A wind shear detection method based on regional fitting, a computer device and a medium

Abstract

This invention belongs to the field of wind shear detection technology, specifically relating to a wind shear detection method, computer device, and medium based on region fitting. The method includes: S1, acquiring wind speed data within the detection area; S2, calculating radial shear, tangential shear, and vertical shear based on the wind speed data; S3, synthesizing the shear based on the radial, tangential, and vertical shear to obtain a synthesized shear, which is then used as the detected wind shear. This invention comprehensively considers radial, tangential, and vertical shear directions during shear synthesis, ensuring that the final synthesized shear is not limited to a single plane but can be obtained in any direction within three-dimensional space. This allows for a complete reflection of the three-dimensional spatial characteristics of wind shear, significantly improving the accuracy of wind shear detection. This invention solves the technical problem of inaccurate wind shear detection in existing technologies.

Description

Technical Field

[0001] This invention belongs to the field of wind shear detection technology, specifically relating to a wind shear detection method based on region fitting, as well as a computer device and medium. Background Technology

[0002] Wind shear is a meteorological phenomenon characterized by significant changes in wind speed and direction within a certain spatial range, typically occurring in the troposphere and atmospheric boundary layer. The formation mechanism of wind shear is closely related to factors such as local topography, weather systems, and thermal convection activity. Due to its sudden and localized nature, wind shear has a significant impact on aviation safety, wind farm operation, and meteorological observation.

[0003] In the aviation field, wind shear is considered one of the most important factors affecting the safety of aircraft takeoff and landing. Due to the strong airflow disturbances it generates, wind shear can cause sudden increases or decreases in lift, leading to deviations from the flight path or even loss of flight control, and ultimately causing serious flight accidents. Therefore, real-time detection and accurate identification of wind shear has become an important component of aviation meteorological early warning systems.

[0004] Laser wind radar, as an emerging wind field detection technology, can achieve high-resolution wind field observation based on the Doppler effect, and is particularly suitable for identifying near-surface wind shear. Compared with traditional weather radar, laser wind radar has higher spatial resolution and more sensitive low-elevation angle detection capability. However, due to the significant multi-scale variation characteristics of wind shear, existing wind shear detection methods often struggle to simultaneously meet the requirements of high-precision identification and real-time performance in complex low-altitude wind field environments, especially in the quantitative representation of wind shear intensity and direction, where significant technical challenges remain.

[0005] Traditional wind shear identification methods typically rely on wind speed gradient analysis in a single plane, such as radial and vertical wind speed variations, to reflect the intensity and direction of wind shear by calculating wind speed differences in a specific area. However, these methods have the following shortcomings: First, gradient analysis in a single plane cannot comprehensively reflect the three-dimensional characteristics of wind shear and easily overlooks the influence of tangential wind speed variations on wind shear; second, existing methods lack the ability to comprehensively weight multi-directional wind field data, making it difficult to accurately describe the actual intensity and direction of wind shear measured in a specific direction; third, under complex meteorological conditions, data noise and incompleteness can significantly reduce the reliability of the identification results.

[0006] A Chinese invention patent application with publication number CN115508862A and publication date of December 23, 2022, discloses a method for early warning of airport wind shear based on lidar. This method acquires raw wind field data through lidar scanning, performs preprocessing such as missing data filling and noise reduction, and then fits the wind field data using the least squares method to obtain the values ​​of range shear and azimuth shear. The range and azimuth shears are then combined, and wind shear warnings are issued based on the combined shear values. However, this method only obtains wind shear values ​​in a single planar direction and cannot reflect the three-dimensional characteristics of wind shear in space, leading to inaccurate wind shear detection. Summary of the Invention

[0007] The purpose of this invention is to provide a wind shear detection method, computer device, and medium based on region fitting, so as to solve the technical problem of inaccurate wind shear detection in the prior art.

[0008] To solve the above-mentioned technical problems, the present invention provides a wind shear detection method based on region fitting, the technical solution of which is as follows: A wind shear detection method based on region fitting, the method comprising:

[0009] S1. Obtain wind speed data within the area to be detected;

[0010] S2. Calculate the radial shear, tangential shear, and vertical shear based on the wind speed data.

[0011] S3. Based on the radial shear, tangential shear and vertical shear, shear synthesis is performed to obtain the synthesized shear, and the synthesized shear is used as the detected wind shear.

[0012] The beneficial effects of the above technical solution are as follows: The technical solution of the wind shear detection method based on region fitting of the present invention belongs to an improved invention. Unlike existing technologies, the present invention comprehensively considers radial shear, tangential shear, and vertical shear during shear synthesis. Based on these three directions, the final synthesized shear is not limited to a single plane, but can be obtained in any direction within three-dimensional space, thus fully reflecting the three-dimensional spatial characteristics of wind shear and greatly improving the accuracy of wind shear detection. The present invention solves the technical problem of inaccurate wind shear detection in existing technologies.

[0013] Furthermore, the radial shear, tangential shear, and vertical shear in S3 are all weighted radial shear, tangential shear, and vertical shear.

[0014] Furthermore, the shear synthesis method in S3 is as follows:

[0015]

[0016] a1 + a2 + a3 = 1

[0017] Among them, C s C1 represents the composite shear; C2 represents the radial shear; C3 represents the tangential shear; and a1, a2, and a3 represent the composite factors corresponding to the radial, tangential, and vertical shears, respectively.

[0018] Furthermore, during shear synthesis in S3, the weights corresponding to the radial shear, the tangential shear, and the vertical shear satisfy the following condition: the higher the absolute value of the shear, the greater the weight.

[0019] Furthermore, during shear synthesis in S3, the synthesis factors corresponding to the radial shear, the tangential shear, and the vertical shear are determined by the following formula:

[0020]

[0021] Where j = 1, 2, 3, representing the radial, shear, and vertical directions, respectively; a j V is the composition factor corresponding to the shear in direction j; mean,j Let C be the mean wind speed in the j-direction; j σ is the shear in the j-direction; σ is an adjustment factor used to adjust the influence of shear in different directions on the synthesized shear; θ is a scaling factor used to control V. mean,j The range of influence; ε is a constant used to prevent the denominator from being zero.

[0022] Furthermore, the wind speed data is radial wind speed data obtained through a wind-measuring radar; the radial shear, tangential shear, and vertical shear in S2 are calculated according to the following formula:

[0023]

[0024] Wherein, C1 is radial shear; C2 is tangential shear; C3 is vertical shear; b R The slope of the straight line obtained by fitting radial wind speed data to a straight line; b T The slope of the straight line obtained by fitting the tangential wind speed data; b v Δr is the slope of the straight line obtained by fitting the vertical wind speed data; Δr is the distance between the wind measurement points of the two wind speed data points; Δθ1 and Δθ2 are the angular differences between the wind measurement points of the two wind speed data points in the radial and tangential directions, respectively; L R The length of the wind-measuring radar data is r; r is the distance from the wind-measuring radar to the wind-measuring point. This represents the angular resolution of the wind-measuring radar.

[0025] Furthermore, the shear in the corresponding direction is calculated within a sliding window that slides in one direction, wherein the sliding window satisfies:

[0026] M + α × L = row_length

[0027] Where M is the size of the sliding window; L is the sliding step size of the sliding window in this direction; row_length is the number of wind measurement points in this direction; and α is an integer.

[0028] Furthermore, the wind speed data in S1 is the data after preprocessing the original wind measurement data, and the preprocessing includes outlier detection and missing value imputation.

[0029] Furthermore, the raw wind measurement data is obtained by performing a small-range, low-elevation PPI scan using a laser wind-measuring radar.

[0030] The present invention also provides a technical solution for a computer device: a computer device including a processor, the processor being used to execute a computer program to implement the steps of the wind shear detection method based on region fitting as described above.

[0031] The present invention also provides a technical solution for a computer-readable storage medium: a computer-readable storage medium having a computer program stored therein, the computer program being executed by a processor to implement the steps of the wind shear detection method based on region fitting as described above. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of region fitting in an embodiment of the wind shear detection method based on region fitting of the present invention;

[0033] Figure 2 This is a flowchart illustrating an embodiment of the wind shear detection method based on region fitting of the present invention. Detailed Implementation

[0034] Unlike existing technologies, this invention comprehensively considers radial shear, tangential shear, and vertical shear during shear synthesis. Based on these three directions, the final synthesized shear is not limited to a single plane but can be obtained in any direction within three-dimensional space. This allows for a complete reflection of the three-dimensional spatial characteristics of wind shear, significantly improving the accuracy of wind shear detection. This invention solves the technical problem of inaccurate wind shear detection in existing technologies.

[0035] Example of a wind shear detection method based on region fitting:

[0036] A wind shear detection method based on region fitting, such as Figure 2 As shown, the method includes:

[0037] S1. Obtain wind speed data within the area to be detected.

[0038] Specifically, in this embodiment, a small-range, low-elevation-angle PPI scan is performed using a laser wind-measuring radar to obtain the radial wind speed centered on the radar as the raw wind measurement data.

[0039] Then, the k-neighborhood frequency method is used to preprocess the original wind measurement data to obtain the preprocessed wind speed data as wind speed data information for detecting wind shear.

[0040] Specifically, the preprocessing in this embodiment uses the k-neighborhood frequency method, combined with singular value detection and missing value detection mechanisms, to realize singular value detection and missing value filling of radar data.

[0041] S2. Calculate the radial shear, tangential shear, and vertical shear based on the wind speed data.

[0042] In this embodiment, a sliding window is defined, and the least squares method is used to perform linear fitting on the wind speed data information within the sliding window, and the radial shear, tangential shear, and vertical shear are calculated.

[0043] In other implementations, other linear fitting methods can also be used for linear fitting, such as ridge regression, minimum absolute deviation regression, etc.

[0044] Taking a radial sliding window as an example, let the window size be M and the radial sliding step size be L. For the number of shear points to be calculated within each window, due to the sliding window mechanism, the number of calculation points is equal to L, and is uniformly represented by L. The settings for M and L must meet the following conditions:

[0045] M + α × L = row_length

[0046] Where M is the size of the sliding window; L is the sliding step size in the radial direction of the sliding window; row_length is the number of wind measurement points in that radial direction; and α is an integer. If there exists α∈Z such that M+α×L=row_length holds, then the sliding window is set with the values ​​of M and L at that time. Z is the set of all integers.

[0047] At the same time, there is a critical situation where the shear value calculation of all observation points (excluding the two edge points) within the window is satisfied when L = M - 2. Users can select the values ​​of M and L by considering accuracy and speed. However, the values ​​of M and L should not be too large, otherwise the detection of local wind shear characteristics will be lost.

[0048] The slope of the fitted line obtained by the least squares fitting method is:

[0049]

[0050] Where b1 is the calculation of the slope of the fitted straight line in the radial direction, and v i r represents the radial wind speed value at the i-th wind measurement point within the window. i b1 represents the actual distance from the i-th wind measurement point within the window to the radar radial direction; b2 is the calculation of the slope of the fitted straight line in the tangential and vertical directions, θ i Let represent the azimuth angle of the i-th wind measuring point within the window; n is the number of wind measuring points within the window. Then, calculate the radial shear, tangential shear, and vertical shear according to the following formula:

[0051]

[0052] Wherein, C1 is radial shear; C2 is tangential shear; C3 is vertical shear; b R b is the slope of the straight line obtained by least squares fitting in the radial direction; T b is the slope of the line obtained by fitting the line along the tangent using the least squares method; v Δr is the slope of the straight line obtained by least squares fitting in the vertical direction; Δr is the distance between the wind measurement points of the two wind speed data points; Δθ1 and Δθ2 are the angular differences between the wind measurement points of the two wind speed data points in the radial and tangential directions, respectively; L R The length of the wind-measuring radar data is r; r is the distance from the wind-measuring radar to the wind-measuring point. The distance from the wind shear point to the measuring point is used to determine the wind shear direction. The sign of C1, C2, and C3 can be used to determine the direction of the wind shear.

[0053] like Figure 1 As shown, taking radial shear as an example: L R Let Δr be the distance between two wind speed measurement points, and ΔR be the representative distance of the actual wind speed range at that measurement point. The slope of the radial fit is calculated using formula b1 above. The radial shear value is calculated using formula C1, where ΔR = Δr + L. R .

[0054] S3. Based on radial shear, tangential shear and vertical shear, shear synthesis is performed to obtain a composite shear, which is used as the detected wind shear.

[0055] In this embodiment, to reflect the influence of shear in different directions on the final synthesized shear, the radial shear, tangential shear, and vertical shear are weighted before shear synthesis.

[0056] Specifically, this embodiment performs shear synthesis in the following manner:

[0057]

[0058] a1 + a2 + a3 = 1

[0059] Among them, C s C1 represents the composite shear; C2 represents the radial shear; C3 represents the tangential shear; and a1, a2, and a3 represent the composite factors (i.e., the composite factors corresponding to the radial, tangential, and vertical shears, respectively). Figure 2 (α1, α1, and α1 in the text).

[0060] It should be noted that the weight β mentioned above is related to the composition factor a. j The relationship is:

[0061] In this embodiment, the weights corresponding to radial shear, tangential shear, and vertical shear satisfy the following condition: the higher the absolute value of the shear, the greater the weight.

[0062] Furthermore, in this embodiment, the weights a1, a2, and a3 are determined as follows:

[0063]

[0064] Where j = 1, 2, 3, representing the radial, shear, and vertical directions, respectively; V mean,j Let C be the mean wind speed in the j-direction; j σ is the shear in the j-direction; σ is an adjustment factor used to adjust the influence of shear in different directions on the synthesized shear; θ is a scaling factor used to control V. mean,j The scope of its influence.

[0065] To prevent the denominator from being zero during calculation, a very small constant ε is added to the denominator to prevent division by zero errors. The formulas for calculating weights a1, a2, and a3 are as follows:

[0066]

[0067] In other embodiments, shear synthesis can also refer to the shear synthesis method in the patent document with publication number CN115508862A, and synthesize directly without weighting. Alternatively, the weights a1, a2, and a3 can be determined in other ways, such as based on experience.

[0068] Calculate the synthetic shear C s Subsequently, synthetic shear C s As the detected wind shear, the wind shear (i.e., C) sThe wind shear threshold is compared with a preset wind shear threshold to provide a wind shear warning. Specific wind shear warning methods can be found in existing technologies, and will not be described in detail in this embodiment. The wind shear threshold can be set according to the type and size of the aircraft and the detection requirements.

[0069] Computer device embodiment:

[0070] A computer device includes a processor for executing a computer program to implement the steps of the region-fitting-based wind shear detection method as described above. The specific region-fitting-based wind shear detection method has been described in sufficient detail in the above-described embodiments and will not be repeated here.

[0071] Specifically, a processor can be a CPU, or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. A processor can also be a processor that supports the Advanced Reduced Instruction Set Machine (ARM) architecture.

[0072] Examples of computer-readable storage media:

[0073] A computer-readable storage medium stores a computer program internally, the computer program being executed by a processor to implement the steps of the region-fit-based wind shear detection method as described above. The specific region-fit-based wind shear detection method has been described in sufficient detail in the above-described embodiments and will not be repeated here.

[0074] Specifically, the computer-readable storage medium can be volatile memory or non-volatile memory, or may include both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which serves as an external cache. For example, Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), SynchLink DRAM (SLDRAM), or Direct Rambus RAM (DRRAM).

[0075] This invention has the following characteristics:

[0076] This invention utilizes wind field data from low elevation angle regions to accurately describe the intensity and direction of wind shear through comprehensive calculation of radial, tangential, and vertical wind shear values. By comprehensively considering the shear magnitude and average wind speed, it introduces factors a1, a2, and a3 to achieve weighted shear synthesis, thereby addressing the insufficient comprehensive identification capability of multi-directional wind shear in existing technologies. Furthermore, this method combines shear threshold analysis to provide a visual display of wind shear intensity and direction, thus meeting the real-time detection needs of multiple scenarios and aircraft types, demonstrating significant technical advantages and broad application prospects.

[0077] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still make modifications to the technical solutions described in the foregoing embodiments without creative effort, or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A wind shear detection method based on region fitting, characterized in that, The method includes: S1. Obtain wind speed data within the area to be detected; S2. Calculate the radial shear, tangential shear, and vertical shear based on the wind speed data. S3. Based on the radial shear, tangential shear and vertical shear, shear synthesis is performed to obtain the synthesized shear, and the synthesized shear is used as the detected wind shear.

2. The wind shear detection method based on region fitting according to claim 1, characterized in that, The radial shear, tangential shear, and vertical shear in S3 are all weighted radial shear, tangential shear, and vertical shear.

3. The wind shear detection method based on region fitting according to claim 1, characterized in that, The method of shear synthesis in S3 is as follows: a1 + a2 + a3 = 1 Among them, C s C1 represents the composite shear; C2 represents the radial shear; C3 represents the tangential shear; and a1, a2, and a3 represent the composite factors corresponding to the radial, tangential, and vertical shears, respectively.

4. The wind shear detection method based on region fitting according to claim 2, characterized in that, When shear synthesis is performed in S3, the weights corresponding to the radial shear, the tangential shear, and the vertical shear satisfy the following condition: the higher the absolute value of the shear, the greater the weight.

5. The wind shear detection method based on region fitting according to claim 3, characterized in that, When shear synthesis is performed in S3, the synthesis factors corresponding to the radial shear, the tangential shear, and the vertical shear are determined by the following formula: Where j = 1, 2, 3, representing the radial, shear, and vertical directions, respectively; a j V is the composition factor corresponding to the shear in direction j; mean,j Let C be the mean wind speed in the j-direction; j σ is the shear in the j-direction; σ is an adjustment factor used to adjust the influence of shear in different directions on the synthesized shear; θ is a scaling factor used to control V. mean,j The range of influence; ε is a constant used to prevent the denominator from being zero.

6. The wind shear detection method based on region fitting according to claim 1, characterized in that, The wind speed data is radial wind speed data obtained by wind-measuring radar; the radial shear, tangential shear, and vertical shear in S2 are calculated according to the following formula: Wherein, C1 is radial shear; C2 is tangential shear; C3 is vertical shear; b R The slope of the straight line obtained by fitting radial wind speed data to a straight line; b T The slope of the straight line obtained by fitting the tangential wind speed data; b v Δr is the slope of the straight line obtained by fitting the vertical wind speed data; Δr is the distance between the wind measurement points of the two wind speed data points; Δθ1 and Δθ2 are the angular differences between the wind measurement points of the two wind speed data points in the radial and tangential directions, respectively; L R The length of the wind-measuring radar data is r; r is the distance from the wind-measuring radar to the wind-measuring point. This represents the angular resolution of the wind-measuring radar.

7. The wind shear detection method based on region fitting according to claim 1, characterized in that, The shear in a given direction is calculated within a sliding window that slides in one direction, wherein the sliding window satisfies: M + α × L = row_length Where M is the size of the sliding window; L is the sliding step size of the sliding window in this direction; row_length is the number of wind measurement points in this direction; and α is an integer.

8. The wind shear detection method based on region fitting according to claim 1, characterized in that, The wind speed data in S1 is the data after preprocessing the original wind measurement data. The preprocessing includes outlier detection and missing value imputation.

9. The wind shear detection method based on region fitting according to claim 8, characterized in that, The raw wind measurement data was obtained by performing a small-range, low-elevation-angle PPI scan using a laser wind measuring radar.

10. A computer device comprising a processor, characterized in that, The processor is used to execute a computer program to implement the steps of the wind shear detection method based on region fitting as described in any one of claims 1 to 9.

11. A computer-readable storage medium, wherein a computer program is stored internally, characterized in that, The computer program is executed by a processor to implement the steps of the wind shear detection method based on region fitting as described in any one of claims 1 to 9.

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