An earthquake early warning anti-false alarm method and system

Abstract

The present invention relates to the field of earthquake early warning, and particularly to an earthquake early warning anti-false alarm method and system. The method includes: obtaining earthquake data sets of each monitoring point, where the earthquake data sets include the acceleration of seismic waves; calculating the characteristic values of the seismic waves, and the characteristic values are positively correlated with the acceleration; obtaining the acceleration of the mobile device and constructing an acceleration vector, calculating the state parameters of the mobile device, correcting the state parameters to obtain the optimal state parameters, and predicting the earthquake magnitude according to the optimal state parameters. The present invention can prevent the phenomenon of false alarms in earthquake early warning.

Description

Technical Field

[0001] The present invention relates to the field of earthquake early warning, and particularly to an earthquake early warning anti-false alarm method and system. Background Art

[0002] An earthquake, also known as ground motion or earth vibration, is a natural phenomenon that causes vibrations during the rapid release of energy in the earth's crust, during which seismic waves are generated. The main cause of earthquakes is the mutual extrusion and collision between plates on the earth, resulting in dislocation and rupture at the edges and within the plates. Earthquake early warning refers to using the characteristic that the propagation speed of seismic waves is less than that of electric waves during an earthquake to give an early warning to the target area where the seismic waves have not yet arrived in advance. After receiving the early warning, the public and projects can take evasive actions and emergency responses to reduce casualties and secondary disasters.

[0003] The Chinese patent application document with the publication number CN116340757A discloses a characteristic adaptive earthquake early warning magnitude prediction method and its system. The method includes the following steps: S1: Obtain historical earthquake data, perform feature selection from it, and obtain the selected features; S2: Establish an earthquake early warning magnitude prediction model based on a support vector machine according to the selected features; S3: Obtain real-time earthquake data and obtain the selected real-time feature data; S4: Input the selected real-time feature data into the earthquake early warning magnitude prediction model based on a support vector machine to obtain the predicted earthquake early warning magnitude. Through feature selection, representative features are summarized from seismic signals, and a classification model is constructed based on this to improve the magnitude evaluation effect and reduce the computational complexity.

[0004] During earthquake early warning, there are non-earthquake interferences, such as explosion vibrations and impacts between objects, which will generate signals similar to seismic waves, resulting in misjudgment of the system as an earthquake and low accuracy of the system's earthquake early warning. Summary of the Invention

[0005] To solve the problem of false alarms during earthquake early warning, the present invention provides an earthquake early warning anti-false alarm method and system.

[0006] In the first aspect, the present invention provides an earthquake early warning anti-false alarm method, adopting the following technical solution:

[0007] Obtain the earthquake data set of each monitoring point, where the earthquake data set includes the acceleration of seismic waves; calculate the characteristic value of the seismic wave, and the characteristic value is positively correlated with the acceleration;

[0008] Obtain the acceleration of the mobile device and construct an acceleration vector, calculate the state parameter of the mobile device, correct the state parameter to obtain the optimal state parameter, and predict the earthquake level according to the optimal state parameter; where the expression of the state parameter is:

[0009] ;

[0010] Wherein, represents the device state parameter of the mobile device j corresponding to the monitoring point i, represents the propagation acceleration of the seismic wave in the geological environment corresponding to the monitoring point i, represents the acceleration of the mobile device j corresponding to the monitoring point i, represents the acceleration vector of the mobile device j corresponding to the monitoring point i, represents the propagation acceleration vector of the seismic wave in the geological environment corresponding to the monitoring point i, represents the eigenvalue of the seismic wave at the monitoring point i, represents the density difference between the geological density of the monitoring point i and the density of the epicenter geology, represents the distance between the mobile device j and the monitoring point i.

[0011] By calculating the device state parameter, it is possible to understand the degree of influence of the seismic wave on the mobile device during an earthquake, that is, by observing the mobile device in a moving state, the intensity of the seismic wave can be understood, and thus the magnitude of the current earthquake can be judged according to the intensity of the seismic wave. By comparing the obtained earthquake magnitude with the earthquake magnitude obtained from the outside world, the phenomenon of false earthquake early warning can be prevented.

[0012] Preferably, the expression of the eigenvalue is:

[0013] ;

[0014] Wherein, represents the eigenvalue of the seismic wave at the monitoring point i, represents the propagation acceleration of the seismic wave in the geological environment corresponding to the monitoring point i, represents the time required for the seismic wave to reach the monitoring point i, represents the epicenter distance.

[0015] Calculating the eigenvalue through factors in multiple dimensions improves the accuracy of the calculated result of the eigenvalue.

[0016] Preferably, the expression of the eigenvalue is:

[0017] ;

[0018] Wherein, represents the eigenvalue of the seismic wave at the monitoring point i, represents the propagation acceleration of the seismic wave in the geological environment corresponding to the monitoring point i, represents the time required for the seismic wave to reach the monitoring point i, represents the epicenter distance, and exp represents the exponential function with e as the base.

[0019] The degree of influence of seismic waves on the monitoring points and the characteristics of seismic waves can be understood through the eigenvalue. The larger the eigenvalue, the greater the damage degree of the seismic wave, the higher the corresponding earthquake level, and the greater the influence of the seismic wave on the monitoring point.

[0020] Preferably, the method for correcting the state parameters is as follows:

[0021] Obtain a historical data set, where the historical data set includes the eigenvalues of seismic waves in historical earthquakes;

[0022] Calculate the loss functions of the generator and discriminator in the GAN algorithm, and use the GAN algorithm to adjust the state parameters to obtain the optimal state parameters;

[0023] ;

[0024] In the formula, represents the loss function of the generator, represents the loss function of the discriminator, represents the device state parameter of the mobile device j corresponding to the monitoring point i, represents the eigenvalue of the l-th seismic wave at the monitoring point i during a historical earthquake, represents the expected value of sampling in the historical real data distribution, represents the expected value of sampling the generated data in the prior distribution.

[0025] By constructing the loss function, the accuracy of the GAN algorithm in correcting the state parameters is improved, and further the accuracy of the optimal state parameters is improved, which is convenient for predicting the earthquake level.

[0026] Preferably, the expression of the propagation acceleration is:

[0027] ;

[0028] In the formula, represents the propagation acceleration of the seismic wave in the geological environment corresponding to the monitoring point i, represents the component of the acceleration on the X-axis of the space coordinate system, represents the acceleration in the space coordinate system axis component, represents the component of the acceleration on the z-axis of the space coordinate system.

[0029] Preferably, the method for predicting the earthquake level based on the optimal state parameters is: set multiple state parameter intervals, each state parameter corresponds to an earthquake level, and obtain the earthquake level according to the state parameter interval in which the optimal state parameter falls.

[0030] Predicting the current earthquake magnitude through optimal state parameters provides a theoretical basis for earthquake early warning and prevents false earthquake alarms.

[0031] Preferably, the seismic waves include P-waves and S-waves.

[0032] In a second aspect, the present invention provides an earthquake early warning anti-false alarm system, adopting the following technical solutions:

[0033] An earthquake early warning anti-false alarm system includes: a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, an earthquake early warning anti-false alarm method as described above is implemented.

[0034] Generate a computer program for the earthquake early warning anti-false alarm method as described above and store it in the memory to be loaded and executed by the processor. Thus, a system is made according to the memory and the processor, which is convenient to use.

[0035] The present invention has the following technical effects:

[0036] By calculating the state parameters of the device, it is possible to understand the degree of influence of the mobile device by seismic waves during an earthquake, that is, by observing the mobile device in a moving state, the intensity of the seismic waves can be understood. Thus, the magnitude of the current earthquake can be judged according to the intensity of the seismic waves, and the magnitude of the earthquake obtained is compared with the earthquake magnitude obtained from the outside, thereby preventing the phenomenon of false earthquake early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the drawings, several embodiments of the present invention are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0038] Figure 1 It is a flowchart of an earthquake early warning anti-false alarm method according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0040] It should be understood that when terms such as "first" and "second" are used in the claims, the description, and the drawings of the present invention, they are only used to distinguish different objects and not to describe a specific order. The terms "comprising" and "including" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0041] An embodiment of the present invention discloses a method for preventing false alarms in earthquake early warning. Referring to Figure 1 , the method includes the following steps, specifically as follows:

[0042] S1: Obtain the earthquake data sets of each monitoring point.

[0043] The earthquake data sets include the propagation acceleration of seismic waves, the time when the seismic waves reach the monitoring point, and the epicenter distance; wherein, the acceleration is calculated from the acceleration components in each direction of the spatial coordinate system, and the seismic waves include P-waves and S-waves.

[0044] The expression for the propagation acceleration is:

[0045] ;

[0046] In the formula, represents the propagation acceleration of the seismic wave in the geological environment corresponding to monitoring point i, represents the component of the acceleration on the X-axis of the spatial coordinate system, represents the component of the acceleration on the axis of the spatial coordinate system, represents the component of the acceleration on the z-axis of the spatial coordinate system.

[0047] S2: Calculate the characteristic value of the seismic wave, and the characteristic value is positively correlated with the acceleration.

[0048] In one embodiment, the expression for the characteristic value is:

[0049] ;

[0050] In the formula, represents the characteristic value of the seismic wave at monitoring point i, represents the propagation acceleration of the seismic wave in the geological environment corresponding to monitoring point i, represents the time required for the seismic wave to reach monitoring point i, represents the epicenter distance.

[0051] The greater the propagation acceleration of the seismic wave, the faster the speed of the seismic wave when it reaches the monitoring point, and the greater the impact of the seismic wave on the monitoring point. Similarly, the less time it takes for the seismic wave to reach the monitoring point and the smaller the epicenter distance, the greater the impact of the seismic wave on the monitoring point. The eigenvalue of the seismic wave at the monitoring point comprehensively reflects the degree of influence of the seismic wave on the monitoring point and the characteristics of the seismic wave. Specifically, the larger the eigenvalue, the greater the damage degree of the seismic wave, the higher the corresponding earthquake magnitude, and the greater the impact of the seismic wave on the monitoring point. Conversely, the smaller the eigenvalue, the smaller the damage degree of the seismic wave, the lower the corresponding earthquake magnitude, and the smaller the impact of the seismic wave on the monitoring point.

[0052] In one embodiment, the expression of the eigenvalue is:

[0053] ;

[0054] In the formula, represents the eigenvalue of the seismic wave at monitoring point i, represents the propagation acceleration of the seismic wave in the geological environment corresponding to monitoring point i, represents the time required for the seismic wave to reach monitoring point i, represents the epicenter distance, and exp represents the exponential function with base e.

[0055] S3: Obtain the acceleration of the mobile device and construct an acceleration vector, and calculate the state parameters of the mobile device.

[0056] Set a mobile device at the monitoring point. The mobile device can be an electronic device in a moving state, such as a mobile phone or a tablet. Collect the acceleration of the mobile device in a moving state and construct an acceleration vector according to the acceleration.

[0057] The expression of the state parameter is:

[0058] ;

[0059] In the formula, represents the device state parameter of mobile device j corresponding to monitoring point i, represents the propagation acceleration of the seismic wave in the geological environment corresponding to monitoring point i, represents the acceleration of mobile device j corresponding to monitoring point i, represents the acceleration vector of mobile device j corresponding to monitoring point i, represents the propagation acceleration vector of the seismic wave in the geological environment corresponding to monitoring point i, represents the eigenvalue of the seismic wave at monitoring point i, represents the geological density difference corresponding to monitoring point i, specifically the density difference between the geology of the monitoring point and the geology of the epicenter, Denotes the distance between mobile device j and monitoring point i.

[0060] It reflects the impact of the acceleration of the mobile device on the propagation acceleration of seismic waves. The larger its value, the greater the impact of the moving mobile device on the propagation acceleration of the collected seismic waves, preliminarily indicating that the mobile device is greatly affected by the earthquake and the higher the earthquake magnitude; Reflects the influence of geological conditions and distance on the device state parameters.

[0061] The overall device state parameters reflect the degree of influence of seismic waves on the mobile device during an earthquake, that is, by observing the moving mobile device, the intensity of seismic waves can be understood, reducing the interference caused by external factors to the earthquake magnitude during earthquake early warning.

[0062] S4: Modify the state parameters to obtain the optimal state parameters.

[0063] Obtain the historical data set, which includes the characteristic values of seismic waves in historical earthquakes; calculate the loss functions of the generator and discriminator in the GAN algorithm, and use the GAN algorithm to adjust the state parameters to obtain the optimal state parameters;

[0064] ;

[0065] In the formula, Represents the loss function of the generator, Represents the loss function of the discriminator, Represents the device state parameter of mobile device j corresponding to monitoring point i, Represents the characteristic value of the l-th seismic wave at monitoring point i during historical earthquakes, Represents the expected value of sampling in the historical real data distribution, Represents the expected value of sampling the generated data in the prior distribution, Represents the logarithmic function with base e.

[0066] Through Reflects the confidence of real data. Through Reflects the confidence of generated data. Using the GAN algorithm to adjust the state parameters is a prior art, and the specific steps are not elaborated here.

[0067] S5: Predict the earthquake magnitude according to the optimal state parameters.

[0068] Set multiple state parameter intervals, where each state parameter corresponds to an earthquake magnitude. Obtain the earthquake magnitude based on the state parameter interval into which the optimal state parameter falls. Compare the obtained earthquake magnitude with the earthquake magnitude in the received external earthquake information. If the two results are inconsistent, send a prompt message indicating the inconsistent magnitudes to prevent false alarms in earthquake early warnings.

[0069] Exemplarily, the state parameter intervals are 、 and , corresponding to earthquake magnitudes of level 1, level 2, and level 3 respectively. When the state parameter falls into the interval during earthquake prediction, it indicates that the current earthquake magnitude is level 2.

[0070] An embodiment of the present invention also discloses an earthquake early warning anti-false alarm system, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, an earthquake early warning anti-false alarm method according to the present invention is implemented.

[0071] The above system also includes other components well-known to those skilled in the art, such as a communication bus and a communication interface. Their settings and functions are known in the art, so they will not be elaborated here.

[0072] In the present invention, the aforementioned memory can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, device, or component. For example, a computer-readable storage medium can be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory (RRAM), a dynamic random access memory (DRAM), a static random access memory (SRAM), an enhanced dynamic random access memory (EDRAM), a high bandwidth memory (HBM), a hybrid memory cube (HMC), etc., or any other medium that can be used to store the required information and can be accessed by an application program, module, or both. Any such computer storage medium can be part of the device or accessible or connectable to the device.

[0073] Although this specification has shown and described multiple embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will envision many changes, alterations, and alternative ways without departing from the spirit and concept of the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed in the practice of the present invention.

[0074] The above are all preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention shall be covered within the protection scope of the present invention.

Claims

1. A method for preventing false alarms of earthquake early warning, characterized in that: Includes steps: Obtaining a seismic data set at each monitoring point, the seismic data set including the acceleration of the seismic wave; calculating the characteristic value of the seismic wave, the characteristic value is positively correlated with the acceleration; The acceleration of the mobile device is obtained and the acceleration vector is constructed. The state parameters of the mobile device are calculated, the state parameters are corrected to obtain the optimal state parameters, and the earthquake level is predicted based on the optimal state parameters. The expression of the state parameters is: ； In the formula, represents the device state parameter of mobile device j corresponding to monitoring point i, represents the propagation acceleration of seismic waves in the geological environment corresponding to the monitoring point i, represents the acceleration of mobile device j corresponding to monitoring point i, represents the acceleration vector of mobile device j corresponding to monitoring point i, represents the propagation acceleration vector of the seismic wave in the geological environment corresponding to the monitoring point i, represents the characteristic value of the seismic wave at monitoring point i, represents the difference between the geological density of monitoring point i and the density of the epicenter, Represents the distance between mobile device j and monitoring point i.

2. The earthquake early warning and false alarm prevention method according to claim 1, characterized in that: The expression of the eigenvalue is: ； In the formula, represents the characteristic value of the seismic wave at monitoring point i, represents the propagation acceleration of seismic waves in the geological environment corresponding to the monitoring point i, represents the time required for the seismic wave to reach monitoring point i, Indicates the distance from the epicenter.

3. The earthquake early warning and false alarm prevention method according to claim 1, characterized in that: The expression of the eigenvalue is: ； In the formula, represents the characteristic value of the seismic wave at monitoring point i, represents the propagation acceleration of seismic waves in the geological environment corresponding to the monitoring point i, represents the time required for the seismic wave to reach monitoring point i, represents the epicenter distance, and exp represents the exponential function with e as the base.

4. The earthquake early warning and false alarm prevention method according to claim 2 or 3, characterized in that: The method for correcting the state parameters is: Acquire a historical data set, the historical data set including characteristic values ​​of seismic waves in historical earthquakes; Calculate the loss function of the generator and discriminator in the GAN algorithm, and use the GAN algorithm to adjust the state parameters to obtain the optimal state parameters; ； In the formula, represents the loss function of the generator, represents the loss function of the discriminator, represents the device state parameter of mobile device j corresponding to monitoring point i, represents the characteristic value of the lth seismic wave in the historical earthquake at the monitoring point i, represents the expected value of sampling in the historical real data distribution, represents the expected value of generating data sampled from the prior distribution.

5. The earthquake early warning and false alarm prevention method according to claim 2 or 3, characterized in that: The expression of propagation acceleration is: ； In the formula, represents the propagation acceleration of seismic waves in the geological environment corresponding to the monitoring point i, represents the component of acceleration on the X-axis of the spatial coordinate system, Represents acceleration in the space coordinate system The weight on the axis, Represents the component of acceleration on the z-axis of the spatial coordinate system.

6. The earthquake early warning and false alarm prevention method according to claim 1, characterized in that: The method for predicting the level of an earthquake based on the optimal state parameters is: setting multiple state parameter intervals, each state parameter corresponds to an earthquake level, and obtaining the earthquake level based on the state parameter interval into which the optimal state parameter falls.

7. The earthquake early warning and false alarm prevention method according to claim 1, characterized in that: Seismic waves include longitudinal waves and transverse waves.

8. An earthquake early warning and anti-false alarm system, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, an earthquake early warning and false alarm prevention method according to any one of claims 1-7 is implemented.

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