A smart drug dispensing system and control method for unmanned aerial vehicle (UAV) operations

Abstract

This invention discloses an intelligent pesticide dispensing system and control method for UAV operations, comprising: acquiring pesticide dispensing task instructions and concentrate ratio parameter data; performing zoned load collaborative calibration analysis through several weighbridge sensors on the mixing ton to achieve adaptive leveling of the weighing benchmark; performing independent measurement through weighbridges in each concentrate tank and conducting dual verification deviation analysis in collaboration with the mixing ton; generating water pump and solenoid valve control instructions based on the verification results to achieve automated control of concentrate addition, mixing, and quantitative pesticide application; the system includes a pesticide dispensing control unit, a mixing ton assembly, a concentrate metering assembly, a liquid conveying assembly, and a liquid storage assembly; this invention, through zoned load collaborative acquisition and dual verification architecture, can eliminate weighing errors caused by uneven mountainous operating environments, solve the core problem of insufficient accuracy in multi-agent mixing, and provide core data support for differentiated and precise pesticide dispensing for UAV-based terraced plant protection.

Description

Technical Field

[0001] This invention relates to the field of drone-based plant protection technology, and in particular to an intelligent pesticide dispensing system and control method for drone operations. Background Technology

[0002] Unmanned aerial vehicle (UAV) plant protection operations have seen rapid development in agricultural pest and disease control in recent years, especially in complex terrain conditions such as mountainous terraced fields. UAV operations, with their high efficiency and flexibility, have become an important technological means to replace manual spraying. One of the core aspects of UAV plant protection operations is the precise preparation of pesticides, where the accuracy of pesticide weighing directly affects the control effect and the quality of the operation. In actual operations, the pesticide preparation system needs to mix multiple stock solutions according to a preset ratio, and then quantitatively add the mixed solution to the UAV's tank. Therefore, the reliability of the weighing and metering system is crucial to ensuring the accuracy of pesticide preparation.

[0003] In mountainous terraced field operations, the dispensing system typically needs to be deployed and operated in non-standardized temporary sites. Due to the slope variations in mountainous terrain and the fact that the ground is mostly loose soil or gravel, local settlement can easily occur after the equipment is placed due to unstable foundations. This can cause load-bearing equipment such as mixing tanks and concentrate tanks to tilt. The tilting of the equipment will cause the force direction of the weighing sensor to shift, resulting in a deviation between the weighing reading and the actual weight. In severe cases, it may even lead to completely distorted weighing data.

[0004] However, in existing technologies, the weighing and metering of pesticide dispensing systems generally adopts a single reference plane design, assuming that the equipment is placed horizontally and the ground will not settle. Under this premise, the weight of the concentrate and the quantitative dispensing of the mixture are performed. This design does not consider the special characteristics of mountainous terraced fields. When the equipment tilts due to uneven ground or settlement, the measurement results of a single weighing sensor will not reflect the true weight of the material, leading to a series of problems such as imbalances in the concentrate ratio and deviations in the total amount of mixture. Due to the lack of a weighing error calibration mechanism for uneven sites, existing pesticide dispensing systems cannot meet the stringent requirements for the accuracy of multi-agent mixing in differentiated pest and disease control in mountainous terraced fields, becoming a technical bottleneck restricting the improvement of the quality of drone-based plant protection operations.

[0005] Therefore, it is necessary to provide an intelligent drug dispensing system and control method for unmanned aerial vehicle (UAV) operations to solve the above-mentioned technical problems. Summary of the Invention

[0006] This invention overcomes the shortcomings of the prior art and provides an intelligent drug dispensing system and control method for unmanned aerial vehicle (UAV) operations.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: an intelligent drug dispensing system for unmanned aerial vehicle (UAV) operations, comprising: a drug dispensing control unit, a stirring tank assembly, a raw liquid metering assembly, a liquid conveying assembly, and a liquid storage assembly, wherein the drug dispensing control unit is electrically connected to the stirring tank assembly, the raw liquid metering assembly, the liquid conveying assembly, and the liquid storage assembly, respectively.

[0008] In a preferred embodiment of the present invention, the mixing ton assembly includes a mixing ton, several weighbridge sensors, a mixing motor, and a liquid level sensor. The weighbridge sensors are respectively disposed below three support points at the bottom of the mixing ton, the mixing motor is disposed at the top of the mixing ton, and the liquid level sensor is embedded in the side wall of the mixing ton for monitoring the liquid level of the mixture. The raw liquid metering assembly includes several raw liquid tanks and several weighbridge sensors. Each of the raw liquid tanks has a weighbridge sensor at its bottom, and the raw liquid tanks are respectively connected to a liquid delivery assembly via pipelines. The liquid delivery assembly includes several water pumps and several solenoid valves. The water pumps are respectively connected to the raw liquid tanks and the storage tank, and the output end of each water pump is connected to the liquid inlet at the top of the mixing ton via a pipeline connected in series with the solenoid valves. The storage assembly includes a water storage tank and a liquid level monitor. The water storage tank is connected to one of the water pumps via a pipeline.

[0009] In a preferred embodiment of the present invention, several of the weighbridge sensors are respectively disposed at three support points distributed in a triangle at the bottom of the mixing tank, and the support points are arranged in an equilateral triangle to ensure the comprehensiveness and symmetry of load collection.

[0010] This invention also proposes an intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations, comprising the following steps:

[0011] S1. Obtain drug dispensing task instruction data, original solution ratio parameter data, weighbridge weighing sensor data, and weighbridge weighing sensor data;

[0012] S2. Based on the weighbridge weighing sensor data, perform zoned load collaborative calibration analysis on the mixing ton, and make adaptive leveling judgment on the weighing benchmark of the mixing ton according to the zoned load collaborative calibration analysis results. Based on the adaptive leveling judgment results, obtain the real-time corrected weighing benchmark data of the mixing ton.

[0013] S3. Based on the weighing sensor data of the weighing scale, each raw liquid tank is independently weighed. Based on the real-time correction of the weighing reference data of the mixing tank, the mixed liquid is weighed collaboratively. Based on the independent weighing data and the collaborative weighing data, a double verification deviation analysis is performed. Based on the results of the double verification deviation analysis, it is determined whether the drug dispensing is accurate.

[0014] S4. Generate dosing execution control instructions based on the results of double verification deviation analysis, and control each water pump and solenoid valve to perform raw solution addition, stirring and quantitative dosing operations according to the dosing execution control instructions.

[0015] In a preferred embodiment of the present invention, the specific steps of S1 are as follows:

[0016] S11. Obtain the drug dispensing task instruction data through the drug dispensing control unit. The drug dispensing task instruction data includes the target ratio of each raw liquid, the total demand of the mixed liquid, and the water pump start-up sequence data.

[0017] S12. Obtain the stock solution ratio parameter data through the drug dispensing control unit. The stock solution ratio parameter data includes the density data of each stock solution, the weight percentage data of each stock solution, and the preset accuracy threshold range data.

[0018] S13. Obtain the original weighing data of the zoned load through several weighbridge sensors of the mixing ton, and obtain the independent weighing data of each raw liquid tank through the weighbridge sensors of each raw liquid tank.

[0019] S14. After analyzing and processing the acquired data, store it in the control unit's memory for use in the drug dispensing control process.

[0020] In a preferred embodiment of the present invention, step S2 in section 3 is as follows:

[0021] S21. Calculate the real-time load value at each point based on the original weighing data of the zoned load collected by several weighbridge sensors in the mixing ton.

[0022] S22. Calculate the overall load deviation of the mixing ton based on the real-time net load values ​​at each point;

[0023] S23. Adaptive leveling judgment of weighing benchmark based on overall load deviation value.

[0024] In a preferred embodiment of the present invention, step 4, S3, includes the following specific steps:

[0025] S31. Perform independent weighing of each raw liquid based on the independent weighing data collected by the weighbridge sensors of each raw liquid tank;

[0026] S32. Calculate the synergistic weighing value of the mixture based on the corrected weighing reference data of the mixing ton;

[0027] S33. Obtain the independent measurement values ​​of each original solution and the synergistic weighing measurement value of the mixed solution, and calculate the double verification deviation value;

[0028] S34. Determine whether the double verification deviation value is within the preset accuracy threshold range. If the double verification deviation value is less than the preset accuracy threshold, the drug dispensing measurement is determined to be accurate and the operation proceeds to the next stage. If the double verification deviation value is greater than or equal to the preset accuracy threshold, an abnormal alarm is triggered and subsequent measurement parameters are automatically corrected before proceeding to the next stage.

[0029] In a preferred embodiment of the present invention, step S4 in step 5 is as follows:

[0030] S41. Generate a water pump control command sequence based on the drug dispensing task instruction data and the results of the double verification deviation analysis. The water pump control command sequence includes: the start-up duration data, start-up sequence data, and flow rate adjustment data of each water pump.

[0031] S42. Generate a solenoid valve control instruction sequence based on the drug dispensing task instruction data, wherein the solenoid valve control instruction sequence includes the opening and closing timing data and the switching status data of each solenoid valve.

[0032] S43. Generate stirring motor control instructions based on the drug dispensing task instruction data and stirring motor control parameters, wherein the stirring motor control instructions include stirring speed data, stirring duration data and stirring interval duration data;

[0033] S44. The control unit sends corresponding control commands to each water pump, solenoid valve and stirring motor to complete the full-process automated control of raw material addition, drug mixing and quantitative drug addition.

[0034] In a preferred embodiment of the present invention, the specific parameters of the water pump control command sequence are as follows: the first water pump corresponds to the control of adding raw solution A, the second water pump corresponds to the control of adding raw solution B, the third water pump corresponds to the control of adding raw solution C, and the fourth water pump corresponds to the control of adding clean water. The start-up time of each water pump is calculated and determined according to the target ratio of the corresponding raw solution and the preset flow rate value.

[0035] In a preferred embodiment of the present invention, the specific parameters of the solenoid valve control command sequence are as follows: the first to fifth solenoid valves are respectively set at each pipeline node, and the corresponding opening and closing actions are executed according to the water pump opening sequence and control logic to realize the on-off control of the raw liquid pipeline, the clean water pipeline and the mixed liquid conveying pipeline.

[0036] This invention addresses the shortcomings of the prior art and has the following beneficial effects:

[0037] (1) This invention provides an intelligent drug dispensing system and control method for unmanned aerial vehicle (UAV) operations. The weighing benchmark is adaptively leveled and judged through the mixing ton assembly, which effectively eliminates the weighing error caused by uneven terrain. The mixing ton assembly is equipped with multiple weighbridge sensors to collect load data in different zones. Several weighbridge sensors collect and analyze the load data of the bottom support points of the mixing ton synchronously. The weighing benchmark of the mixing ton can be judged in real time and adaptive leveling can be completed. The existing drug dispensing system adopts a single benchmark plane design concept and does not consider the weighing deviation caused by the tilt and settlement of mountainous terrain. This method does not require manual leveling and calibration, and eliminates the inherent error of the drug dispensing weighing system caused by the uneven mountainous operating environment from the root.

[0038] (2) This invention provides an intelligent drug dispensing system and control method for UAV operations. By cooperating with the raw liquid metering component and the mixing ton container component, a dual verification deviation analysis is completed to ensure the metering accuracy of multi-agent mixing. The raw liquid metering component independently measures each raw liquid container based on the weighing sensor of the ground scale. At the same time, it performs collaborative weighing measurement of the mixed liquid by combining the weighing benchmark corrected by the mixing ton container component. The two metering methods are independent of each other and mutually verify each other. They can perform dual verification deviation analysis and determine whether the drug dispensing measurement is accurate. The existing technology lacks a dual verification architecture for drug dispensing measurement, which is prone to the situation of raw liquid ratio imbalance and total volume measurement deviation of mixed liquid. This collaborative verification method completely solves the core problem of insufficient accuracy of multi-agent mixing for the prevention and control of differentiated pests and diseases in fragmented terraced mountainous areas.

[0039] (3) This invention provides an intelligent pesticide dispensing system and control method for UAV operations. The pesticide dispensing control unit links various components to achieve automated control of the entire pesticide dispensing process, thereby improving the intelligence level of UAV plant protection pesticide dispensing operations. The pesticide dispensing control unit is electrically connected to the mixing tank component, the stock solution metering component, the liquid conveying component, and the liquid storage component, respectively. Based on the results of the double verification deviation analysis, it generates accurate control commands for the water pump, solenoid valve, and mixing motor, which can coordinate the components to complete the stock solution addition, pesticide mixing, and quantitative pesticide addition operations in an orderly manner. Existing pesticide dispensing operations mostly rely on manual operation, which is not only inefficient but also prone to affecting the accuracy of pesticide dispensing due to human error. This automated control mode provides core data support for differentiated and precise pesticide dispensing in UAV terraced fields, effectively improving the overall quality of UAV plant protection operations. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present 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 only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic diagram of the overall process of an intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to the present invention;

[0042] Figure 2 This is a schematic diagram of the S3 step double verification deviation analysis process of the intelligent drug dispensing control method for unmanned aerial vehicle operations according to the present invention;

[0043] Figure 3 This is a schematic diagram of the overall framework of an intelligent drug dispensing system for unmanned aerial vehicle (UAV) operations according to the present invention;

[0044] In the diagram: 1. Mixing tank; 2. Weighbridge sensor; 3. Mixing motor; 4. Liquid level sensor; 5. Raw material tank; 6. Weighbridge sensor; 7. Water pump; 8. Solenoid valve; 9. Water storage tank; 10. Liquid level monitor. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein. Therefore, the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0047] like Figure 1 As shown, the present invention provides an intelligent drug dispensing system and control method for unmanned aerial vehicle (UAV) operations, comprising the following steps:

[0048] S1. Obtain drug dispensing task instruction data, original solution ratio parameter data, weighbridge weighing sensor data, and weighbridge weighing sensor data;

[0049] S2. Based on the weighbridge weighing sensor data, perform zoned load collaborative calibration analysis on the mixing ton, and make adaptive leveling judgment on the weighing benchmark of the mixing ton according to the zoned load collaborative calibration analysis results. Based on the adaptive leveling judgment results, obtain the real-time corrected weighing benchmark data of the mixing ton.

[0050] S3. Based on the weighing sensor data of the weighing scale, each raw liquid tank is independently weighed. Based on the real-time correction of the weighing reference data of the mixing tank, the mixed liquid is weighed collaboratively. Based on the independent weighing data and the collaborative weighing data, a double verification deviation analysis is performed. Based on the results of the double verification deviation analysis, it is determined whether the drug dispensing is accurate.

[0051] S4. Generate dosing execution control instructions based on the results of double verification deviation analysis, and control each water pump and solenoid valve to perform raw solution addition, stirring and quantitative dosing operations according to the dosing execution control instructions.

[0052] The following will describe each step in detail.

[0053] In this embodiment, the specific steps of S1 are as follows:

[0054] S11. Obtain the drug dispensing task instruction data through the drug dispensing control unit. The drug dispensing task instruction data includes the target ratio of each raw liquid, the total demand of the mixed liquid, and the water pump start-up sequence data.

[0055] S12. Obtain the stock solution ratio parameter data through the drug dispensing control unit. The stock solution ratio parameter data includes the density data of each stock solution, the weight percentage data of each stock solution, and the preset accuracy threshold range data.

[0056] S13. Obtain the original weighing data of the zoned load through several weighbridge sensors of the mixing ton, and obtain the independent weighing data of each raw liquid tank through the weighbridge sensors of each raw liquid tank.

[0057] S14. After analyzing and processing the acquired data, store it in the control unit's memory for use in the drug dispensing control process.

[0058] In one implementation of the present invention, the drug dispensing control unit obtains drug dispensing task instruction data, which includes the target ratio of each stock solution, the total demand of the mixture, and the pump start-up sequence data, in order to determine the specific quantity and order of each stock solution to be added, and to ensure that the drug dispensing process is carried out in an orderly manner according to the preset plan.

[0059] The drug dispensing control unit obtains the stock solution ratio parameter data, which includes the density data of each stock solution, the weight percentage data of each stock solution, and the preset accuracy threshold range data. This data is used to accurately calculate the weight ratio relationship of each stock solution, while the accuracy threshold range is used to verify the accuracy of drug dispensing in the future.

[0060] The original weighing data of the zoned load is obtained by several weighbridge sensors on the mixing ton, which is used to monitor the stress state of each support point of the mixing ton. The independent weighing data of each raw liquid tank is obtained by the weighbridge sensors on each raw liquid tank, which is used to independently measure the weight of each raw liquid.

[0061] In this embodiment, S2 includes the following specific steps:

[0062] S21. Calculate the real-time load value at each point based on the original weighing data of the zoned load collected by several weighbridge sensors on the mixing ton. The weighbridge sensors are respectively installed below three support points of the mixing ton. The formula for calculating the real-time load value at each point is as follows: ;

[0063] in, Numbering of the support points for the mixing tank. It can be any one of 1 to 3. For the first mixing tank The load values ​​collected in real time by the weighbridge sensors at each support point. For the first time when the mixing tank is unloaded The calibration reference value for the weighbridge sensor at each support point. For the first mixing tank Real-time net load values ​​for each support point;

[0064] It should be noted that in this formula, the difference between the real-time collected load value and the calibration reference value under no-load condition is calculated to eliminate sensor zero drift and inherent system error, obtain the true net load value of each point, and provide basic data for subsequent load deviation calculation.

[0065] S22. Calculate the overall load deviation of the mixing ton based on the real-time net load values ​​at each location. The formula for calculating the overall load deviation is as follows: ;

[0066] in, This represents the average real-time net load value at the three support points of the mixing tank. This refers to the overall load deviation value of the mixing tank;

[0067] It should be noted that the maximum deviation between the net load value at each point and the average value is calculated in this formula. This is used to quantify the uniformity of force distribution among the three support points of the mixing ton. When the mixing ton tilts or settles, the force distribution at each point will be differentiated, and the overall load deviation value will increase significantly.

[0068] S23. Based on the overall load deviation value, adaptive leveling judgment of the weighing benchmark is performed, wherein the calculation formula for adaptive leveling judgment of the weighing benchmark is: ;

[0069] in, The set load difference threshold, As a judgment result flag, when the overall load deviation value is greater than the load difference threshold, the judgment result flag is set to 1 to indicate that the weighing benchmark needs to be corrected; when the overall load deviation value is less than or equal to the load difference threshold, the judgment result flag is set to 0 to indicate that the weighing benchmark does not need to be corrected.

[0070] It should be noted that in this formula, the overall load deviation value is compared with the set load difference threshold to determine whether the mixing ton has tilted or settled. When the judgment result flag is 1, the system automatically starts the dynamic calibration program of the weighing benchmark, calculates the correction coefficient according to the distribution ratio of the real-time net load value of each point, and applies it to all subsequent weighing and measurement, thereby eliminating the weighing error caused by equipment tilting from the root.

[0071] For example, to illustrate the design advantages and basis of this formula: This formula sets a load difference threshold. As a criterion, when the mixing tank tilts on uneven terrain such as mountain terraces, the force distribution at the three support points will differ, resulting in an overall load deviation value. Will exceed the threshold The system automatically identifies and triggers the calibration procedure, avoiding the weighing distortion problem caused by equipment tilt in the traditional single sensor solution, and improving the reliability of drug dispensing and metering in complex operating environments.

[0072] like Figure 2 As shown, in this embodiment, S3 includes the following specific steps:

[0073] S31. Based on the independent weighing data collected by the weighbridge sensors of each raw liquid tank, each raw liquid is independently measured, wherein the first... The formula for calculating the independent volume of the seed stock solution is as follows: ;

[0074] in, Number the type of stock solution. From 1 to Any one of them, For the first The weight value of the raw material tank is collected in real time by the weighing sensor. For the first The calibration reference value of the weighbridge sensor under the empty state of the raw material tank. For the first Real-time measurement of the weight of the stock solution;

[0075] It should be noted that this formula uses independent sensors to measure each stock solution tank separately, avoiding mutual interference when multiple stock solutions are mixed and measured, improving the accuracy of single stock solution measurement, and providing accurate basic data for subsequent ratio calculations.

[0076] S32. Calculate the synergistic weighing value of the mixture based on the corrected weighing reference data of the mixing ton, wherein the formula for calculating the synergistic weighing value of the mixture is: ;

[0077] in, The real-time net load values ​​of the weighbridge sensors at the three support points of the mixing drum are as follows. This is the synergistic weighing value of the mixture;

[0078] It should be noted that in this formula, the total weight of the mixture in the mixing ton is obtained by summing the net load values ​​of the three corrected support points. The coordinated weighing method can effectively offset the single-point measurement error caused by equipment tilting and improve the accuracy of the total volume measurement of the mixture.

[0079] S33. Obtain the independent measurement values ​​of each original solution and the synergistic weighing measurement value of the mixture, and calculate the double verification deviation value. The formula for calculating the double verification deviation value is as follows: ;

[0080] in, This is the sum of the independent measured values ​​of each original solution. This is the synergistic weighing value of the mixture. This is a double-checked deviation value. Preset precision threshold;

[0081] It should be noted that in this formula, the sum of the independent measurement values ​​of each raw liquid is compared with the co-weighing measurement value of the mixing ton. The accuracy of the dosage is verified through a dual verification mechanism. The two measurement methods are independent of each other but also corroborate each other, effectively identifying and eliminating measurement anomalies.

[0082] S34. Determine whether the double verification deviation value is within the preset accuracy threshold range. If the double verification deviation value is less than the preset accuracy threshold, determine that the drug dispensing measurement is accurate and proceed to the next stage of operation.

[0083] If the deviation value of the double verification is greater than or equal to the preset accuracy threshold, an abnormal alarm will be triggered and subsequent measurement parameters will be automatically corrected before proceeding to the next stage of operation.

[0084] In this embodiment, the specific step of S34 is: obtaining the calculated double check deviation value. Double check deviation value Compared with the preset accuracy threshold To make a comparison, if If the dosage is accurate, the system proceeds to the next stage of operation; otherwise... If the dosage is incorrect, the system will detect a deviation in the dosage and trigger an alarm signal to prompt the operator to check the equipment status.

[0085] At the same time, the metering parameter correction program is automatically started, and the subsequent metering coefficients are adjusted according to the magnitude and direction of the deviation to ensure that the final dispensing accuracy meets the requirements.

[0086] It should be noted that the self-checking and self-correcting function of the dispensing and metering is realized through the dual verification mechanism, which effectively improves the fault tolerance and metering reliability of the dispensing system in complex environments.

[0087] In this embodiment, the specific steps of S4 are as follows:

[0088] S41. Generate a water pump control command sequence based on the drug dispensing task instruction data and the double verification deviation analysis results. The water pump control command sequence includes the start-up duration data, start-up sequence data and flow regulation data of each water pump.

[0089] S42. Generate a solenoid valve control instruction sequence based on the drug dispensing task instruction data, wherein the solenoid valve control instruction sequence includes the opening and closing timing data and the switching status data of each solenoid valve.

[0090] S43. Generate stirring motor control instructions based on the drug dispensing task instruction data and stirring motor control parameters, wherein the stirring motor control instructions include stirring speed data, stirring duration data and stirring interval duration data;

[0091] S44. The control unit sends corresponding control commands to each water pump, solenoid valve and stirring motor to complete the full-process automated control of raw material addition, drug mixing and quantitative drug addition.

[0092] In one implementation of the present invention, a water pump control command sequence is generated based on the drug dispensing task instruction data and the results of double verification deviation analysis. The water pump control command sequence includes the start-up duration data, start-up sequence data and flow rate adjustment data of each water pump, which are used to control the amount of each stock solution added.

[0093] Specifically, a sequence of solenoid valve control instructions is generated based on the drug dispensing task instruction data. The sequence of solenoid valve control instructions includes the opening and closing timing data and the switching status data of each solenoid valve, which is used to control the on-off timing of the pipeline and ensure the correctness of the raw liquid dispensing path.

[0094] Based on the drug dispensing task instruction data and the stirring motor control parameters, a stirring motor control instruction is generated. The stirring motor control instruction includes stirring speed data, stirring duration data, and stirring interval duration data to ensure that the mixture is stirred evenly.

[0095] The control unit sends corresponding control commands to each water pump, solenoid valve and stirring motor to complete the full-process automated control of the original solution addition, pesticide mixing and quantitative pesticide application, realizing the intelligent and precise pesticide application of drone plant protection operations.

[0096] In this embodiment, the specific parameters of the water pump control command sequence are as follows: the first water pump corresponds to the control of adding raw solution A, the second water pump corresponds to the control of adding raw solution B, the third water pump corresponds to the control of adding raw solution C, and the fourth water pump corresponds to the control of adding clean water. The start-up time of each water pump is calculated and determined according to the target ratio of the corresponding raw solution and the preset flow rate value.

[0097] In this embodiment, the specific parameters of the solenoid valve control command sequence are as follows: the first to fifth solenoid valves are respectively set at each pipeline node, and execute corresponding opening and closing actions according to the water pump start-up sequence and control logic to realize the on-off control of the raw liquid pipeline, the clean water pipeline and the mixed liquid delivery pipeline.

[0098] In this embodiment, the water tank level monitor is used to monitor the water level in the water tank in real time. When the water level is lower than the set minimum level, a water replenishment reminder signal is automatically triggered.

[0099] It should be noted that the setting parameters in this embodiment (such as the load difference threshold) Preset precision threshold (Parameters such as water pump flow rate need to be set by those skilled in the art based on relevant experiments);

[0100] The specific experimental method is as follows: Data from the dispensing task instruction, stock solution ratio parameters, weighbridge sensor data, and floor scale sensor data are acquired and used in the steps of this embodiment to calculate the dispensing measurement accuracy. Measurement error data under different site conditions is obtained, and this measurement error data is imported into fitting software for continuous fitting. The resulting output parameters that meet the dispensing accuracy requirements (e.g., load difference threshold) are then used. Preset precision threshold (etc.) values.

[0101] Based on the above implementation details, this embodiment has the following advantages over the prior art: This embodiment acquires drug dispensing task instruction data, original solution ratio parameter data, weighbridge weighing sensor data, and weighbridge weighing sensor data;

[0102] Based on the weighbridge sensor data, a zoned load collaborative calibration analysis is performed on the mixing ton. Based on the results of the zoned load collaborative calibration analysis, an adaptive leveling judgment is made on the weighing benchmark of the mixing ton. Based on the results of the adaptive leveling judgment on the weighing benchmark, the real-time corrected weighing benchmark data of the mixing ton is obtained.

[0103] Each raw material tank is independently measured based on the weighing sensor data of the weighbridge. The mixed liquid is then weighed collaboratively based on the real-time correction weighing reference data of the mixing tank. A double-verification deviation analysis is performed based on the independent measurement data and the collaborative weighing measurement data. The accuracy of the drug dispensing measurement is then determined based on the results of the double-verification deviation analysis.

[0104] The system generates dispensing execution control commands based on the results of dual-verification deviation analysis. According to the dispensing execution control commands, it controls each water pump and solenoid valve to perform the addition of raw liquid, stirring and quantitative dosing operations. Several weighbridge sensors are configured in the stirring tank to collect load data in different zones, realizing adaptive leveling and discrimination of the weighing benchmark. During the operation of the system, no manual leveling and calibration is required. The system automatically calculates the load difference threshold at each point and corrects the weighing benchmark in real time, eliminating the inherent error of the dispensing and weighing system caused by the uneven mountainous working environment from the root.

[0105] By employing a dual-verification architecture—independent metering with a dedicated weighbridge for the concentrate tank and collaborative weighing with the mixing ton—the system achieves dual verification of single concentrate metering and multi-concentrate mixing weighing. This completely solves the core problem of insufficient precision in mixing multiple pesticides for differentiated pest and disease control in fragmented terraced mountainous areas, providing core data support for differentiated and precise pesticide application in drone-based terraced field plant protection.

[0106] like Figure 3As shown, this embodiment also provides an intelligent drug dispensing system for unmanned aerial vehicle (UAV) operations, which is based on the above-mentioned intelligent drug dispensing control method for UAV operations. Specifically, it includes a drug dispensing control unit, a stirring tank assembly, a raw liquid metering assembly, a liquid conveying assembly, and a liquid storage assembly. The drug dispensing control unit is electrically connected to the stirring tank assembly, the raw liquid metering assembly, the liquid conveying assembly, and the liquid storage assembly, respectively.

[0107] The mixing ton assembly includes a mixing ton, several weighbridge sensors, a mixing motor, and a liquid level sensor. The weighbridge sensors are respectively set below three support points at the bottom of the mixing ton, the mixing motor is set at the top of the mixing ton, and the liquid level sensor is embedded in the side wall of the mixing ton to monitor the liquid level height of the mixture.

[0108] The raw liquid metering component includes several raw liquid tanks and several weighing sensors. Each of the raw liquid tanks is equipped with a weighing sensor at the bottom, and the raw liquid tanks are respectively connected to the liquid delivery component through pipelines.

[0109] The liquid delivery assembly includes several water pumps and several solenoid valves. The water pumps are respectively connected to the raw liquid tank and the storage tank. The output end of each water pump is connected to the solenoid valve in series through pipelines and then connected to the liquid inlet at the top of the mixing tank.

[0110] The liquid storage assembly includes a water tank and a level monitor, with the water tank connected to one of the water pumps via a pipeline.

[0111] In one implementation of the present invention, the dispensing control unit serves as the core control hub of the system and is electrically connected to the mixing tank assembly, the raw liquid metering assembly, the liquid conveying assembly, and the liquid storage assembly, respectively, to achieve coordinated control and data acquisition of each assembly. The mixing tank assembly includes a mixing tank, several weighbridge sensors, a stirring motor, and a liquid level sensor. The weighbridge sensors are respectively located below three support points at the bottom of the mixing tank, the stirring motor is located at the top of the mixing tank, and the liquid level sensor is embedded in the side wall of the mixing tank to monitor the liquid level of the mixture. The weighbridge sensors are arranged in a triangular pattern at the three support points at the bottom of the mixing tank, which can collect the force data at each point in real time, providing data support for the zoned load collaborative calibration analysis.

[0112] The raw liquid metering component includes several raw liquid tanks and several weighing sensors. Each raw liquid tank is equipped with a weighing sensor at its bottom. The raw liquid tanks are connected to the liquid delivery component through pipelines to achieve independent metering of each raw liquid.

[0113] The liquid delivery assembly includes several water pumps and several solenoid valves. The water pumps are respectively connected to the raw liquid tank and the storage tank. The output end of each water pump is connected to the solenoid valve in series through pipelines and then connected to the liquid inlet at the top of the mixing tank to realize the addition of raw liquid and clean water. The storage assembly includes a water storage tank and a liquid level monitor. The water storage tank is connected to one of the water pumps through pipelines and is used to store clean water and monitor the liquid level.

[0114] It should be noted that, as a preferred technical solution for an intelligent drug dispensing system for drone operations, several weighbridge sensors are respectively set at three support points distributed in a triangle at the bottom of the mixing tank. The support points are arranged in an equilateral triangle to ensure the comprehensiveness and symmetry of load data collection.

[0115] It should be noted that, as a preferred technical solution for an intelligent drug dispensing system for drone operations, the weighing range of the weighing sensors in each raw liquid tank is 0-200kg, the measurement accuracy level is C3, and the corresponding scale division value is 20g.

[0116] It should be noted that, as a preferred technical solution for an intelligent drug dispensing system for drone operations, the flow rate range of several water pumps is 0-50L / min, and each water pump is equipped with an independent frequency converter to achieve precise flow rate adjustment.

[0117] The specific steps for each unit module in the intelligent drug dispensing system for unmanned aerial vehicle (UAV) operations described above to implement the corresponding functions can be found in the steps of the embodiments of the intelligent drug dispensing control method for UAV operations described above, and will not be repeated here.

[0118] Based on the preferred embodiments of the present invention described above, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. An intelligent drug dispensing system for unmanned aerial vehicle (UAV) operations, comprising: The dosing control unit, the mixing tank assembly, the stock solution metering assembly, the liquid conveying assembly, and the liquid storage assembly are characterized in that; The dosing control unit is electrically connected to the stirring tank assembly, the stock solution metering assembly, the liquid conveying assembly, and the liquid storage assembly, respectively. The mixing ton assembly includes: a mixing ton (1), several weighbridge sensors (2), a mixing motor (3) and a liquid level sensor (4). The several weighbridge sensors (2) are respectively set below the three support points at the bottom of the mixing ton (1), the mixing motor (3) is set at the top of the mixing ton (1), and the liquid level sensor (4) is embedded in the side wall of the mixing ton (1) to monitor the liquid level height of the mixture. The raw liquid metering component includes: several raw liquid tanks (5) and several floor scale sensors (6). Each of the several raw liquid tanks (5) is provided with a floor scale sensor (6) at its bottom. The several raw liquid tanks (5) are respectively connected to the liquid delivery component through pipelines. The liquid delivery assembly includes: several water pumps (7) and several solenoid valves (8). The several water pumps (7) are respectively connected to the original liquid tank (5) and the storage tank. The output ends of the several water pumps (7) are connected to the solenoid valves (8) in series through pipelines and then connected to the liquid inlet at the top of the mixing ton (1).

2. The intelligent drug dispensing system for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: The liquid storage assembly includes a water tank (9) and a liquid level monitor (10), wherein the water tank (9) is connected to one of the water pumps (7) via a pipeline.

3. The intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: Several of the weighbridge sensors (2) are respectively set at three support points distributed in a triangle at the bottom of the mixing ton (1). Each support point is arranged in an equilateral triangle to ensure the comprehensiveness and symmetry of load collection.

4. A method for intelligent drug dispensing control in unmanned aerial vehicle (UAV) operations, based on an intelligent drug dispensing system for UAV operations according to any one of claims 1-3, characterized in that: Includes the following steps: S1. Obtain drug dispensing task instruction data, original solution ratio parameter data, weighbridge weighing sensor data, and weighbridge weighing sensor data; S2. Based on the weighbridge weighing sensor data, perform zoned load collaborative calibration analysis on the mixing ton, and make adaptive leveling judgment on the weighing benchmark of the mixing ton (1) according to the zoned load collaborative calibration analysis results. Based on the adaptive leveling judgment results of the weighing benchmark, obtain the real-time corrected weighing benchmark data of the mixing ton (1). S3. Based on the weighing sensor data of the weighing scale, each original liquid tank (5) is independently weighed. Based on the real-time correction of the weighing reference data of the mixing ton (1), the mixed liquid is weighed collaboratively. Based on the independent weighing data and the collaborative weighing data, a double verification deviation analysis is performed. Based on the results of the double verification deviation analysis, it is determined whether the drug metering is accurate. S4. Generate drug dispensing execution control instructions based on the results of double verification deviation analysis, and control each water pump (7) and solenoid valve (8) to perform raw liquid addition, stirring and quantitative drug addition operations according to the drug dispensing execution control instructions.

5. The intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: The specific steps of S1 are as follows: S11. Obtain the drug dispensing task instruction data through the drug dispensing control unit. The drug dispensing task instruction data includes the target ratio of each original liquid, the total demand of the mixed liquid, and the start-up sequence data of the water pump (7). S12. Obtain the stock solution ratio parameter data through the drug dispensing control unit. The stock solution ratio parameter data includes the density data of each stock solution, the weight percentage data of each stock solution, and the preset accuracy threshold range data. S13. Obtain the original weighing data of the zone load through several weighbridge sensors (2) of the mixing ton (1), and obtain the independent weighing data of each raw liquid tank (5) through the weighbridge sensors (6) of each raw liquid tank (5). S14. After analyzing and processing the acquired data, store it in the control unit's memory for use in the drug dispensing control process.

6. The intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: The specific steps of S2 are as follows: S21. Calculate the real-time load value at each point based on the original weighing data of the zoned load collected by several weighbridge sensors of the mixing ton (1). S22. Calculate the overall load deviation of the mixing ton based on the real-time net load value of each point; S23. Adaptive leveling judgment of weighing benchmark based on overall load deviation value.

7. The intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: S3 includes the following specific steps: S31. Based on the independent weighing data collected by the weighing sensor (6) of each raw liquid tank (5), each raw liquid is independently metered. S32. Calculate the synergistic weighing value of the mixture based on the corrected weighing reference data of the mixing ton; S33. Obtain the independent measurement values ​​of each original solution and the synergistic weighing measurement value of the mixed solution, and calculate the double verification deviation value; S34. Determine whether the double verification deviation value is within the preset accuracy threshold range. If the double verification deviation value is less than the preset accuracy threshold, determine that the drug dispensing measurement is accurate and proceed to the next stage of operation. If the deviation value of the double verification is greater than or equal to the preset accuracy threshold, an abnormal alarm will be triggered and subsequent measurement parameters will be automatically corrected before proceeding to the next stage of operation.

8. The intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: S41. Generate a water pump (7) control command sequence based on the drug dispensing task instruction data and the results of the double verification deviation analysis. The water pump (7) control command sequence includes: the start-up duration data, start-up sequence data and flow rate adjustment data of each water pump (7). S42. Generate a sequence of solenoid valve control instructions based on the drug dispensing task instruction data. The sequence of solenoid valve (8) control instructions includes the opening and closing timing data and the switching status data of each solenoid valve. S43. Generate control instructions for the stirring motor (3) based on the drug dispensing task instruction data and the control parameters of the stirring motor (3), wherein the control instructions for the stirring motor (3) include stirring speed data, stirring duration data and stirring interval duration data; S44. The control unit sends corresponding control commands to each water pump (7), solenoid valve (8) and stirring motor (3) to complete the full-process automated control of raw liquid addition, drug mixing and quantitative drug addition.

9. The intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: The specific parameters of the control command sequence of the water pump (7) are as follows: the first water pump corresponds to the control of adding raw liquid A, the second water pump corresponds to the control of adding raw liquid B, the third water pump corresponds to the control of adding raw liquid C, the fourth water pump corresponds to the control of adding clean water, and the start-up time of several water pumps (7) is calculated and determined according to the target ratio of the corresponding raw liquid and the preset flow rate value.

10. The intelligent drug dispensing control method for unmanned aerial vehicle (UAV) operations according to claim 1, characterized in that: The specific parameters of the control command sequence of the solenoid valve (8) are as follows: several solenoid valves (8) are respectively set at each pipeline node, and perform corresponding opening and closing actions according to the pump opening sequence and control logic to realize the on-off control of the raw liquid pipeline, the clean water pipeline and the mixed liquid conveying pipeline.

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