Gas flow monitoring methods and systems for large cross-section channels

Abstract

This application relates to a gas flow monitoring method and system for large-section channels, belonging to the field of safety production monitoring technology. The method includes: acquiring wind speed and gas concentration monitoring values ​​at at least three monitoring points on the target cross-section of the channel in real time; determining the wind speed and gas concentration measured values ​​for each grid on the corresponding measurement surface of the cross-section using a preset spatial interpolation algorithm based on the wind speed and gas concentration measured values ​​and the spatial distribution of each monitoring point on the cross-section; calculating the gas flow rate value for the corresponding grid based on the wind speed and gas concentration measured values, and accumulating the calculation results to obtain the accumulated result as the gas flow rate monitoring value of the channel. The technical solution of this application can obtain more accurate gas flow rate monitoring data within the actual channel.

Description

Technical Field

[0001] This application belongs to the field of safety production monitoring technology, specifically relating to a gas flow monitoring method and system for large cross-section channels. Background Technology

[0002] In industrial and mining production scenarios such as thermal power generation and coal mining, it is necessary to use pipelines, ventilation shafts, and tunnels to transmit or discharge relevant gases, such as the exhaust air from coal mines. For production safety or environmental protection purposes, it is necessary to monitor the gas flow rate in these channels.

[0003] To monitor the flow rate of a target gas, wind speed sensors and concentration sensors for that type of gas are typically installed at the gas flow path. Flow rate monitoring data is then calculated based on wind speed and concentration data. In existing technologies, a single-point sensor is installed at a cross-section within the channel, and the flow rate of the target gas is calculated based on the single-point data to achieve the monitoring objective.

[0004] However, in industrial and mining production scenarios, the channels involved are generally large-section channels. Under actual working conditions, wind speed and concentration may be unevenly distributed across the channel cross-section. The monitoring data obtained by existing monitoring methods obviously have accuracy issues and cannot meet the monitoring needs of some monitoring scenarios.

[0005] Therefore, in scenarios involving monitoring gas flow in large cross-section channels, improving monitoring accuracy has become a pressing technical problem. Summary of the Invention

[0006] To overcome at least some of the problems existing in the related technologies, this application provides a gas flow monitoring method and system for large cross-section channels. It adopts multi-point monitoring to acquire basic data and obtains gas flow monitoring data with higher accuracy based on specific calculation implementation methods, so as to solve the technical problem of how to improve the monitoring accuracy in the monitoring scenario of gas flow in large cross-section channels.

[0007] To achieve the above objectives, this application adopts the following technical solution:

[0008] Firstly,

[0009] This application provides a method for monitoring gas flow in large cross-section channels, the method comprising:

[0010] Real-time acquisition of wind speed and gas concentration monitoring values ​​at at least three monitoring points on the target section of the channel;

[0011] Based on the wind speed monitoring value and gas concentration monitoring value, as well as the spatial distribution of each monitoring point on the cross section, a preset spatial interpolation algorithm is used to determine the wind speed measurement value and gas concentration measurement value of each grid on the measurement surface corresponding to the cross section.

[0012] The gas flow rate of the corresponding grid is calculated based on the wind speed and gas concentration measurements, and the calculation results are accumulated. The accumulated result is used as the gas flow rate monitoring value of the channel.

[0013] Optionally, the step of using a preset spatial interpolation algorithm to determine the wind speed and gas concentration measurements of each grid on the measurement surface corresponding to the cross-section includes the following processing steps for the first type of monitoring points for obtaining wind speed monitoring parameters and the second type of monitoring points for obtaining gas concentration monitoring parameters:

[0014] Using the position points corresponding to each monitoring point on the measurement surface as vertices, the measurement surface is triangulated to determine the triangular region enclosed by each vertex;

[0015] For each of the triangular regions, the monitoring values ​​of the monitoring points corresponding to each vertex of the corresponding region are used as the z-axis coordinate values. The two-dimensional coordinates of the corresponding vertices on the measurement surface are upgraded to obtain the three-dimensional coordinates of the vertices of the measurement projection area corresponding to each triangular region, and then the plane equation of the measurement projection area corresponding to each triangular region is determined.

[0016] For any of the aforementioned grids, the triangular region to which it belongs is determined based on the two-dimensional coordinates of the corresponding grid on the measurement surface, and the z-axis coordinate value of the corresponding measurement projection point of the grid is calculated based on the following expression.

[0017] F(x a0 y a0 , z a ) = 0

[0018] Where F represents the plane equation of the measured projection area corresponding to the triangular region to which the grid belongs, a represents the measured projection point corresponding to the grid, and x a0 This represents the x-axis coordinate value of the grid on the measurement surface, and the y-axis coordinate value... a0 This represents the y-axis coordinate value of the grid on the measurement surface, and the z-axis coordinate value. a This represents the z-axis coordinate value of the measured projection point corresponding to the grid.

[0019] The z-axis coordinates of the calculated projection points corresponding to each grid are used as the calculated values ​​of the monitoring parameters for the monitoring point type of the corresponding grid.

[0020] Optionally, the triangulation process can be performed using the Delaunay triangulation rule.

[0021] Optionally, the distribution locations of the first type of monitoring points and the second type of monitoring points on the target section of the channel overlap.

[0022] Optionally, the ratio of the total obstruction area of ​​the monitoring sensing device corresponding to each monitoring point on the target cross section of the channel to the area of ​​the target cross section of the channel is less than or equal to a preset value.

[0023] Optionally, the distribution of each monitoring point on the target cross section of the channel is selected and determined based on the distribution of sensing measurements on the actual cross section.

[0024] Secondly,

[0025] This application provides a gas flow monitoring system for large cross-section channels, the system comprising:

[0026] At least three wind speed sensors and at least three gas concentration sensors are arranged at preset monitoring points on the target section of the channel to perform real-time sensing of the corresponding monitoring points.

[0027] The monitoring host is used to determine the wind speed and gas concentration values ​​of each grid on the measurement surface corresponding to the cross-section based on the real-time data sensed by each sensor and the spatial distribution of each monitoring point on the cross-section, using a preset spatial interpolation algorithm.

[0028] And to calculate the gas flow rate value of the corresponding grid based on the wind speed measurement value and the gas concentration measurement value respectively, and to accumulate the calculation results, using the accumulated result as the gas flow rate monitoring value of the channel.

[0029] Optionally, it also includes,

[0030] The first processing device is used to aggregate and upload the first data sensed by each of the wind speed sensors;

[0031] The second processing device is used to summarize and upload the second data sensed by each of the gas concentration sensors;

[0032] A communication relay device is used to perform communication relay processing on the received first data and second data, and to transmit the processed third data to the monitoring host;

[0033] Power supply equipment, used to provide power for system operation;

[0034] The monitoring host is further configured to parse the third data to obtain the real-time wind speed monitoring value and the real-time gas concentration monitoring value corresponding to the monitoring point.

[0035] Optionally, the monitoring host is further configured to display and output the gas flow monitoring value, the real-time wind speed monitoring value and the real-time gas concentration monitoring value at the corresponding monitoring point, and the wind speed measurement value and gas concentration measurement value of each grid on the measurement surface.

[0036] Optionally, the gas concentration sensor is a laser methane sensor; the wind speed sensor is installed on the target section of the channel in the form of a probe.

[0037] The application employs the above technical solution and has at least the following beneficial effects:

[0038] The gas flow monitoring method for large-section channels in this application includes real-time acquisition of wind speed and gas concentration monitoring values ​​at at least three monitoring points on the target cross-section of the channel; based on the wind speed and gas concentration monitoring values, and the spatial distribution of each monitoring point on the cross-section, a preset spatial interpolation algorithm is used to determine the wind speed and gas concentration calculation values ​​of each grid on the corresponding measurement surface of the cross-section; the gas flow value of the corresponding grid is calculated based on the wind speed and gas concentration calculation values, and the calculation results are accumulated, with the accumulated result used as the gas flow monitoring value of the channel. In this technical solution, multi-point monitoring is performed on the channel cross-section, and the gas flow values ​​of each grid on the corresponding measurement surface are calculated and accumulated based on the spatial interpolation algorithm to obtain the gas flow monitoring value of the channel cross-section. This method of monitoring cross-sectional gas flow based on multi-point wind speed and concentration monitoring data on the cross-section better reflects the uneven distribution of wind speed and concentration on the actual cross-section, and can obtain more accurate gas flow monitoring data within the actual channel.

[0039] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from an examination of the following, or may be learned from the practice of the invention. Attached Figure Description

[0040] The accompanying drawings are used to provide a further understanding of the technical solutions of this application or the prior art, and constitute a part of the specification. The drawings illustrating embodiments of this application, together with the embodiments of this application, are used to explain the technical solutions of this application, but do not constitute a limitation on the technical solutions of this application.

[0041] Figure 1 A schematic flowchart of a gas flow monitoring method for a large cross-section channel provided in one embodiment of this application;

[0042] Figure 2 This is a schematic diagram illustrating the calculated values ​​corresponding to each grid cell of the measurement surface obtained in one embodiment of this application;

[0043] Figure 3 This is a schematic diagram illustrating the triangulation process in the spatial interpolation algorithm of one embodiment of this application;

[0044] Figure 4 This is a schematic diagram illustrating data dimensionality upscaling in a spatial interpolation algorithm in one embodiment of this application;

[0045] Figure 5 This is a schematic diagram of the system structure of a gas flow monitoring system for a large cross-section channel provided in one embodiment of this application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be described in detail below. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] As described in the background section, in industrial and mining production scenarios such as thermal power generation and coal mining, it is necessary to use pipelines, ventilation shafts, and tunnels to transmit or discharge relevant gases, such as the exhaust gas from coal mines. For production safety or environmental protection purposes, it is necessary to monitor the gas flow rate in these channels.

[0048] To monitor the flow rate of a target gas, wind speed sensors and concentration sensors for that type of gas are typically installed at the gas flow path. Flow rate monitoring data is then calculated based on wind speed and concentration data. In existing technologies, a single-point sensor is installed at a cross-section within the channel, and the flow rate of the target gas is calculated based on the single-point data to achieve the monitoring objective.

[0049] However, in industrial and mining production scenarios, the channels involved are generally large-section channels. Under actual working conditions, wind speed and concentration may be unevenly distributed across the channel cross-section. The monitoring data obtained by existing monitoring methods obviously have accuracy issues and cannot meet the monitoring needs of some monitoring scenarios.

[0050] To address this, this application proposes a gas flow monitoring method for large cross-section channels. In one embodiment, such as... Figure 1 As shown, the gas flow monitoring method includes:

[0051] Step S110: Real-time acquisition of wind speed monitoring values ​​and gas concentration monitoring values ​​at at least three monitoring points on the target section of the channel;

[0052] For example, the channel here is the exhaust ventilation shaft of a coal mine. In fact, it is necessary to monitor the methane gas flow rate of the exhaust ventilation shaft. In this step, according to the actual monitoring needs, a section of the exhaust ventilation shaft can be determined as the target section. Multiple wind speed sensors and methane concentration sensors are installed on the target section (it is easy to understand that the actual sampling point on the section after the sensor is installed is the monitoring point) to obtain the wind speed monitoring value and the methane (gas) concentration monitoring value in real time.

[0053] Step S120: Based on the wind speed monitoring value and gas concentration monitoring value obtained in step S110, and the distribution of each monitoring point on the target section of the channel, a preset spatial interpolation method is used to determine the wind speed measurement value and gas concentration measurement value of each grid on the measurement surface corresponding to the target section of the channel.

[0054] It should be noted that spatial interpolation is a data processing method used in Geographic Information Systems (GIS) for geospatial data modeling. In the application scenario of this application, the applicant's research found that the parameters to be measured at each point on the channel cross-section are correlated with their location. Therefore, the channel cross-section can be used as the study area, and based on spatial interpolation, monitoring data from discrete points within the area can be used to estimate and determine the wind speed and concentration parameters corresponding to each point on the cross-section, thereby obtaining the required wind speed and gas concentration values. For example, such as... Figure 2 The diagram shown illustrates how the measured values ​​of each grid on the measurement surface are obtained in an implementation scenario.

[0055] After step S120, proceed to step S130, calculate the gas flow rate value of the corresponding grid based on the wind speed measurement value and the gas concentration measurement value, and accumulate the calculation results, using the accumulated result as the gas flow rate monitoring value of the channel.

[0056] It's easy to understand that in this step, the gas flow rate value of the grid = the wind speed measurement value of the grid * the grid area * the gas concentration measurement value of the grid. The gas flow rate values ​​of each grid are then summed to obtain the gas flow rate monitoring value of the channel. For example, in a specific implementation scenario, the cross-section width * length is 2.7m * 2.1m. The corresponding measurement surface is divided into grids of 10cm, resulting in 270 * 210 grids. It's also easy to understand that in actual implementation, based on scenario requirements and with sufficient computing power, the grid of the cross-section can be further refined to improve the overall monitoring accuracy through smaller grids.

[0057] In this technical solution, multi-point monitoring is performed on the channel cross-section, and the gas flow rate values ​​of each grid on the corresponding measurement surface are calculated and accumulated based on the spatial interpolation algorithm to obtain the gas flow rate monitoring value of the channel cross-section. This method of monitoring the gas flow rate of the cross-section based on the wind speed and concentration monitoring data of multiple points on the cross-section is more in line with the uneven distribution of wind speed and concentration on the actual cross-section, and can obtain the actual gas flow rate monitoring data in the channel more accurately.

[0058] Furthermore, in some specific implementation scenarios, in order to better achieve the accuracy of the measurement, the distribution of each monitoring point on the target cross section of the channel can be selected and determined based on the distribution of the sensing measurements on the actual cross section.

[0059] For example, if the channel is a gas emission channel and the exhaust fan is an axial flow fan in practice, the wind speed distribution on the channel cross-section is relatively uniform, and the monitoring points of the wind speed sensor can be evenly set on the cross-section. However, if the exhaust fan is a centrifugal fan in practice, the wind speed distribution on the cross-section is generally uneven. Monitoring points can be set at the inflection point of wind speed change on the cross-section (in practice, the calculation method proposed in this application can be used for trial calculation, and the inflection point position in the specific scenario can be gradually determined based on the results).

[0060] Furthermore, it should be noted that in general spatial interpolation applications, such as geospatial data modeling, more and denser data sampling points are usually set to achieve modeling accuracy. However, in this application, the channel itself is used to pass gas, and in some scenarios, it is necessary to ensure gas flow performance.

[0061] Based on this, in some specific implementation scenarios, the ratio of the total occlusion area of ​​the monitoring sensor device corresponding to each monitoring point on the target cross section of the channel to the area of ​​the target cross section of the channel is less than or equal to a preset value (for example, in the scenario of exhaust ventilation in a coal mine, the preset value is 15%, that is, the occlusion rate must be less than 15%). In other words, in specific actual scenarios, too many monitoring points cannot be set up, and the occlusion rate requirement must be met.

[0062] To facilitate understanding of the technical solution of this application, the principle of the spatial interpolation algorithm used in the technical solution of this application will be introduced and explained below.

[0063] Specifically, in one embodiment, this application employs a preset spatial interpolation algorithm to determine the wind speed and gas concentration calculation values ​​of each grid on the measurement surface corresponding to the cross-section (the measurement surface is a virtual two-dimensional plane region determined based on the measured cross-section boundary conditions and other data after measuring the actual cross-section). This includes the following processing steps for the first type of monitoring points acquiring wind speed monitoring parameters and the second type of monitoring points acquiring gas concentration monitoring parameters:

[0064] Using the positions of each monitoring point on the measurement surface as vertices, the measurement surface is triangulated to determine the triangular regions enclosed by each vertex. In practice, the Delaunay triangulation rule can be used for triangulation (the Delaunay triangulation rule can be found in relevant publicly available technical documents, which will not be detailed here), thereby ensuring the uniqueness and certainty of the triangulation results. For example, such as... Figure 3 The figure shows a schematic diagram of the triangulation results of one embodiment, with 9 "monitoring points" in the figure.

[0065] Once the triangular regions are determined, the monitoring values ​​of the monitoring points corresponding to the vertices of each triangular region can be used as the z-axis coordinates to upgrade the two-dimensional coordinates of the corresponding vertices on the measurement surface, thereby constructing the three-dimensional coordinates of the vertices of the measurement projection regions corresponding to each triangular region, and then determining the plane equation of the measurement projection regions corresponding to each triangular region.

[0066] like Figure 4 As shown, this is a schematic diagram illustrating data dimensionality upgrade. The plane containing the xy coordinate system in the figure is the measurement surface. The position of the base of each square column legend represents the vertex position (x0, y0), and the height of the square column legend represents the monitoring value z0 of the monitoring point corresponding to the vertex. Since three points in space can determine a plane, the three vertices of each triangular region, after data dimensionality upgrade, can also form a triangular face (referred to as the measurement projection area in this application) with the corresponding three three-dimensional coordinates. These three points are obviously the vertices of this triangular face.

[0067] Therefore, for any given grid, its triangular region can be determined based on its two-dimensional coordinates on the measurement surface (in practice, the grid is a square, and the coordinates of the center point of the square can be used as the grid's coordinates), and the z-axis coordinate value of the corresponding measurement projection point of the grid can be calculated based on the following expression.

[0068] F(x a0 y a0 , z a )=0 (1)

[0069] In expression (1), F represents the plane equation of the measured projection area corresponding to the triangular region to which the grid belongs, a represents the measured projection point corresponding to the grid, and x a0 This represents the x-axis coordinate value of the grid on the measurement surface (this value is the same as the x-axis coordinate value of the corresponding measured projection point of the grid), y a0 This represents the y-axis coordinate value of the grid on the measurement surface (this value is the same as the y-axis coordinate value of the corresponding measured projection point of the grid), z a This represents the z-axis coordinate value of the measured projection point corresponding to the grid.

[0070] The z-axis coordinates of the calculated projection points corresponding to each grid are used as the calculated values ​​of the monitoring parameters for the monitoring point type of the corresponding grid.

[0071] The spatial interpolation algorithm described above in this application is based on the assumption that wind speed and concentration change linearly in the cross-sectional direction. The monitoring parameter information of each point on the surface can be represented by (x, y, z), thereby using a three-dimensional method to solve two-dimensional problems in practical engineering.

[0072] It should also be noted that, since the actual channel cross-section has a variety of shapes, the corresponding measurement surface also has a variety of shapes. In the process of triangulation described above, by adding auxiliary points (also as vertices), the overall region formed by each triangular region after triangulation can be approximated to any cross-sectional shape.

[0073] Correspondingly, if auxiliary points are used as vertices during the actual triangulation of the measurement surface, and the data dimensionality is increased, since these "vertices" do not correspond to actual monitoring values, the z-values ​​of the auxiliary points can be directly assigned. For example, the assignment can be the average value of the solution of the region enclosed by the known points (i.e., determining the plane defined by the three known points around the point, and averaging the z-values ​​of the points in the plane; in the specific implementation, the measurement method proposed in this application needs to be used to perform real-time measurement based on this requirement to obtain the value). Of course, other assignment methods can also be used, such as taking the z-value of the nearest known (vertices) point, or performing linear interpolation based on the relationship of nearby known points.

[0074] In the technical solution of this application, there are two types of monitoring points for obtaining wind speed monitoring parameters and two types of monitoring points for obtaining gas concentration monitoring parameters. As mentioned above, in the implementation principle of the spatial interpolation algorithm, these two types of monitoring points need to be solved separately.

[0075] Based on this, as a preferred option, in order to improve the solution speed, in the actual implementation of the scheme, the first type of monitoring points and the second type of monitoring points can be arranged in the same way. Even if the distribution positions of the first type of monitoring points and the second type of monitoring points on the target section of the channel overlap, the triangulation results in the algorithm implementation will be consistent. In the implementation of the solution program, related calculation and judgment steps (such as the judgment of which triangular region the grid is in) can be saved.

[0076] Furthermore, this implementation method, while meeting the occlusion rate requirements, allows for the setting of more monitoring points, resulting in more refined interpolation results and further improving the accuracy of gas flow monitoring data.

[0077] In one embodiment, such as Figure 5 As shown, this application also proposes a gas flow monitoring system for large cross-section channels, the system comprising:

[0078] At least three wind speed sensors and at least three gas concentration sensors are used, each positioned at a pre-set monitoring point on the target cross-section of the channel, for real-time sensing of the corresponding monitoring point. Specifically, for example... Figure 5 As shown, the channel here is a ventilation shaft, the gas concentration sensor is a laser methane sensor, and the wind speed sensor is installed on the target section of the channel in the form of a probe.

[0079] The system also includes a monitoring host, which, based on real-time data from each sensor and the spatial distribution of each monitoring point on the cross-section, uses a preset spatial interpolation algorithm to determine the wind speed and gas concentration values ​​for each grid on the corresponding measurement surface of the cross-section.

[0080] It is used to calculate the gas flow rate of the corresponding grid based on the wind speed and gas concentration, and to accumulate the calculation results, using the accumulated result as the gas flow rate monitoring value of the channel.

[0081] Furthermore, considering the actual field environment, the system also includes,

[0082] First processing equipment (such as) Figure 5 The distributed flow field host in the system is used to aggregate and upload the first data sensed by each wind speed sensor.

[0083] Second processing equipment (such as) Figure 5 The distributed laser methane generator (in the system) is used to aggregate and upload the second data sensed by each gas concentration sensor;

[0084] Communication relay equipment (such as) Figure 5 The distributed signal converter and Ethernet switch in the system are used to perform communication relay processing on the received first and second data, and transmit the processed third data to the monitoring host.

[0085] Power supply equipment (such as) Figure 5 (Power supply diagram in the image), used to provide power for system operation;

[0086] In this scenario, the monitoring host is also configured to parse and process the third-party data (such as communication unpacking), and obtain the real-time wind speed monitoring value and real-time gas concentration monitoring value corresponding to the monitoring point.

[0087] Regarding the monitoring host in the above embodiments, the specific way in which it processes and executes the relevant algorithms has been described in detail in the embodiments related to the method, and will not be elaborated here.

[0088] Furthermore, based on the monitoring needs of specific scenarios, the monitoring host is also configured to display and output the gas flow monitoring value, the real-time wind speed monitoring value and the real-time gas concentration monitoring value of the corresponding monitoring point, as well as the wind speed measurement value and gas concentration measurement value of each grid on the measurement surface.

[0089] Visualizing relevant data in various forms is a well-known technique in the field, and this application will not elaborate on it.

[0090] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for monitoring gas flow rate in large cross-section channels, characterized in that, The large-section channel is a channel for gas transmission or emission, and the gas flow monitoring method includes: The wind speed and gas concentration monitoring values ​​of at least three monitoring points on the target section of the channel are acquired in real time. The ratio of the total occlusion area of ​​the monitoring sensor corresponding to each monitoring point on the target section of the channel to the area of ​​the target section of the channel is less than or equal to a preset value. Based on the wind speed monitoring value and gas concentration monitoring value, as well as the spatial distribution of each monitoring point on the cross section, a preset spatial interpolation algorithm is used to determine the wind speed measurement value and gas concentration measurement value of each grid on the measurement surface corresponding to the cross section. The gas flow rate of the corresponding grid is calculated based on the wind speed and gas concentration, and the calculation results are accumulated. The accumulated result is used as the gas flow rate monitoring value of the channel. The step of using a preset spatial interpolation algorithm to determine the wind speed and gas concentration measurements of each grid on the measurement surface corresponding to the cross-section includes obtaining a first type of monitoring points for wind speed monitoring parameters and a second type of monitoring points for gas concentration monitoring parameters. The first and second types of monitoring points are processed using the following steps respectively: The position points corresponding to each monitoring point on the measurement surface are used as vertices. The measurement surface is triangulated to determine the triangular region enclosed by each vertex. For each of the triangular regions, the monitoring values ​​of the monitoring points corresponding to each vertex of the corresponding region are used as the z-axis coordinate values. The two-dimensional coordinates of the corresponding vertices on the measurement surface are upgraded to obtain the three-dimensional coordinates of the vertices of the measurement projection area corresponding to each triangular region, and then the plane equation of the measurement projection area corresponding to each triangular region is determined. For any of the aforementioned grids, the triangular region to which it belongs is determined based on the two-dimensional coordinates of the corresponding grid on the measurement surface, and the z-axis coordinate value of the corresponding measurement projection point of the grid is calculated based on the following expression. F(x a0 ,y a0 ,z a )=0 Where F represents the plane equation of the measured projection area corresponding to the triangular region to which the grid belongs, a represents the measured projection point corresponding to the grid, and x a0 This represents the x-axis coordinate value of the grid on the measurement surface, and the y-axis coordinate value... a0 This represents the y-axis coordinate value of the grid on the measurement surface, and the z-axis coordinate value. a This represents the z-axis coordinate value of the measured projection point corresponding to the grid. The z-axis coordinates of the calculated projection points corresponding to each grid are used as the calculated values ​​of the monitoring parameters for the type of monitoring point corresponding to the first or second type of monitoring point of the corresponding grid.

2. The gas flow monitoring method according to claim 1, characterized in that, The triangulation process is performed using the Delaunay triangulation rule.

3. The gas flow monitoring method according to claim 1, characterized in that, The distribution locations of the first type of monitoring points and the second type of monitoring points on the target section of the channel overlap.

4. The gas flow monitoring method according to claim 1, characterized in that, The distribution of each monitoring point on the target cross section of the channel is selected and determined based on the distribution of sensing measurements on the actual cross section.

5. A gas flow monitoring system for large cross-section channels, characterized in that, The large-section channel is a channel for gas transmission or emission, and the gas flow monitoring system includes: At least three wind speed sensors and at least three gas concentration sensors are arranged at preset monitoring points on the target cross-section of the channel to perform real-time sensing of the corresponding monitoring points. The ratio of the total obstruction area of ​​the monitoring sensing device corresponding to each monitoring point on the target cross-section of the channel to the area of ​​the target cross-section of the channel is less than or equal to a preset value. The monitoring host is used to determine the wind speed and gas concentration values ​​of each grid on the measurement surface corresponding to the cross-section based on the real-time data sensed by each sensor and the spatial distribution of each monitoring point on the cross-section, using a preset spatial interpolation algorithm. And to calculate the gas flow rate value of the corresponding grid based on the wind speed measurement value and the gas concentration measurement value respectively, and to accumulate the calculation results, using the accumulated result as the gas flow rate monitoring value of the channel; The step of using a preset spatial interpolation algorithm to determine the wind speed and gas concentration measurements of each grid on the measurement surface corresponding to the cross-section includes obtaining a first type of monitoring points for wind speed monitoring parameters and a second type of monitoring points for gas concentration monitoring parameters. The first and second types of monitoring points are processed using the following steps respectively: The position points corresponding to each monitoring point on the measurement surface are used as vertices. The measurement surface is triangulated to determine the triangular region enclosed by each vertex. For each of the triangular regions, the monitoring values ​​of the monitoring points corresponding to each vertex of the corresponding region are used as the z-axis coordinate values. The two-dimensional coordinates of the corresponding vertices on the measurement surface are upgraded to obtain the three-dimensional coordinates of the vertices of the measurement projection area corresponding to each triangular region, and then the plane equation of the measurement projection area corresponding to each triangular region is determined. For any of the aforementioned grids, the triangular region to which it belongs is determined based on the two-dimensional coordinates of the corresponding grid on the measurement surface, and the z-axis coordinate value of the corresponding measurement projection point of the grid is calculated based on the following expression. F(x a0 ,y a0 ,z a )=0 Where F represents the plane equation of the measured projection area corresponding to the triangular region to which the grid belongs, a represents the measured projection point corresponding to the grid, and x a0 This represents the x-axis coordinate value of the grid on the measurement surface, and the y-axis coordinate value... a0 This represents the y-axis coordinate value of the grid on the measurement surface, and the z-axis coordinate value. a This represents the z-axis coordinate value of the measured projection point corresponding to the grid. The z-axis coordinates of the calculated projection points corresponding to each grid are used as the calculated values ​​of the monitoring parameters for the type of monitoring point corresponding to the first or second type of monitoring point of the corresponding grid.

6. The gas flow monitoring system according to claim 5, characterized in that, It also includes, The first processing device is used to aggregate and upload the first data sensed by each of the wind speed sensors; The second processing device is used to summarize and upload the second data sensed by each of the gas concentration sensors; A communication relay device is used to perform communication relay processing on the received first data and second data, and to transmit the processed third data to the monitoring host; Power supply equipment, used to provide power for system operation; The monitoring host is further configured to parse the third data to obtain the real-time wind speed monitoring value and the real-time gas concentration monitoring value corresponding to the monitoring point.

7. The gas flow monitoring system according to claim 6, characterized in that, The monitoring host is also configured to display and output the gas flow monitoring value, the real-time wind speed monitoring value and the real-time gas concentration monitoring value of the corresponding monitoring point, as well as the wind speed measurement value and gas concentration measurement value of each grid on the measurement surface.

8. The gas flow monitoring system according to claim 5, characterized in that, The gas concentration sensor is a laser methane sensor; the wind speed sensor is installed on the target section of the channel in the form of a probe.

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