Method, system and equipment for simulating wind field along railway and distributing wind monitoring points

Abstract

The invention relates to the technical field of railway disaster protection, and discloses a method, a system and equipment for simulating a wind field along a railway and distributing wind monitoring points. The method comprises the following steps: constructing a circular 3D earth surface model along a railway according to railway line latitude and longitude data based on a geographic information technology; smoothing the transition region of the circular 3D earth surface model by using a square cosine function to obtain a terrain model; grid division is carried out on the terrain model based on the full wind direction, and calculation is carried out by adopting computational fluid mechanics to obtain a calculation result; and determining a potential strong wind area in the wind field according to a calculation result based on a full wind direction maximum wind speed area rule or a strong wind maximum probability area rule, and determining a wind monitoring arrangement position. According to the method, a digital 3D terrain model along a railway is constructed by utilizing a geographic information technology, wind field simulation evaluation is performed in combination with a computational fluid dynamics (CFD) technology and railway engineering characteristics, a potential strong wind area is screened out to realize wind monitoring arrangement position selection, and the method is used for wind field evaluation of a newly-built railway and an existing railway.

Description

Technical Field

[0001] The present invention relates to the technical field of railway disaster protection, and in particular to a method, system and equipment for simulating wind fields and distributing wind monitoring points along railways. Background Art

[0002] At present, the following methods are usually used for wind field simulation and wind monitoring along railways:

[0003] 1. Based on the correlation analysis of existing wind speed data of railways, an optimization algorithm is used to guide the supplementation of existing wind monitoring points. This method needs to be based on the existing wind speed data of railways and is only applicable to the supplementation of wind monitoring points of existing railways. It uses correlation analysis technology and is not applicable to new railways.

[0004] 2. Layout of high-speed rail wind monitoring points: Calculate the crosswind along the track of the preliminary selected line; determine the crosswind sensitive area to be verified based on the maximum crosswind and average crosswind; verify the crosswind sensitive area to be verified, and determine the verified sensitive area to be verified as the sensitive area; for the verified sensitive area, establish a single meteorological element site time and space sequence; selectively eliminate to obtain the monitoring points to be determined. This method uses meteorological data to screen out crosswind sensitive areas, and determines the location of railway wind monitoring points by verifying the crosswind sensitive areas. Its application basis is inseparable from meteorological data, but when there are few meteorological stations along the railway or the distance to the meteorological station is far, it will affect the application scenario and accuracy of this method.

[0005] 3. Layout of high-speed railway wind monitoring points: Based on the wind speed, wind direction and other data of meteorological stations along and around the high-speed railway, analyze the distribution characteristics of strong winds and count the frequency distribution of wind speeds under each wind direction, and lay out basic monitoring points; establish the correlation between the wind field between any two points along the railway under complex terrain based on topographic data, and use the theory and method of computational fluid dynamics (CFD) to simulate the wind field along the high-speed railway, and lay out interpolation monitoring points; simulate the wind field of special sections, combine wind tunnel experiments, and lay out special monitoring points. This method requires the implementation of basic monitoring points on site, which consumes observation time and may affect the progress of project implementation.

[0006] 4. Based on the wind speed series data collected by the wind monitoring points installed along the high-speed railway, the wind speed changes in the area where the monitoring points are not installed are interpolated, and then a cluster analysis is performed on the monitoring points on the line (including the interpolation points) to explore the spatial correlation of the monitoring points. Combined with the evaluation method of the installed monitoring points, this method can only be used for existing railway lines and requires a long period of wind speed series data. It is not suitable for the evaluation and selection of wind monitoring points for newly built railways.

[0007] 5. Automatic search for optimized network layout for strong wind monitoring along high-speed railways: Step 1: Determine the transition area between at least two different terrains in various terrain environments along the high-speed railway as a system module, and establish a system module group; Step 2: Take the terrain characteristic parameters of each system module in the system module group as research variables, and establish an independent wind tunnel test model or CFD numerical simulation model corresponding to the system module; Step 3: For the terrain characteristic parameters included in each system module, change the values ​​of the terrain characteristic parameters to obtain a finite number of variable working conditions, and obtain the wind load value corresponding to each variable working condition in the wind tunnel test model or the CFD numerical simulation model, and use it as the control data point corresponding to the variable working condition; Step 4: According to the finite number of variable working conditions of the system module and the corresponding finite number of control data points, according to the actual Under the continuous variable working condition value conditions within the range corresponding to the terrain situation, the interpolation calculation method is used to obtain each wind load value corresponding to the continuous variable working condition value conditions within the transition area of ​​the system module, and an independent interpolation database of wind load values ​​corresponding to each variable working condition of the system module is established; Step 5, for the wind load value interpolation database in Step 4, search and determine the maximum wind load value, and obtain the variable working condition corresponding to the maximum wind load value. The terrain position corresponding to the variable working condition in the system module is the system module under the continuous variable working condition value conditions within the actual terrain range. The optimized network monitoring point for strong wind monitoring along the line; Step 6, determine the corresponding system module according to the actual terrain characteristic parameters, repeat steps 3 to 5, and you can get the optimized network monitoring point for strong wind monitoring along the line corresponding to the terrain characteristic parameters. This method uses a limited number of system modules to interpolate and fit the terrain around the railway line, which may have large errors when the terrain is complex.

[0008] VI. Setting of high-wind monitoring points along high-speed railways: (1) Determine the area along the railway where high-wind monitoring points need to be set up based on meteorological data; (2) Use a tool that includes a ground elevation information acquisition system to establish a three-dimensional terrain model for the area; (3) Discretize the three-dimensional terrain model, and simulate the wind field characteristics around the railway represented by the three-dimensional model. According to the wind field characteristic simulation results, determine a number of wind speed hazard points where the wind acceleration factor is greater than the set value; (4) Divide the wind speed hazard area according to the several wind speed hazard points, and perform secondary zoning within the area based on the wind speed hazard area determination results to form multiple high-wind monitoring points. Points of secondary sub-regions; (5) each secondary sub-region is refined and several secondary wind speed monitoring points are set respectively, and the wind field characteristics of the wind speed along the railway in the secondary sub-region are simulated as above, and the most unfavorable wind acceleration factor value and its corresponding wind direction angle of each secondary wind speed monitoring point in each secondary sub-region that have the greatest impact on train operation are obtained; (6) by comparing and analyzing the most unfavorable wind acceleration factor values ​​of each secondary wind speed monitoring point in each secondary sub-region, the specific location of each secondary sub-region strong wind monitoring point is calibrated; (7) the strong wind monitoring points calibrated in step (6) are optimized, and the relevant equipment and facilities for strong wind monitoring are arranged at the optimized strong wind monitoring points. The first step of this method is to use the meteorological station data to first screen the strong wind point area range, which requires high accuracy and precision of meteorological data. When meteorological data is missing or the meteorological station is far away from the railway line, it is difficult to ensure accuracy.

[0009] In summary, the above-mentioned methods have the following deficiencies: Method 1, Method 2 and Method 4 all require wind speed data from meteorological stations or other nearby areas when implemented. Method 1 and Method 4 can only be used to optimize the location of existing railway wind monitoring points, and cannot be used for the evaluation and layout of new railway wind monitoring points. Methods 3, 4 and 5 use interpolation calculation methods to deal with wind speed discontinuity areas, and cannot achieve continuous processing of wind speed laws. Method 6 only performs CFD calculations on some areas that are considered dangerous, rather than the entire railway line. At the same time, this method uses a rectangle as the CFD calculation domain, and needs to re-divide the grid under different wind conditions, which increases the amount of calculation and is more troublesome. Summary of the invention

[0010] The main purpose of the present invention is to provide a method, system and equipment for simulating wind fields and deploying wind monitoring points along railways, aiming to solve at least one of the above-mentioned technical problems.

[0011] To achieve the above object, the present invention provides a method for simulating a wind field along a railway and deploying wind monitoring points, comprising:

[0012] Based on geographic information technology, a circular 3D surface model along the railway is constructed according to the longitude and latitude data of the railway line;

[0013] The transition area of ​​the circular 3D surface model is smoothed by using a square cosine function to obtain a terrain model;

[0014] The terrain model is meshed based on all wind directions and is calculated using computational fluid dynamics to obtain calculation results;

[0015] Based on the maximum wind speed zone rule in all wind directions or the maximum probability zone rule for strong winds, the potential strong wind area in the wind farm is determined according to the calculation results and the wind monitoring layout position is determined.

[0016] In some embodiments, the method of constructing a circular 3D surface model along the railway according to the longitude and latitude data of the railway line based on geographic information technology includes:

[0017] Obtain the longitude and latitude data of railway lines;

[0018] Querying and intercepting elevation data of a preset area in a global digital elevation model according to the longitude and latitude data of the railway line position;

[0019] Divide the railway line into several areas along its length;

[0020] Circular 3D surface models of several areas are respectively established based on the elevation data.

[0021] In some embodiments, the step of establishing circular 3D surface models of several regions based on the elevation data includes:

[0022] Take the point on the railway line as the center and divide two concentric circles with the first radius and the second radius respectively; the first radius is larger than the second radius, the first radius is the modeling area, the second radius is the research area, and the annular area from the second radius to the first radius is the transition area;

[0023] The elevation data is intercepted with the first radius, and circular 3D surface models of several areas are respectively established.

[0024] In some embodiments, the terrain model is gridded based on all wind directions and calculated using computational fluid dynamics to obtain calculation results, including:

[0025] Placing the terrain model in a calculation domain; wherein the calculation domain is set in a cuboid, and the cuboid is a square in the horizontal direction;

[0026] Determining the number of grid divisions based on the full wind direction and the computational domain;

[0027] Based on the number of grid divisions, the computational domain is discretized using a structured hexahedral grid, and a dense grid is performed on a preset key area and a boundary layer of the railway line;

[0028] After the grid is divided, computational fluid dynamics is used to calculate the terrain model respectively to obtain model calculation results under various wind directions;

[0029] The model calculation results under the various wind directions are normalized to obtain calculation results.

[0030] In some embodiments, the normalizing the model calculation results under the various wind directions to obtain the calculation results includes:

[0031] Preserve overlapping areas in selected areas of adjacent terrain models;

[0032] When the same wind speed and wind direction are used as input conditions, the wind speed of one of the adjacent terrain models is normalized according to the wind speed value of the overlapping area;

[0033] All terrain models are normalized and the normalized results are used as calculation results.

[0034] In some embodiments, the method of determining the potential high wind area in the wind farm and determining the wind monitoring arrangement position based on the maximum wind speed area rule in all wind directions or the high wind maximum probability area rule according to the calculation result includes:

[0035] For newly built railways, based on the maximum wind speed zone rule in all wind directions, the potential high wind area in the wind field is determined according to the calculation results and the wind monitoring layout location is determined;

[0036] For existing railways, the potential high wind area in the wind field is determined according to the calculation results based on the high wind maximum probability area rule and the wind monitoring layout position is determined.

[0037] In some embodiments, for a newly built railway, determining the potential high wind area in the wind farm and determining the wind monitoring layout location based on the calculation result based on the maximum wind speed zone rule in all wind directions includes:

[0038] For a newly built railway, the maximum wind speed occurring in each wind direction along the railway is counted according to the calculation results;

[0039] Compare the relative magnitude of the maximum wind speed along the railway, and use the point with the maximum wind speed within a section of the railway as the potential high wind area and anemometer deployment area;

[0040] The wind monitoring layout location is determined according to the anemometer layout area.

[0041] In some embodiments, for an existing railway, determining a potential high wind area in a wind field and determining a wind monitoring arrangement location based on the high wind maximum probability area rule according to the calculation result includes:

[0042] For existing railways, the prevailing wind direction at a known point and the probability of strong winds of various levels occurring in the prevailing wind direction are calculated based on actual wind speed data;

[0043] According to the ratio relationship between adjacent points of the terrain model, the probability distribution of wind speed at each point along the railway under the dominant wind direction of the known point is calculated;

[0044] According to the wind speed probability distribution, the point with the highest probability is selected as the potential high wind area and the wind monitoring layout location.

[0045] In addition, to achieve the above-mentioned purpose, the present invention also proposes a wind field simulation and wind monitoring point distribution system along the railway, comprising:

[0046] A model building module is used to construct a circular 3D surface model along the railway based on the longitude and latitude data of the railway line based on geographic information technology;

[0047] A smoothing processing module, used for smoothing the transition area of ​​the circular 3D surface model using a square cosine function to obtain a terrain model;

[0048] A grid division and calculation module, used to divide the terrain model into grids based on all wind directions and perform calculations using computational fluid dynamics to obtain calculation results;

[0049] A rule determination module is used to determine the potential high wind area in the wind farm and determine the wind monitoring layout position based on the maximum wind speed area rule in all wind directions or the high wind maximum probability area rule according to the calculation results.

[0050] In addition, to achieve the above-mentioned purpose, the present invention also proposes an electronic device, which includes: a memory, a processor, and a program for simulating wind field simulation and wind monitoring points along the railway, which is stored in the memory and can be run on the processor, and the program for simulating wind field simulation and wind monitoring points along the railway is configured to implement the method for simulating wind field simulation and wind monitoring points along the railway as described above.

[0051] The present invention provides a method for simulating a wind field and arranging wind monitoring points along a railway, including: constructing a circular 3D surface model along the railway according to the longitude and latitude data of the railway line based on geographic information technology; smoothing the transition area of ​​the circular 3D surface model using a square cosine function to obtain a terrain model; gridding the terrain model based on all wind directions and calculating using computational fluid dynamics to obtain calculation results; determining the potential high wind area in the wind field and determining the wind monitoring layout position based on the calculation results based on the maximum wind speed area rule of all wind directions or the maximum probability area rule of high winds. In the present invention, geographic information technology is used to construct a digital 3D terrain model along the railway, and combined with computational fluid dynamics CFD technology and railway engineering characteristics, wind field simulation and high wind area evaluation are performed, which can screen out potential high wind areas and realize the selection of wind monitoring layout positions, and is suitable for the railway. No meteorological data is required, and it can be used for wind field evaluation of new railways and existing railways, and has a wide range of applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A schematic diagram of the structure of an electronic device in a hardware operating environment involved in an embodiment of the present invention;

[0053] Figure 2 It is a flow chart of an embodiment of a method for simulating a wind field along a railway and distributing wind monitoring points according to the present invention;

[0054] Figure 3 It is a schematic diagram of the wind field simulation and high wind area assessment process suitable for railways involved in the embodiment of the present invention;

[0055] Figure 4a The DEM elevation information map involved in the embodiment of the present invention;

[0056] Figure 4b This is a schematic diagram of a research area divided into 8km radius involved in an embodiment of the present invention;

[0057] Figure 5a A schematic diagram of a terrain curved surface without a transition section involved in an embodiment of the present invention;

[0058] Figure 5b A schematic diagram of a terrain surface with a transition section added according to an embodiment of the present invention;

[0059] Figure 5c It is a 3D top view of the transition section after processing involved in the embodiment of the present invention;

[0060] Figure 5d It is a 3D side view of the transition section after processing involved in the embodiment of the present invention;

[0061] Figure 6aA schematic diagram of a horizontal grid involved in an embodiment of the present invention;

[0062] Figure 6b A schematic diagram of a ground surface grid involved in an embodiment of the present invention;

[0063] Figure 6c A schematic diagram of a vertical grid involved in an embodiment of the present invention;

[0064] Figure 6d A schematic diagram of a near-ground vertical grid involved in an embodiment of the present invention;

[0065] Figure 7a Schematic diagram of 16 wind directions involved in the embodiment of the present invention;

[0066] Figure 7b The wind speed inflow and outflow diagrams involved in the embodiments of the present invention;

[0067] Figure 8 A schematic diagram of line positions and divisions involved in an embodiment of the present invention;

[0068] Fig. 9 The present invention is a structural block diagram of an embodiment of a system for simulating wind fields and monitoring wind monitoring points along railways.

[0069] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0072] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0073] Reference Figure 1 , Figure 1 The figure is a schematic diagram of the structure of an electronic device of the hardware operating environment involved in the embodiment of the present invention.

[0074] like Figure 1 As shown, the electronic device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM memory) or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0075] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0076] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a program for simulating wind farms along railways and deploying wind monitoring points.

[0077] exist Figure 1In the electronic device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the electronic device of the present invention can be set in the electronic device, and the electronic device calls the railway wind field simulation and wind monitoring point layout program stored in the memory 1005 through the processor 1001, and executes the railway wind field simulation and wind monitoring point layout method provided in the embodiment of the present invention.

[0078] The meteorological data of the meteorological station only reflects the macro-climate situation, and it is difficult to reflect the local wind field changes caused by the topography along the railway. At present, the railway mainly uses the basic wind speed of the meteorological station combined with the terrain along the railway to correct the terrain and screen the strong wind area. The accuracy of this method is relatively low. In order to study the changes in the local wind field, the classic research method of building a physical model of the terrain and structure and placing the model in a wind tunnel for experiment can be adopted. However, due to the long line and strip distribution of the railway line, the investment in building a physical model is large and the cycle is long, which is difficult to meet the requirements of large-scale engineering applications.

[0079] In view of this, the present invention proposes a method, system and equipment for simulating wind fields and deploying wind monitoring points along railways.

[0080] The embodiment of the present invention provides a method for simulating a wind field along a railway and deploying wind monitoring points, referring to Figure 2 , Figure 2 The present invention is a flow chart of an embodiment of a method for simulating wind fields and deploying wind monitoring points along a railway.

[0081] like Figure 2 As shown, the method for simulating the wind field along the railway and distributing wind monitoring points includes:

[0082] Step S100: constructing a circular 3D surface model along the railway according to the longitude and latitude data of the railway line based on geographic information technology;

[0083] Step S200: using a square cosine function to smooth the transition area of ​​the circular 3D surface model to obtain a terrain model;

[0084] Step S300: gridding the terrain model based on all wind directions and performing calculations using computational fluid dynamics to obtain calculation results;

[0085] Step S400: Based on the maximum wind speed zone rule for all wind directions or the maximum probability zone rule for strong winds, the potential strong wind area in the wind farm is determined according to the calculation result and the wind monitoring arrangement position is determined.

[0086] It should be noted that the execution subject in this embodiment may be an electronic device, which may be a computer device with data processing functions, or other devices that can achieve the same or similar functions. This embodiment does not limit this. In this embodiment, a computer device is used as an example for explanation.

[0087] It is understandable that this embodiment is described by taking the wind field simulation and high wind area assessment along the railway as an example. In view of the shortcomings of the above-mentioned background technology, this embodiment mainly solves the following key technical problems: (1) Without meteorological data, this embodiment can evaluate the wind field along the railway, so it can be used for both new railways and existing railways, and has a wide range of applications. (2) The wind field assessment range of this embodiment can cover all sections along the railway, there is no discontinuous area, and no interpolation algorithm is used. (3) This embodiment adopts circular area 3D terrain modeling and rectangular parallelepiped calculation domain, making full use of geometric symmetry and significantly reducing the number of grid divisions. (4) This embodiment uses the cosine algorithm (square cosine function) as the transition algorithm for the circular area 3D terrain model, eliminating the "artificial cliff" effect caused by 3D model interception and ensuring the calculation accuracy. (5) The railway line stretches for hundreds or even thousands of kilometers. This embodiment adopts segmented modeling to ensure the feasibility of the calculation scale. At the same time, a normalization method for wind speed between segmented models is proposed, and the calculation results of the segmented models can be uniformly compared. (6) This embodiment adopts a progressively extended grid division method, which not only ensures sufficient accuracy of the grid near the surface, but also reduces the total number of grids and balances the calculation time. (7) This embodiment proposes two rules: the maximum wind speed zone rule for all wind directions and the maximum probability zone rule for strong winds, which are respectively applicable to the layout of wind monitoring points without meteorological data and with meteorological data. The following is an explanation of this embodiment in conjunction with specific steps.

[0088] In one embodiment, a circular 3D surface model along the railway is constructed based on the longitude and latitude data of the railway line based on geographic information technology, including: obtaining the longitude and latitude data of the railway line; querying and intercepting the elevation data of a preset area in the global digital elevation model based on the longitude and latitude data of the railway line; dividing the railway line into several areas along the length direction; and establishing circular 3D surface models of the several areas based on the elevation data.

[0089] In one embodiment, circular 3D surface models of several areas are established based on the elevation data, including: taking a point on the railway line as the center of the circle, dividing two concentric circles with a first radius and a second radius respectively; wherein the first radius is greater than the second radius, the first radius range is the modeling area, the second radius range is the research area, and the annular area from the second radius to the first radius is the transition area; the elevation data is intercepted with the first radius to establish circular 3D surface models of several areas.

[0090] Specifically, the establishment of a 3D terrain model along the railway: Figure 3 As shown in Figure 1, the longitude and latitude data of the railway line are used to segment and extract the elevation data of the corresponding area in the global digital elevation map (DEM). Figure 4a The DEM elevation information map shown in FIG. 1 is used to intercept elevation data with a certain radius, such as 8 km, with the point on the line as the center, and generate a circular 3D surface model.

[0091] Specifically, in this embodiment, only the longitude and latitude coordinates of the railway line are required as input. The longitude and latitude coordinates (longitude and latitude data) can be provided by relevant design units. Generally, the longitude and latitude data can be provided by professional units involved in railway design. These units usually have professional geographic information collection and processing capabilities. Query and intercept the global digital elevation model DEM (DEM can use different resolutions such as 30m, 12.5m, 5m, etc.), divide the entire railway line into several areas, and establish terrain models separately. Figure 4a and 4b As shown in the figure, the terrain area corresponding to the railway line is found on the DEM map through the longitude and latitude coordinates of the railway line, and then the modeling study area is divided into about 201 square kilometers with the line as the center and a radius of 8km. Figure 4b The study area divided by a radius of 8 km as shown is divided into two concentric circles with a point on the line as the center and a first radius (e.g. 8 km) and a second radius (e.g. 6 km) as the radii (different radii can also be used). The first radius (e.g. 8 km) is the modeling area, the second radius (e.g. 6 km) is the study area, and the annular area from the second radius (e.g. 6 km) to the first radius (e.g. 8 km) is the transition area.

[0092] It should be noted that the terrain modeling of the railway line is carried out using the Geographic Information System (GIS): after obtaining the latitude and longitude coordinates of the railway line, the corresponding Digital Elevation Model (DEM) can be queried and intercepted. DEM is a digital geographic data set that contains the elevation information of the surface. Different resolutions such as 30m, 12.5m, and 5m represent the degree of refinement of the DEM data. The lower the resolution, the coarser the accuracy of the data, which is usually used for large areas; the higher the resolution, the higher the accuracy of the data, which is suitable for detailed terrain analysis. After obtaining the DEM data, the railway line will be divided into several smaller areas along its length. For each area, the DEM data is used to establish a terrain model to more carefully analyze and simulate the ground undulations that the railway line passes through. This process involves the acquisition of accurate location information, the query and processing of terrain data, and the establishment of a terrain model.

[0093] In this embodiment, no meteorological data is required, and the wind field along the railway can be evaluated. It can be used for both new railways and existing railways, and has a wide range of applications. The railway line stretches for hundreds or even thousands of kilometers. This embodiment adopts segmented modeling to ensure the feasibility of the calculation scale. The wind field evaluation range can cover all sections along the railway, there is no discontinuous area, and no interpolation algorithm is required.

[0094] In one embodiment, a square cosine function is used to smooth the transition area of ​​the circular 3D surface model to obtain a terrain model.

[0095] It is understandable that due to the significant undulations of the landform, the edges of the intercepted terrain model are not in the same height, which will cause a discontinuous vertical drop between the edge of the terrain model and the ground of the numerical calculation domain. This drop is called an "artificial cliff", such as Figure 5a As shown. The high degree of discontinuity will cause flow separation, turbulent transition and local cavitation at the edge of the terrain, which is significantly different from the continuous flow state in actual conditions. Especially in the wind field simulation study with limited simulation range and complex terrain geometry, the influence of the above effects is particularly prominent. After comparing various transition curve forms such as slope form, transition curve based on cylindrical flow, square cosine curve, etc., the square cosine curve was finally selected to process the transition area of ​​the terrain model with a radius of 6km to 8km. The results after processing are referenced Figure 5b , Figure 5c as well as Figure 5d .

[0096] Specifically, in this embodiment, after comparing various transition curve forms such as slope forms, transition curves based on cylindrical flow, and square cosine curves, the cosine algorithm, i.e., square cosine curve (square cosine function) is selected to process the terrain model transition area from the second radius (e.g., 6 km) to the first radius (e.g., 8 km). The circular 3D surface model transition section is smoothed, and the processed model (terrain model) is meshed.

[0097] For example, a square cosine function is used, which takes a value of 0 at the boundary of the transition area and a value of 1 at the center of the transition area. Therefore, this function can achieve a smooth transition from the original terrain height to 0. By adjusting the value of L (the width of the transition area, that is, the length or diameter of the transition area), the width of the transition area can be controlled, thereby affecting the degree of smoothness. In practical applications, this smoothing process is usually performed at the meshing stage of the numerical model to ensure the continuity of the terrain data and the accuracy of the simulation results.

[0098] In this embodiment, the cosine algorithm (square cosine function) is used as the transition algorithm for the circular area 3D terrain model, thereby eliminating the "artificial cliff" effect caused by the 3D model interception and ensuring the calculation accuracy.

[0099] In one embodiment, the terrain model is meshed based on all wind directions and calculated using computational fluid dynamics to obtain calculation results, including: placing the terrain model in a calculation domain; wherein the calculation domain is set in a cuboid, and the cuboid is a square in the horizontal direction; determining the number of meshing times based on all wind directions and the calculation domain; discretizing the calculation domain using a structured hexahedral grid based on the number of meshing times, and densely meshing preset key areas and boundary layers of the railway line; after meshing, calculating the terrain model using computational fluid dynamics to obtain model calculation results under various wind directions; and normalizing the model calculation results under various wind directions to obtain calculation results.

[0100] Exemplarily, the model is gridded for all wind directions (a total of 16 wind directions) and calculated using computational fluid dynamics (CFD).

[0101] Specifically, the computational domain and grid division: To ensure the full development of the flow field, the terrain model (3D terrain model) is placed in the computational domain of 16000m in the X direction (horizontal), 16000m in the Y direction (horizontal), and 5000m in the Z direction (vertical). According to calculations, the numerical wind tunnel blockage ratio is less than 5%. This is a huge computational space of 16km×16km×5km. If the usual grid division method is used, a large number of grids (about 12 million) will be generated. In this embodiment, a structured hexahedral grid is used to discretize the computational domain. For example, the horizontal size of the terrain model surface grid is 25m, the minimum size of the computational domain grid X and Y (horizontal) is 25m, the grid extension rate is set to 1.2, and it gradually expands from the terrain area to the outside. The minimum thickness of the Z direction (vertical) grid is 1m, which is the first layer of grid close to the ground, the grid extension rate is 1.2, and the final total number of volume grids is 9.22 million. Among them, the grid is densely divided for the area around the railway line and the boundary layer to improve the numerical simulation accuracy of key areas.

[0102] Specifically, the model boundary and working condition settings: According to the meteorological specifications, the wind is divided into 16 wind directions at intervals of 22.5°. Different wind directions will form different wind fields for the same terrain model, and it is usually necessary to mesh the 16 situations separately. In this embodiment, the calculation area is set in a rectangular parallelepiped, and the rectangular parallelepiped structure is set to a square in the horizontal direction. The geometric symmetry of the square can reduce the number of mesh divisions. Only 4 mesh divisions are needed to meet the model requirements of all 16 working conditions (all wind directions and 16 wind directions).

[0103] For example, reference Figures 6a to 6d , Figure 6a The horizontal grid division in the middle is denser in the center area and sparser in the edge area. Figure 6b The ground surface grid after division. Figure 6c and Figure 6d A vertical grid for a vertical interface. Figure 6c is the vertical grid, Figure 6d It is a vertical grid near the ground. Since railway wind monitoring is more concerned with the distribution of wind fields near the surface, the grid division near the ground is denser, and the grid away from the surface is gradually sparse.

[0104] It should be noted that the reference Figure 7a to Figure 7b In meteorology, in order to classify wind directions, they are usually divided into several categories at certain angle intervals. Each wind direction is deflected 22.5° relative to the next wind direction, and a total of 16 different wind directions can be divided (such as Figure 7a ). Figure 7b The wind speed inflow and outflow diagrams shown in the figure show that the wind field flowing through the same terrain model will be different due to different wind directions. In the traditional numerical simulation method, in order to study the influence of all wind directions on the model, it is necessary to perform a separate grid division and simulation calculation for each wind direction, so for 16 wind directions, 16 independent grid divisions and simulations are required. This embodiment proposes a method using geometric symmetry to optimize the simulation process. Here, the calculation area is set to a rectangular parallelepiped, and its horizontal cross-section is a square. Since the square has symmetry in four directions, this symmetry can be used to reduce the number of grid divisions required. Specifically, only four different wind directions need to be gridded, and then the symmetry of the square can be used to infer the wind field conditions under the remaining wind directions, that is, the geometric symmetry of the square is used to adjust the input and output conditions to reduce the number of grid divisions, and only 4 grid divisions are needed to meet the model requirements of all 16 working conditions. This means that for 16 wind directions, this embodiment only needs to perform 4 grid divisions, instead of the traditional 16 times, which greatly improves the simulation efficiency.

[0105] In this embodiment, circular area 3D terrain modeling and rectangular parallelepiped calculation domain are used to make full use of geometric symmetry and significantly reduce the number of grid divisions. In addition, this embodiment adopts a progressive extension grid division method, which not only ensures sufficient accuracy of the grid near the surface, but also reduces the total number of grids and balances the calculation time.

[0106] In one embodiment, the model calculation results under the various wind directions are normalized to obtain the calculation results, including: retaining the overlapping area in the selected area of ​​the adjacent terrain models; when the same wind speed and wind direction are used as input conditions, the wind speed of one of the adjacent terrain models is normalized according to the wind speed value of the overlapping area; all terrain models are normalized, and the normalized result is used as the calculation result.

[0107] Specifically, wind speed normalization: the entire railway is divided into several areas and modeled and calculated separately. The wind speeds calculated by different models must be normalized to achieve comparability. In this embodiment, a certain overlapping area is reserved in the selected areas of adjacent models. When the same wind speed and wind direction are used as input conditions, the wind speed of one of the models can be normalized according to the wind speed value of the overlapping area.

[0108] Exemplarily, the specific steps of normalization are as follows: Let model A and model B be set A and set B respectively. ia is the wind speed v at any point in set A ia ∈A,v ib is the wind speed v at any point in set B ib ∈B, each point in the overlapping area A∩B=C of set A and set B has two calculated wind speeds, which are the wind speed v in model A and kca and the wind speed v in model B kcb Find point P in set C, whose corresponding wind speed in model A is the maximum wind speed v in set C apmax , under the same input conditions, the corresponding wind speed in model B is v bp The ratio of the two is k ba The wind speed at any point in model A is normalized to The wind speed at any point in model B is

[0109] For example, two models are selected and named Model A and Model B. Model A and Model B calculate the wind speed of each point in the model under the same wind speed and wind direction input conditions. The overlapping area of ​​Model A and Model B is named Area C. In Area C of Model A, point P with the largest wind speed is selected, and its wind speed value is v pa Similarly, we can find the corresponding point P in area C of model B, where the wind speed is v pb , then any point Q in model A a Wind speed v qa , the wind speed ratio is Any point Q in model B b Wind speed v qb , the wind speed ratio is

[0110] References Figure 8As shown in the line position and division diagram, although the entire railway is divided into several areas for calculation, the wind speed evaluation of the entire line is unified. It is necessary to solve the problem of normalizing the wind speed ratio between adjacent models. In this embodiment, a certain overlapping area is reserved in the selected area of ​​adjacent models. When the same wind speed and the same wind direction are used as input conditions, the wind speed of one model is normalized according to the wind speed value of the overlapping area.

[0111] In this embodiment, for railway lines that stretch for hundreds or even thousands of kilometers, segmented modeling is adopted to ensure the feasibility of the calculation scale. At the same time, a wind speed normalization method between segmented models is proposed, so that the calculation results of the segmented models can be uniformly compared.

[0112] In one embodiment, based on the maximum wind speed zone rule in all wind directions or the maximum probability zone rule for strong winds, the potential strong wind area in the wind farm is determined according to the calculation results and the wind monitoring layout position is determined, including: for a newly built railway, based on the maximum wind speed zone rule in all wind directions, the potential strong wind area in the wind farm is determined according to the calculation results and the wind monitoring layout position is determined; for an existing railway, based on the maximum probability zone rule for strong winds, the potential strong wind area in the wind farm is determined according to the calculation results and the wind monitoring layout position is determined.

[0113] In one embodiment, for a newly built railway, the potential high wind area in the wind field is determined and the wind monitoring layout position is determined based on the calculation results based on the maximum wind speed zone rule in all wind directions, including: for a newly built railway, the maximum wind speed occurring in each wind direction along the railway is counted according to the calculation results; the relative size of the maximum wind speed along the railway is compared, and the point where the maximum wind speed occurs within a section of the railway line is taken as the potential high wind area and the anemometer layout area; the wind monitoring layout position is determined according to the anemometer layout area.

[0114] In one embodiment, for existing railways, based on the high wind maximum probability area rule, the potential high wind area in the wind field is determined according to the calculation results and the wind monitoring layout position is determined, including: for existing railways, the prevailing wind direction of a known point and the probability of various levels of high winds occurring in the prevailing wind direction are calculated according to actual wind speed data; the wind speed probability distribution of each point along the railway in the prevailing wind direction of the known point is calculated according to the ratio relationship between adjacent points in the terrain model; and the point with the largest probability is selected as the potential high wind area and the wind monitoring layout position according to the wind speed probability distribution.

[0115] Specifically, for the calculation results under various wind directions, the maximum wind speed zone rule for all wind directions or the maximum probability zone rule for strong winds is used to determine the area in the wind field where the maximum wind speed is most likely to occur, and to determine the locations of the anemometers.

[0116] Exemplarily, the rule for the maximum wind speed zone in all wind directions is: when there is no meteorological data, the terrain model is used to simulate and calculate the wind field under 16 wind direction conditions. The maximum wind speed of any point in the terrain model under all wind directions is taken as the maximum wind speed of that point. The point where the maximum wind speed appears within a section of railway line is taken as the potential high wind area and anemometer distribution area.

[0117] For example, the rule of the maximum probability area of ​​strong winds: when there is existing wind speed data, the existing wind speed data is used to find the dominant wind direction at the location, and the probability of strong winds of various levels occurring under the dominant wind direction. Using the proportional relationship between adjacent points calculated in the wind field of this embodiment, the probability of strong winds occurring at each point along the railway under the dominant wind direction can be found, and the point with the highest probability of strong winds occurring is used as the potential strong wind point distribution area.

[0118] Specifically, for newly built railways, due to the lack of on-site measured wind data, the maximum wind speeds in all wind directions along the railway are counted based on the rule of the maximum wind speed zone in all wind directions, and then the relative size of the maximum wind speeds along the line is compared to determine the reasonable location of the points. For existing railways where wind monitoring points have been deployed, the wind speed distribution of known points is first calculated based on the actual wind speed data, and then the conversion relationship between the known points and the adjacent points is calculated to obtain the probability distribution of wind speeds at each point along the railway. Based on the rule of the maximum probability zone of strong winds, points with high probability of strong winds are selected as the locations for the wind monitoring points.

[0119] In this embodiment, two rules are proposed: the maximum wind speed zone rule for all wind directions and the maximum probability zone rule for strong winds, which are respectively applicable to the deployment of wind monitoring points without meteorological data and with meteorological data. Through the simulation calculation of the wind field of the entire line, the wind speed value and proportional relationship of each point in the wind field can be obtained in a numerical way. The maximum wind speed zone rule for all wind directions or the maximum probability zone rule for strong winds can be used to screen out potential strong wind areas, and points can be deployed according to the strong wind areas.

[0120] Compared with traditional technologies, this embodiment realizes the simulation calculation of the wind field of the entire railway line. The input conditions of the wind field distribution only require the longitude and latitude coordinates of the railway line position. It is suitable for both newly built railways and the assessment of potential high wind areas of existing railways. It has a wide range of applications and high accuracy.

[0121] In one example, a railway is used to evaluate the wind field using the method described in this embodiment as an example for detailed description. According to the measured longitude and latitude coordinates of the line, the DEM data set is downloaded, and the DEM data set is imported into the professional terrain software Global Mapper for further processing. The DEM data set is read using the Global Mapper software, the small-scale terrain of the specified area is clipped, and the plane coordinates and elevation data of the target area are extracted using the UTM projection and CGCS2000 benchmark (to ensure consistency with the coordinate system of the measuring point), and the horizontal resolution can be 30m. The terrain boundary is transitionally processed using the square cosine function, and a model (terrain model) with a horizontal size of 8000m×8000m is finally obtained. According to the size of the research object, considering that the flow field is fully developed vertically, the size of the calculated fluid domain in this example is: 16000m in the X direction (horizontal), 16000m in the Y direction (horizontal), and 5000m in the Z direction (vertical). Fluent Meshing is used to generate a full hexahedral structured grid. In order to ensure that the near-ground grid is fine enough, the number of grids is controlled at the same time to balance the calculation time. The horizontal size of the terrain model surface grid is 25m; the minimum size of the X and Y (horizontal) grids in the computational domain is 25m, and the grid extension rate is set to 1.2, gradually expanding from the terrain area to the outside; the minimum thickness of the Z (vertical) grid is 1m, which is the first layer of grid close to the ground, and the grid extension rate is 1.2; the final total number of volume grids is 9.22 million.

[0122] Determine the boundary conditions for the model calculation domain, set the inlet boundary as the velocity inlet boundary (velocity inlet), and the outlet as the free outlet boundary condition (outflow). On the top and both sides of the calculation domain, symmetric boundary conditions (symmetry) are used, and the bottom surface is the ground containing the terrain, and the no-slip wall boundary condition (wall) is used. The RANS calculation method is adopted, the standard model is used, and the SIMPLE algorithm is selected for computational fluid dynamics CFD iterative solution. With due north as 0°, due east as 90°, and a wind direction angle of 0°, it means that the incoming wind direction is due north. Considering the variability of natural wind direction and the impact of different incoming wind directions on the wind environment along the railway, this example calculates the wind direction starting from 0°, and sets a group every 22.5°, for a total of 16 groups.

[0123] In this example, for newly built railways, due to the lack of on-site measured wind data, the maximum wind speeds in each wind direction along the railway are counted, and then the relative size of the maximum wind speeds along the line is compared to determine the reasonable location of the points. For existing railways where wind monitoring points have been deployed, the wind speed distribution of known points is first calculated based on the actual wind speed data, and then the conversion relationship between the known points and adjacent points is calculated to obtain the probability distribution of wind speeds at each point along the railway, and points with a high probability of strong winds are selected as the locations for the wind monitoring points.

[0124] This embodiment provides a method for simulating a wind field and arranging wind monitoring points along a railway, including: constructing a circular 3D surface model along the railway according to the longitude and latitude data of the railway line based on geographic information technology; smoothing the transition area of ​​the circular 3D surface model using a square cosine function to obtain a terrain model; gridding the terrain model based on all wind directions and calculating using computational fluid dynamics to obtain calculation results; determining the potential high wind area in the wind field and determining the wind monitoring layout location based on the calculation results based on the maximum wind speed area rule for all wind directions or the maximum probability area rule for high winds. In this embodiment, geographic information technology is used to construct a digital 3D terrain model along the railway, and combined with computational fluid dynamics CFD technology and railway engineering characteristics, wind field simulation and high wind area assessment are performed to screen out potential high wind areas and realize wind monitoring layout location selection, which is suitable for the railway. No meteorological data is required, and it can be used for both newly built railways and wind field assessment of existing railways, with a wide range of applications.

[0125] In addition, an embodiment of the present invention also proposes a storage medium, on which a program for simulating wind farms along railways and deploying wind monitoring points is stored. When the program for simulating wind farms along railways and deploying wind monitoring points is executed by a processor, the steps of the method for simulating wind farms along railways and deploying wind monitoring points are implemented as described above.

[0126] Reference Fig. 9 , Fig. 9 The present invention is a structural block diagram of an embodiment of a system for simulating wind fields and monitoring wind monitoring points along railways.

[0127] like Fig. 9 As shown, the wind field simulation and wind monitoring point distribution system along the railway includes:

[0128] The model building module 10 is used to build a circular 3D surface model along the railway according to the longitude and latitude data of the railway line based on geographic information technology;

[0129] A smoothing processing module 20 is used to smooth the transition area of ​​the circular 3D surface model using a square cosine function to obtain a terrain model;

[0130] A grid division and calculation module 30, for gridding the terrain model based on all wind directions and performing calculations using computational fluid dynamics to obtain calculation results;

[0131] The rule determination module 40 is used to determine the potential high wind area in the wind farm and determine the wind monitoring layout position based on the maximum wind speed area rule in all wind directions or the high wind maximum probability area rule according to the calculation results.

[0132] Specifically, by simulating the wind field of the entire line, the wind speed value and proportional relationship of each point in the wind field can be obtained in a numerical manner. The potential strong wind area can be screened out by the maximum wind speed area rule of all wind directions or the maximum probability area rule of strong winds, and points can be arranged according to the strong wind area. Compared with the traditional technology, this embodiment realizes the simulation calculation of the wind field of the entire railway line. The input conditions of the wind field distribution only require the longitude and latitude coordinates of the railway line position. It is suitable for both new railways and existing railways in the potential strong wind area assessment, with a wide range of applications and high accuracy.

[0133] This embodiment provides a wind field simulation and wind monitoring point distribution system along the railway, which uses geographic information technology to build a digital 3D terrain model along the railway, combines computational fluid dynamics CFD technology and railway engineering characteristics, performs wind field simulation and high wind area assessment, can screen out potential high wind areas, and realize wind monitoring layout location selection, which is suitable for railways. No meteorological data is required, and it can be used for wind field assessment of new railways and existing railways, with a wide range of applications.

[0134] It should be noted that the technical details that are not described in detail in the embodiment of the system for simulating wind fields and deploying wind monitoring points along railways can be referred to the method for simulating wind fields and deploying wind monitoring points along railways as described above provided in any embodiment of the present invention, and will not be repeated here.

[0135] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0136] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0137] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0138] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0139] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0140] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for simulating wind fields and deploying wind monitoring points along a railway, characterized in that: include: Based on geographic information technology, a circular 3D surface model along the railway is constructed according to the longitude and latitude data of the railway line; The transition area of ​​the circular 3D surface model is smoothed by using a square cosine function to obtain a terrain model; The terrain model is meshed based on all wind directions and is calculated using computational fluid dynamics to obtain calculation results; Based on the maximum wind speed zone rule in all wind directions or the maximum probability zone rule for strong winds, the potential strong wind area in the wind farm is determined according to the calculation results and the wind monitoring layout position is determined.

2. The method according to claim 1, characterized in that The method of constructing a circular 3D surface model along the railway according to the longitude and latitude data of the railway line based on geographic information technology includes: Obtain the longitude and latitude data of railway lines; Querying and intercepting elevation data of a preset area in a global digital elevation model according to the longitude and latitude data of the railway line position; Divide the railway line into several areas along its length; Circular 3D surface models of several areas are respectively established based on the elevation data.

3. The method according to claim 2, characterized in that The circular 3D surface models of several regions are established based on the elevation data, including: Take the point on the railway line as the center and divide two concentric circles with the first radius and the second radius respectively; the first radius is larger than the second radius, the first radius is the modeling area, the second radius is the research area, and the annular area from the second radius to the first radius is the transition area; The elevation data is intercepted with the first radius, and circular 3D surface models of several areas are respectively established.

4. The method according to claim 1, characterized in that The terrain model is gridded based on all wind directions and is calculated using computational fluid dynamics to obtain calculation results, including: Placing the terrain model in a calculation domain; wherein the calculation domain is set in a cuboid, and the cuboid is a square in the horizontal direction; Determining the number of grid divisions based on the full wind direction and the computational domain; Based on the number of grid divisions, the computational domain is discretized using a structured hexahedral grid, and a dense grid is performed on a preset key area and a boundary layer of the railway line; After the grid is divided, computational fluid dynamics is used to calculate the terrain model respectively to obtain model calculation results under various wind directions; The model calculation results under the various wind directions are normalized to obtain calculation results.

5. The method according to claim 4, characterized in that The model calculation results under the various wind directions are normalized to obtain calculation results, including: Preserve overlapping areas in selected areas of adjacent terrain models; When the same wind speed and wind direction are used as input conditions, the wind speed of one of the adjacent terrain models is normalized according to the wind speed value of the overlapping area; All terrain models are normalized and the normalized results are used as calculation results.

6. The method according to claim 1, characterized in that The method of determining the potential high wind area in the wind farm and determining the wind monitoring arrangement position based on the maximum wind speed area rule in all wind directions or the high wind maximum probability area rule according to the calculation result includes: For newly built railways, based on the maximum wind speed zone rule in all wind directions, the potential high wind area in the wind field is determined according to the calculation results and the wind monitoring layout location is determined; For existing railways, the potential high wind area in the wind field is determined according to the calculation results based on the high wind maximum probability area rule and the wind monitoring layout position is determined.

7. The method according to claim 6, characterized in that For the newly built railway, based on the maximum wind speed zone rule in all wind directions, the potential high wind area in the wind field is determined according to the calculation results and the wind monitoring layout position is determined, including: For a newly built railway, the maximum wind speed occurring in each wind direction along the railway is counted according to the calculation results; Compare the relative magnitude of the maximum wind speed along the railway, and use the point with the maximum wind speed within a section of the railway as the potential high wind area and anemometer deployment area; The wind monitoring layout location is determined according to the anemometer layout area.

8. The method according to claim 6, characterized in that For the existing railway, based on the high wind maximum probability area rule, determining the potential high wind area in the wind field and determining the wind monitoring layout location according to the calculation result, includes: For existing railways, the prevailing wind direction at a known point and the probability of strong winds of various levels occurring in the prevailing wind direction are calculated based on actual wind speed data; According to the ratio relationship between adjacent points of the terrain model, the probability distribution of wind speed at each point along the railway under the dominant wind direction of the known point is calculated; According to the wind speed probability distribution, the point with the highest probability is selected as the potential high wind area and the wind monitoring layout location.

9. A wind field simulation and wind monitoring point distribution system along a railway, characterized in that: include: A model building module is used to construct a circular 3D surface model along the railway based on the longitude and latitude data of the railway line based on geographic information technology; A smoothing processing module, used for smoothing the transition area of ​​the circular 3D surface model using a square cosine function to obtain a terrain model; A grid division and calculation module, used to divide the terrain model into grids based on all wind directions and perform calculations using computational fluid dynamics to obtain calculation results; A rule determination module is used to determine the potential high wind area in the wind farm and determine the wind monitoring layout position based on the maximum wind speed area rule in all wind directions or the high wind maximum probability area rule according to the calculation results.

10. An electronic device, characterized in that: The electronic device includes: a memory, a processor, and a program for simulating wind fields and deploying wind monitoring points along railways stored in the memory and executable on the processor, wherein the program for simulating wind fields and deploying wind monitoring points along railways is configured to implement a method for simulating wind fields and deploying wind monitoring points along railways as described in any one of claims 1 to 8.

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