An earthquake single-station positioning correction method, system, storage medium and terminal

Abstract

The present invention discloses a method, a system, a storage medium and a terminal for correcting single-station earthquake positioning, including: collecting the latitudes and longitudes of each station, dividing each station by the Voronoi diagram method to obtain the V-diagram area of each station; clustering according to historical earthquake records to obtain the clustering area of the epicenter; calculating the corresponding epicentral distance and azimuth of the first station by single-station calculation to obtain the initial epicenter; judging whether the initial epicenter is within the V-diagram area monitored by the first station by the Voronoi diagram method, correcting the initial epicenter into the V-diagram area of the first station, and outputting the positioning result. The present invention corrects the single-station positioning result based on the clustering and Voronoi diagram algorithms and according to the existing station layout and historical earthquake distribution, so as to improve the positioning accuracy of the first station.

Description

Technical Field

[0001] The present invention relates to the technical field of earthquake early warning, and particularly to an earthquake single-station positioning correction method, system, storage medium and terminal. Background Art

[0002] Earthquake early warning refers to, after an earthquake occurs, using the initial information of seismic waves observed by seismic stations near the earthquake source to quickly estimate earthquake parameters and predict the impact of the earthquake on surrounding areas, and releasing early warning information on the ground motion intensity and arrival time of each location before the destructive seismic waves reach the surrounding areas of the epicenter, providing an early warning time of several seconds to dozens of seconds to the target area, enabling enterprises and the public to take earthquake emergency response measures in advance, and thus reducing earthquake casualties and property losses. It is one of the effective means of reducing earthquake disasters developed in recent years. In addition to providing early warning services for the public, the earthquake early warning system can also provide safety guarantee services for major projects. By receiving the alarm information issued by the earthquake early warning system, major projects such as high-speed railways can automatically activate corresponding emergency disposal systems such as braking and shutdown according to the plan, reducing direct earthquake disasters and secondary disasters.

[0003] When an earthquake occurs, wave field separation will occur when seismic waves propagate in the medium, generating P waves, S waves, surface waves, etc. P waves have small damage and fast speed, while S waves have large damage and slow speed. P waves are one of the two body waves (the name of body waves is because this wave penetrates the interior of the earth, and the opposite of body waves is surface waves), and the other body wave is S waves. P waves mean primary waves (primary wave) or pressure waves (pressure wave). Among all seismic waves, P waves have the fastest propagation speed. Therefore, when an earthquake occurs, P waves are the first to reach the measuring station and are recorded by the seismograph, which is also the origin of the name of P waves. The P in P waves can also represent pressure, coming from the fact that its vibration transmission is similar to sound waves, belonging to a type of longitudinal wave (or compression wave). When transmitting, the vibration direction of the medium is parallel to the propagation direction of the seismic wave energy. Due to the characteristics of P waves, they are often used for single-station positioning detection of earthquake early warning. The early warning process includes seismic phase identification, P wave picking, magnitude estimation, epicenter positioning, intensity estimation of the target area, and early warning information release, etc.

[0004] When a train is running at high speed, an earthquake of a relatively small magnitude can cause major accidents endangering the lives of passengers due to the impact on the subgrade, track, bridge, etc. Under such circumstances, for high-speed railways, if earthquake alarms and emergency responses can be implemented even just dozens of seconds or even seconds in advance before the arrival of destructive ground motions, the probability of occurrence of losses of passengers' lives and property will be greatly reduced. Therefore, in order to minimize the earthquake disasters of high-speed railways, in addition to providing high-level earthquake fortification for railway structures and taking derailment protection measures for operating trains, building a high-speed railway earthquake monitoring and early warning system is also a very effective means. The existing single-station positioning algorithms for earthquake early warning based on P waves mainly consist of two parts: 1. The B-delta method for epicentral distance prediction; 2. The PCA method for azimuth calculation. These two methods mainly rely on waveform information to calculate the epicentral distance and azimuth. Although the accuracy of early warning is improved to a certain extent, the situation where P waves are interfered is not considered. Since the earthquake waveform is easily affected by noise or Pn waves (longitudinal waves emitted from the earthquake source, traveling along the Mohorovicic discontinuity for a certain distance and then propagating to the surface) during the propagation process, large deviations occur in the calculation of the azimuth and epicentral distance, and the positioning accuracy of the first station is relatively low, making it impossible to avoid false alarms, which has a potential impact on the life and property safety in high-speed railways. Summary of the Invention

[0005] The object of the present invention is to overcome the problem of insufficient single-station positioning accuracy in the prior art, and provide an earthquake single-station positioning correction method, system, storage medium and terminal.

[0006] The object of the present invention is achieved by the following technical solutions:

[0007] In the first solution, an earthquake single-station positioning correction method is provided, and the method includes the following steps:

[0008] S1. Collect the longitude and latitude of each station, divide each station using the Voronoi diagram method to obtain the V diagram area of each station; and cluster according to historical earthquake records to obtain the clustering area of the epicenter;

[0009] S2. Calculate the corresponding epicentral distance and azimuth through the first station to obtain the initial epicenter;

[0010] S3. Judge whether the initial epicenter is within the V diagram area monitored by the first station through the Voronoi diagram method. If the initial epicenter is within the V diagram area monitored by the first station, go to step S4; otherwise, go to step S5;

[0011] S4. Judge whether the initial epicenter is within the clustering area. If the initial epicenter is within the clustering area, directly output the positioning result; otherwise, correct the initial epicenter to the clustering point in the nearest clustering area;

[0012] S5. Determine the distance to the initial epicenter and correct the initial epicenter into the V - diagram area of the first station, and output the positioning result.

[0013] As a preferred option, a method for correcting single - station earthquake positioning, the step S5 includes:

[0014] S51. Preset a distance threshold, and determine whether the distance to the initial epicenter is greater than the distance threshold;

[0015] S52. Reduce the distance to the initial epicenter to the distance threshold and then perform angle correction;

[0016] S53. Correct the distance to the initial epicenter to the clustering point in the clustering area to obtain a positioning point;

[0017] S54. Determine whether the positioning point is within the V - diagram area of the first station.

[0018] As a preferred option, a method for correcting single - station earthquake positioning, the distance threshold in step S51 is 300 km.

[0019] As a preferred option, a method for correcting single - station earthquake positioning, if the positioning point is within the V - diagram area of the first station in step S54, then output the positioning result; otherwise, randomly position within the V - diagram area.

[0020] As a preferred option, a method for correcting single - station earthquake positioning, the historical earthquake records include earthquake event clusters within 200 km of the warning point in the past 10 years.

[0021] As a preferred option, a method for correcting single - station earthquake positioning, the epicentral distance of the first single - station is calculated by the B - delta method.

[0022] As a preferred option, a method for correcting single - station earthquake positioning, the clustering is the K - means clustering method.

[0023] In the second solution, a system for correcting single - station earthquake positioning is provided, and the system includes:

[0024] A station data processing module, which is used to collect the longitude and latitude of each station, divide each station using the Voronoi diagram method to obtain the V - diagram area of each station; and cluster according to historical earthquake records to obtain the clustering area of the epicenter;

[0025] A first - station epicenter calculation module, which calculates the corresponding epicentral distance and azimuth of the first station to obtain the initial epicenter;

[0026] An initial epicenter judgment module, which judges whether the initial epicenter is within the V - diagram area monitored by the first station through the Voronoi diagram method;

[0027] An initial epicenter correction module that corrects the initial epicenter to a clustering point in the nearest clustering area;

[0028] A positioning output module that outputs the corrected positioning result.

[0029] In the third solution, a storage medium is provided, on which computer instructions are stored, and when the computer instructions run, the steps of any one of the earthquake single-station positioning correction methods are executed.

[0030] In the fourth solution, a terminal is provided, including a memory and a processor. Computer instructions that can run on the processor are stored on the memory, and when the processor runs the computer instructions, the steps of any one of the earthquake single-station positioning correction methods are executed.

[0031] It should be further noted that the technical features corresponding to the above options can be combined or replaced with each other without conflict to form a new technical solution.

[0032] Compared with the prior art, the beneficial effects of the present invention are:

[0033] According to the characteristics of linear and relatively small density of station layout, the present invention constrains the epicenter positioning point based on clustering, Voronoi diagram algorithm and distance classification, and corrects the single-station positioning result according to the existing station layout and historical earthquake occurrence distribution. It can lock the single-station positioning result within the area where historical earthquakes occurred, achieve the purpose of correcting the first-station positioning result, improve the accuracy of the first-station positioning result of earthquake early warning, enable the emergency disposal server to more accurately divide the disposal scope of the line, and avoid false alarm situations. Description of the Drawings

[0034] Figure 1 It is a flowchart of an earthquake single-station positioning correction method shown in an embodiment of the present invention;

[0035] Figure 2 It is a schematic diagram of the Voronoi diagram method shown in an embodiment of the present invention;

[0036] Figure 3 It is a schematic diagram of the Voronoi diagram area division of each station on the Chengdu-Chongqing line shown in an embodiment of the present invention;

[0037] Figure 4 It is a specific schematic diagram of single-station positioning correction shown in an embodiment of the present invention. Detailed Embodiments

[0038] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work belong to the scope of protection of the present invention.

[0039] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0040] In an exemplary embodiment, a method for correcting the single-station positioning of earthquakes is provided. Referring to Figure 1 , the method includes the following steps:

[0041] S1. Collect the longitude and latitude of each station, divide each station using the Voronoi diagram method to obtain the V-diagram area of each station; and cluster according to historical earthquake records to obtain the clustering area of the epicenter. The division of the V-diagram area and the clustering have sequential steps. This is because the clustering range is divided according to the station duty area divided by the V-diagram. Performing the division of the V-diagram area first can further limit the clustering range, which is equivalent to adding boundary conditions. On the premise of determining the duty V-diagram area of each station, then perform the division of the clustering area, reduce the calculation amount, make the clustering faster, and at the same time make the division of the clustering area more accurate, improving the accuracy of subsequent station positioning;

[0042] S2. Calculate the corresponding epicentral distance and azimuth of the first station through single-station calculation to obtain the initial epicenter; among them, single-station positioning mainly uses the 2-3 second P-wave signal to calculate the azimuth and epicentral distance, and inversely calculate the earthquake longitude and latitude;

[0043] S3. Judge whether the initial epicenter is within the V-diagram area where the first station is on duty through the Voronoi diagram method. If the initial epicenter is within the V-diagram area where the first station is on duty, go to step S4; otherwise, go to step S5;

[0044] S4. Judge whether the initial epicenter is within the clustering area. If the initial epicenter is within the clustering area, directly output the positioning result; otherwise, correct the initial epicenter to the clustering point in the nearest clustering area;

[0045] S5. Judge the distance of the initial epicenter and correct the initial epicenter into the V-diagram area of the first station, and output the positioning result.

[0046] Specifically, according to the characteristics of linear and relatively low-density station layout, the epicenter location points are constrained based on clustering, Voronoi diagram algorithm, and distance classification. The single-station location results are corrected according to the existing station layout and historical earthquake occurrence distribution. The V diagram's limited range mainly divides the station duty range for each station. If a certain station is the first to be triggered, then the earthquake must occur within the V diagram range it is responsible for, which can lock the single-station location result within the area where historical earthquakes occurred, achieving the purpose of correcting the first-station location result and improving the accuracy of the first-station location result for earthquake early warning.

[0047] In one example, the azimuth calculation idea is to use the polarization information of the P band to determine the azimuth, mainly relying on the covariance matrix M of the three-direction signals as follows:

[0048]

[0049] Among them, the variance of the three-component records of the original acceleration is represented by Var, and Cov represents the covariance between channels. Var(NS) = Cov(NS, NS).

[0050] Where u ns is the mean value of the original record in the NS direction, and u ew is the mean value of the original record in the EW direction. When the matrix variance satisfies M * X = λ * X, the three-dimensional (non-zero) vector represents the three main axis directions of the ellipsoid, and these three-dimensional vectors are the eigenvectors of the matrix M.

[0051] Let the eigenvalues of the M matrix be λ1, λ2, and λ3 respectively, and the corresponding eigenvectors be ξ1, ξ2, and ξ3 respectively, and each eigenvector is mutually orthogonal. The square matrix composed of the three eigenvectors is X. According to the projection of the eigenvector corresponding to the largest eigenvalue on the horizontal plane, the azimuth of the earthquake can be determined. Let the eigenvector ξ1 corresponding to the largest eigenvalue = (mn, me, mz). The actual azimuth of the earthquake relative to the station can be determined according to the magnitudes and signs of me and mn. The determination method is shown in the following table (α is the azimuth):

[0052] Table 1. Actual azimuth of the earthquake relative to the station

[0053] When mz < 0, mn > 0 and me > 0 <![CDATA[α = tan -1 (|me| / |mn|)]]> When mz < 0, mn < 0 and me > 0 <![CDATA[α = π - tan -1 (|me| / |mn|)]]> When mz < 0, mn < 0 and me < 0 <![CDATA[α = π + tan -1 (|me| / |mn|)]]> When mz < 0, mn > 0 and me < 0 <![CDATA[α = 2π - tan -1 (|me| / |mn|)]]> When mz > 0, mn > 0 and me > 0 <![CDATA[α = π + tan -1 (|me| / |mn|)]]> When mz > 0, mn < 0 and me > 0 <![CDATA[α = 2π - tan -1 (|me| / |mn|)]]> When mz > 0, mn < 0 and me < 0 <![CDATA[α = tan -1 (|me| / |mn|)]]> When mz > 0, mn > 0 and me < 0 <![CDATA[α = π - tan -1 (|me| / |mn|)]]>

[0054] In one example, the epicentral distance of the first single station is calculated by the B-delta method. Specifically, the seismic wave signal has the characteristic of increasing from zero to a certain maximum value and then gradually decaying. The P-band seismic signal is quantitatively described by the gradual change signal model:

[0055] S(t) = B * t * exp(-A * t + i * w * t) * u(t)

[0056] Where w is the main frequency of the P-band signal, B is the slope factor, A is the amplitude change factor related to the signal gradual change process, and u(t) is the step signal. The changes in the B and A parameters directly affect the morphological differences of the P-wave envelope. The envelope information of the P-band seismic signal waveform is obtained according to the Hilbert transform, that is:

[0057] S(t) = B * t * exp(-A * t) * u(t)

[0058] According to the research of Japanese researchers Odaka et al. on the acceleration records of earthquakes, log(B) is inversely proportional to log(Δ). Therefore, the value of B can be inversely calculated from a part of the data at the front end of the P-band, and then the epicentral distance can be obtained through the formula Distance = M * log(B) + C, where M and C are fitting coefficients.

[0059] In an example, the Voronoi diagram method is used to divide each station. Specifically, the Voronoi diagram method, also known as the Thiessen polygon or Dirichlet diagram, is composed of a set of continuous polygons formed by the perpendicular bisectors of the lines connecting two adjacent points. N distinct points on the plane are divided according to the nearest neighbor principle; each point is associated with its nearest neighbor region. The Delaunay triangle is formed by connecting the relevant points that share a side with the adjacent Voronoi polygons. The circumcenter of the Delaunay triangle is a vertex of the Voronoi polygon related to the triangle. Refer to Figure 2 , and the specific steps are as follows:

[0060] 1. Automatically construct a triangular network for discrete points, that is, construct a Delaunay triangular network. Number the discrete points and the formed triangles, and record which three discrete points each triangle is composed of.

[0061] 2. Calculate the circumcenter of each triangle and record it.

[0062] 3. Traverse the triangle linked list to find the adjacent triangles TriA, TriB, and TriC that share a side with the three sides of the current triangle pTri.

[0063] 4. If found, connect the circumcenter of the found triangle with the circumcenter of pTri and store it in the Voronoi edge linked list. If not found, find the outermost perpendicular bisector ray and store it in the Voronoi edge linked list.

[0064] 5. After the traversal is completed, all Voronoi edges are found, and the Voronoi diagram is drawn according to the edges.

[0065] The Voronoi diagram method is a relatively common method in earthquake duty areas. The V diagram method can lock the single-station positioning within a certain area, but it cannot converge on its positioning. Figure 3 It is the Voronoi diagram area division for each station on the Chengyu Line.

[0066] In one example, a method for correcting single-station earthquake positioning, where the clustering is the K-means clustering method. Specifically, the k-means clustering algorithm is an iterative clustering analysis algorithm. Its steps are as follows: First, divide the data into K groups in advance, then randomly select K objects as the initial clustering centers, and then calculate the distance between each object and each seed clustering center, and assign each object to the clustering center closest to it. The clustering centers and the objects assigned to them represent a cluster. Each time a sample is assigned, the clustering center of the cluster will be recalculated based on the existing objects in the cluster. This process will be repeated continuously until a certain termination condition is met. The termination condition can be that no (or the minimum number of) objects are reassigned to different clusters, no (or the minimum number of) clustering centers change anymore, or the sum of squared errors is locally minimized.

[0067] The K-means algorithm itself is actually a process of normal distribution test during the clustering process, and a normal distribution is established according to the clustering trend of the existing data.

[0068] Furthermore, the steps of the K-means algorithm in earthquake early warning are as follows:

[0069] 1. Collect earthquake event clusters within 200 km of the warning points in the past 10 years as the original data.

[0070] 2. Randomly select k points as the initial clustering centers according to the data distribution.

[0071] 3. Calculate the Euclidean distance from each data point to each clustering center and assign it to the cluster where the nearest clustering center is located.

[0072] 4. Calculate the new center of each cluster, that is, the average value of all data points within the cluster. If there are no data points in a cluster, its center remains unchanged.

[0073] 5. Repeat steps 3 and 4 until the clustering centers no longer change. Specifically, it can be judged whether convergence is achieved by comparing whether the positions of the clustering centers in the previous and subsequent iterations are the same, or whether the error is less than a predetermined threshold (10).

[0074] 6. After the algorithm converges, K mass points and their corresponding clusters R will be obtained.

[0075] 7. Determine whether the distribution of the mass points is too close (<30 km), and delete the clustering points with too close distances and their clustering distances.

[0076] 8. Return the final clustering result, and thus obtain a clustering model based on the historical earthquake distribution.

[0077] In one example, referring to Figure 4 , a method for correcting the single-station earthquake location, the step S5 includes:

[0078] S51. Preset a distance threshold, and determine whether the distance of the initial epicenter (i.e., the epicentral distance obtained by the single-station location of the first station) is greater than the distance threshold;

[0079] S52. After reducing the distance of the initial epicenter to the distance threshold, perform angle correction. The angle correction mainly limits the azimuth angles of each station within a certain range through the duty areas of each station, and corrects the azimuth angles exceeding this range to the boundaries of this azimuth angle range. Here, only the result of the first station is corrected.

[0080] S53. Correct the distance of the initial epicenter to the clustering points in the clustering area to obtain a location point;

[0081] S54. Determine whether the location point is within the V-diagram area of the first station.

[0082] In one example, for a method for correcting the single-station earthquake location, the distance threshold in step S51 is 300 km. The distance threshold can be selected according to the actual situation, and this is not construed as a limitation of this application here.

[0083] In one example, for a method for correcting the single-station earthquake location, in step S54, if the location point is within the V-diagram area of the first station, the location result is output; otherwise, random location is performed within the V-diagram area. The random location method is to randomly select the longitude and latitude within the V-diagram range.

[0084] In the second solution, a system for correcting the single-station earthquake location is provided. The system includes:

[0085] A station data processing module, which is used to collect the longitude and latitude of each station, divide each station using the Voronoi diagram method to obtain the V-diagram area of each station; and cluster according to the historical earthquake records to obtain the clustering area of the epicenter;

[0086] A first-station epicenter calculation module, which calculates the corresponding epicentral distance and azimuth angle of the first station through single-station calculation to obtain the initial epicenter;

[0087] An initial epicenter judgment module, which judges whether the initial epicenter is within the V-diagram area of the first station through the Voronoi diagram method;

[0088] An initial epicenter correction module that corrects the initial epicenter to the clustering point in the nearest clustering region;

[0089] A positioning output module that outputs the corrected positioning result.

[0090] In the third solution, a storage medium is provided, on which computer instructions are stored, and when the computer instructions run, they execute the steps of any one of the earthquake single-station positioning correction methods.

[0091] Based on such an understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present invention. And the aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs and other various media that can store program codes.

[0092] In the fourth solution, a terminal is provided, including a memory and a processor. Computer instructions that can run on the processor are stored on the memory, and when the processor runs the computer instructions, it executes the steps of any one of the earthquake single-station positioning correction methods.

[0093] The processor can be a single-core or multi-core central processing unit or a specific integrated circuit, or one or more integrated circuits configured to implement the present invention.

[0094] The embodiments of the subject matter and functional operations described in this specification can be implemented in the following: tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. The embodiments of the subject matter described in this specification can be implemented as one or more computer programs, that is, one or more modules in computer program instructions encoded on a tangible non-transitory program carrier to be executed by a data processing device or to control the operation of a data processing device. Alternatively or additionally, the program instructions can be encoded on an artificially generated propagated signal, such as a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode and transmit information to a suitable receiver device for execution by a data processing device.

[0095] The processes and logical flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform the corresponding functions by operating on input data and generating output. The processes and logical flows can also be performed by, for example, special logic circuitry such as an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit), and the apparatus can also be implemented as special logic circuitry.

[0096] Processors suitable for executing computer programs include, by way of example, general and / or special purpose microprocessors, or any other type of central processing unit. In general, a central processing unit will receive instructions and data from a read-only memory and / or a random access memory. Basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. In general, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, etc., or the computer will be operatively coupled to such mass storage devices to receive data therefrom or transfer data thereto, or both. However, a computer need not have such devices. In addition, a computer may be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name just a few.

[0097] Although this specification contains many specific implementation details, these should not be construed as limiting the scope of any invention or the scope of what is claimed, but rather as mainly describing the features of specific embodiments of a particular invention. Certain features that are described in this specification in the context of multiple embodiments can also be implemented in a single embodiment in combination. On the other hand, the various features described in a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub-combination. In addition, although features may operate in certain combinations as described above and even be claimed as such initially, one or more features from a claimed combination can in some cases be removed from the combination, and the claimed combination can be directed to a sub-combination or a variation of a sub-combination.

[0098] Similarly, although operations are depicted in the drawings in a particular order, this should not be understood as requiring that the operations be performed in the particular order shown or sequentially, or that all illustrated operations be performed, to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above embodiments should not be understood as required in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0099] The above specific embodiments are detailed descriptions of the present invention. It cannot be determined that the specific embodiments of the present invention are only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions and substitutions can be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for correcting single-station earthquake location, characterized in that The method includes the following steps: S1. Collect the longitude and latitude of each station, divide each station using the Voronoi diagram method to obtain the V - diagram area of each station; and cluster according to historical earthquake records to obtain the clustering area of the epicenter; S2. Calculate the corresponding epicentral distance and azimuth angle through the single - station of the first station to obtain the initial epicenter; S3. Judge whether the initial epicenter is within the V - diagram area monitored by the first station through the Voronoi diagram method. If the initial epicenter is within the V - diagram area monitored by the first station, go to step S4; otherwise, go to step S5; S4. Judge whether the initial epicenter is within the clustering area. If the initial epicenter is within the clustering area, directly output the positioning result; otherwise, correct the initial epicenter to the clustering point in the nearest clustering area; S5. Judge the distance of the initial epicenter and correct the initial epicenter into the V - diagram area of the first station, and output the positioning result.

2. The method for correcting single-station earthquake positioning according to claim 1, wherein The step S5 includes: S51. Preset a distance threshold, and judge whether the distance of the initial epicenter is greater than the distance threshold; S52. Reduce the distance of the initial epicenter to the distance threshold and then perform angle correction; S53. Correct the distance of the initial epicenter to the clustering point in the clustering area to obtain the positioning point; S54. Judge whether the positioning point is within the V - diagram area of the first station.

3. A method for correcting the single-station earthquake location according to claim 2, characterized in that, The distance threshold is 300 km.

4. A method for correcting single-station earthquake location according to claim 2, characterized in that, If the positioning point is within the V - diagram area of the first station, output the positioning result; otherwise, randomly position within the V - diagram area.

5. A method for correcting the single-station earthquake location according to claim 1, characterized in that, The historical earthquake records include earthquake event clusters within 200 km of the warning points in the past 10 years.

6. A method for correcting single-station earthquake location according to claim 1, characterized in that, The epicentral distance of the single - station of the first station is calculated by the B - delta method.

7. A method for correcting the single-station earthquake location according to claim 1, characterized in that, The clustering is the K - means clustering method.

8. An earthquake single-station positioning correction system, characterized in that, The system includes: A station data processing module, which is used to collect the longitude and latitude of each station, divide each station using the Voronoi diagram method to obtain the V - diagram area of each station; and cluster according to historical earthquake records to obtain the clustering area of the epicenter; A first - station epicenter calculation module, which calculates the corresponding epicentral distance and azimuth angle through the single - station of the first station to obtain the initial epicenter; An initial epicenter judgment module, which judges whether the initial epicenter is within the V - diagram area monitored by the first station through the Voronoi diagram method; An initial epicenter correction module, which corrects the initial epicenter to the clustering point in the nearest clustering area; A positioning output module, which outputs the corrected positioning result.

9. A storage medium, on which computer instructions are stored, characterized in that, When the computer instructions run, they execute the steps of the earthquake single - station positioning and correction method described in any one of claims 1 - 7.

10. A terminal, comprising a memory and a processor, wherein the memory stores computer instructions that can run on the processor, characterized in that, When the processor runs the computer instructions, it executes the steps of the earthquake single - station positioning and correction method described in any one of claims 1 - 7.

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