Aerial pesticide application method, device and system based on pesticide liquid droplet drift trajectory prediction

Abstract

The application provides an aerial pesticide application method, device and system based on pesticide mist droplet drift trajectory prediction, which comprises the following steps: obtaining the actual value of the environmental parameter in the target area in the preparation period; obtaining the simulation value of the target parameter of the target pesticide mist droplet in the first period based on the flight parameter and the spraying parameter of the target aerial pesticide application task and the actual value of the environmental parameter in the target area in the preparation period; obtaining the simulation value of the target parameter of the target pesticide mist droplet in the second period based on the simulation value of the target parameter of the target pesticide mist droplet at the end time of the first period; and executing the target aerial pesticide application task under the condition that the execution condition of the target aerial pesticide application task is met. The aerial pesticide application method, device and system based on pesticide mist droplet drift trajectory prediction can more accurately and efficiently estimate the drift trajectory of the pesticide mist droplet, and can more accurately and efficiently perform aerial pesticide application based on the drift trajectory of the pesticide mist droplet.

Description

Technical Field

[0001] This invention relates to the field of smart agriculture technology, and in particular to an aerial spraying method, apparatus and system based on the prediction of pesticide droplet drift trajectory. Background Technology

[0002] Aerial spraying refers to the operation of spraying pesticides on farmland or other target areas using aircraft equipped with spraying equipment. Compared with traditional manual and semi-mechanized spraying operations, aerial spraying has advantages such as high pesticide utilization rate, large pesticide load, long flight time, and less restriction by terrain.

[0003] However, during aerial spraying, pesticide droplets are prone to drift due to various factors such as aircraft wake vortices, downwash, and ambient wind fields. This drift can lead to adverse effects such as soil and water pollution, damage to non-target crops, and threats to human and animal health. Therefore, eliminating the adverse effects of pesticide droplet drift during aerial spraying is crucial for improving agricultural efficiency and reducing potential harm to the environment and non-target crops.

[0004] In related technologies, the drift trajectory of pesticide droplets during aerial spraying can be estimated through sampling measurements. However, this method can only be used after the pesticide droplets have settled on the ground or been captured by the sampling device, making it difficult to accurately obtain the drift trajectory of the pesticide droplets in space. Consequently, it is difficult to accurately conduct aerial spraying operations based on the drift trajectory of the pesticide droplets in space. Furthermore, estimating the drift trajectory of pesticide droplets during aerial spraying through sampling measurements requires significant labor and time costs.

[0005] In related technologies, numerical simulations can be used to model the aerial spraying process and estimate the drift trajectory of pesticide droplets during the aerial spraying operation. However, numerical simulations of the aerial spraying process typically require significant computational resources and are time-consuming, making it difficult to efficiently obtain the drift trajectory of pesticide droplets in space. Consequently, it is challenging to achieve efficient aerial spraying operations based on the drift trajectory of pesticide droplets in space. Summary of the Invention

[0006] This invention provides a method, apparatus, and system for aerial pesticide application based on the prediction of pesticide droplet drift trajectories. This addresses the shortcomings of existing technologies, which struggle to accurately and efficiently acquire the drift trajectories of pesticide droplets during aerial pesticide application, thus hindering accurate and efficient aerial pesticide application based on these trajectories. The invention achieves more accurate and efficient acquisition of pesticide droplet drift trajectories during aerial pesticide application, enabling more accurate and efficient aerial pesticide application based on these trajectories.

[0007] This invention provides an aerial spraying method based on the prediction of the drift trajectory of liquid spray droplets, comprising the following steps.

[0008] When it is determined that a target aerial spraying operation task has been triggered, the actual values ​​of environmental parameters in the target area during the preparation period are obtained. The target aerial spraying operation task is an aerial spraying operation task that sprays the target pesticide solution onto the crops in the target area during the target period. The preparation period is a period of a first preset duration before the target period. The environmental parameters include wind speed.

[0009] Based on the flight parameters and spraying parameters of the target aerial spraying operation and the actual values ​​of the environmental parameters in the target area during the preparation period, simulated values ​​of the target parameters of the target liquid droplets are obtained during the first time period. The spraying parameters include the spraying angle, the initial particle size of the liquid droplets, and the initial velocity of the liquid droplets. The flight parameters include the flight altitude and / or flight speed. The start time of the first time period is the time when the target liquid droplets are sprayed out, and the end time of the first time period is the time after the start time of the first time period, which is the second preset time. The target parameters include particle size information, position information, and velocity information.

[0010] Based on the simulated value of the target parameters of the target liquid droplets at the end time of the first time period, the actual value of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation, the simulated value of the target parameters of the target liquid droplets in the second time period is obtained. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the third preset time after the start time of the second time period.

[0011] Based on the simulated values ​​of the target parameters of the target liquid droplets in the first time period and the simulated values ​​of the target parameters of the target liquid droplets in the second time period, if the execution conditions of the target aerial spraying operation are met, the target aerial spraying operation is executed.

[0012] According to the present invention, an aerial pesticide application method based on the prediction of pesticide droplet drift trajectory, wherein the method for obtaining simulated values ​​of target parameters of target pesticide droplets within a first time period is based on the flight parameters and spraying parameters of the target aerial pesticide application task and the actual values ​​of environmental parameters within the target area during the preparation period, includes:

[0013] The spraying parameters of the target aerial spraying operation and the actual values ​​of the environmental parameters in the target area during the preparation period are input into the droplet drift trajectory prediction model to obtain the simulated values ​​of the target parameters of the target liquid droplets in the first time period output by the droplet drift trajectory prediction model.

[0014] The droplet drift trajectory prediction model is obtained by training based on sample data and corresponding sample labels. The sample data includes flight parameters and spraying parameters of the sample aerial spraying operation task, as well as the actual values ​​of environmental parameters in the sample area during the sample preparation period. The sample labels include simulated values ​​of target parameters of the sample liquid droplets during the third time period. The start time of the third time period is the time when the sample liquid droplets are sprayed, and the end time of the third time period is the time after the start time of the third time period for the second preset duration. The sample aerial spraying operation task is an aerial spraying operation task that sprays sample liquid in the sample area during the sample time period. The sample preparation period is the time period before the sample time period for the first preset duration.

[0015] According to the present invention, an aerial spraying operation method based on the prediction of pesticide droplet drift trajectory, wherein the method for obtaining the simulated values ​​of the target parameters of the target pesticide droplets in a second time period based on the simulated values ​​of the target parameters of the target pesticide droplets at the end time of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation time period, and the flight parameters and spraying parameters of the target aerial spraying operation task, includes:

[0016] Based on the flight parameters of the target aerial spraying operation, the wind speed of the wind field generated by the aircraft during the execution of the target aerial spraying operation is calculated and used as the target wind speed.

[0017] Based on the simulated values ​​of the target parameters of the target liquid droplets at the end time of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation time period, and the spraying parameters of the target aerial spraying operation, the Reynolds number, aerodynamic drag, volume, mass, and gravity of the target liquid droplets are calculated.

[0018] Based on the Reynolds number, aerodynamic drag, volume, mass, and gravity of the target drug droplet, and the first [time period]... jThe simulated values ​​of the target parameters of the target drug droplets at the nth time point are used to calculate the nth time period within the second time period. j Simulated values ​​of the target parameters of the target drug droplets at +1 time points. j Represents a positive integer with an initial value of 1. The first time point within the second time period is the start time of the second time period, and the second time point within the second time period is the start time of the second time period. j The time node and the second time period j +1 time interval between the fourth preset duration j It represents a positive integer with an initial value of 1.

[0019] According to the aerial spraying operation method based on the prediction of liquid droplet drift trajectory provided by the present invention, the sample labels corresponding to the sample data are obtained based on the following steps:

[0020] A three-dimensional model of the sample aircraft is obtained by performing a three-dimensional modeling.

[0021] Based on the three-dimensional model of the sample aircraft and the flight parameters of the sample aerial spraying operation, the wind field of the sample aircraft during flight is numerically simulated to obtain the wind field model of the sample aircraft during flight.

[0022] Based on the spraying parameters of the sample aerial spraying operation, the motion trajectory of the sample pesticide droplets is simulated in the wind field model during the flight of the sample aircraft, and the simulated values ​​of the target parameters of the sample pesticide droplets in the third time period corresponding to the sample data are obtained.

[0023] According to the present invention, an aerial pesticide application method based on the prediction of pesticide droplet drift trajectory is provided. The calculation formula for the target wind speed based on the flight parameters of the target aerial pesticide application task is as follows:

[0024]

[0025] in, Indicates the target wind speed; This represents a coefficient determined based on atmospheric turbulence. The flight altitude of the target aerial pesticide application operation is indicated. If the flight parameters of the target aerial pesticide application operation do not include the flight altitude, the flight altitude of the target aerial pesticide application operation is a preset flight altitude.

[0026] According to the present invention, an aerial pesticide application method based on the prediction of pesticide droplet drift trajectory is provided. The method determines whether the execution conditions of the target aerial pesticide application task are met by using simulated values ​​of target parameters of the target pesticide droplets in the first time period and simulated values ​​of target parameters of the target pesticide droplets in the second time period. The method includes:

[0027] Based on the avoidance zone of the target aerial pesticide application task, the simulated values ​​of the target parameters of the target pesticide droplets in the first time period, and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period, it is determined whether the target pesticide droplets will enter the avoidance zone of the target aerial pesticide application task after the target aerial pesticide application task is executed.

[0028] If, after determining that the target pesticide droplets will not enter the avoidance zone of the target aerial pesticide application operation, the execution conditions of the target aerial pesticide application operation are met, and if, after determining that the target pesticide droplets will enter the avoidance zone of the target aerial pesticide application operation, the flight parameters and spraying parameters of the target aerial pesticide application operation and at least one of the target time period are updated, the process returns to the step of obtaining the actual values ​​of environmental parameters within the target area of ​​the preparation time period, until the execution conditions of the target aerial pesticide application operation are met.

[0029] The present invention also provides an aerial spraying device based on the prediction of the drift trajectory of liquid spray droplets, comprising the following modules:

[0030] The data acquisition module is used to acquire the actual values ​​of environmental parameters in the target area during the preparation period when the target aerial spraying operation task is determined to be triggered. The target aerial spraying operation task is an aerial spraying operation task that sprays the target pesticide solution onto the crops in the target area during the target period. The preparation period is a period of a first preset duration before the target period. The environmental parameters include wind speed.

[0031] The first estimation module is used to obtain simulated values ​​of target parameters of the target liquid pesticide droplets within a first time period based on the flight parameters and spraying parameters of the target aerial spraying operation and the actual values ​​of environmental parameters in the target area during the preparation period. The spraying parameters include spraying angle, initial particle size of liquid pesticide droplets, and initial velocity of liquid pesticide droplets. The flight parameters include flight altitude and / or flight speed. The start time of the first time period is the time when the target liquid pesticide droplets are sprayed out, and the end time of the first time period is the time after the start time of the first time period, which is a second preset time. The target parameters include particle size information, position information, and velocity information.

[0032] The second estimation module is used to obtain the simulated value of the target parameter of the target liquid droplet in the second time period based on the simulated value of the target parameter of the target liquid droplet at the end time of the first time period, the actual value of the environmental parameter in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation task. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the time after the start time of the second time period, which is the third preset time period.

[0033] The task execution module is used to execute the target aerial pesticide application task when the execution conditions of the target aerial pesticide application task are met, based on the simulated values ​​of the target parameters of the target pesticide droplets in the first time period and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period.

[0034] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aerial spraying operation method based on the prediction of the drift trajectory of liquid droplets as described above.

[0035] The present invention also provides an aerial spraying system based on the prediction of the drift trajectory of liquid droplets, comprising: electronic equipment, an aircraft, and a spraying device as described above; the electronic equipment is electrically connected to the aircraft and the spraying device respectively; the spraying device is connected to the aircraft;

[0036] The aircraft is used to move the spraying device in response to the control of the electronic equipment;

[0037] The spraying device is used to spray liquid droplets in response to the control of the electronic device.

[0038] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aerial spraying operation method based on the prediction of the drift trajectory of liquid droplets as described above.

[0039] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the aerial spraying operation method based on the prediction of the drift trajectory of liquid droplets as described above.

[0040] The present invention provides a method, apparatus, and system for aerial pesticide application based on the prediction of pesticide droplet drift trajectories. This method, apparatus, and system, upon determining that a target aerial pesticide application task has been triggered, acquires the actual values ​​of environmental parameters within the target area during the preparation period. Based on the flight and spraying parameters of the target aerial pesticide application task and the actual values ​​of the environmental parameters within the target area during the preparation period, it acquires simulated values ​​of target parameters for the target pesticide droplets within a first time period. Based on the simulated values ​​of target parameters for the target pesticide droplets at the end of the first time period, the actual values ​​of the environmental parameters within the target area during the preparation period, and the flight and spraying parameters of the target aerial pesticide application task, it acquires simulated values ​​of target parameters for the second time period. The simulated values ​​of target parameters for the target pesticide droplets within a segment, and then, based on the simulated values ​​of target parameters for the target pesticide droplets in the first time period and the simulated values ​​of target parameters for the target pesticide droplets in the second time period, determine the execution conditions that meet the target aerial pesticide application task, and then execute the target aerial pesticide application task. This can more accurately and efficiently estimate the drift trajectory of pesticide droplets in space, and thus, based on the drift trajectory of pesticide droplets in space, conduct more accurate and efficient aerial pesticide application operations. It can also better avoid adverse effects such as water and soil pollution, non-target crops, and threats to human and animal health caused by pesticide droplet drift during aerial pesticide application operations. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the aerial spraying operation method based on the prediction of the drift trajectory of liquid spray droplets provided by the present invention.

[0043] Figure 2 This is a schematic diagram of the aerial spraying device based on the prediction of the drift trajectory of liquid droplets provided by the present invention.

[0044] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0046] In the description of the invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" 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 mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0047] In the description of this application, the terms "first," "second," etc., are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, in the description of this application, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects have an "or" relationship.

[0048] It should be noted that aerial crop protection refers to the use of aircraft for pest and disease control, weeding, and field plant growth management. With the development of modern precision agriculture technology, aerial crop protection will provide agricultural production with more efficient and environmentally friendly solutions.

[0049] In aerial plant protection, aerial spraying refers to the operation of spraying pesticides on farmland or other target areas by aircraft carrying spraying equipment.

[0050] Related technologies can estimate the drift trajectory of pesticide droplets during aerial spraying operations through sampling measurements. Sampling devices can include, but are not limited to, water-sensitive paper, cotton thread, polyethylene cards, and petri dishes, as well as fluorescent paper tape and capacitive blade sensors. However, the above methods can only be used for analysis after the pesticide droplets have been deposited on the ground or captured by the sampling device. It is difficult to accurately obtain the drift trajectory of the pesticide droplets in space, and therefore difficult to accurately control aerial spraying operations based on the drift trajectory of the pesticide droplets in space.

[0051] Furthermore, if the number of time nodes is set too small, their distribution will be sparse, resulting in low spatial resolution and insufficient sampled data. This affects the accuracy of estimating the drift trajectory of pesticide droplets during aerial spraying operations. Conversely, if the number of time nodes is set too large, significant manpower and time costs will be required for sampling, leading to low efficiency and high costs in obtaining the drift trajectory of pesticide droplets in space.

[0052] In related technologies, computational fluid dynamics (CFD) software can be used to simulate the aerial pesticide application process through numerical simulation, thereby estimating the drift trajectory of pesticide droplets during the aerial pesticide application operation. However, the aforementioned CFD software requires enormous computational resources, and the computation time required to simulate the aerial pesticide application process is long. It is difficult to complete numerical simulations of large areas exceeding 100 meters, making it difficult to quickly and efficiently obtain the drift trajectory of pesticide droplets in space in practical applications. Consequently, it is difficult to achieve efficient control of aerial pesticide application operations based on the drift trajectory of pesticide droplets in space.

[0053] In view of the shortcomings of related technologies in estimating the drift trajectory of pesticide droplets during aerial pesticide application operations, such as large computational resource requirements, long time consumption, and limited simulation range, it is difficult to accurately and efficiently obtain the drift trajectory of pesticide droplets during aerial pesticide application operations in diverse configurations and complex operating environments. Consequently, it is difficult to accurately and efficiently control aerial pesticide application operations based on the drift trajectory of pesticide droplets. This invention provides an aerial pesticide application operation method based on the prediction of pesticide droplet drift trajectory.

[0054] The aerial spraying method based on pesticide droplet drift trajectory prediction provided by this invention can estimate the drift trajectory of pesticide droplets during aerial spraying within ten seconds, representing a speed improvement of more than four orders of magnitude compared to estimation based on CFD software. This method considers the effects of Earth's gravity, ambient wind, air resistance, and air humidity on the pesticide droplets during their movement, supported by rigorous physical formulas and possessing high prediction accuracy. Furthermore, this method directly provides the spatial distribution and velocity of pesticide droplets at any given time, and displays this information visually, helping agricultural and forestry aerial spraying personnel to maintain sufficient safety distances during actual operations. It can also provide a reference for the design and operational planning of agricultural drones.

[0055] The following is combined Figure 1 This invention describes an aerial pesticide application method based on the prediction of pesticide droplet drift trajectories.

[0056] Figure 1 This is a flowchart illustrating the aerial pesticide application method based on the prediction of pesticide droplet drift trajectory provided by the present invention, as shown below. Figure 1 As shown, the method includes the following steps: Step 101: When it is determined that the target aerial spraying operation task is triggered, the actual values ​​of environmental parameters in the target area during the preparation period are obtained. The target aerial spraying operation task is an aerial spraying operation task that sprays the target pesticide solution on the crops in the target area during the target period. The preparation period is the period of the first preset duration before the target period. The environmental parameters include wind speed.

[0057] It should be noted that the execution entity in this embodiment of the invention is an aerial spraying device based on the prediction of pesticide droplet drift trajectories. This aerial spraying device based on the prediction of pesticide droplet drift trajectories can be configured in electronic devices such as smart terminals, computers, or servers.

[0058] Specifically, technicians can trigger aerial spraying crop tasks by inputting control commands, and can input task parameters for the aforementioned target aerial spraying operation tasks based on actual needs.

[0059] The parameters of the above-mentioned target aerial spraying operation may include, but are not limited to, the execution area, target time period, spraying altitude, pesticide type, and spraying parameters of the above-mentioned target aerial spraying operation. The spraying parameters may include, but are not limited to, spraying altitude, spraying angle, and initial particle size of pesticide droplets. The initial particle size of pesticide droplets refers to the particle size of pesticide droplets when they are sprayed out by the spraying equipment.

[0060] It should be noted that, in this embodiment of the invention, the pesticide solution that needs to be sprayed onto the execution area for the above-mentioned target aerial pesticide application operation is defined as the target pesticide solution.

[0061] If it is determined that a target aerial spraying operation has been triggered, the time period before the target time period of the target aerial spraying operation can be determined as a preparation period based on the task parameters of the target aerial spraying operation. Then, various sensors can be used to collect the actual values ​​of environmental parameters within the execution area of ​​the target aerial spraying operation during the preparation period.

[0062] It should be noted that the environmental parameters in the embodiments of the present invention may include wind speed, as well as humidity, temperature and air pressure.

[0063] It should be noted that the first preset duration in the embodiments of the present invention can be determined based on prior knowledge and / or actual conditions. For example, the value of the first preset duration can be from 60 minutes to 120 minutes. The specific value of the first preset duration is not limited in the embodiments of the present invention.

[0064] Step 102: Based on the flight parameters and spraying parameters of the target aerial spraying operation and the actual values ​​of environmental parameters in the target area during the preparation period, obtain the simulated values ​​of the target parameters of the target liquid droplets in the first time period. The spraying parameters include the spraying angle, the initial particle size of the liquid droplets, and the initial velocity of the liquid droplets. The flight parameters include the flight altitude and / or flight speed. The start time of the first time period is the time when the target liquid droplets are sprayed out, and the end time of the first time period is the time after the start time of the first time period, which is the second preset time. The target parameters include particle size information, position information, and velocity information.

[0065] Specifically, after obtaining the actual values ​​of environmental parameters within the target area of ​​the target aerial spraying operation during the preparation period, the simulated values ​​of the target parameters of the target liquid droplets in the first time period can be obtained based on the actual values ​​of the environmental parameters and the spraying altitude of the target aerial spraying operation, through numerical calculation, mathematical statistics, or deep learning techniques.

[0066] It should be noted that the second preset duration in the embodiments of the present invention can be determined based on prior knowledge and / or actual conditions. For example, the value of the second preset duration can be between 2 seconds and 4 seconds. The specific value of the second preset duration is not limited in the embodiments of the present invention.

[0067] It is understood that the target liquid droplets in the embodiments of the present invention are droplets sprayed out by the spraying equipment. The number of target liquid droplets in the embodiments of the present invention is multiple.

[0068] It should be noted that if the flight parameters for the target aerial pesticide application operation do not include flight altitude, the flight altitude for the target aerial pesticide application operation will be the preset flight altitude. Similarly, if the flight parameters for the target aerial pesticide application operation do not include the flight speed of the pesticide droplets, the flight speed for the target aerial pesticide application operation will be the preset flight speed.

[0069] It should be noted that, if the initial particle size of the pesticide droplets is not included in the spraying parameters for the target aerial pesticide application operation, the initial velocity of the pesticide droplets in the target aerial pesticide application operation shall be a preset velocity. If the initial particle size of the pesticide droplets is not included in the spraying parameters for the target aerial pesticide application operation, the initial particle size of the pesticide droplets in the target aerial pesticide application operation shall be a preset particle size.

[0070] As an optional embodiment, based on the flight parameters and spraying parameters of the target aerial spraying operation and the actual values ​​of environmental parameters in the target area during the preparation period, the simulated values ​​of the target parameters of the target liquid droplets in the first time period are obtained, including: inputting the spraying parameters of the target aerial spraying operation and the actual values ​​of environmental parameters in the target area during the preparation period into the droplet drift trajectory prediction model, and obtaining the simulated values ​​of the target parameters of the target liquid droplets in the first time period output by the droplet drift trajectory prediction model.

[0071] The droplet drift trajectory prediction model is obtained by training based on sample data and corresponding sample labels. The sample data includes the flight parameters and spraying parameters of the sample aerial spraying operation task, as well as the actual values ​​of environmental parameters in the sample area during the sample preparation period. The sample labels include the simulated values ​​of the target parameters of the sample liquid droplets in the third time period. The start time of the third time period is the time when the sample liquid droplets are sprayed, and the end time of the third time period is the second preset time after the start time of the third time period. The sample aerial spraying operation task is the aerial spraying operation task of spraying sample liquid in the sample area during the sample time period. The sample preparation period is the first preset time period before the sample time period.

[0072] Specifically, the droplet drift trajectory prediction model in this embodiment of the invention can be constructed based on the Transformer model. It is obtained by training the model with the actual values ​​of the spraying parameters and flight parameters of the sample aerial spraying operation task and the environmental parameters in the sample area during the sample preparation period, and the simulated values ​​of the target parameters of the sample liquid droplets in the third time period corresponding to the above sample data as sample labels.

[0073] It should be noted that the sample time period in the embodiments of the present invention can be any time period, and the spraying parameters of the sample aerial spraying operation can be any value.

[0074] Understandably, in order to improve the robustness of the trained droplet drift trajectory prediction model, the selection of sample time periods and the determination of spraying parameters for sample aerial spraying operations can be as diverse as possible.

[0075] As an optional embodiment, the sample labels corresponding to the sample data are obtained based on the following steps: performing three-dimensional modeling of the sample aircraft to obtain a three-dimensional model of the sample aircraft.

[0076] Specifically, in this embodiment of the invention, modeling software or deep learning technology can be used to perform three-dimensional modeling of the sample aircraft to obtain a three-dimensional model of the sample aircraft.

[0077] Based on the three-dimensional model of the sample aircraft and the flight parameters of the sample aerial spraying operation, the wind field of the sample aircraft during flight is numerically simulated to obtain the wind field model of the sample aircraft during flight.

[0078] Specifically, after obtaining the three-dimensional model of the sample aircraft, the three-dimensional model of the sample aircraft can be imported into the XFlow software, and the flight parameters of the sample aerial spraying operation can be input. Then, a numerical model of the wind field of the sample aircraft during flight can be generated in the XFlow software to obtain the wind field model of the sample aircraft during flight.

[0079] It should be noted that XFlow software is a new method for CFD calculation based on the Lattice Boltzmann Method (LBM). XFlow software can accurately capture the development process of rotor tip vortices and has great advantages in studying and analyzing the distribution of the downwash wind field and the drift of the propellant in aircraft.

[0080] Based on the spraying parameters of the sample aerial spraying operation, the motion trajectory of the sample pesticide droplets is simulated in the wind field model during the flight of the sample aircraft, and the simulated values ​​of the target parameters of the sample pesticide droplets in the third time period corresponding to the sample data are obtained.

[0081] Specifically, after obtaining the wind field model of the sample aircraft during flight, spraying equipment can be added to the three-dimensional model of the sample aircraft in the XFlow software, and the spraying parameters of the sample aerial spraying operation can be input. Then, the motion trajectory of the sample liquid droplets under the influence of the downwash wind field of the sample aircraft can be numerically simulated in the XFlow software. Based on the numerical simulation results, the simulated values ​​of the target parameters of the sample liquid droplets in the third time period corresponding to the above sample data can be obtained.

[0082] After obtaining the actual values ​​of environmental parameters within the target area of ​​the preparatory aerial spraying operation, the flight parameters and spraying parameters of the target aerial spraying operation, as well as the actual values ​​of environmental parameters within the target area of ​​the preparatory aerial spraying operation, can be input into the trained droplet drift trajectory prediction model.

[0083] The trained droplet drift trajectory prediction model can predict the trajectory of the target pesticide droplets starting from the beginning of the first time period, based on the flight parameters and spraying parameters of the target aerial pesticide application operation and the actual values ​​of environmental parameters within the target area of ​​the target aerial pesticide application operation during the preparation period.

[0084] Specifically, starting from the beginning of the first time period, multiple time nodes can be determined within the first time period according to preset intervals. For the first time period...i At each time point, the trained droplet drift trajectory prediction model can, based on the flight and spraying parameters of the aforementioned target aerial spraying operation and the actual values ​​of environmental parameters within the target area of ​​the aforementioned preparatory period, obtain the first time value of multiple target pesticide droplets closest to any target pesticide droplet within the first time period. i Simulated values ​​of the target parameters at +1 time points. i Represents a positive integer greater than 0.

[0085] Step 103: Based on the simulated values ​​of the target parameters of the target liquid droplets at the end time of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation, obtain the simulated values ​​of the target parameters of the target liquid droplets in the second time period. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the time three preset durations after the start time of the second time period.

[0086] Specifically, after obtaining the simulated values ​​of the target parameters of the target liquid droplets in the first time period, the simulated values ​​of the target parameters of the target liquid droplets in the second time period can be obtained based on the simulated values ​​of the target parameters of the target liquid droplets at the end of the first time period and the actual values ​​of the environmental parameters in the target area of ​​the target aerial spraying operation task in the preparatory period, through numerical calculation, mathematical statistics or deep learning technology.

[0087] It should be noted that the third preset duration in the embodiments of the present invention can be determined based on prior knowledge and / or actual conditions. For example, the value of the third preset duration can be 40 seconds to 60 seconds, or the third preset duration can be determined based on the time required for the target liquid droplets to settle to the ground. The specific value of the third preset duration is not limited in the embodiments of the present invention.

[0088] As an optional embodiment, based on the simulated value of the target parameters of the target liquid droplets at the end time of the first time period, the actual value of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation, the simulated value of the target parameters of the target liquid droplets in the second time period is obtained, including: based on the flight parameters of the target aerial spraying operation, the wind speed of the wind field generated by the aircraft during the execution of the target aerial spraying operation is calculated as the target wind speed.

[0089] As an optional embodiment, the formula for calculating the target wind speed based on the flight parameters of the target aerial spraying operation is as follows:

[0090]

[0091] in, Indicates the target wind speed; This represents a coefficient determined based on atmospheric turbulence. This indicates the flight altitude of the target aerial pesticide application operation. If the flight parameters of the target aerial pesticide application operation do not include the flight altitude, the flight altitude of the target aerial pesticide application operation is the preset flight altitude.

[0092] Based on the simulated values ​​of the target parameters of the target liquid droplets at the end of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation period, and the spraying parameters of the target aerial spraying operation, the Reynolds number, aerodynamic drag, volume, mass, and gravity of the target liquid droplets are calculated.

[0093] Specifically, in this embodiment of the invention, the Reynolds number of the target drug droplet can be calculated using the following formula. :

[0094]

[0095] in, Indicates air density; The particle size of the target drug droplets indicates the end time of the first time period; This indicates the velocity of the target liquid droplets at the end of the first time period; This indicates the actual wind speed within the target area during the preparation period.

[0096] In this embodiment of the invention, the aerodynamic resistance of the target drug droplets can be calculated using the following formula. :

[0097]

[0098] in, This represents the drag coefficient.

[0099] It should be noted that the drag coefficient in the embodiments of the present invention The value of is affected by the Reynolds number corresponding to the target drug droplet. Impact, drag coefficient The values ​​are determined as follows:

[0100] exist In this case, (Stokes formula);

[0101] exist In this case, (Allen formula);

[0102] exist In this case, (Newton formula);

[0103] In this embodiment of the invention, the volume of the target drug droplet can be calculated using the following formula. :

[0104] .

[0105] In this embodiment of the invention, the mass of the target drug droplet can be calculated using the following formula. :

[0106] .

[0107] In this embodiment of the invention, the gravity of the target drug droplet can be calculated using the following formula. :

[0108]

[0109] in, It represents the acceleration due to gravity.

[0110] It should be noted that, based on the simulated values ​​of the target parameters of the target pesticide droplets at the end of the first time period, the actual values ​​of the environmental parameters within the target area during the preparation period, and the spraying parameters of the target aerial spraying operation, the evaporation rate of the target pesticide droplets per unit time can also be calculated. The evaporation rate of the target pesticide droplets per unit time can affect the change in the droplet size over time, thereby affecting the droplet's drift trajectory.

[0111] Based on the Reynolds number, aerodynamic drag, volume, mass, and gravity of the target drug droplets, and the second time period... j Simulated values ​​of target parameters for the target drug droplets at each time point are used to calculate the target parameters for the second time period. j Simulated values ​​of target parameters for the target drug droplets at +1 time point. j Represents a positive integer with an initial value of 1. The first time point in the second time period is the start time of the second time period, and the second time point in the second time period is the start time of the second time period. j The first time node and the second time period j +1 time interval between the fourth preset duration.

[0112] It is understandable that the particle size of the target drug droplets at the first time point of the second time period... The particle size of the target drug droplets at the end of the first time period. The velocity of the target drug droplets at the first time point of the second period. The velocity of the target liquid droplets at the end of the first time period. .

[0113] It should be noted that the fourth preset duration in the embodiments of the present invention can be determined based on prior knowledge and / or actual conditions. For example, the value range of the fourth preset duration can be between 0.1s and 0.5s. The specific value of the fourth preset duration is not limited in the embodiments of the present invention.

[0114] Specifically, in this embodiment of the invention, the second time period can be calculated using the following formula. j Gravitational acceleration of target drug droplets at each time point :

[0115]

[0116] in, Indicates the second time period j The mass of the target drug droplets at each time point; Indicates the second time period j The gravity of the target drug droplets at each time point.

[0117] In this embodiment of the invention, the second time period can be calculated using the following formula. j +1 time point target drug droplet velocity :

[0118]

[0119] in, This indicates the fourth preset duration.

[0120] In this embodiment of the invention, the second time period can be calculated using the following formula. j +1 time point target drug droplet position :

[0121]

[0122]

[0123] in, Indicates the second time period j The location of the target drug droplets at each time point; Indicates the second time period j From the first time point to the second period j +1 time point. The distance the target drug droplet traveled.

[0124] In this embodiment of the invention, the diameter of the target drug droplets during the second time period can be expressed by the following formula. Changes over time:

[0125]

[0126] in, Indicates the elapsed time; This represents the wet-bulb and dry-bulb temperature difference. The value of is determined based on prior knowledge, and the dry-bulb and wet-bulb temperature difference The value is usually 10.

[0127] Step 104: Based on the simulated values ​​of the target parameters of the target liquid droplets in the first time period and the simulated values ​​of the target parameters of the target liquid droplets in the second time period, if the execution conditions for the target aerial spraying operation are met, execute the target aerial spraying operation.

[0128] As an optional embodiment, based on the simulated values ​​of the target parameters of the target liquid droplets in the first time period and the simulated values ​​of the target parameters of the target liquid droplets in the second time period, it is determined whether the execution conditions of the target aerial spraying operation task are met. This includes: based on the avoidance area of ​​the target aerial spraying operation task, the simulated values ​​of the target parameters of the target liquid droplets in the first time period and the simulated values ​​of the target parameters of the target liquid droplets in the second time period, it is determined whether the target liquid droplets will enter the avoidance area of ​​the target aerial spraying operation task after the target aerial spraying operation task is executed.

[0129] If it is determined that the target pesticide droplets will not enter the avoidance zone of the target aerial pesticide application operation after the target aerial pesticide application operation is executed, then if it is determined that the execution conditions of the target aerial pesticide application operation are met, then if it is determined that the target pesticide droplets will enter the avoidance zone of the target aerial pesticide application operation after the target aerial pesticide application operation is executed, then at least one of the flight parameters, spraying parameters, and target time period of the target aerial pesticide application operation is updated, and the process returns to the step of obtaining the actual values ​​of environmental parameters in the target area during the preparation period, until the execution conditions of the target aerial pesticide application operation are met.

[0130] It should be noted that the avoidance area for the target aerial spraying operation in this embodiment of the invention is an area where the target pesticide solution cannot be sprayed. If the target pesticide droplets enter the avoidance area of ​​the target aerial spraying operation, it will cause adverse effects such as water and soil pollution, non-target crops, and threats to human and animal health in the avoidance area.

[0131] Understandably, the avoidance zone for target aerial spraying operations can also be determined based on input from technical personnel.

[0132] This invention, in its embodiments, obtains the actual values ​​of environmental parameters within the target area during the preparation period when a target aerial pesticide application operation is determined to be triggered. Based on the flight and spraying parameters of the target aerial pesticide application operation and the actual values ​​of environmental parameters within the target area during the preparation period, simulated values ​​of target parameters for the target pesticide droplets are obtained within a first time period. Based on the simulated values ​​of target parameters for the target pesticide droplets at the end of the first time period, the actual values ​​of environmental parameters within the target area during the preparation period, and the flight and spraying parameters of the target aerial pesticide application operation, target parameters for the target pesticide droplets are obtained within a second time period. Based on the simulated values ​​of the target parameters of the target pesticide droplets in the first time period and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period, the execution conditions for the target aerial pesticide application task are determined. This allows for a more accurate and efficient estimation of the drift trajectory of the pesticide droplets in space. Consequently, based on the drift trajectory of the pesticide droplets in space, more accurate and efficient aerial pesticide application operations can be carried out. This also better avoids adverse effects such as water and soil pollution, non-target crops, and threats to human and animal health caused by pesticide droplet drift during aerial pesticide application operations.

[0133] This invention provides an aerial pesticide application method based on predicting the drift trajectory of pesticide droplets. The method decomposes the droplet drift process into a short, complex near-field motion phase within seconds of release and a longer far-field drift phase. The near-field motion phase is dominated by the complex wind field of the rotor and is predicted using numerical modeling and deep learning models. The far-field drift phase is influenced by atmospheric environmental factors and is predicted using a theoretical model established with physical formulas. The combination of these two methods solves the problem of predicting the entire droplet deposition and drift process.

[0134] The aerial spraying method based on the prediction of the drift trajectory of liquid pesticide droplets provided by this invention uses a deep learning model to learn the motion pattern of droplets in a numerical simulation database built by XFlow software in a short period of time after release. This allows for more accurate and efficient calculation of the motion trajectory and distribution prediction results of the target liquid pesticide droplets in a short period of time.

[0135] The aerial pesticide application method based on the prediction of pesticide droplet drift trajectory provided by this invention reads the simulated values ​​of particle size, position and velocity information of each target pesticide droplet, incorporates the influence of factors such as gravity, ambient wind speed and air humidity, and performs rapid theoretical calculations on the drift motion of pesticide droplets at different times according to physical constraint formulas such as gravity, Reynolds number and aerodynamic drag, as well as random wind speed constrained by the function variation curve of different wind speeds at different altitudes.

[0136] The aerial pesticide application method based on pesticide droplet drift trajectory prediction provided by this invention can calculate the drift trajectories of 1000 target pesticide droplets within 10 minutes (including the first and second time periods) in just 20 seconds. In contrast, traditional CFD software, even with wind field calculations already completed, requires at least 2 hours to simulate the drift trajectories of 1000 target pesticide droplets within 3 seconds. Therefore, the aerial pesticide application method based on pesticide droplet drift trajectory prediction provided by this invention can improve the estimation efficiency by several orders of magnitude.

[0137] Meanwhile, the aerial spraying method based on the prediction of pesticide droplet drift trajectory provided by this invention has low experimental cost, small code size, and requires little computing resources. It is easy to embed into terminal devices such as aircraft remote controllers, filling the gap in the current field operation process of lacking rapid prediction of droplet drift trajectory.

[0138] Figure 2 This is a schematic diagram of the aerial spraying device based on the prediction of pesticide droplet drift trajectory provided by the present invention. The following is in conjunction with... Figure 2 The aerial pesticide application device based on the prediction of pesticide droplet drift trajectory provided by this invention is described below. The aerial pesticide application device based on the prediction of pesticide droplet drift trajectory described below can be referred to in correspondence with the aerial pesticide application method based on the prediction of pesticide droplet drift trajectory provided by this invention described above. Figure 2 As shown, the device includes: a data acquisition module 201, a first estimation module 202, a second estimation module 203, and a task execution module 204.

[0139] The data acquisition module 201 is used to acquire the actual values ​​of environmental parameters in the target area during the preparation period when the target aerial spraying operation task is determined to be triggered. The target aerial spraying operation task is an aerial spraying operation task that sprays the target pesticide solution on the crops in the target area during the target period. The preparation period is the first preset time period before the target period. The environmental parameters include wind speed.

[0140] The first estimation module 202 is used to obtain the simulated values ​​of the target parameters of the target liquid pesticide droplets in the first time period based on the actual values ​​of the flight parameters and spraying parameters of the target aerial spraying operation task and the environmental parameters in the target area during the preparation period. The spraying parameters include the spraying angle, the initial particle size of the liquid pesticide droplets and the initial velocity of the liquid pesticide droplets. The flight parameters include the flight altitude and / or flight speed. The start time of the first time period is the time when the target liquid pesticide droplets are sprayed out, and the end time of the first time period is the time after the start time of the first time period, which is the second preset time. The target parameters include particle size information, position information and velocity information.

[0141] The second estimation module 203 is used to obtain the simulated value of the target parameter of the target liquid droplet in the second time period based on the simulated value of the target parameter of the target liquid droplet at the end time of the first time period, the actual value of the environmental parameter in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the time after the start time of the second time period, which is the third preset time period.

[0142] The task execution module 204 is used to execute the target aerial pesticide application task when the execution conditions for the target aerial pesticide application task are met, based on the simulated values ​​of the target parameters of the target pesticide droplets in the first time period and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period.

[0143] Specifically, the data acquisition module 201, the first estimation module 202, the second estimation module 203, and the task execution module 204 are electrically connected.

[0144] The aerial pesticide application device based on pesticide droplet drift trajectory prediction in this embodiment of the invention obtains the actual values ​​of environmental parameters within the target area during the preparation period when a target aerial pesticide application task is determined to be triggered. Based on the flight parameters and spraying parameters of the target aerial pesticide application task and the actual values ​​of environmental parameters within the target area during the preparation period, it obtains the simulated values ​​of target parameters of the target pesticide droplets in the first time period. Based on the simulated values ​​of target parameters of the target pesticide droplets at the end of the first time period, the actual values ​​of environmental parameters within the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial pesticide application task, it obtains the simulated values ​​of target parameters in the second time period. The simulated values ​​of the target parameters of the target pesticide droplets, and then, based on the simulated values ​​of the target parameters of the target pesticide droplets in the first time period and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period, determine the execution conditions that meet the target aerial pesticide application task, and execute the target aerial pesticide application task. This can more accurately and efficiently estimate the drift trajectory of the pesticide droplets in space, and thus, based on the drift trajectory of the pesticide droplets in space, conduct more accurate and efficient aerial pesticide application operations. It can also better avoid adverse effects such as water and soil pollution, non-target crops, and threats to human and animal health caused by pesticide droplet drift during aerial pesticide application operations.

[0145] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communications bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other through the communications bus 340. The processor 310 can call logic instructions in the memory 330 to execute an aerial spraying operation method based on the prediction of pesticide droplet drift trajectories. This method includes: upon determining that a target aerial spraying operation task has been triggered, acquiring actual values ​​of environmental parameters within a target area during a preparatory period. The target aerial spraying operation task is an aerial spraying operation task involving the spraying of a target pesticide solution onto crops within a target area during a target time period. The preparatory period is a time period of a first preset duration prior to the target time period. Environmental parameters include wind speed. Based on the flight parameters and spraying parameters of the target aerial spraying operation task and the actual values ​​of environmental parameters within the target area during the preparatory period, acquiring simulated values ​​of target parameters for the pesticide droplets within a first time period. The spraying parameters include spraying angle, initial droplet size, and initial droplet velocity. Flight parameters include flight altitude and / or flight speed. The start time of the first time period... The first time period ends at the moment the target pesticide droplets are sprayed, and the end time of the first time period is the second preset time after the start time of the first time period. The target parameters include particle size information, position information, and velocity information. Based on the simulated values ​​of the target parameters of the target pesticide droplets at the end time of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial pesticide application task, the simulated values ​​of the target parameters of the target pesticide droplets in the second time period are obtained. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the third preset time after the start time of the second time period. Based on the simulated values ​​of the target parameters of the target pesticide droplets in the first time period and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period, if the execution conditions of the target aerial pesticide application task are met, the target aerial pesticide application task is executed.

[0146] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a 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 various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0147] Based on the above embodiments, an aerial pesticide application system based on the prediction of pesticide droplet drift trajectories includes: electronic equipment, an aircraft, and a spraying device as described above; the electronic equipment is electrically connected to the aircraft and the spraying device respectively; the spraying device is connected to the aircraft.

[0148] The aircraft is used to move the spraying device in response to the control of the electronic equipment;

[0149] The spraying device is used to spray liquid droplets in response to the control of the electronic device.

[0150] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the aerial spraying operation method based on the prediction of pesticide droplet drift trajectory provided by the above methods. The method includes: when a target aerial spraying operation task is determined to be triggered, obtaining the actual values ​​of environmental parameters in the target area during a preparatory period, wherein the target aerial spraying operation task is an aerial spraying operation task of spraying a target pesticide solution on crops in the target area during a target period, and the preparatory period is a period of a first preset duration before the target period, and the environmental parameters include wind speed; and based on the flight parameters and spraying parameters of the target aerial spraying operation task and the actual values ​​of the environmental parameters in the target area during the preparatory period, obtaining the simulated values ​​of the target parameters of the target pesticide droplets in the first period, wherein the spraying parameters include the spraying angle, the initial particle size of the pesticide droplets, and the pesticide droplet size. The initial velocity, flight parameters including flight altitude and / or flight speed, the start time of the first time period is the moment when the target pesticide droplets are sprayed, the end time of the first time period is the moment after the start time of the first time period, and the target parameters include particle size information, position information and velocity information; based on the simulated value of the target pesticide droplets' target parameters at the end time of the first time period, the actual value of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial pesticide application task, the simulated value of the target pesticide droplets' target parameters in the second time period is obtained, the start time of the second time period is the end time of the first time period, and the end time of the second time period is the moment after the start time of the second time period, and the third preset time period; based on the simulated value of the target pesticide droplets' target parameters in the first time period and the simulated value of the target pesticide droplets' target parameters in the second time period, if the execution conditions of the target aerial pesticide application task are met, the target aerial pesticide application task is executed.

[0151] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the aerial spraying operation method based on the prediction of pesticide droplet drift trajectory provided by the above-described methods. The method includes: upon determining that a target aerial spraying operation task has been triggered, acquiring actual values ​​of environmental parameters within a target area during a preparatory period; the target aerial spraying operation task is an aerial spraying operation task involving spraying a target pesticide solution onto crops within a target area during a target period; the preparatory period is a period of a first preset duration prior to the target period; and the environmental parameters include wind speed; based on the flight parameters and spraying parameters of the target aerial spraying operation task and the actual values ​​of the environmental parameters within the target area during the preparatory period, acquiring simulated values ​​of target parameters of the target pesticide droplets within a first period; the spraying parameters include spraying angle, initial droplet size, and initial droplet velocity; and the flight parameters include flight... The altitude and / or flight speed are determined. The start time of the first time period is the moment when the target pesticide droplets are sprayed, and the end time of the first time period is the second preset time after the start time of the first time period. The target parameters include particle size information, position information, and velocity information. Based on the simulated values ​​of the target parameters of the target pesticide droplets at the end time of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial pesticide application task, the simulated values ​​of the target parameters of the target pesticide droplets in the second time period are obtained. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the third preset time after the start time of the second time period. Based on the simulated values ​​of the target parameters of the target pesticide droplets in the first time period and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period, if the execution conditions of the target aerial pesticide application task are met, the target aerial pesticide application task is executed.

[0152] The device embodiments described above are merely illustrative. 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 modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0153] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for aerial pesticide application based on the prediction of pesticide droplet drift trajectory, characterized in that, include: When it is determined that a target aerial spraying operation task has been triggered, the actual values ​​of environmental parameters in the target area during the preparation period are obtained. The target aerial spraying operation task is an aerial spraying operation task that sprays the target pesticide solution onto the crops in the target area during the target period. The preparation period is a period of a first preset duration before the target period. The environmental parameters include wind speed. Based on the flight parameters and spraying parameters of the target aerial spraying operation and the actual values ​​of the environmental parameters in the target area during the preparation period, simulated values ​​of the target parameters of the target liquid droplets are obtained during the first time period. The spraying parameters include the spraying angle, the initial particle size of the liquid droplets, and the initial velocity of the liquid droplets. The flight parameters include the flight altitude and / or flight speed. The start time of the first time period is the time when the target liquid droplets are sprayed out, and the end time of the first time period is the time after the start time of the first time period, which is the second preset time. The target parameters include particle size information, position information, and velocity information. Based on the simulated value of the target parameters of the target liquid droplets at the end time of the first time period, the actual value of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation, the simulated value of the target parameters of the target liquid droplets in the second time period is obtained. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the third preset time after the start time of the second time period. Based on the simulated values ​​of the target parameters of the target liquid droplets in the first time period and the simulated values ​​of the target parameters of the target liquid droplets in the second time period, if the execution conditions of the target aerial spraying operation are met, the target aerial spraying operation is executed.

2. The aerial spraying method based on the prediction of pesticide droplet drift trajectory according to claim 1, characterized in that, The method of obtaining simulated values ​​of target parameters for the target pesticide droplets within the first time period based on the flight parameters and spraying parameters of the target aerial pesticide application operation and the actual values ​​of environmental parameters within the target area during the preparation period includes: The spraying parameters of the target aerial spraying operation and the actual values ​​of the environmental parameters in the target area during the preparation period are input into the droplet drift trajectory prediction model to obtain the simulated values ​​of the target parameters of the target liquid droplets in the first time period output by the droplet drift trajectory prediction model. The droplet drift trajectory prediction model is obtained by training based on sample data and corresponding sample labels. The sample data includes flight parameters and spraying parameters of the sample aerial spraying operation task, as well as the actual values ​​of environmental parameters in the sample area during the sample preparation period. The sample labels include simulated values ​​of target parameters of the sample liquid droplets during the third time period. The start time of the third time period is the time when the sample liquid droplets are sprayed, and the end time of the third time period is the time after the start time of the third time period for the second preset duration. The sample aerial spraying operation task is an aerial spraying operation task that sprays sample liquid in the sample area during the sample time period. The sample preparation period is the time period before the sample time period for the first preset duration.

3. The aerial spraying method based on the prediction of pesticide droplet drift trajectory according to claim 1, characterized in that, The method of obtaining the simulated values ​​of the target parameters of the target pesticide droplets in the second time period based on the simulated values ​​of the target parameters of the target pesticide droplets at the end time of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation, includes: Based on the flight parameters of the target aerial spraying operation, the wind speed of the wind field generated by the aircraft during the execution of the target aerial spraying operation is calculated and used as the target wind speed. Based on the simulated values ​​of the target parameters of the target liquid droplets at the end time of the first time period, the actual values ​​of the environmental parameters in the target area during the preparation time period, and the spraying parameters of the target aerial spraying operation, the Reynolds number, aerodynamic drag, volume, mass, and gravity of the target liquid droplets are calculated. Based on the Reynolds number, aerodynamic drag, volume, mass, and gravity of the target drug droplet, and the first [time period]... j The simulated values ​​of the target parameters of the target drug droplets at the nth time point are used to calculate the nth time period within the second time period. j Simulated values ​​of the target parameters of the target drug droplets at +1 time points. j Represents a positive integer with an initial value of 1. The first time point within the second time period is the start time of the second time period, and the second time point within the second time period is the start time of the second time period. j The time node and the second time period j +1 time interval between the fourth preset duration j It represents a positive integer with an initial value of 1.

4. The aerial spraying method based on the prediction of pesticide droplet drift trajectory according to claim 2, characterized in that, The sample labels corresponding to the sample data are obtained based on the following steps: A three-dimensional model of the sample aircraft is obtained by performing a three-dimensional modeling. Based on the three-dimensional model of the sample aircraft and the flight parameters of the sample aerial spraying operation, the wind field of the sample aircraft during flight is numerically simulated to obtain the wind field model of the sample aircraft during flight. Based on the spraying parameters of the sample aerial spraying operation, the motion trajectory of the sample pesticide droplets is simulated in the wind field model during the flight of the sample aircraft, and the simulated values ​​of the target parameters of the sample pesticide droplets in the third time period corresponding to the sample data are obtained.

5. The aerial spraying method based on the prediction of pesticide droplet drift trajectory according to claim 3, characterized in that, Based on the flight parameters of the target aerial spraying operation, the formula for calculating the target wind speed is as follows: in, Indicates the target wind speed; This represents a coefficient determined based on atmospheric turbulence. The flight altitude of the target aerial pesticide application operation is indicated. If the flight parameters of the target aerial pesticide application operation do not include the flight altitude, the flight altitude of the target aerial pesticide application operation is a preset flight altitude.

6. The aerial spraying method based on the prediction of liquid droplet drift trajectory according to any one of claims 1 to 5, characterized in that, in The simulated values ​​of the target parameters of the target pesticide droplets during the first time period and the simulated values ​​of the target parameters of the target pesticide droplets during the second time period are used to determine whether the execution conditions of the target aerial pesticide application task are met, including: Based on the avoidance zone of the target aerial pesticide application task, the simulated values ​​of the target parameters of the target pesticide droplets in the first time period, and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period, it is determined whether the target pesticide droplets will enter the avoidance zone of the target aerial pesticide application task after the target aerial pesticide application task is executed. If, after determining that the target pesticide droplets will not enter the avoidance zone of the target aerial pesticide application operation, the execution conditions of the target aerial pesticide application operation are met, and if, after determining that the target pesticide droplets will enter the avoidance zone of the target aerial pesticide application operation, the flight parameters and spraying parameters of the target aerial pesticide application operation and at least one of the target time period are updated, the process returns to the step of obtaining the actual values ​​of environmental parameters within the target area of ​​the preparation time period, until the execution conditions of the target aerial pesticide application operation are met.

7. An aerial pesticide application device based on the prediction of pesticide droplet drift trajectory, characterized in that, include: The data acquisition module is used to acquire the actual values ​​of environmental parameters in the target area during the preparation period when the target aerial spraying operation task is determined to be triggered. The target aerial spraying operation task is an aerial spraying operation task that sprays the target pesticide solution onto the crops in the target area during the target period. The preparation period is a period of a first preset duration before the target period. The environmental parameters include wind speed. The first estimation module is used to obtain simulated values ​​of target parameters of the target liquid pesticide droplets within a first time period based on the flight parameters and spraying parameters of the target aerial spraying operation and the actual values ​​of environmental parameters in the target area during the preparation period. The spraying parameters include spraying angle, initial particle size of liquid pesticide droplets, and initial velocity of liquid pesticide droplets. The flight parameters include flight altitude and / or flight speed. The start time of the first time period is the time when the target liquid pesticide droplets are sprayed out, and the end time of the first time period is the time after the start time of the first time period, which is a second preset time. The target parameters include particle size information, position information, and velocity information. The second estimation module is used to obtain the simulated value of the target parameter of the target liquid droplet in the second time period based on the simulated value of the target parameter of the target liquid droplet at the end time of the first time period, the actual value of the environmental parameter in the target area during the preparation period, and the flight parameters and spraying parameters of the target aerial spraying operation task. The start time of the second time period is the end time of the first time period, and the end time of the second time period is the time after the start time of the second time period, which is the third preset time period. The task execution module is used to execute the target aerial pesticide application task when the execution conditions of the target aerial pesticide application task are met, based on the simulated values ​​of the target parameters of the target pesticide droplets in the first time period and the simulated values ​​of the target parameters of the target pesticide droplets in the second time period.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the aerial spraying operation method based on the prediction of the drift trajectory of liquid droplets as described in any one of claims 1 to 6.

9. An aerial pesticide application system based on the prediction of pesticide droplet drift trajectory, characterized in that, include: The electronic device, the aircraft, and the spraying device as described in claim 8; the electronic device is electrically connected to both the aircraft and the spraying device; the spraying device is connected to the aircraft; The aircraft is used to move the spraying device in response to the control of the electronic equipment; The spraying device is used to spray liquid droplets in response to the control of the electronic device.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the aerial spraying operation method based on the prediction of the drift trajectory of liquid droplets as described in any one of claims 1 to 6.

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