CN113467529A - Greenhouse ozone accurate control method and device based on multi-model fusion - Google Patents
Greenhouse ozone accurate control method and device based on multi-model fusion Download PDFInfo
- Publication number
- CN113467529A CN113467529A CN202110571199.3A CN202110571199A CN113467529A CN 113467529 A CN113467529 A CN 113467529A CN 202110571199 A CN202110571199 A CN 202110571199A CN 113467529 A CN113467529 A CN 113467529A
- Authority
- CN
- China
- Prior art keywords
- ozone
- concentration
- model
- greenhouse
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 title claims abstract description 401
- 238000000034 method Methods 0.000 title claims abstract description 71
- 230000004927 fusion Effects 0.000 title claims abstract description 46
- 230000007613 environmental effect Effects 0.000 claims abstract description 26
- 238000004590 computer program Methods 0.000 claims description 11
- 238000012544 monitoring process Methods 0.000 claims description 9
- 238000001514 detection method Methods 0.000 claims description 8
- 238000003860 storage Methods 0.000 claims description 8
- 238000012360 testing method Methods 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 abstract description 9
- 201000010099 disease Diseases 0.000 abstract description 8
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 abstract description 8
- 230000002265 prevention Effects 0.000 abstract description 7
- 230000000694 effects Effects 0.000 abstract description 6
- 244000052616 bacterial pathogen Species 0.000 abstract description 5
- 235000013311 vegetables Nutrition 0.000 abstract description 5
- 238000010586 diagram Methods 0.000 description 6
- 238000004891 communication Methods 0.000 description 5
- 230000001276 controlling effect Effects 0.000 description 4
- 238000009792 diffusion process Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 230000001105 regulatory effect Effects 0.000 description 3
- 238000000354 decomposition reaction Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000012271 agricultural production Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001954 sterilising effect Effects 0.000 description 1
- 238000004659 sterilization and disinfection Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000017260 vegetative to reproductive phase transition of meristem Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D11/00—Control of flow ratio
- G05D11/02—Controlling ratio of two or more flows of fluid or fluent material
- G05D11/13—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means
- G05D11/139—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by measuring a value related to the quantity of the individual components and sensing at least one property of the mixture
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G9/00—Cultivation in receptacles, forcing-frames or greenhouses; Edging for beds, lawn or the like
- A01G9/18—Greenhouses for treating plants with carbon dioxide or the like
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Pure & Applied Mathematics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Mathematical Physics (AREA)
- Computational Mathematics (AREA)
- Geometry (AREA)
- Computer Hardware Design (AREA)
- Operations Research (AREA)
- Probability & Statistics with Applications (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Algebra (AREA)
- Artificial Intelligence (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Automation & Control Theory (AREA)
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Environmental Sciences (AREA)
- Greenhouses (AREA)
Abstract
The invention provides a greenhouse ozone accurate control method and device based on multi-model fusion, and the method comprises the following steps: determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model; determining initial ozone release concentration and duration which can meet a standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration; according to the collected current actual concentration, based on a preset ozone prediction model, ozone concentration predicted values in different growth periods are obtained, and according to the ozone concentration predicted values and standard values obtained by an ozone calibration model, ozone release is adjusted so that the predicted values can reach the standard values. The method realizes dynamic and accurate control of ozone concentration, and achieves the effect of killing germs without damaging crops. On the basis of the multifunctional plant protection machine, technical support is provided for large-scale application of an ozone technology in prevention and treatment of diseases of protected vegetables, and the method has very important practical significance for improving safety of agricultural products.
Description
Technical Field
The invention relates to the technical field of agricultural production, in particular to a greenhouse ozone accurate control method and device based on multi-model fusion.
Background
Because the diffusion rule of ozone, the distribution of ozone in facility space, the tolerance rule of crops to ozone and the like under different environmental conditions are not clear, the potential of ozone for preventing and treating diseases cannot be fully exerted compared with the sterilization effect of laboratory small spaces. The method comprehensively considers a plurality of factors influencing the ozone concentration, realizes the effect of killing germs without damaging crops only by dynamically and accurately controlling the ozone concentration, and further promotes the popularization and the promotion of the green prevention and control technology in facility agriculture.
How to realize accurate control of greenhouse ozone provides theoretical basis and technical support for large-scale application of an ozone technology in prevention and treatment of diseases of greenhouse vegetables, has very important practical significance for improving safety of agricultural products, and is a problem to be solved urgently at present.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a greenhouse ozone accurate control method and device based on multi-model fusion.
The invention provides a greenhouse ozone accurate control method based on multi-model fusion, which comprises the following steps: determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model; determining initial ozone release concentration and duration which can meet the standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration; according to the collected current actual concentration, based on a preset ozone prediction model, obtaining ozone concentration prediction values of different growth periods, and according to the ozone concentration prediction values and a standard value obtained by the ozone calibration model, adjusting ozone release so that the prediction values reach the standard value; wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
According to the greenhouse ozone accurate control method based on multi-model fusion, provided by the embodiment of the invention, before the ozone concentration standard value is determined according to the current growth period and a preset ozone calibration model, the method further comprises the following steps: setting the ozone release duration by using different growth periods of crops as test periods and adopting a time schedule controller, and detecting the ozone release concentration; according to the change of the physiological index values of the crops before and after the ozone treatment, the standard values and the time lengths of the ozone release concentrations in different growth periods are determined, and an ozone concentration calibration model of the ozone concentration standard values in the whole growth period of the crops is established.
According to the greenhouse ozone accurate control method based on multi-model fusion, provided by the embodiment of the invention, before the ozone concentration standard value is determined according to the current growth period and a preset ozone calibration model, the method further comprises the following steps: detecting the actual ozone concentration collected by the ozone sensor under the conditions of different environmental parameters, ozone release concentrations and release time in different growth periods, and constructing a multi-factor ozone dissipation model by adopting a multiple regression method.
According to the greenhouse ozone accurate control method based on multi-model fusion, provided by the embodiment of the invention, before the ozone concentration standard value is determined according to the current growth period and a preset ozone calibration model, the method further comprises the following steps: taking actual ozone concentrations acquired by a plurality of ozone sensors under the current environment as initial conditions, and continuously monitoring to obtain changed ozone concentration values acquired by the ozone sensors at different times; and fitting to obtain ozone prediction models at different positions and at different times according to the initial conditions and the changed ozone concentration value. Wherein the plurality of ozone sensors are disposed at different locations of the greenhouse.
According to the greenhouse ozone accurate control method based on multi-model fusion, which is disclosed by the embodiment of the invention, the continuously monitoring and obtaining the changed ozone concentration values acquired by the ozone sensors at different times comprises the following steps: setting a fan and setting corresponding fan parameters, and continuously monitoring changed ozone concentration values acquired by ozone sensors at different time under the operation of the fan parameters; correspondingly, according to the initial condition and the changed ozone concentration value, fitting to obtain ozone prediction models at different positions and at different times, specifically: and fitting to obtain ozone prediction models at different positions, different times and different fan parameters according to the initial conditions, the fan parameters and the changed ozone concentration value.
According to the greenhouse ozone accurate control method based on multi-model fusion, which is disclosed by the embodiment of the invention, the method for obtaining the ozone concentration predicted values in different growth periods based on the preset ozone prediction model according to the collected current actual concentration comprises the following steps: and obtaining ozone concentration predicted values in different growth periods based on a preset ozone prediction model according to the acquired current actual concentration and current fan parameters.
According to the greenhouse ozone accurate control method based on multi-model fusion, provided by the embodiment of the invention, the growing period is obtained by dividing each growing period of crops according to the preset time length.
The invention also provides a greenhouse ozone accurate control device based on multi-model fusion, which comprises: the ozone calibration module is used for determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model; the ozone initial adjustment module is used for determining initial ozone release concentration and duration which can meet the standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration; the ozone fine adjustment module is used for obtaining ozone concentration predicted values in different growth periods based on a preset ozone prediction model according to the collected current actual concentration, and adjusting ozone release according to the ozone concentration predicted values and a standard value obtained by the ozone calibration model so as to enable the predicted values to reach the standard value; wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
The invention also provides electronic equipment which comprises a memory, a processor and a computer program which is stored on the memory and can be run on the processor, wherein the processor executes the program to realize the steps of any one of the above greenhouse ozone accurate control method based on multi-model fusion.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the steps of the multi-model fusion-based greenhouse ozone precise control method as described in any of the above.
The greenhouse ozone accurate control method and device based on multi-model fusion comprehensively consider a plurality of factors influencing the ozone concentration, realize dynamic and accurate control on the ozone concentration, achieve the effect of killing germs without damaging crops, and further promote the popularization and the promotion of a green control technology in facility agriculture. On the basis of the multifunctional plant protection machine, technical support is provided for large-scale application of an ozone technology in prevention and treatment of diseases of protected vegetables, and the method has very important practical significance for improving safety of agricultural products.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a greenhouse ozone precise control method based on multi-model fusion according to the present invention;
FIG. 2 is a second schematic flowchart of the precise control method for ozone in a greenhouse based on multi-model fusion according to the present invention;
FIG. 3 is a schematic structural diagram of a greenhouse ozone precision system based on multi-model fusion provided by the invention;
FIG. 4 is a schematic structural diagram of a greenhouse ozone precision control device based on multi-model fusion, provided by the invention;
fig. 5 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The following describes the greenhouse ozone accurate control method and device based on multi-model fusion in combination with fig. 1-5. Fig. 1 is a schematic flow chart of a precise control method for greenhouse ozone based on multi-model fusion, and as shown in fig. 1, the precise control method for greenhouse ozone based on multi-model fusion includes:
101. and determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model.
The ozone calibration model is determined according to different growth periods of different crops, is obtained by fitting a theoretical model and a large amount of experimental data, and is used for determining reasonable concentration and duration of ozone release in different growth and growth periods.
102. And determining the initial ozone release concentration and duration which can meet the standard value according to the current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration.
The ozone dissipation model is a model constructed through analysis of experimental data of a large number of different environments. And fusing the ozone calibration model and the ozone dissipation model corresponding to each growth period of the crops to preliminarily obtain the ozone release range of the equipment suitable for the growth period of the crops, and guiding the multifunctional plant protection machine to release the ozone. The environmental parameters may include temperature and humidity, among other parameters. Considering the decomposition process of ozone, the ozone dissipation model is a model for predicting the concentration which can be reached after ozone is released according to the initial ozone release concentration and the current environmental parameters.
103. According to the collected current actual concentration, based on a preset ozone prediction model, ozone concentration prediction values in different growth periods are obtained, and according to the ozone concentration prediction values and a standard value obtained by the ozone calibration model, ozone release is adjusted so that the prediction values reach the standard value.
The ozone prediction model can carry out ozone diffusion in the greenhouse by setting the operating parameters of the fan, analyze a large amount of test data of the ozone concentration distribution in the greenhouse, and construct the greenhouse ozone concentration prediction model of the multifunctional plant protection machine under the condition of setting the ozone release by adopting an optimization method. The ozone calibration model and the ozone prediction model corresponding to each growth period of the crops are fused, the prediction value of the prediction model and the specific crop tolerance value of the calibration model are automatically compared, and the accurate concentration suitable for the crops is further regulated and controlled, so that the multifunctional plant protection machine intelligently regulates and controls the release of ozone to achieve the reasonable concentration required by the crops.
The greenhouse ozone accurate control method based on multi-model fusion comprehensively considers a plurality of factors influencing the ozone concentration, realizes dynamic and accurate control on the ozone concentration, achieves the effect of killing germs without damaging crops, and further promotes the popularization and the popularization of a green prevention and control technology in facility agriculture. On the basis of the multifunctional plant protection machine, technical support is provided for large-scale application of an ozone technology in prevention and treatment of diseases of protected vegetables, and the method has very important practical significance for improving safety of agricultural products.
In one embodiment, before determining the standard value of the ozone concentration according to the current growth period and a preset ozone calibration model, the method further includes: setting the ozone release duration by using different growth periods of crops as test periods and adopting a time schedule controller, and detecting the ozone release concentration; according to the change of the physiological index values of the crops before and after the ozone treatment, the standard values and the time lengths of the ozone release concentrations in different growth periods are determined, and an ozone concentration calibration model of the ozone concentration standard values in the whole growth period of the crops is established.
Firstly, an ozone concentration calibration model of the whole growth period of crops is established. Optionally, the growing period is each growing period of the crop and is obtained by dividing according to a preset time length. For example, the ozone calibration model can set growth periods such as seedling period, flowering period and fruit period of various crops as a test period, 5 days (preset time) of each period is a growth period, a time schedule controller is adopted to set ozone release time, physiological indexes before and after ozone treatment are measured, the change rate of various physiological and ecological indexes before and after ozone release is calculated, the change rate is compared with a contrast, and reasonable concentration and time of ozone release are determined.
In one embodiment, before determining the standard value of the ozone concentration according to the current growth period and a preset ozone calibration model, the method further includes: detecting the actual ozone concentration collected by the ozone sensor under the conditions of different environmental parameters, ozone release concentrations and release time in different growth periods, and constructing a multi-factor ozone dissipation model by adopting a multiple regression method.
In the process of establishing the ozone dissipation model, 5 days can be set as a period in different growth periods of crops, the wireless ozone sensor automatically monitors the ozone concentration under the environmental condition combination by setting different ozone concentrations and release time, the decomposition rate of ozone under different environmental factors is analyzed, and the whole process from release to dissipation of ozone in the greenhouse is monitored. The ozone dissipation model can be obtained by analyzing a large amount of experimental data of different environments and constructing by adopting a multiple regression method.
In one embodiment, before determining the standard value of the ozone concentration according to the current growth period and a preset ozone calibration model, the method further includes: taking actual ozone concentrations acquired by a plurality of ozone sensors under the current environment as initial conditions, and continuously monitoring to obtain changed ozone concentration values acquired by the ozone sensors at different times; and fitting to obtain ozone prediction models at different positions and at different times according to the initial conditions and the changed ozone concentration value. Wherein the plurality of ozone sensors are disposed at different locations of the greenhouse.
And constructing a greenhouse ozone concentration prediction model of the multifunctional plant protection machine under the set ozone release condition by adopting an optimization method. Through the fusion of the ozone calibration model and the ozone prediction model corresponding to each growth period of crops, the prediction value of the prediction model and the specific crop tolerance value of the calibration model are automatically compared, and the accurate concentration suitable for the crops is further regulated and controlled, so that the multifunctional plant protection machine intelligently regulates and controls the release of ozone to achieve the reasonable concentration required by the crops.
In one embodiment, the continuously monitoring results in varying ozone concentration values collected by ozone sensors at different times, including: setting a fan and setting corresponding fan parameters, and continuously monitoring changed ozone concentration values acquired by ozone sensors at different time under the operation of the fan parameters; correspondingly, according to the initial condition and the changed ozone concentration value, fitting to obtain ozone prediction models at different positions and at different times, specifically: and fitting to obtain ozone prediction models at different positions, different times and different fan parameters according to the initial conditions, the fan parameters and the changed ozone concentration value.
Specifically, the ozone prediction model can perform ozone diffusion in the greenhouse by setting the operating parameters of the fan, and analyze a large amount of test data of the concentration distribution of ozone in the greenhouse. Correspondingly, the ozone prediction model also determines an ozone concentration prediction value according to the ozone concentration value and the fan parameter. After the predicted value is obtained, the ozone release concentration is adjusted to reach the standard value.
In one embodiment, the obtaining of the predicted ozone concentration values in different growth periods based on a preset ozone prediction model according to the collected current actual concentration includes: and obtaining ozone concentration predicted values in different growth periods based on a preset ozone prediction model according to the acquired current actual concentration and current fan parameters. Under the condition of setting the fan, specifically, the ozone concentration is predicted according to the collected current actual concentration and fan parameters.
Fig. 2 is a second schematic flow chart of the greenhouse ozone precise control method based on multi-model fusion, as shown in fig. 2, including an ozone calibration model, an ozone dissipation model and an ozone prediction model, wherein three basic models are serially fused, connected in series, and advanced layer by layer. And preliminarily obtaining a proper ozone release range through the fusion of the ozone calibration model and the dissipation model, further fusing the ozone prediction model to regulate and control to the proper accurate concentration of crops, and intelligently regulating and controlling the ozone release.
Fig. 3 is a schematic structural diagram of a greenhouse ozone accurate system based on multi-model fusion, as shown in fig. 3, the system comprises a multifunctional plant protection machine main controller, an ozone generator, a fan, a greenhouse environment parameter collector and an ozone concentration sensor, the intelligent level of the multifunctional plant protection machine is improved, accurate regulation and control of ozone release are realized, and diseases are effectively prevented and treated.
Specifically, the method is realized by the multifunctional plant protection main controller, the greenhouse environment parameter collector and the ozone concentration sensor realize the collection of greenhouse environment parameters and ozone concentration, reference is provided for the multifunctional plant protection main controller to control the running states of the ozone generator and the fan, and the ozone generator and the fan release ozone and uniformly diffuse the ozone to the greenhouse environment under the regulation and control of the main controller, so that the ozone concentration which is suitable for the growth of crops and can effectively prevent and treat diseases is achieved.
The following describes the greenhouse ozone accurate control device based on multi-model fusion, and the greenhouse ozone accurate control device based on multi-model fusion described below and the greenhouse ozone accurate control method based on multi-model fusion described above can be referred to correspondingly.
Fig. 4 is a schematic structural diagram of a greenhouse ozone precise control device based on multi-model fusion, as shown in fig. 4, the greenhouse ozone precise control device based on multi-model fusion includes: ozone scaling module 401, ozone primary tuning module 402 and ozone fine tuning module 403. The ozone calibration module 401 determines an ozone concentration standard value according to the current growth period and a preset ozone calibration model; the ozone initial adjustment module 402 determines initial ozone release concentration and duration which can meet the standard value according to the current environmental parameters and a preset ozone dissipation model, and releases ozone according to the initial ozone release concentration; the ozone fine adjustment module 403 obtains predicted values of ozone concentrations in different growth periods based on a preset ozone prediction model according to the collected current actual concentration, and adjusts ozone release according to the predicted values of ozone concentrations and the standard values obtained by the ozone calibration model so that the predicted values reach the standard values; wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
The device embodiment provided in the embodiments of the present invention is for implementing the above method embodiments, and for details of the process and the details, reference is made to the above method embodiments, which are not described herein again.
The greenhouse ozone accurate control device based on multi-model fusion provided by the embodiment of the invention comprehensively considers a plurality of factors influencing the ozone concentration, realizes dynamic and accurate control on the ozone concentration, achieves the effect of killing germs without damaging crops, and further promotes the popularization and the promotion of a green control technology in facility agriculture. On the basis of the multifunctional plant protection machine, technical support is provided for large-scale application of an ozone technology in prevention and treatment of diseases of protected vegetables, and the method has very important practical significance for improving safety of agricultural products.
Fig. 5 is a schematic structural diagram of an electronic device provided in the present invention, as shown in fig. 5, the electronic device may include: a processor (processor)501, a communication Interface (Communications Interface)502, a memory (memory)503, and a communication bus 504, wherein the processor 501, the communication Interface 502, and the memory 503 are configured to communicate with each other via the communication bus 504. The processor 501 can call logic instructions in the memory 503 to execute a greenhouse ozone accurate control method based on multi-model fusion, and the method comprises the following steps: determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model; determining initial ozone release concentration and duration which can meet the standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration; according to the collected current actual concentration, based on a preset ozone prediction model, obtaining ozone concentration prediction values of different growth periods, and according to the ozone concentration prediction values and a standard value obtained by the ozone calibration model, adjusting ozone release so that the prediction values reach the standard value; wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
In addition, the logic instructions in the memory 503 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, when the program instructions are executed by a computer, the computer being capable of executing the method for precisely controlling greenhouse ozone based on multi-model fusion provided by the above methods, the method comprising: determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model; determining initial ozone release concentration and duration which can meet the standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration; according to the collected current actual concentration, based on a preset ozone prediction model, obtaining ozone concentration prediction values of different growth periods, and according to the ozone concentration prediction values and a standard value obtained by the ozone calibration model, adjusting ozone release so that the prediction values reach the standard value; wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to execute the method for accurately controlling greenhouse ozone based on multi-model fusion provided in the above embodiments, the method comprising: determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model; determining initial ozone release concentration and duration which can meet the standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration; according to the collected current actual concentration, based on a preset ozone prediction model, obtaining ozone concentration prediction values of different growth periods, and according to the ozone concentration prediction values and a standard value obtained by the ozone calibration model, adjusting ozone release so that the prediction values reach the standard value; wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A greenhouse ozone accurate control method based on multi-model fusion is characterized by comprising the following steps:
determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model;
determining initial ozone release concentration and duration which can meet the standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration;
according to the collected current actual concentration, based on a preset ozone prediction model, obtaining ozone concentration prediction values of different growth periods, and according to the ozone concentration prediction values and a standard value obtained by the ozone calibration model, adjusting ozone release so that the prediction values reach the standard value;
wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
2. The greenhouse ozone accurate control method based on multi-model fusion as claimed in claim 1, wherein before determining the ozone concentration standard value according to the current growth period and the preset ozone calibration model, the method further comprises:
setting the ozone release duration by using different growth periods of crops as test periods and adopting a time schedule controller, and detecting the ozone release concentration;
according to the change of the physiological index values of the crops before and after the ozone treatment, the standard values and the time lengths of the ozone release concentrations in different growth periods are determined, and an ozone concentration calibration model of the ozone concentration standard values in the whole growth period of the crops is established.
3. The greenhouse ozone accurate control method based on multi-model fusion as claimed in claim 1, wherein before determining the ozone concentration standard value according to the current growth period and the preset ozone calibration model, the method further comprises:
detecting the actual ozone concentration collected by the ozone sensor under the conditions of different environmental parameters, ozone release concentrations and release time in different growth periods, and constructing a multi-factor ozone dissipation model by adopting a multiple regression method.
4. The greenhouse ozone accurate control method based on multi-model fusion as claimed in claim 1, wherein before determining the ozone concentration standard value according to the current growth period and the preset ozone calibration model, the method further comprises:
taking actual ozone concentrations acquired by a plurality of ozone sensors under the current environment as initial conditions, and continuously monitoring to obtain changed ozone concentration values acquired by the ozone sensors at different times;
fitting to obtain ozone prediction models at different positions and at different times according to the initial conditions and the changed ozone concentration values;
wherein the plurality of ozone sensors are disposed at different locations of the greenhouse.
5. The greenhouse ozone accurate control method based on multi-model fusion as claimed in claim 4, wherein the continuously monitoring to obtain the changed ozone concentration value collected by the ozone sensor at different time comprises:
setting a fan and setting corresponding fan parameters, and continuously monitoring changed ozone concentration values acquired by ozone sensors at different time under the operation of the fan parameters;
correspondingly, according to the initial condition and the changed ozone concentration value, fitting to obtain ozone prediction models at different positions and at different times, specifically:
and fitting to obtain ozone prediction models at different positions, different times and different fan parameters according to the initial conditions, the fan parameters and the changed ozone concentration value.
6. The greenhouse ozone accurate control method based on multi-model fusion as claimed in claim 5, wherein the obtaining of the predicted ozone concentration values in different growth periods based on a preset ozone prediction model according to the collected current actual concentration comprises:
and obtaining ozone concentration predicted values in different growth periods based on a preset ozone prediction model according to the acquired current actual concentration and current fan parameters.
7. The greenhouse ozone accurate control method based on multi-model fusion as claimed in claim 1, characterized in that the growing period is obtained by dividing each growing period of crops according to a preset time length.
8. The utility model provides an accurate controlling means of greenhouse ozone based on multi-model fuses which characterized in that includes:
the ozone calibration module is used for determining an ozone concentration standard value according to the current growth period and a preset ozone calibration model;
the ozone initial adjustment module is used for determining initial ozone release concentration and duration which can meet the standard value according to current environmental parameters and a preset ozone dissipation model, and releasing ozone according to the initial ozone release concentration;
the ozone fine adjustment module is used for obtaining ozone concentration predicted values in different growth periods based on a preset ozone prediction model according to the collected current actual concentration, and adjusting ozone release according to the ozone concentration predicted values and a standard value obtained by the ozone calibration model so as to enable the predicted values to reach the standard value;
wherein the ozone calibration model is a model related to the growth period of crops and a corresponding standard value of ozone concentration; the ozone dissipation model is a model relating to environmental parameters and ozone dissipation rate; the ozone prediction model is a prediction value of the ozone concentration obtained by detection at different positions and time.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for the precise control of greenhouse ozone based on multi-model fusion according to any one of claims 1 to 7 when executing the program.
10. A non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the steps of the multi-model fusion based greenhouse ozone accurate control method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110571199.3A CN113467529A (en) | 2021-05-25 | 2021-05-25 | Greenhouse ozone accurate control method and device based on multi-model fusion |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110571199.3A CN113467529A (en) | 2021-05-25 | 2021-05-25 | Greenhouse ozone accurate control method and device based on multi-model fusion |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113467529A true CN113467529A (en) | 2021-10-01 |
Family
ID=77871592
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110571199.3A Pending CN113467529A (en) | 2021-05-25 | 2021-05-25 | Greenhouse ozone accurate control method and device based on multi-model fusion |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113467529A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117461501A (en) * | 2023-12-28 | 2024-01-30 | 北京市农林科学院智能装备技术研究中心 | Multi-span greenhouse prevention and control method and system based on path planning |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101940136A (en) * | 2010-08-27 | 2011-01-12 | 大连创科君英科技发展有限公司 | Ozone generator for greenhouse crop disease-preventing yield-increasing device |
| CN101946657A (en) * | 2010-08-27 | 2011-01-19 | 大连创科君英科技发展有限公司 | Method for controlling greenhouse crop disease-prevention production-increasing machine |
| CN105557388A (en) * | 2015-12-14 | 2016-05-11 | 西北农林科技大学 | Wireless and intelligent carbon dioxide regulating and controlling method and system for facility crops |
| CN105739575A (en) * | 2016-01-29 | 2016-07-06 | 中国农业大学 | Greenhouse vegetable environmental parameter data fusion method, data fusion device, and data fusion system |
| CN106178034A (en) * | 2016-08-19 | 2016-12-07 | 北京农业智能装备技术研究中心 | A kind of greenhouse cluster ozone intelligent disinfecting method utilizing PID to control and decontaminating apparatus |
| CN107318534A (en) * | 2017-07-06 | 2017-11-07 | 西北农林科技大学 | A kind of roller shutter machine of solar greenhouse intelligent temperature control method and system with temperature prediction function |
| CN108108836A (en) * | 2017-12-15 | 2018-06-01 | 清华大学 | A kind of ozone concentration distribution forecasting method and system based on space-time deep learning |
| CN110047011A (en) * | 2019-05-16 | 2019-07-23 | 淮阴师范学院 | A kind of facilities horticulture No-harmful apple orchard ozone sterilization insect-killing device |
| CN110119767A (en) * | 2019-04-19 | 2019-08-13 | 淮阴工学院 | A kind of cucumber green house temperature intelligent detection device based on LVQ neural network |
| CN112449956A (en) * | 2020-11-16 | 2021-03-09 | 中国科学院合肥物质科学研究院 | Micro-nano ozone green prevention and control device |
| CN112668394A (en) * | 2020-11-30 | 2021-04-16 | 山东大学 | On-line prediction method and system for agricultural greenhouse production |
| CN112733958A (en) * | 2021-01-22 | 2021-04-30 | 北京农业信息技术研究中心 | Greenhouse ozone concentration control method and system |
| CN112826965A (en) * | 2021-01-27 | 2021-05-25 | 农芯科技（北京）有限责任公司 | Automatic adjust degassing unit of ozone concentration |
| CN113791650A (en) * | 2021-08-16 | 2021-12-14 | 北京农业信息技术研究中心 | Method and system for adjusting ozone concentration |
| CN114297907A (en) * | 2021-11-17 | 2022-04-08 | 北京市农林科学院智能装备技术研究中心 | Greenhouse environment spatial distribution prediction method and device |
-
2021
- 2021-05-25 CN CN202110571199.3A patent/CN113467529A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101940136A (en) * | 2010-08-27 | 2011-01-12 | 大连创科君英科技发展有限公司 | Ozone generator for greenhouse crop disease-preventing yield-increasing device |
| CN101946657A (en) * | 2010-08-27 | 2011-01-19 | 大连创科君英科技发展有限公司 | Method for controlling greenhouse crop disease-prevention production-increasing machine |
| CN105557388A (en) * | 2015-12-14 | 2016-05-11 | 西北农林科技大学 | Wireless and intelligent carbon dioxide regulating and controlling method and system for facility crops |
| CN105739575A (en) * | 2016-01-29 | 2016-07-06 | 中国农业大学 | Greenhouse vegetable environmental parameter data fusion method, data fusion device, and data fusion system |
| CN106178034A (en) * | 2016-08-19 | 2016-12-07 | 北京农业智能装备技术研究中心 | A kind of greenhouse cluster ozone intelligent disinfecting method utilizing PID to control and decontaminating apparatus |
| CN107318534A (en) * | 2017-07-06 | 2017-11-07 | 西北农林科技大学 | A kind of roller shutter machine of solar greenhouse intelligent temperature control method and system with temperature prediction function |
| CN108108836A (en) * | 2017-12-15 | 2018-06-01 | 清华大学 | A kind of ozone concentration distribution forecasting method and system based on space-time deep learning |
| CN110119767A (en) * | 2019-04-19 | 2019-08-13 | 淮阴工学院 | A kind of cucumber green house temperature intelligent detection device based on LVQ neural network |
| CN110047011A (en) * | 2019-05-16 | 2019-07-23 | 淮阴师范学院 | A kind of facilities horticulture No-harmful apple orchard ozone sterilization insect-killing device |
| CN112449956A (en) * | 2020-11-16 | 2021-03-09 | 中国科学院合肥物质科学研究院 | Micro-nano ozone green prevention and control device |
| CN112668394A (en) * | 2020-11-30 | 2021-04-16 | 山东大学 | On-line prediction method and system for agricultural greenhouse production |
| CN112733958A (en) * | 2021-01-22 | 2021-04-30 | 北京农业信息技术研究中心 | Greenhouse ozone concentration control method and system |
| CN112826965A (en) * | 2021-01-27 | 2021-05-25 | 农芯科技（北京）有限责任公司 | Automatic adjust degassing unit of ozone concentration |
| CN113791650A (en) * | 2021-08-16 | 2021-12-14 | 北京农业信息技术研究中心 | Method and system for adjusting ozone concentration |
| CN114297907A (en) * | 2021-11-17 | 2022-04-08 | 北京市农林科学院智能装备技术研究中心 | Greenhouse environment spatial distribution prediction method and device |
Non-Patent Citations (5)
| Title |
|---|
| R. PANDISELVAM, V. THIRUPATHI, V. CHANDRASEKAR, ANJINEYULU KOTHAKOTA & S. ANANDAKUMAR: "Numerical Simulation and Validation of Mass Transfer Process of Ozone Gas in Rice Grain Bulks", OZONE: SCIENCE & ENGINEERING, vol. 40, no. 3, pages 191 - 197 * |
| 乔晓军;余礼根;张云鹤;段丹丹;贺一民: "设施蔬菜病虫害绿色防控系统研制与初步应用", 农业工程技术, vol. 37, no. 31, pages 29 - 31 * |
| 刘楠: "基于臭氧浓度控制的设施蔬菜净化清洁系统", 中国优秀硕士学位论文全文数据库 农业科技辑, no. 2017, pages 048 - 50 * |
| 李学海: "蔬菜生产技术", 30 April 2016, 中国农业大学出版社, pages: 229 * |
| 王志彬，乔晓军，刘智，王莹，李玉凤: "设施蔬菜臭氧植保机设计与试验", 农业机械学报, vol. 52, no. 05, pages 293 - 300 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117461501A (en) * | 2023-12-28 | 2024-01-30 | 北京市农林科学院智能装备技术研究中心 | Multi-span greenhouse prevention and control method and system based on path planning |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110503253A (en) | A kind of planting environment self-adaptation control method and device | |
| EP3278660B1 (en) | Fertigation system, fertigation control server, salts accumulation determination method, and soil ec sensor | |
| US20160050862A1 (en) | Control system for a hydroponic greenhouse growing environment | |
| NO345829B1 (en) | C-fish – fish welfare control | |
| CN113467529A (en) | Greenhouse ozone accurate control method and device based on multi-model fusion | |
| CN105630045A (en) | System and method for intelligently growing flowers | |
| CN110915734A (en) | Aquaculture system based on Internet of things | |
| KR20190053703A (en) | Irrigation Control Method Considering Water Stress According to Plant Leaf Temperature and Watering Control System Using Thereof | |
| CN112989688A (en) | Method and device for intelligently monitoring pesticide residues of kumquats | |
| CN117114448A (en) | Agricultural production management system and method based on machine learning and Internet of things technology | |
| CN113791650A (en) | Method and system for adjusting ozone concentration | |
| CN117873238A (en) | Plant growth control method and system, computer equipment and storage medium | |
| CN116523149B (en) | Method and device for predicting appropriate period for preventing and controlling tiny pests, electronic equipment and storage medium | |
| CN117854012B (en) | Crop environment monitoring method and system based on big data | |
| CN112132700A (en) | Formula decision method for regulating and controlling water quality | |
| CN108334139A (en) | A kind of method and system of the greenhouse automation control based on big data | |
| TW201521571A (en) | Greenhouse apparatus for monitoring and controlling growth factors of plant factory and the method thereof | |
| CN113359628B (en) | Control method and device for green tea processing process | |
| CN117852912A (en) | Crop planting income measuring and calculating method and system | |
| CN111815472A (en) | Agricultural breeding environment monitoring system based on big data and environment analysis method | |
| Rahmawati et al. | Design of android base fuzzy wireles sensor network for mini smart green house | |
| KR20190098905A (en) | Method, system and non-transitory computer-readable recording medium for supporting insect rearing | |
| CN109003200A (en) | A kind of determining plant retains the method and terminal device of the number of blade | |
| Lu et al. | Research and development of a fuzzy control system of greenhouse microclimate for button mushroom | |
| CN112449956A (en) | Micro-nano ozone green prevention and control device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |