Flow velocity measuring point arrangement method and system in fixed source carbon monitoring

Abstract

The invention discloses a flow velocity measuring point arrangement method and system in fixed source carbon monitoring, and the method comprises the steps: building a target flue model matched with a target flue based on the structure of the target flue; according to the target flue model, flow velocity distribution data in the target flue model are obtained based on steady-state and / or non-steady-state flow field simulation; according to the flow velocity distribution data, obtaining an alternative monitoring surface and monitoring surface flow velocity data corresponding to the alternative monitoring surface; according to the monitoring surface flow velocity data of each alternative monitoring surface, obtaining average flow velocity data of a key point configuration scheme on each alternative monitoring surface; obtaining an optimal monitoring surface according to the correlation between the average flow velocity data of the key point configuration scheme on each alternative monitoring surface and the monitoring surface flow velocity data of each alternative monitoring surface; and obtaining a flow velocity measuring point arrangement scheme according to the optimal monitoring surface. The problem of large average flow velocity estimation error caused by insufficient measuring points in a complex area of a flow field or redundant measuring points in an unimportant area in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of fluid dynamics data analysis technology, and in particular to a method and system for arranging velocity measurement points in stationary source carbon monitoring. Background Technology

[0002] Accurate measurement of flue gas flow rate from stationary pollution sources is a crucial prerequisite for precise carbon emission metering. Currently, flow velocity measurement typically employs a method of arranging multiple measuring points (such as the grid method) on the flue gas monitoring cross-section. By measuring local flow velocities and calculating the average flow velocity, the flue gas flow rate is obtained by combining the local flow velocity with the cross-sectional area.

[0003] However, due to factors such as flue structure, bends, and fans, the flow field distribution within the flue is extremely uneven, exhibiting severe velocity gradients and eddies. The traditional equal-area grid method for measuring point placement is highly arbitrary, failing to optimize based on actual flow field characteristics. This results in insufficient measuring points in complex flow field regions or redundant measuring points in unimportant areas, directly leading to large errors in average velocity estimation and consequently inaccurate flow rate and final carbon measurement results.

[0004] While computational fluid dynamics (CFD) has been used to simulate flue gas flow fields, a scientific and systematic method for translating CFD simulation results into specific, engineering-guided measurement point layout schemes remains lacking. Therefore, developing a method to scientifically determine the optimal number and location of measurement points based on flow field characteristics is crucial for improving the accuracy and reliability of carbon emission monitoring data. Summary of the Invention

[0005] This invention provides a method and system for arranging flow velocity measurement points in stationary source carbon monitoring. It offers a method that can scientifically determine the optimal number and location of measurement points based on flow field characteristics. This solves the problem that existing technologies fail to optimize based on actual flow field characteristics, resulting in insufficient measurement points in complex flow field areas or redundant measurement points in unimportant areas. This directly leads to large errors in average flow velocity estimation, which in turn causes inaccuracies in flow rate and final carbon measurement results.

[0006] On the one hand, a method for arranging velocity measurement points in stationary source carbon monitoring includes: Based on the structure of the target flue, a target flue model matching the target flue is established; Based on the target flue model, at least one velocity distribution data in the target flue model is obtained through steady-state and / or unsteady-state flow field simulation; Based on the at least one flow velocity distribution data, at least one candidate monitoring surface and the flow velocity data of the monitoring surface corresponding to the candidate monitoring surface are obtained; Based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface is obtained, and the number of key points included in each key point configuration scheme on each candidate monitoring surface is different. Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained. Based on the at least one preferred monitoring surface, a flow velocity measurement point layout scheme is obtained.

[0007] Optionally, establishing a target flue model that matches the target flue based on its structure includes: Based on the structure of the target flue, a three-dimensional geometric model matching the target flue is created or imported into CFD software; Configure boundary conditions and meshes for the three-dimensional geometric model to obtain a target flue model that matches the target flue.

[0008] Optionally, obtaining at least one candidate monitoring surface and the monitoring surface velocity data corresponding to the candidate monitoring surface based on the at least one velocity distribution data includes: Based on the at least one velocity distribution data, regions in the target flue model that exhibit similar velocity characteristics in different flow field simulations are selected as candidate regions. Based on the candidate areas, at least one candidate monitoring surface is obtained in the candidate areas; Based on at least one alternative monitoring surface, obtain the flow velocity data of the monitoring surface corresponding to the alternative monitoring surface.

[0009] Optionally, obtaining the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface based on the flow velocity data of each candidate monitoring surface includes: Based on each candidate monitoring surface, the candidate monitoring surface is divided into multiple dense grids according to preset rules; Based on the flow velocity data of each candidate monitoring surface, the grid flow velocity data of each grid is obtained; Based on the flow velocity data of each grid, at least some of the grids are taken as key points to obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

[0010] Optionally, the step of obtaining average flow velocity data for at least a portion of the multiple grids as key points based on the grid flow velocity data of each grid, and obtaining average flow velocity data for at least one key point configuration scheme on each candidate monitoring surface, includes: Based on the target key point configuration scheme, obtain the target number of key points in the target key point configuration scheme; Based on the number of key points in the target key point configuration scheme, at least one key point mapping is obtained, and each key point mapping is used to characterize the mapping relationship between a set of target key points and the grid. Based on the mapping of all key points, the average flow rate data of the target number of key points is obtained as the average flow rate data of the target key point configuration scheme.

[0011] Optionally, obtaining at least one keypoint mapping based on the number of keypoints in the target keypoint configuration scheme includes: Based on the target number of key points in the target key point configuration scheme, and based on the structure of the target flue, at least one flow velocity measurement point installation scheme corresponding to the target number of key points is obtained. Based on the flow velocity measurement point installation scheme, obtain the mapping relationship between the coordinates of the flow velocity measurement points and the grid in each flow velocity measurement point installation scheme; Based on the mapping relationship between the coordinates of the velocity measuring points and the grid in the velocity measuring point installation scheme, at least one key point mapping is obtained.

[0012] Optionally, obtaining at least one preferred monitoring surface based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface includes: The first weight data is obtained by comparing the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface with the flow velocity data of the monitoring surface on each candidate monitoring surface. The second weighting data is obtained based on the relative error between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface. The third weight data is obtained based on the number of key points in the key point configuration scheme; Based on the first weight data, the second weight data, and the third weight data, the total weight data of each candidate monitoring surface is obtained; Based on the total weight data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

[0013] Optionally, obtaining the flow velocity measurement point layout scheme based on the at least one preferred monitoring surface includes: Based on the at least one preferred monitoring surface, the optimal location and number of flow velocity monitoring points on the at least one preferred monitoring surface are determined using a mixed integer programming method; or Based on the at least one preferred monitoring surface and a preset index system, determine the optimal location and number of flow velocity monitoring points on the at least one preferred monitoring surface.

[0014] On the other hand, a system for arranging velocity measurement points in stationary source carbon monitoring includes a fluid dynamics simulation platform and a data analysis platform; The fluid dynamics simulation platform is configured as follows: Based on the structure of the target flue, a target flue model matching the target flue is established; Based on the target flue model, at least one velocity distribution data in the target flue model is obtained through steady-state and / or unsteady-state flow field simulation; The data analysis platform is configured as follows: Based on the at least one flow velocity distribution data, at least one candidate monitoring surface and the flow velocity data of the monitoring surface corresponding to the candidate monitoring surface are obtained; Based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface is obtained, and the number of key points included in each key point configuration scheme on each candidate monitoring surface is different. Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained. Based on the at least one preferred monitoring surface, a flow velocity measurement point layout scheme is obtained.

[0015] Optionally, obtaining the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface based on the flow velocity data of each candidate monitoring surface includes: Based on each candidate monitoring surface, the candidate monitoring surface is divided into multiple dense grids according to preset rules; Based on the flow velocity data of each candidate monitoring surface, the grid flow velocity data of each grid is obtained; Based on the flow velocity data of each grid, at least some of the grids are taken as key points to obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

[0016] On the other hand, a computer device includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the above-described method.

[0017] On the other hand, a computer storage medium storing a computer program, wherein a processor executes the computer program to implement the above-described method.

[0018] Compared with the prior art, the present invention has the following advantages and beneficial effects: This invention discloses a method and system for arranging velocity measurement points in stationary source carbon monitoring, comprising: establishing a target flue model matching the target flue based on the structure of the target flue; obtaining at least one velocity distribution data in the target flue model based on steady-state and / or unsteady-state flow field simulations; obtaining at least one candidate monitoring surface and corresponding monitoring surface velocity data based on the at least one velocity distribution data; obtaining average velocity data of at least one key point configuration scheme on each candidate monitoring surface based on the monitoring surface velocity data of each candidate monitoring surface, wherein the number of key points included in each key point configuration scheme on each candidate monitoring surface is different; obtaining at least one preferred monitoring surface based on the correlation between the average velocity data of at least one key point configuration scheme on each candidate monitoring surface and the monitoring surface velocity data of each candidate monitoring surface; and obtaining a velocity measurement point arrangement scheme based on the at least one preferred monitoring surface. This solves the problem that existing methods fail to optimize based on actual flow field characteristics, resulting in insufficient measurement points in complex flow field regions or redundant measurement points in unimportant regions, which directly leads to large errors in average flow velocity estimation and consequently inaccurate flow rate and final carbon measurement results. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0020] Figure 1 This is a flowchart illustrating a method for arranging velocity measurement points in stationary source carbon monitoring according to this application. Figure 2 This is a schematic diagram of the structure of a computer device according to this application.

[0021] The diagram is labeled as follows: 101-Processor, 102-Communication bus, 103-Network interface, 104-User interface, 105-Memory.

[0022] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present disclosure, the technical solutions of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present disclosure.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] Example 1 like Figure 1 As shown, a method for arranging velocity measurement points in stationary source carbon monitoring includes: S1. Based on the structure of the target flue, establish a target flue model that matches the target flue.

[0026] Optionally, the structure of the target flue may include: the cross-sectional shape of the flue, the cross-sectional dimensions of the flue, the length of the flue, the location of the bends and the location of the tapering sections in the flue, etc.

[0027] Optionally, a 3D modeling software can be used to construct the flue geometry model, which can then be directly imported into CFD software.

[0028] S2. Based on the target flue model, obtain at least one velocity distribution data in the target flue model through steady-state and / or unsteady-state flow field simulation.

[0029] Optionally, steady-state simulations can assume uniform flow velocity at the flue inlet and free outflow at the outlet; unsteady-state simulations can consider the pulse effect of intermittent blast furnace exhaust.

[0030] Optionally, CFD software can be used to solve the steady-state or unsteady-state Navier-Stokes equations. The k-ε model can be selected as the turbulence model, and the simulation results can be output. The simulation results can include a cloud map of the flow velocity distribution in the flue section under steady state or a curve of the flow velocity changing with time under unsteady state.

[0031] S3. Based on at least one flow velocity distribution data, obtain at least one candidate monitoring surface and the flow velocity data of the monitoring surface corresponding to the candidate monitoring surface.

[0032] Optionally, based on at least one velocity distribution data, regions in the target flue model that exhibit similar velocity characteristics in different flow field simulations are selected as candidate regions. Velocity characteristics include high-speed regions, low-speed regions, and vortex regions. To facilitate subsequent analysis, this scheme generally selects candidate monitoring surfaces from regions that exhibit high-speed or low-speed regions in different flow field simulations.

[0033] Furthermore, regions that exhibit high-speed or low-speed zones in different flow field simulations are generally represented by their height within the chimney, such as a region with a height of 10 to 15 meters. After determining this region, at least one alternative monitoring surface is obtained according to a preset scheme. The preset scheme may be to obtain several monitoring surfaces on average in each region or to obtain several monitoring surfaces according to a normal distribution, or to obtain a monitoring surface for every fixed height change, such as obtaining a monitoring surface every 0.5 meters from 10 meters to 15 meters.

[0034] S4. Based on the flow velocity data of each candidate monitoring surface, obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

[0035] Specifically, the number of key points included in each key point configuration scheme on each alternative monitoring surface varies.

[0036] Optionally, keypoint configuration schemes can include low-density, medium-density, and high-density configuration schemes. A specific example is as follows: The low-density configuration scheme includes 4 key points, the medium-density configuration scheme includes 9 key points, and the high-density configuration scheme includes 16 key points. For the flow rate at the key points of each scheme, the average flow rate at the key points in each scheme is obtained.

[0037] Optionally, each configuration scheme may also include sub-schemes that set key points in different locations, and the average flow rate of the key points in each scheme may be the average of the average flow rates of each sub-scheme.

[0038] S5. Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

[0039] Specifically, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of the monitoring surface on each candidate monitoring surface are both time series data. Correlation can be calculated using methods such as Pearson correlation coefficient. Furthermore, the relative error between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of the monitoring surface on each candidate monitoring surface can be considered in addition to the correlation to obtain at least one preferred monitoring surface.

[0040] S6. Obtain a flow velocity measurement point layout scheme based on at least one preferred monitoring surface.

[0041] The above solution solves the problem that existing methods fail to optimize for the actual flow field characteristics, resulting in insufficient measurement points in complex flow field areas or redundant measurement points in unimportant areas, which directly leads to large errors in the average flow velocity estimation and consequently inaccurate flow rate and final carbon measurement results.

[0042] Example 2 This embodiment, based on Embodiment 1, provides a method for arranging velocity measurement points in stationary source carbon monitoring, including: S1. Based on the structure of the target flue, establish a target flue model that matches the target flue.

[0043] Optionally, based on the structure of the target flue, a target flue model matching the target flue is established, including: Based on the structure of the target flue, a three-dimensional geometric model matching the target flue is created or imported into CFD software. Configure boundary conditions and meshes for the 3D geometric model to obtain a target flue model that matches the target flue.

[0044] S2. Based on the target flue model, obtain at least one velocity distribution data in the target flue model through steady-state and / or unsteady-state flow field simulation.

[0045] Optionally, based on at least one velocity distribution data, at least one candidate monitoring surface and the corresponding monitoring surface velocity data are obtained, including: Based on at least one velocity distribution data, regions in the target flue model that exhibit similar velocity characteristics in different flow field simulations are selected as candidate regions. Based on the candidate areas, at least one candidate monitoring surface is obtained within the candidate areas; Based on at least one alternative monitoring surface, obtain the flow velocity data of the monitoring surface corresponding to the alternative monitoring surface.

[0046] S3. Based on at least one flow velocity distribution data, obtain at least one candidate monitoring surface and the flow velocity data of the monitoring surface corresponding to the candidate monitoring surface.

[0047] S4. Based on the flow velocity data of each candidate monitoring surface, obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

[0048] Specifically, the number of key points included in each key point configuration scheme on each alternative monitoring surface varies; Optionally, based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface is obtained, including: Based on each candidate monitoring surface, each candidate monitoring surface is divided into multiple dense grids according to preset rules; Based on the flow velocity data of each candidate monitoring surface, obtain the grid flow velocity data of each grid. Based on the flow velocity data of each grid, at least some of the grids are taken as key points to obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

[0049] Optionally, based on the grid velocity data of each grid, at least some of the grids in the multiple grids are selected as key points to obtain the average velocity data of at least one key point configuration scheme on each candidate monitoring surface, including: Based on the target key point configuration scheme, obtain the target number of key points in the target key point configuration scheme; Based on the number of key points in the target key point configuration scheme, at least one key point mapping is obtained. Each key point mapping is used to characterize the mapping relationship between a set of key points and the grid. Based on the mapping of all key points, the average flow rate data of the target number of key points is obtained as the average flow rate data of the target key point configuration scheme.

[0050] Optionally, based on the number of targets for key points in the target key point configuration scheme, at least one key point mapping is obtained, including: Based on the target number of key points in the target key point configuration scheme, and based on the structure of the target flue, at least one flow velocity measurement point installation scheme corresponding to the target number of key points is obtained. Based on the flow velocity measurement point installation scheme, obtain the mapping relationship between the coordinates of the flow velocity measurement points and the grid in each flow velocity measurement point installation scheme; Based on the mapping relationship between the coordinates of the velocity measuring points and the grid in the velocity measuring point installation scheme, at least one key point mapping is obtained.

[0051] Optionally, in a specific example, if the number of key points in the target key point configuration scheme is 4, and the target flue is a square cross-section flue, based on the structure of the target flue, the velocity measurement point installation scheme corresponding to the target number of key points includes 4 schemes: Scheme 1 is to set the 4 velocity measurement points at the four corners of the square cross-section; Scheme 2 is to set the 4 velocity measurement points at the midpoint of the line connecting the four corners of the square cross-section to the center of the square cross-section; Scheme 3 is to set the 4 velocity measurement points at the midpoint of the four sides of the square cross-section; Scheme 4 is to set the 4 velocity measurement points at the midpoint of the line connecting the four sides of the square cross-section to the center of the square cross-section.

[0052] Optionally, in a specific example, if the number of key points in the target key point configuration scheme is 4, and the target flue is a circular cross-section flue, based on the structure of the target flue, the velocity measurement point installation scheme corresponding to the target number of key points includes 4 schemes: Scheme 1 is to evenly place 4 velocity measurement points on the circumference of the circular cross-section; Scheme 2 is to evenly place 3 velocity measurement points on the circumference of the circular cross-section and 1 velocity measurement point at the center; Scheme 3 is to evenly place 4 velocity measurement points on the circumference of a circle with a diameter half that of the circular cross-section and concentric with the circular cross-section; Scheme 4 is to evenly place 3 velocity measurement points on the circumference of a circle with a diameter half that of the circular cross-section and concentric with the circular cross-section and 1 velocity measurement point at the center.

[0053] S5. Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

[0054] Optionally, based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of the monitoring surface on each candidate monitoring surface, at least one preferred monitoring surface is obtained, including: The first weight data is obtained by comparing the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface with the flow velocity data of the monitoring surface on each candidate monitoring surface. The second weighting data is obtained based on the relative error between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface. The third weight data is obtained based on the number of key points in the key point configuration scheme; Based on the first weight data, the second weight data, and the third weight data, the total weight data of each candidate monitoring surface is obtained; Based on the total weight data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

[0055] Optionally, generally speaking, we set the larger the total weight data, the more suitable the candidate monitoring surface is as the preferred monitoring surface. In this case, the average flow velocity data of the key point configuration scheme on the candidate monitoring surface is more correlated with the monitoring surface flow velocity data of each candidate monitoring surface. The larger the first weight data, the smaller the relative error between the average flow velocity data of the key point configuration scheme on the candidate monitoring surface and the monitoring surface flow velocity data of each candidate monitoring surface. The larger the second weight data, the fewer the number of key points in the key point configuration scheme. The larger the third weight data, the more suitable the candidate monitoring surface is as a candidate monitoring surface.

[0056] A concrete example is as follows: if the correlation between the average flow velocity data of key point configuration scheme A on candidate monitoring surface A and the flow velocity data of candidate monitoring surface A is 0.85, then the first weight of key point configuration scheme A on candidate monitoring surface A is 0.85; if the correlation between the average flow velocity data of key point configuration scheme A on candidate monitoring surface A and the flow velocity data of candidate monitoring surface B is 0.8, then the first weight of key point configuration scheme B on candidate monitoring surface A is 0.8; if the relative error between the average flow velocity data of key point configuration scheme A on candidate monitoring surface A and the flow velocity data of candidate monitoring surface A is 10%, then the second weight of key point configuration scheme A on candidate monitoring surface A is 1-10%. The relative error between the average flow velocity data of configuration scheme B and the flow velocity data of the monitoring surface of candidate monitoring surface A is 5%. The second weight of key point configuration scheme B on candidate monitoring surface A is 1-5%. Configuration scheme A uses 9 key points and configuration scheme B uses 4 key points. The total number of grids is 100. The third weight of key point configuration scheme A is 100 / 9, and the third weight of key point configuration scheme B is 100 / 4. Finally, the total weight data of candidate monitoring surface A is the sum of the total weight data of key point configuration scheme A and key point configuration scheme B. The total weight data of key point configuration scheme A = the first weight of key point configuration scheme A * the second weight of key point configuration scheme A * the third weight of key point configuration scheme A.

[0057] The advantage of using the above method to select the optimal monitoring surface is that, in actual production, due to the influence of many factors, the flow of flue gas in the flue cannot be exactly the same as in the simulation. The optimal monitoring surface selected by the above method has stronger reliability and stability. No matter which key point configuration scheme the user adopts, or if there is a certain difference between the actual installation location and the preset key point configuration scheme, or even if there is a certain difference between the flow of flue gas in the flue and the simulation, it can be ensured that setting the flow velocity measurement point on the optimal monitoring surface can obtain relatively accurate results.

[0058] Optionally, obtaining at least one preferred monitoring surface based on the total weight data of each candidate monitoring surface means selecting a certain percentage of candidate monitoring surfaces with the highest total weight data from each candidate monitoring surface as preferred monitoring surfaces, such as the top 5% of candidate monitoring surfaces with the highest total weight data.

[0059] Optionally, based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface can be obtained. Based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of all key points on each candidate monitoring surface is obtained.

[0060] Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of the monitoring surface on each candidate monitoring surface, at least one preferred monitoring surface can be obtained. Alternatively, it can be: Based on the correlation between the average flow velocity data of all key points on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

[0061] Based on the correlation between the average flow velocity data of all key points on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface can be obtained. Alternatively, it can be: Based on all key points on each candidate monitoring surface, the probability of installing a flow velocity measurement point at each key point is determined. The weight of each key point is obtained based on the probability of installing a flow velocity measurement point at each key point. Based on the weights of all key points on each candidate monitoring surface and the correlation between the average flow velocity data and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

[0062] S6. Obtain a flow velocity measurement point layout scheme based on at least one preferred monitoring surface.

[0063] Optionally, based on at least one preferred monitoring surface, a flow velocity measurement point layout scheme is obtained, including: Based on at least one preferred monitoring surface, using a mixed-integer programming method, determine the optimal location and number of flow velocity monitoring points on at least one preferred monitoring surface; or Based on at least one preferred monitoring surface and a preset index system, determine the optimal location and number of flow velocity monitoring points on at least one preferred monitoring surface.

[0064] Optionally, determining the optimal location and number of velocity monitoring points on at least one preferred monitoring surface based on the mixed integer programming method means determining the velocity monitoring point layout scheme with the smallest error between the average velocity data and the velocity data of the monitoring surface when using various different velocity monitoring point layout schemes on all preferred monitoring surfaces as the final velocity monitoring point layout scheme. Optionally, a preset index system refers to an index system that takes into account factors such as construction difficulty, construction cost, and service life, while also considering errors. The final flow velocity measurement point layout scheme is obtained by scoring through expert scoring.

[0065] This further addresses the problem that existing methods fail to optimize based on actual flow field characteristics, resulting in insufficient measurement points in complex flow field regions or redundant measurement points in unimportant regions. This directly leads to large errors in average flow velocity estimation, which in turn causes inaccuracies in flow rate and final carbon measurement results.

[0066] Example 3 Based on Examples 1 and 2, this embodiment provides a system for arranging velocity measurement points in stationary source carbon monitoring, including a fluid dynamics simulation platform and a data analysis platform. The fluid dynamics simulation platform is configured as follows: Based on the structure of the target flue, a target flue model matching the target flue is established; Based on the target flue model, at least one velocity distribution data in the target flue model is obtained through steady-state and / or unsteady-state flow field simulation; The data analytics platform is configured as follows: Based on at least one flow velocity distribution data, obtain at least one candidate monitoring surface and the flow velocity data of the monitoring surface corresponding to the candidate monitoring surface; Based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface is obtained. The number of key points included in each key point configuration scheme on each candidate monitoring surface is different. Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained. Based on at least one preferred monitoring surface, a flow velocity measurement point layout scheme is obtained.

[0067] Optionally, based on the structure of the target flue, a target flue model matching the target flue is established, including: Based on the structure of the target flue, a three-dimensional geometric model matching the target flue is created or imported into CFD software. Configure boundary conditions and meshes for the 3D geometric model to obtain a target flue model that matches the target flue.

[0068] Optionally, based on at least one velocity distribution data, at least one candidate monitoring surface and the corresponding monitoring surface velocity data are obtained, including: Based on at least one velocity distribution data, regions in the target flue model that exhibit similar velocity characteristics in different flow field simulations are selected as candidate regions. Based on the candidate areas, at least one candidate monitoring surface is obtained within the candidate areas; Based on at least one alternative monitoring surface, obtain the flow velocity data of the monitoring surface corresponding to the alternative monitoring surface.

[0069] Optionally, based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface is obtained, including: Based on each candidate monitoring surface, each candidate monitoring surface is divided into multiple dense grids according to preset rules; Based on the flow velocity data of each candidate monitoring surface, obtain the grid flow velocity data of each grid. Based on the flow velocity data of each grid, at least some of the grids are taken as key points to obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

[0070] Optionally, based on the grid velocity data of each grid, at least some of the grids in the multiple grids are selected as key points to obtain the average velocity data of at least one key point configuration scheme on each candidate monitoring surface, including: Based on the target key point configuration scheme, obtain the target number of key points in the target key point configuration scheme; Based on the number of key points in the target key point configuration scheme, at least one key point mapping is obtained. Each key point mapping is used to characterize the mapping relationship between a set of key points and the grid. Based on the mapping of all key points, the average flow rate data of the target number of key points is obtained as the average flow rate data of the target key point configuration scheme.

[0071] Optionally, based on the number of targets for key points in the target key point configuration scheme, at least one key point mapping is obtained, including: Based on the target number of key points in the target key point configuration scheme, and based on the structure of the target flue, at least one flow velocity measurement point installation scheme corresponding to the target number of key points is obtained. Based on the flow velocity measurement point installation scheme, obtain the mapping relationship between the coordinates of the flow velocity measurement points and the grid in each flow velocity measurement point installation scheme; Based on the mapping relationship between the coordinates of the velocity measuring points and the grid in the velocity measuring point installation scheme, at least one key point mapping is obtained.

[0072] Optionally, based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of the monitoring surface on each candidate monitoring surface, at least one preferred monitoring surface is obtained, including: The first weight data is obtained by comparing the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface with the flow velocity data of the monitoring surface on each candidate monitoring surface. The second weighting data is obtained based on the relative error between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface. The third weight data is obtained based on the number of key points in the key point configuration scheme; Based on the first weight data, the second weight data, and the third weight data, the total weight data of each candidate monitoring surface is obtained; Based on the total weight data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

[0073] Optionally, based on at least one preferred monitoring surface, a flow velocity measurement point layout scheme is obtained, including: Based on at least one preferred monitoring surface, using a mixed-integer programming method, determine the optimal location and number of flow velocity monitoring points on at least one preferred monitoring surface; or Based on at least one preferred monitoring surface and a preset index system, determine the optimal location and number of flow velocity monitoring points on at least one preferred monitoring surface.

[0074] Example 4 This embodiment provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement any of the methods described above.

[0075] Specifically, such as Figure 2 As shown, Figure 2 This is a schematic diagram of the structure of a computer device according to this application. The computer device may include: a processor 101, such as a central processing unit (CPU), a communication bus 102, a user interface 104, a network interface 103, and a memory 105. The communication bus 102 is used to enable communication between these components. The user interface 104 may include a display screen and an input unit such as a keyboard. Optionally, the user interface 104 may also include a standard wired interface or a wireless interface. The network interface 103 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 105 may be a storage device independent of the aforementioned processor 101. The memory 105 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as at least one disk storage device. The processor 101 may be a general-purpose processor, including a central processing unit, a network processor, etc., or it may be a digital signal processor, an application-specific integrated circuit, a field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component.

[0076] Those skilled in the art will understand that the appendix Figure 2 The structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0077] like Figure 2As shown, the memory 105, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and an application program for implementing a method for arranging flow velocity measurement points in fixed-source carbon monitoring.

[0078] exist Figure 2 In the electronic device shown, the network interface 103 is mainly used for data communication with the network server; the user interface 104 is mainly used for data interaction with the user; the processor 101 and the memory 105 in this application can be set in the electronic device, and the electronic device can call the application program stored in the memory 105 to implement a method for arranging flow velocity measuring points in a fixed source carbon monitoring through the processor 101 to implement the above method.

[0079] Example 5 This embodiment provides a computer-readable storage medium on which a computer program is stored, and a processor executes the computer program to implement any of the methods described above.

[0080] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a device including one or any combination of the above-mentioned memories. The computer may be a variety of computing devices, including smart terminals and servers.

[0081] In the above embodiments of this disclosure, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0082] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0083] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0084] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0085] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a non-volatile storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this disclosure. The aforementioned non-volatile storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0086] The above are merely preferred embodiments of this disclosure. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this disclosure, and these improvements and modifications should also be considered within the scope of protection of this disclosure.

Claims

1. A method for arranging velocity measuring points in stationary source carbon monitoring, characterized in that, include: Based on the structure of the target flue, a target flue model matching the target flue is established; Based on the target flue model, at least one velocity distribution data in the target flue model is obtained through steady-state and / or unsteady-state flow field simulation; Based on the at least one flow velocity distribution data, at least one candidate monitoring surface and the flow velocity data of the monitoring surface corresponding to the candidate monitoring surface are obtained; Based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface is obtained, and the number of key points included in each key point configuration scheme on each candidate monitoring surface is different. Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained. Based on the at least one preferred monitoring surface, a flow velocity measurement point layout scheme is obtained.

2. The method for arranging velocity measuring points in stationary source carbon monitoring according to claim 1, characterized in that, The process of establishing a target flue model that matches the target flue structure includes: Based on the structure of the target flue, a three-dimensional geometric model matching the target flue is created or imported into CFD software; Configure boundary conditions and meshes for the three-dimensional geometric model to obtain a target flue model that matches the target flue.

3. The method for arranging velocity measuring points in stationary source carbon monitoring according to claim 1, characterized in that, The step of obtaining at least one candidate monitoring surface and the corresponding monitoring surface flow velocity data based on the at least one flow velocity distribution data includes: Based on the at least one velocity distribution data, regions in the target flue model that exhibit similar velocity characteristics in different flow field simulations are selected as candidate regions. Based on the candidate areas, at least one candidate monitoring surface is obtained in the candidate areas; Based on at least one alternative monitoring surface, obtain the flow velocity data of the monitoring surface corresponding to the alternative monitoring surface.

4. The method for arranging velocity measuring points in stationary source carbon monitoring according to claim 1, characterized in that, The step of obtaining the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface based on the flow velocity data of each candidate monitoring surface includes: Based on each candidate monitoring surface, the candidate monitoring surface is divided into multiple dense grids according to preset rules; Based on the flow velocity data of each candidate monitoring surface, the grid flow velocity data of each grid is obtained; Based on the flow velocity data of each grid, at least some of the grids are taken as key points to obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

5. The method for arranging velocity measuring points in stationary source carbon monitoring according to claim 4, characterized in that, The step of obtaining average flow velocity data for at least a portion of the multiple grids as key points based on the grid flow velocity data of each grid, and obtaining average flow velocity data for at least one key point configuration scheme on each candidate monitoring surface, includes: Based on the target key point configuration scheme, obtain the target number of key points in the target key point configuration scheme; Based on the number of key points in the target key point configuration scheme, at least one key point mapping is obtained, and each key point mapping is used to characterize the mapping relationship between a set of target key points and the grid. Based on the mapping of all key points, the average flow rate data of the target number of key points is obtained as the average flow rate data of the target key point configuration scheme.

6. The method for arranging velocity measuring points in stationary source carbon monitoring according to claim 5, characterized in that, The step of obtaining at least one keypoint mapping based on the number of keypoints in the target keypoint configuration scheme includes: Based on the target number of key points in the target key point configuration scheme, and based on the structure of the target flue, at least one flow velocity measurement point installation scheme corresponding to the target number of key points is obtained. Based on the flow velocity measurement point installation scheme, obtain the mapping relationship between the coordinates of the flow velocity measurement points and the grid in each flow velocity measurement point installation scheme; Based on the mapping relationship between the coordinates of the velocity measuring points and the grid in the velocity measuring point installation scheme, at least one key point mapping is obtained.

7. The method for arranging velocity measuring points in stationary source carbon monitoring according to claim 5, characterized in that, The step of obtaining at least one preferred monitoring surface based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface includes: The first weight data is obtained by comparing the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface with the flow velocity data of the monitoring surface on each candidate monitoring surface. The second weighting data is obtained based on the relative error between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface. The third weight data is obtained based on the number of key points in the key point configuration scheme; Based on the first weight data, the second weight data, and the third weight data, the total weight data of each candidate monitoring surface is obtained; Based on the total weight data of each candidate monitoring surface, at least one preferred monitoring surface is obtained.

8. The method for arranging velocity measuring points in stationary source carbon monitoring according to claim 1, characterized in that, The step of obtaining a flow velocity measurement point layout scheme based on the at least one preferred monitoring surface includes: Based on the at least one preferred monitoring surface, the optimal location and number of flow velocity monitoring points on the at least one preferred monitoring surface are determined using a mixed integer programming method; or Based on the at least one preferred monitoring surface and a preset index system, determine the optimal location and number of flow velocity monitoring points on the at least one preferred monitoring surface.

9. A system for arranging velocity measuring points in stationary source carbon monitoring, characterized in that, This includes a fluid dynamics simulation platform and a data analysis platform; The fluid dynamics simulation platform is configured as follows: Based on the structure of the target flue, a target flue model matching the target flue is established; Based on the target flue model, at least one velocity distribution data in the target flue model is obtained through steady-state and / or unsteady-state flow field simulation; The data analysis platform is configured as follows: Based on the at least one flow velocity distribution data, at least one candidate monitoring surface and the flow velocity data of the monitoring surface corresponding to the candidate monitoring surface are obtained; Based on the flow velocity data of each candidate monitoring surface, the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface is obtained, and the number of key points included in each key point configuration scheme on each candidate monitoring surface is different. Based on the correlation between the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface and the flow velocity data of each candidate monitoring surface, at least one preferred monitoring surface is obtained. Based on the at least one preferred monitoring surface, a flow velocity measurement point layout scheme is obtained.

10. A system for arranging velocity measuring points in stationary source carbon monitoring according to claim 9, characterized in that, The step of obtaining the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface based on the flow velocity data of each candidate monitoring surface includes: Based on each candidate monitoring surface, the candidate monitoring surface is divided into multiple dense grids according to preset rules; Based on the flow velocity data of each candidate monitoring surface, the grid flow velocity data of each grid is obtained; Based on the flow velocity data of each grid, at least some of the grids are taken as key points to obtain the average flow velocity data of at least one key point configuration scheme on each candidate monitoring surface.

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