Flight risk identification method, device and electronic equipment

Abstract

The application discloses a flight flight risk identification method and device and electronic equipment, relates to the technical field of data processing, and aims to improve the accuracy of flight flight risk identification results. The method comprises the following steps: in response to receiving a regional risk determination instruction, obtaining a target static temperature jump number and a target vertical overload jump number corresponding to a target region indicated in the regional risk determination instruction; the target static temperature jump number is used to represent the number of times of abnormal static temperature parameters of an airplane when the airplane runs in the target region; the target vertical overload jump number is used to represent the number of times of abnormal vertical overload parameters of the airplane when the airplane runs in the target region; and based on the target static temperature jump number and the target vertical overload jump number, a weather abnormal risk corresponding to the target region is determined.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus and electronic device for identifying flight risks. Background Technology

[0002] With the rapid development of the civil aviation industry, the number of flights is increasing day by day, and the area covered by flight operations is also becoming wider and wider. The risks of flight operations are inevitable, and the identification of risks during flight is directly related to the airline's operational efficiency and customer experience.

[0003] Currently, flight risk warning methods based on relevant technologies primarily rely on the personal experience and knowledge of risk assessment experts to analyze flight conditions and determine flight risks. Because these methods depend on the capabilities and subjective understanding of risk assessment experts, the identified flight risks are highly subjective, resulting in low accuracy. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, and electronic device for identifying flight risks, aiming to solve the problem of how to improve the accuracy of flight risk identification results.

[0005] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application provides a method for identifying flight risks, including, in response to receiving a regional risk determination instruction, acquiring the number of target static temperature jumps and the number of target vertical overload jumps corresponding to the target area indicated in the regional risk determination instruction; the number of target static temperature jumps is used to indicate the number of times the static temperature parameters of the aircraft are abnormal when operating in the target area; the number of target vertical overload jumps is used to indicate the number of times the vertical overload parameters of the aircraft are abnormal when operating in the target area; and determining the weather abnormality risk corresponding to the target area based on the number of target static temperature jumps and the number of target vertical overload jumps.

[0006] Based on the aforementioned technical means, the technical solution provided in this application takes into account the jump in static temperature parameters of an aircraft before and after encountering a lightning strike; that is, the number of static temperature jumps can accurately reflect the probability of an aircraft encountering a lightning strike risk. Simultaneously, it also notes that the vertical overload parameters of an aircraft will jump before and after encountering turbulence; therefore, the number of vertical overload jumps can accurately reflect the probability of an aircraft encountering turbulence risk. Based on this, after receiving a regional risk determination instruction, by acquiring the number of static temperature jumps and vertical overload jumps in the target area, the lightning strike risk and abnormal airflow risk faced by the aircraft while flying in the target area can be accurately determined. This allows for an accurate assessment of the weather anomaly risk in the target area, improving the accuracy of flight risk results.

[0007] In one possible approach, an abnormal static temperature parameter is used to indicate that there is a change in the static temperature parameter within a preset window that exceeds a first threshold.

[0008] In one possible approach, the method further includes: acquiring at least one aircraft operating data, including: static temperature parameter changes, vertical overload parameter changes, and position changes; for each aircraft operating data, determining static temperature jump data based on the static temperature parameter changes and position changes; the static temperature jump data is used to represent the position information of the aircraft each time a static temperature jump occurs; for each aircraft operating data, determining vertical overload jump data based on the vertical overload parameter changes and position changes, the vertical overload jump data is used to represent the position information of the aircraft each time a vertical overload jump occurs; acquiring the target static temperature jump count and the target vertical overload jump count corresponding to the target area indicated in the area risk determination instruction, including: determining the number of position information matching the area range of the target area in at least one static temperature jump data to obtain the target static temperature jump count; determining the number of position information matching the area range of the target area in at least one vertical overload jump data to obtain the target vertical overload jump count.

[0009] One possible approach involves determining static temperature jump data based on changes in static temperature parameters and their locations, including: extracting a first portion of static temperature parameters from the static temperature parameter changes using a preset window; obtaining the maximum and minimum values ​​of the static temperature parameters in the first portion, and determining that a static temperature jump has occurred in the first portion of static temperature parameters if the difference between the maximum and minimum values ​​is greater than a first threshold; moving the preset window by a preset step size to extract a second portion of static temperature parameters and determining whether a jump has occurred in the second portion, until the preset window moves to the last static temperature parameter in the static temperature parameter changes; and determining the static temperature jump data based on the static temperature parameters that have experienced static temperature jumps and their corresponding location information.

[0010] In one possible approach, the aircraft operating data also includes altitude changes. Before determining the static temperature jump data, the method further includes: for each static temperature parameter in the static temperature parameter change data, based on the static temperature parameter and the corresponding altitude data, correcting the static temperature parameter at different altitudes to the static temperature parameter at the standard altitude.

[0011] In one possible approach, the method further includes: obtaining the number of static temperature jumps and the number of vertical overload jumps for each region in multiple regions; generating a weather anomaly risk heatmap based on the number of static temperature jumps and the number of vertical overload jumps for each region; the weather anomaly risk heatmap is used to indicate the distribution of weather anomaly risks in different target areas.

[0012] In one possible approach, aircraft operation data may also include at least one of the following: changes in longitude, changes in latitude, departure location, destination, flight number, time parameters, changes in equipment status, and changes in pitch angle.

[0013] Secondly, this application provides a flight risk identification device, comprising: an acquisition module and a determination module. The acquisition unit is configured to, in response to receiving a regional risk determination instruction, acquire the target static temperature jump count and the target vertical overload jump count corresponding to the target area indicated in the regional risk determination instruction; the target static temperature jump count is used to represent the number of times the static temperature parameter is abnormal when the aircraft is operating in the target area; the target vertical overload jump count is used to represent the number of times the vertical overload parameter is abnormal when the aircraft is operating in the target area; the determination unit is configured to, based on the target static temperature jump count and the target vertical overload jump count, determine the weather abnormality risk corresponding to the target area.

[0014] Thirdly, this application provides an electronic device including a memory and a processor; the memory and the processor are coupled; the memory is used to store instructions executable by the processor; when the processor executes the instructions, it performs the methods described in the first aspect and any possible implementation thereof.

[0015] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the methods described in the first aspect and any possible implementation thereof.

[0016] Fifthly, this application provides a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run computer programs or instructions to implement the methods described in the first aspect and any possible implementation thereof.

[0017] Sixthly, this application provides a computer program product containing instructions that, when executed by a computer, cause the computer to perform the methods described in the first aspect and any possible implementation thereof.

[0018] The technical problems that the flight risk identification device, electronic equipment, computer storage medium, chip or computer program product can solve and the technical effects it can achieve can be found in the technical problems and effects solved in the first aspect above, and will not be repeated here. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic diagram of a flight risk identification system provided in this application embodiment; Figure 2 A flowchart illustrating a method for determining static temperature jump data and vertical overload jump data, provided in an embodiment of this application; Figure 3 A flowchart illustrating a flight risk identification method provided in this application embodiment; Figure 4 A flowchart illustrating a target region visualization method provided in this application embodiment; Figure 5 A schematic diagram illustrating a high-bump risk area provided for an embodiment of this application; Figure 6 A graph showing the number of static temperature jumps over time, provided as an embodiment of this application; Figure 7 This application provides a pie chart for visualizing group risk in an embodiment. Figure 8 A schematic diagram of group risk analysis provided for an embodiment of this application; Figure 9 This is a structural diagram of a flight risk identification device provided in an embodiment of this application. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the description of this application, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or relative positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and for simplification, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Unless otherwise specified, the above-mentioned orientational descriptions can be flexibly set in practical applications, provided that the relative positional relationships shown in the accompanying drawings are satisfied.

[0023] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0024] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "communication" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a direct connection or an indirect connection through an intermediate medium, or a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0025] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0026] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0027] In the description of this specification, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0028] With the rapid development of the civil aviation industry, the number of flights is increasing day by day, and the area covered by flight operations is also becoming wider and wider. The risks of flight operations are inevitable, and the identification of risks during flight is directly related to the airline's operational efficiency and customer experience.

[0029] Currently, risk management generally includes three stages: risk identification, risk assessment, and risk response. In the risk identification stage, risk identification and prediction are mainly carried out through brainstorming, the Delphi method, scenario analysis, and SWOT analysis. Among them, brainstorming mainly involves multiple experts freely discussing and proposing risk sources; the Delphi method involves multiple rounds of anonymous consultation with experts to gradually reach a consensus; scenario analysis predicts potential risks and their causes based on reasonable assumptions; and SWOT analysis systematically identifies risks from four dimensions: strengths, weaknesses, opportunities, and threats.

[0030] In the risk assessment phase, four main methods are employed: expert scoring, analytic hierarchy process (AHP), decision tree method, and fuzzy comprehensive evaluation. Expert scoring relies heavily on the subjective assessment of domain experts to quantify the degree of risk through professional judgment. AHP combines qualitative analysis with quantitative calculation, constructing a hierarchical model to assign weights and rank risk factors. Decision tree method utilizes a tree-like graphical structure to systematically compare the benefits and risks of different decision paths, thereby selecting the optimal solution. Fuzzy comprehensive evaluation addresses the uncertainty of risk by transforming qualitative assessments into quantitative indicators, achieving a comprehensive multi-factor evaluation through membership functions.

[0031] The risk response phase primarily involves determining the risk level based on the risk assessment results and formulating corresponding countermeasures. Specific measures include risk mitigation, risk avoidance, risk transfer, and risk acceptance. Risk avoidance addresses high-risk situations that exceed controllable limits, proactively terminating or adjusting the project direction to completely eliminate the threat. Risk transfer utilizes tools such as insurance, outsourcing, or contractual clauses to shift risk responsibility to a third party with stronger response capabilities. Risk acceptance applies to risks with minor impacts or situations where intervention is impossible; it specifically includes proactively reserving contingency resources to address potential consequences and passively ensuring the risk remains at an acceptable level through regular monitoring.

[0032] As described above regarding existing flight risk identification methods, these methods primarily rely on the personal experience and knowledge of risk assessment experts to analyze flight conditions and determine flight risks. Because these methods depend on the capabilities and subjective understanding of risk assessment experts, the identified flight risks are highly subjective, resulting in low accuracy.

[0033] In view of this, based on the aforementioned technical means, the technical solution provided in this application takes into account the jump in static temperature parameters of an aircraft before and after encountering lightning strikes; that is, the number of static temperature jumps can accurately reflect the probability of an aircraft encountering lightning strike risk. Simultaneously, it also notes that the vertical overload parameters of an aircraft will jump before and after encountering turbulence; therefore, the number of vertical overload jumps can accurately reflect the probability of an aircraft encountering turbulence risk. Based on this, after receiving a regional risk determination instruction, by acquiring the number of static temperature jumps and the number of vertical overload jumps in the target area, the lightning strike risk and abnormal airflow risk faced by the aircraft while flying in the target area can be accurately determined. This allows for an accurate assessment of the weather anomaly risk in the target area, thereby improving the accuracy of flight risk identification results.

[0034] The flight risk identification method provided in this application can be applied to a flight risk identification system. Please refer to [link / reference]. Figure 1 The flight risk identification system may include: a data terminal 101 and a flight risk identification device 102; the data terminal 101 and the flight risk identification device 102 are connected in communication.

[0035] The data terminal 101 can be an electronic device such as a personal computer (PC), a laptop computer, a mobile device, a tablet computer, or a laptop computer. This application embodiment does not limit the specific form of the electronic device.

[0036] The data terminal 101 is used to display a human-computer interaction interface, which includes human-computer interaction controls. Users can input regional risk determination commands based on the human-computer interaction page. The data terminal 101 sends the regional risk determination commands to the flight risk identification device 102 for risk identification.

[0037] The flight risk identification device 102 can be an electronic device such as a personal computer (PC), laptop computer, mobile device, tablet computer, or laptop computer. This application embodiment does not limit the specific form of the electronic device. Alternatively, the flight risk identification device 102 can also be a server, or a server cluster consisting of multiple servers. In some implementations, the server cluster can be a distributed cluster server. This application embodiment does not impose any restrictions in this regard.

[0038] The flight risk identification device 102, in response to receiving a regional risk determination instruction, acquires the target static temperature jump count and the target vertical overload jump count corresponding to the target area indicated in the instruction. The target static temperature jump count indicates the number of times the aircraft's static temperature parameters are abnormal during operation in the target area. The target vertical overload jump count indicates the number of times the aircraft's vertical overload parameters are abnormal during operation in the target area. Based on the target static temperature jump count and the target vertical overload jump count, the weather abnormality risk corresponding to the target area is determined.

[0039] Furthermore, the actions, terms, etc., involved in the various embodiments of this application can be referenced interchangeably without limitation. The message names or parameter names in the messages exchanged between the various devices in the embodiments of this application are merely examples, and other names may be used in specific implementations without limitation.

[0040] It should be noted that the system architecture and application scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems. For example, the data terminal 101 and the flight risk identification device 102 can be separate devices or different functional modules on the same device.

[0041] The flight risk identification method provided in this application embodiment can be applied to the aforementioned flight risk identification device, specifically to the processor of the flight risk identification device.

[0042] In some embodiments, before obtaining the target static temperature jump count and target vertical overload jump count corresponding to the target region, the target static temperature jump count and target vertical overload jump count corresponding to multiple regions can be obtained first.

[0043] As a feasible way to achieve this, such as Figure 2 As shown, the flight risk identification method provided in this application specifically includes: S201. Obtain at least one aircraft operation data.

[0044] The aircraft operation data includes: changes in static temperature parameters, changes in vertical overload parameters, and changes in position.

[0045] The static temperature parameter refers to the temperature of the external atmosphere at the aircraft's current altitude when it is stationary or in slow-moving conditions. Analysis of extensive data shows that the static temperature parameter value at the aircraft's current altitude undergoes significant changes before and after a lightning strike. Therefore, by analyzing these fluctuations, the risk of a lightning strike can be determined relatively accurately. For example, at a certain moment while the aircraft is flying at an altitude of 9200 meters, the external static temperature is collected by the aircraft's built-in quick access recorder (QAR), and the result shows that the external static temperature at 9200 meters is -42 degrees Celsius.

[0046] Vertical overload parameter is the ratio of the resultant force (excluding gravity) in the vertical direction (hereinafter referred to as lift) to the aircraft's weight. It reflects the stress state of the aircraft in the vertical direction. Analysis of a large amount of data shows that the vertical overload parameter value of an aircraft changes significantly before and after encountering turbulence. Therefore, by analyzing the jumps in the vertical overload parameter value, the risk of the aircraft encountering turbulence can be determined relatively accurately.

[0047] For example, during level flight, that is, when the aircraft is not accelerating or decelerating in the vertical direction, the vertical overload parameters of the aircraft are collected by the aircraft's built-in QAR. It is found that during level flight, the vertical overload parameter of the aircraft is about 1, that is, the lift and gravity experienced by the aircraft are basically the same.

[0048] For example, during the acceleration and ascent of the aircraft, the vertical overload parameters of the aircraft are collected by the aircraft's built-in QAR. It is found that the vertical overload parameter of the aircraft during the acceleration and ascent is about 3.5, that is, the lift force on the aircraft is 3.5 times the weight.

[0049] The static temperature parameter variation refers to a series of static temperature parameters during aircraft operation. These variations reflect the thermodynamic characteristics and aerodynamic effects of the aircraft during flight. This series of static temperature parameters can be a sequence of parameters ordered chronologically, a curve showing the variation of static temperature parameters over time, or a table containing static temperature parameters, time, and other aircraft operational data (e.g., altitude).

[0050] Understandably, the changes in vertical overload parameters and positional changes, like the changes in static temperature parameters, can be represented as a set of corresponding parameter values ​​sorted by time, a parameter curve that changes over time, or a table that includes parameters, time, and other aircraft operating data (such as speed).

[0051] For example, when the static temperature parameter changes are a sequence of static temperature parameters ordered chronologically, the static temperature parameter changes can be represented as S = (s0, s1, … s N-1 The corresponding time series is T=(t0, t1, … t). N-1 ), where t n For the nth time slot of the corresponding flight (0≤n≤N), s n Indicates at t n The static temperature parameter value at any given time. The corresponding vertical overload parameter variation can be represented as V = (v0, v1, … v N-1 The following examples present the parameter changes as a sequence ordered chronologically, specifically the static temperature parameter changes as S = (s0, s1, … s). N-1 The vertical overload parameters change as follows: V = (v0, v1, … v) N-1 Let's take an example to illustrate.

[0052] It should be noted that the embodiments of this application do not limit the form in which the static temperature parameter changes are represented. In practical applications, the representation can be set according to requirements to cover different application scenarios. For example, in scenarios with high data visualization requirements, the static temperature parameter change can be a curve showing the static temperature parameter changing over time. In scenarios where there is a need for correlation analysis between the static temperature parameter and other aircraft operation data, the static temperature parameter change can be a table containing the static temperature parameter, time, and other aircraft operation data.

[0053] In one possible implementation, the aircraft operation data may also include at least one of the following: longitude changes, latitude changes, takeoff location, destination location, flight number, time parameters, equipment status changes, tail number, and pitch angle changes. The equipment status changes may further include the status of multiple radar devices and the pitch stick status.

[0054] Because the parameters in aircraft operation data change at different frequencies and are of varying importance to the analysis of flight risks, different data acquisition frequencies are set for each type of aircraft operation data. For parameters that change frequently or are of greater importance to the analysis of flight risks, the data acquisition frequency is increased to improve the accuracy of data acquisition. For parameters that change infrequently or are of less importance to the analysis of flight risks, the data acquisition frequency is decreased to reduce the load on the equipment.

[0055] As exemplified, Table 1 provides a parameter data table for an embodiment of this application, which includes the parameter code, parameter name, and acquisition frequency of aircraft operation data. The acquisition frequency is in Hertz. If the acquisition frequency for acquiring a certain aircraft operation data is 4 Hertz, then the corresponding aircraft operation data is acquired 4 times per second.

[0056] Table 1 Parameter Data Table

[0057] Aircraft operation data refers to data collected during aircraft operation. Therefore, aircraft operation data can be acquired during aircraft operation using data acquisition equipment inside the aircraft.

[0058] A Quick Access Recorder (QAR) is a data recording device installed on modern commercial aircraft. Its core function is to continuously and automatically record a large amount of flight parameter data and automatically upload this data after the aircraft lands. In one possible implementation, at least one piece of aircraft operational data can be obtained by acquiring at least one piece of aircraft operational data through the aircraft's built-in QAR during the aircraft's operation.

[0059] It should be noted that the above example of acquiring at least one aircraft operation data is only one possible implementation method. In actual applications, it can be set according to requirements to cover different application scenarios. For example, aircraft operation data can be collected through the aircraft's built-in flight data recorder, also known as the "black box," or it can be acquired through various sensors in the aircraft based on the aircraft status monitoring system.

[0060] After the aircraft's data acquisition equipment acquires the aircraft's operational data, data cleaning is required to facilitate data analysis. For aircraft operational data with a sampling frequency of 1 Hz, relevant data is extracted into the preprocessed result dataset using flight document codes and time (down to the second) as keywords. For aircraft operational data with a sampling frequency greater than 1 Hz, the first data acquired per second is extracted as the representative data for the corresponding time, achieving multi-frequency to single-frequency conversion. Then, the representative data is used to extract relevant data into the preprocessed result dataset using flight document codes and time (down to the second) as keywords. For aircraft operational data with a sampling frequency less than 1 Hz, the most recently acquired data from historical data is used as the representative data for the corresponding time.

[0061] For example, as shown in Table 1, the sampling frequency of the static temperature parameter is 1 Hz. Data cleaning is completed by associating the collected static temperature parameter with the corresponding time. The sampling frequency of the longitude parameter is 4 Hz, so there are four longitude parameters per second. Data cleaning is completed by extracting the first longitude parameter from the four longitude parameters per second as the representative longitude parameter for the corresponding time and associating the representative longitude parameter with the corresponding time.

[0062] For example, during actual flight, most turbulence occurs within a few seconds. To improve the accuracy of identifying turbulence risks, although the sampling frequency of the vertical overload parameter is 8 Hz, no multi-frequency to single-frequency conversion processing is performed on the vertical overload parameter. Therefore, the variation of the vertical overload parameter is V = (v0, v1, … v N-1 The time series T corresponding to the vertical overload parameters is T=(t0, t1, … t). N-1 In the time series, at each time point t... n This represents the change in vertical overload parameters for each v in the case of the nth second. n It includes 8 vertical overload parameters, namely v n =( v n1 , v n2 , … v n8 ).

[0063] S202. For each aircraft operation data, determine the static temperature jump data based on the changes in static temperature parameters and position.

[0064] Among them, the static temperature jump data is used to represent the aircraft's position information each time a static temperature jump occurs.

[0065] Under standard atmospheric conditions, the static temperature decreases regularly with increasing altitude, dropping by approximately 2 degrees Celsius every 1,000 feet. Therefore, in order to compensate for the static temperature changes caused by altitude, the static temperature parameters need to be corrected.

[0066] In one possible implementation, the aircraft operation data also includes altitude changes. Before determining the static temperature jump data, the static temperature parameters can be corrected as follows: for each static temperature parameter in the static temperature parameter change data, based on the static temperature parameter and the corresponding altitude data, the static temperature parameter under different altitude data is corrected to the static temperature parameter under the standard altitude.

[0067] In one possible implementation, the static temperature parameter at standard altitude satisfies the following formula 1: SAT_C = SAT + ALT_STD × 0.002 (Formula 1)

[0068] Where SAT_C is the static temperature parameter at standard altitude, SAT is the static temperature parameter, and ALT_STD is the altitude data corresponding to the static temperature parameter.

[0069] For example, the static temperature parameter obtained by the aircraft during flight at 35,000 feet is -56.5°C. Substituting this static temperature parameter into Formula 1, the static temperature parameter at the standard altitude is obtained as 13.5°C.

[0070] By converting the static temperature parameters at different altitudes into those at a standard altitude, the variation in static temperature parameters caused by altitude changes is avoided, reducing the error in static temperature parameters and providing an accurate data foundation for subsequent analysis of flight risks, thereby improving the accuracy of flight risk identification results.

[0071] The static temperature parameters refer to a series of static temperature parameters during aircraft operation. These changes reflect the thermodynamic characteristics and aerodynamic effects of the aircraft during flight. Specifically, by analyzing whether the static temperature parameters change significantly within a preset window, it can be determined whether there have been any abrupt changes.

[0072] In one possible implementation, S202 can be implemented as follows: obtaining the static temperature parameter within a first preset window. If there is an abnormal static temperature parameter within the first preset window, it is determined that there is a static temperature jump within the first preset window, and the static temperature jump data is determined based on the position information corresponding to the static temperature parameter within the first preset window.

[0073] In one possible implementation, an abnormal static temperature parameter is used to indicate that a change in the static temperature parameter within a first preset window exceeds a first threshold. The first preset window is a sliding window with a preset window length and a preset step size, used to acquire the static temperature parameter within a preset time length. The preset time length is the duration of the risk event.

[0074] For example, the duration of a lightning strike risk event on an aircraft is generally less than 10 seconds. Therefore, when using the first preset window to capture the static temperature parameter, the window length of the first preset window can be set to 10 seconds.

[0075] S203. For each aircraft operation data, determine the vertical overload jump data based on the changes in vertical overload parameters and position.

[0076] Among them, the vertical overload jump data is used to represent the position information of the aircraft each time a vertical overload jump occurs.

[0077] This refers to a series of dynamic data on vertical overload parameters during aircraft operation. Changes in these parameters reflect the structural stress characteristics and attitude changes during flight. Specifically, by analyzing whether significant fluctuations or large changes occur in the vertical overload parameters within a preset window, it can be determined whether abrupt changes have taken place.

[0078] In one possible implementation, S203 can be implemented as follows: obtaining the vertical overload parameter within the second preset window. If there is an abnormal vertical overload parameter within the second preset window, determining that there is a vertical overload jump in the vertical overload parameter within the second preset window, and determining the vertical overload jump data based on the position information corresponding to the vertical overload parameter within the second preset window.

[0079] In one possible implementation, an anomaly in the vertical overload parameter indicates that a change in the vertical overload parameter within a second preset window exceeds a second threshold. The second preset window is a sliding window with a preset window length and a preset step size, used to acquire the vertical overload parameter within a preset time period. The preset time period is the duration of the risk event.

[0080] For example, the duration of a turbulence risk event for an aircraft is generally less than 3 seconds. Therefore, when using the second preset window to capture the vertical overload parameters, the window length of the second preset window can be set to 3 seconds.

[0081] By acquiring aircraft operational data and using it to determine static temperature fluctuation and vertical overload fluctuation data, when a client requests a risk assessment for a specific area, there is no need to temporarily collect and analyze aircraft operational data for that area to determine if fluctuations exist. Retrieving relevant information for the corresponding area directly from a pre-defined database allows for risk assessment results to be provided in a very short time, significantly shortening the assessment cycle and improving efficiency.

[0082] In some embodiments, after acquiring aircraft operational data, it is necessary to determine the static temperature jump data and the vertical overload jump data. The following describes a specific implementation method for determining the static temperature jump data; this method is also applicable to determining the vertical overload jump data.

[0083] As a feasible implementation method, S202 can be specifically implemented as follows: S2021 extracts the first part of the static temperature parameters from the static temperature parameter changes based on a preset window.

[0084] After obtaining the static temperature parameter changes, these changes often encompass static temperature parameters over a long timescale, corresponding to multiple regions. To determine the static temperature jump data, i.e., the static temperature jump situation across multiple regions, it is necessary to extract a portion of the static temperature parameters and determine whether that portion of the static temperature parameters has experienced a jump.

[0085] In one possible implementation, S1021 is specifically implemented as follows: based on a preset window of preset length, a static temperature parameter of the corresponding preset length is extracted from the static temperature parameter change situation, that is, the first part of the static temperature parameter.

[0086] When using preset windows to capture changes in static temperature parameters and vertical overload parameters, the size and step size of the preset windows may differ. For ease of description, the first preset window is used when capturing changes in static temperature parameters, while the second preset window is used when capturing changes in vertical overload parameters.

[0087] For example, considering the static temperature parameter variation S=(s0, s1, … s N-1 The first part of the static temperature parameter, S, is obtained by capturing the static temperature parameter changes through a first preset window of size W. W =(s t0 , s t1 , … s t+W-1 ).

[0088] S2022. Obtain the maximum and minimum static temperature data in the first part of static temperature parameters. If the difference between the maximum and minimum static temperature data is greater than the first threshold, determine that the first part of static temperature parameters has experienced a static temperature jump.

[0089] After extracting the first portion of static temperature parameters from the static temperature parameter changes, it is necessary to determine whether a static temperature jump has occurred in this first portion. Specifically, this can be determined by whether the difference between the maximum and minimum values ​​of the first portion of static temperature parameters is greater than a first threshold.

[0090] The first threshold can be set based on tolerance for low-consequence risk events. A higher first threshold means fewer instances of abrupt changes are identified, indicating a higher tolerance for low-consequence events; conversely, a lower first threshold means more instances of abrupt changes are identified, indicating a lower tolerance for low-consequence events. Therefore, appropriate thresholds can be set based on actual needs to monitor low-consequence events of varying degrees. For example, when identifying flight risks for the A330 aircraft, the first threshold can be set at [1.5, 3] (in degrees Celsius).

[0091] In one possible implementation, the difference between the maximum and minimum static temperature data satisfies the following formula 2: d s = max(S W )- min(S W ) Formula 2.

[0092] Where, d s The maximum and minimum values ​​of the static temperature data are represented by max(S). W ) represents the maximum static temperature data, min(S) W Minimum static temperature data.

[0093] In one possible implementation, determining whether the first part of the static temperature parameter has changed abruptly can also be achieved by: determining the difference between any two static temperature data in the first part of the static temperature parameter; if the absolute value of the difference between two static temperature data in the first part of the static temperature parameter is greater than a first threshold, it can be determined that the first part of the static temperature parameter has changed abruptly.

[0094] In one possible implementation, the absolute value of the difference between the two static temperature data satisfies the following formula 3: D s =|S m – S n |Formula 3.

[0095] Among them, D s S is the absolute value of the difference between two static temperature data points. m and S n These are static temperature data at two different times.

[0096] S2023. Move the preset window based on the preset step size, capture the second part of the static temperature parameters, and determine whether the second part of the static temperature parameters has changed, until the preset window moves to the last static temperature parameter in the static temperature parameter change situation.

[0097] After determining whether there is a static temperature jump in the first part of the static temperature parameters, the first preset window can be moved backward to determine whether other parts of the static temperature parameters have jumped in the static temperature parameter change situation.

[0098] In one possible implementation, S1023 can be implemented as follows: after determining whether there is a static temperature jump in the first part of the static temperature parameters, the first preset window is moved back by a preset step size to capture the second part of the static temperature parameters. This process is repeated until the first preset window captures the last static temperature parameter of the static temperature parameter change.

[0099] For example, the preset window is shifted backward by a preset step. When the preset step is one moment, i.e., shifted backward by one static temperature parameter, the second static temperature parameter is S. W =(s t1 , s t2 , … s t+W The movement ends after moving to the last static temperature parameter in the preset window.

[0100] S2024. Based on the static temperature parameters that cause static temperature jumps and the location information corresponding to the static temperature parameters, determine the static temperature jump data.

[0101] After determining whether a static temperature jump exists in each part of the static temperature parameter, it is necessary to determine the static temperature jump data by identifying the location information corresponding to the static temperature parameter where the jump occurred. One possible implementation is as follows: acquire each part of the static temperature parameter that experienced a jump; for each part of the static temperature parameter, determine the location information corresponding to that part of the static temperature parameter; and define that part of the static temperature parameter, the magnitude of the jump, and the location information as the static temperature jump data for that part of the static temperature parameter.

[0102] For example, after determining whether a static temperature jump exists for each part of the static temperature parameter, it is determined that a static temperature jump occurred between the 10th and 11th seconds. At this time, the location information corresponding to this part of the static temperature parameter is: 32.56°N, 118.78°E. The data from the 10th to 11th seconds, the magnitude of the jump, and the latitude and longitude information are determined as the static temperature jump data for this part of the static temperature parameter.

[0103] The system extracts a portion of the static temperature parameter changes through a first preset window and performs jump analysis on some of the data. By breaking down the large volume of static temperature parameter changes into multiple smaller static temperature parameters, the computational load is greatly reduced, and the data analysis speed for static temperature parameter changes is improved. In addition, by moving the preset window with a preset step size, the system can perform detailed analysis of static temperature parameter changes, providing an accurate data foundation for subsequent analysis of flight risks.

[0104] In some embodiments, for the vertical overload parameter, a second preset window and a second preset step size can be used to capture the changes in the vertical overload parameter. The second preset window is preset and can be the same as or different from the first preset window; for specific determination methods, please refer to the static temperature parameter above.

[0105] The vertical overload parameters captured by the second preset window can be judged by determining whether the difference between the maximum and minimum values ​​of the vertical overload data in this part of the vertical overload parameters is greater than the second threshold, thus determining whether the vertical overload parameters have changed abruptly.

[0106] The second threshold can be set based on tolerance for low-consequence risk events. A larger second threshold results in fewer instances of identified transitions, indicating a higher tolerance for low-consequence events; conversely, a smaller second threshold leads to more identified transitions, indicating a lower tolerance for low-consequence events. Therefore, appropriate transition thresholds can be set based on actual needs to monitor low-consequence events of varying degrees. For example, when identifying flight risks for the A330 aircraft, the second threshold can be set between [0.8, 1.5] (unit: gravitational acceleration g).

[0107] In some embodiments, please refer to Figure 3 The flight risk identification method provided in this application specifically includes S301-S302.

[0108] S301. In response to receiving the regional risk determination instruction, obtain the target static temperature jump number and the target vertical overload jump number corresponding to the target area indicated in the regional risk determination instruction.

[0109] The regional risk determination instruction is a user-issued instruction used to obtain the weather anomaly risk of a target area. The format of this instruction can be natural language text or voice. The instruction includes the location information of the target area. This location information can be specific coordinates or an identifier that indicates the target area; this application does not limit the format of the location information.

[0110] When a user needs to assess the risk of a target area, they must issue a risk determination command for that area. Upon receiving the command, the flight risk identification device can extract the location information of the target area. It should be noted that this embodiment does not limit the method by which the user inputs the risk determination command. In practical applications, the method can be set according to requirements to cover different interaction modes and device scenarios. For example, as one implementation, the method of inputting the risk determination command may include at least one of the following: voice input, conversational interaction, template filling input, gesture or graphical input, text box input, and handwriting input.

[0111] Upon receiving the area risk determination instruction, it is necessary to obtain the target static temperature jump count and the target vertical overload jump count corresponding to the target area indicated in the instruction. The target static temperature jump count indicates the number of times the aircraft's static temperature parameters are abnormal during operation in the target area. The target vertical overload jump count indicates the number of times the aircraft's vertical overload parameters are abnormal during operation in the target area.

[0112] In the process of obtaining the target static temperature jump number and target vertical overload jump number corresponding to the target area indicated in the regional risk determination instruction, in order to match the location of the obtained target static temperature jump number and target vertical overload jump number with the location of the target area indicated in the regional risk determination instruction, the regional risk determination instruction often includes the location information of the target area. Therefore, the corresponding target static temperature jump number and target vertical overload jump number can be matched by the location information of the target area in the risk determination instruction.

[0113] In one possible implementation, obtaining the target static temperature jump number and target vertical overload jump number corresponding to the target area indicated in the regional risk determination instruction can be achieved by: determining the location information of the target area in the risk determination instruction, and determining the corresponding target static temperature jump number and target vertical overload jump number based on the location information of the target area.

[0114] For example, the flight risk identification device can have a built-in data storage module. This module can store multiple location information entries and corresponding static temperature jump counts and vertical overload jump counts. When the user's requirement is to determine the flight operation risk within Province A, the regional risk determination command can be: "Determine the flight operation risk in Province A." The flight risk identification device uses this command to determine the location information of the target region, "Province A." Based on this location information, it matches the target static temperature jump count and target vertical overload jump count from the data storage module. These two counts are used to subsequently determine the corresponding weather anomaly risk for the target region.

[0115] In one possible implementation, obtaining the target static temperature jump count corresponding to the target area indicated in the regional risk determination instruction is specifically achieved by: determining the number of location information matching the regional range of the target area in at least one static temperature jump data, thereby obtaining the target static temperature jump count.

[0116] After obtaining the regional risk determination instruction, it is possible to determine whether the location information indicated in the static temperature jump data is within the regional range of the target area indicated in the regional risk determination instruction, and whether the regional range of the static temperature jump data and the target area indicated in the regional risk determination instruction match.

[0117] For example, if there are 10 locations in "Province A" where the static temperature jump data indicates that static temperature jump data has occurred, then the target static temperature jump count is 10.

[0118] In one possible implementation, obtaining the number of target vertical overload jumps corresponding to the target area indicated in the regional risk determination instruction is specifically achieved by: determining the number of location information matching the regional range of the target area in at least one vertical overload jump data, thereby obtaining the number of target vertical overload jumps.

[0119] After obtaining the regional risk determination instruction, it is possible to determine whether the regional range of the vertical overload jump data and the target area indicated in the regional risk determination instruction are matched by judging whether the location information indicated in the vertical overload jump data is within the regional range of the target area indicated in the regional risk determination instruction.

[0120] For example, if there are 10 locations in “Province A” where vertical overload jump data indicates that vertical overload jump data has occurred, then the target number of vertical overload jumps is 10.

[0121] For example, the following is pseudocode for a method to determine the number of vertical overload jumps and the number of static temperature parameter jumps.

[0122] Input: static temperature sequence Vertical overload sequence Sliding window size static temperature jump threshold Vertical overload jump threshold

[0123] Output: Number of static temperature jumps Number of vertical overload jumps

[0124] 1: , , , # Initialize hyperparameters 2: ,

[0125] 2: do 3: # Get the static temperature sequence of the (i+1)th sliding window 4: #Get the vertical overload sequence of the (i+1)th sliding window 5: Use formula (3) to calculate the maximum static temperature difference within the sliding window. 6: Use formula (4) to calculate the maximum difference in vertical overload within the sliding window. 7: if then 8: +=1 9: else if then 10: +=1 11: end if 12: end for S302. Based on the number of target static temperature jumps and the number of target vertical overload jumps, determine the weather anomaly risk corresponding to the target area.

[0126] Among them, abnormal weather risk is used to indicate the flight risk under abnormal weather conditions.

[0127] The static temperature parameters of an aircraft change drastically before and after being struck by lightning. The number of static temperature changes can accurately reflect the probability of an aircraft encountering a lightning strike. Similarly, the vertical overload parameters of an aircraft change drastically before and after encountering turbulence. The number of vertical overload changes can accurately reflect the probability of an aircraft encountering turbulence. Therefore, by analyzing the number of vertical overload changes and static temperature changes in a target area, the corresponding weather anomaly risk in that area can be determined.

[0128] In one possible implementation, S302 can be implemented as follows: if the number of static temperature jumps corresponding to the target area is greater than a preset static temperature jump number threshold, the target area is determined as a high lightning strike risk area; if the number of static temperature jumps corresponding to the target area is less than or equal to the preset static temperature jump number threshold, the target area is determined as a low lightning strike risk area.

[0129] In one possible implementation, S302 can be implemented as follows: if the number of vertical overload jumps corresponding to the target area is greater than a preset threshold for the number of vertical overload jumps, the target area is determined as a high-bump risk area. If the number of vertical overload jumps corresponding to the target area is less than or equal to the preset threshold for the number of vertical overload jumps, the target area is determined as a low-bump risk area.

[0130] For example, the flight risk identification device, based on the location information of "Province A," matches the target static temperature fluctuation count (5 times) and target vertical overload fluctuation count (12 times) for "Province A" from the data storage module. The threshold for static temperature fluctuation count is 10 times, and the threshold for vertical overload fluctuation count is 8 times. The comparison shows that "Province A" is a low lightning strike risk area and a high turbulence risk area. It should be noted that the above example of determining the weather anomaly risk corresponding to the target area is only one possible implementation method.

[0131] As described in the above technical solution, this application determines the corresponding weather anomaly risk in the target area by obtaining the number of static temperature jumps and vertical overload jumps in the target area. Specifically, the static temperature parameter of an aircraft changes drastically before and after being struck by lightning, and the number of static temperature jumps can accurately reflect the probability of the aircraft encountering a lightning strike. Similarly, the vertical overload parameter of an aircraft changes drastically before and after encountering turbulence, and the number of vertical overload jumps can accurately reflect the probability of the aircraft encountering turbulence. Therefore, this application, by obtaining the number of static temperature jumps and vertical overload jumps in the target area, can improve the accuracy of flight risk assessment results.

[0132] In some embodiments, to help airlines, airports and air traffic control departments identify potential threats in different regions in advance, optimize resource allocation and develop targeted response measures, the risk of abnormal weather in different regions can be analyzed and visualized.

[0133] As a feasible way to achieve this, such as Figure 4 As shown in the embodiments of this application, the flight risk identification method also includes: S401. Obtain the static temperature jump count and vertical overload jump count for each region in multiple regions.

[0134] Before visualizing the risk of abnormal weather in different regions, it is necessary to determine the number of static temperature jumps and vertical overload jumps in each region. Specifically, this can be done by statistically analyzing the number of static temperature jumps and vertical overload jumps in the same region based on location information, thus determining the corresponding number of static temperature jumps and vertical overload jumps for each region.

[0135] In one possible implementation, S401 can be implemented as follows: acquiring aircraft operation data collected by data acquisition equipment, determining the number of static temperature jumps and vertical overload jumps corresponding to the aircraft operation data through the above method, grouping the number of static temperature jumps and vertical overload jumps based on the location information of the number of static temperature jumps and vertical overload jumps, grouping the number of static temperature jumps and vertical overload jumps in the same area into one group, and determining the number of static temperature jumps and vertical overload jumps corresponding to each area in multiple areas.

[0136] S402. Generate a heat map of weather anomaly risk based on the number of static temperature jumps and the number of vertical overload jumps for each region.

[0137] Among them, the weather anomaly risk heat map is used to indicate the distribution of weather anomaly risks in different target areas.

[0138] After obtaining the number of static temperature jumps and vertical overload jumps for each of the multiple regions, it is possible to determine whether each region is a high-risk region by analyzing the number of static temperature jumps and vertical overload jumps for each region.

[0139] In one possible implementation, S402 above can be implemented as follows: For each region, if the number of corresponding static temperature jumps exceeds a preset regional static temperature risk threshold, the region is identified as a high lightning strike risk region. For each region, if the number of corresponding vertical overload jumps exceeds a preset regional vertical overload risk threshold, the region is identified as a high turbulence risk region. By marking the high-risk regions, a weather anomaly risk heat map is generated.

[0140] For example, such as Figure 5 The diagram shown is a visualization of a high-bump risk area provided in an embodiment of this application. The shaded area represents the high-bump risk area.

[0141] As can be seen from the above technical solution, this application visualizes high-risk areas by generating a weather anomaly risk heat map. The weather anomaly risk heat map can facilitate the identification of high turbulence risk areas, assess the risk of operation in the corresponding areas, and provide data support and decision-making reference for subsequent safety management work.

[0142] In some embodiments, the high-risk period can be visualized by obtaining the number of static temperature jumps and the number of vertical overload jumps within a specified time period, and generating curves showing the changes in the number of static temperature jumps and the number of vertical overload jumps over time.

[0143] As a feasible implementation method, the method provided in this application embodiment further includes: in response to receiving a time period risk determination instruction, extracting daily aircraft operation data for a specified time period, and determining the number of static temperature jumps and the number of vertical overload jumps corresponding to the time period indicated in the regional risk determination instruction. Based on the number of static temperature jumps and the number of vertical overload jumps for the corresponding time period, determining the flight risk for the corresponding time period.

[0144] By identifying the flight risks for specific time periods, airlines, flight crews, and air traffic control can understand these risks in advance, make necessary preparations, and reduce the probability of flight accidents.

[0145] For example, such as Figure 6 The figure shown is a graph illustrating the change in the number of static temperature jumps over time, as provided in an embodiment of this application.

[0146] By displaying the number of daily jumps within a specified time period, risk trends can be identified for different time periods.

[0147] In some embodiments, risk response can be targeted at a few captains by determining whether temperature fluctuations or vertical load factor fluctuations occur concentrated among them. Specifically, the "fluctuation captain ratio" can be determined by comparing the total number of flights experiencing temperature fluctuations or vertical load factor fluctuations with the number of captains experiencing such fluctuations. Taking temperature fluctuations as an example, if the fluctuation captain ratio is greater than a preset value, it indicates that the lightning strike risk for this group is mainly concentrated on a few crews. In this case, key management should be implemented for this group to prevent risks in a timely manner. If the fluctuation captain ratio is less than the preset value, it indicates that the lightning strike risk is relatively dispersed among the relevant crews, and general attention is sufficient.

[0148] For example, Indicates the number of people in a group. Indicates the first Groups ( ). Representing a group The number of aircraft experiencing a static temperature jump. Representing a group The number of flights experiencing static temperature jumps is used to calculate the number of flights. The ratio of the number of flights experiencing temperature jumps to the number of captains experiencing temperature jumps within a given group is used to determine the temperature jump captain ratio. .

[0149] In one possible implementation, the static temperature jump machine length ratio satisfies the following formula 4: Formula 4.

[0150] in, Representing a group The number of flights experiencing temperature jumps during the period. Representing a group The number of aircraft experiencing a static temperature jump. The static temperature jump ratio is the length ratio of the machine, where i is an integer.

[0151] Understandably, the risk level of turbulence encountered by this group of passengers can also be determined using the methods described above, which will not be elaborated upon below.

[0152] For example, such as Figure 7 The image shown is a pie chart illustrating the visualization of group risk according to an embodiment of this application. This pie chart visually presents the proportion of different groups within the overall risk.

[0153] For risks across multiple groups, the risk of a given group can be determined by identifying the ratio of the number of flights experiencing temperature or vertical overload changes to the total number of flights in that group, and by applying the relationship between "mean + 1x variance" and "mean + 2x variance".

[0154] To analyze populations through static temperature jumps Taking the risk level as an example, for each group, the number of flights experiencing a sudden change in static temperature within the group is used as an indicator. and total number of flights The ratio of the static temperature jump flights was used to determine the ratio of the static temperature jump flights for each group. Calculate the mean risk of temperature fluctuations during flights for each group. and variance .

[0155] For each group, the proportion of flights with temperature jumps within that group Less than the mean plus 1 variance In this case, the group was identified as a low-risk group, and the number of flights with temperature fluctuations in this group was compared to... Greater than the mean plus 1 variance If the risk level is less than the mean plus twice the variance, this group is classified as a medium-risk group. The proportion of flights with temperature fluctuations within this group is also considered. If the value is greater than the mean plus twice the variance, the group is identified as a high-risk group.

[0156] In one possible implementation, the static temperature jump flight ratio satisfies the following formula 5: Formula 5.

[0157] in, For group i, the ratio of flights with temperature jumps. The number of flights that exhibit a temperature jump in group i. Let i be the total number of flights in group i.

[0158] In one possible implementation, the mean risk of static temperature fluctuations for each flight group satisfies the following formula 6: Formula 6.

[0159] in, C represents the average risk of temperature fluctuations during flights for each group, where C is the total number of groups.

[0160] In one possible implementation, the variance of the static temperature change risk for each flight group satisfies the following formula 7: Formula 7.

[0161] in, The variance of the risk of temperature fluctuations during flights for each group.

[0162] For example, such as Figure 8 The diagram shown is a schematic diagram of a group risk analysis provided in an embodiment of this application.

[0163] The foregoing mainly describes the solutions provided in the embodiments of this application from a methodological perspective. It is understood that, in order to achieve the above functions, the flight risk identification device includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, based on the flight risk identification method steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0164] This application also provides a flight risk identification device. This device can be a server, a CPU within the server, a module within the server used to assess flight seat availability, or a client within the server used to assess flight seat availability.

[0165] This application embodiment can divide the flight risk identification device into functional modules or functional units according to the above method example. For example, each function can be divided into a separate functional module or functional unit, or two or more functions can be integrated into one processing unit. The integrated module can be implemented in hardware or in software functional modules or functional units. The module or unit division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0166] When dividing each function into modules according to its corresponding function. Figure 9 A structural diagram of a flight risk identification device provided in this application is shown below. Figure 9 As shown, the flight risk identification device can be used to perform... Figure 2 , Figure 3 , Figure 4 The method for identifying flight risks is shown. The flight risk identification device 90 includes an acquisition module 901 and a processing module 902.

[0167] In one possible approach, the acquisition unit 901 is configured to, in response to receiving a regional risk determination instruction, acquire the target static temperature jump count and the target vertical overload jump count corresponding to the target area indicated in the regional risk determination instruction; the target static temperature jump count is used to represent the number of times the aircraft's static temperature parameters are abnormal when operating in the target area; the target vertical overload jump count is used to represent the number of times the aircraft's vertical overload parameters are abnormal when operating in the target area; and the determination unit 902 is configured to determine the weather anomaly risk corresponding to the target area based on the target static temperature jump count and the target vertical overload jump count.

[0168] This disclosure also provides a computer-readable storage medium storing instructions that, when executed by a processor of an electronic device, enable the electronic device to perform the flight risk identification method provided in the embodiments of this disclosure described above.

[0169] This disclosure also provides a computer program product containing instructions that, when run on an electronic device, cause the electronic device to execute the flight risk identification method provided in the above-described embodiments of this disclosure.

[0170] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires; a portable computer disk drive; a hard disk drive; a random access memory (RAM); a read-only memory (ROM); an erasable programmable read-only memory (EPROM); a register; a hard disk drive; an optical fiber; a portable compact disc read-only memory (CD-ROM); an optical storage device; a magnetic storage device; or any suitable combination thereof; or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may reside in an application-specific integrated circuit (ASIC). In the embodiments of this application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0171] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0172] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0173] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the classified units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0174] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0175] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, essentially, or the part that contributes to the prior art, or a complete or partial classification of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0176] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for identifying flight risks, characterized in that, The method includes: In response to receiving a regional risk determination instruction, the system acquires the target static temperature jump count and the target vertical overload jump count corresponding to the target region indicated in the regional risk determination instruction; the target static temperature jump count is used to indicate the number of times the aircraft's static temperature parameters are abnormal when operating in the target region; the target vertical overload jump count is used to indicate the number of times the aircraft's vertical overload parameters are abnormal when operating in the target region. Based on the number of target static temperature jumps and the number of target vertical overload jumps, the weather anomaly risk corresponding to the target area is determined; the weather anomaly risk is used to indicate the flight risk under abnormal weather conditions.

2. The method according to claim 1, characterized in that, The abnormal static temperature parameter is used to indicate that there is a change in the static temperature parameter within a preset window that is greater than a first threshold.

3. The method according to claim 1, characterized in that, The method further includes: Acquire at least one aircraft operation data, including: static temperature parameter changes, vertical overload parameter changes, and position changes; For each of the aircraft operation data, static temperature jump data is determined based on the changes in the static temperature parameter and the changes in the position; the static temperature jump data is used to represent the position information of the aircraft each time a static temperature jump occurs; For each of the aircraft operation data, based on the changes in the vertical overload parameters and the changes in position, vertical overload jump data is determined. The vertical overload jump data is used to represent the position information of the aircraft each time a vertical overload jump occurs. The acquisition of the target static temperature jump count and the target vertical overload jump count corresponding to the target area indicated in the area risk determination instruction includes: In at least one of the static temperature jump data, determine the number of location information that matches the regional range of the target area to obtain the target static temperature jump number; In at least one of the vertical overload jump data, determine the number of location information that matches the regional range of the target area to obtain the target vertical overload jump number.

4. The method according to claim 3, characterized in that, The determination of static temperature jump data based on the changes in static temperature parameters and location includes: Based on a preset window, a first portion of the static temperature parameters is extracted from the static temperature parameter changes. Obtain the maximum and minimum values ​​of the static temperature parameters in the first part of static temperature parameters. If the difference between the maximum and minimum values ​​of the static temperature parameters is greater than a first threshold, it is determined that the first part of static temperature parameters has experienced a static temperature jump. The preset window is moved based on a preset step size to capture the second part of the static temperature parameters and to determine whether the second part of the static temperature parameters has changed, until the preset window moves to the last static temperature parameter in the static temperature parameter change situation; Based on the static temperature parameters that experienced static temperature jumps and the location information corresponding to those static temperature parameters, the static temperature jump data is determined.

5. The method according to claim 3, characterized in that, The aircraft operational data also includes altitude changes. Before determining the static temperature jump data, the method further includes: For each static temperature parameter in the static temperature parameter variation, based on the static temperature parameter and the corresponding altitude data, the static temperature parameter under different altitude data is corrected to the static temperature parameter under the standard altitude.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the static temperature jump count and vertical overload jump count for each region in multiple regions; Based on the number of static temperature jumps and the number of vertical overload jumps corresponding to each region, a weather anomaly risk heat map is generated; the weather anomaly risk heat map is used to indicate the distribution of weather anomaly risks in different target areas.

7. The method according to claim 3, characterized in that, The aircraft operation data also includes at least one of the following: longitude changes, latitude changes, takeoff location, destination location, flight number, time parameters, equipment status changes, and pitch angle changes.

8. A flight risk identification device, characterized in that, The device includes: an acquisition unit and a determination unit; The acquisition unit is configured to, in response to receiving a regional risk determination instruction, acquire the target static temperature jump count and the target vertical overload jump count corresponding to the target area indicated in the regional risk determination instruction; the target static temperature jump count is used to indicate the number of times the aircraft's static temperature parameters are abnormal when operating in the target area; the target vertical overload jump count is used to indicate the number of times the aircraft's vertical overload parameters are abnormal when operating in the target area. The determining unit is used to determine the weather anomaly risk corresponding to the target area based on the number of target static temperature jumps and the number of target vertical overload jumps; the weather anomaly risk is used to indicate the flight risk under abnormal weather conditions.

9. An electronic device, characterized in that, include: A processor and a communication interface; the communication interface is coupled to the processor, the processor being configured to run computer programs or instructions to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing instructions, characterized in that, When the computer executes the instruction, the computer performs the method described in any one of claims 1-7.

Images