A method, device, system, and storage medium for locating microseismic sensors.

Abstract

This invention provides a microseismic sensor positioning method, device, system, and storage medium, relating to the field of rockburst equipment technology. The method includes: acquiring the source coordinates and waveform of a preset seismic source; constructing an objective function based on the source coordinates, waveform, and geological information of the monitoring area; optimizing the objective function to obtain the initial coordinates of the sensor; and obtaining the target coordinates of the sensor using a double-difference algorithm based on the source coordinates and initial coordinates. The beneficial effects of this invention are: by acquiring the source coordinates and waveform, and constructing an objective function using the geological information of the monitoring area, the initial coordinates of the sensor with low precision are quickly obtained. Then, the initial coordinates are further corrected using a double-difference algorithm, realizing intelligent positioning of the microseismic sensor. This effectively avoids the problems of inaccurate positioning and low positioning efficiency caused by manual measurement errors and non-standard sensor protection, increasing the positioning efficiency of the microseismic sensor, and thus effectively improving the accuracy and reliability of rockburst early warning.

Description

Technical Field

[0001] This invention relates to the field of rockburst equipment technology, and more specifically, to a micro-vibration sensor positioning method, device, system, and storage medium. Background Technology

[0002] Rockbursts are a common geological hazard that poses significant risks to mines, tunnels, hydropower projects, and other infrastructure. To prevent and mitigate rockburst accidents, microseismic monitoring and timely warning signals are essential. Therefore, the location of the microseismic sensors used for monitoring is crucial; even slight errors in the sensors can lead to mismonitoring of rockbursts.

[0003] Currently, high-precision measuring instruments such as total stations are typically used to obtain relatively accurate microseismic sensor coordinates. However, during underground construction, microseismic sensors may shift as construction progresses. After each construction phase, it is necessary to remeasure the microseismic sensors using high-precision measuring instruments such as total stations to accurately locate and warn of microseismic events. This process is time-consuming and labor-intensive, leading to increased monitoring costs. Summary of the Invention

[0004] The problem addressed by this invention is how to improve the positioning efficiency of microseismic sensors.

[0005] To address the aforementioned problems, this invention provides a microseismic sensor positioning method, apparatus, system, and storage medium.

[0006] In a first aspect, the present invention provides a method for locating a microseismic sensor, comprising:

[0007] Obtain the source coordinates and source waveform of the preset seismic source;

[0008] An objective function is constructed based on the source coordinates, the source waveform, and the geological information of the monitoring area. The initial coordinates of the sensor are obtained by solving the objective function.

[0009] The target coordinates of the sensor are obtained using the double-difference algorithm based on the source coordinates and the initial coordinates.

[0010] Optionally, the step of constructing the objective function based on the source coordinates, the source waveform, and the geological information of the monitoring area includes:

[0011] The wave velocity and attenuation coefficient of the source waveform are obtained based on the preset geological standards and the geological information of the monitoring area, and the frequency of the source waveform is obtained based on the source waveform.

[0012] The distance difference between the preset source and any two sensors is obtained based on the wave velocity, the attenuation coefficient, the frequency, and the source coordinates.

[0013] The objective function is constructed based on the distance difference and the wave propagation formula.

[0014] Optionally, obtaining the distance difference from the preset source to any two sensors based on the wave velocity, the attenuation coefficient, the frequency, and the source coordinates includes:

[0015] The signal attenuation degree of the sensor is obtained based on the wave velocity, the attenuation coefficient, and the frequency.

[0016] The first distance and the second distance are obtained by subtracting the earthquake source coordinates from the coordinates of any two of the sensors.

[0017] Based on the degree of signal attenuation, the difference between the first distance and the second distance is obtained.

[0018] Optionally, constructing the objective function based on the distance difference and the wave propagation formula includes:

[0019] The objective function is constructed using a first formula, which includes:

[0020] ,

[0021] Where Θ represents the objective function, n represents the number of preset seismic sources, and R i R represents the distance between sensor i and the preset vibration source. j This represents the distance between sensor j and the preset seismic source, where x0, y0, and z0 represent the coordinates of the seismic source. i y i z i Let x represent the initial coordinates of sensor i. j y j z j This represents the initial coordinates of sensor j.

[0022] Optionally, obtaining the target coordinates of the sensor using a double-difference algorithm based on the source coordinates and the initial coordinates includes:

[0023] Obtain the residuals of any two sensors, and subtract the residuals of the two sensors to obtain the double difference;

[0024] Perform a Taylor expansion on the double difference and construct a positioning matrix based on the double difference after the Taylor expansion;

[0025] The target coordinates of the sensor are obtained by solving the positioning matrix.

[0026] Optionally, solving the positioning matrix to obtain the target coordinates of the sensor includes:

[0027] The positioning matrix is ​​solved using the singular value decomposition method to obtain the positioning correction value of the sensor;

[0028] The target coordinates of the sensor are obtained by summing the initial coordinates with the positioning correction value.

[0029] Optionally, the preset seismic source includes historical seismic sources and calibrated seismic sources, and obtaining the source coordinates and source waveform of the preset seismic source includes:

[0030] Obtain the source coordinates of the historical earthquake source, and based on the occurrence time of the historical earthquake source, search the monitoring data to obtain the source waveform of the historical earthquake source;

[0031] Alternatively, the calibration source can be set, the source coordinates of the calibration source can be obtained, and a vibration signal can be emitted at the source coordinates of the calibration source. After the sensor collects the vibration signal, it generates the source waveform of the calibration source.

[0032] In this invention, by acquiring the source coordinates and waveform, and constructing an objective function using the source coordinates, waveform, and geological information of the monitoring area, the initial coordinates of the sensor with low precision can be quickly obtained. Then, the initial coordinates are further corrected using a double-difference algorithm to obtain more accurate target coordinates. This realizes intelligent positioning of the microseismic sensor, effectively avoiding the problems of inaccurate positioning and low positioning efficiency caused by manual measurement errors and non-standard sensor protection, thereby increasing the positioning efficiency of the microseismic sensor and effectively improving the accuracy and reliability of rockburst early warning.

[0033] The present invention also provides a micro-vibration sensor positioning device, comprising:

[0034] The acquisition module is used to acquire the source coordinates and source waveform of the preset seismic source;

[0035] The first processing module is used to construct an objective function based on the source coordinates, the source waveform, and the geological information of the monitoring area, and solve the objective function to obtain the initial coordinates of the sensor;

[0036] The second processing module is used to obtain the target coordinates of the sensor using a double-difference algorithm based on the source coordinates and the initial coordinates.

[0037] The sensor positioning device and the microseismic sensor positioning method provided by this invention can produce essentially the same technical effects, and will not be described in detail here.

[0038] The present invention also provides a system comprising a computer-readable storage medium storing a computer program and a processor, wherein when the computer program is read and executed by the processor, the microseismic sensor positioning method as described above is implemented.

[0039] The electronic device and the micro-vibration sensor positioning method provided by this invention can produce essentially the same technical effects, and will not be described in detail here.

[0040] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the micro-vibration sensor positioning method as described above.

[0041] The computer-readable storage medium and the microseismic sensor positioning method provided by this invention can produce essentially the same technical effects, and will not be described in detail here. Attached Figure Description

[0042] Figure 1 This is a flowchart illustrating the microseismic sensor positioning method according to an embodiment of the present invention.

[0043] Figure 2 This is a schematic diagram of the micro-vibration sensor positioning device according to an embodiment of the present invention. Detailed Implementation

[0044] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0045] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0046] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0047] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0048] It is understood that any part of this application relating to data acquisition or collection has been authorized.

[0049] like Figure 1 As shown, the present invention provides a method for locating a microseismic sensor, comprising:

[0050] Step S1: Obtain the source coordinates and source waveform of the preset seismic source.

[0051] Specifically, before acquiring the preset seismic source, a monitoring device and network are first constructed within the monitoring area. For example, the monitoring device includes multiple microseismic sensors, a data acquisition device, a data processing device, and an early warning device. The microseismic sensors can be placed inside or on the surface of the rock mass to monitor microseismic signals within the rock mass. The data acquisition device collects the signals generated by the microseismic sensors and transmits them to the data processing device. The data processing device processes and analyzes the microseismic signals to determine the spatial coordinates of the microseismic sensors. The early warning device issues a rockburst warning signal based on the characteristics of the microseismic signals. After the monitoring device and network are deployed, the acquisition software needs to be run, and appropriate screening and filtering parameters need to be set to ensure that the monitoring network can acquire and save effective vibration signals. In this embodiment, a micro-vibration sensor with 8 or more channels is arranged. Each channel adopts a single-axis acceleration type micro-vibration sensor or a velocity type micro-vibration sensor. The micro-vibration sensor transmits the collected vibration signal to a data acquisition device and a data processing device. The data acquisition device and the data processing device collect, process and filter the vibration signal to obtain an effective vibration signal. The preliminarily processed vibration signal is transmitted to a remote analysis system via wired or wireless means for signal type identification, timely pickup and analysis.

[0052] The preset seismic source can be a seismic source with a known location from historical monitoring, i.e., a historical seismic source, or a new seismic source with a defined location can be constructed, i.e., the location of the calibrated seismic source is determined, obtaining the calibration seismic source (e.g., a calibration shot) and its coordinates. When the preset seismic source is a historical seismic source, the stored monitoring information of the historical seismic source is directly retrieved. For example, based on the time of occurrence of the historical seismic source, the source coordinates and waveform of the historical seismic source are found. When the preset seismic source is a calibration seismic source, the coordinates of the calibration seismic source are pre-set. The calibration shot is activated, or the coordinate location of the calibration seismic source is struck, and the deployed microseismic sensors receive the vibration signal to generate the source waveform of the calibration seismic source.

[0053] Step S2: Construct an objective function based on the source coordinates, the source waveform, and the geological information of the monitoring area, and solve the objective function to obtain the initial coordinates of the sensor.

[0054] Specifically, the initial coordinates are low-precision coordinates determined based on the source coordinates, source waveform, and geological information of the monitoring area, which serve as preliminary positioning for the sensor. It should be noted that each microseismic monitoring environment, such as the geological environment, is different. Therefore, when constructing the objective function using the source waveform and source coordinates, the transmission of vibration signals by different geological environments should be considered. Thus, based on the known source coordinates, source waveform, and geological information of the monitoring area, an objective function is constructed to solve for the low-precision initial coordinates of the sensor, providing a basis for determining the subsequent target coordinates.

[0055] Step S3: Based on the source coordinates and the initial coordinates, obtain the target coordinates of the sensor using the double-difference algorithm.

[0056] In this embodiment, by acquiring the source coordinates and source waveform, and constructing an objective function using the source coordinates, source waveform, and geological information of the monitoring area, the low-precision initial coordinates of the sensor can be quickly obtained. Then, the initial coordinates are further corrected using a double-difference algorithm to obtain more accurate target coordinates. This realizes intelligent positioning of the microseismic sensor, effectively avoiding the problems of inaccurate positioning and low positioning efficiency caused by manual measurement errors and non-standard sensor protection, thereby increasing the positioning efficiency of the microseismic sensor and effectively improving the accuracy and reliability of rockburst early warning.

[0057] Optionally, the step of constructing the objective function based on the source coordinates, the source waveform, and the geological information of the monitoring area includes:

[0058] The wave velocity and attenuation coefficient of the source waveform are obtained based on the preset geological standards and the geological information of the monitoring area, and the frequency of the source waveform is obtained based on the source waveform.

[0059] Specifically, the preset geological standards may include geological survey data, which are used to determine the geological information of the monitoring area. Then, the corresponding wave velocity and micro-seismic wave attenuation coefficient are determined, and the waveform frequency is obtained based on the acquired source waveform.

[0060] The distance difference between the preset seismic source and any two sensors is obtained based on the wave velocity, the attenuation coefficient, the frequency, and the source coordinates, including:

[0061] The signal attenuation degree of the sensor is obtained based on the wave velocity, the attenuation coefficient, and the frequency, and can be expressed by the following formula:

[0062] ,

[0063] Where R represents the distance between the sensor and the preset seismic source, A(R) represents the signal attenuation at a distance of R, exp represents the natural exponential function, c represents the wave velocity, Q represents the attenuation coefficient, and f represents the frequency.

[0064] The first distance R is obtained by subtracting the coordinates of the seismic source from the coordinates of any two of the sensors (e.g., sensor i and sensor j). i Second distance R j .

[0065] Based on the degree of signal attenuation, the first distance R i and the second distance R j The difference is calculated by subtracting the values ​​to obtain the distance difference.

[0066] The first distance R i Second distance R j Substituting the difference into the formula for representing signal attenuation, we get:

[0067] ,

[0068] Where i and j are the sensor numbers, R i R represents the first distance between sensor i and the preset vibration source. j A represents the second distance between sensor j and the preset seismic source. i and A j These represent the maximum amplitude of the source waveforms of sensor i and sensor j, respectively.

[0069] The objective function is constructed based on the distance difference and the wave propagation formula.

[0070] Specifically, the formula for wave propagation is: Then, based on the first distance R i Second distance R j The objective function is constructed using the wave propagation formula, and the objective function is constructed using the first formula, which includes:

[0071] ,

[0072] Where Θ represents the objective function, n represents the number of preset seismic sources, and R i R represents the distance between sensor i and the preset vibration source. j This represents the distance between sensor j and the preset seismic source, where x0, y0, and z0 represent the coordinates of the seismic source. i y i z i Let x represent the initial coordinates of sensor i. j y j z j This represents the initial coordinates of sensor j.

[0073] Optimization algorithms such as the Nelder-Mead simplex localization method or particle swarm optimization are used to optimize the objective function, minimizing the initial coordinates x of sensor i to minimize Θ. i y i z i and the initial coordinates x of sensor j j y j z j This process continues until the initial coordinates of all sensors are determined.

[0074] Optionally, obtaining the target coordinates of the sensor using a double-difference algorithm based on the source coordinates and the initial coordinates includes:

[0075] Obtain the residuals of any two sensors, and subtract the residuals of the two sensors to obtain the double difference.

[0076] Specifically, for a micro-seismic event k, there must be a residual between the theoretical and actual travel time of the elastic wave reaching sensor i. ,Right now ,in, Indicates theoretical timekeeping, This represents the actual travel time. Since the elastic wave reaches two sensors, i and j, which are close to each other, there must be a residual. and Subtracting the two results in a set of double residuals, i.e., double difference. Specifically, it is expressed as:

[0077] ,

[0078] Among them, t i k t represents the travel time of the elastic wave from the preset source to sensor i. j k This represents the travel time of the elastic wave from the preset source to the sensor j.

[0079] Performing a Taylor expansion on the double difference yields the following results: :

[0080] ,

[0081] in, This represents the positioning correction value for the initial coordinates of sensor i. , , This is the coordinate vector correction amount for sensor i. Δξ is the correction value for the estimated time of vibration of sensor i. j =(Δx j Δyj Δz j , Δt j ) represents the positioning correction value of the initial coordinates of sensor j, Δx j Δy j Δz j Let Δt be the coordinate vector correction for sensor j. j Let ξ be the correction value for the estimated time of earthquake by sensor j, ξ represent the set of parameter variables related to the sensor coordinate correction value, and ∂ represent the partial derivative operation with respect to ξ (or other variables).

[0082] Expanding, we get:

[0083] ,

[0084] Among them, v P R represents the P-wave velocity. ik R jk x represents the distance from the preset seismic source k to sensor i and sensor j, respectively. k y k and z k This indicates the coordinates of the preset earthquake source k.

[0085] Based on the double difference after Taylor expansion, the positioning matrix Gm=d is constructed:

[0086] ,

[0087] ,

[0088] .

[0089] Solving the positioning matrix to obtain the target coordinates of the sensor includes:

[0090] The positioning matrix Gm=d is solved using methods such as Singular Value Decomposition (SVD) or Least Square QR-factorization (LSQR) to obtain the positioning correction value of the sensor. and ;

[0091] The target coordinates of the sensor are obtained by summing the initial coordinates with the positioning correction value.

[0092] Specifically, the initial coordinates of sensor i are summed with the positioning correction value of sensor i, i.e. Sum the initial coordinates of sensor j with the positioning correction value of sensor j, i.e. Repeat the steps of constructing the positioning matrix based on the double difference after Taylor expansion, when the correction amount Δξ i and Δξ j When the time is sufficiently short, the iteration ends. The target coordinates of sensor i and sensor j are then obtained.

[0093] The initial coordinates of the other sensors are corrected using the method described above to obtain the target coordinates of all sensors.

[0094] This embodiment also provides a micro-vibration sensor positioning device, including:

[0095] The acquisition module is used to acquire the source coordinates and source waveform of the preset seismic source;

[0096] The first processing module is used to construct an objective function based on the source coordinates, the source waveform, and the geological information of the monitoring area, and solve the objective function to obtain the initial coordinates of the sensor;

[0097] The second processing module is used to obtain the target coordinates of the sensor using a double-difference algorithm based on the source coordinates and the initial coordinates.

[0098] The first processing module is also used to obtain the wave velocity and attenuation coefficient of the monitoring area according to the preset geological standards and the geological information of the monitoring area, and to obtain the frequency according to the source waveform; to obtain the distance difference from the preset source to any two of the sensors based on the wave velocity, the attenuation coefficient, the frequency and the source coordinates; and to construct the objective function according to the distance difference and the wave propagation formula.

[0099] The first processing module is further configured to obtain the signal attenuation degree of the sensor based on the wave velocity, the attenuation coefficient, and the frequency; to obtain a first distance and a second distance by subtracting the source coordinates from any two sensor coordinates; and to obtain the distance difference by subtracting the first distance and the second distance based on the signal attenuation degree.

[0100] The first processing module is further configured to construct the objective function using a first formula, the first formula comprising:

[0101] ,

[0102] Where Θ represents the objective function, k represents ..., n represents the number of preset seismic sources, and R i R represents the distance between sensor i and the preset vibration source. j This represents the distance between sensor j and the preset seismic source, where x0, y0, and z0 represent the coordinates of the seismic source. i y i z i Let x represent the initial coordinates of sensor i. j yj z j This represents the initial coordinates of sensor j.

[0103] The second processing module is also used to obtain the residuals of any two sensors, subtract the residuals of the two sensors to obtain a double difference; perform a Taylor expansion on the double difference, and construct a positioning matrix based on the double difference after Taylor expansion; solve the positioning matrix to obtain the target coordinates of the sensor.

[0104] The second processing module is also used to solve the positioning matrix using the singular value decomposition method to obtain the positioning correction value of the sensor; and to sum the initial coordinates with the positioning correction value to obtain the target coordinates of the sensor.

[0105] The acquisition module is also used to acquire the source coordinates of the historical earthquake source, search the monitoring data according to the occurrence time of the historical earthquake source, and obtain the source waveform of the historical earthquake source; or set the calibration earthquake source, acquire the source coordinates of the calibration earthquake source, and emit a vibration signal at the source coordinates of the calibration earthquake source, and the sensor generates the source waveform of the calibration earthquake source after acquiring the vibration signal.

[0106] The microseismic sensor positioning device and the microseismic sensor positioning method provided in this embodiment can produce basically the same technical effects, which will not be described in detail here.

[0107] This embodiment also provides a system including a computer-readable storage medium storing a computer program and a processor, which, when the computer program is read and run by the processor, implements the microseismic sensor positioning method as described above.

[0108] The system provided in this embodiment achieves essentially the same technical effect as the microseismic sensor positioning method, and will not be described in detail here.

[0109] This embodiment also provides a computer-readable storage medium, characterized in that the storage medium stores a computer program, which, when executed by a processor, implements the micro-vibration sensor positioning method as described above.

[0110] The computer-readable storage medium provided in this embodiment and the microseismic sensor positioning method can produce essentially the same technical effects, and will not be described again here.

[0111] The present invention will now describe electronic devices that can serve as servers or clients of the present invention, which are examples of hardware devices that can be applied to various aspects of the present invention. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0112] Electronic devices include a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM can also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0113] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other.

[0114] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.

[0115] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for locating a microseismic sensor, characterized in that, include: Obtain the source coordinates and source waveform of the preset seismic source; An objective function is constructed based on the source coordinates, the source waveform, and the geological information of the monitoring area. The initial coordinates of the sensor are obtained by solving the objective function. The target coordinates of the sensor are obtained using the double-difference algorithm based on the source coordinates and the initial coordinates. The step of obtaining the target coordinates of the sensor using a double-difference algorithm based on the source coordinates and the initial coordinates includes: Obtain the residuals of any two sensors, and subtract the residuals of the two sensors to obtain a double difference, expressed as: ， Among them, t i k t represents the travel time of the elastic wave from the preset source to the sensor i. j k The travel time of the elastic wave from the preset seismic source to sensor j is represented by k, where k represents the micro-vibration event. This represents the theoretical travel time of the elastic wave reaching sensor i. Compared with actual time The residual between, r j k This represents the theoretical travel time of the elastic wave reaching sensor j. Compared with actual time The residual between, r ij k This indicates the double difference; The Taylor expansion of the double difference is expressed as: ， in, This represents the double difference after Taylor expansion. This represents the positioning correction value for the initial coordinates of sensor i. , , This is the coordinate vector correction amount for sensor i. Δξ is the correction value for the estimated time of vibration of sensor i. j =(Δx j Δy j Δz j , Δt j ) represents the positioning correction value of the initial coordinates of sensor j, Δx j Δy j Δz j Δt is the coordinate vector correction amount for sensor j. j Let ξ be the correction value for the estimated time of earthquake occurrence of sensor j, ξ represent the set of parameter variables related to the sensor coordinate correction value, and ∂ represent the correction value for Δξ. j and Δξ i Performing a partial derivative operation, the double-difference expansion after the Taylor expansion is expressed as: ， Among them, v P R represents the P-wave velocity. ik R jk x represents the distance from the preset earthquake source k to the sensor i and sensor j, respectively. k y k and z k This represents the coordinates of the preset earthquake source k; And based on the double difference after Taylor expansion, a positioning matrix is ​​constructed, which is expressed as: Gm=d, in, , , ; Solving the positioning matrix yields the target coordinates of the sensor; The process of solving the positioning matrix to obtain the target coordinates of the sensor includes: The positioning matrix is ​​solved using the singular value decomposition method to obtain the positioning correction value of the sensor; The target coordinates of the sensor are obtained by summing the initial coordinates with the positioning correction value.

2. The microseismic sensor positioning method according to claim 1, characterized in that, The construction of the objective function based on the seismic source coordinates, the seismic source waveform, and the geological information of the monitoring area includes: The wave velocity and attenuation coefficient of the source waveform are obtained based on the preset geological standards and the geological information of the monitoring area, and the frequency of the source waveform is obtained based on the source waveform. The distance difference between the preset source and any two sensors is obtained based on the wave velocity, the attenuation coefficient, the frequency, and the source coordinates. The objective function is constructed based on the distance difference and the wave propagation formula.

3. The microseismic sensor positioning method according to claim 2, characterized in that, The step of obtaining the distance difference from the preset seismic source to any two sensors based on the wave velocity, the attenuation coefficient, the frequency, and the source coordinates includes: The signal attenuation degree of the sensor is obtained based on the wave velocity, the attenuation coefficient, and the frequency. The first distance and the second distance are obtained by subtracting the earthquake source coordinates from the coordinates of any two of the sensors. Based on the degree of signal attenuation, the difference between the first distance and the second distance is obtained.

4. The microseismic sensor positioning method according to claim 2, characterized in that, The construction of the objective function based on the distance difference and the wave propagation formula includes: The objective function is constructed using a first formula, which includes: ， Where Θ represents the objective function, n represents the number of preset seismic sources, and R i R represents the distance between sensor i and the preset vibration source. j This represents the distance between sensor j and the preset seismic source, where x0, y0, and z0 represent the coordinates of the seismic source. i 、y i z i Let x represent the initial coordinates of sensor i. j 、y j z j This represents the initial coordinates of sensor j.

5. The microseismic sensor positioning method according to claim 1, characterized in that, The preset seismic source includes historical seismic sources and calibrated seismic sources; obtaining the source coordinates and source waveform of the preset seismic source includes: Obtain the source coordinates of the historical earthquake source, and based on the occurrence time of the historical earthquake source, search the monitoring data to obtain the source waveform of the historical earthquake source; Alternatively, the calibration source can be set, the source coordinates of the calibration source can be obtained, and a vibration signal can be emitted at the source coordinates of the calibration source. After the sensor collects the vibration signal, it generates the source waveform of the calibration source.

6. A micro-vibration sensor positioning device, characterized in that, include: The acquisition module is used to acquire the source coordinates and source waveform of the preset seismic source; The first processing module is used to construct an objective function based on the source coordinates, the source waveform, and the geological information of the monitoring area, and solve the objective function to obtain the initial coordinates of the sensor; The second processing module is used to obtain the target coordinates of the sensor using a double-difference algorithm based on the source coordinates and the initial coordinates. The step of obtaining the target coordinates of the sensor using the double-difference algorithm based on the source coordinates and the initial coordinates includes: obtaining the residuals of any two sensors, and subtracting the residuals of the two sensors to obtain the double difference, expressed as: ， Among them, t i k t represents the travel time of the elastic wave from the preset source to the sensor i. j k The travel time of the elastic wave from the preset seismic source to sensor j is represented by k, where k represents the micro-vibration event. This represents the theoretical travel time of the elastic wave reaching sensor i. Compared with actual time The residual between, r j k This represents the theoretical travel time of the elastic wave reaching sensor j. Compared with actual time The residual between, r ij k This indicates the double difference; The Taylor expansion of the double difference is expressed as: ， in, This represents the double difference after Taylor expansion. This represents the positioning correction value for the initial coordinates of sensor i. , , This is the coordinate vector correction amount for sensor i. Δξ is the correction value for the estimated time of vibration of sensor i. j =(Δx j Δy j Δz j , Δt j ) represents the positioning correction value of the initial coordinates of sensor j, Δx j Δy j Δz j Δt is the coordinate vector correction amount for sensor j. j Let ξ be the correction value for the estimated earthquake time of sensor j, ξ represent the set of parameter variables related to the sensor coordinate correction value, and ∂ represent the partial derivative operation. The double-difference expansion after the Taylor expansion is expressed as: ， Among them, v P R represents the P-wave velocity. ik R jk x represents the distance from the preset earthquake source k to the sensor i and sensor j, respectively. k y k and z k This represents the coordinates of the preset earthquake source k; And based on the double difference obtained from the Taylor expansion, a positioning matrix is ​​constructed, which is expressed as: Gm=d, in, , , ; Solving the positioning matrix yields the target coordinates of the sensor; solving the positioning matrix to obtain the target coordinates of the sensor includes: solving the positioning matrix using singular value decomposition to obtain the positioning correction value of the sensor; and summing the initial coordinates and the positioning correction value to obtain the target coordinates of the sensor.

7. A system, characterized in that, The method includes a computer-readable storage medium storing a computer program and a processor, which, when read and run by the processor, implements the microseismic sensor positioning method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the microseismic sensor positioning method as described in any one of claims 1-5.

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