Pipeline natural gas leakage concentration field reconstruction method and system

Abstract

The invention provides a pipeline natural gas leakage concentration field reconstruction method and system. The method comprises the following steps: converting a two-dimensional grayscale image of a leakage area of pipeline natural gas into a two-dimensional concentration projection image based on a concentration-grayscale mapping relation, calculating a leakage concentration value of a two-dimensional grid obtained by segmenting the two-dimensional concentration projection image, and then constructing a leakage concentration equation of the leakage area; and a gas three-dimensional concentration field of the leakage area is generated based on an algebraic iteration algorithm. Therefore, the reconstruction of the gas three-dimensional concentration field of the leakage area is realized through the acquired image of the leakage area, the defect that personnel enter a leakage site for detection is effectively avoided, the efficiency and safety of emergency rescue work after pipeline leakage are improved, the safety management after pipeline natural gas leakage events is greatly improved, and the safety of the pipeline is improved. Technical support is provided for rapid and effective emergency rescue after pipeline natural gas leakage.

Description

Technical Field

[0001] This application relates to the technical field of pipeline natural gas, and particularly to a method and system for reconstructing the leakage concentration field of pipeline natural gas. Background Art

[0002] With the rapid development of social economy, natural gas is increasingly becoming one of the most important energy sources for promoting industrial development. However, the distribution of natural gas resources is extremely uneven. Some regions have rich energy reserves, while other regions are relatively scarce.

[0003] Due to the uneven distribution of such resources, pipeline transportation plays a key role in maintaining the energy supply chain. This is mainly manifested in that in order to ensure the energy needs of industrial production and daily life in various regions, a large number of pipeline networks are built, and natural gas is transported from resource-rich regions to resource-scarce regions through pipeline transportation to ensure stable energy supply and meet the energy needs of different regions.

[0004] With the rapid development of society, fossil energy such as oil and natural gas has an increasingly greater impact on promoting industrial and economic development. The number and transportation volume of gas pipelines have been greatly increased. And natural gas is flammable and explosive. With the increase in high-pressure large-diameter pipelines, its danger is also increasing. Once a gas pipeline leaks, if it cannot be quickly and effectively emergently treated, it is very likely to cause damage to personnel, pipelines, the environment, buildings, etc. Summary of the Invention

[0005] The purpose of this application is to provide a method and system for reconstructing the leakage concentration field of pipeline natural gas to solve or alleviate the problems existing in the above-mentioned prior art.

[0006] To achieve the above purpose, this application provides the following technical solutions:

[0007] This application provides a method for reconstructing the leakage concentration field of pipeline natural gas, including: Step S101, based on the pre-calibrated concentration-gray scale mapping relationship, convert the two-dimensional gray scale image of the leakage area of the pipeline natural gas obtained into a two-dimensional concentration projection image, and calculate the leakage concentration values of the two-dimensional grids obtained by segmenting the two-dimensional concentration projection image; Step S102, construct the leakage concentration equation of the leakage area according to the leakage concentration values, and generate the three-dimensional gas concentration field of the leakage area based on the algebraic iteration algorithm.

[0008] Preferably, in step S101, the two-dimensional gray-scale image obtained by synchronously scanning the leakage area from two different preset orientations based on the mid-infrared camera is converted into the two-dimensional concentration projection image, and the two-dimensional concentration projection image is two-dimensionally segmented along the direction perpendicular to the light propagation direction of the mid-infrared camera, and the average concentration value in each two-dimensional grid obtained by the segmentation is calculated.

[0009] Preferably, the conversion of the two-dimensional gray-scale image obtained by synchronously scanning the leakage area from two different preset orientations based on the mid-infrared camera into the two-dimensional concentration projection image includes: calibrating the concentration-gray-scale mapping relationship between the gray scale of the captured image of the mid-infrared camera and the natural gas concentration; performing feature extraction on the two-dimensional gray-scale image based on Swin Transformer to separate the leakage gas cloud in the leakage area from the two-dimensional gray-scale image; and converting the two-dimensional gray-scale image into the two-dimensional concentration projection image based on the concentration-gray-scale mapping relationship according to the gray-scale value of the leakage gas cloud.

[0010] Preferably, in step S102, the propagation trajectory of the detection light emitted by the mid-infrared camera is simulated in the established three-dimensional space model of the pipeline natural gas, and according to the spatial coordinates of the three-dimensional grid cells discretized in the leakage area in the three-dimensional space model, the optical path length of each detection light passing through each three-dimensional grid cell is calculated; wherein, the planar projection of the three-dimensional grid cell is the two-dimensional grid obtained by segmenting the two-dimensional concentration projection image.

[0011] According to the total leakage concentration on the optical path of each detection light and the optical path length in the corresponding three-dimensional grid cell, a leakage concentration equation of the three-dimensional space model is established, and all the leakage concentration equations are solved based on the algebraic iterative algorithm to generate the three-dimensional gas concentration field of the leakage area; wherein, the total leakage concentration on the optical path of the i-th detection light emitted by the mid-infrared camera is the leakage concentration value of the corresponding two-dimensional grid, and i is a positive integer.

[0012] Preferably, the calculation of the optical path length of each detection light passing through each three-dimensional grid cell includes: simulating the propagation trajectory of the detection light emitted by the mid-infrared camera in the three-dimensional space model based on two different preset orientations, and according to the spatial coordinates of the three-dimensional grid cell, calculating the entry grid intersection point and the exit grid intersection point of each detection light with each three-dimensional grid cell, so as to obtain the optical path length of the corresponding detection light passing through each three-dimensional grid cell.

[0013] Preferably, according to the formula:

[0014]

[0015] Calculate the leakage concentration value in each of the three-dimensional grid cells of the three-dimensional space model to generate a three-dimensional gas concentration field of the leakage area; wherein, is the leakage concentration value in the j-th three-dimensional grid cell obtained by the k-th iteration; is the leakage concentration value in the j-th three-dimensional grid cell obtained by the (k + 1)-th iteration; A is the matrix of the optical path lengths corresponding to all the three-dimensional grid cells; A i is the matrix of the optical path lengths corresponding to the three-dimensional grid cells through which the i-th detection ray passes; O i represents the total leakage concentration on the optical path of the i-th detection ray; λ is the convergence factor, and j is a positive integer.

[0016] The embodiment of the present application further provides a pipeline natural gas leakage concentration field reconstruction system, including:

[0017] A data acquisition unit, configured to convert the obtained two-dimensional grayscale image of the leakage area of the pipeline natural gas into a two-dimensional concentration projection image based on a pre-calibrated concentration-gray scale mapping relationship, and calculate the leakage concentration value of the two-dimensional grid obtained by segmenting the two-dimensional concentration projection image;

[0018] A concentration reconstruction unit, configured to construct a leakage concentration equation of the leakage area according to the leakage concentration value, and generate a three-dimensional gas concentration field of the leakage area based on an algebraic iteration algorithm.

[0019] The embodiment of the present application further provides an electronic device, including: a memory, a processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory, so that the processor executes the above pipeline natural gas leakage concentration field reconstruction method.

[0020] The embodiment of the present application further provides a computer-readable storage medium, in which computer execution instructions are stored, and when the computer execution instructions are executed by a processor, they are used to implement the above pipeline natural gas leakage concentration field reconstruction method.

[0021] The embodiment of the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the above pipeline natural gas leakage concentration field reconstruction method.

[0022] Beneficial effects:

[0023] In a method and system for reconstructing the leakage concentration field of pipeline natural gas provided by an embodiment of the present application, based on a pre-calibrated concentration-gray scale mapping relationship, a two-dimensional gray scale image of the leakage area of the pipeline natural gas is converted into a two-dimensional concentration projection image, and the leakage concentration values of the two-dimensional grids obtained by segmenting the two-dimensional concentration projection image are calculated. Then, a leakage concentration equation for the leakage area is constructed, and a three-dimensional gas concentration field of the leakage area is generated based on an algebraic iterative algorithm. Thereby, the three-dimensional gas concentration field of the leakage area is reconstructed through the obtained image of the leakage area, effectively avoiding the deficiency of personnel entering the leakage site for detection, improving the efficiency and safety of the emergency rescue work after a leakage occurs in a high-pressure large-diameter pipeline, greatly improving the safety management after a pipeline natural gas leakage incident, and providing technical support for quickly and effectively carrying out emergency rescue after a pipeline natural gas leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The attached drawings forming a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation of this application. Among them:

[0025] Figure 1 It is a schematic flowchart of a method for reconstructing the leakage concentration field of pipeline natural gas provided by an embodiment of this application;

[0026] Figure 2 It is a schematic logical diagram of the method for reconstructing the leakage concentration field of pipeline natural gas provided by an embodiment of this application;

[0027] Figure 3 It is a schematic diagram of the segmentation and extraction of leakage concentration values of the two-dimensional concentration projection image corresponding to the two-dimensional gray scale image taken by the mid-infrared camera from directly above the leakage center at a height of 20 m provided by an embodiment of this application;

[0028] Figure 4 It is a schematic diagram of the segmentation and extraction of leakage concentration values of the two-dimensional concentration projection image corresponding to the two-dimensional gray scale image of the leakage area taken by the mid-infrared camera from 10 m directly in front of the leakage center and at a height of 10 m when pipeline natural gas leaks provided by an embodiment of this application;

[0029] Figure 5 It is a schematic diagram of ray tracing in a three-dimensional space model provided by an embodiment of this application;

[0030] Figure 6 It is a two-dimensional gray scale image of the leakage area taken by the mid-infrared camera from directly above the leakage center at a height of 20 m when pipeline natural gas leaks provided by an embodiment of this application;

[0031] Figure 7It is a two-dimensional grayscale image of the leakage area captured by a mid-infrared camera 10m in front of the leakage center and 10m in height when pipeline natural gas leaks provided by an embodiment of the present application;

[0032] Figure 8 It is Figure 6 the three-dimensional gas concentration field of the leakage area reconstructed when the pipeline natural gas leaks as shown;

[0033] Figure 9 It is a schematic structural diagram of a pipeline natural gas leakage concentration field reconstruction system provided by an embodiment of the present application. Specific embodiments

[0034] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments. Each example is provided by way of explanation of the present application rather than a limitation of the present application. In fact, those skilled in the art will clearly understand that modifications and variations can be made to the present application without departing from the scope or spirit of the present application. For example, features shown or described as part of one embodiment can be used in another embodiment to produce yet another embodiment. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the embodiments of the present invention shall fall within the scope of protection of the embodiments of the present invention.

[0035] In the high-pressure gas transmission pipeline of natural gas, it is extremely important to quickly and effectively carry out effective emergency treatment for the leakage of the gas transmission pipeline and quickly and accurately determine the concentration of the leaked gas. However, traditional detection methods require personnel to carry detection equipment into the leakage area to detect the leakage site, which not only has great danger but also low detection efficiency.

[0036] Based on this, the present application proposes a method for reconstructing the concentration field of pipeline natural gas leakage, using a drone carrying a mid-infrared camera to scan the leakage area and overcoming the problems of low algorithm accuracy and slow calculation speed in traditional reconstruction algorithms through a new three-dimensional concentration field reconstruction algorithm. Figure 1 It is a schematic flow diagram of a method for reconstructing the concentration field of pipeline natural gas leakage provided by an embodiment of the present application; Figure 2 It is a logical schematic diagram of a method for reconstructing the concentration field of pipeline natural gas leakage provided by an embodiment of the present application. As Figure 1 and Figure 2 shown, the method for reconstructing the concentration field of pipeline natural gas leakage includes:

[0037] Step S101: Based on the pre-calibrated concentration-gray scale mapping relationship, convert the two-dimensional grayscale image of the leakage area of the pipeline natural gas into a two-dimensional concentration projection image, and calculate the leakage concentration values of the two-dimensional grids obtained by segmenting the two-dimensional concentration projection image.

[0038] In this application, the mid-infrared camera mounted on the unmanned aerial vehicle (UAV) synchronously scans the leakage area of pipeline natural gas from two different perspectives to capture the infrared images of the leakage area. Specifically, the two-dimensional concentration image obtained by synchronously scanning the leakage area from two different preset azimuths based on the mid-infrared camera is converted into a two-dimensional concentration projection image. For example, taking the leakage point of pipeline natural gas as the reference system center, two UAVs equipped with mid-infrared cameras are used to synchronously scan the leakage area from positions 20 m directly above the leakage center, 10 m directly in front of the leakage center, and at a height of 10 m, respectively, to obtain the two-dimensional grayscale images of the leakage gas cloud in the above two directions. Figure 6 This is the two-dimensional grayscale image of the leakage area taken by the mid-infrared camera 20 m directly above the leakage center when pipeline natural gas leaks in the embodiment of this application; Figure 7 This is the two-dimensional grayscale image of the leakage area taken by the mid-infrared camera 10 m directly in front of the leakage center and at a height of 10 m when pipeline natural gas leaks in the embodiment of this application. Then, after performing preprocessing operations such as noise removal, boundary extraction, and quality enhancement on the obtained two-dimensional grayscale image, the two-dimensional grayscale image is segmented to separate leakage features such as the boundary and shape of the gas leakage area. Specifically, feature extraction is performed on the two-dimensional grayscale image based on Swin Transformer to separate the leakage gas cloud in the leakage area from the two-dimensional grayscale image, that is, semantic segmentation is performed on the two-dimensional grayscale image through Swin Transformer to extract the gas area from the complex background of the two-dimensional grayscale image to obtain a two-dimensional grayscale image containing only the leakage gas cloud; then, based on the mapping relationship between the grayscale value of the captured image of the mid-infrared camera and the natural gas concentration calibrated in the laboratory, the grayscale value of the leakage gas cloud in the leakage area separated from the two-dimensional grayscale image is converted into the corresponding concentration value to convert the two-dimensional grayscale image into a two-dimensional concentration projection image. Figure 3 This is a schematic diagram of the segmentation of the two-dimensional concentration projection image corresponding to the two-dimensional grayscale image taken by the mid-infrared camera 20 m directly above the leakage center and the extraction of the leakage concentration value in the embodiment of this application. Figure 4 This is a schematic diagram of the segmentation of the two-dimensional concentration projection image corresponding to the two-dimensional grayscale image of the leakage area taken by the mid-infrared camera 10 m directly in front of the leakage center and at a height of 10 m when pipeline natural gas leaks in this embodiment and the extraction of the leakage concentration value.

[0039] Specifically, first, in the laboratory, the grayscale of the captured image of the mid-infrared camera and the natural gas concentration are calibrated to obtain the concentration-gray scale mapping relationship between the grayscale value of the captured image of the mid-infrared camera and the natural gas concentration value; then, based on the concentration-gray scale mapping relationship between the grayscale value of the captured image and the natural gas concentration value, the grayscale value of the leakage gas cloud in the leakage area separated from the two-dimensional grayscale image is converted into the corresponding concentration value to realize the conversion of the two-dimensional grayscale image into a two-dimensional concentration projection image.

[0040] Next, perform two-dimensional segmentation on the two-dimensional concentration projection image along the direction perpendicular to the light propagation direction of the mid-infrared camera, and calculate the average concentration value within each two-dimensional grid obtained by the segmentation. By segmenting the two-dimensional concentration projection image, the two-dimensional concentration projection image is divided into multiple two-dimensional grids. Here, it is defined that the concentration within each two-dimensional grid is evenly distributed. Furthermore, calculate the average concentration value within each two-dimensional grid, that is, the leakage concentration value within each two-dimensional grid.

[0041] When calculating the average concentration value of each two-dimensional grid, extract the average gray value of each two-dimensional grid in the two-dimensional gray image through the gray extraction algorithm. Then, based on the concentration-gray mapping relationship between the captured image gray value of the mid-infrared camera and the natural gas concentration value, convert the average gray value of each two-dimensional grid into an average concentration value. Characterize the total concentration value of the corresponding detection light in the subsequent ray tracing through the average concentration value within each two-dimensional grid, laying a foundation for the reconstruction of the concentration field in the leakage area.

[0042] Step S102: Construct a leakage concentration equation for the leakage area based on the leakage concentration value, and generate a three-dimensional gas concentration field for the leakage area based on the algebraic iteration algorithm.

[0043] In this application, Figure 5 It is a schematic diagram of ray tracing within the three-dimensional space model provided by the embodiment of this application. Simulate the propagation of the detection light emitted by the mid-infrared camera within the leakage area through ray tracing, and simulate the propagation trajectory of the detection light emitted by the mid-infrared camera within the established three-dimensional space model of pipeline natural gas; and based on ray tracing, determine the optical path length of each detection light in the discrete three-dimensional grid cells by spatially discretizing the corresponding part of the leakage area within the three-dimensional space model. At the same time, combine the total concentration of each detection light (the average concentration value of each two-dimensional grid), establish a leakage concentration equation for the detection light, and on the basis of the leakage concentration equation, use the algebraic iteration algorithm for iterative solution to obtain the gas concentration value within each three-dimensional grid cell. Furthermore, realize the reconstruction of the leakage concentration field in the leakage area.

[0044] First, simulate the propagation trajectory of the detection light emitted by the mid-infrared camera within the established three-dimensional space model of pipeline natural gas, and calculate the optical path length of each detection light passing through each three-dimensional grid cell according to the spatial coordinates of the three-dimensional grid cells discretized from the leakage area in the three-dimensional space model. Here, it should be noted that the planar projection of the three-dimensional grid cell is the two-dimensional grid obtained by segmenting the two-dimensional concentration projection image.

[0045] Among them, when calculating the optical path length in each three-dimensional grid cell, according to the propagation trajectories of the simulated detection rays emitted by mid-infrared cameras in two different preset orientations in the three-dimensional space model and the spatial coordinates of the three-dimensional grid cell, the entry grid intersection points and exit grid intersection points of each detection ray and each three-dimensional grid cell are calculated, and the optical path length of each detection ray passing through each three-dimensional grid cell is obtained. That is to say, through the spatial coordinates of the three-dimensional grid cell, the intersection point coordinates where the detection ray enters the three-dimensional grid cell and the intersection point coordinates where the detection ray exits the three-dimensional grid cell are determined on the light ray propagation path. Furthermore, the distance between the intersection point coordinates where the detection ray enters the three-dimensional grid cell and the intersection point coordinates where the detection ray exits the three-dimensional grid cell is calculated, which is the optical path length of the detection ray in the corresponding three-dimensional grid cell.

[0046] Then, the average concentration value calculated in each two-dimensional grid is used as the leakage concentration within the optical path (the entire optical path) of the detection ray in the corresponding three-dimensional grid cell, and combined with the optical path length within the corresponding three-dimensional grid cell, a leakage concentration equation for the three-dimensional grid cell within the entire optical path of this detection ray is established. That is, according to the total leakage concentration on the optical path of each detection ray and the optical path length in the corresponding three-dimensional grid cell, a leakage concentration equation for the three-dimensional space model is established, as follows:

[0047] O i =∑L i , j *X j

[0048] In the formula, O i is the total leakage concentration on the optical path of the i-th detection ray emitted by the mid-infrared camera, that is, the leakage concentration value of the corresponding two-dimensional grid, L i , j is the optical path length of the i-th detection ray passing through the j-th three-dimensional grid cell, and X j is the leakage concentration value within the j-th three-dimensional grid cell.

[0049] Next, based on the algebraic iteration algorithm, all the leakage concentration equations are solved to generate the three-dimensional gas concentration field of the leakage area. Among them, according to the formula:

[0050]

[0051] The leakage concentration value within each three-dimensional grid cell of the three-dimensional space model is calculated to generate the three-dimensional gas concentration field of the leakage area. In the formula, is the leakage concentration value within the j-th three-dimensional grid cell obtained in the k-th iteration; is the leakage concentration value within the j-th three-dimensional grid cell obtained in the (k + 1)-th iteration; A is the matrix of the optical path lengths corresponding to all three-dimensional grid cells; A iis the matrix of the optical path lengths corresponding to the three-dimensional grid cells through which the i-th detected ray passes; O i represents the total leakage concentration on the optical path of the i-th detected ray; λ is the convergence factor, and j is a positive integer.

[0052] Thereby, based on ray tracing and the algebraic iteration algorithm, the reconstruction of the three-dimensional concentration field in the entire leakage area is realized, effectively solving the problem that the traditional method can only reconstruct the two-dimensional concentration field or reconstruct the concentration field in each segmented area after dividing the three-dimensional space and then superimposing them to form the three-dimensional concentration field of the leakage area. Not only is the boundary of the leakage gas cloud accurately depicted and the reconstruction error of the concentration field small, but also the calculation speed is fast and the algorithm structure is simple.

[0053] Meanwhile, the leakage area is scanned by an unmanned aerial vehicle carrying a mid-infrared camera to obtain an image of the leakage area, realizing the reconstruction of the three-dimensional gas concentration field of the leakage area. Figure 8 is the three-dimensional gas concentration field of the leakage area reconstructed and generated when the pipeline natural gas leaks provided by the embodiment of the present application. It effectively avoids the deficiency of personnel entering the leakage site for detection, not only improves the efficiency and safety of the emergency rescue work after the leakage of high-pressure large-diameter pipelines, greatly improves the safety management after the leakage of pipeline natural gas, and provides technical support for quickly and effectively carrying out emergency rescue after the leakage of pipeline natural gas; moreover, this method has migration and can be applied to the reconstruction of the concentration fields of various gas leaks, realizing unmanned detection with high safety, and providing an effective reference for the emergency rescue work of gas pipeline leaks.

[0054] Figure 9 A pipeline natural gas leakage concentration field reconstruction system provided by an embodiment of the present application, as Figure 9 shown, the system includes:

[0055] A data acquisition unit 901, configured to acquire a two-dimensional concentration projection image of the leakage area of pipeline natural gas and calculate the leakage concentration values of the two-dimensional grids obtained by segmenting the two-dimensional concentration projection image;

[0056] A concentration reconstruction unit 902, configured to construct a leakage concentration equation for the leakage area according to the leakage concentration values and generate a three-dimensional gas concentration field of the leakage area based on the algebraic iteration algorithm.

[0057] The pipeline natural gas leakage concentration field reconstruction system provided by the embodiment of the present application can implement the steps and processes of the pipeline natural gas leakage concentration field reconstruction method in any of the above embodiments and achieve the same technical effects, which will not be elaborated here one by one.

[0058] The electronic device provided by the embodiment of the present application includes: at least one processor and a memory. Optionally, the electronic device further includes a communication component. Among them, the processor, the memory, and the communication component are connected through a bus. In a specific implementation process, at least one processor executes the computer-executable instructions stored in the memory, so that at least one processor executes the above-mentioned method. For the specific implementation process of the processor, reference can be made to the above-mentioned method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here in this embodiment.

[0059] The embodiment of the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the above-mentioned method is implemented.

[0060] The embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the processor executes the computer-executable instructions, the above-mentioned method is implemented.

[0061] In the description of the present invention, the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0062] The above are only the preferred embodiments of the present application and are not used to limit the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for reconstructing the concentration field of pipeline natural gas leakage, characterized in that, Including: Step S101: Based on a pre-calibrated concentration-gray level mapping relationship, convert the two-dimensional gray level image of the leakage area of the pipeline natural gas into a two-dimensional concentration projection image, and calculate the leakage concentration value of the two-dimensional grid obtained by segmenting the two-dimensional concentration projection image; Step S102: Construct a leakage concentration equation for the leakage area according to the leakage concentration value, and generate a three-dimensional gas concentration field of the leakage area based on an algebraic iterative algorithm.

2. The method for reconstructing the pipeline natural gas leakage concentration field according to claim 1, characterized in that In step S101, Convert the two-dimensional gray level image obtained by synchronously scanning the leakage area from two different preset orientations based on a mid-infrared camera into the two-dimensional concentration projection image, and perform two-dimensional segmentation on the two-dimensional concentration projection image along the direction perpendicular to the light propagation direction of the mid-infrared camera, and calculate the leakage concentration value in each two-dimensional grid obtained by segmentation.

3. The method for reconstructing the pipeline natural gas leakage concentration field according to claim 2, wherein The conversion of the two-dimensional gray level image obtained by synchronously scanning the leakage area from two different preset orientations based on a mid-infrared camera into the two-dimensional concentration projection image includes: Calibrate the concentration-gray level mapping relationship between the gray level of the captured image of the mid-infrared camera and the natural gas concentration; Extract features from the two-dimensional gray level image based on Swin Transformer to separate the leakage gas cloud in the leakage area from the two-dimensional gray level image; According to the gray level value of the leakage gas cloud, convert the two-dimensional gray level image into the two-dimensional concentration projection image based on the concentration-gray level mapping relationship.

4. The method for reconstructing the pipeline natural gas leakage concentration field according to claim 1, wherein In step S102, Simulate the propagation trajectory of the detection light emitted by the mid-infrared camera in the established three-dimensional space model of the pipeline natural gas, and calculate the optical path length of each detection light passing through each three-dimensional grid unit according to the spatial coordinates of the three-dimensional grid units discretized in the leakage area in the three-dimensional space model; wherein, the planar projection of the three-dimensional grid unit is the two-dimensional grid obtained by segmenting the two-dimensional concentration projection image; Establish a leakage concentration equation for the three-dimensional space model according to the total leakage concentration on the optical path of each detection light and the optical path length in the corresponding three-dimensional grid unit, and solve all the leakage concentration equations based on an algebraic iterative algorithm to generate a three-dimensional gas concentration field of the leakage area; wherein, the total leakage concentration on the optical path of the i-th detection light emitted by the mid-infrared camera is the leakage concentration value of the corresponding two-dimensional grid, and i is a positive integer.

5. The method for reconstructing the leakage concentration field of pipeline natural gas according to claim 4, wherein, The calculation of the optical path length of each detection light passing through each three-dimensional grid unit includes: Simulate the propagation trajectory of the detection light emitted by the mid-infrared camera in the three-dimensional space model based on two different preset orientations, and calculate the entry grid intersection point and the exit grid intersection point of each detection light and each three-dimensional grid unit according to the spatial coordinates of the three-dimensional grid unit, so as to obtain the optical path length of each detection light passing through each three-dimensional grid unit.

6. The method for reconstructing the pipeline natural gas leakage concentration field according to claim 4, wherein According to the formula: Calculate the leakage concentration value in each three-dimensional grid unit of the three-dimensional space model to generate a three-dimensional gas concentration field of the leakage area; Among them, is the leakage concentration value in the j-th three-dimensional grid cell obtained in the k-th iteration; is the leakage concentration value in the j-th three-dimensional grid cell obtained in the (k + 1)-th iteration; A is the matrix of the optical path lengths corresponding to all the three-dimensional grid cells; A i is the matrix of the optical path lengths corresponding to the three-dimensional grid cells through which the i-th detection light ray passes; O i represents the total leakage concentration on the optical path of the i-th detection light ray; λ is the convergence factor, and j is a positive integer.

7. A pipeline natural gas leakage concentration field reconstruction system, characterized in that, Including: A data acquisition unit, configured to convert a two-dimensional grayscale image of a leakage area of the pipeline natural gas into a two-dimensional concentration projection image based on a pre-calibrated concentration-gray scale mapping relationship, and calculate leakage concentration values of two-dimensional grids obtained by segmenting the two-dimensional concentration projection image; A concentration reconstruction unit, configured to construct a leakage concentration equation of the leakage area according to the leakage concentration values, and generate a three-dimensional gas concentration field of the leakage area based on an algebraic iteration algorithm.

8. An electronic device, characterized in that, Comprising: A memory and a processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the pipeline natural gas leakage concentration field reconstruction method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Comprising a computer program, which when executed by a processor implements the method according to any one of claims 1 to 6.

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