CN109845625A - A kind of multidimensional parameter crops intelligent irrigation control method neural network based - Google Patents
A kind of multidimensional parameter crops intelligent irrigation control method neural network based Download PDFInfo
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Abstract
The invention discloses a kind of multidimensional parameter crops intelligent irrigation control methods neural network based, by the rainfall information for acquiring current irrigated farmland, information on soil moisture, wind speed information, temperature and humidity information, the parameters such as illumination intensity information and flow information, based on neural network using crops thirst signal as the crop water requirement model of response message, calculation processing is carried out to crops multi-dimensional environment parameter by the model, finally predict the water requirement of current farmland crops, controller passes through to water requirement, rainfall and soil moisture content make comprehensive court verdict and control solenoid valve according to court verdict, complete the Precision Irrigation to crops, whole process is without human intervention, work efficiency is high, and accuracy is high, water utilization rate can be improved, crop yield and IT application to agriculture degree, reduce crop production cost, Human cost, while there is active promoting function to the quality and yield for improving crops, there is apparent social benefit.
Description
Technical field
The present invention relates to crop irrigation technical field, in particular to a kind of multidimensional parameter crops neural network based
Intelligent irrigation control method.
Background technique
With the development of science and technology, agricultural production also promptly changes traditional tillage system reform, modern section
It learns and industrial technology gradually penetrates into agricultural production, agricultural technology gradually develops to scientific, information-based direction, modern
Industrialized agriculture is come into being, and becomes most active one of the industry in the world today.
And as technology develops, China also generally realizes automation plantation, however, the field irrigation for crops, I
Farmland is irrigated still in manual control by state, and working efficiency is low, and accuracy is low.
Summary of the invention
The invention mainly solves the technical problem of providing a kind of multidimensional parameter crops neural network based intelligently to fill
Control method is irrigate, can be controlled according to the growing environment parameter of crops and farmland is irrigated, work efficiency is high, and accuracy
It is high.
In order to solve the above technical problems, one technical scheme adopted by the invention is that: it provides a kind of neural network based
Multidimensional parameter crops intelligent irrigation control method, comprising: believed based on neural network with crops thirst signal for response
The crop water requirement model of breath；Believed using rainfall information, information on soil moisture, the wind speed that sensor acquires current irrigated farmland
Breath, the temperature and humidity information of surrounding air, current light strength information and irrigation conduit flow information；Controller utilizes wireless transmission
Mode obtains rainfall information, soil moisture information, wind speed information, temperature and humidity information, illumination intensity information and pipeline flow information；Control
Device calculates wind speed information, temperature and humidity information and intensity of illumination using crop water requirement model, predicts current farmland
The water requirement of crops；Controller is by making comprehensive court verdict to water requirement, rainfall and soil moisture content and according to judgement
As a result irrigation instruction, irrigation quantity are obtained and is poured water the duration；Controller will be irrigated to instruct to be sent to wireless transmission method and be set
Set the solenoid valve on the irrigation conduit of irrigated farmland；Solenoid valve instructs the conducting of control irrigation conduit according to irrigating, to pass through
Irrigation conduit conveys water corresponding with instruction is irrigated to field irrigation.
Wherein, wireless transmission method includes NBIOT transmission mode and LORA transmission mode.
Wherein, the step of acquiring the rainfall information of current irrigated farmland using sensor includes: to irrigate agriculture using setting
The rainfall information of the precipitation rain fall sensor acquisition irrigated farmland of preset distance within a predetermined period of time above field.
Wherein, it is arranged at intervals with multiple soil moisture content sensors in the soil of irrigated farmland, is acquired using sensor current
The step of information on soil moisture of irrigated farmland includes: to be worked as using the multiple soil moisture content sensors acquisition for being embedded in predetermined depth
The information on soil moisture of preceding irrigated farmland.
Wherein, the step of acquiring the wind speed information of current irrigated farmland using sensor includes: to irrigate agriculture using setting
The air velocity transducer of preset distance detects the wind speed information of current irrigated farmland above field.
Wherein, it is provided with Temperature Humidity Sensor above irrigated farmland, the temperature of current irrigated farmland is acquired using sensor
The step of humidity information includes: the temperature and humidity information that current irrigated farmland ambient enviroment is detected using Temperature Humidity Sensor.
Wherein, the step of acquiring the illumination intensity information of current irrigated farmland using sensor includes: to be filled using setting
The intensity of illumination sensor for irrigating preset distance above farmland detects the illumination intensity information of current irrigated farmland；Wherein utilize sensing
Device acquire the step of flow information of current irrigation conduit include: monitored using the pulse flowmeter that irrigation conduit is arranged in it is current
Irrigation conduit flow information.
Wherein, based on the neural network one crop water requirement prediction model with 3 layer network structures, and according to
Input of the wind speed, temperature and humidity, illumination intensity information of irrigated farmland actual measurement as crop water requirement prediction model, crops are real
Border water requirement ET can obtain according to formula (1),
ET=ET0*Kc (1)
Wherein, ET0For the crop reference evapotranspiration of model output, KcFor crop coefficient.
Wherein, the practical irrigation quantity M in period t is determined by water balance formula (2),
M=ET+ (Wt-W0)-P0-Wr-K (2)
Wherein: (Wt-W0) be the period at the beginning of and planned moist layer in soil inner storing water amount when any time t, Wr be that plan is wet
Layer increases and increased water, P0To be stored in the effective rainfall in planned moist layer in soil, K is that the underground water in period t is mended
To amount, ET is the practical water requirement of crops in period t；
Crop irrigation total amount T is obtained by formula (3),
T=M/Q (3)
Wherein: Q is the flow of irrigation conduit.
Wherein, the preset distance above irrigated farmland is provided with rectangular container by first support bar, receiving
Slot is equipped with delivery outlet, motor-driven valve connected to the controller is wherein provided in delivery outlet, the bottom of container is equipped with and controller
The height that the water of container is detected in container, this method is arranged in the pressure sensor of connection, precipitation rain fall sensor further include:
When pressure sensor has detected pressure, controller controls motor-driven valve closure；Controller judges that pressure sensor has detected pressure
Whether the time of power is greater than preset time；If it is, controller obtains the height that precipitation rain fall sensor detects the water of container
Value, and control motor-driven valve opening, and when re-executing pressure sensor and having detected pressure, controller controls motor-driven valve closure
Step；The top of the crops of irrigated farmland is provided with Temperature Humidity Sensor, second support bar interval pair by second support bar
Claim the first motor for being provided with the first screw rod and connecting with the first screw rod, be threaded with Temperature Humidity Sensor on the first screw rod,
The bottom of Temperature Humidity Sensor is equipped with range sensor, this method further include: range sensor judges Temperature Humidity Sensor and agriculture
Whether the distance of crop is in preset range；If not, controller control first motor rotation, to drive the first screw rod to turn
It is dynamic, to drive Temperature Humidity Sensor to go up and down along the first screw rod, so that Temperature Humidity Sensor is at a distance from crops in default
In range；Being horizontally disposed in the soil of irrigated farmland has the first slide bar, and multiple soil moisture content sensors are removably set on first
In slide bar.
The beneficial effects of the present invention are: be in contrast to the prior art, it is disclosed in this invention neural network based
Multidimensional parameter crops intelligent irrigation control method includes: based on neural network using crops thirst signal as response message
Crop water requirement model；Believed using rainfall information, information on soil moisture, the wind speed that sensor acquires current irrigated farmland
Breath, the temperature and humidity information of surrounding air, current light strength information and irrigation conduit flow information；Controller utilizes wireless transmission
Mode obtains rainfall information, soil moisture information, wind speed information, temperature and humidity information, illumination intensity information and pipeline flow information；Control
Device calculates wind speed information, temperature and humidity information and intensity of illumination using crop water requirement model, predicts current farmland
The water requirement of crops；Controller is by making comprehensive court verdict to water requirement, rainfall and soil moisture content and according to judgement
As a result irrigation instruction is obtained；Controller, which will irrigate to instruct, is sent to the irrigation conduit that irrigated farmland is arranged in wireless transmission method
On solenoid valve；Solenoid valve instructs the conducting of control irrigation conduit according to irrigating, and is instructed with being conveyed and being irrigated by irrigation conduit
Corresponding water is to field irrigation.By the above-mentioned means, the present invention can be controlled according to the growing environment parameter of crops to agriculture
Field is irrigated, and whole to can be realized farmland intelligent irrigation without human intervention, work efficiency is high, and accuracy is high.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of the multidimensional parameter crops intelligent irrigation control system the present invention is based on neural network；
Fig. 2 is the flow diagram of the multidimensional parameter crops intelligent irrigation control method the present invention is based on neural network；
Fig. 3 is the structural schematic diagram of neural network.
Specific embodiment
The present invention discloses a kind of multidimensional parameter crops intelligent irrigation control system neural network based, as shown in Figure 1,
The system includes the solenoid valve 11 being arranged on irrigation conduit, the controller 10 being wirelessly connected with solenoid valve 11 and controller 10
The precipitation rain fall sensor 101 of connection, the soil moisture content sensor 102 connecting with controller 10, the wind speed connecting with controller 10 pass
Sensor 103, the Temperature Humidity Sensor 104 being connect with controller 10, the intensity of illumination sensor 105 being connect with controller 10 and with
The pulse flowmeter 106 that controller 10 connects.
Solenoid valve 11 is used to control the on-off of irrigation conduit, i.e., when solenoid valve 11 is opened, irrigation conduit conducting, can be farmland
Duty, when solenoid valve 11 is closed, irrigation conduit disconnects conducting.Precipitation rain fall sensor 101 is used for rainfall information collection.Soil moisture in the soil
Feelings sensor 102 is for acquiring soil tilth information.Air velocity transducer 103 is for acquiring wind speed information.Temperature Humidity Sensor
104 for acquiring temperature and humidity information.Intensity of illumination sensor 105 is for acquiring illumination intensity information.Pulse flowmeter 106 is used for
Monitor current irrigation conduit flow information (i.e. flow information).Controller 10 irrigates instruction to solenoid valve 11 for sending, with
So that solenoid valve 11 is according to instruction unpack or closure is irrigated, wherein crop water requirement neural network based built in controller 10
Model, it should be appreciated that the structure of the crop water requirement model of neural network is as shown in Figure 3.
In the present embodiment, mould is predicted based on neural network one crop water requirement with 3 layer network structures
Type；By repeatedly train after, when crop water requirement prediction model hidden layer neuron node number be 4, model calculation effect
It is optimal；Mode input layer choosing takes 4 variables, i.e. wind speed, temperature, humidity, intensity of illumination, and crop water requirement is as prediction mould
Type output layer, therefore output layer number of nodes is set as 1.Input layer is exported to selection activation primitive tansig between hidden layer
Layer uses function purelin, using trainlm as training function；It is right by historical wind speed, temperature and humidity, intensity of illumination and institute
Crop reference evapotranspiration (the ET answered0) long sequence data is trained and verifies, it is final to determine crop water requirement prediction model.
In the present embodiment, water is needed as crops according to the wind speed of irrigated farmland actual measurement, temperature and humidity, illumination intensity information
The input of prediction model is measured, the practical water requirement ET of crops can be obtained according to formula (1),
ET=ET0*Kc (1)
Wherein, ET0For the crop reference evapotranspiration of model output, KcIt (can specifically be participated in traditional on the market for crop coefficient
FAO crop coefficient table checks in).
In the present embodiment, the practical irrigation quantity M in period t is determined by water balance formula (2),
M=ET+ (Wt-W0)-P0-Wr-K (2)
Wherein: (Wt-W0) be the period at the beginning of and planned moist layer in soil inner storing water amount when any time t, Wr be that plan is wet
Layer increases and increased water, P0To be stored in the effective rainfall in planned moist layer in soil, K is that the underground water in period t is mended
To amount, ET is the practical water requirement of crops in period t.
Further, the present embodiment also passes through formula (3) acquisition crop irrigation total amount T,
T=M/Q (3)
Wherein: Q is the flow of irrigation conduit.
In the present embodiment, solenoid valve 11 is connect using wireless transmission method with controller 10.Preferably, wireless transmission side
Formula includes NBIOT transmission mode and LORA transmission mode.Specifically, controller 10 is transmitted by NBIOT transmission mode or LORA
Mode is connect with solenoid valve 11.It should be understood that NBIOT transmission mode and LORA transmission mode are low power consumption transmission mode, so that control
Device 10 processed can keep working condition with solenoid valve 11 for a long time.
It should be understood that in the present embodiment, controller 10 by wire transmission mode respectively with precipitation rain fall sensor 101, soil
Soil moisture content sensor 102, air velocity transducer 103, Temperature Humidity Sensor 104, intensity of illumination sensor 105 and pulse flowmeter 106
Connection.
Certainly, in some embodiments, controller 10 by wireless transmission method respectively with precipitation rain fall sensor 101, soil
Soil moisture content sensor 102, air velocity transducer 103, Temperature Humidity Sensor 104, intensity of illumination sensor 105 and pulse flowmeter 106
Connection, specifically, device 10 processed by NBIOT transmission mode or LORA transmission mode respectively with precipitation rain fall sensor 101, soil moisture content
Sensor 102, air velocity transducer 103, Temperature Humidity Sensor 104, intensity of illumination sensor 105 and pulse flowmeter 106 connect.
It should be understood that controller 10 is connect by wireless transmission method with sensor, i.e., passed respectively in precipitation rain fall sensor 101, soil moisture content
Increase on sensor 102, air velocity transducer 103, Temperature Humidity Sensor 104, intensity of illumination sensor 105 and pulse flowmeter 106
NBIOT transmits mould group or LORA transmits mould group, so that precipitation rain fall sensor 101, soil moisture content sensor 102, air velocity transducer
103, Temperature Humidity Sensor 104, intensity of illumination sensor 105 and pulse flowmeter 106 are able to carry out wireless transmission, enable to
Sensor can be set in farmland any position and avoid the occurrence of what line mixed so that the distance and position of sensor is unrestricted
Phenomenon occurs.
As shown in Fig. 2, Fig. 2 is the stream of the multidimensional parameter crops intelligent irrigation control method the present invention is based on neural network
Journey schematic diagram.Method includes the following steps:
Step S101: based on neural network using crops thirst signal as the crop water requirement mould of response message
Type.It should be understood that the present embodiment passes through controller 10 based on neural network using crops thirst signal as the agriculture of response message
Water demand of crop model, i.e. controller 10 can detect crops thirst signal by crop water requirement model.
In the present embodiment, mould is predicted based on neural network one crop water requirement with 3 layer network structures
Type；By repeatedly train after, when crop water requirement prediction model hidden layer neuron node number be 4, model calculation effect
It is optimal；Mode input layer choosing takes 4 variables, i.e. wind speed, temperature, humidity, intensity of illumination, and crop water requirement is as prediction mould
Type output layer, therefore output layer number of nodes is set as 1.Input layer is exported to selection activation primitive tansig between hidden layer
Layer uses function purelin, using trainlm as training function.
Step S102: using sensor acquire the rainfall information of current irrigated farmland, information on soil moisture, wind speed information,
Temperature and humidity information, current light strength information and the irrigation conduit flow information of surrounding air.
In the present embodiment, the step of acquiring the rainfall information of current irrigated farmland using sensor includes: to utilize setting
The precipitation rain fall sensor 101 of preset distance acquires the rainfall information of irrigated farmland within a predetermined period of time above irrigated farmland.
It should be understood that in some embodiments, the preset distance above irrigated farmland is provided with by first support bar in square
The container of shape can accommodate rainwater by the container, and wherein container is equipped with delivery outlet, is accommodated with being exported by delivery outlet
Rainwater in slot, and motor-driven valve connected to the controller is provided in delivery outlet, to control the on-off of delivery outlet by motor-driven valve.
Further, the bottom of container is equipped with pressure sensor connected to the controller, to detect container by pressure sensor
In whether rain, i.e., when pressure sensor has detected pressure, illustrate rain in container.Precipitation rain fall sensor setting is being received
The height of the water of container is detected in tank.
In addition, this method further include:
Step a1: when pressure sensor has detected pressure, controller controls motor-driven valve closure.It should be understood that pressure sensing
When device has detected pressure, illustrate rain in container, then controller 10 controls motor-driven valve closure, prevents rainwater from container
Middle outflow.
Step a2: controller judges that pressure sensor detects whether the time of pressure is greater than preset time.It should be understood that
Preset time is the artificial time, and preset time can be 1 hour, and 10 hours, 24 hours or one month, the specific time was according to reality
Depending on border needs.
Step a3: if it is, controller obtains the height value that precipitation rain fall sensor detects the water of container, and electricity is controlled
The step of dynamic valve is opened, and when re-executing pressure sensor and having detected pressure, and controller controls motor-driven valve closure.Ying Li
Solution can be passed when controller determines that pressure sensor detects that the time of pressure is greater than preset time by rainfall at this time
Sensor detects rainfall information within a preset time, therefore gets the letter of rainfall detected by precipitation rain fall sensor in controller
When breath, controller controls motor-driven valve and opens, so that the rainwater in container is exported from delivery outlet.In addition, when in container
Rainwater streamer after, when re-executing pressure sensor and having detected pressure, the step of controller controls motor-driven valve closure, this
Sample can repeated detection to rainfall information within a preset time, have multiple numerical value, calculate average value, it is more accurate in this way.
In the present embodiment, multiple soil moisture content sensors 102 are arranged at intervals in the soil of irrigated farmland, wherein utilizing
It includes: using being embedded in multiple soil moisture in the soils of predetermined depth that sensor, which acquires the step of information on soil moisture of current irrigated farmland,
Feelings sensor 102 acquires the information on soil moisture of current irrigated farmland.It should be understood that the needs of soil moisture content sensor 102 are buried in
In soil, it could not be influenced in this way by the weeds on soil face.
In the present embodiment, the step of acquiring the wind speed information of current irrigated farmland using sensor includes: to utilize setting
The air velocity transducer 103 of preset distance detects the wind speed information of current irrigated farmland above irrigated farmland.
It should be understood that in order to complete detection soil tilth situation, in some embodiments, in the soil of irrigated farmland
Horizontally disposed to have the first slide bar, multiple soil moisture content sensors are removably set in the first slide bar, so that soil moisture content senses
The soil that device is capable of multiple positions to farmland comprehensively detects.
In the present embodiment, Temperature Humidity Sensor 104 is provided with above irrigated farmland, it is preferable that Temperature Humidity Sensor
The 20-50 centimeters of the top of 104 crops in irrigated farmland, in this way can be closer to the ambient enviroment of crops
The case where temperature and humidity.The step of temperature and humidity information of current irrigated farmland is wherein acquired using sensor includes: to utilize temperature and humidity
Sensor 105 detects the temperature and humidity information of current irrigated farmland ambient enviroment.
It should be understood that Temperature Humidity Sensor must be kept and farming since crops are as the time constantly grows
Object has a certain distance, therefore in some embodiments, and the top of the crops of irrigated farmland is arranged by second support bar
Have Temperature Humidity Sensor, second support bar is vertically inserted on farmland, second support bar interval be symmetrically arranged with the first screw rod and
The first motor connecting with the first screw rod is threaded with Temperature Humidity Sensor, the bottom of Temperature Humidity Sensor on the first screw rod
Equipped with range sensor, it should be appreciated that Temperature Humidity Sensor is equipped with first through hole and the first threaded hole, and second support bar is threaded through the
In one through-hole, the first screw rod is threadedly coupled with the first threaded hole.
In addition, this method further include:
Step b1: range sensor judges whether Temperature Humidity Sensor is in preset range at a distance from crops.It answers
Understand, since crop growth speed is slow, range sensor interval send infrared detection Temperature Humidity Sensor with
The distance of crops, as send within range sensor 12 hours or 24 hours infrared detection Temperature Humidity Sensors and crops away from
From.
Step b1: if not, controller control first motor rotation, to drive the rotation of the first screw rod, to drive warm and humid
Degree sensor is gone up and down along the first screw rod, so that Temperature Humidity Sensor is at a distance from crops in preset range.It should be understood that working as
Range sensor determines that controller receives this letter when being not in preset range at a distance from Temperature Humidity Sensor and crops
After breath, controller controls first motor rotation, to drive Temperature Humidity Sensor to rise.
In the present embodiment, the step of acquiring the illumination intensity information of current irrigated farmland using sensor includes: to utilize
The intensity of illumination sensor 105 that preset distance above irrigated farmland is arranged in detects the illumination intensity information of current irrigated farmland.
In the present embodiment, the step of acquiring the flow information of current irrigation conduit using sensor includes: to utilize setting
Current irrigation conduit flow information is monitored in the pulse flowmeter 106 of irrigation conduit.I.e. pulse flowmeter 106 can be with real-time statistics
Flow information in irrigation conduit.
Step S103: controller 10 obtains rainfall information, soil moisture information, wind speed information, warm and humid using wireless transmission method
Spend information, illumination intensity information and pipeline flow information.
In step s 103, controller 10 in real time with precipitation rain fall sensor 101, soil moisture content sensor 102, air velocity transducer
103, Temperature Humidity Sensor 104, intensity of illumination sensor 105 and pulse flowmeter 106 connect, and in real time from precipitation rain fall sensor
101, soil moisture content sensor 102, air velocity transducer 103, Temperature Humidity Sensor 104,105 pulse flow of intensity of illumination sensor
Rainfall information, soil moisture information, wind speed information, temperature and humidity information, illumination intensity information and pipeline flow information are obtained in meter 106.
Step S104: controller using crop water requirement model to wind speed information, temperature and humidity information and intensity of illumination into
Row calculates, and predicts the water requirement of current farmland crops.
In step S104, controller 10 get rainfall information, soil moisture information, wind speed information, temperature and humidity information and
After intensity of illumination, controller 10 is strong to wind speed information, temperature and humidity information and illumination using the crop water requirement model in S101
Degree is calculated, to predict the water requirement of current farmland crops.Specifically, in conjunction with Fig. 3, neural network gets wind speed letter
After ceasing X1, humidity information X2, temperature information X3 and intensity of illumination X4, corresponding crop water requirement ET is counted.
Step S105: controller is by making comprehensive court verdict and root to water requirement ET, rainfall P and soil moisture content W
Irrigation instruction, irrigation quantity are obtained according to court verdict and are poured water the duration.
In step s105, after controller 10 gets crop water requirement ET, rainfall P, controller is according to farmland water
It measures equilibrium principle and calculates practical irrigation quantity M.
Specifically, controller is surveyed according to irrigated farmland wind speed, temperature and humidity, illumination intensity information need water as crops
The input of prediction model is measured, and obtains the practical water requirement ET of crops using formula (1),
ET=ET0*Kc (1)
Secondly, controller determines the practical irrigation quantity M in period t by water balance formula (2),
M=ET+ (Wt-W0)-P0-Wr-K (2)
Finally, controller obtains crop irrigation total amount T by formula (3),
T=M/Q (3)
It should be understood that the crop irrigation total amount T of the present embodiment is the actual amount of water finally irrigated.
In step s105, controller 10 presets soil moisture content threshold value W0 (W0 is to adjust the coefficient that withers) and is used as judgment condition,
After the acquisition of controller 10 soil moisture content W compared with soil moisture content threshold value W0, if W < WO, i.e. controller need to issue irrigation instruction.
Step S106: controller 10, which will irrigate to instruct, is sent to the irrigation pipe that irrigated farmland is arranged in wireless transmission method
Solenoid valve 11 on road.
It is being filled it should be understood that controller 10 will irrigate to instruct to be sent to be arranged with NBIOT transmission mode or LORA transmission mode
Irrigate the solenoid valve 11 on the irrigation conduit in farmland.
Step S107: solenoid valve 11 is according to the conducting for irrigating instruction control irrigation conduit, with defeated by irrigation conduit
Send water corresponding with instruction is irrigated to field irrigation.
In step s 107, when solenoid valve 11 receives irrigation instruction, solenoid valve 11 is opened, and irrigation conduit is connected at this time,
Irrigation conduit can transport water and be irrigated with realizing at this time.
In the present embodiment, when pulse flowmeter 106 detects that the water for flowing through irrigation conduit reaches water requirement, feedback letter
It ceases to controller 10, controller 10 sends halt instruction to solenoid valve 11 after receiving feedback information, and solenoid valve 11, which receives, to stop
When only instructing, solenoid valve 11 is closed, and completes the Precision Irrigation to crops.
It should be understood that when controller 10 detect irrigation conduit conveying water duration of pouring water reach predetermined value when, control
Device 10 sends halt instruction to solenoid valve 11, and when solenoid valve 11 receives halt instruction, solenoid valve 11 is closed, and completes to crops
Precision Irrigation.
It should be understood that the growth parameter of the present embodiment multidimensional crops, can be according to rainfall information, soil moisture content as references object
Information, wind speed information, temperature and humidity information, illumination intensity information and pipeline flow information make decisions judgement, convey agriculture for farmland
The water that crop needs, reaches intelligent irrigation control.
To sum up, multidimensional parameter crops intelligent irrigation control method neural network based disclosed in this invention, passes through
Acquire rainfall information, information on soil moisture, wind speed information, temperature and humidity information, illumination intensity information and the stream of current irrigated farmland
The parameters such as information are measured, based on neural network using crops thirst signal as the crop water requirement model of response message, are led to
It crosses the model and calculation processing is carried out to crops multi-dimensional environment parameter, finally predict the water requirement of current farmland crops, control
Device processed by making comprehensive court verdict to water requirement, rainfall and soil moisture content and controls solenoid valve according to court verdict, complete
The Precision Irrigation of pairs of crops, whole work efficiency is high without human intervention, and accuracy is high, and water resource benefit can be improved
With rate, crop yield and IT application to agriculture degree, crop production cost, human cost are reduced, while to raising crops
Quality and yield has active promoting function, has apparent social benefit.
The above description is only an embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of multidimensional parameter crops intelligent irrigation control method neural network based characterized by comprising
Based on neural network using crops thirst signal as the crop water requirement model of response message；
Using sensor acquire the rainfall information of current irrigated farmland, information on soil moisture, wind speed information, surrounding air it is warm and humid
Spend information, current light strength information and irrigation conduit flow information；
Controller obtains rainfall information, soil moisture information, wind speed information, temperature and humidity information, intensity of illumination using wireless transmission method
Information and pipeline flow information；
Controller calculates wind speed information, temperature and humidity information and intensity of illumination using crop water requirement model, predicts
The water requirement of current farmland crops；
Controller by making comprehensive court verdict to water requirement, rainfall and soil moisture content and obtains irrigation according to court verdict
Instruction and is poured water the duration at irrigation quantity；
Controller will irrigate the solenoid valve for instructing and being sent on the irrigation conduit that irrigated farmland is arranged in wireless transmission method；
Solenoid valve is according to the conducting for irrigating instruction control irrigation conduit, with corresponding with instruction is irrigated by irrigation conduit conveying
Water to field irrigation.
2. the method according to claim 1, wherein the wireless transmission method include NBIOT transmission mode and
LORA transmission mode.
3. the method according to claim 1, wherein the rainfall for acquiring current irrigated farmland using sensor
The step of information includes:
The rain of irrigated farmland within a predetermined period of time is acquired using the precipitation rain fall sensor that preset distance above irrigated farmland is arranged in
Measure information.
4. the method according to claim 1, wherein being arranged at intervals with multiple soil moisture in the soils in the soil of irrigated farmland
The step of feelings sensor, the information on soil moisture that current irrigated farmland is acquired using sensor includes:
The information on soil moisture of current irrigated farmland is acquired using the multiple soil moisture content sensors for being embedded in predetermined depth.
5. the method according to claim 1, wherein the wind speed for acquiring current irrigated farmland using sensor
The step of information includes:
The wind speed information of current irrigated farmland is detected using the air velocity transducer that preset distance above irrigated farmland is arranged in.
6. the method according to claim 1, wherein be provided with Temperature Humidity Sensor above irrigated farmland, institute
The step of stating the temperature and humidity information that current irrigated farmland is acquired using sensor include:
The temperature and humidity information of current irrigated farmland ambient enviroment is detected using Temperature Humidity Sensor.
7. the method according to claim 1, wherein the illumination for acquiring current irrigated farmland using sensor
The step of strength information includes:
The intensity of illumination of current irrigated farmland is detected using the intensity of illumination sensor that preset distance above irrigated farmland is arranged in
Information；
Wherein the step of flow information that current irrigation conduit is acquired using sensor includes:
Current irrigation conduit flow information is monitored using the pulse flowmeter that irrigation conduit is arranged in.
8. the method according to claim 1, wherein there are 3 layer network structures based on neural network one
Crop water requirement prediction model, and according to the wind speed of irrigated farmland actual measurement, temperature and humidity, illumination intensity information is as crops
The input of Water Demand Prediction model, the practical water requirement ET of crops can obtain according to formula (1),
ET=ET0*Kc (1)
Wherein, ET0For the crop reference evapotranspiration of model output, KcFor crop coefficient.
9. according to the method described in claim 8, it is characterized in that, determining the reality in period t by water balance formula (2)
Irrigation quantity M,
M=ET+ (Wt-W0)-P0-Wr-K (2)
Wherein: (Wt-W0) be the period at the beginning of and planned moist layer in soil inner storing water amount when any time t, Wr be that irrigation wetting depth increases
Add and increased water, P0To be stored in the effective rainfall in planned moist layer in soil, K is the increment of groundwater in period t,
ET is the practical water requirement of crops in period t；
Crop irrigation total amount T is obtained by formula (3),
T=M/Q (3)
Wherein: Q is the flow of irrigation conduit.
10. according to the method described in claim 3, it is characterized in that, the preset distance above irrigated farmland passes through the first support
Bar is provided with rectangular container, and container is equipped with delivery outlet, electricity connected to the controller is wherein provided in delivery outlet
Dynamic valve, the bottom of container are equipped with pressure sensor connected to the controller, and precipitation rain fall sensor is arranged in container with detection
The height of the water of container, this method further include:
When pressure sensor has detected pressure, controller controls motor-driven valve closure；
Controller judges that pressure sensor detects whether the time of pressure is greater than preset time；
If it is, controller obtains the height value that precipitation rain fall sensor detects the water of container, and controls motor-driven valve opening, and
When re-executing pressure sensor and having detected pressure, the step of controller controls motor-driven valve closure；
Wherein, the top of the crops of irrigated farmland is provided with Temperature Humidity Sensor by second support bar, between second support bar
Every being threaded with temperature and humidity sensing in the first motor for being symmetrically arranged with the first screw rod and connecting with the first screw rod, the first screw rod
The bottom of device, Temperature Humidity Sensor is equipped with range sensor, this method further include:
Range sensor judges whether Temperature Humidity Sensor is in preset range at a distance from crops；
If not, controller control first motor rotation, to drive the rotation of the first screw rod, to drive Temperature Humidity Sensor along the
One screw rod lifting, so that Temperature Humidity Sensor is at a distance from crops in preset range；
Wherein, being horizontally disposed in the soil of irrigated farmland has the first slide bar, and multiple soil moisture content sensors are removably set on the
In one slide bar.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109588289A (en) * | 2019-01-18 | 2019-04-09 | 闫家珲 | Able to resisting flood and drought management method and device based on crops soil moisture content |
| CN110332957A (en) * | 2019-07-12 | 2019-10-15 | 仲恺农业工程学院 | Crop cultivation information processing system and method |
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102779391A (en) * | 2012-07-24 | 2012-11-14 | 中国农业科学院农田灌溉研究所 | Drought early-warning method and drought early-warning system |
| CN104904569A (en) * | 2015-05-25 | 2015-09-16 | 华南农业大学 | Intelligent irrigation regulation and control system and method based on dynamic water content estimation |
| CN204762533U (en) * | 2015-08-05 | 2015-11-18 | 将乐桃花源记农业发展有限公司 | Over -and -under type humidity control device for green house |
| CN106595754A (en) * | 2016-10-26 | 2017-04-26 | 天津理工大学 | Height self-regulating temperature and humidity monitoring device |
| CN107087539A (en) * | 2017-05-27 | 2017-08-25 | 苟瀚文 | A kind of fruits and vegetables Intelligent irrigation system based on Internet of Things |
| CN107258494A (en) * | 2017-07-06 | 2017-10-20 | 郑州大学 | A kind of intelligent precisely mixing system of vegetation ecological high-efficient water use |
| CN108279042A (en) * | 2018-03-20 | 2018-07-13 | 陈红燕 | A kind of environmental detection set |
-
2018
- 2018-12-12 CN CN201811521571.4A patent/CN109845625A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102779391A (en) * | 2012-07-24 | 2012-11-14 | 中国农业科学院农田灌溉研究所 | Drought early-warning method and drought early-warning system |
| CN104904569A (en) * | 2015-05-25 | 2015-09-16 | 华南农业大学 | Intelligent irrigation regulation and control system and method based on dynamic water content estimation |
| CN204762533U (en) * | 2015-08-05 | 2015-11-18 | 将乐桃花源记农业发展有限公司 | Over -and -under type humidity control device for green house |
| CN106595754A (en) * | 2016-10-26 | 2017-04-26 | 天津理工大学 | Height self-regulating temperature and humidity monitoring device |
| CN107087539A (en) * | 2017-05-27 | 2017-08-25 | 苟瀚文 | A kind of fruits and vegetables Intelligent irrigation system based on Internet of Things |
| CN107258494A (en) * | 2017-07-06 | 2017-10-20 | 郑州大学 | A kind of intelligent precisely mixing system of vegetation ecological high-efficient water use |
| CN108279042A (en) * | 2018-03-20 | 2018-07-13 | 陈红燕 | A kind of environmental detection set |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109588289A (en) * | 2019-01-18 | 2019-04-09 | 闫家珲 | Able to resisting flood and drought management method and device based on crops soil moisture content |
| CN109588289B (en) * | 2019-01-18 | 2021-07-02 | 闫家珲 | Flood-control drought-resisting management method and device based on crop soil moisture content |
| CN110332957A (en) * | 2019-07-12 | 2019-10-15 | 仲恺农业工程学院 | Crop cultivation information processing system and method |
| CN111011176A (en) * | 2019-11-01 | 2020-04-17 | 凯通科技股份有限公司 | High-efficient water conservation intelligence irrigation system |
| CN110839519A (en) * | 2019-12-02 | 2020-02-28 | 成都信息工程大学 | Internet of things intelligent agricultural irrigation device and method based on deep learning |
| CN111492959A (en) * | 2020-06-02 | 2020-08-07 | 山东贵合信息科技有限公司 | Irrigation method and equipment based on Internet of things |
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| CN111656940A (en) * | 2020-07-10 | 2020-09-15 | 张艳霞 | Control method for water conservancy irrigation |
| IT202100004280A1 (en) * | 2021-02-24 | 2022-08-24 | Bluetentacles S R L | INTELLIGENT IRRIGATION SYSTEM |
| CN113557890B (en) * | 2021-06-01 | 2022-01-28 | 中国农业科学院蔬菜花卉研究所 | Intelligent water precise irrigation control system and method for fruit and vegetable cultivation in sunlight greenhouse |
| CN113557890A (en) * | 2021-06-01 | 2021-10-29 | 中国农业科学院蔬菜花卉研究所 | Intelligent water precise irrigation control system and method for fruit and vegetable cultivation in sunlight greenhouse |
| CN113141940A (en) * | 2021-06-01 | 2021-07-23 | 中国农业科学院蔬菜花卉研究所 | Intelligent water precise irrigation control system and method for fruit and vegetable cultivation in sunlight greenhouse |
| WO2022253057A1 (en) * | 2021-06-01 | 2022-12-08 | 中国农业科学院蔬菜花卉研究所 | Intelligent moisture precise irrigation control system and method for fruit and vegetable cultivation in solar greenhouse |
| CN113229123A (en) * | 2021-06-02 | 2021-08-10 | 湖北工程学院 | Intelligent irrigation method, device and equipment for crops and storage medium |
| CN113848782A (en) * | 2021-09-24 | 2021-12-28 | 塔里木大学 | Farmland environment monitoring and automatic irrigation system |
| CN113875562A (en) * | 2021-10-29 | 2022-01-04 | 山东润浩水利科技有限公司 | Multi-user prepayment farmland intelligent irrigation and fertilization automation equipment and method |
| CN114451257A (en) * | 2021-12-23 | 2022-05-10 | 珠海格力电器股份有限公司 | Irrigation method and device based on neural network, storage medium and electronic equipment |
| CN115633622A (en) * | 2022-06-06 | 2023-01-24 | 华南农业大学 | Intelligent orchard irrigation system and method |
| CN116784217A (en) * | 2023-06-15 | 2023-09-22 | 四川省农业机械科学研究院 | Intelligent agricultural irrigation system based on wind energy, solar energy and soil humidity |
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Application publication date: 20190607 |