A flight low-level wind shear early warning method

Abstract

The application belongs to the technical field of meteorological monitoring, and discloses a flight low-altitude wind shear early warning method; meteorological data sets and environmental data sets are collected and pretreated, the meteorological data sets include wind speed data and atmospheric stability data, and the environmental data sets include terrain height data and ground roughness data; the meteorological data sets and the environmental data sets are processed to obtain wind shear prediction reference values, and classification is performed to obtain wind shear prediction results; the wind shear prediction results are analyzed to obtain wind shear decision results; the wind shear decision results are displayed, and the ground meteorological management platform is connected to query meteorological information in a specified ground area; and overall, the application has the remarkable advantages of strong auxiliary prediction capability, good auxiliary decision effect and great flight safety improvement.

Description

Technical Field

[0001] This invention relates to the field of meteorological monitoring technology, and more specifically, to a method for early warning of low-altitude wind shear for flights. Background Technology

[0002] Wind shear is an atmospheric phenomenon, representing the change in wind vectors (wind direction and speed) over horizontal and / or vertical distances in the air. Wind shear can be categorized by wind direction into horizontal wind shear, vertical wind shear, and vertical wind shear. The presence of vertical wind shear can damage bridges, tall buildings, and aircraft. Low-altitude wind shear is a significant hazard during aircraft takeoff and landing, often referred to as an "invisible killer." With my country's rapid economic development in recent years, aviation, as a highly efficient mode of transportation, has become increasingly popular. During aviation, aircraft are susceptible to various factors, among which wind shear, as an atmospheric phenomenon, can easily become a major hazard.

[0003] Patent application CN115862388B discloses a method, device, equipment, and storage medium for low-altitude wind shear warning of flights. It obtains the wind shear warning point of the target airport through the flight approach procedure, receives ADS-B messages sent by the target flight, and tracks the target flight's position in real time based on the ADS-B messages. When the target flight is detected to have passed the wind shear warning point and low-altitude wind shear exists at the target airport, a low-altitude wind shear warning is issued. Therefore, when implementing the low-altitude wind shear warning function, the above method only issues a low-altitude wind shear warning when both the target flight has passed the wind shear warning point and low-altitude wind shear exists at the target airport, reducing the false alarm rate.

[0004] However, although the aforementioned method, device, equipment, and storage medium for low-altitude wind shear warning of flights have a certain degree of warning effect on ground wind shear based on meteorological data provided by the ground, they are difficult to solve the problem of the rapid response required by the staff when wind shear occurs during flight take-off and landing. Wind shear usually causes the aircraft to shake, stall, or be pushed. Such sudden situations can easily cause people to lose their ability to think for a short period of time, making it difficult to quickly change the state of the fuselage to deal with wind shear, which can easily lead to major flight accidents.

[0005] In view of this, the present invention proposes a method for early warning of low-altitude wind shear for flights to solve the above problems. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: including:

[0007] The data acquisition module is used to collect meteorological and environmental datasets and perform preprocessing. The meteorological dataset includes wind speed data and atmospheric stability data, while the environmental dataset includes terrain height data and surface roughness data.

[0008] Furthermore, methods for collecting meteorological and environmental datasets include:

[0009] By installing an anemometer, wind speed data is obtained by collecting wind speeds at a preset height within a designated area.

[0010] By connecting to a meteorological platform, the rate of temperature change with altitude within a designated area is collected to obtain atmospheric stability data;

[0011] By installing a laser rangefinder, terrain height data is obtained by collecting the terrain height within a designated area.

[0012] By installing a laser scanner, roughness indicators of the ground undulation within a designated area are collected to obtain surface roughness data;

[0013] Preprocessing methods include data cleaning, data denoising, and data normalization;

[0014] The data processing module is used to process meteorological and environmental datasets to obtain wind shear prediction reference values, classify them, and obtain wind shear prediction results.

[0015] Furthermore, the steps for processing the meteorological and environmental datasets include:

[0016] Q1: By substituting into the calculation formula: The wind shear reference value is obtained, where Aa is the vertical wind shear coefficient, Ab is the wind speed at the reference height, Ac is the wind speed data, Ad is the reference height, and Ae is the correction coefficient.

[0017] Q2: Collect K sets of historical wind shear reference values ​​as a sample set, and divide the sample set into a 70%K training set, a 15%K test set, and a 15%K validation set;

[0018] Q3: Establish a wind shear classification model based on the training set, obtain historical wind shear reference values ​​in the training set, preset low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3, and randomly select three data points in the training set as primary cluster centers to represent low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3 respectively.

[0019] Q4: By substituting into the calculation formula The distances between data items are obtained. The distances between data items in the training set and the low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3 are calculated respectively. The data items are then assigned to the nearest primary cluster center to obtain three intermediate cluster centers. Here, x and y are the coordinates of the data points, xb and yb are the values ​​of the two data points on b sub-data items respectively, and m is the number of primary cluster centers.

[0020] Q5: Calculate the mean of the three intermediate cluster centers respectively, and use them as the new primary cluster centers for recalculation;

[0021] Q6: Repeat Q4 and Q5 until the preset number of iterations is reached to obtain the wind shear degree classification model;

[0022] Q7: Input the wind shear reference value into the wind shear degree classification model, and output the wind shear prediction reference value;

[0023] Furthermore, the methods of classification include:

[0024] A preset intensity threshold range (W1, W2) is set. When the wind shear prediction reference value is less than W1, an attention signal is generated. When the wind shear prediction reference value is greater than W1 and less than W2, a warning signal is generated. When the wind shear prediction reference value is greater than W2, an emergency warning signal is generated.

[0025] The attention signal contains a set of fields representing low wind shear intensity, the warning signal contains a set of fields representing medium wind shear intensity, and the emergency warning signal contains a set of fields representing high wind shear intensity.

[0026] By packaging attention signals, warning signals, and emergency warning signals, wind shear prediction results can be obtained.

[0027] The wind shear early warning module is used to analyze the wind shear prediction results and obtain wind shear decision results;

[0028] Furthermore, methods for analyzing wind shear prediction results include:

[0029] When the wind shear prediction result is a warning signal, a warning SMS message is sent to the staff receiving end through the communication unit; when the wind shear prediction result is a warning signal, a warning SMS message is sent to the staff receiving end through the communication unit; when the wind shear prediction result is an emergency warning signal, an emergency warning SMS message is sent to the staff receiving end through the communication unit.

[0030] The text message should include a notice that we are about to enter a low-speed wind shear area, reminding staff to take appropriate measures, listen to ground weather reports, and pay close attention to any abnormal instrument readings.

[0031] The warning text message includes an explanation that the area ahead is about to enter a medium-speed wind shear zone. During the takeoff phase, staff are required to be alert to airspeed fluctuations, use maximum takeoff thrust, and read deviations from the vertical flight trajectory instruments. During the landing phase, staff are required to choose a runway that can avoid the wind shear zone, increase the airspeed correction appropriately, or suddenly increase the airspeed.

[0032] Emergency warning text messages include instructions to temporarily abort the flight during takeoff and to stop the landing and perform a go-around during descent.

[0033] Pack attention SMS, warning SMS and emergency warning SMS to obtain wind shear decision results;

[0034] The user interface module is used to display wind shear decision results and query meteorological information for a specified area on the ground by connecting to the ground meteorological management platform;

[0035] Further, S1: Collect meteorological datasets and environmental datasets, and perform preprocessing. The meteorological datasets include wind speed data and atmospheric stability data, and the environmental datasets include terrain height data and surface roughness data.

[0036] S2: Process the meteorological and environmental datasets to obtain wind shear prediction reference values, classify them, and obtain wind shear prediction results;

[0037] S3: Analyze the wind shear prediction results to obtain the wind shear decision results;

[0038] S4: Displays wind shear decision results and queries meteorological information for a designated area on the ground by connecting to the ground meteorological management platform.

[0039] The technical effects and advantages of the low-altitude wind shear early warning method for flights according to the present invention are as follows:

[0040] This invention, through processing meteorological and environmental datasets, obtains wind shear prediction reference values ​​that can assist personnel in predicting the occurrence and intensity of wind shear. Analysis of the wind shear prediction results yields wind shear decision-making results, which can help personnel quickly implement countermeasures based on the intensity of wind shear, thereby significantly reducing the possibility of flight accidents. The user interface module allows for the display, alerts, and querying of the intensity and location of wind shear, greatly reducing the safety threat posed by wind shear to aircraft. Overall, this invention has significant advantages in terms of strong predictive capabilities, effective decision-making support, and substantial improvement in flight safety. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of a flight low-altitude wind shear early warning system according to the present invention;

[0042] Figure 2 This is a schematic diagram of a flight low-altitude wind shear early warning method according to the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Example 1

[0045] Please see Figure 1 As shown in this embodiment, a flight low-altitude wind shear early warning system includes:

[0046] The data acquisition module is used to collect meteorological and environmental datasets and perform preprocessing. The meteorological dataset includes wind speed data and atmospheric stability data, while the environmental dataset includes terrain height data and surface roughness data.

[0047] Furthermore, methods for collecting meteorological and environmental datasets include:

[0048] By installing an anemometer, wind speed data is obtained by collecting wind speeds at a preset height within a designated area.

[0049] By connecting to a meteorological platform, the rate of temperature change with altitude within a designated area is collected to obtain atmospheric stability data;

[0050] By installing a laser rangefinder, terrain height data is obtained by collecting the terrain height within a designated area.

[0051] By installing a laser scanner, roughness indicators of the ground undulation within a designated area are collected to obtain surface roughness data;

[0052] Preprocessing methods include data cleaning, data denoising, and data normalization;

[0053] The data processing module is used to process meteorological and environmental datasets to obtain wind shear prediction reference values, classify them, and obtain wind shear prediction results.

[0054] Further steps in processing the meteorological and environmental datasets include:

[0055] Q1: By substituting into the calculation formula: The wind shear reference value is obtained, where Aa is the vertical wind shear coefficient, Ab is the wind speed at the reference height, Ac is the wind speed data, Ad is the reference height, and Ae is the correction coefficient.

[0056] It should be explained that the vertical wind shear coefficient is the value obtained by weighted multiplication of atmospheric stability data and surface roughness data, and the correction coefficient is a correction value composed of time variation, wind direction variation, atmospheric stability data, terrain height data and surface roughness data.

[0057] Q2: Collect K sets of historical wind shear reference values ​​as a sample set, and divide the sample set into a 70%K training set, a 15%K test set, and a 15%K validation set;

[0058] Q3: Establish a wind shear classification model based on the training set, obtain historical wind shear reference values ​​in the training set, preset low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3, and randomly select three data points in the training set as primary cluster centers to represent low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3 respectively.

[0059] Q4: By substituting into the calculation formula The distances between data items are obtained. The distances between data items in the training set and the low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3 are calculated respectively. The data items are then assigned to the nearest primary cluster center to obtain three intermediate cluster centers. Here, x and y are the coordinates of the data points, xb and yb are the values ​​of the two data points on b sub-data items respectively, and m is the number of primary cluster centers.

[0060] Q5: Calculate the mean of the three intermediate cluster centers respectively, and use them as the new primary cluster centers for recalculation;

[0061] Q6: Repeat Q4 and Q5 until the preset number of iterations is reached to obtain the wind shear degree classification model;

[0062] Q7: Input the wind shear reference value into the wind shear degree classification model, and output the wind shear prediction reference value;

[0063] Furthermore, the methods of classification include:

[0064] A preset intensity threshold range (W1, W2) is set. When the wind shear prediction reference value is less than W1, an attention signal is generated. When the wind shear prediction reference value is greater than W1 and less than W2, a warning signal is generated. When the wind shear prediction reference value is greater than W2, an emergency warning signal is generated.

[0065] The attention signal contains a set of fields representing low wind shear intensity, the warning signal contains a set of fields representing medium wind shear intensity, and the emergency warning signal contains a set of fields representing high wind shear intensity.

[0066] By packaging attention signals, warning signals, and emergency warning signals, wind shear prediction results can be obtained.

[0067] The wind shear early warning module is used to analyze the wind shear prediction results and obtain wind shear decision results;

[0068] Furthermore, methods for analyzing wind shear prediction results include:

[0069] When the wind shear prediction result is a warning signal, a warning SMS message is sent to the staff receiving end through the communication unit; when the wind shear prediction result is a warning signal, a warning SMS message is sent to the staff receiving end through the communication unit; when the wind shear prediction result is an emergency warning signal, an emergency warning SMS message is sent to the staff receiving end through the communication unit.

[0070] The text message should include a notice that we are about to enter a low-speed wind shear area, reminding staff to take appropriate measures, listen to ground weather reports, and pay close attention to any abnormal instrument readings.

[0071] The warning text message includes an explanation that the area ahead is about to enter a medium-speed wind shear zone. During the takeoff phase, staff are required to be alert to airspeed fluctuations, use maximum takeoff thrust, and read deviations from the vertical flight trajectory instruments. During the landing phase, staff are required to choose a runway that can avoid the wind shear zone, increase the airspeed correction appropriately, or suddenly increase the airspeed.

[0072] Emergency warning text messages include instructions to temporarily abort the flight during takeoff and to stop the landing and perform a go-around during descent.

[0073] Pack attention SMS, warning SMS and emergency warning SMS to obtain wind shear decision results;

[0074] The user interface module is used to display wind shear decision results and query meteorological information for a specified area on the ground by connecting to the ground meteorological management platform;

[0075] In this embodiment, the beneficial effects are that by processing meteorological and environmental datasets, the wind shear prediction reference value obtained can assist staff in predicting the occurrence of wind shear and judging its intensity. By analyzing the wind shear prediction results, the resulting wind shear decision-making results can assist staff in quickly taking countermeasures based on the intensity of the wind shear, thereby greatly reducing the possibility of flight accidents. Through the established user interface module, the intensity and location of wind shear can be displayed, reminded, and queried, greatly reducing the safety threat of wind shear to aircraft. Overall, this invention has significant advantages in terms of strong auxiliary prediction capability, good auxiliary decision-making effect, and significant improvement in flight safety.

[0076] Example 2

[0077] Please see Figure 2 As shown, the parts not described in detail in this embodiment are described in Embodiment 1. A method for early warning of low-altitude wind shear for flights is provided, including: S1: collecting meteorological datasets and environmental datasets and performing preprocessing. The meteorological datasets include wind speed data and atmospheric stability data, and the environmental datasets include terrain height data and surface roughness data.

[0078] S2: Process the meteorological and environmental datasets to obtain wind shear prediction reference values, classify them, and obtain wind shear prediction results;

[0079] S3: Analyze the wind shear prediction results to obtain the wind shear decision results;

[0080] S4: Displays wind shear decision results and queries meteorological information for a designated area on the ground by connecting to the ground meteorological management platform.

[0081] Example 3

[0082] This embodiment discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the operation mode of the flight low-altitude wind shear early warning method described above.

[0083] Since the electronic device described in this embodiment is the electronic device used to implement the flight low-altitude wind shear warning method in this application embodiment, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the flight low-altitude wind shear warning method described in this application embodiment. Therefore, how the electronic device implements the method in this application embodiment will not be described in detail here. Any electronic device used by those skilled in the art to implement the flight low-altitude wind shear warning method in this application embodiment falls within the scope of protection of this application.

[0084] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0085] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for users of ordinary technical skills, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A flight low-altitude wind shear early warning system, characterized in that, include: The data acquisition module is used to collect meteorological and environmental datasets and perform preprocessing. The meteorological dataset includes wind speed data and atmospheric stability data, while the environmental dataset includes terrain height data and surface roughness data. The data processing module is used to process meteorological and environmental datasets to obtain wind shear prediction reference values, classify them, and obtain wind shear prediction results. The wind shear early warning module is used to analyze the wind shear prediction results and obtain wind shear decision results; The user interface module is used to display wind shear decision results and query meteorological information for a specified area on the ground by connecting to the ground meteorological management platform; Methods for collecting meteorological and environmental datasets include: By installing an anemometer, wind speed data is obtained by collecting wind speeds at a preset height within a designated area. By connecting to a meteorological platform, the rate of temperature change with altitude within a designated area is collected to obtain atmospheric stability data; By installing a laser rangefinder, terrain height data is obtained by collecting the terrain height within a designated area. By installing a laser scanner, roughness indicators of the ground undulation within a designated area are collected to obtain surface roughness data; Preprocessing methods include data cleaning, data denoising, and data normalization; The steps for processing meteorological and environmental datasets include: Q1: By substituting into the calculation formula: The wind shear reference value is obtained, where denoted as the vertical wind shear coefficient. For reference altitude wind speed, Wind speed data, For reference height, This is a correction factor; Q2: Collect K sets of historical wind shear reference values ​​as a sample set, and divide the sample set into a 70%K training set, a 15%K test set, and a 15%K validation set; Q3: Establish a wind shear classification model based on the training set, obtain historical wind shear reference values ​​in the training set, preset low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3, and randomly select three data points in the training set as primary cluster centers to represent low-speed data cluster M1, medium-speed data cluster M2 and high-speed data cluster M3 respectively. Q4: By substituting into the calculation formula The distances between data items are obtained. The distances between each data item in the training set and the low-speed data cluster M1, medium-speed data cluster M2, and high-speed data cluster M3 are calculated. Each data item is then assigned to the nearest primary cluster center, resulting in three intermediate cluster centers. and These are the coordinates of the data points. and For the two data points respectively at The values ​​of each sub-data item The number of primary cluster centers; Q5: Calculate the mean of the three intermediate cluster centers respectively, and use them as the new primary cluster centers for recalculation; Q6: Repeat Q4 and Q5 until the preset number of iterations is reached to obtain the wind shear degree classification model; Q7: Input the wind shear reference value into the wind shear degree classification model, and get the wind shear prediction reference value as the output.

2. The flight low-altitude wind shear early warning system according to claim 1, characterized in that, The methods of classification include: A preset intensity threshold range (W1, W2) is set. When the wind shear prediction reference value is less than W1, an attention signal is generated. When the wind shear prediction reference value is greater than W1 and less than W2, a warning signal is generated. When the wind shear prediction reference value is greater than W2, an emergency warning signal is generated. The attention signal contains a set of fields representing low wind shear intensity, the warning signal contains a set of fields representing medium wind shear intensity, and the emergency warning signal contains a set of fields representing high wind shear intensity. By packaging attention signals, warning signals, and emergency warning signals, wind shear prediction results are obtained.

3. The flight low-altitude wind shear early warning system according to claim 2, characterized in that, Methods for analyzing wind shear prediction results include: When the wind shear prediction result is a warning signal, a warning SMS message is sent to the staff receiving end through the communication unit; when the wind shear prediction result is a warning signal, a warning SMS message is sent to the staff receiving end through the communication unit; when the wind shear prediction result is an emergency warning signal, an emergency warning SMS message is sent to the staff receiving end through the communication unit. The text message should include a notice that a low-speed wind shear area is approaching, reminding staff to take appropriate measures, listen to ground weather reports, and closely monitor instruments for any abnormal conditions. The warning text message includes an explanation that the area ahead is about to enter a medium-speed wind shear zone. During the takeoff phase, staff are required to be alert to airspeed fluctuations, use maximum takeoff thrust, and read deviations from the vertical flight trajectory instruments. During the landing phase, staff are required to choose a runway that can avoid the wind shear zone, increase the airspeed correction appropriately, or suddenly increase the airspeed. Emergency warning text messages include instructions to temporarily abort the flight during takeoff and to stop the landing and perform a go-around during descent. Pack up attention text messages, warning text messages, and emergency warning text messages to obtain wind shear decision results.

4. A method for early warning of low-altitude wind shear for flights, implemented according to any one of the flight low-altitude wind shear early warning systems described in claims 1-3, characterized in that, S1: Collect meteorological and environmental datasets and preprocess them. The meteorological dataset includes wind speed data and atmospheric stability data, and the environmental dataset includes terrain height data and surface roughness data. S2: Process the meteorological and environmental datasets to obtain wind shear prediction reference values, classify them, and obtain wind shear prediction results; S3: Analyze the wind shear prediction results to obtain the wind shear decision results; S4: Displays wind shear decision results and queries meteorological information for a designated area on the ground by connecting to the ground meteorological management platform.

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