Geological disaster early warning method based on deformation monitoring, medium and device

Abstract

The present application relates to the technical field of geological disaster prediction, in particular to a geological disaster early warning method based on deformation monitoring, medium and equipment. The early warning method comprises: setting N*N evenly distributed sensing points in the monitoring area; calculating the first early warning probability of each sensing point, and defining the sensing point with the first early warning probability greater than the set hidden danger threshold as a hidden danger point; calculating the mean value of the first early warning probability of all sensing points within the set error radius of each hidden danger point to obtain the second early warning probability; defining the monitoring area within the set influence radius centered on the hidden danger point as the influence area of the hidden danger point; merging the influence areas of the hidden danger points in the intersection area to obtain a plurality of hidden danger area domains; calculating the area S of each hidden danger area domain, if S is less than M, no early warning is needed, and if S is greater than or equal to M, early warning is needed. The present application performs early warning analysis on the area of the hidden danger area domain, accurately early warns the whole monitoring area, and is convenient for obtaining more accurate and intuitive early warning information of the monitoring area.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geological disaster prediction, and particularly relates to a geological disaster early warning method based on deformation monitoring, a medium and equipment. BACKGROUND

[0002] At present, in the process of geological disaster monitoring, the main methods are total station, GNSS receiver, and wire displacement meter; with the development of technology, ground-based synthetic aperture monitoring equipment and other means of monitoring in the form of surface area are also widely used in the process of geological disaster monitoring. In the existing early warning method, the monitoring points are too discrete, the monitoring data are not representative, the data are not comprehensive, and the entire monitoring surface area cannot be accurately and precisely warned. SUMMARY

[0003] The present application aims to provide a geological disaster early warning method based on deformation monitoring for accurately and precisely warning the entire monitoring surface area, and the specific technical solutions are as follows:

[0004] The present application provides a geological disaster early warning method based on deformation monitoring, comprising the following steps:

[0005] S1: uniformly distributing N*N sensing points in the monitoring area, and acquiring deformation monitoring data of each sensing point by using a monitoring device;

[0006] S2: calculating the first early warning probability of each sensing point based on the deformation monitoring data in S1, and defining the sensing point with a first early warning probability greater than a set hidden danger threshold as a hidden danger point;

[0007] S3: calculating the mean value of the first early warning probability of all sensing points within the set error radius of each hidden danger point to obtain the second early warning probability of each hidden danger point;

[0008] S4: determining a set influence radius according to the second early warning probability and the geological conditions of the monitoring area, and defining the monitoring area within the set influence radius and centered on the hidden danger point as the influence surface area of the hidden danger point;

[0009] S5: merging the influence surface areas of the hidden danger points with intersecting areas in the monitoring area to obtain a plurality of hidden danger surface areas;

[0010] S6: calculating the area S of each hidden danger surface area, and respectively judging: if S

[0011] Optionally, the deformation monitoring data of each sensing point comprises a deformation amount and a deformation rate;

[0012] The specific calculation formula of the first early warning probability is as follows:

[0013]

[0014] wherein: (n, m) is the coordinate of the hidden danger point corresponding to the sensing point, n and m are natural numbers from 1 to N respectively; p (n,m) is the first warning probability of the hidden danger point with coordinate (n, m); d (n,m) is the deformation of the hidden danger point with coordinate (n, m); v (n,m) is the deformation rate of the hidden danger point with coordinate (n, m); D and V are both set hidden danger thresholds, D is the set threshold of the cumulative deformation of the monitoring area; V is the set threshold of the cumulative deformation rate of the monitoring area.

[0015] Optionally, the specific calculation formula of the second warning probability is as follows:

[0016]

[0017] wherein: is the second warning probability of the hidden danger point with coordinate (n, m); l is the set error radius; p (i,j) is the first warning probability of the sensing point within the set error radius of the hidden danger point with coordinate (n, m), (i, j) is the coordinate of the sensing point within the set error radius of the hidden danger point with coordinate (n, m); k is the number of the sensing point within the set error radius of the hidden danger point with coordinate (n, m).

[0018] Optionally, in S4, when , the set influence radius L = A; when , the set influence radius wherein: A is a set value; a is a coefficient set according to the geological conditions of the monitoring area, when the monitoring area is not prone to geological disasters, a takes a value of 1, and when the monitoring area is prone to geological disasters, a takes a value of 1.5-3.0.

[0019] Optionally, the value range of the set warning threshold M is 25m 2 -100m 2 ; the value range of the set error radius l is 3m-5m; the value range of the set value A is 3m-5m.

[0020] Optionally, after S6, it further includes: respectively evaluating the risk levels of each hidden danger area according to the areas of the hidden danger areas, specifically:

[0021] When S < M, the risk level of each hidden danger area in the hidden danger area is green level, and no warning is needed;

[0022] When 1.5M ≥ S ≥ M, the risk level of each hidden danger area in the hidden danger area is blue level, and warning is needed;

[0023] When 2M≥S≥1.5M, the risk level of each hidden danger area in the hidden danger zone is yellow level, and early warning is performed;

[0024] When 3M≥S≥2M, the risk level of each hidden danger area in the hidden danger zone is orange level, and early warning is performed;

[0025] When S≥3M, the risk level of each hidden danger area in the hidden danger zone is red level, and early warning is performed;

[0026] Wherein, the geological disaster risk increases in the order of green level, blue level, yellow level, orange level and red level.

[0027] The application further provides a readable storage medium, which has computer program instructions stored thereon, and the geological disaster early warning method based on deformation monitoring is realized when the computer program instructions are executed by a processor.

[0028] The application further provides an electronic device, which is characterized by comprising at least one processor, at least one memory and computer program instructions stored in the memory, and the geological disaster early warning method based on deformation monitoring is realized when the computer program instructions are executed by the processor.

[0029] According to the technical scheme of the application, the hidden danger points in the monitoring area are calculated according to the deformation monitoring data, the influence face domains of the hidden danger points are determined, the multiple hidden danger face domains in the monitoring area are obtained by merging the influence face domains in the intersection area, the early warning analysis is performed through the area of the hidden danger face domain, the entire monitoring face domain is accurately early warned, and the more accurate and intuitive early warning information of the monitoring area is obtained.

[0030] In addition to the purposes, features and advantages described above, the application has other purposes, features and advantages. The application will be further described below with reference to the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0031] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application, and are incorporated in and constitute a part of this application. The embodiments of the application illustrated in the drawings, and their description thereto, are presented to provide the applicant's best contemplation of the application, and are not intended to be an improper limitation of the application. In the drawings:

[0032] Figure 1 is a flowchart of the geological disaster early warning method based on deformation monitoring in the embodiments of the application. DETAILED DESCRIPTION

[0033] The embodiments of the application will be described in detail below with reference to the drawings, but the application can be implemented in various different ways limited and covered by the claims.

[0034] The geological disaster landslide is a surface area topographic deformation process. In the formation process of the landslide, three stages of an initial stage, a development stage and an emergency stage are experienced.

[0035] The initial stage: a deformation amount of a point or a small surface area exceeds a threshold value, and a geological disaster hidden point is formed.

[0036] The development stage: a hidden surface area continuously expands and develops, and a hidden surface area range continuously expands.

[0037] The emergency stage: a hidden surface area reaches a certain value, is close to an unstable state, a deformation rate is obviously accelerated, and until an unstable state occurs, a substantial landslide geological disaster occurs.

[0038] As described above, the main variables for observing the hidden surface area are displacement and displacement speed. In the initial process, a deformation area becomes large, when the deformation area reaches a certain region, the region loses stability, and the deformation speed is accelerated. Finally, a substantial disaster is caused.

[0039] In an embodiment, a geological disaster warning method based on deformation monitoring for accurately warning the entire monitoring surface area is provided, and includes the following steps:

[0040] S1: N*N sensing points are uniformly distributed in a monitoring area, and deformation monitoring data of each sensing point is obtained by using a monitoring device.

[0041] The deformation monitoring data of each sensing point includes a deformation amount and a deformation rate, and the size of the sensing point is set according to the measurement resolution of the monitoring device. In this embodiment, the monitoring device is a radar.

[0042] S2: The first warning probability of each sensing point is calculated based on the deformation monitoring data in S1, and the sensing point with a first warning probability greater than a set hidden danger threshold value is defined as a hidden point.

[0043] The specific calculation formula of the first warning probability is as follows:

[0044]

[0045] Wherein: (n, m) is the coordinate of the hidden point corresponding to the sensing point, n and m are natural numbers from 1 to N; p (n,m) is the first warning probability of the hidden point with the coordinate (n, m); d (n,m) is the deformation amount of the hidden point with the coordinate (n, m); v (n,m)is the deformation rate of the potential hazard point at coordinates (n, m); D and V are both thresholds for potential hazards: D is the threshold for the cumulative deformation of the monitored area, and V is the threshold for the cumulative deformation rate of the monitored area. This formula assigns weights based on the deformation and deformation rate. The faster the deformation or deformation rate, the greater the weight, which is more realistic.

[0046] S3: Calculate the average of the first warning probabilities of all sensor points within the set error radius of each hidden danger point to obtain the second warning probability of each hidden danger point; generally, the information of a single point is limited and cannot truly reflect the actual disaster situation. Generally, the occurrence of disasters is area-based. Calculating the second warning probability is conducive to truly reflecting the actual disaster situation.

[0047] The specific calculation formula of the second warning probability is as follows:

[0048]

[0049] in: is the second warning probability of the potential danger point with coordinates (n, m); l is the set error radius; p (i,j) The first warning probability of the sensor point within the error radius of the potential danger point with coordinates (n, m) is set. (i, j) is the coordinate of the sensor point within the error radius of the potential danger point with coordinates (n, m); k is the number of the sensor point within the error radius of the potential danger point with coordinates (n, m).

[0050] S4: Determine the set influence radius based on the second warning probability and the geological conditions of the monitoring area, and define the monitoring area within the set influence radius with the hidden danger point as the center as the influence area of ​​the hidden danger point;

[0051] In S4, when When the influence radius L is set to A; when When setting the influence radius Wherein: A is the set value; α is a coefficient set according to the geological conditions of the monitoring area. When the monitoring area is an area not prone to geological disasters, α is 1; when the monitoring area is an area prone to geological disasters, α is 1.5-3.0. Areas prone to geological disasters are areas with sparse geological structures, high slopes and high water content.

[0052] S5: Merge the impact areas of the hidden danger points that intersect in the monitoring area to obtain multiple hidden danger areas;

[0053] The manner of judging the intersection region is that when the influence area of one hidden point contains another hidden point, the influence areas of the two hidden points are considered to have an intersection region, and are merged to obtain a hidden surface area. All hidden points in the monitoring area are sequentially judged to obtain a plurality of hidden surface areas in the monitoring area.

[0054] S6: Calculate the area S of each hidden surface area, and respectively judge whether S≤M or S>M, wherein M is a set warning threshold.

[0055] The S6 further includes: respectively evaluating the risk level of each hidden area according to the area of each hidden area, specifically:

[0056] When S

[0057] When 1.5M≥S≥M, the risk level of each hidden area in the hidden area is blue, and a warning is performed.

[0058] When 2M≥S≥1.5M, the risk level of each hidden area in the hidden area is yellow, and a warning is performed.

[0059] When 3M≥S≥2M, the risk level of each hidden area in the hidden area is orange, and a warning is performed.

[0060] When S≥3M, the risk level of each hidden area in the hidden area is red, and a warning is performed.

[0061] The geological disaster risk increases in the order of green, blue, yellow, orange, and red.

[0062] In the embodiment, the value range of the set warning threshold M is 25m 2 ~100m 2 , the value range of the set error radius l is 3m~5m, and the value range of the set value A is 3m~5m. D and V are set according to the actual situation by the design or survey unit.

[0063] The embodiment also provides a readable storage medium having computer program instructions stored thereon, and the computer program instructions are executed by a processor to implement the geological disaster warning method based on deformation monitoring.

[0064] It should be noted that the apparatus embodiments described above are merely illustrative, and the units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs. In addition, the connection relationship between the modules in the apparatus embodiments provided by the present application indicates that there is a communication connection between them, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0065] The embodiment also includes an electronic device, comprising at least one processor, at least one memory, and computer program instructions stored in the memory, when the computer program instructions are executed by the processor, the deformation monitoring based geological disaster early warning method as described above.

[0066] For example, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the electronic device.

[0067] The electronic device can be a mobile phone, a desktop computer, a notebook computer, a palm computer, a cloud server, and other computing devices. The electronic device can include, but is not limited to, a processor, a memory. For example, the electronic device can also include an input / output device, a network access device, a bus, etc.

[0068] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and connects all parts of the electronic device through various interfaces and lines.

[0069] The memory can be used to store the computer program and / or modules, and the processor realizes the computer program by running or executing the computer program and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required by a function (such as a sound playing function, an image playing function, etc.), etc.; and the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0070] The modules / units integrated in the electronic device can be stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a readable storage medium. When the processor executes the computer program, the steps of the above-mentioned various method embodiments can be realized. The computer program includes computer program code, which can be in the form of source code, object code, an executable file, or some intermediate form, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the contents included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0071] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A geological disaster early warning method based on deformation monitoring, characterized in that: It includes the following steps: S1: Set N*N sensing points evenly distributed in the monitoring area, and use monitoring equipment to obtain the deformation monitoring data at each sensing point; S2: Based on the deformation monitoring data in S1, calculate the first warning probability of each sensing point respectively, and define the sensing points with the first warning probability greater than the set hidden danger threshold as hidden danger points; S3: Calculate the mean value of the first warning probabilities of all sensing points within the set error radius of each hidden danger point to obtain the second warning probability of each hidden danger point; S4: Determine the set influence radius according to the second warning probability and the geological conditions of the monitoring area, and define the monitoring area within the set influence radius centered on the hidden danger point as the influence area domain of the hidden danger point; S5: Combine the influence area domains of the hidden danger points with intersecting areas in the monitoring area to obtain multiple hidden danger area domains; S6: Calculate the area S of each hidden danger area domain, and judge respectively: if S < M, no warning is required; if S ≥ M, it is considered that there is a geological disaster risk and a warning is issued, where: M is the set warning threshold.

2. The geological disaster early warning method based on deformation monitoring according to claim 1 is characterized in that: The deformation monitoring data of each sensing point respectively includes the amount of deformation and the deformation rate; The specific calculation formula of the first warning probability is as follows: Where: (n,m) is the coordinate of the sensor point corresponding to the hidden danger point, n and m are natural numbers from 1 to N respectively; p (n,m) is the first warning probability of the potential danger point with coordinates (n, m); d (n,m) v is the deformation variable of the potential hazard point with coordinates (n, m); (n,m) is the deformation rate of the potential danger point with coordinates (n, m); D and V are both thresholds for setting potential dangers, D is the threshold for setting the cumulative deformation of the monitoring area; V is the threshold for setting the cumulative deformation rate of the monitoring area.

3. The geological disaster early warning method based on deformation monitoring according to claim 2 is characterized in that: The specific calculation formula of the second warning probability is as follows: in: is the second warning probability of the potential danger point with coordinates (n, m); l is the set error radius; p (i,j) The first warning probability of the sensor point within the error radius of the potential danger point with coordinates (n, m) is set. (i, j) is the coordinate of the sensor point within the error radius of the potential danger point with coordinates (n, m); k is the number of the sensor point within the error radius of the potential danger point with coordinates (n, m).

4. The geological disaster early warning method based on deformation monitoring according to claim 3 is characterized in that: In S4, when When the influence radius L is set to A; when When setting the influence radius Where: A is the set value; α is a coefficient set according to the geological conditions of the monitoring area. When the monitoring area is an area not prone to geological disasters, α is 1; when the monitoring area is an area prone to geological disasters, α is 1.5-3.

0.

5. The geological disaster early warning method based on deformation monitoring according to claim 4 is characterized in that: Set the warning threshold M to a value range of 25m 2 ~100m 2 ; Set the error radius l to a range of 3m to 5m; Set the value A to a range of 3m to 5m.

6. The geological disaster early warning method based on deformation monitoring according to any one of claims 1 to 5, characterized in that: After S6, it further includes: performing risk level evaluation according to the areas of each hidden danger area, specifically: When S < M, the risk level of each hidden danger area in this hidden danger area is the green level, and no warning is required; When 1.5M ≥ S ≥ M, the risk level of each hidden danger area in this hidden danger area is the blue level, and a warning is issued; When 2M ≥ S ≥ 1.5M, the risk level of each hidden danger area in this hidden danger area is the yellow level, and a warning is issued; When 3M ≥ S ≥ 2M, the risk level of each hidden danger area in this hidden danger area is the orange level, and a warning is issued; When S ≥ 3M, the risk level of each hidden danger area in this hidden danger area is the red level, and a warning is issued; Among them: The geological disaster risk increases in sequence according to the green level, blue level, yellow level, orange level, and red level.

7. A readable storage medium, characterized in that: It stores computer program instructions, and when the computer program instructions are executed by a processor, it implements the geological disaster warning method based on deformation monitoring as described in any one of claims 1 to 6.

8. An electronic device, characterized in that: It includes: At least one processor, at least one memory, and computer program instructions stored in the memory. When the computer program instructions are executed by the processor, it implements the geological disaster warning method based on deformation monitoring as described in any one of claims 1 to 6.

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