Model-based airport bird identification method and system

Abstract

The invention discloses a model-based airport bird recognition method and system, and the method comprises the steps: obtaining the recognition information of a to-be-recognized object through a camera or radar, the identification information comprises the speed and wind speed of the to-be-identified object, the flight mode of the to-be-identified object, the reference value of the temperature, the variable quantity of the temperature, the reference value of the wind speed, the positions of disturbance sources and the number of the disturbance sources; a comprehensive bird recognition model is set, the probability that the to-be-recognized object is a bird is calculated according to the recognition information of the to-be-recognized object, and when the probability that the to-be-recognized object is the bird exceeds a preset threshold value, it is judged that the to-be-recognized object is the bird; and when the to-be-identified object is judged to be a flying bird, informing airport workers to repel the bird.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of airport bird monitoring, more specifically, relates to an airport bird identification method and system based on a model. BACKGROUND

[0002] The presence of airport birds can have multiple impacts on aviation safety, operational efficiency, and economy.

[0003] Here are some major impacts:

[0004] 1. Aviation safety risks

[0005] Bird strikes are a significant hazard to aviation safety, especially during takeoff and landing phases. Collisions between birds and aircraft can lead to serious accidents, even causing plane crashes. The main risks of bird strikes include:

[0006] Airplane structure damage: Birds may hit the engines, wings, fuselage, or windshield of the aircraft, causing structural damage. Large birds or bird flocks can exert significant pressure on the wings and engines of the aircraft.

[0007] Engine failure: Bird strikes on engines can cause engine stall, especially during the initial stages of takeoff, resulting in engine loss or emergency landing.

[0008] Line of sight obstruction: Birds may hit the windshield of the cockpit, affecting the pilot's vision, or even shatter the glass, endangering the pilot's safety.

[0009] Airplane instrument damage: Bird strikes can damage the aircraft's sensors, radar systems, or other critical instruments, affecting the aircraft's navigation and control systems.

[0010] 2. Flight delays and decreased operational efficiency

[0011] Airports with frequent bird activity often need to take additional measures to reduce the risk of bird strikes, such as:

[0012] Increased patrols and monitoring: Airports will assign dedicated personnel to drive away and monitor birds, increasing workload and costs.

[0013] Flight delays: Bird presence can cause flights to be temporarily delayed or canceled, especially in large-scale bird strike incidents or when the airport has to take emergency landing measures. Delays not only affect the punctuality of flights but also may affect the trust of airlines and passengers.

[0014] Aircraft inspection and maintenance: Bird strikes can cause damage to the aircraft, and airlines need to inspect and maintain the aircraft, increasing operational costs and downtime.

[0015] In summary, the bird identification and driving away of the airport can play a role in safe production, but the existing technology has low accuracy in identifying birds, and misjudgment may occur. SUMMARY

[0016] To solve the above technical problems, the present application provides an airport bird identification method based on a model, comprising:

[0017] Through a camera or a radar, identification information of a to-be-identified object is obtained, wherein the identification information includes: a speed of the to-be-identified object, a wind speed, a flight mode of the to-be-identified object, a reference value of temperature, a temperature variation, a reference value of wind speed, a position of a disturbance source, and a number of disturbance sources;

[0018] A comprehensive bird identification model is set, and a probability that the to-be-identified object is a bird is calculated according to the identification information of the to-be-identified object, wherein when the probability that the to-be-identified object is a bird exceeds a preset threshold, it is determined that the to-be-identified object is a bird;

[0019] When it is determined that the to-be-identified object is a bird, an airport staff is notified to drive away the bird.

[0020] Further, the acceleration dynamic response model of the to-be-identified object comprises:

[0021]

[0022] wherein A mode is an acceleration dynamic response value of the to-be-identified object, used to represent the acceleration response of the to-be-identified object under different flight modes, γ′ j is a first adjustment factor of the jth flight mode, α′ j is a second adjustment factor of the jth flight mode, N is the number of flight modes, α i is a weight of the ith flight mode, β i is a speed weight of the to-be-identified object under the ith flight mode, v(t) is the speed of the to-be-identified object at time t, γ i is a wind speed weight under the ith flight mode, f wind (t) is the wind speed at time t, δ i is a third adjustment factor of the jth flight mode, v max is the maximum speed of the to-be-identified object, β′ j is a fourth adjustment factor of the jth flight mode.

[0023] Further, the temperature and airflow coupling effect model is used to describe that the flight of the to-be-identified object is affected by the double effects of airflow and temperature gradient, comprising:

[0024]

[0025] Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

[0026] Furthermore, the external disturbance model, used to describe the influence of external disturbances on the flight path of the object to be identified, includes:

[0027]

[0028] Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′ Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

[0029] Furthermore, the comprehensive bird recognition model includes:

[0030]

[0031] Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λ j′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp (t) and external disturbance value D ext .

[0032] This invention also proposes a model-based airport bird recognition system, comprising:

[0033] The identification information acquisition module is used to acquire identification information of the object to be identified through a camera or radar. The identification information includes: the speed of the object to be identified, wind speed, flight mode of the object to be identified, reference temperature value, temperature change, reference wind speed value, location of disturbance source, and number of disturbance sources.

[0034] The model setting module is used to set up a comprehensive bird recognition model and calculate the probability that the object to be identified is a bird based on the recognition information of the object to be identified. When the probability that the object to be identified is a bird exceeds a preset threshold, the object to be identified is determined to be a bird.

[0035] The determination module is used to notify airport staff to carry out bird control when the object to be identified is determined to be a bird.

[0036] Furthermore, the acceleration dynamic response model of the object to be identified includes:

[0037]

[0038] Among them, A mode γ′ is the dynamic acceleration response value of the object to be identified, used to represent the acceleration response of the object under different flight modes. j α′ is the first adjustment factor for the j-th flight mode. j α is the second adjustment factor for the j-th flight mode, N is the number of flight modes, and α i β is the weight of the i-th flight mode. i Let γ be the velocity weight of the object to be identified in the i-th flight mode, v(t) be the velocity of the object to be identified at time t, and γ be the velocity weight of the object to be identified. i f represents the weight of wind speed in the i-th flight mode. wind (t) represents the wind speed at time t, δ i v is the third adjustment factor for the j-th flight mode. max β′ represents the maximum speed of the object to be identified. j It is the fourth adjustment factor for the j-th flight mode.

[0039] Furthermore, the temperature-airflow coupling effect model is used to describe the dual influence of airflow and temperature gradient on the flight of the object to be identified, including:

[0040]

[0041] Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

[0042] Furthermore, the external disturbance model, used to describe the influence of external disturbances on the flight path of the object to be identified, includes:

[0043]

[0044] Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′ Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

[0045] Furthermore, the comprehensive bird recognition model includes:

[0046]

[0047] Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λ j′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp (t) and external disturbance value D ext .

[0048] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0049] The present invention, through the above technical solution, can identify birds flying over airport runways, and through corresponding models, improve the identification accuracy and reduce misjudgments, thereby guiding staff to accurately drive away birds and achieving the technical effect of production safety. Attached Figure Description

[0050] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention;

[0051] Figure 2 This is a system structure diagram of Embodiment 2 of the present invention. Detailed Implementation

[0052] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0053] The method provided by this invention can be implemented in a terminal environment that may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0054] A processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the terminal, and performs various functions and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and by calling data stored in the storage medium.

[0055] Storage media can include random access memory (RAM) or read-only memory (ROM). Storage media can be used to store instructions, programs, code, code sets, or instructions.

[0056] The display screen is used to show the user interface of each application.

[0057] In addition, those skilled in the art will understand that the above-described structure of the terminal does not constitute a limitation on the terminal. The terminal may include more or fewer components, or combine certain components, or have different component arrangements. For example, the terminal may also include radio frequency circuits, input units, sensors, audio circuits, power supplies, and other components, which will not be described in detail here.

[0058] Example 1

[0059] like Figure 1 As shown in the figure, this invention proposes a model-based method for airport bird identification, including:

[0060] Step 101: Obtain identification information of the object to be identified through a camera or radar. The identification information includes: the speed of the object to be identified, wind speed, flight mode of the object to be identified (for example, the flight mode may be acceleration, uniform flight, gliding, soaring, cruising, hovering, etc.), the reference value of temperature, the amount of temperature change, the reference value of wind speed, the location of disturbance sources (for example, the disturbance source may be airflow vortex or ground effect caused by buildings, etc.) and the number of disturbance sources.

[0061] Step 102: Set up a comprehensive bird recognition model and calculate the probability that the object to be identified is a bird based on the recognition information of the object to be identified. When the probability that the object to be identified is a bird exceeds a preset threshold, the object to be identified is determined to be a bird.

[0062] Specifically, the acceleration dynamic response model of the object to be identified includes:

[0063]

[0064] Among them, A mode γ′ is the dynamic acceleration response value of the object to be identified, used to represent the acceleration response of the object under different flight modes. j α′ is the first adjustment factor for the j-th flight mode. j α is the second adjustment factor for the j-th flight mode, N is the number of flight modes, and α i β is the weight of the i-th flight mode. i Let γ be the velocity weight of the object to be identified in the i-th flight mode, v(t) be the velocity of the object to be identified at time t, and γ be the velocity weight of the object to be identified. i f represents the weight of wind speed in the i-th flight mode. wind (t) represents the wind speed at time t, δ i v is the third adjustment factor for the j-th flight mode. max β′ represents the maximum speed of the object to be identified. j It is the fourth adjustment factor for the j-th flight mode.

[0065] Specifically, the temperature-airflow coupling effect model is used to describe the dual influence of airflow and temperature gradient on the flight of the object to be identified, including:

[0066]

[0067] Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

[0068] Specifically, the external disturbance model is used to describe the impact of external disturbances on the flight path of the object to be identified, including:

[0069]

[0070] Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

[0071] Specifically, the integrated bird recognition model includes:

[0072]

[0073] Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λ j′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp (t) and external disturbance value D ext .

[0074] Step 103: When the object to be identified is determined to be a bird, airport staff are notified to carry out bird control.

[0075] Example 2

[0076] like Figure 2 As shown, this embodiment of the invention also provides a model-based airport bird recognition system, comprising:

[0077] The identification information acquisition module is used to acquire identification information of the object to be identified through a camera or radar. The identification information includes: the speed of the object to be identified, wind speed, flight mode of the object to be identified, reference temperature value, temperature change, reference wind speed value, location of disturbance source, and number of disturbance sources.

[0078] The model setting module is used to set up a comprehensive bird recognition model and calculate the probability that the object to be identified is a bird based on the recognition information of the object to be identified. When the probability that the object to be identified is a bird exceeds a preset threshold, the object to be identified is determined to be a bird.

[0079] Specifically, the acceleration dynamic response model of the object to be identified includes:

[0080]

[0081] Among them, A mode γ′ is the dynamic acceleration response value of the object to be identified, used to represent the acceleration response of the object under different flight modes. j α′ is the first adjustment factor for the j-th flight mode. j α is the second adjustment factor for the j-th flight mode, N is the number of flight modes, and α i β is the weight of the i-th flight mode.i Let γ be the velocity weight of the object to be identified in the i-th flight mode, v(t) be the velocity of the object to be identified at time t, and γ be the velocity weight of the object to be identified. i f represents the weight of wind speed in the i-th flight mode. wind (t) represents the wind speed at time t, δ i v is the third adjustment factor for the j-th flight mode. max β′ represents the maximum speed of the object to be identified. j It is the fourth adjustment factor for the j-th flight mode.

[0082] Specifically, the temperature-airflow coupling effect model is used to describe the dual influence of airflow and temperature gradient on the flight of the object to be identified, including:

[0083]

[0084] Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

[0085] Specifically, the external disturbance model is used to describe the impact of external disturbances on the flight path of the object to be identified, including:

[0086]

[0087] Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′ Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

[0088] Specifically, the integrated bird recognition model includes:

[0089]

[0090] Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λj′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp (t) and external disturbance value D ext .

[0091] The determination module is used to notify airport staff to carry out bird control when the object to be identified is determined to be a bird.

[0092] Example 3

[0093] This invention also proposes a storage medium storing multiple instructions for implementing the model-based airport bird recognition method.

[0094] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0095] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: Step 101, acquiring identification information of the object to be identified through a camera or radar, wherein the identification information includes: the speed of the object to be identified, wind speed, flight mode of the object to be identified, reference value of temperature, amount of temperature change, reference value of wind speed, location of disturbance source and number of disturbance sources;

[0096] Step 102: Set up a comprehensive bird recognition model and calculate the probability that the object to be identified is a bird based on the recognition information of the object to be identified. When the probability that the object to be identified is a bird exceeds a preset threshold, the object to be identified is determined to be a bird.

[0097] Specifically, the acceleration dynamic response model of the object to be identified includes:

[0098]

[0099] Among them, A mode γ′ is the dynamic acceleration response value of the object to be identified, used to represent the acceleration response of the object under different flight modes. j α′ is the first adjustment factor for the j-th flight mode. j α is the second adjustment factor for the j-th flight mode, N is the number of flight modes, and α i β is the weight of the i-th flight mode. i Let γ be the velocity weight of the object to be identified in the i-th flight mode, v(t) be the velocity of the object to be identified at time t, and γ be the velocity weight of the object to be identified. i f represents the weight of wind speed in the i-th flight mode. wind(t) represents the wind speed at time t, δ i v is the third adjustment factor for the j-th flight mode. max β′ represents the maximum speed of the object to be identified. j It is the fourth adjustment factor for the j-th flight mode.

[0100] Specifically, the temperature-airflow coupling effect model is used to describe the dual influence of airflow and temperature gradient on the flight of the object to be identified, including:

[0101]

[0102] Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

[0103] Specifically, the external disturbance model is used to describe the impact of external disturbances on the flight path of the object to be identified, including:

[0104]

[0105] Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′ Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

[0106] Specifically, the integrated bird recognition model includes:

[0107]

[0108] Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λ j′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp(t) and external disturbance value D ext .

[0109] Step 103: When the object to be identified is determined to be a bird, airport staff are notified to carry out bird control.

[0110] Example 4

[0111] This invention also proposes an electronic device, including a processor and a storage medium connected to the processor. The storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the model-based airport bird recognition method.

[0112] Specifically, the electronic device in this embodiment can be a computer terminal, which may include one or more processors and a storage medium.

[0113] The storage medium can be used to store software programs and modules, such as the model-based airport bird recognition method in this embodiment of the invention. The corresponding program instructions / modules are executed by the processor through running the software programs and modules stored in the storage medium, thereby performing various functional applications and data processing, thus realizing the aforementioned model-based airport bird recognition method. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely configured relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0114] The processor can call the information and application stored in the storage medium through the transmission system to perform the following steps: Step 101, acquire the identification information of the object to be identified through a camera or radar, wherein the identification information includes: the speed of the object to be identified, the wind speed, the flight mode of the object to be identified, the reference value of the temperature, the amount of temperature change, the reference value of the wind speed, the location of the disturbance source and the number of disturbance sources.

[0115] Step 102: Set up a comprehensive bird recognition model and calculate the probability that the object to be identified is a bird based on the recognition information of the object to be identified. When the probability that the object to be identified is a bird exceeds a preset threshold, the object to be identified is determined to be a bird.

[0116] Specifically, the acceleration dynamic response model of the object to be identified includes:

[0117]

[0118] Among them, Amode γ′ is the dynamic acceleration response value of the object to be identified, used to represent the acceleration response of the object under different flight modes. j α′ is the first adjustment factor for the j-th flight mode. j α is the second adjustment factor for the j-th flight mode, N is the number of flight modes, and α i β is the weight of the i-th flight mode. i Let γ be the velocity weight of the object to be identified in the i-th flight mode, v(t) be the velocity of the object to be identified at time t, and γ be the velocity weight of the object to be identified. i f represents the weight of wind speed in the i-th flight mode. wind (t) represents the wind speed at time t, δ i v is the third adjustment factor for the j-th flight mode. max β′ represents the maximum speed of the object to be identified. j It is the fourth adjustment factor for the j-th flight mode.

[0119] Specifically, the temperature-airflow coupling effect model is used to describe the dual influence of airflow and temperature gradient on the flight of the object to be identified, including:

[0120]

[0121] Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

[0122] Specifically, the external disturbance model is used to describe the impact of external disturbances on the flight path of the object to be identified, including:

[0123]

[0124] Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′ Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

[0125] Specifically, the integrated bird recognition model includes:

[0126]

[0127] Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λ j′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp (t) and external disturbance value D ext .

[0128] Step 103: When the object to be identified is determined to be a bird, airport staff are notified to carry out bird control.

[0129] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0130] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0131] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The system embodiments described above are merely illustrative; for example, the division of 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 system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0132] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0133] Furthermore, the functional units in the various embodiments of the present invention 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.

[0134] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, optical disks, and other media capable of storing program code.

[0135] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A model-based method for airport bird identification, characterized in that, include: The identification information of the object to be identified is obtained through a camera or radar. The identification information includes: the speed of the object to be identified, the wind speed, the flight mode of the object to be identified, the reference value of the temperature, the amount of temperature change, the reference value of the wind speed, the location of the disturbance source, and the number of disturbance sources. A comprehensive bird recognition model is set up, and the probability that the object to be identified is a bird is calculated based on the recognition information of the object to be identified. When the probability that the object to be identified is a bird exceeds a preset threshold, the object to be identified is determined to be a bird. When the object to be identified is determined to be a bird, airport staff will be notified to carry out bird control measures.

2. The model-based airport bird recognition method as described in claim 1, characterized in that, The acceleration dynamic response model of the object to be identified includes: Among them, A mode γ′ is the dynamic acceleration response value of the object to be identified, used to represent the acceleration response of the object under different flight modes. j Let α′ be the first adjustment factor for the j-th flight mode. j α is the second adjustment factor for the j-th flight mode, N is the number of flight modes, and α i β is the weight of the i-th flight mode. i Let γ be the velocity weight of the object to be identified in the i-th flight mode, v(t) be the velocity of the object to be identified at time t, and γ be the velocity weight of the object to be identified. i f represents the weight of wind speed in the i-th flight mode. wind (t) represents the wind speed at time t, δ i v is the third adjustment factor for the j-th flight mode. max β′ represents the maximum speed of the object to be identified. j It is the fourth adjustment factor for the j-th flight mode.

3. The model-based airport bird recognition method as described in claim 2, characterized in that, The temperature-airflow coupling effect model is used to describe the dual influence of airflow and temperature gradient on the flight of the object to be identified, including: Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

4. The model-based airport bird recognition method as described in claim 3, characterized in that, The external disturbance model is used to describe the impact of external disturbances on the flight path of the object to be identified, including: Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′ Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

5. The model-based airport bird recognition method as described in claim 4, characterized in that, The comprehensive bird recognition model includes: Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λ j′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp (t) and external disturbance value D ext .

6. A model-based airport bird recognition system, characterized in that, include: The identification information acquisition module is used to acquire identification information of the object to be identified through a camera or radar. The identification information includes: the speed of the object to be identified, wind speed, flight mode of the object to be identified, reference temperature value, temperature change, reference wind speed value, location of disturbance source, and number of disturbance sources. The model setting module is used to set up a comprehensive bird recognition model and calculate the probability that the object to be identified is a bird based on the recognition information of the object to be identified. When the probability that the object to be identified is a bird exceeds a preset threshold, the object to be identified is determined to be a bird. The determination module is used to notify airport staff to carry out bird control when the object to be identified is determined to be a bird.

7. The model-based airport bird recognition system as described in claim 6, characterized in that, The acceleration dynamic response model of the object to be identified includes: Among them, A mode γ′ is the dynamic acceleration response value of the object to be identified, used to represent the acceleration response of the object under different flight modes. j Let α′ be the first adjustment factor for the j-th flight mode. j α is the second adjustment factor for the j-th flight mode, N is the number of flight modes, and α i β is the weight of the i-th flight mode. i Let γ be the velocity weight of the object to be identified in the i-th flight mode, v(t) be the velocity of the object to be identified at time t, and γ be the velocity weight of the object to be identified. i f represents the weight of wind speed in the i-th flight mode. wind (t) represents the wind speed at time t, δ i v is the third adjustment factor for the j-th flight mode. max β′ represents the maximum speed of the object to be identified. j It is the fourth adjustment factor for the j-th flight mode.

8. The model-based airport bird recognition system as described in claim 7, characterized in that, The temperature-airflow coupling effect model is used to describe the dual influence of airflow and temperature gradient on the flight of the object to be identified, including: Among them, C wind-temp (t) represents the coupling effect value of temperature and airflow at time t, δ1 is the first adjustment factor of the temperature and airflow coupling effect model, and T ref Let V be the baseline temperature, ΔT(t′) be the temperature change at time t′, α″ be the second adjustment factor in the temperature-airflow coupling effect model, and V be the reference temperature. wind f is the baseline value for wind speed. wind (t′) represents the wind speed at time t′, and β″ is the third adjustment factor in the coupling effect model of temperature and airflow.

9. The model-based airport bird recognition system as described in claim 8, characterized in that, The external disturbance model is used to describe the impact of external disturbances on the flight path of the object to be identified, including: Among them, D ext The external disturbance value, γ″ i′ Let r be the adjustment factor for the i′-th disturbance source, and r′ be the position of the object to be identified. i′ Let ω be the position of the i′-th disturbance source. i′ Let φ be the frequency of the i′-th disturbance source. i′ Let σ be the phase of the i′-th disturbance source. i′ Let N be the spatial extension range of the i′-th disturbance source, and N′ be the number of disturbance sources.

10. The model-based airport bird recognition system as described in claim 9, characterized in that, The comprehensive bird recognition model includes: Among them, R bird (t) represents the probability that the object to be identified is a bird at time t, σ′ is the Sigmoid function, M is the number of factors, and λ j′ Let A be the weight of the j′-th factor, where the factor is the acceleration dynamic response value A of the object to be identified. mode The coupling effect value C between temperature and airflow at time t. wind-temp (t) and external disturbance value D ext .

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