Method, device and equipment for calculating longitude and latitude coordinates based on alarm position and medium

Abstract

This application relates to the field of communication technology and discloses a method, apparatus, device, and medium for calculating latitude and longitude coordinates based on alarm location. The method includes: constructing a raw large dataset based on environmental information data of distributed optical fiber lines; determining linear interpolation advantage regions, curve fitting advantage regions, and transitional mixed regions based on the raw large dataset using clustering and classification algorithms, convolutional neural networks, and long short-term memory networks; determining a target region from the linear interpolation advantage regions, curve fitting advantage regions, and transitional mixed regions based on the location of the alarm point; and determining the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target region. This application solves the technical problems of low accuracy in locating optical fiber alarm positions and low alarm handling efficiency in existing technologies.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus, device and medium for calculating latitude and longitude coordinates based on alarm location. Background Technology

[0002] With the application of distributed optical fiber in the safety protection of oil and gas pipelines, the need for timely and accurate location of optical fiber alarms and their corresponding actual geographical locations is becoming increasingly urgent.

[0003] In existing technologies, this challenge can be addressed through linear interpolation, curve fitting, map projection-based transformation methods, or georeferenced model-based methods.

[0004] However, linear interpolation is suitable for areas where fiber optic cables are laid in relatively straight lines. When the fiber optic cable has significant bends or the terrain is complex, causing the fiber optic cable to have a non-linear path, linear interpolation may produce large errors. Curve fitting may not be able to accurately fit the true path of the fiber optic cable when there are few or unevenly distributed data points. Map projection-based conversion methods require accurate projection parameter information. If the projection parameters are incorrect or incomplete, it will lead to large errors in the converted latitude and longitude coordinates. Geographic reference model-based methods are highly dependent on the accuracy and resolution of the geographic reference model. If the DEM data has low accuracy or insufficient resolution, it will affect the accuracy of latitude and longitude coordinate calculations.

[0005] Therefore, there is an urgent need for a technical solution to improve the accuracy of alarm location and the efficiency of alarm handling. Summary of the Invention

[0006] This application provides a method, apparatus, device, and medium for calculating latitude and longitude coordinates based on alarm location, which can solve the technical problems of low accuracy of positioning fiber optic alarm location and low alarm handling efficiency in the prior art.

[0007] To achieve the above objectives, this application provides the following technical solution: A method for calculating latitude and longitude coordinates based on alarm location, the method comprising: Constructing a raw large dataset based on environmental information data from distributed fiber optic lines. Based on the original large dataset, the linear interpolation advantage region, the curve fitting advantage region, and the transitional mixed region are determined by clustering and classification algorithms, convolutional neural networks, and long short-term memory networks. The target region is determined from the linear interpolation advantage region, the curve fitting advantage region, and the transition mixing region based on the location of the alarm point; Based on the strategy corresponding to the target area, the latitude and longitude coordinates of the alarm point are determined.

[0008] Optionally, in one embodiment, the linear interpolation advantage region is a region within a certain length window where the rate of change of fiber curvature is lower than a first preset value and the terrain undulation is gentle. The curve fitting advantage region is the area where the fiber curvature change rate is higher than the second preset value and the terrain is complex and varied within the corresponding length range. The transitional mixing region is a region that lies between the linear interpolation advantage region and the curve fitting advantage region, and has both linear and nonlinear characteristics.

[0009] Optionally, in one embodiment, determining the target region from the linear interpolation dominance region, the curve fitting dominance region, and the transitional mixing region based on the location of the alarm point includes: Select the fiber segment where the alarm point is located in the initial big data fiber segment dataset; The target region is determined from the linear interpolation advantage region, the curve fitting advantage region, and the transitional mixing region based on the morphological pattern of the fiber segment.

[0010] Optionally, in one embodiment, the target region is the linear interpolation advantage region, and determining the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target region includes: Obtain the first and second collection points adjacent to the alarm point from the original big data set; The latitude and longitude coordinates of the first acquisition point and the latitude and longitude coordinates of the second acquisition point are transformed to obtain the plane rectangular coordinates of the first acquisition point and the second acquisition point; Based on the plane rectangular coordinates of the first and second acquisition points, the plane rectangular coordinates of the alarm point when the target area is the linear interpolation advantage area are calculated using the latitude and longitude coordinate calculation formula; The Cartesian coordinates of the alarm point when the target area is the linear interpolation dominance area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the linear interpolation dominance area; The formula for calculating the latitude and longitude coordinates is as follows:

[0011] In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the linear interpolation dominance region. Represents the Cartesian coordinates of the first data collection point. This represents the Cartesian coordinates of the second acquisition point. This represents the correction factor for environmental data in the X direction. This represents the correction factor for environmental data in the Y direction, and L represents the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the first optical fiber corresponding to the first acquisition point; This indicates the relative length of the second optical fiber corresponding to the second acquisition point.

[0012] Optionally, in one embodiment, the target region is the curve fitting advantage region, and determining the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target region includes: Several collection points within a preset range of the alarm points are obtained from the original big data set, and are denoted as follows: ,in, This represents the i-th data collection point. This represents the relative length of the optical fiber corresponding to the i-th acquisition point among the plurality of acquisition points. This represents the longitude coordinates of the i-th collection point among the plurality of collection points. This represents the latitude coordinates of the i-th collection point among the plurality of collection points. This represents the elevation of the i-th data collection point. This represents the direction angle of the i-th acquisition point. This represents the pitch angle of the i-th data acquisition point; Based on the aforementioned collection points, a piecewise cubic Hermite interpolation method is used for positioning to obtain a third and fourth collection points adjacent to the alarm point, wherein the cumulative distance of the alarm point falls within the range of the cumulative distance of the third and fourth collection points. Based on the third and fourth acquisition points, a polynomial function is constructed using high-order curve fitting techniques with Hermite interpolation. Based on the first cumulative distance between the third acquisition point and the third acquisition point, the second cumulative distance between the fourth acquisition point and the third acquisition point, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance, the coefficients to be determined in the polynomial function are solved to obtain the solved coefficients to be determined. Based on the solved coefficients and the polynomial function, the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region are calculated. The Cartesian coordinates of the alarm point when the target area is the curve fitting advantage area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; The polynomial function is as follows:

[0013] In the formula, This represents the cumulative distance from any target point to the third acquisition point within the segment of the fitted curve between the third and fourth acquisition points. L represents the relative length of the optical fiber corresponding to the target point. This indicates the relative length of the optical fiber corresponding to the third acquisition point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. Represents a polynomial function in the X direction. Represents a polynomial function in the Y direction.

[0014] Optionally, in one embodiment, the step of solving for the coefficients to be determined in the polynomial function based on the first cumulative distance between the third acquisition point and the fourth acquisition point, the second cumulative distance between the fourth acquisition point and the third acquisition point, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance, to obtain the solved coefficients to be determined, includes: Substituting the first cumulative distance from the third acquisition point to the third acquisition point and the first derivative of the first cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the first system of equations, wherein the first system of equations is as follows:

[0015] In the formula, Indicates the first cumulative distance The corresponding polynomial function in the X direction, Indicates the longitude coordinates of the third data collection point. Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the third data collection point. Indicates the direction angle of the third acquisition point. Indicates the elevation angle of the third acquisition point; Indicates the first cumulative distance The corresponding polynomial function in the Y direction, Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the third data collection point. The derivative representing the latitude coordinates of the third data collection point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. The first derivative represents the first cumulative distance in the X direction. The first derivative represents the first cumulative distance in the Y direction; Substituting the second cumulative distance from the fourth acquisition point to the third acquisition point and the second derivative of the second cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the second system of equations, which is as follows:

[0016] In the formula, Indicates the second cumulative distance The corresponding polynomial function in the X direction, This indicates the longitude coordinates of the fourth data collection point. Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the fourth data collection point. Indicates the direction angle of the fourth acquisition point. Indicates the elevation angle of the fourth acquisition point; Indicates the second cumulative distance The corresponding polynomial function in the Y direction, Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the fourth data collection point. The derivative of the latitude coordinates of the fourth data collection point. The second derivative represents the second cumulative distance in the X direction. The second derivative represents the second cumulative distance in the Y direction; Based on the first set of equations and the second set of equations, the coefficients to be solved are obtained.

[0017] Optionally, in one embodiment, calculating the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region based on the solved coefficients and the polynomial function includes: Substitute the solved coefficients into the polynomial function to calculate the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. The calculation process is as follows:

[0018] In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. This represents the third cumulative distance from the alarm point to the third data collection point. , This indicates the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the optical fiber corresponding to the third acquisition point. , , and This represents the coefficients to be determined in the X direction after the solution is obtained. , , and This represents the coefficient to be determined in the Y direction after the solution is obtained.

[0019] Optionally, in one embodiment, the target area is the transitional mixing zone, and determining the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target area includes: Based on the rate of change of fiber curvature and the degree of terrain undulation, the initial weights of linear interpolation and curve fitting are dynamically adjusted to obtain the adjusted linear interpolation weights and adjusted curve fitting weights. Obtain the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area, and the second latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; Based on the adjusted linear interpolation weights, the adjusted curve fitting weights, the first latitude and longitude coordinates, and the second latitude and longitude coordinates, the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone are calculated using a preset formula. The preset formula is as follows:

[0020] In the formula, This indicates the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone. This represents the adjusted linear interpolation weights. This represents the adjusted curve fitting weights. This indicates the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area. The second latitude and longitude coordinates of the alarm point indicate when the target area is the curve fitting advantage area.

[0021] Based on the same inventive concept, embodiments of this application also provide a device for calculating latitude and longitude coordinates based on alarm location, the device comprising: The data acquisition module is configured to construct a raw large dataset based on environmental information data from distributed fiber optic lines. The region segmentation module is configured to determine linear interpolation advantage regions, curve fitting advantage regions, and transitional mixed regions based on the original large dataset using clustering and classification algorithms, convolutional neural networks, and long short-term memory networks. The target region determination module is configured to determine a target region from the linear interpolation dominance region, the curve fitting dominance region, and the transitional mixing region based on the location of the alarm point; The latitude and longitude coordinate determination module is configured to determine the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target area.

[0022] Based on the same inventive concept, this application also provides an electronic device, including: a memory and a processor; the processor is used to read and execute a computer program stored in the memory to implement the steps of the aforementioned method for calculating latitude and longitude coordinates based on alarm location.

[0023] Based on the same inventive concept, embodiments of this application also provide a computer storage medium storing computer-executable instructions, which, when executed, implement the steps of the aforementioned method for calculating latitude and longitude coordinates based on alarm locations.

[0024] The technical effects and advantages of this application are as follows: By combining the GIS coordinates and relative position information of the communication optical cable, the alarm can be accurately located. Compared with the traditional coarse positioning method based on the division of defense zones, this application can be accurate to specific latitude and longitude coordinates, which greatly improves the positioning accuracy. Precise location capabilities enable maintenance personnel to quickly locate alarm points, reducing troubleshooting time and improving alarm handling efficiency. This application solves the technical problems of low accuracy in locating fiber optic alarms and low efficiency in alarm handling in the prior art.

[0025] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1A flowchart illustrating the method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the functional modules of an embodiment of the device for calculating latitude and longitude coordinates based on alarm location according to this application; Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0028] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] To address the shortcomings of existing technologies, refer to Figure 1 This application discloses a method for calculating latitude and longitude coordinates based on alarm location, including: Step S10: Construct the original large dataset based on the environmental information data of the distributed optical fiber lines; In this embodiment, a high-precision measuring instrument is used to collect geographic information omnidirectionally along the distributed optical fiber line at preset intervals (e.g., every 100 meters). This includes determining the latitude and longitude coordinates of each point, three-dimensional orientation (pitch angle, yaw angle, etc.), real-time strain, surrounding topographic features (including slope, undulation, geological type, etc.), and environmental temperature and humidity data, among other multi-source heterogeneous environmental information. It should be noted that in actual operation, the 100-meter error method can be used to determine if the linear interpolation advantage zone is met, even if the length is over a kilometer, no additional sampling points are needed. If a nonlinear region exists between two linear interpolation advantage zones, additional sampling points are required to fit the optical cable route. If the length of the curve fitting advantage zone is too large, additional sampling points are also required. In engineering practice, implementation depends on the required calculation accuracy and site conditions.

[0030] Kalman filtering is employed to classify, clean, and structurally integrate the massive and complex multi-source heterogeneous environmental information data. Abnormal data points caused by equipment noise, environmental interference, etc., are removed, constructing a multi-dimensional, ordered original large dataset, which is then stored in the Ceph distributed storage system for easy subsequent retrieval and retrieval. Ceph is an open-source distributed storage system that supports object storage, block storage, and file storage, and features high reliability, scalability, and ease of management.

[0031] Step S20: Based on the original large dataset, determine the linear interpolation advantage region, curve fitting advantage region, and transitional mixed region through clustering and classification algorithms, convolutional neural networks, and long short-term memory networks; In this embodiment, based on clustering and classification algorithms, in-depth mining is performed on the fiber optic routing characteristics and topographic data in the original big data set. By combining a convolutional neural network with a long short-term memory network, the morphological patterns of different segments of the fiber optic line are automatically identified, accurately dividing the linear interpolation advantage region, the curve fitting advantage region, and the transitional mixed region. The linear interpolation advantage region is defined as an area within a certain length window where the fiber curvature change rate is lower than a first preset value and the terrain undulation is gentle. The curve fitting advantage region is an area within a corresponding length interval where the fiber curvature change rate is higher than a second preset value and the terrain is complex and varied. The transitional mixed region is an area between the linear interpolation advantage region and the curve fitting advantage region, possessing both linear and nonlinear characteristics. The first preset value is lower than the second preset value.

[0032] Among them, based on the fiber segment dataset, during initialization, the latitude and longitude, elevation angle, and optical signal length information of the sampling points can be used to calculate the difference between the latitude and longitude distance of a fiber segment and the fiber length to determine the terrain undulation and terrain complexity. In practice, the error per 100 meters is used, for example: Generally, in statistical terms, an error of 100 meters or less is defined as a region with gentle terrain undulations, where the linear interpolation error is within the first error threshold (e.g., 0.5 meters). In this region, the linear interpolation error is within an acceptable range.

[0033] Generally, statistically speaking, the area outside the second error threshold (e.g., 3 meters) is defined as a region with complex and varied terrain. In this region, the interpolation error of curve fitting is optimal.

[0034] Optical cables are usually laid in a straight line, but there is an elevation angle, so the elevation angle is needed as a basis for calculating the error per 100 meters.

[0035] For further optimization, fiber optic routes and topographic data from the original big data can be introduced for in-depth analysis, defining the advantageous areas of various algorithms and recommending the best interpolation method.

[0036] In practical implementation, to save computing power and improve processing efficiency, and to fully utilize the recommended hybrid algorithm optimization and curve fitting methods to improve interpolation accuracy, a fiber optic segment dataset is constructed from the original big data. Through preprocessing, the following items are added: latitude and longitude, elevation, fiber optic cable length, cable number, uplink and downlink numbers, elevation angle, azimuth angle, error per 100 meters, recommended interpolation calculation method, initial correction value for linear interpolation, and curve fitting parameter set. This fiber optic segment dataset improves the program's efficiency in processing real-time alarm data and requires no code changes during continuous optimization.

[0037] By preprocessing and pre-selecting algorithms (interpolation calculation methods) and pre-optimizing parameters (linear interpolation parameter sets, curve fitting parameter sets), we can: 1) simplify code implementation and optimization steps, and provide a systematic mechanism guarantee for continuous parameter optimization; 2) greatly simplify the calculation process and save the computing resources required for positioning: alarm events triggered by fiber optic vibration on pipelines are often continuous and long-term, and even the location is frequently changing. This method of using fiber optic distance to locate the segment, caching the positioning algorithm and parameters of the segment, and directly calculating the alarm location using the simplified algorithm greatly saves resources and improves resource utilization efficiency.

[0038] Step S30: Determine the target region from the linear interpolation advantage region, the curve fitting advantage region, and the transition mixing region based on the location of the alarm point; Further, in one embodiment, step S30 includes: Select the fiber segment where the alarm point is located in the initial big data fiber segment dataset; The target region is determined from the linear interpolation advantage region, the curve fitting advantage region, and the transitional mixing region based on the morphological pattern of the fiber segment.

[0039] In this embodiment, when a fiber optic alarm is generated, the location of the fiber optic alarm point (optical cable number, optical cable uplink / downlink number, alarm point location (length)) is read, and the fiber segment where the alarm point is located is selected in the fiber optic segment dataset that initializes large data.

[0040] Based on the morphological pattern of the fiber segment where the alarm point is located, determine which region of the fiber segment where the alarm point is located—the linear interpolation dominance region, the curve fitting dominance region, or the transitional mixed region—and determine the region corresponding to the morphological pattern of the fiber segment where the alarm point is located (linear interpolation dominance region, curve fitting dominance region, or transitional mixed region) as the target region.

[0041] Then, based on the recommended interpolation method in the target area, the parameters or parameter groups are adjusted, and the interpolation method is called to calculate the longitude and latitude of the alarm point. Recommended interpolation methods include: linear interpolation, curve fitting, and a hybrid method.

[0042] It is easy to understand that the alarm point location provided by the fiber optic device in this embodiment is actually the length of the optical signal propagation, which cannot be used in actual production environments and needs to be converted to latitude and longitude before it can be used.

[0043] Step S40: Determine the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target area.

[0044] In this embodiment, the target region is any one of the linear interpolation advantage region, curve fitting advantage region, and transitional mixed region. Each target region has its corresponding strategy for calculating the latitude and longitude coordinates of the alarm point. Therefore, after determining the target region, the latitude and longitude coordinates of the alarm point can be determined based on the strategy corresponding to the target region.

[0045] Further, in one embodiment, the target region is the linear interpolation advantage region, and step S40 includes: Obtain the first and second collection points adjacent to the alarm point from the original big data set; The latitude and longitude coordinates of the first acquisition point and the latitude and longitude coordinates of the second acquisition point are transformed to obtain the plane rectangular coordinates of the first acquisition point and the second acquisition point; Based on the plane rectangular coordinates of the first and second acquisition points, the plane rectangular coordinates of the alarm point when the target area is the linear interpolation advantage area are calculated using the latitude and longitude coordinate calculation formula; The Cartesian coordinates of the alarm point when the target area is the linear interpolation dominance area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the linear interpolation dominance area; The formula for calculating the latitude and longitude coordinates is as follows:

[0046] In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the linear interpolation dominance region. Represents the Cartesian coordinates of the first data collection point. This represents the Cartesian coordinates of the second acquisition point. This represents the correction factor for environmental data in the X direction. This represents the correction factor for environmental data in the Y direction, and L represents the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the first optical fiber corresponding to the first acquisition point; This indicates the relative length of the second optical fiber corresponding to the second acquisition point.

[0047] In this embodiment, when the alarm point falls within the linear interpolation advantage region, preferably, two optimal acquisition points adjacent to the alarm point are located in the original big data set, namely the first acquisition point and the second acquisition point. The selection of these two acquisition points is based not only on the principle of closest proximity, but also on a comprehensive consideration of their data quality (such as coordinate measurement accuracy, strain stability, etc.). Let these two points be... and First collection point The corresponding relative length of the first optical fiber is Second collection point The corresponding relative length of the first optical fiber is Given that the relative length corresponding to the alarm point is L, .

[0048] To ensure calculation accuracy, a coordinate transformation operation needs to be performed, as follows: The latitude and longitude coordinates of the first and second acquisition points are converted into Cartesian XY coordinates; interpolation calculations are performed based on the converted Cartesian XY coordinates; and the interpolation results are converted back from Cartesian XY coordinates to latitude and longitude coordinates.

[0049] Specifically, the latitude and longitude coordinates of the first acquisition point and the latitude and longitude coordinates of the second acquisition point are transformed to obtain the plane rectangular coordinates of the first acquisition point and the second acquisition point; Based on the plane rectangular coordinates of the first and second acquisition points, the plane rectangular coordinates of the alarm point when the target area is a linear interpolation advantage area are calculated using the latitude and longitude coordinate calculation formula. The formulas for calculating latitude and longitude coordinates are as follows:

[0050] In the formula, This represents the Cartesian coordinates of the alarm point when the target area is a linear interpolation dominance area. Represents the Cartesian coordinates of the first data collection point. This represents the Cartesian coordinates of the second acquisition point. This represents the correction factor for environmental data in the X direction. This represents the correction factor for environmental data in the Y direction, and L represents the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the first optical fiber corresponding to the first acquisition point; This indicates the relative length of the second optical fiber corresponding to the second acquisition point.

[0051] By performing coordinate transformation on the Cartesian coordinates of the alarm point when the target area is a linear interpolation advantage zone, the latitude and longitude coordinates of the alarm point when the target area is the linear interpolation advantage zone can be obtained.

[0052] Further, in one embodiment, the target region is the curve fitting advantage region, and step S40 includes: Several collection points within a preset range of the alarm points are obtained from the original big data set, and are denoted as follows: ,in, This represents the i-th data collection point. This represents the relative length of the optical fiber corresponding to the i-th acquisition point among the plurality of acquisition points. This represents the longitude coordinates of the i-th collection point among the plurality of collection points. This represents the latitude coordinates of the i-th collection point among the plurality of collection points. This represents the elevation of the i-th data collection point. This represents the direction angle of the i-th acquisition point. This represents the pitch angle of the i-th data acquisition point; Based on the aforementioned collection points, a piecewise cubic Hermite interpolation method is used for positioning to obtain a third and fourth collection points adjacent to the alarm point, wherein the cumulative distance of the alarm point falls within the range of the cumulative distance of the third and fourth collection points. Based on the third and fourth acquisition points, a polynomial function is constructed using high-order curve fitting techniques with Hermite interpolation. Based on the first cumulative distance between the third acquisition point and the third acquisition point, the second cumulative distance between the fourth acquisition point and the third acquisition point, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance, the coefficients to be determined in the polynomial function are solved to obtain the solved coefficients to be determined. Based on the solved coefficients and the polynomial function, the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region are calculated. The Cartesian coordinates of the alarm point when the target area is the curve fitting advantage area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; The polynomial function is as follows:

[0053] In the formula, This represents the cumulative distance from any target point to the third acquisition point within the segment of the fitted curve between the third and fourth acquisition points. L represents the relative length of the optical fiber corresponding to the target point. This indicates the relative length of the optical fiber corresponding to the third acquisition point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. Represents a polynomial function in the X direction. Represents a polynomial function in the Y direction.

[0054] In this embodiment, if the alarm point is located in the curve fitting advantage region, a number of representative collection points within a preset range of the alarm point are intelligently selected from the original big data set (the number is dynamically determined by the machine learning model according to the curve complexity, generally 15-20), denoted as... The parameters are defined as follows: This represents the i-th data collection point; This represents the fiber length corresponding to the i-th acquisition point among the extracted acquisition points; This represents the longitude coordinates of the i-th collection point out of a set of collection points. This represents the latitude coordinates of the i-th collection point among a set of collection points. This represents the elevation of the i-th data collection point. This represents the direction angle of the i-th acquisition point. This represents the elevation angle of the i-th acquisition point.

[0055] For distributed fiber optic cables running parallel to oil pipelines with smooth trajectories, segmented cubic Hermite interpolation is used to locate alarm points from several extracted data collection points. The adjacent third collection point and the fourth collection point The cumulative distance of the alarm points falls between the cumulative distances of the third and fourth data collection points. Furthermore, for routes with complex trajectories, more data collection points need to be introduced to improve the fitting accuracy.

[0056] Based on the selected third and fourth acquisition points, a polynomial function is constructed using high-order curve fitting techniques with Hermite interpolation. The polynomial function is as follows:

[0057] In the formula, This represents the cumulative distance from any target point to the third acquisition point within the segment of the fitted curve between the third and fourth acquisition points. L represents the relative length of the optical fiber corresponding to the target point. This indicates the relative length of the optical fiber corresponding to the third acquisition point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. Represents a polynomial function in the X direction. Represents a polynomial function in the Y direction.

[0058] By utilizing the continuous function value and derivative value of the Hermite interpolation function, the coefficients to be determined in the polynomial function are solved based on the first cumulative distance between the third acquisition point and the third acquisition point, the second cumulative distance between the fourth acquisition point and the third acquisition point, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance.

[0059] Specifically, the first cumulative distance between the third collection point and the third collection point. Substituting the first derivative of the first cumulative distance into the polynomial function and its derivative, we obtain the first system of equations, which are as follows:

[0060] In the formula, Indicates the first cumulative distance The corresponding polynomial function in the X direction, Indicates the longitude coordinates of the third data collection point. Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the third data collection point. Indicates the direction angle of the third acquisition point. Indicates the elevation angle of the third acquisition point; Indicates the first cumulative distance The corresponding polynomial function in the Y direction, Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the third data collection point. The derivative representing the latitude coordinates of the third data collection point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. The first derivative of the first cumulative distance in the X direction. The first derivative represents the first cumulative distance in the Y direction; Substituting the second cumulative distance from the fourth acquisition point to the third acquisition point and the second derivative of the second cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the second system of equations, which is as follows:

[0061] In the formula, Indicates the second cumulative distance The corresponding polynomial function in the X direction, This indicates the longitude coordinates of the fourth data collection point. Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the fourth data collection point. Indicates the direction angle of the fourth acquisition point. Indicates the elevation angle of the fourth acquisition point; Indicates the second cumulative distance The corresponding polynomial function in the Y direction, Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the fourth data collection point. The derivative of the latitude coordinates of the fourth data collection point. The second derivative represents the second cumulative distance in the X direction. The second derivative represents the second cumulative distance in the Y direction; Based on the first and second sets of equations, the coefficients to be determined in the polynomial function can be solved to obtain the coefficients after the solution.

[0062] It should be noted that the first cumulative distance Second cumulative distance The derivatives in the X direction are respectively and The "arc length derivative" of the optical cable route, i.e., the speed magnitude v, is a direction vector per unit length. In engineering, it is usually taken as 1, so the first cumulative distance... Second cumulative distance The derivatives in the X direction are respectively and Similarly, the first cumulative distance Second cumulative distance The derivatives in the Y direction are respectively and .

[0063] Furthermore, by substituting the solved coefficients into the polynomial function, the Cartesian coordinates of the alarm point when the target region is a curve-fitting advantage area can be calculated. The specific calculation process is as follows:

[0064] In the formula, The plane rectangular coordinates of the alarm point represent the curve fitting advantage region when the target region is the target region. This represents the third cumulative distance from the alarm point to the third data collection point. , This indicates the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the optical fiber corresponding to the third acquisition point. , , and This represents the coefficients to be determined in the X direction after the solution is obtained. , , and This represents the coefficient to be determined in the Y direction after the solution is obtained.

[0065] When the target area is a curve fitting advantage zone, the plane rectangular coordinates of the alarm point are transformed into latitude and longitude coordinates, and the latitude and longitude coordinates of the alarm point when the target area is a curve fitting advantage zone can be obtained.

[0066] Further, in one embodiment, the target region is the transition mixing region, and step S40 includes: Based on the rate of change of fiber curvature and the degree of terrain undulation, the initial weights of linear interpolation and curve fitting are dynamically adjusted to obtain the adjusted linear interpolation weights and adjusted curve fitting weights. Obtain the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area, and the second latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; Based on the adjusted linear interpolation weights, the adjusted curve fitting weights, the first latitude and longitude coordinates, and the second latitude and longitude coordinates, the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone are calculated using a preset formula. The preset formula is as follows:

[0067] In the formula, This indicates the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone. This represents the adjusted linear interpolation weights. This represents the adjusted curve fitting weights. This indicates the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area. The second latitude and longitude coordinates of the alarm point indicate when the target area is the curve fitting advantage area.

[0068] In this embodiment, the initial weights for linear interpolation and curve fitting are first set. That is, at the beginning of the transition region, initial weights are set for linear interpolation and curve fitting respectively according to the specific values ​​of the judgment index. For example, if the rate of change of curvature just begins to exceed the threshold of the linear interpolation advantage zone, the linear interpolation weight can be set to 0.7 and the curve fitting weight can be set to 0.3.

[0069] Then, the weights are dynamically adjusted: as the fiber optic shape and environmental factors change, the initial weights of linear interpolation and curve fitting are dynamically adjusted to obtain the adjusted linear interpolation weights and adjusted curve fitting weights. For example, when the rate of change of fiber curvature continues to increase or the terrain undulations become more pronounced, the weight of linear interpolation is gradually reduced while the weight of curve fitting is increased. The adjustment range can be determined based on the rate of change of factors such as curvature change and terrain undulations to better adapt to different transition situations.

[0070] After determining the weights of linear interpolation and curve fitting, the first latitude and longitude coordinates of the alarm point when the target area is a curve fitting advantage area and the second latitude and longitude coordinates of the alarm point when the target area is a curve fitting advantage area are fused to obtain the latitude and longitude coordinates of the alarm point when the target area is the transitional mixed area.

[0071] Specifically, the adjusted linear interpolation weights, the adjusted curve fitting weights, the first latitude and longitude coordinates of the alarm point when the target region is a curve fitting advantage area, and the second latitude and longitude coordinates of the alarm point when the target region is a curve fitting advantage area are substituted into the preset formula. This allows us to calculate the latitude and longitude coordinates of the alarm point when the target area is a transitional mixed zone.

[0072] In the formula, This indicates the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone. This represents the adjusted linear interpolation weights. This represents the adjusted curve fitting weights. , This indicates the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area. The second latitude and longitude coordinates of the alarm point indicate when the target area is the curve fitting advantage area.

[0073] Furthermore, after determining the latitude and longitude coordinates of the alarm point, it is also necessary to periodically (e.g., every two weeks or every month, depending on the sensitivity of the application scenario) re-collect the geographic information of key areas or changing road sections to ensure that the entire system is always closely synchronized with the actual dynamic changes of the fiber optic line, and continuously improve the accuracy and reliability of alarm location.

[0074] In this embodiment, an original large dataset is constructed based on environmental information data from distributed optical fiber lines. Based on this original large dataset, linear interpolation dominance regions, curve fitting dominance regions, and transitional mixed regions are determined using clustering and classification algorithms, convolutional neural networks, and long short-term memory networks. A target region is determined from these regions based on the location of the alarm point. The latitude and longitude coordinates of the alarm point are determined based on the strategy corresponding to the target region. This embodiment, by combining the GIS coordinates and relative position information of the communication optical cable, achieves precise alarm location. Compared to the traditional coarse location method based on defense zone division, this application can pinpoint specific latitude and longitude coordinates, greatly improving location accuracy. This precise location capability allows maintenance personnel to quickly locate alarm points, reducing troubleshooting time and improving alarm handling efficiency. It solves the technical problems of low accuracy in locating optical fiber alarms and low alarm handling efficiency in existing technologies.

[0075] In this embodiment, by organically combining curve fitting and interpolation, high-precision coordinate transformation can be achieved under both complex and simple terrains, enabling accurate mapping of distributed fiber optic alarms to latitude and longitude coordinates on GIS maps. Based on the adaptive selection method of fiber optic routing and terrain, simple and fast linear interpolation is used in the linear interpolation advantage area to ensure real-time performance while maintaining a certain level of accuracy. Although the curve fitting advantage area is computationally complex, it accurately handles complex situations, balancing computational resources and efficiency requirements overall. It can be widely applied in many fields such as smart grids, oil and gas pipelines, rail transit, and security monitoring that rely on distributed fiber optic sensing technology for line monitoring and need to be combined with geographic information, demonstrating significant practical value and broad market prospects.

[0076] Based on the same inventive concept, embodiments of this application also provide a device for calculating latitude and longitude coordinates based on alarm location.

[0077] In one embodiment, reference is made to Figure 2 , Figure 2 This is a functional module diagram of an embodiment of the apparatus for calculating latitude and longitude coordinates based on alarm location according to this application. Figure 2 As shown, the device for calculating latitude and longitude coordinates based on alarm location includes: Data acquisition module 10 is configured to construct a raw large dataset based on environmental information data from distributed optical fiber lines; The region segmentation module 20 is configured to determine linear interpolation advantage regions, curve fitting advantage regions, and transitional mixed regions based on the original large dataset by using clustering and classification algorithms, convolutional neural networks, and long short-term memory networks. The target region determination module 30 is configured to determine a target region from the linear interpolation advantage region, the curve fitting advantage region, and the transition mixing region based on the location of the alarm point; The latitude and longitude coordinate determination module 40 is configured to determine the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target area.

[0078] Optionally, in one embodiment, the linear interpolation advantage region is a region within a certain length window where the rate of change of fiber curvature is lower than a first preset value and the terrain undulation is gentle. The curve fitting advantage region is the area where the fiber curvature change rate is higher than the second preset value and the terrain is complex and varied within the corresponding length range. The transitional mixing region is a region that lies between the linear interpolation advantage region and the curve fitting advantage region, and has both linear and nonlinear characteristics.

[0079] Optionally, in one embodiment, the target region determination module 30 is configured to: Select the fiber segment where the alarm point is located in the initial big data fiber segment dataset; The target region is determined from the linear interpolation advantage region, the curve fitting advantage region, and the transitional mixing region based on the morphological pattern of the fiber segment.

[0080] Optionally, in one embodiment, the target region is the linear interpolation advantage region, and the latitude and longitude coordinate determination module 40 is configured to: Obtain the first and second collection points adjacent to the alarm point from the original big data set; The latitude and longitude coordinates of the first acquisition point and the latitude and longitude coordinates of the second acquisition point are transformed to obtain the plane rectangular coordinates of the first acquisition point and the second acquisition point; Based on the plane rectangular coordinates of the first and second acquisition points, the plane rectangular coordinates of the alarm point when the target area is the linear interpolation advantage area are calculated using the latitude and longitude coordinate calculation formula; The Cartesian coordinates of the alarm point when the target area is the linear interpolation dominance area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the linear interpolation dominance area; The formula for calculating the latitude and longitude coordinates is as follows:

[0081] In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the linear interpolation dominance region. Represents the Cartesian coordinates of the first data collection point. This represents the Cartesian coordinates of the second acquisition point. This represents the correction factor for environmental data in the X direction. This represents the correction factor for environmental data in the Y direction, and L represents the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the first optical fiber corresponding to the first acquisition point; This indicates the relative length of the second optical fiber corresponding to the second acquisition point.

[0082] Optionally, in one embodiment, the target region is the curve fitting advantage region, and the latitude and longitude coordinate determination module 40 is configured to: Several collection points within a preset range of the alarm points are obtained from the original big data set, and are denoted as follows: ,in, This represents the i-th data collection point. This represents the relative length of the optical fiber corresponding to the i-th acquisition point among the plurality of acquisition points. This represents the longitude coordinates of the i-th collection point among the plurality of collection points. This represents the latitude coordinates of the i-th collection point among the plurality of collection points. This represents the elevation of the i-th data collection point. This represents the direction angle of the i-th acquisition point. This represents the pitch angle of the i-th data acquisition point; Based on the aforementioned collection points, a piecewise cubic Hermite interpolation method is used for positioning to obtain a third and fourth collection points adjacent to the alarm point, wherein the cumulative distance of the alarm point falls within the range of the cumulative distance of the third and fourth collection points. Based on the third and fourth acquisition points, a polynomial function is constructed using high-order curve fitting techniques with Hermite interpolation. Based on the first cumulative distance between the third acquisition point and the third acquisition point, the second cumulative distance between the fourth acquisition point and the third acquisition point, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance, the coefficients to be determined in the polynomial function are solved to obtain the solved coefficients to be determined. Based on the solved coefficients and the polynomial function, the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region are calculated. The Cartesian coordinates of the alarm point when the target area is the curve fitting advantage area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; The polynomial function is as follows:

[0083] In the formula, This represents the cumulative distance from any target point to the third acquisition point within the segment of the fitted curve between the third and fourth acquisition points. L represents the relative length of the optical fiber corresponding to the target point. This indicates the relative length of the optical fiber corresponding to the third acquisition point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. Represents a polynomial function in the X direction. Represents a polynomial function in the Y direction.

[0084] Optionally, in one embodiment, the target region is the curve fitting advantage region, and the latitude and longitude coordinate determination module 40 is configured to: Substituting the first cumulative distance from the third acquisition point to the third acquisition point and the first derivative of the first cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the first system of equations, wherein the first system of equations is as follows:

[0085] In the formula, Indicates the first cumulative distance The corresponding polynomial function in the X direction, Indicates the longitude coordinates of the third data collection point. Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the third data collection point. Indicates the direction angle of the third acquisition point. Indicates the elevation angle of the third acquisition point; Indicates the first cumulative distance The corresponding polynomial function in the Y direction, Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the third data collection point. The derivative representing the latitude coordinates of the third data collection point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. The first derivative represents the first cumulative distance in the X direction. The first derivative represents the first cumulative distance in the Y direction; Substituting the second cumulative distance from the fourth acquisition point to the third acquisition point and the second derivative of the second cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the second system of equations, which is as follows:

[0086] In the formula, Indicates the second cumulative distance The corresponding polynomial function in the X direction, This indicates the longitude coordinates of the fourth data collection point. Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the fourth data collection point. Indicates the direction angle of the fourth acquisition point. Indicates the elevation angle of the fourth acquisition point; Indicates the second cumulative distance The corresponding polynomial function in the Y direction, Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the fourth data collection point. The derivative of the latitude coordinates of the fourth data collection point. The second derivative represents the second cumulative distance in the X direction. The second derivative represents the second cumulative distance in the Y direction; Based on the first set of equations and the second set of equations, the coefficients to be solved are obtained.

[0087] Optionally, in one embodiment, the target region is the curve fitting advantage region, and the latitude and longitude coordinate determination module 40 is configured to: Substitute the solved coefficients into the polynomial function to calculate the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. The calculation process is as follows:

[0088] In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. This represents the third cumulative distance from the alarm point to the third data collection point. , This indicates the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the optical fiber corresponding to the third acquisition point. , , and This represents the coefficients to be determined in the X direction after the solution is obtained. , , and This represents the coefficient to be determined in the Y direction after the solution is obtained.

[0089] Optionally, in one embodiment, the target area is the transitional mixing zone, and the latitude and longitude coordinate determination module 40 is configured to: Based on the rate of change of fiber curvature and the degree of terrain undulation, the initial weights of linear interpolation and curve fitting are dynamically adjusted to obtain the adjusted linear interpolation weights and adjusted curve fitting weights. Obtain the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area, and the second latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; Based on the adjusted linear interpolation weights, the adjusted curve fitting weights, the first latitude and longitude coordinates, and the second latitude and longitude coordinates, the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone are calculated using a preset formula. The preset formula is as follows:

[0090] In the formula, This indicates the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone. This represents the adjusted linear interpolation weights. This represents the adjusted curve fitting weights. This indicates the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area. The second latitude and longitude coordinates of the alarm point indicate when the target area is the curve fitting advantage area.

[0091] The functions of each module in the device for calculating latitude and longitude coordinates based on alarm location correspond to the steps in the method embodiment for calculating latitude and longitude coordinates based on alarm location. Their functions and implementation processes will not be described in detail here.

[0092] Based on the same inventive concept, embodiments of this application also provide an electronic device, the structure of which is as follows: Figure 3As shown, it includes: a memory and a processor, wherein the processor is used to read and execute the computer program stored in the memory to implement the aforementioned method for calculating latitude and longitude coordinates based on alarm location.

[0093] Based on the same inventive concept, this application also provides a computer storage medium storing computer-executable instructions, which, when executed, implement the aforementioned method for calculating latitude and longitude coordinates based on alarm location.

[0094] Finally, it should be noted that while some processes described in the embodiments of this application include multiple operations or steps that appear in a specific order, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0095] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for calculating latitude and longitude coordinates based on alarm location, characterized in that, The method includes: Based on environmental information data from distributed optical fiber lines, a raw large dataset is constructed. Based on the original large dataset, the linear interpolation advantage region, the curve fitting advantage region, and the transitional mixed region are determined by clustering and classification algorithms, convolutional neural networks, and long short-term memory networks. The target region is determined from the linear interpolation advantage region, the curve fitting advantage region, and the transition mixing region based on the location of the alarm point; Based on the strategy corresponding to the target area, the latitude and longitude coordinates of the alarm point are determined.

2. The method for calculating latitude and longitude coordinates based on alarm location according to claim 1, characterized in that, The linear interpolation advantage region is a region within a certain length window where the rate of change of fiber curvature is lower than a first preset value and the terrain undulation is gentle. The curve fitting advantage region is the area where the fiber curvature change rate is higher than the second preset value and the terrain is complex and varied within the corresponding length range. The transitional mixing region is a region that lies between the linear interpolation advantage region and the curve fitting advantage region, and has both linear and nonlinear characteristics.

3. The method for calculating latitude and longitude coordinates based on alarm location according to claim 1, characterized in that, The determination of the target region from the linear interpolation dominance region, the curve fitting dominance region, and the transitional mixing region based on the location of the alarm point includes: Select the fiber segment where the alarm point is located in the initial big data fiber segment dataset; The target region is determined from the linear interpolation advantage region, the curve fitting advantage region, and the transitional mixing region based on the morphological pattern of the fiber segment.

4. The method for calculating latitude and longitude coordinates based on alarm location according to claim 1, characterized in that, The target region is the linear interpolation advantage region, and determining the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target region includes: Obtain the first and second collection points adjacent to the alarm point from the original big data set; The latitude and longitude coordinates of the first acquisition point and the latitude and longitude coordinates of the second acquisition point are transformed to obtain the plane rectangular coordinates of the first acquisition point and the second acquisition point; Based on the plane rectangular coordinates of the first and second acquisition points, the plane rectangular coordinates of the alarm point when the target area is the linear interpolation advantage area are calculated using the latitude and longitude coordinate calculation formula; The Cartesian coordinates of the alarm point when the target area is the linear interpolation dominance area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the linear interpolation dominance area; The formula for calculating the latitude and longitude coordinates is as follows: In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the linear interpolation dominance region. Represents the Cartesian coordinates of the first data collection point. This represents the Cartesian coordinates of the second acquisition point. This represents the correction factor for environmental data in the X direction. This represents the correction factor for environmental data in the Y direction, and L represents the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the first optical fiber corresponding to the first acquisition point; This indicates the relative length of the second optical fiber corresponding to the second acquisition point.

5. The method for calculating latitude and longitude coordinates based on alarm location according to claim 1, characterized in that, The target region is the curve fitting advantage area, and the step of determining the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target region includes: Several collection points within a preset range of the alarm points are obtained from the original big data set, and are denoted as follows: ,in, This represents the i-th data collection point. This represents the relative length of the optical fiber corresponding to the i-th acquisition point among the plurality of acquisition points. This represents the longitude coordinates of the i-th collection point among the plurality of collection points. This represents the latitude coordinates of the i-th collection point among the plurality of collection points. This represents the elevation of the i-th data collection point. This represents the direction angle of the i-th sampling point. This represents the elevation angle of the i-th data acquisition point; Based on the aforementioned collection points, a piecewise cubic Hermite interpolation method is used for positioning to obtain a third and fourth collection points adjacent to the alarm point, wherein the cumulative distance of the alarm point falls within the range of the cumulative distance of the third and fourth collection points. Based on the third and fourth acquisition points, a polynomial function is constructed using high-order curve fitting techniques with Hermite interpolation. Based on the first cumulative distance between the third acquisition point and the third acquisition point, the second cumulative distance between the fourth acquisition point and the third acquisition point, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance, the coefficients to be determined in the polynomial function are solved to obtain the solved coefficients to be determined. Based on the solved coefficients and the polynomial function, the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region are calculated. The Cartesian coordinates of the alarm point when the target area is the curve fitting advantage area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; The polynomial function is as follows: In the formula, This represents the cumulative distance from any target point to the third acquisition point within the segment of the fitted curve between the third and fourth acquisition points. L represents the relative length of the optical fiber corresponding to the target point. This indicates the relative length of the optical fiber corresponding to the third acquisition point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. Represents a polynomial function in the X direction. Represents a polynomial function in the Y direction.

6. The method for calculating latitude and longitude coordinates based on alarm location according to claim 5, characterized in that, The process involves solving for the coefficients of the polynomial function based on the first cumulative distance between the third and fourth acquisition points, the second cumulative distance between the fourth and third acquisition points, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance, to obtain the solved coefficients. Substituting the first cumulative distance from the third acquisition point to the third acquisition point and the first derivative of the first cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the first system of equations, wherein the first system of equations is as follows: In the formula, Indicates the first cumulative distance The corresponding polynomial function in the X direction, Indicates the longitude coordinates of the third data collection point. Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the third data collection point. Indicates the direction angle of the third acquisition point. Indicates the elevation angle of the third acquisition point; Indicates the first cumulative distance The corresponding polynomial function in the Y direction, Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the third data collection point. The derivative representing the latitude coordinates of the third data collection point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. The first derivative represents the first cumulative distance in the X direction. The first derivative represents the first cumulative distance in the Y direction; Substituting the second cumulative distance from the fourth acquisition point to the third acquisition point and the second derivative of the second cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the second system of equations, which is as follows: In the formula, Indicates the second cumulative distance The corresponding polynomial function in the X direction, This indicates the longitude coordinates of the fourth data collection point. Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the fourth data collection point. Indicates the direction angle of the fourth acquisition point. Indicates the elevation angle of the fourth acquisition point; Indicates the second cumulative distance The corresponding polynomial function in the Y direction, Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the fourth data collection point. The derivative of the latitude coordinates of the fourth data collection point. The second derivative represents the second cumulative distance in the X direction. The second derivative represents the second cumulative distance in the Y direction; Based on the first set of equations and the second set of equations, the coefficients to be solved are obtained.

7. The method for calculating latitude and longitude coordinates based on alarm location according to claim 5, characterized in that, The calculation of the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region, based on the solved coefficients and the polynomial function, includes: Substitute the solved coefficients into the polynomial function to calculate the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. The calculation process is as follows: In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. This represents the third cumulative distance from the alarm point to the third data collection point. , This indicates the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the optical fiber corresponding to the third acquisition point. , , and This represents the coefficients to be determined in the X direction after the solution is obtained. , , and This represents the coefficient to be determined in the Y direction after the solution is obtained.

8. The method for calculating latitude and longitude coordinates based on alarm location according to any one of claims 1 to 7, characterized in that, The target area is the transitional mixing zone, and determining the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target area includes: Based on the rate of change of fiber curvature and the degree of terrain undulation, the initial weights of linear interpolation and curve fitting are dynamically adjusted to obtain the adjusted linear interpolation weights and adjusted curve fitting weights. Obtain the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area, and the second latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; Based on the adjusted linear interpolation weights, the adjusted curve fitting weights, the first latitude and longitude coordinates, and the second latitude and longitude coordinates, the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone are calculated using a preset formula. The preset formula is as follows: In the formula, This indicates the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone. This represents the adjusted linear interpolation weights. This represents the adjusted curve fitting weights. This indicates the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area. The second latitude and longitude coordinates of the alarm point indicate when the target area is the curve fitting advantage area.

9. A device for calculating latitude and longitude coordinates based on alarm location, characterized in that, The device includes: The data acquisition module is configured to construct a raw large dataset based on environmental information data from distributed fiber optic lines. The region segmentation module is configured to determine linear interpolation advantage regions, curve fitting advantage regions, and transitional mixed regions based on the original large dataset using clustering and classification algorithms, convolutional neural networks, and long short-term memory networks. The target region determination module is configured to determine a target region from the linear interpolation dominance region, the curve fitting dominance region, and the transitional mixing region based on the location of the alarm point; The latitude and longitude coordinate determination module is configured to determine the latitude and longitude coordinates of the alarm point based on the strategy corresponding to the target area.

10. The apparatus for calculating latitude and longitude coordinates based on alarm location according to claim 9, characterized in that, The target region is the linear interpolation advantage region, and the latitude and longitude coordinate determination module is specifically configured to: Obtain the first and second collection points adjacent to the alarm point from the original big data set; The latitude and longitude coordinates of the first acquisition point and the latitude and longitude coordinates of the second acquisition point are transformed to obtain the plane rectangular coordinates of the first acquisition point and the second acquisition point; Based on the plane rectangular coordinates of the first and second acquisition points, the plane rectangular coordinates of the alarm point when the target area is the linear interpolation advantage area are calculated using the latitude and longitude coordinate calculation formula; The Cartesian coordinates of the alarm point when the target area is the linear interpolation dominance area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the linear interpolation dominance area; The formula for calculating the latitude and longitude coordinates is as follows: In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the linear interpolation dominance region. Represents the Cartesian coordinates of the first data collection point. This represents the Cartesian coordinates of the second acquisition point. This represents the correction factor for environmental data in the X direction. This represents the correction factor for environmental data in the Y direction, and L represents the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the first optical fiber corresponding to the first acquisition point; This indicates the relative length of the second optical fiber corresponding to the second acquisition point.

11. The apparatus for calculating latitude and longitude coordinates based on alarm location according to claim 9, characterized in that, The target region is the curve fitting advantage area, and the latitude and longitude coordinate determination module is specifically configured to: Several collection points within a preset range of the alarm points are obtained from the original big data set, and are denoted as follows: ,in, This represents the i-th data collection point. This represents the relative length of the optical fiber corresponding to the i-th acquisition point among the plurality of acquisition points. This represents the longitude coordinates of the i-th collection point among the plurality of collection points. This represents the latitude coordinates of the i-th collection point among the plurality of collection points. This represents the elevation of the i-th data collection point. This represents the direction angle of the i-th sampling point. This represents the elevation angle of the i-th data acquisition point; Based on the aforementioned collection points, a piecewise cubic Hermite interpolation method is used for positioning to obtain a third and fourth collection points adjacent to the alarm point, wherein the cumulative distance of the alarm point falls within the range of the cumulative distance of the third and fourth collection points. Based on the third and fourth acquisition points, a polynomial function is constructed using high-order curve fitting techniques with Hermite interpolation. Based on the first cumulative distance between the third acquisition point and the third acquisition point, the second cumulative distance between the fourth acquisition point and the third acquisition point, the first derivative of the first cumulative distance, and the second derivative of the second cumulative distance, the coefficients to be determined in the polynomial function are solved to obtain the solved coefficients to be determined. Based on the solved coefficients and the polynomial function, the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region are calculated. The Cartesian coordinates of the alarm point when the target area is the curve fitting advantage area are transformed to obtain the latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area; The polynomial function is as follows: In the formula, This represents the cumulative distance from any target point to the third acquisition point within the segment of the fitted curve between the third and fourth acquisition points. L represents the relative length of the optical fiber corresponding to the target point. This indicates the relative length of the optical fiber corresponding to the third acquisition point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. Represents a polynomial function in the X direction. Represents a polynomial function in the Y direction.

12. The apparatus for calculating latitude and longitude coordinates based on alarm location according to claim 9, characterized in that, The target region is the curve fitting advantage area, and the latitude and longitude coordinate determination module is specifically configured to: Substituting the first cumulative distance from the third acquisition point to the third acquisition point and the first derivative of the first cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the first system of equations, wherein the first system of equations is as follows: In the formula, Indicates the first cumulative distance The corresponding polynomial function in the X direction, Indicates the longitude coordinates of the third data collection point. Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the third data collection point. Indicates the direction angle of the third acquisition point. Indicates the elevation angle of the third acquisition point; Indicates the first cumulative distance The corresponding polynomial function in the Y direction, Indicates the first cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the third data collection point. The derivative representing the latitude coordinates of the third data collection point; , , and This represents the coefficient to be determined in the X direction. , , and This represents the coefficient to be determined in the Y direction. The first derivative represents the first cumulative distance in the X direction. The first derivative represents the first cumulative distance in the Y direction; Substituting the second cumulative distance from the fourth acquisition point to the third acquisition point and the second derivative of the second cumulative distance into the polynomial function and the derivative function of the polynomial function, we obtain the second system of equations, which is as follows: In the formula, Indicates the second cumulative distance The corresponding polynomial function in the X direction, This indicates the longitude coordinates of the fourth data collection point. Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the X direction. The derivative of the longitude coordinates of the fourth data collection point. Indicates the direction angle of the fourth acquisition point. Indicates the elevation angle of the fourth acquisition point; Indicates the second cumulative distance The corresponding polynomial function in the Y direction, Indicates the second cumulative distance The derivative function of the corresponding polynomial function in the Y direction. This represents the latitude coordinates of the fourth data collection point. The derivative of the latitude coordinates of the fourth data collection point. The second derivative represents the second cumulative distance in the X direction. The second derivative represents the second cumulative distance in the Y direction; Based on the first set of equations and the second set of equations, the coefficients to be solved are obtained.

13. The apparatus for calculating latitude and longitude coordinates based on alarm location according to claim 9, characterized in that, The target region is the curve fitting advantage area, and the latitude and longitude coordinate determination module is specifically configured to: Substitute the solved coefficients into the polynomial function to calculate the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. The calculation process is as follows: In the formula, This represents the Cartesian coordinates of the alarm point when the target region is the curve fitting advantage region. This represents the third cumulative distance from the alarm point to the third data collection point. , This indicates the relative length of the optical fiber corresponding to the alarm point. This indicates the relative length of the optical fiber corresponding to the third acquisition point. , , and This represents the coefficients to be determined in the X direction after the solution is obtained. , , and This represents the coefficient to be determined in the Y direction after the solution is obtained.

14. The apparatus for calculating latitude and longitude coordinates based on alarm location according to claim 9, characterized in that, The target area is the transitional mixing zone, and the latitude and longitude coordinate determination module is specifically configured to: Based on the rate of change of fiber curvature and the degree of terrain undulation, the initial weights of linear interpolation and curve fitting are dynamically adjusted to obtain the adjusted linear interpolation weights and adjusted curve fitting weights. When the target region is the curve fitting advantage region, the first latitude and longitude coordinates of the alarm point are obtained, and the second latitude and longitude coordinates of the alarm point are obtained when the target region is the curve fitting advantage region; Based on the adjusted linear interpolation weights, the adjusted curve fitting weights, the first latitude and longitude coordinates, and the second latitude and longitude coordinates, the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone are calculated using a preset formula. The preset formula is as follows: In the formula, This indicates the latitude and longitude coordinates of the alarm point when the target area is the transitional mixing zone. This represents the adjusted linear interpolation weights. This represents the adjusted curve fitting weights. This indicates the first latitude and longitude coordinates of the alarm point when the target area is the curve fitting advantage area. The second latitude and longitude coordinates of the alarm point indicate when the target area is the curve fitting advantage area.

15. An electronic device, characterized in that, include: Memory, processor; The processor is configured to read and execute the computer program stored in the memory to implement the method for calculating latitude and longitude coordinates based on alarm location as described in any one of claims 1-8.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed, implement the method for calculating latitude and longitude coordinates based on alarm location as described in any one of claims 1-8.

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