directions in FIG. 1 ). Examples of the vibrometer 10 include piezoelectric, servo, electromagnetic, and semiconductor vibration sensors (acceleration sensors and velocity sensors), as well as MEMS (microelectromechanical systems) vibration sensors (acceleration sensors and velocity sensors). The vibrometer 10 according to this embodiment includes two vibrometers: a first vibrometer 11 installed on a structure 2 disposed in an air fluid so as to be exposed to the surrounding wind, and a second vibrometer 12 installed on the ground (earth) 3. The number and arrangement of the vibrometers 10 are not limited to those described above and can be changed as appropriate, taking into account the desired disaster information, etc.

[0037] The structure 2 on which the first vibrometer 11 is installed can be configured as, for example, a columnar member erected above the ground 3, installed in a position exposed to wind. The structure 2 is not particularly limited in shape or size, as long as it can vibrate when exposed to wind. Existing structures such as utility poles and streetlights can also be used as this structure 2. On the other hand, the "ground" on which the second vibrometer 12 is installed should be understood to include not only the ground 3 but also structures installed on the ground 3, as long as they do not vibrate when exposed to wind.

[0038] The data processing unit 20 may be a component for acquiring desired disaster information based on the output results of the vibrometer 10. The data processing unit 20 may be realized by, for example, a programmable logic controller (PLC) or a well-known computer connected to a power supply (not shown). Therefore, various calculations performed in the data processing unit 20 may be performed by a processor (not shown) or the like within the data processing unit 20. The data processing unit 20 according to this embodiment includes, for example, a data collection unit 21 that collects the output results of the vibrometer 10, a wind speed calculation unit 22 that calculates an estimate of the wind speed at the installation location from the output results of the vibrometer 10 collected by the data collection unit 21, a rainfall intensity calculation unit 23 that calculates an estimate of the rainfall intensity at the installation location from the output results of the vibrometer 10 collected by the data collection unit 21, a landslide detection unit 24 that detects the occurrence of a landslide at the installation location and its surroundings from the output results of the vibrometer 10 collected by the data collection unit 21, an earthquake detection unit 25 that detects an earthquake at the installation location from the output results of the vibrometer 10 collected by the data collection unit 21, a memory 26 that can store various data, and a communication interface 27. The data processing unit 20 does not need to have all of the above-mentioned components, and can adopt any components selected as appropriate.

[0039] The data collection unit 21 may be electrically connected to the vibrometer 10 via wired or wireless communication and may be capable of collecting output results detected by the vibrometer 10. The output results of the vibrometer 10 may be data indicating changes over time in the detected acceleration (vibration) (specifically, acceleration waveforms or vibration waveforms), or information corresponding thereto, transmitted in the form of electrical signals to the data collection unit 21. The data collection unit 21 may then function to at least temporarily store the received data in the memory 26.

[0040] The wind speed calculation unit 22, the rainfall intensity calculation unit 23, the landslide disaster detection unit 24, and the earthquake detection unit 25 may be components for calculating or detecting desired disaster information, specifically, information on the presence or absence of strong winds, information on the presence or absence of heavy rain, information on the occurrence of a landslide disaster, and information on the presence or absence of an earthquake, from the output results of the vibration meter 10 collected by the data collection unit 21. In this embodiment, the wind speed calculation unit 22, the rainfall intensity calculation unit 23, the landslide disaster detection unit 24, and the earthquake detection unit 25 are provided within the data processing unit 20. This allows disaster information data to be generated within the disaster information acquisition device 1, thereby significantly reducing the amount of data transmitted via the communication interface 27 compared to transmitting the output results of the vibration meter 10, and suppressing an increase in communication traffic. Specific calculation or detection methods used by each component will be described in detail below.

[0041] The memory 26 may be configured with a well-known volatile or non-volatile recording medium, and may store data collected by the data collection unit 21 and information used when calculating or detecting various types of disaster information. The communication interface 27 may be used to transmit and receive various types of disaster information calculated or detected within the data processing unit 20. The communication interface 27 may transmit predetermined disaster information to the management server 4 or the client terminal 5 via a communication network NW connected via wired or wireless communication, or receive control signals transmitted from the management server 4 or the client terminal 5 for calculating or detecting disaster information. While the communication interface 27 is illustrated as being connected to the communication network NW via wired or wireless communication, it may also be used for local connection to the management server 4 or the client terminal 5.

[0042] The disaster information acquisition device 1 according to this embodiment, which is configured as described above, can identify multiple types of disaster information from the output results of the vibration meter 10 serving as a measuring means. Therefore, the methods for acquiring disaster information by the wind speed calculation unit 22, rainfall intensity calculation unit 23, landslide disaster detection unit 24, and earthquake detection unit 25 will be described below in order.

[0043] <Wind speed estimation method> In general, wind speed is measured using a dedicated measuring device such as a windmill-type anemometer. In contrast, the wind speed calculation unit 22 of the disaster information acquisition device 1 according to this embodiment uses the output result of the vibration meter 10 to measure wind speed, or more precisely, to calculate an estimated value of wind speed.

[0044] The wind speed calculation unit 22 according to this embodiment may calculate an estimated value of wind speed based on the output results detected by the vibrometer 10, particularly the first vibrometer 11, collected by the data collection unit 21. That is, the wind speed calculation unit 22 may calculate an estimated value of wind speed using a vibration waveform detected when the first vibrometer 11 and the structure 2 on which the first vibrometer 11 is installed vibrate due to wind.

[0045] In order to identify the correlation between the output result of the first vibrometer 11 and the wind speed of the wind occurring around the first vibrometer 11, the output result when wind of an arbitrary wind speed was applied to the first vibrometer 11 is shown in FIGS. 2 and 3. Here, FIG. 2 is a graph showing the relationship between the maximum acceleration detected by the first vibrometer of the disaster information acquisition device shown in FIG. 1 and the wind speed. FIG. 2(A) plots the maximum acceleration actually observed by the first vibrometer 11 as the observation point on the graph, and FIG. 2(B) shows a function modeling the observation point shown in FIG. 2(A). Also, FIG. 3 is a graph showing the relationship between the RMS (root mean square, also referred to as "effective value") acceleration detected by the first vibrometer of the disaster information acquisition device shown in FIG. 1 and the wind speed. FIG. 3(A) plots the RMS acceleration actually observed multiple times by the first vibrometer 11 as the observation point on the graph, and FIG. 3(B) shows a function modeling the observation point shown in FIG. 3(A). Incidentally, as can be seen by comparing Figures 2 and 3, there is a tendency for RMS acceleration to have smaller variations between observation points than maximum acceleration.

[0046] The observation points are indicated by dots in Figures 2 and 3. From these observation points, it can be seen that the first vibrometer 11 and the structure 2, which are exposed to the wind, are forced to vibrate due to a so-called gust response (or buffeting). Here, the forced vibration due to the gust response can be modeled using an exponential function, as shown in parts A and C enclosed by dotted lines in Figures 2(A) and 3(A).

[0047] On the other hand, when the wind hits the first vibrometer 11 and the structure 2, vortex-induced vibration (or galloping) can occur due to the release of Karman vortices downstream. The increase in acceleration at a specific wind speed caused by this vortex-induced vibration (shown by arrows B and D in Figures 2(A) and 3(A)) can be modeled using a Gaussian function.

[0048] From the above, the wind speed calculation unit 22 can use, for example, a regression model shown in the following equation (1) to calculate an estimated value of the wind speed at the installation position where the first vibrometer 11 is installed from the output result detected by the first vibrometer 11, for example, the RMS acceleration.

number

[0049] The method for calculating the wind speed by the wind speed calculation unit 22 is not limited to the method using the above-mentioned formula (1). Specifically, an estimated value of the wind speed at the installation position can also be calculated from a Fourier spectrum obtained by Fourier transforming the output result detected by the first vibrometer 11. A positive correlation is found between the spectral intensity (average value of Fourier amplitude in a predetermined frequency range) of the Fourier spectrum obtained by Fourier transforming the output result detected by the first vibrometer 11 and the wind speed. Therefore, the spectral intensity in each direction can be modeled using regression analysis into the regression model shown in the above formula (1).

[0050] Therefore, by using the above-described modeled regression equation (1), it is possible to calculate the estimated value x of the wind speed at the installation position where the first vibrometer 11 is installed from the output result of the first vibrometer 11.

[0051] However, the vibrations detected by the first vibrometer 11 are not limited to those caused by wind. For example, if an earthquake occurs at the installation location of the first vibrometer 11, vibrations (seismic motion) caused by the earthquake may also be detected. Therefore, in order to accurately calculate an estimated value of wind speed, it is necessary to identify the cause of the vibrations detected by the first vibrometer 11. Therefore, a method for distinguishing between vibrations caused by wind and vibrations caused by other factors will be described below as one method for calculating an estimated value of wind speed from the output result detected by the first vibrometer 11.

[0052] In order to distinguish whether the vibrations detected by the first vibrometer 11 are caused by wind or other factors, particularly earthquakes, the disaster information acquisition device 1 according to this embodiment includes the above-described second vibrometer 12 in addition to the first vibrometer 11 as the vibrometer 10. The second vibrometer 12 is preferably installed on the ground 3, particularly on the ground 3 relatively close to the structure 2. "Close" here refers to a positional relationship such that, in the event of an earthquake, the seismic motion detected by the first vibrometer 11 and the seismic motion detected by the second vibrometer 12 are substantially the same. Therefore, the positions of the first vibrometer 11 and the second vibrometer 12 do not need to be strictly adjacent to each other as shown in FIG. 1 , but may be separated by a certain distance.

[0053] 1, the wind speed calculation unit 22 may include a first vibration determination unit 31 that determines whether or not the output result of the first vibrometer 11 includes a vibration component caused by wind, based on a difference obtained by comparing the output result of the first vibrometer 11 with the output result of the second vibrometer 12. Specifically, the first vibration determination unit 31 may be capable of determining whether or not the output result of the first vibrometer 11 includes a vibration component caused by wind by comparing the amplitude value of the Fourier spectrum obtained by Fourier transforming the output result of the first vibrometer 11 with the amplitude value of the Fourier spectrum obtained by Fourier transforming the output result of the second vibrometer 12, and detecting whether or not the difference is equal to or greater than a first threshold value.

[0054] 4A to 4C show the Fourier spectra of the X, Y, and Z components of the output results detected by the first and second vibrometers, respectively, and FIGS. 4D to 4F show the Fourier spectra of the X, Y, and Z components of the output results detected by the second vibrometer, respectively. Also shown in FIGS. 4A to 4F are the Fourier spectra of the output results when winds of different speeds (0.4 m / s, 3.1 m / s, and 6.2 m / s) were blown onto each vibrometer.

[0055] As can be seen from Fig. 4, the amplitude of the Fourier spectrum (Fourier amplitude) corresponding to the output result of the second vibrometer 12 installed on the ground 3 hardly changes even when the wind speed changes. On the other hand, the amplitude of the Fourier spectrum corresponding to the output result of the first vibrometer 11 installed on the structure 2 changes significantly in proportion to the wind speed. From this, the first vibration determination unit 31 determines that the vibration components in the output result of the first vibrometer 11 that cannot be detected by the second vibrometer 12 are vibration components caused by wind, thereby preventing the wind speed calculation unit 22 from mistakenly identifying vibration components other than those caused by wind as being caused by wind.

[0056] The determination method used by the first vibration determination unit 31 may be, for example, to compare the amplitude values ​​of the Fourier spectra of the output results of the first and second vibrometers 11 and 12 and determine whether the difference is equal to or greater than a first threshold. The first threshold may be set in advance based on experiments, etc. Then, the wind speed calculation unit 22 calculates an estimated wind speed from the output result of the first vibrometer 11 when a difference equal to or greater than the first threshold is detected, thereby achieving calculation of an estimated wind speed based on the vibration component caused by wind.

[0057] Additionally, in addition to the calculation of the estimated wind speed by the wind speed calculation unit 22 described above, an earthquake may be detected using the earthquake detection unit 25 described below from the output result of the second vibration meter 11 when a difference equal to or greater than the first threshold is detected. If the calculation of the estimated wind speed by the wind speed calculation unit 22 and the detection of an earthquake are performed in parallel, it is possible to obtain a calculation result that takes into account the vibration component due to the earthquake when calculating the estimated wind speed by the wind speed calculation unit 22. Therefore, even if a complex disaster involving an earthquake and strong winds occurs, it is possible to provide the user with information on both disasters with high accuracy.

[0058] The duration of vibration can also be used as another method for determining whether the output result of the first vibration meter 11 includes a vibration component caused by wind. In this regard, the wind speed calculation unit 22 according to this embodiment can include a second vibration determination unit 32 instead of the first vibration determination unit 31 described above or in addition to the first vibration determination unit 31.

[0059] The second vibration determination unit 32 may detect whether the duration of the vibration detected by the first vibrometer 11 is equal to or greater than a second threshold. The method for measuring the duration of the vibration by the second vibration determination unit 32 is not particularly limited, but at least one of the Trifunac cumulative power method and the Jennings envelope function method may be used. The Trifunac cumulative power method defines the cumulative power as the time integral of the squared amplitude of the time history from the beginning to the end of the vibration measurement record, and defines the duration as a certain interval on the time axis of this cumulative power. This is typically the interval where the cumulative power is 5% to 95%. The Jennings envelope function method is a method devised to simulate the time characteristics of the time history waveform of seismic waves. The envelope function consists of an initial part, a main part, and a coda part. The vibration measurement record is fitted to this envelope function, and the duration is determined to be from the start time of the initial part to the end time of the coda part.

[0060] Figure 5 shows the results of measuring the duration of vibrations detected by a vibrometer using Trifunac's cumulative power method. Figure 5(A) shows the duration of vibrations caused by several past earthquakes, and Figure 5(B) shows the duration of vibrations caused by wind at three different times. Figure 6 shows the results of measuring the duration of vibrations detected by a vibrometer using Jennings' envelope function method. Figure 6(A) shows the duration of vibrations caused by several past earthquakes, and Figure 6(B) shows the duration of vibrations caused by wind at three different times. As can be seen from Figures 5 and 6, with both measurement methods, earthquake-induced vibrations lasted relatively short periods of time (less than 100 seconds), while wind-induced vibrations lasted relatively long periods of time (more than 1,500 seconds). Therefore, the second vibration determination unit 32 can accurately determine whether the vibration detected by the vibration meter includes a vibration component caused by wind by setting the second threshold to any value (e.g., 200 seconds) within the range of 100 seconds or more and less than 1500 seconds.

[0061] As described above, according to the wind speed estimation calculation method of the disaster information acquisition device 1 of this embodiment, the wind speed calculation unit 22 can calculate an estimated wind speed from the output results detected by the vibration meter 10. Therefore, disaster information related to strong winds can be acquired without using a dedicated measurement device such as a windmill-type anemometer. Note that the above-mentioned calculation method tends to be relatively less accurate than methods using dedicated measurement devices. However, in the disaster information acquisition device 1 of this embodiment, if it can determine whether or not strong winds, such as wind speeds exceeding 10 m / s, are occurring, the information can be sufficiently used as disaster information. Therefore, it can be said that even the above-mentioned calculation method can acquire disaster information with usable accuracy.

[0062] Furthermore, according to the above-described method, since the vibration meter 10 is used as a means for measuring wind speed, the output result of the vibration meter 10 can be used to obtain information on disasters other than wind speed, such as earthquakes, etc. This makes it possible to obtain information on multiple disasters all at once, thereby enabling comprehensive disaster countermeasures.

[0063] <Rainfall intensity estimation method> To measure rainfall intensity, it is common to use dedicated measuring means such as a tipping bucket rain gauge that collects and measures actual rainfall or a distrometer that measures using laser light. On the other hand, the rainfall intensity calculation unit 23 of the disaster information acquisition device 1 according to this embodiment measures rainfall intensity, or more precisely, calculates an estimated value of rainfall intensity, using the output results of the vibration meter 10 collected by the data collection unit 21, just like in the case of wind speed.

[0064] The rainfall intensity calculation unit 23 of the disaster information acquisition device 1 according to this embodiment may calculate an estimated value of rainfall intensity based on the output result detected by the vibration meter 10, for example, the second vibration meter 12. In other words, the rainfall intensity calculation unit 23 may calculate an estimated value of rainfall intensity using a vibration waveform caused by raindrops falling on or near the second vibration meter 12. Note that the rainfall intensity calculation unit 23 may also use the output result detected by the first vibration meter 11 when calculating the estimated value of rainfall intensity. However, because the first vibration meter 11 may include vibrations due to wind as described above, it is expected that calculation results with higher accuracy can be obtained more easily by using the output result of the second vibration meter 12, which does not substantially include vibrations due to wind.

[0065] In order to identify the correlation between the output result of the second vibrometer 12 and rainfall intensity, the output result when rainfall was artificially induced on the second vibrometer 12 is shown in Fig. 7. Fig. 7 is a graph showing the relationship between the acceleration detected by the second vibrometer shown in Fig. 1 and rainfall intensity, and Figs. 7(A) to 7(C) are plots of the acceleration components in the X, Y, and Z directions, particularly the RMS acceleration, of the output result detected by the second vibrometer 12, at observation points.

[0066] As can be seen from Figure 7, the observed RMS acceleration for each direction and rainfall intensity can be modeled for each of the three directional components using regression analysis, for example, into a linear regression model shown by the dotted line in Figure 7 and the following equation (2).

number

[0067] Therefore, by using the above-described modeled regression equation (2), it is possible to calculate an estimated value y1 of the rainfall intensity at the installation location where the second vibrometer 12 is installed from the amplitude of the time history of the output result of the second vibrometer 12 (specifically, acceleration or velocity).

[0068] FIG. 8 is a graph showing Fourier spectra obtained by Fourier transforming the output results of the second vibrometer shown in FIG. 1 observed at various rainfall intensities. FIGS. 8(A) to 8(C) respectively show the Fourier spectra of the X, Y, and Z components of the output results detected by the second vibrometer. Also, in FIGS. 8(A) to 8(C), R0 indicates the Fourier spectrum when the rainfall intensity is zero, while the other figures indicate the Fourier spectrum when rain is present (specific rainfall intensities are set to 15 mm / h, 75 mm / h, 135 mm / h, and 300 mm / h, respectively). From FIG. 8, it can be seen that the amplitude value of the Fourier spectrum of the second vibrometer 12 tends to increase in proportion to the rainfall intensity in the relatively high frequency range. Based on this point, FIG. 9 shows the relationship between the spectral intensity of the Fourier spectrum (the average value of the Fourier amplitude in a predetermined high frequency band) and the rainfall intensity.

[0069] 9A to 9C are graphs showing the relationship between the rainfall intensity and the spectral intensity values ​​in a specific frequency range of the Fourier spectrum obtained by Fourier transforming the output results detected by the second vibrometer shown in FIG. 1. Each of FIGS. 9A to 9C plots the spectral intensity values ​​of the Fourier spectrum of the X, Y, and Z components of the output results detected by the second vibrometer 12 as observation points. The specific frequency ranges can be set appropriately within a relatively high frequency range. As can be seen from FIG. 9, the observation results of the spectral intensity for each direction in the specific frequency range can be modeled, for example, as a linear regression model shown by the dotted line in FIG. 9 and the following equation (3) for each of the three directional components using regression analysis, similar to that shown in FIG. 7.

number

[0070] Therefore, by using the above-described modeled regression equation (3), it is possible to calculate an estimated value y2 of the rainfall intensity at the installation position where the second vibration meter 12 is installed from the output result of the second vibration meter 12.

[0071] As described above, according to the method for calculating an estimated rainfall intensity in the disaster information acquisition device 1 of this embodiment, the rainfall intensity calculation unit 23 can calculate an estimated rainfall intensity from the output result detected by the vibration meter 10. Therefore, disaster information related to heavy rain can be acquired without using dedicated measurement means such as a tipping bucket rain gauge or a distrometer that measures using laser light. Note that, because the above-described calculation method calculates an estimated value, its accuracy tends to be relatively lower than that of actual measurement of rainfall such as the dedicated measurement means. However, in the disaster information acquisition device 1 of this embodiment, if an approximate rainfall intensity (for example, rainfall intensity with an accuracy of double digits) can be determined, it can be sufficiently used as disaster information. Therefore, it can be said that even the above-described calculation method can acquire disaster information with usable accuracy.

[0072] Furthermore, according to the above-described method, since the vibration meter 10 is used as a means for measuring rainfall intensity, the output result of the vibration meter 10 can be used to obtain information on disasters other than rainfall intensity, such as earthquakes. This makes it possible to obtain information on multiple disasters at once, thereby enabling comprehensive disaster countermeasures.

[0073] <Landslide disaster occurrence detection method> Landslides such as cliff collapses, mudslides, and debris flows are generally detected using dedicated measurement means such as wire sensors that are installed in advance in locations where landslides are likely to occur. On the other hand, the landslide detection unit 24 of the disaster information acquisition device 1 according to this embodiment uses the output results of the vibrometer 10 collected by the data collection unit 21 to detect the occurrence of a landslide.

[0074] The landslide disaster detection unit 24 according to this embodiment can detect the occurrence of a landslide based on the output results detected by the vibration meter 10 and collected by the data collection unit 21. In other words, the landslide disaster detection unit 24 can detect whether the vibrations detected by at least one of the first and second vibration meters 11, 12 are caused by the occurrence of a landslide. Note that the detection of a landslide by the landslide disaster detection unit 24 may use the output results of either the first or second vibration meters 11, 12.

[0075] As a specific method for detecting the occurrence of a landslide disaster, the landslide disaster detection unit 24 can employ a method for detecting the occurrence of a landslide disaster based on the number of pulse peaks that exceed a third threshold (i.e., the number of times the vibration waveform exceeds the third threshold) among the vibration waveforms detected by the vibration meter 10. Note that in order to detect the occurrence of a landslide disaster with high accuracy using this method, it is advisable to place the vibration meter 10 in or near a location where a landslide disaster is likely to occur.

[0076] Fig. 10 is a graph showing an example of an acceleration waveform detected by the vibrometer shown in Fig. 1. The acceleration waveform shown in Fig. 10 is an example of an acceleration waveform of the Z-direction component among the output results detected by the vibrometer 10. In the landslide disaster detection unit 24 according to this embodiment, as shown in Fig. 10, the third threshold is set to ±100 cm / s 2 The landslide disaster detection unit 24 then detects the peak of the pulses that exceed this third threshold (the part marked with an arrow P in FIG. 10), and can detect the occurrence of a landslide disaster based on the number of detected pulses per unit time (for example, one second) (i.e., pulse density). Note that the specific value of the third threshold is not limited to the above, and can be changed as appropriate in consideration of the detection accuracy.

[0077] 11 is a graph showing another example of an acceleration waveform caused by soil movement detected by the vibrometer shown in FIG. 1 and its relationship with pulse density, where FIG. 11(A) shows the acceleration waveform, FIG. 11(B) shows the time series of pulse peaks detected in the acceleration waveform of FIG. 11(A) that exceed the third threshold, and FIG. 11(C) shows the change in the number of pulse peaks (pulse density) detected in FIG. 11(B) in time series. In the acceleration waveform shown in FIG. 11(A), the pulse density of ±100 cm / s 2 The pulse peaks exceeding the third threshold set in (a) appear at the timings shown in Fig. 11(B), and their appearance frequencies are as shown in Fig. 11(C). If the pulse density at which it is determined that the vibration is due to a landslide is set to, for example, 40 times per second, the landslide detection unit 24 can determine from Fig. 11(C) that the landslide occurred 12 seconds after the vibration meter 10 detected the acceleration waveform. The pulse density at which it is determined that the vibration is due to a landslide can be adjusted as appropriate.

[0078] The vibrations detected by the vibrometer 10 are not limited to those caused by landslides, but can also be detected by other disasters, such as earthquakes. Figure 12 is a graph showing the time series of pulse density shown in Figure 11(C) alongside the time series of pulse density of the acceleration waveform caused by an earthquake. Figure 12(A) corresponds to Figure 11(C), and Figures 12(B) and 12(C) show the time series of pulse density obtained by processing the seismic motions of two past earthquakes detected by the vibrometer using a method similar to that shown in Figure 11(C). As can be seen from Figure 12, the pulse density derived from the acceleration waveforms that the vibrometer 10 can detect when an earthquake occurs appears similar to the pulse density derived from the acceleration waveforms that the vibrometer 10 can detect when a landslide occurs. Therefore, there is a possibility that vibrations caused by an earthquake (earthquake motion) may be mistaken for vibrations caused by a landslide, especially when an earthquake occurs near the installation location of the vibrometer 10. Therefore, the following describes a method for the landslide detection unit 24 to distinguish between vibrations caused by landslides and vibrations caused by earthquakes, as one method for reliably detecting vibrations caused by the occurrence of a landslide from the output results of the vibration meter 10.

[0079] Analysis of vibrations caused by earthquakes and vibrations caused by landslides has revealed that most of the vibrations caused by earthquakes are in a lower frequency range than the vibrations caused by landslides. Therefore, the landslide detection unit 24 according to this embodiment uses a high-pass filter 41 that extracts vibration components with frequencies equal to or higher than a predetermined frequency from the output results detected by the vibration meter 10, and identifies whether the vibrations detected by the vibration meter 10 are caused by the occurrence of a landslide or by seismic activity. The following is an example of such a unit.

[0080] The high-pass filter 41 may block vibration components in a relatively low frequency range from the output results detected by the vibration meter 10 and pass vibration components in other frequency ranges. The threshold of this high-pass filter 41 may be set to a frequency that can block vibration components caused by earthquakes. Figure 13 shows the results of applying the high-pass filter 41 to the graphs of vibrations caused by landslides and earthquakes shown in Figure 12. As can be seen from Figure 13, when the high-pass filter 41 is applied, there is almost no change in the pulse density of vibrations caused by landslides (see Figure 13(A)), whereas virtually all components of vibrations caused by earthquakes cannot pass through the high-pass filter 41, resulting in pulse peaks exceeding the third threshold being undetectable (see Figures 13(B) and 13(C)).

[0081] Therefore, by analyzing the vibration components after passing through the high-pass filter 41, the landslide detection unit 24 will no longer mistakenly identify vibrations caused by earthquakes as vibrations caused by the occurrence of landslides, and will be able to accurately detect the occurrence of landslides.

[0082] The above-described method can achieve highly accurate detection of landslides occurring near the vibrometer 10. However, if a landslide occurs at a location distant from the installation position of the vibrometer 10, components in a relatively high frequency range (pulses with large amplitudes) among the vibration components caused by the landslide are attenuated as they reach the installation position of the vibrometer 10. Therefore, the above-described landslide detection method using pulse density alone may not accurately detect landslides occurring at a location distant from the installation position of the vibrometer 10. Therefore, the landslide detection unit 24 according to this embodiment may further include, in addition to the above-described high-pass filter 41, a fitting unit 42 for detecting landslides occurring at a location distant from the installation position of the vibrometer 10. The fitting unit 42 according to this embodiment may fit an arbitrary curve to a Fourier spectrum obtained by Fourier transforming the output result detected by the vibrometer 10.

[0083] Figure 14 shows graphs of Fourier spectra obtained by detecting vibrations caused by landslides using two different vibrometers. Figures 14(A) to 14(C) show the Fourier spectra of the X, Y, and Z components of the output from one vibrometer, respectively. Figures 14(D) to 14(F) show the Fourier spectra of the X, Y, and Z components of the output from the other vibrometer, respectively. Figure 14 also shows approximate curves obtained by fitting arbitrary curves to each Fourier spectrum. Both the first and second vibrometers can be installed in the ground, similar to the second vibrometer 12, but their installation locations may be different. The observation records shown in Figure 14 indicate that the Fourier spectrum of vibrations caused by landslides exhibits a stable, single-peaked convex shape. Therefore, the Fourier spectrum of vibrations caused by landslides can be modeled, for example, as a Gaussian function, as shown in Equation (4) below.

number

[0084] Considering the above, the fitting unit 42 of the landslide disaster detection unit 24 fits a curve represented by the Gaussian function shown in Equation (4) to the Fourier spectrum of the output result of the vibrometer 10, and based on the difference between the two, i.e., the Fourier spectrum and the Gaussian function, it can identify that the vibration detected by the vibrometer 10 is caused by the occurrence of a landslide disaster. For example, this identification can be performed by comparing the difference with a fourth threshold value set in advance. Furthermore, for example, the residual sum of squares or normalized RMSE (root mean square error) can be used as an index for the difference.

[0085] Therefore, the landslide detection unit 24 continuously creates an approximation curve expressed by a Gaussian function from the detection results of the vibration meter 10 in the fitting unit 42, and by comparing it with the Fourier spectrum of the measured vibration, it becomes possible to detect landslides that occur at locations far from the vibration meter 10.

[0086] As described above, according to the landslide disaster detection method of the disaster information acquisition device 1 of this embodiment, the landslide disaster detection unit 24 can detect not only landslide disasters occurring near the installation location of the vibrometer 10 but also landslide disasters occurring far from the installation location of the vibrometer 10 from the output results detected by the vibrometer 10. Therefore, disaster information related to landslide disasters can be acquired without using a dedicated measurement means such as a wire sensor. Furthermore, according to the landslide disaster detection method described above, landslide disasters occurring far from the installation location of the vibrometer 10 can be detected, making it easier to detect landslide disasters over a wider area than by installing a wire sensor. Note that, to further improve the accuracy of landslide disaster detection, a well-known geophone (georeceiver) or the like may be separately and supplementarily employed.

[0087] Furthermore, according to the above-described method, since the vibration meter 10 is used as a means for measuring landslides, the output results of the vibration meter 10 can be used to obtain information on disasters other than landslides such as earthquakes. This makes it possible to obtain information on multiple disasters at once, thereby enabling comprehensive disaster countermeasures.

[0088] <Earthquake detection method> Finally, a brief description will be given of the case where an earthquake is detected using the disaster information acquisition device 1 according to this embodiment. The disaster information acquisition device 1 according to this embodiment may include an earthquake detection unit 25 that detects an earthquake at the installation location of the vibrometer 10 based on the output result of the vibrometer 10. The earthquake detection unit 25 may employ a conventionally known conversion method to detect the seismic intensity of an earthquake from the acceleration waveform detected by the vibrometer 10. Specifically, the acceleration components of the X, Y, and Z directions detected by the vibrometer are subjected to Fourier transform, filtering, and inverse Fourier transform in this order, and a vector waveform is synthesized from the obtained values. The synthesized value A of the obtained vector waveform is then used to calculate I=2logA+0.94, which determines the measured seismic intensity I, thereby detecting the seismic intensity of the earthquake. Furthermore, to further improve the accuracy of earthquake detection, a known magnetic sensor or the like may be separately employed.

[0089] The disaster information acquired by the earthquake detection method described above does not prevent the acquisition of other disaster information calculated or detected by the disaster information acquisition device 1 according to this embodiment. Specifically, when the wind speed calculation unit 22 calculates an estimated wind speed and the earthquake detection unit 25 detects an earthquake simultaneously, for example, the output result detected by the first vibrometer 11 may be used to calculate the estimated wind speed, and the output result detected by the second vibrometer 12 may be used to detect the earthquake. Alternatively, as described above, taking into consideration that wind-induced vibrations last longer than earthquake-induced vibrations, the wind speed calculation unit 22 may calculate an estimated wind speed based on data detected by the first vibrometer 11 for a time other than the time when the earthquake was detected, thereby enabling both earthquakes and wind speeds to be calculated and detected with high accuracy.

[0090] Furthermore, when the calculation of an estimated value of rainfall intensity by the rainfall intensity calculation unit 23 and the detection of an earthquake by the earthquake detection unit 25 are performed simultaneously, it is sufficient to determine whether the vibration is caused by rainfall or an earthquake based on the frequency characteristics of the vibration detected by the vibrometer. Specifically, when it is desired to detect an earthquake during a rainfall period, it is sufficient to extract components with desired frequency characteristics from the output result detected by the vibrometer using a low-pass filter that passes only relatively low frequencies, and then detect the earthquake by the earthquake detection unit 25. Furthermore, when the detection of the occurrence of a landslide disaster by the landslide disaster detection unit 24 and the detection of an earthquake by the earthquake detection unit 25 are performed simultaneously, it is sufficient to distinguish between the two and detect them by taking into consideration, for example, the frequency range of the vibration detected by the vibration meter 10.

[0091] As described above, according to the earthquake detection method of the disaster information acquisition device 1 of this embodiment, the earthquake detection unit 25 can detect an earthquake that has occurred at the installation position of the vibration meter 10 from the output result detected by the vibration meter 10 without interfering with the detection of other disaster information. Therefore, it becomes possible for the disaster information acquisition device 1 to acquire multiple pieces of disaster information.

[0092] In addition, the disaster information acquisition device 1 according to this embodiment can also calculate or detect disaster information other than earthquakes in parallel without interfering with each other's acquisition. Specifically, for example, the calculation of an estimated wind speed and the calculation of an estimated rainfall intensity can be performed separately by using the output results of different vibration meters. Furthermore, since the calculation of an estimated rainfall intensity and the detection of the occurrence of a landslide disaster involve completely different vibration components, the calculation and detection can be performed separately based on the magnitude of the vibration components. Furthermore, the calculation of an estimated wind speed and the detection of the occurrence of a landslide disaster can be performed separately by using the output results of different vibration meters, just as in the case of the calculation of an estimated wind speed and the calculation of an estimated rainfall intensity.

[0093] Furthermore, although the disaster information acquisition device 1 according to the embodiment described above has been described as a single device in which the vibrometer 10 and the data processing unit 20 are locally connected, the disaster information acquisition device 1 can also be modified to be a system in which the vibrometer 10 and the data processing unit 20 exist separately. Specifically, a disaster information acquisition system can also be configured in which an information terminal (such as the server 4 shown in FIG. 1 ) installed at a location remote from the vibrometer 10 functions as the data processing unit 20. In this case, the information terminal functioning as the data processing unit 20 and the vibrometer 10 are connected via a communication network, and the output result of the vibrometer 10 can be transmitted to the information terminal, thereby enabling the information terminal to acquire disaster information for the location where the vibrometer 10 is installed.

[0094] Furthermore, the regression equations used in some of the calculation methods or detection methods exemplified in the present embodiment can be replaced by other regression analysis equations, i.e., a parametric regression equation other than those described above can be replaced, or similar results can be obtained using non-parametric regression.

[0095] The present disclosure is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit and scope of the present disclosure, all of which are included in the technical concept of the present disclosure. [Explanation of symbols]

[0096] 1 Disaster information acquisition device 2 structures 3 Ground 10 Vibration meter 11 First Vibration Meter 12 Second Vibration Meter 20 Data Processing Unit 21 Data Collection Department 22 Wind speed calculation section 23 Rainfall intensity calculation section 24 Landslide detection unit 25 Earthquake detection unit 26 memory 27 Communication Interface 31 First vibration determination unit 32 Second vibration determination unit 41 High-pass filter 42 Fitting section

Claims

1. a vibration meter capable of detecting vibrations at the installation position; a data processing unit for acquiring disaster information for the installation position from the output result of the vibration meter, the data processing unit includes one or more of a wind speed calculation unit that calculates an estimated value of wind speed at the installation position from the output result of the vibrometer, a rainfall intensity calculation unit that calculates an estimated value of rainfall intensity at the installation position from the output result of the vibrometer, and a landslide disaster detection unit that detects the occurrence of a landslide disaster at the installation position and around the installation position from the output result of the vibrometer; The vibrometer includes a first vibrometer installed on a structure disposed in an air fluid; the wind speed calculation unit calculates an estimated value of the wind speed at the installation position using a regression model shown in the following formula (1) in which the output result detected by the first vibrometer is used as an explanatory variable: Disaster information acquisition device. [Equation 1] Here, x is the wind speed, y is the output result of the first vibrometer, and a, b, c, α, and β are arbitrary constants.

2. A vibration meter capable of detecting vibration at the installation position; a data processing unit for acquiring disaster information for the installation position from the output result of the vibration meter, the data processing unit includes one or more of a wind speed calculation unit that calculates an estimated value of wind speed at the installation position from the output result of the vibrometer, a rainfall intensity calculation unit that calculates an estimated value of rainfall intensity at the installation position from the output result of the vibrometer, and a landslide disaster detection unit that detects the occurrence of a landslide disaster at the installation position and around the installation position from the output result of the vibrometer; the vibrometer comprises a first vibrometer installed on a structure disposed in an air fluid, and a second vibrometer installed on the ground; the wind speed calculation unit includes a first vibration determination unit that compares an amplitude value of a Fourier spectrum obtained by Fourier transforming the output result of the first vibrometer with an amplitude value of a Fourier spectrum obtained by Fourier transforming the output result of the second vibrometer, and detects whether the difference is equal to or greater than a first threshold value; and calculates an estimated value of the wind speed at the installation position from the output result of the first vibrometer when the first vibration determination unit detects a difference equal to or greater than the first threshold value. Disaster information acquisition device.

3. The data processing unit further includes an earthquake detection unit that detects an earthquake at the installation position from an output result of the vibrometer. The disaster information acquisition device according to claim 1 or 2.

4. the wind speed calculation unit includes a second vibration determination unit that detects whether the duration of the vibration detected by the first vibration meter is equal to or greater than a second threshold, and calculates an estimated value of the wind speed at the installation position from an output result of the first vibration meter when the second vibration determination unit detects a duration equal to or greater than the second threshold. The disaster information acquisition device according to claim 1 or 2.

5. the second vibration determination unit specifies the duration using at least one of a Trifunac cumulative power method and a Jennings envelope function method; The disaster information acquisition device according to claim 4 .

6. the rainfall intensity calculation unit calculates an estimated value of rainfall intensity at the installation position from the amplitude of a time history of the output result detected by the vibration meter. The disaster information acquisition device according to claim 1 or 2.

7. the rainfall intensity calculation unit calculates an estimated value of rainfall intensity at the installation position from an amplitude value in a predetermined frequency region of a Fourier spectrum obtained by Fourier transforming the output result detected by the vibration meter. The disaster information acquisition device according to claim 1 or 2.

8. the landslide disaster detection unit detects the occurrence of a landslide disaster at the installation position and around the installation position based on the number of times that the output result detected by the vibration meter exceeds a third threshold within a unit time. The disaster information acquisition device according to claim 1 or 2.

9. The landslide disaster detection unit includes a high-pass filter that extracts vibration components having a frequency equal to or higher than a predetermined frequency from the output result detected by the vibration meter, and detects the occurrence of a landslide disaster at the installation position and the vicinity of the installation position from the vibration components extracted by the high-pass filter. The disaster information acquisition device according to claim 1 , 2 , or 8 .

10. The landslide disaster detection unit includes a fitting unit that fits a curve represented by a Gaussian function to a Fourier spectrum obtained by Fourier transforming the output result of the vibrometer and detects the difference, and detects the occurrence of a landslide disaster at the installation position and around the installation position based on the difference. The disaster information acquisition device according to any one of claims 1 to 9.

11. a vibration meter connected to a communication network and capable of detecting vibrations at an installation position; a data processing unit capable of acquiring an output result of the vibrometer via the communication network, and for acquiring disaster information for the installation position from the output result of the vibrometer; the data processing unit includes one or more of a wind speed calculation unit that calculates an estimated value of wind speed at the installation position from the output result of the vibrometer, a rainfall intensity calculation unit that calculates an estimated value of rainfall intensity at the installation position from the output result of the vibrometer, and a landslide disaster detection unit that detects the occurrence of a landslide disaster at the installation position and around the installation position from the output result of the vibrometer; The vibrometer includes a first vibrometer installed on a structure disposed in an air fluid; the wind speed calculation unit calculates an estimated value of the wind speed at the installation position using a regression model shown in the following formula (1) in which the output result detected by the first vibrometer is used as an explanatory variable: [Equation 1] Here, x is the wind speed, y is the output result of the first vibrometer, and a, b, c, α, and β are arbitrary constants. Disaster information acquisition system.

12. A vibration meter connected to a communication network and capable of detecting vibrations at an installation position; a data processing unit capable of acquiring an output result of the vibrometer via the communication network, and for acquiring disaster information for the installation position from the output result of the vibrometer; the data processing unit includes one or more of a wind speed calculation unit that calculates an estimated value of wind speed at the installation position from the output result of the vibrometer, a rainfall intensity calculation unit that calculates an estimated value of rainfall intensity at the installation position from the output result of the vibrometer, and a landslide disaster detection unit that detects the occurrence of a landslide disaster at the installation position and around the installation position from the output result of the vibrometer; the vibrometer comprises a first vibrometer installed on a structure disposed in an air fluid, and a second vibrometer installed on the ground; the wind speed calculation unit includes a first vibration determination unit that compares an amplitude value of a Fourier spectrum obtained by Fourier transforming the output result of the first vibrometer with an amplitude value of a Fourier spectrum obtained by Fourier transforming the output result of the second vibrometer, and detects whether the difference is equal to or greater than a first threshold value; and calculates an estimated value of the wind speed at the installation position from the output result of the first vibrometer when the first vibration determination unit detects a difference equal to or greater than the first threshold value. Disaster information acquisition system.

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