A multi-sensor fusion agricultural precision irrigation system

Abstract

The present invention relates to the field of automatic irrigation control technology, specifically a multi-sensor fusion agricultural precision irrigation system, which includes a leaf area analysis module, an environmental assessment module, a task scheduling module, an execution control module, and a feedback regulation module. In the present invention, by introducing a comparison between the crop leaf area index and the growth stage target value, a dynamic expression of the group water demand is achieved. The environmental evapotranspiration impact factor is generated by combining light and temperature disturbance parameters, enhancing the timeliness of water demand driving force identification. Regional water pressure disturbance data is used to determine the task execution order, optimizing the multi-region irrigation resource allocation process. The dual-factor adjustment mechanism of water volume and pressure difference is utilized to improve the rationality of time allocation and response accuracy. The water supply status is analyzed and the deviation of the task target is compared to achieve dynamic supplementary irrigation control, improve the closed-loop capability and supplementary irrigation accuracy of the irrigation cycle control, and enhance the stable allocation capability and irrigation response efficiency of the irrigation system under the influence of multiple variables.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic irrigation control, and in particular to a multi-sensor fusion agricultural precision irrigation system. Background Art

[0002] The field of automatic irrigation control technology includes technologies for automated management of agricultural irrigation processes through sensor monitoring, data collection, and control execution. The core content of this technology lies in the comprehensive formulation of irrigation control strategies based on crop water demand, soil moisture changes, meteorological factors, and environmental parameter information, and the use of actuators such as solenoid valves, drip irrigation systems, or sprinkler systems to achieve precise irrigation operations. This field involves multiple technical links including sensor layout, data acquisition terminals, signal transmission methods, control logic settings, and control node layout, aiming to improve water resource utilization efficiency, ensure timely satisfaction of crop water needs, and realize irrigation automation, informatization, and intelligence.

[0003] Among them, the multi-sensor fusion agricultural precision irrigation system refers to a composite perception network constructed based on multiple types of sensor devices such as soil moisture sensors, ambient temperature and humidity sensors, and light sensors. It continuously monitors the crop growth environment and soil conditions through multi-source sensor nodes deployed in the field, and uses the terminal acquisition module to integrate the acquired parameters in time series and perform data judgment. Combined with the control module, it realizes the control operation of irrigation equipment such as electromagnetic valves or water pumps. The system mainly covers soil moisture perception, climate factor acquisition, data processing module judgment output, and actuator response. Specifically, it obtains representative environmental information in the area by deploying sensor nodes at multiple points, collects and integrates multi-source data through edge computing devices, and triggers irrigation instructions according to set thresholds or judgment rules to build an irrigation response system consisting of perception, transmission, analysis and control.

[0004] Traditional agricultural precision irrigation control systems rely on single-point monitoring and static threshold triggering of soil moisture and environmental data, and lack a structural expression of the water carrying capacity of crop groups, resulting in a lag in the identification of actual dynamic water demand. Under drastic environmental fluctuations, false triggering and supply-demand mismatch problems are prone to occur. The execution sorting of irrigation tasks is mostly based on rotation or static priority configuration, and the execution order cannot be dynamically adjusted according to the real-time pressure supply capacity, which can easily cause high-load nodes to overlap and lead to abnormal pressure drop in local water supply systems, resulting in flow imbalance and uneven crop water supply problems. In the task completion assessment, a single valve control execution time is relied upon as the completion standard, and the comparison process between pressure supply fluctuations, regional task targets and actual water supply is not introduced, resulting in difficulty in identifying biased irrigation and missed irrigation, affecting the accuracy of supplementary irrigation management and the efficiency of water resource utilization. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and propose a multi-sensor fusion agricultural precision irrigation system.

[0006] In order to achieve the above objectives, the present invention adopts the following technical solutions: A multi-sensor fusion agricultural precision irrigation system includes:

[0007] The leaf area analysis module acquires crop canopy images, extracts the current leaf area estimate, calls the target leaf area parameters corresponding to the crop type and growth stage, analyzes the impact of actual leaf area on canopy transpiration intensity, assesses the response to the water consumption capacity of the plant population, and generates a leaf area index response coefficient.

[0008] The environmental assessment module uses the leaf area index response coefficient to call the data sequence of the light sensor and the temperature sensor, analyzes the impact of light intensity and temperature level on crop transpiration rate, evaluates the impact of real-time environmental factors on water demand, and obtains the environmental evapotranspiration influencing factor;

[0009] The task arrangement module uses the environmental evapotranspiration influencing factor to obtain water pressure data at multiple locations of the water supply network in real time, analyzes the impact of executing irrigation tasks in multiple areas on the pressure of the water supply network, adjusts the execution order of irrigation tasks in multiple areas, and generates a task execution list;

[0010] The execution control module calls the leaf area index response coefficient, environmental evapotranspiration influencing factor and task execution list to calculate the amount of irrigation water required for each area, combines the difference between the real-time water pressure and the preset supply pressure standard, calculates the irrigation time, and obtains the irrigation time control parameter.

[0011] As a further solution of the present invention, the leaf area index response coefficient includes the leaf area index difference, the transpiration area ratio, and the stage response level; the environmental evaporation influencing factor includes the light fluctuation amplitude coefficient, the temperature rise rate value, and the environmental hysteresis response factor; the task execution list specifically includes the partition priority level, water supply interference intensity, and task sorting number; the irrigation duration control parameter specifically refers to the dynamic duration correction value, the water pressure correction coefficient, and the valve opening and closing matching value.

[0012] As a further solution of the present invention, the leaf area analysis module includes:

[0013] The image acquisition submodule acquires crop canopy images and analyzes the crop leaf area in the target irrigation area based on the proportion of green pixels in each area of ​​the image to obtain an estimated leaf area value.

[0014] The leaf area comparison submodule calls the leaf area estimation value and establishes a leaf area index difference value according to the leaf area parameters corresponding to the target crop type at each growth stage;

[0015] The response degree calculation submodule calls the leaf area index difference and uses the formula:

[0016]

[0017] Calculate the leaf area index response coefficient;

[0018] Among them, C LAI represents the leaf area index response coefficient, LAI e Represents the estimated leaf area ratio, dimensionless, LAI t Represents the leaf area ratio parameter corresponding to the target growth stage, dimensionless, S c Represents the transpiration sensitivity coefficient of the crop stage, dimensionless, A r Represents the transpiration base area in square meters, N p Represents the area occupied by a single plant, in square meters.

[0019] As a further solution of the present invention, the environmental assessment module includes:

[0020] The environmental parameter acquisition submodule uses the leaf area index response coefficient to call the light sensor and the temperature sensor to collect the light intensity sequence and soil surface temperature value in real time, analyzes the fluctuation characteristics of the data, and establishes the environmental fluctuation characteristic value;

[0021] The transpiration correlation submodule analyzes the effects of light intensity and temperature level on crop transpiration rate based on the environmental fluctuation characteristic value, evaluates the effects of various environmental conditions on crop water demand, and obtains transpiration correlation dynamic values;

[0022] The environmental impact analysis submodule calls the transpiration-related dynamic value to evaluate the impact of real-time environmental factors on water demand using the formula:

[0023]

[0024] Calculate environmental evapotranspiration impact factors;

[0025] Among them, E f is the environmental evapotranspiration influencing factor, unit is dimensionless, I m I is the maximum light intensity of the day, in watts per square meter. a is the actual light intensity in the current period, in watts per square meter, |I m -I a | is the absolute value of the light intensity offset, in watts per square meter, T s is the current surface temperature of the soil in degrees Celsius, T b is the physiological starting temperature threshold of evapotranspiration, in degrees Celsius, W j is the disturbance weight factor of the jth period, in dimensionless units, Ir The reference value of sunlight intensity set in the area, in watts per square meter, T r is the daily average temperature reference value set in the area, in degrees Celsius, and j is the index number of the recording point, in dimensionless units.

[0026] As a further solution of the present invention, the task arrangement module includes:

[0027] The pressure data acquisition submodule calls the environmental evapotranspiration influencing factor and uses pressure sensors to collect water pressure data at multiple locations in the water supply network before, during, and after irrigation, analyzes the pressure drop amplitude and pressure recovery time of the network, and generates regional water pressure disturbance characteristic values;

[0028] The pipe network load determination submodule calls the regional water pressure disturbance characteristic value and uses the formula:

[0029]

[0030] Calculate the pipe network pressure influence coefficient;

[0031] Among them, C p is the pipe network pressure influence coefficient, dimensionless, P min is the lowest water pressure in the current mission area, in kPa, P b is the water supply bottom pressure, in kPa, ΔP is the water pressure increment in the recovery phase, in kPa, T r is the water pressure recovery time in seconds, P j is the instantaneous water pressure at the jth moment, in kPa, is the average water pressure value of the irrigation section, in kPa, P s is the standard supply pressure value, in kPa, A c is the irrigation area of ​​the current region, in square meters, j is the index number of the sampling time, dimensionless, and m is the total number of sampling periods, dimensionless;

[0032] The task sequence optimization submodule calls the pipe network pressure influence coefficient, adjusts the execution order of the irrigation tasks in multiple irrigation areas according to the impact of the irrigation tasks in multiple irrigation areas on the water supply pipe network pressure, and obtains a task execution list.

[0033] As a further solution of the present invention, the execution control module includes:

[0034] The water quantity calculation submodule calls the leaf area index response coefficient, environmental evapotranspiration influencing factor and task execution list, evaluates the irrigation water quantity demand of each irrigation area according to the area, leaf area, light intensity and temperature level of each irrigation area, and generates the regional irrigation water quantity value;

[0035] The water pressure extraction submodule calls the regional irrigation water volume value, collects the real-time water pressure monitoring data of each irrigation area in the water supply network, calculates the pressure difference data corresponding to each irrigation area in combination with the preset supply pressure standard value, and obtains the supply pressure offset amplitude value;

[0036] The duration control submodule calls the supply pressure offset amplitude value, calculates the irrigation time required for each area, and adjusts the irrigation solenoid valve control parameters of each irrigation area to obtain the irrigation duration control parameters.

[0037] As a further embodiment of the present invention, the system further comprises:

[0038] Based on the irrigation duration control parameters, the feedback regulation module obtains the solenoid valve opening duration and water pressure fluctuation data of each irrigation area in each irrigation task, calculates the actual water supply completion status of each area, compares it with the target water supply plan, calculates the degree of deviation, configures the supplementary irrigation task, and generates a precise irrigation configuration task;

[0039] The precision irrigation configuration task includes a water supply deviation ratio, a supplementary irrigation period, and a water replenishment target.

[0040] As a further solution of the present invention, the feedback adjustment module includes:

[0041] The water supply status extraction submodule calculates the actual water supply completion status of each task area based on the irrigation duration control parameter by collecting the solenoid valve opening duration and water pressure fluctuation data in each irrigation task, and obtains the actual water supply completion value;

[0042] The execution deviation determination submodule calls the actual water supply completion value, combines the water volume value required by the task target, calculates the water supply deviation of each area, and generates a water supply execution deviation value;

[0043] The supplementary irrigation configuration generation submodule calls the water supply execution deviation value, evaluates the water supply deviation level of multiple areas according to the water supply deviation, configures supplementary irrigation tasks, and generates precise irrigation configuration tasks.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are:

[0045] In the present invention, by introducing the comparison between the crop leaf area index and the growth stage target value, the dynamic expression of the group water demand is realized, the environmental evapotranspiration influencing factor is generated by combining the light and temperature disturbance parameters, the timeliness of the water demand driving force identification is enhanced, the regional water pressure disturbance data is used to determine the task execution order, the multi-region irrigation resource allocation process is optimized, and the water volume and pressure difference dual-factor adjustment mechanism is used to improve the rationality of time allocation and response accuracy. The deviation comparison of water supply status analysis and task objectives is realized to realize dynamic irrigation control, improve the closed-loop capability of irrigation cycle control and the accuracy of irrigation, and enhance the stable allocation capability and irrigation response efficiency of the irrigation system under the influence of multiple variables. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a system flow chart of the present invention;

[0047] Figure 2 This is a flow chart of the leaf area analysis module of the present invention;

[0048] Figure 3 This is a flow chart of the environmental assessment module of the present invention;

[0049] Figure 4 A flowchart of the task arrangement module of the present invention;

[0050] Figure 5 This is a flow chart of the execution control module of the present invention;

[0051] Figure 6 This is a flow chart of the feedback adjustment module of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0054] See also Figure 1 , a multi-sensor fusion agricultural precision irrigation system includes:

[0055] The leaf area analysis module acquires crop canopy images, extracts the current leaf area estimate, calls the target leaf area parameters corresponding to the crop type and growth stage, analyzes the impact of actual leaf area on canopy transpiration intensity, assesses the response to the water consumption capacity of the plant population, and generates a leaf area index response coefficient.

[0056] The environmental assessment module uses the leaf area index response coefficient and calls the data series of the light sensor and temperature sensor to analyze the impact of light intensity and temperature levels on crop transpiration rate, evaluate the impact of real-time environmental factors on water demand, and obtain the environmental evapotranspiration influencing factor;

[0057] The task arrangement module uses environmental evapotranspiration influencing factors to obtain real-time water pressure data at multiple locations in the water supply network. By analyzing the impact of executing irrigation tasks in multiple areas on the water supply network pressure, it adjusts the execution order of irrigation tasks in multiple areas and generates a task execution list.

[0058] The execution control module calls the leaf area index response coefficient, environmental evapotranspiration influencing factor and task execution list to calculate the amount of irrigation water required for each area. Based on the difference between the real-time water pressure and the preset supply pressure standard, it calculates the irrigation duration and obtains the irrigation duration control parameters.

[0059] The feedback regulation module uses irrigation duration control parameters to obtain the solenoid valve opening duration and water pressure fluctuation data for each irrigation area during each irrigation task. It calculates the actual water supply completion status of each area, compares it with the target water supply plan, calculates the degree of deviation, and configures supplementary irrigation tasks to generate precise irrigation configuration tasks.

[0060] The leaf area index response coefficient includes the leaf area index difference, the transpiration area ratio, and the stage response level. The environmental evaporation influencing factors include the light fluctuation amplitude coefficient, the temperature rise rate value, and the environmental lag response factor. The task execution list specifically includes the partition priority level, water supply interference intensity, and task sorting number. The irrigation duration control parameters specifically refer to the dynamic duration correction value, the water pressure correction coefficient, and the valve opening and closing matching value. The precision irrigation configuration task includes the water supply deviation ratio, the supplementary irrigation period, and the water replenishment target.

[0061] See also Figure 2 , the leaf area analysis module includes:

[0062] The image acquisition submodule acquires crop canopy images and analyzes the crop leaf area in the target irrigation area based on the proportion of green pixels in each area of ​​the image to obtain an estimated leaf area value.

[0063] The image acquisition submodule is used to obtain crop canopy images in the target area. This process uses multispectral images collected by high-resolution optical sensors as input data sources, divides the image into multiple sub-areas by pre-setting the area contour coordinates, extracts the number of green pixels in each sub-area and calculates the ratio with the total number of pixels. This ratio is the green pixel ratio. In a single area, this ratio reflects the green coverage of the surface of the area. Combined with the type of crop in the irrigated plot and the preset green coverage expectation at the current age stage, the green pixels that meet the target plot are screened. For image samples within the color ratio threshold range, if the green pixel threshold is set to 0.65, then when the number of green pixels in a sub-region is 26,000 and the total number of pixels is 40,000, the green ratio of the region is 0.65, which meets the screening criteria. Furthermore, the green ratios of all sub-regions in the target region are traversed to form a green coverage matrix array. For example, the green ratio value array is G = [0.65, 0.63, 0.68, 0.70, 0.66]. After averaging the array, the average green coverage of the crop canopy in the current plot is obtained, which is recorded as: The linear conversion relationship between the green percentage and leaf area index (LAI) of the crop stage is obtained by looking up the table: LAI = a·G avg +b, where LAI is the leaf area index, a is the green cover conversion coefficient set for different crop stages, G avg is the average green pixel ratio in the target area, and b is the fixed offset value in the conversion relationship. Setting a = 4.5 and b = 0.2, and substituting the numerical values ​​into: LAI = 4.5 · 0.664 + 0.2 = 3.188, we obtain the estimated leaf area value for the region.

[0064] The leaf area comparison submodule calls the leaf area estimation value and establishes the leaf area index difference based on the leaf area parameters corresponding to the target crop type at each growth stage;

[0065] The leaf area comparison submodule obtains the leaf area estimate value and refers to the type of crop planted and the current growth stage to call the corresponding target leaf area parameter in the preset database. For example, the target leaf area parameter of corn at the jointing stage is 3.00. According to the preset value classification standard of different crop stages, LAI is set as a set of threshold segments. For example, the reasonable range of the jointing stage is (2.80, 3.20). If the actual estimated value is 3.188, it falls within this range and is recorded as valid data. The index difference calculation formula between the estimated value and the target parameter is further established: LAI diff =LAI e -LAI t =3.188-3.00=0.188, where LAI diff is the leaf area index difference, LAI e LAI is the leaf area estimate obtained by image analysis. t= is the preset target leaf area index parameter, which is dimensionless. If the difference exceeds ±0.3, it is marked as an abnormal area and requires image resampling. In addition, to clarify the impact of this difference on the subsequent transpiration response coefficient, the response level is divided according to the difference amplitude. If the difference is in the interval [-0.1, 0.1], it is Level I; if it is in the interval [-0.2, -0.1)∪(0.1, 0.2], it is Level II; if it exceeds the above range, it is Level III. The current difference is 0.188, so it is in Level II, providing a basis for subsequent response degree calculations.

[0066] The response degree calculation submodule calls the leaf area index difference using the formula:

[0067]

[0068] Calculate the leaf area index response coefficient;

[0069] Among them, C LAI represents the leaf area index response coefficient, LAI e Represents the estimated leaf area ratio, dimensionless, LAI t Represents the leaf area ratio parameter corresponding to the target growth stage, dimensionless, S c Represents the transpiration sensitivity coefficient of the crop stage, dimensionless, A r Represents the transpiration base area in square meters, N p Represents the area occupied by a single plant, in square meters;

[0070] The response degree calculation submodule, based on the calculation of leaf area index difference, calls each participating parameter and performs parameter normalization, formula substitution and multiple multiplication and division operations. First, it reads the leaf area estimated ratio value LAI e =0.85, target leaf area parameter LAI t =0.75, the square of the difference between the two is calculated as (0.85-0.75) 2 =0.01, then read the crop stage transpiration sensitivity coefficient S c =1.2, read the transpiration base area A r =3.5m 2 , read the area N occupied by a single plant p =0.25m 2 , enter the calculation formula:

[0071]

[0072] This value represents the leaf area index response coefficient of the current plot at the current crop stage. In order to facilitate differential calculations for different crop plots at different times, parameter collection and quantification standards need to be set. cThe value is obtained through the crop water sensitivity test, and the general range is set to [1.0, 2.0]. r According to the field transpiration measurement standard, the range is set to 3.0–4.5 square meters, N p The data is collected based on the crop planting density, such as the corn planting density is 4 plants / m 2 , then the area occupied by a single plant is 0.25m 2 . Among them, the leaf area index response coefficient is a comprehensive indicator used to quantify the relationship between the current crop leaf area and its target leaf area in the growth stage. It reflects the response degree of the leaf area per unit area of ​​the current crop population to water transpiration. The calculation of this coefficient takes into account factors such as the estimated leaf area of ​​the crop, the target leaf area parameters during the growth period, the crop transpiration sensitivity coefficient, the transpiration baseline area, and the area occupied by a single plant. It reflects whether the actual leaf area of ​​the crop meets its physiological water requirements, thus becoming an important basis for determining irrigation priority. If the coefficient is low, it means that the crop water absorption capacity in this area is low and water supplementation is required as a priority; if the coefficient is high, it means that its leaf coverage and water use efficiency are at a better level. The formula is constructed based on the physiological response principle of the relationship between crop leaf area index and transpiration water demand. In agricultural irrigation control, the leaf area of ​​the crop canopy The leaf area index reflects the structural basis of photosynthesis and transpiration. The larger the leaf area, the greater the transpiration area and the stronger the water consumption capacity. Therefore, when the actual leaf area deviates from the leaf area required for the target growth stage, it will lead to an increase or decrease in the water demand per unit area. In order to reflect the impact of this deviation on the intensity of transpiration water response, the system uses the leaf area index deviation as the basic input, and uses the transpiration sensitivity of the crop in the current growth stage as the adjustment factor. The stage adjustment factor is introduced to strengthen the difference in the response of different crops to the deviation during the growth period. The planting density and the reference transpiration area are further combined to normalize the transpiration demand per unit area of ​​the group, so that the irrigation water demand response intensity in different regions, different varieties and different configuration methods is comparable. Therefore, the response coefficient becomes an important basis for judging the priority of regional water regulation needs.

[0073] Table 1 Leaf area index response parameter setting table

[0074] Crop type Growth stage Transpiration sensitivity coefficient <![CDATA[Transpiration reference area (m 2 )]]> <![CDATA[Single plant floor area (m 2 )]]> corn Jointing stage 1.2 3.5 0.25 rice Tillering period 1.4 3.0 0.20 wheat Jointing stage 1.1 3.8 0.22

[0075] As shown in Table 1, differentiated response models can be set for different crop types and growth stages through parameter configuration. In the current embodiment, the response coefficient calculated by applying the corn parameter combination is 0.01371. This result indicates that the current leaf area deviates from the target parameter to a small extent, and the water consumption capacity is in a moderate to high response state.

[0076] See also Figure 3 , the environmental assessment module includes:

[0077] The environmental parameter acquisition submodule uses the leaf area index response coefficient to call the light sensor and temperature sensor to collect the light intensity sequence and soil surface temperature values ​​in real time, analyze the fluctuation characteristics of the data, and establish the environmental fluctuation characteristic value;

[0078] The environmental parameter acquisition submodule first calls the leaf area index response coefficient value calculated in the corresponding area from the previous module based on the leaf area index response coefficient obtained in the previous module. The value is 0.01371 in the current corn jointing period irrigation plan. Then, the light sensor is used to collect the light intensity value of the current period and store it in the light intensity sequence. The sampling is performed at a unit interval of 10 minutes. If the data is collected from 10:00 to 11:00 in the morning, the value can be obtained as I = [690, 720, 735, 710, 700, 680] (unit: W / m 2 ) data set, and the soil surface temperature value of the corresponding area of ​​the surface is collected by the temperature sensor. For example, the current sampling result at 10:30 is 34°C. The sliding window volatility evaluation operation is performed on the above light data sequence, that is, the difference between the maximum and minimum values ​​in the continuous time period is calculated and divided by the average value to evaluate the degree of fluctuation. For example, max(I)=735, min(I)=680, avg(I)≈706, then the volatility is (735-680) / 706≈0.078. In the preset volatility evaluation range [0,0.05], it is stable, [0.05,0.1] is medium, and [above 0.1 is high volatility], the current light fluctuation is medium. The soil temperature value is further compared with the temperature series of the day, and the degree of deviation of the current temperature from the mean is calculated to form a temperature fluctuation characteristic value. The current environmental fluctuation characteristic value is formed by the balanced combination of the above light fluctuation rate and temperature fluctuation degree. For example, if the light fluctuation is 0.078 and the temperature fluctuation is 0.11, the average of the two is 0.094.

[0079] The transpiration correlation submodule analyzes the effects of light intensity and temperature levels on crop transpiration rate based on the environmental fluctuation characteristic values, evaluates the effects of various environmental conditions on crop water demand, and obtains transpiration correlation dynamic values;

[0080] The transpiration correlation submodule analyzes the environmental fluctuation characteristic values ​​obtained, first reading the light intensity value of the current period, 700W / m 2 The soil surface temperature is 34°C. The table is used to obtain the transpiration sensitivity range of the crop stage. If the current stage is the corn jointing stage, the transpiration sensitivity range is 100% when the light intensity is less than 600W / m 2 When the transpiration rate is limited, it exceeds 800W / m 2 It tends to be saturated, the current light intensity is 700W / m 2Being in the sensitive growth range, transpiration activity is judged to be of medium rate. At the same time, the current temperature of 34°C exceeds the transpiration starting temperature threshold of 28°C by 6°C. A table shows that this temperature difference will increase stomatal opening by 8%, indirectly promoting the transpiration rate. The transpiration impact score is obtained by multiplying and normalizing the combined score of the light sensitivity range judgment and the temperature offset amplitude. If the light sensitivity score is 0.7 and the temperature amplitude score is 0.8, the transpiration impact score is 0.7·0.8=0.56. The disturbance weight factors in different time periods are then weighted and summed, and the weight values ​​of the three sub-periods are set to 1.1, 1.2, and 1.0 respectively. The total dynamic weight formed by the combination of each parameter within 3 hours is 3.3. The current comprehensive transpiration effect value is 3.3·0.56=1.848, which is recorded as the transpiration-related dynamic value.

[0081] The environmental impact analysis submodule uses the dynamic value of transpiration correlation to evaluate the impact of real-time environmental factors on water demand using the formula:

[0082]

[0083] Calculate environmental evapotranspiration impact factors;

[0084] Among them, E f is the environmental evapotranspiration influencing factor, unit is dimensionless, I m I is the maximum light intensity of the day, in watts per square meter. a is the actual light intensity in the current period, in watts per square meter, |I m -I a | is the absolute value of the light intensity offset, in watts per square meter, T s is the current surface temperature of the soil in degrees Celsius, T b is the physiological starting temperature threshold of evapotranspiration, in degrees Celsius, W j is the disturbance weight factor of the jth period, in dimensionless units, I r The reference value of sunlight intensity set in the area, in watts per square meter, T r is the daily average temperature reference value set in the area, in degrees Celsius, and j is the index number of the recording point, in dimensionless units;

[0085] The environmental water demand assessment submodule obtains the transpiration correlation dynamic value of 1.848, calls the current light and temperature parameters, and performs the calculation of the environmental evapotranspiration impact factor. The input parameters are: the maximum light intensity of the day I m =950W / m 2 , current light intensity I a =700W / m 2 Calculate the absolute offset to be |950-700|=250W / m2 , the current soil temperature is T s =34℃, the evapotranspiration starting temperature threshold is T b =28℃, then the absolute value of the temperature difference is 6, and the square root is The three perturbation factors are set to 1.1, 1.2, and 1.0, and the total is:

[0086]

[0087] Substitute the formula to calculate the environmental evapotranspiration impact factor:

[0088]

[0089] Among them, the environmental evapotranspiration impact factor is a dimensionless parameter used to measure the ability of current environmental conditions (mainly including light intensity and soil surface temperature) to drive crop transpiration behavior. It comprehensively evaluates the stimulation intensity of environmental disturbance on crop water evaporation. Specifically, this factor reflects whether environmental factors have an enhancing effect on crop transpiration during a specific period of time. For example, under high temperature and strong light, the crop transpiration rate increases and the demand for water increases, thereby increasing the value of this factor. As an important reference for judging the timing of irrigation, it helps the system dynamically adjust the irrigation plan. The formula first reflects the intensity of light disturbance through the difference between the maximum light intensity of the day and the current actual light value, and then evaluates the evaporation trend caused by temperature fluctuations through the degree of deviation between the current soil temperature and the physiological starting temperature. The two disturbance terms are then combined and superimposed with the disturbance weights in continuous time periods to express the cumulative excitation intensity of environmental disturbances on the transpiration system on a certain time scale. Finally, the above excitation values ​​are normalized relative to the set sunshine reference intensity and average daily temperature to ensure that the output result is a dimensionless relative disturbance ratio, which is used to measure the pure environmental driving ability of the current environmental state on crop evaporation behavior, and serves as an important input coefficient for judging irrigation water demand.

[0090] Table 2 Key parameter settings for environmental assessment module

[0091] Parameter name Numerical unit Source Maximum light intensity 950 <![CDATA[W / m 2 ]]> Sensor maximum value acquisition Actual light intensity 700 <![CDATA[W / m 2 ]]> Sampling time measurement value Soil surface temperature 34 ℃ Temperature probe collection Starting temperature threshold 28 ℃ Transpiration physiological measurement settings Reference sunlight intensity 900 <![CDATA[W / m 2 ]]> Historical statistical mean Temperature reference value 30 ℃ Historical statistical mean Perturbation weight sequence [1.1,1.2,1.0] dimensionless Set by time period

[0092] As shown in Table 2, the above calculation process forms a complete evapotranspiration impact factor, which will be used as an important reference indicator to determine the irrigation sequence of each area in the subsequent task arrangement module.

[0093] See also Figure 4 , the task arrangement module includes:

[0094] The pressure data acquisition submodule uses environmental evapotranspiration influencing factors and pressure sensors to collect water pressure data at multiple locations in the water supply network before, during, and after irrigation. It analyzes the pressure drop and pressure recovery time of the network to generate regional water pressure disturbance characteristic values.

[0095] The pressure data acquisition submodule obtains the environmental evaporation influence factor E output by the previous module f =0.03085, the pressure sensors deployed at the nodes in each area are called. Three time periods are selected in the current scheduling cycle for pressure sampling, namely 1 minute before irrigation, 5 minutes during irrigation, and 10 minutes of continuous monitoring of the pressure recovery process after irrigation. The recorded time points are t1, t2, and t3. In the example setting, the data of the monitoring point A in a certain area are as follows: the water pressure before irrigation is 188kPa, the lowest water pressure during irrigation drops to 180kPa, and the pressure is restored 6 minutes after irrigation. It recovers to 185kPa, recovers to 187kPa in the 10th minute, and finally recovers to 188kPa. The water pressure at the starting recovery point is set to the minimum value of 180kPa and the maximum recovery value is 188kPa. The water pressure recovery increment ΔP = 188-180 = 8kPa. The recovery time is set to 120 seconds from 180kPa to 188kPa. At the same time, the instantaneous water pressure sequence during the sampling irrigation period is P = [182, 188, 185, 183, 186] kPa. The average value of the sequence is calculated as The fluctuation set is obtained by calculating the absolute value of the deviation from the mean at each moment The final water pressure disturbance characteristics are calculated by synthesizing the drop amplitude, water pressure increment and deviation amplitude.

[0096] The pipe network load determination submodule calls the regional water pressure disturbance characteristic value and uses the formula:

[0097]

[0098] Calculate the pipe network pressure influence coefficient;

[0099] Among them, C p is the pipe network pressure influence coefficient, dimensionless, P min is the lowest water pressure in the current mission area, in kPa, P b is the water supply bottom pressure, in kPa, ΔP is the water pressure increment in the recovery phase, in kPa, T r is the water pressure recovery time in seconds, P j is the instantaneous water pressure at the jth moment, in kPa, is the average water pressure value of the irrigation section, in kPa, P s is the standard supply pressure value, in kPa, A c is the irrigation area of ​​the current region, in square meters, j is the index number of the sampling time, dimensionless, and m is the total number of sampling periods, dimensionless;

[0100] After reading the key parameters obtained by the sampling calculation above, the pipe network load determination submodule executes the pipe network pressure influence coefficient C p The calculation process, the parameter values ​​are as follows: the minimum water pressure is P min =180kPa, the water supply bottom pressure is P b =150kPa, so the square of the difference is (180-150) 2 =900, the water pressure recovery increment is ΔP=70kPa, and the recovery time is T r =120s, calculate the square of the incremental term The instantaneous water pressures sampled at the five moments are P1=182, P2=188, P3=185, P4=183, and P5=186 kPa, and the average is The sum of the absolute values ​​of the offset values ​​at each moment is The overall numerator is 900+0.34028+9.2=909.54028, and the standard supply pressure value is P s =200kPa, the irrigation area is A c =500m 2 , the denominator of the product is P s ·A c =100000, the final calculation result is:

[0101]

[0102] Among them, the network pressure impact coefficient is used to evaluate the intensity of disturbance caused to the water supply network during the execution of the task in a specific irrigation area. The coefficient comprehensively considers factors such as the offset between the lowest water pressure in the area during irrigation and the system's lower limit pressure, the increment and time for the water pressure to recover from the lowest value to a stable state, and the amplitude of water pressure fluctuations. It is normalized based on the regional irrigation area and is used to quantify the pressure disturbance risk of the water supply system per unit area. A high coefficient means that the irrigation task in the area has a significant impact on the network pressure, and its execution priority needs to be lowered in the task sorting to avoid system instability caused by insufficient local pressure. The formula evaluates the disturbance behavior caused to the water supply network during the execution of irrigation tasks. First, the offset between the lowest water pressure value monitored in the current irrigation area during the task execution period and the system-set supply pressure limit is used to reflect the risk of extreme pressure loss. The pressure recovery rate is then calculated by dividing the pressure change generated by the pressure recovering from the lowest point to a stable state by the recovery time. The disturbance judgment of the slow recovery area is strengthened by squaring. Then, the offset amplitude between the instantaneous water pressure and the average water pressure value of the section at multiple time points during the task execution is extracted, and the absolute value is summed to reflect the fluctuation frequency and amplitude. Finally, the sum of the three disturbance characteristics is divided by the product of the system standard supply pressure and the current irrigation area area. The pressure disturbance intensity per unit area is output on a unified dimensional scale to construct a dimensionless network pressure influence coefficient for task sorting.

[0103] Table 3 Example of calculation parameters for pipe network pressure impact

[0104] Parameter name Numerical unit Source Minimum water pressure 180 kPa Minimum monitoring value during irrigation Bottom pressure 150 kPa System preset water supply limit Water pressure increase 70 kPa After irrigation, it returned to its initial value Recovery time 120 Second Time from minimum to initial water pressure Standard supply pressure 200 kPa Pipeline network design pressure supply standard Irrigated area 500 <![CDATA[m 2 ]]> Regional planar mapping acquisition Instantaneous water pressure series [182,188,185,183,186] kPa Sampling period measurement records

[0105] As shown in Table 3, all the parameters can be obtained by deploying sensors in a conventional field environment and constitute a complete quantitative description of the pressure disturbance.

[0106] The task sequence optimization submodule calls the pipe network pressure influence coefficient, adjusts the execution order of irrigation tasks in multiple irrigation areas based on the impact of irrigation tasks on the water supply network pressure, and obtains the task execution list;

[0107] After obtaining the pressure influence coefficient calculated from all irrigation areas, the task sequence optimization submodule uses it as the irrigation task priority judgment factor to prioritize multiple areas. The system reads the numbers of the irrigation areas to be irrigated as A, B, C, D, and E, and corresponds to the calculated C p The values ​​are C p= [0.0091, 0.0132, 0.0075, 0.0153, 0.0111]. The system sorts the above values ​​in ascending order to form a task priority of C, A, E, B, D. It also calculates the weights of overlapping areas along the downstream water pressure transmission path based on the upstream pipe network topology. A critical pressure interference threshold is set for overlapping pairs of areas. If the difference in pressure impact coefficients between any pair of areas is less than 0.003 and more than 90% of the nodes in the paths overlap, the area is classified as a mutually exclusive irrigation group and an alternate irrigation strategy is implemented. The resulting irrigation task execution list is C, A, (E, B), D, with a 15-minute interval between the executions of E and B. This result indicates that the system has completed task sorting for all irrigation areas within the current cycle and resolved the conflict in pipe network pressure stability.

[0108] See also Figure 5 , the execution control module includes:

[0109] The water calculation submodule uses the leaf area index response coefficient, environmental evapotranspiration influencing factor and task execution list to evaluate the irrigation water demand of each irrigation area based on the area, leaf area, light intensity and temperature level of each irrigation area, and generates the regional irrigation water value;

[0110] After receiving the leaf area index response coefficient, environmental evapotranspiration impact factor, and task execution list data, the water quantity calculation submodule first calls the basic parameters of each irrigation area in turn. It reads that the area of ​​area A is 500 square meters, its leaf area index response coefficient is 0.0137, and its environmental evapotranspiration impact factor is 0.03085. The light intensity sensor is connected to obtain the current value of 720W / m 2 The temperature sensor reads 33°C. Based on the set empirical adjustment factor model, the system normalizes the light intensity to 0.72, and calculates the temperature adjustment coefficient as 1.8 in the temperature adjustment model with 25°C as the reference. Then, a combined calculation is performed, and the combined coefficient product model is used to multiply each factor to solve the product. The theoretical irrigation water demand for area A is 273.87 liters. This water value will be used in the supply pressure comparison and irrigation time setting in subsequent steps.

[0111] The water pressure extraction submodule calls the regional irrigation water volume value, collects the real-time water pressure monitoring data of each irrigation area in the water supply network, and calculates the pressure difference data corresponding to each irrigation area in combination with the preset supply pressure standard value to obtain the supply pressure offset amplitude value;

[0112] After the water pressure extraction submodule completes the generation of regional irrigation water volume values, it immediately starts the pipe network pressure monitoring interface to obtain the real-time water pressure data corresponding to the irrigation start period of region A. The recorded value is 180kPa. At the same time, the system set supply pressure standard value is called 200kPa. By direct subtraction, the supply pressure offset of the current region is 20kPa, that is: ΔP = 200-180 = 20kPa. The supply pressure offset amplitude value is used to judge the actual flow deviation degree of the current region. The flow rate benchmark set by the system is a water supply rate of 10L / min per unit time under 200kPa. Under the condition of actual water pressure of 180kPa, it needs to be adjusted proportionally. The flow rate correction factor is 180 / 200 = 0.9. The actual available flow rate is: q real =10·0.9=9L / min. This data will be used to calculate the irrigation time in the next step.

[0113] The duration control submodule calls the supply pressure offset amplitude value, calculates the irrigation time required for each area, and adjusts the irrigation solenoid valve control parameters of each irrigation area to obtain the irrigation duration control parameters;

[0114] The duration control submodule receives the actual flow rate q obtained above real =9L / min and the target irrigation water volume Q = 273.87L. The required irrigation time is calculated by the ratio of the two and the unit is converted into minutes to obtain: Minutes, according to the system control logic, after converting 30.43 minutes into seconds, it is adjusted to an integer time to set the solenoid valve opening duration, and finally the irrigation duration control parameter is set to 1826 seconds, which is written into the task table of the solenoid valve controller for timed irrigation opening. The duration parameter will be used as the input signal of the execution control module to execute precise control commands.

[0115] Table 4 Regional irrigation calculation and control parameters

[0116] Parameter name Area A Area B Region C <![CDATA[Irrigation area (m 2 )]]> 500 650 420 Leaf area response coefficient 0.0137 0.0152 0.0129 Evapotranspiration influencing factors 0.03085 0.03410 0.02975 <![CDATA[Illumination intensity (W / m 2 )]]> 720 680 750 Temperature (℃) 33 32 31 Irrigation water volume (L) 273.87 389.47 193.42 Current water pressure (kPa) 180 175 185 Standard water pressure (kPa) 200 200 200 Actual flow rate (L / min) 9.00 8.75 9.25 Irrigation duration (minutes) 30.43 44.51 20.91

[0117] As shown in Table 4, the theoretical irrigation water volume for regions A, B, and C is calculated under the same control logic by calling parameters such as the irrigation area, leaf area response coefficient, environmental evapotranspiration influencing factor, light intensity, and temperature of each region. The actual flow rate is obtained by comparing the current water pressure with the system standard supply pressure value, and finally the irrigation duration control result for each region is formed to ensure that the water allocation and time distribution of each region under different water supply status and environmental conditions are reasonable and controllable.

[0118] See also Figure 6 , the feedback regulation module includes:

[0119] The water supply status extraction submodule is based on the irrigation duration control parameter. By collecting the solenoid valve opening duration and water pressure fluctuation data in each irrigation task, it calculates the actual water supply completion status of each task area and obtains the actual water supply completion value.

[0120] After receiving the irrigation duration control parameters, the water supply status extraction submodule monitors the actual task execution according to the solenoid valve opening control parameters set for each irrigation area and the real-time monitoring value. The specific operation is to read the irrigation opening time set for area A as 1830 seconds. At the same time, the pressure sensor records the average working water pressure during the execution process as 180kPa. According to the proportional relationship between the system supply pressure standard 200kPa and the reference flow rate 10L / min, the current pressure is first converted to the actual flow rate, that is, 180kPa is converted into a relative supply pressure percentage of 180 / 200=0.9. Based on this, the flow rate is adjusted to 10·0.9=9L / min. The actual water supply of the task cycle is calculated based on the time as (9·1830) / 60=274.5L, and compared with the task plan. The target water supply volume of 273.87L was compared with the target water supply volume of 273.87L in the data sheet. The water pressure fluctuation values ​​collected simultaneously were recorded as: peak value 190kPa, valley value 175kPa, standard deviation 5.4kPa, and the fluctuation data were recorded as the background parameters of water supply stability. At this stage, the actual water supply completion value of area A was 274.5L. Subsequently, the water pressure sampling, flow rate conversion and total water supply volume of areas B and C were performed in the same way. The solenoid valve of area B was opened for 2600 seconds, the water pressure was 175kPa, the converted flow rate was 8.75L / min, and the total water supply was 379.17L. The solenoid valve of area C was opened for 1250 seconds, the water pressure was 185kPa, the converted flow rate was 9.25L / min, and the water supply was 192.71L. The three areas all formed independent water supply completion values ​​for subsequent deviation comparison processing.

[0121] The execution deviation determination submodule calls the actual water supply completion value, combines the water volume required by the task target, calculates the water supply deviation of each area, and generates the water supply execution deviation value;

[0122] After receiving the water supply completion values ​​of all areas, the execution deviation judgment submodule first retrieves the target water volume parameters from the configuration table for corresponding comparison. For area A, the target water volume is 273.87L and the actual completion volume is 274.5L. The direct difference is 274.5-273.87=0.63L. Since a positive number represents slightly more water supply, the system further calculates the deviation ratio as (0.63 / 273.87)·100%=0.23%. The system sets the deviation ratio grade classification standard as follows: when the deviation ratio is in the range of 0-5%, it is calibrated as Class I, which belongs to the allowable accuracy range; 5-10% is Class II; more than 10% is Class III, entering In the replenishment control range, area A is 0.23%, which is classified as Level I; the target water volume in area B is 389.47L, the actual water supply is 379.17L, the deviation is -10.30L, and the deviation ratio is (10.30 / 389.47)·100%=2.65%, which is also in Level I; the target water volume in area C is 193.42L, the actual water supply is 192.71L, the deviation is -0.71L, and the deviation ratio is (0.71 / 193.42)·100=0.37%, which is also classified as Level I. The system writes the above deviation levels into the task execution status database to form the water supply execution deviation value and deviation level judgment result.

[0123] The supplementary irrigation configuration generation submodule calls the water supply execution deviation value, evaluates the water supply deviation level of multiple areas based on the water supply deviation value, configures supplementary irrigation tasks, and generates precise irrigation configuration tasks;

[0124] After the deviation level identification is completed, the supplementary irrigation configuration generation submodule uses the deviation level information of all areas as the basis for scheduling configuration. According to the current setting, the immediate supplementary irrigation task configuration will only be executed when the deviation level is II or III. The current areas A, B, and C are all level I, and the system marks them as "no need for supplementary irrigation" and does not register new tasks in the supplementary irrigation task queue. However, this process does not skip the calculation. The system still completes the configuration judgment of the deviation level and deviation amount of each area, and writes the results into the precise irrigation configuration report to facilitate the formation of a complete cycle irrigation feedback data chain. If a region subsequently shows a trend of positive deviation of level I for multiple consecutive cycles, it will also be used to dynamically correct the future water supply setting benchmark value. In the current task cycle, the system does not generate new supplementary irrigation configuration tasks, and only outputs the configuration recommendation report table.

[0125] Table 5 Water supply status and deviation level determination table

[0126] Parameter name Area A Area B Region C Target water volume (L) 273.87 389.47 193.42 Actual water pressure (kPa) 180 175 185 Valve opening time (s) 1830 2600 1250 Actual water supply (L) 274.50 379.17 192.71 Water supply deviation (L) 0.63 -10.30 -0.71 Deviation from proportion 0.23％ 2.65％ 0.37％ Refilling level Ⅰ Ⅰ Ⅰ

[0127] As shown in Table 5, the system calculates the deviation and corresponding ratio based on the difference between the water supply target and the actual completion value of each area in the current execution cycle, and then classifies them into levels. All deviation ratios are within the tolerance range of 0–5%. Therefore, all three areas are marked as Level I and do not constitute a trigger condition for supplementary irrigation configuration.

[0128] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A multi-sensor fusion agricultural precision irrigation system, characterized by: The system comprises: The leaf area analysis module acquires crop canopy images, extracts the current leaf area estimate, calls the target leaf area parameters corresponding to the crop type and growth stage, analyzes the impact of actual leaf area on canopy transpiration intensity, assesses the response to the water consumption capacity of the plant population, and generates a leaf area index response coefficient. The leaf area analysis module includes: The image acquisition submodule acquires crop canopy images and analyzes the crop leaf area in the target irrigation area based on the proportion of green pixels in each area of ​​the image to obtain an estimated leaf area value. The leaf area comparison submodule calls the leaf area estimation value and establishes a leaf area index difference value according to the leaf area parameters corresponding to the target crop type at each growth stage; The response degree calculation submodule calls the leaf area index difference and uses the formula: ； Calculate the leaf area index response coefficient; in, represents the leaf area index response coefficient, represents the estimated proportion of leaf area, Represents the leaf area ratio parameter corresponding to the target growth stage, represents the transpiration sensitivity coefficient of the crop stage, represents the transpiration base area, represents the area occupied by a single plant; The environmental assessment module uses the leaf area index response coefficient to call the data sequence of the light sensor and the temperature sensor, analyzes the impact of light intensity and temperature level on crop transpiration rate, evaluates the impact of real-time environmental factors on water demand, and obtains the environmental evapotranspiration influencing factor; The environmental assessment module includes: The environmental parameter acquisition submodule uses the leaf area index response coefficient to call the light sensor and the temperature sensor to collect the light intensity sequence and soil surface temperature value in real time, analyzes the fluctuation characteristics of the data, and establishes the environmental fluctuation characteristic value; The transpiration correlation submodule analyzes the effects of light intensity and temperature level on crop transpiration rate based on the environmental fluctuation characteristic value, evaluates the effects of various environmental conditions on crop water demand, and obtains transpiration correlation dynamic values; The environmental impact analysis submodule calls the transpiration-related dynamic value to evaluate the impact of real-time environmental factors on water demand using the formula: ； Calculate environmental evapotranspiration impact factors; in, is the environmental evapotranspiration influencing factor, is the maximum light intensity of the day, is the actual light intensity in the current period, is the current surface temperature of the soil, is the physiological starting temperature threshold of evapotranspiration, For the The disturbance weight factor for each period, is the reference value of sunlight intensity set in the area, is the daily average temperature reference value set in the area, The index number of the record point; The task arrangement module uses the environmental evapotranspiration influencing factor to obtain water pressure data at multiple locations of the water supply network in real time, analyzes the impact of executing irrigation tasks in multiple areas on the pressure of the water supply network, adjusts the execution order of irrigation tasks in multiple areas, and generates a task execution list; The execution control module calls the leaf area index response coefficient, environmental evapotranspiration influencing factor and task execution list to calculate the amount of irrigation water required for each area, combines the difference between the real-time water pressure and the preset supply pressure standard, calculates the irrigation time, and obtains the irrigation time control parameter.

2. The multi-sensor fusion agricultural precision irrigation system according to claim 1, characterized in that: The leaf area index response coefficient includes the leaf area index difference, the transpiration area ratio, and the stage response level. The environmental evaporation influencing factors include the light fluctuation amplitude coefficient, the temperature rise rate value, and the environmental hysteresis response factor. The task execution list specifically includes the partition priority level, the water supply interference intensity, and the task sorting number. The irrigation duration control parameters specifically refer to the dynamic duration correction value, the water pressure correction coefficient, and the valve opening and closing matching value.

3. The multi-sensor fusion agricultural precision irrigation system according to claim 1, characterized in that: The task arrangement module includes: The pressure data acquisition submodule calls the environmental evapotranspiration influencing factor and uses pressure sensors to collect water pressure data at multiple locations in the water supply network before, during, and after irrigation, analyzes the pressure drop amplitude and pressure recovery time of the network, and generates regional water pressure disturbance characteristic values; The pipe network load determination submodule calls the regional water pressure disturbance characteristic value and adopts the formula: ； Calculate the pipe network pressure influence coefficient; in, is the pipe network pressure influence coefficient, dimensionless, is the lowest water pressure in the current mission area, in kPa. is the water supply bottom pressure, in kPa. is the water pressure increment in the recovery phase, in kPa, is the water pressure recovery time in seconds, For the The instantaneous water pressure at time , in kilopascals, is the average water pressure value of the irrigation section, in kPa. is the standard supply pressure value, in kPa. is the irrigation area of ​​the current region, in square meters, is the sampling time index number, dimensionless, is the total number of sampling periods, dimensionless; The task sequence optimization submodule calls the pipe network pressure influence coefficient, adjusts the execution order of the irrigation tasks in multiple irrigation areas according to the impact of the irrigation tasks in multiple irrigation areas on the water supply pipe network pressure, and obtains a task execution list.

4. The multi-sensor fusion agricultural precision irrigation system according to claim 3, characterized in that: The execution control module includes: The water quantity calculation submodule calls the leaf area index response coefficient, environmental evapotranspiration influencing factor and task execution list, evaluates the irrigation water demand of each irrigation area according to the area, leaf area, light intensity and temperature level of each irrigation area, and generates a regional irrigation water value; The water pressure extraction submodule calls the regional irrigation water volume value, collects the real-time water pressure monitoring data of each irrigation area in the water supply network, calculates the pressure difference data corresponding to each irrigation area in combination with the preset supply pressure standard value, and obtains the supply pressure offset amplitude value; The duration control submodule calls the supply pressure offset amplitude value, calculates the irrigation time required for each area, and adjusts the irrigation solenoid valve control parameters of each irrigation area to obtain the irrigation duration control parameters.

5. The multi-sensor fusion agricultural precision irrigation system according to claim 4, characterized in that: The system further comprises: Based on the irrigation duration control parameters, the feedback regulation module obtains the solenoid valve opening duration and water pressure fluctuation data of each irrigation area in each irrigation task, calculates the actual water supply completion status of each area, compares it with the target water supply plan, calculates the degree of deviation, configures the supplementary irrigation task, and generates a precise irrigation configuration task; The precision irrigation configuration task includes a water supply deviation ratio, a supplementary irrigation period, and a water replenishment target.

6. The multi-sensor fusion agricultural precision irrigation system according to claim 5, characterized in that: The feedback adjustment module includes: The water supply status extraction submodule calculates the actual water supply completion status of each task area based on the irrigation duration control parameter by collecting the solenoid valve opening duration and water pressure fluctuation data in each irrigation task, and obtains the actual water supply completion value; The execution deviation determination submodule calls the actual water supply completion value, combines the water volume value required by the task target, calculates the water supply deviation of each area, and generates a water supply execution deviation value; The supplementary irrigation configuration generation submodule calls the water supply execution deviation value, evaluates the water supply deviation level of multiple areas according to the water supply deviation, configures supplementary irrigation tasks, and generates precise irrigation configuration tasks.

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