CFD-based glass greenhouse tomato plant growth environment control method

Abstract

The invention provides a CFD (computational fluid dynamics)-based glass greenhouse tomato plant growth environment control method, which comprises the following steps: acquiring deformation stripe data of the surface of a tomato plant acquired by stripe projection equipment, generating a plant three-dimensional morphology graph based on the deformation stripe data, and determining a tomato plant leaf area index. And fitting a tomato plant growth model based on the greenhouse environment data at different moments and the corresponding tomato plant leaf area indexes. And inputting the real-time environment temperature data into the tomato plant growth model, and predicting to obtain a real-time tomato plant leaf area index. And based on the real-time tomato plant leaf area index and the real-time greenhouse environment data, determining a relational expression among the environment control parameters. And inputting the relational expression among the environment control parameters into a pre-constructed three-dimensional CFD model, solving the three-dimensional CFD model based on a preset optimization target and constraint conditions to obtain target environment control parameters, and realizing effective regulation and control of the glass greenhouse tomato growth environment.

Description

Technical Field

[0001] The present invention relates to the technical field of plant growth environment control, and particularly relates to a method for controlling the growth environment of tomato plants in a CFD-based glass greenhouse. Background Art

[0002] The development of glass greenhouses has generated a large number of intelligent control equipment for facility agriculture, but there is still room for improvement in the intelligent environmental control technology. Based on the numerical simulation of Computational Fluid Dynamics (CFD), controlling and managing the temperature and humidity distribution in the glass greenhouse can effectively reduce the energy consumption of equipment such as heaters. The coupling relationship between the greenhouse environment temperature and crop growth will affect the decision-making level of production managers to a certain extent and cannot provide the best strategy.

[0003] Traditional environmental control methods rely on fixed preset values or simple feedback control mechanisms and cannot take into account the growth conditions of tomato plants to simulate and predict the complex climate condition changes inside the greenhouse. Although the CFD-based numerical simulation control method for glass greenhouses has achieved good results, it lacks dynamic adaptability. Summary of the Invention

[0004] The present invention provides a method for controlling the growth environment of tomato plants in a CFD-based glass greenhouse to solve the defect of lack of dynamic adaptability in the prior art and achieve effective regulation of the growth environment of tomato plants in the glass greenhouse. The technical solutions proposed by the present invention are as follows: In a first aspect, the present invention provides a method for controlling the growth environment of tomato plants in a CFD-based glass greenhouse, including: Obtaining the deformed stripe data on the surface of tomato plants collected by a fringe projection device, and generating a three-dimensional plant morphology map based on the deformed stripe data; Determining the leaf area index of tomato plants according to the three-dimensional plant morphology map; Obtaining greenhouse environment data at different times, and fitting a tomato plant growth model based on the greenhouse environment data at different times and the corresponding leaf area index of tomato plants; Obtaining real-time environmental temperature data, inputting the real-time environmental temperature data into the tomato plant growth model, and predicting the real-time leaf area index of tomato plants; Determining the relationship between each environmental control parameter based on the real-time leaf area index of tomato plants and the real-time greenhouse environment data; Inputting the relationship between each environmental control parameter into a pre-constructed three-dimensional CFD model, and solving the three-dimensional CFD model based on a preset optimization objective and constraint conditions to obtain the target environmental control parameters.

[0005] Optionally, the deformed fringe data is a deformed fringe pattern; generating a three-dimensional plant morphology map based on the deformed fringe data includes: Obtain the original fringe pattern, and use the Fourier transform method to extract the phase difference between the original fringe pattern and the deformed fringe pattern; Determine the height of the tomato plant according to the phase difference, and generate a three-dimensional plant morphology map according to the deformed fringe pattern and the height of the tomato plant.

[0006] Optionally, determining the relationship between the environmental control parameters based on the real-time tomato plant leaf area index and the real-time greenhouse environment data includes: Respectively determine the sensible heat exchange amount between the tomato plant and the environment, the ventilation heat between the glass greenhouse and the outside, and the solar radiation heat based on the real-time tomato plant leaf area index and the real-time greenhouse environment data; Determine the supplied heat according to the sensible heat exchange amount between the tomato plant and the environment, the ventilation heat between the glass greenhouse and the outside, and the solar radiation heat; Determine the relationship between the environmental control parameters according to the supplied heat.

[0007] Optionally, the real-time greenhouse environment data includes the heat transfer coefficient of the greenhouse glass, the area of the glass greenhouse wall for heat exchange with the outside air, the surface temperature of the glass greenhouse wall, the air temperature, the average air velocity on the surface of the glass greenhouse wall, and the thickness of the greenhouse glass; The ventilation heat between the glass greenhouse and the outside is determined by the following formula: Wherein, is the ventilation heat between the glass greenhouse and the outside, is the heat transfer coefficient of the greenhouse glass, is the area of the glass greenhouse wall for heat exchange with the outside air, is the surface temperature of the glass greenhouse wall, is the air temperature, is the average air velocity on the surface of the glass greenhouse wall, is the thickness of the greenhouse glass.

[0008] Optionally, the supplied heat is provided by a fan and a heater in the glass greenhouse, and the environmental control parameters include the fan air velocity and the heater temperature; Determining the relationship between the environmental control parameters according to the supplied heat includes: Obtain the heat power of the heater, the air volume of the heater, the fan power, and the fan blade length; According to the supplied heat, the thermal power of the heater, the air volume of the heater, the fan power, and the fan blade length, the relationship between the fan wind speed and the heater temperature is determined by the following formula: Wherein, is the supplied heat, is the fan power, is the thermal power of the heater, is the working duration, is the air density, is the sweeping area, is the fan wind speed, is the fan blade length, is the air volume of the heater, is the heater temperature, is the initial temperature.

[0009] Optionally, the three-dimensional CFD model is: Wherein, is the air density, is the working duration, is the divergence operation, is the fan wind speed, is the momentum density, is the pressure, is the viscous stress tensor, is the gravitational acceleration, is the total energy density, is the total energy per unit mass, is the heat conduction coefficient, is the heater temperature, is the viscous dissipation term.

[0010] In a second aspect, the present invention further provides a CFD-based control device for the growth environment of tomato plants in a glass greenhouse, including the following modules: A data acquisition module, configured to acquire the deformed stripe data on the surface of the tomato plant collected by the stripe projection device, and generate a three-dimensional morphology map of the plant based on the deformed stripe data; An index calculation module, configured to determine the leaf area index of the tomato plant according to the three-dimensional morphology map of the plant; A model fitting module, configured to acquire the greenhouse environment data at different times, and fit a tomato plant growth model based on the greenhouse environment data at different times and the corresponding leaf area index of the tomato plant; An index prediction module, configured to acquire the real-time environmental temperature data, input the real-time environmental temperature data into the tomato plant growth model, and predict the real-time leaf area index of the tomato plant; A relationship determination module, configured to determine the relationship formula between the environmental control parameters based on the real-time tomato plant leaf area index and the real-time greenhouse environmental data; A parameter solving module, configured to input the relationship formula between the environmental control parameters into a pre-constructed three-dimensional CFD model, and solve the three-dimensional CFD model based on the preset optimization objective and constraint conditions to obtain the target environmental control parameters.

[0011] In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, it implements the CFD-based glass greenhouse tomato plant growth environment control method as described in the first aspect above.

[0012] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the CFD-based glass greenhouse tomato plant growth environment control method as described in the first aspect above.

[0013] In a fifth aspect, the present invention further provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the CFD-based glass greenhouse tomato plant growth environment control method as described in the first aspect above.

[0014] Based on the above technical solutions, the beneficial effects of the present invention compared with the prior art are as follows: The CFD-based glass greenhouse tomato plant growth environment control method provided by the present invention can collect the deformed stripe data on the surface of the tomato plant in real time through a stripe projection device, and generate a three-dimensional topography map based on these data, so as to be able to monitor the growth status of the tomato plant in real time. The growth model of the tomato plant is fitted by using the greenhouse environmental data (such as temperature, humidity, light intensity, etc.) at different times and the tomato plant leaf area index. This model can predict the growth status of the tomato plant under different environmental conditions, including key growth indicators such as the leaf area index. According to the real-time predicted growth status of the tomato plant and the greenhouse environmental data, the environmental control parameters in the greenhouse (such as temperature, humidity, light intensity, etc.) are dynamically adjusted. This dynamic adjustment can ensure that the tomato plant is in the most suitable growth environment at different growth stages, realize the effective regulation of the growth environment of the glass greenhouse tomato, and thus improve the growth efficiency and yield. This method can dynamically adjust the environmental control parameters according to different growth stages and external environmental conditions, enhancing the adaptability and flexibility of the greenhouse environment.

[0015] Other features and advantages of the present invention will be set forth in the following description, and in part will be obvious from the description, or may be learned by practice of the present invention. The objectives and other advantages of the present invention are realized and attained by the structure particularly pointed out in the specification, claims as well as the drawings.

[0016] In order to make the above objects, features and advantages of the present invention more comprehensible, the following specific preferred embodiments are given and described in detail in conjunction with the accompanying drawings as follows. Brief Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 is a schematic flow chart of the method for controlling the growth environment of tomato plants in a CFD glass greenhouse provided by the present invention.

[0019] Figure 2 is a schematic structural diagram of the fringe projection device provided by the present invention.

[0020] Figure 3 is a schematic architecture diagram of the method for controlling the growth environment of tomato plants in a CFD glass greenhouse provided by the present invention.

[0021] Figure 4 is a schematic structural diagram of the device for controlling the growth environment of tomato plants in a CFD glass greenhouse provided by the present invention.

[0022] Figure 5 is a schematic structural diagram of the electronic device provided by the present invention. Detailed Embodiments

[0023] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0024] The following combines Figures 1 - 3 to describe the method for controlling the growth environment of tomato plants in a CFD glass greenhouse of the present invention.

[0025] Referring to Figure 1 as shown, the method includes the following: S110. Obtain the deformed fringe data on the surface of the tomato plant collected by the fringe projection device, and generate a three-dimensional morphology map of the plant based on the deformed fringe data.

[0026] During the growth period of the tomato plant, refer to Figure 2 As shown, install a fringe projection device and a camera acquisition device in the glass greenhouse. The fringe projection device and the camera acquisition device are set as a mobile track type and can move on the slideway. Twice a day, in the morning and evening, detect the growth of tomatoes through the fringe projection device.

[0027] Specifically, use the fringe projection device to scan the surface of the tomato plant and collect the deformed fringe data on its surface. Based on the collected deformed fringe data, use image processing techniques (such as phase unwrapping, three-dimensional reconstruction algorithms, etc.) to generate a three-dimensional morphology map of the tomato plant. This process can accurately reflect the morphological characteristics of the tomato plant, including the shape, size, and distribution of the leaves, etc.

[0028] S120. Determine the leaf area index of the tomato plant according to the three-dimensional morphology map of the plant.

[0029] According to the generated three-dimensional morphology map, use image processing software or algorithms to calculate the leaf area index of the tomato plant. The leaf area index is an important indicator reflecting the growth status of the plant population and is of great significance for evaluating photosynthesis efficiency, predicting crop yields, etc.

[0030] S130. Obtain the greenhouse environment data at different times, and fit a tomato plant growth model based on the greenhouse environment data at different times and the corresponding leaf area index of the tomato plant.

[0031] Obtain the greenhouse environment data at different times (such as temperature, humidity, light intensity, etc.) and the corresponding leaf area index of the tomato plant. Use statistical analysis and machine learning algorithms (such as regression analysis, neural network, etc.) to fit a tomato plant growth model based on the greenhouse environment data and the leaf area index. This model can describe the influence law of environmental factors on tomato growth and provide a scientific basis for subsequent environmental control.

[0032] The above tomato plant growth model is used to predict the growth trend and health status of the tomato plant. It can be: + Among them, is the tomato plant growth index, is the temperature, is the relative humidity, is the light intensity. The tomato plant growth index is used to evaluate the health status of the tomato plant. 、 、 、 、 , , are regression coefficients, indicating the influence degree of each environmental factor on the dependent variable (tomato plant growth index). is the error term, representing the unexplained variation or random error in the model. Each regression coefficient and the error term are obtained through fitting.

[0033] S140. Obtain real-time environmental temperature data, input the real-time environmental temperature data into the tomato plant growth model, and predict the real-time tomato plant leaf area index.

[0034] Real-time environmental temperature data is obtained in real time through sensors. Input the real-time environmental temperature data into the fitted tomato plant growth model to predict the real-time tomato plant leaf area index, realize the real-time prediction of the tomato plant leaf area index, provide dynamic feedback for environmental control, and improve the response speed and accuracy of environmental control. This process helps to timely understand the growth status of tomato plants and provide real-time feedback for environmental control.

[0035] S150. Determine the relational expressions between the environmental control parameters based on the real-time tomato plant leaf area index and the real-time greenhouse environmental data.

[0036] Based on the real-time tomato plant leaf area index and the real-time greenhouse environmental data, use data analysis or optimization algorithms to determine the relational expressions between the environmental control parameters. These relational expressions describe the combined influence of different environmental factors on tomato growth.

[0037] S160. Input the relational expressions between the environmental control parameters into a pre-constructed three-dimensional CFD model, and solve the three-dimensional CFD model based on the pre-set optimization objectives and constraint conditions to obtain the target environmental control parameters.

[0038] Construct a three-dimensional CFD model of the greenhouse, including greenhouse structure, plant distribution, ventilation equipment, etc. Input the relational expressions between the environmental control parameters as boundary conditions or source terms into the CFD model. Set optimization objectives (such as maximizing photosynthesis efficiency, minimizing energy consumption) and constraint conditions (such as temperature range, humidity range). Use a CFD solver (such as ANSYS Fluent, OpenFOAM) for numerical simulation to solve the optimal environmental control parameters, that is, the above-mentioned target environmental control parameters. Through CFD simulation, the dynamic changes of environmental parameters such as temperature, humidity, and air flow distribution in the greenhouse can be predicted. The target environmental control parameters can guide the precise regulation of the greenhouse environment to achieve the optimal growth of tomato plants.

[0039] The method for controlling the growth environment of tomato plants in a glass greenhouse based on CFD provided by the present invention collects the deformed stripe data on the surface of tomato plants in real time through a stripe projection device, and generates a three-dimensional topography map based on these data, so as to be able to monitor the growth status of tomato plants in real time. A tomato plant growth model is fitted using greenhouse environment data (such as temperature, humidity, light intensity, etc.) at different times and the leaf area index of tomato plants. This model can predict the growth status of tomato plants under different environmental conditions, including key growth indicators such as the leaf area index. According to the real-time predicted growth status of tomato plants and greenhouse environment data, the environmental control parameters in the greenhouse (such as temperature, humidity, light intensity, etc.) are dynamically adjusted. This dynamic adjustment can ensure that tomato plants are in the most suitable growth environment at different growth stages, thereby improving the growth efficiency and yield. This method can dynamically adjust the environmental control parameters according to different growth stages and external environmental conditions, enhancing the adaptability and flexibility of the greenhouse environment.

[0040] By collecting and analyzing greenhouse environment data and tomato plant growth data in real time, the present invention can more accurately understand the growth requirements of tomatoes and the environmental impact. Using the target environmental control parameters obtained by solving with a three-dimensional CFD model and numerical simulation technology can guide the precise regulation of the greenhouse environment and provide a more suitable growth environment for tomato plants. By precisely controlling greenhouse environmental parameters (such as temperature, humidity, light intensity, etc.), the utilization of resources such as light, temperature, and humidity can be optimized, and the energy utilization efficiency can be improved. At the same time, precise environmental control helps to reduce unnecessary energy consumption and emissions and reduce the impact on the environment. A suitable growth environment helps to promote the healthy growth and development of tomato plants, improve the photosynthesis efficiency and nutrient absorption ability. Precise environmental control can also reduce the occurrence and spread of pests and diseases, reduce the amount of pesticide used, and thus improve the yield and quality of tomatoes.

[0041] In an optional embodiment, the deformed stripe data in S110 is a deformed stripe pattern; the generating of the three-dimensional topography map of the plant based on the deformed stripe data in S110 includes: S1101. Obtain the original stripe pattern, and use the Fourier transform method to extract the phase difference between the original stripe pattern and the deformed stripe pattern.

[0042] The stripe projection method is a non-contact three-dimensional topography measurement technology. By projecting a known black-and-white sinusoidal stripe pattern onto the surface of the object to be measured, the height information is obtained by using the stripe deformation caused by the surface topography of the object. The present invention uses a digital projection device to project a known black-and-white sinusoidal stripe pattern onto the surface of tomato plants. A high-resolution camera is used to take pictures of the deformed stripe pattern on the surface of tomato plants from a specific angle. The relative position and angle between the projection device and the camera are known, and the device is installed on a movable track for multiple measurements at different time points or different positions.

[0043] Project the original fringe pattern onto a flat reference surface and capture the reference fringe pattern. Project the same fringe pattern onto the surface of the tomato plant and capture the deformed fringe pattern. Perform Fourier transforms on the original fringe pattern and the deformed fringe pattern respectively to convert them from the spatial domain to the frequency domain. Extract the phase of the original fringe pattern and the phase of the deformed fringe pattern . Calculate the phase difference: where, is the phase difference, is the phase of the deformed fringe, is the phase of the original fringe.

[0044] S1102. Determine the height of the tomato plant according to the phase difference, and generate a three-dimensional topography map of the plant based on the deformed fringe pattern and the height of the tomato plant.

[0045] According to the phase difference , use the principle of triangulation to calculate the height of each point on the surface of the tomato plant where, is the height of a certain point, is the baseline length between the projection device and the camera, is the fringe spatial frequency.

[0046] According to the height of each point , generate a height map of the surface of the tomato plant. Combine the height map with the deformed fringe pattern to generate a three-dimensional topography map of the tomato plant. Optimize the accuracy and smoothness of the three-dimensional topography map through interpolation and surface fitting algorithms. Extract the geometric information of the leaf surface from the three-dimensional topography map and calculate the leaf surface area. Calculate the area of each leaf through integration or meshing methods, and sum up to obtain the total leaf area of the plant.

[0047] The present invention realizes high-precision three-dimensional topography reconstruction of the surface of a tomato plant through fringe projection method and Fourier transform. Moreover, non-contact measurement is adopted to avoid damaging the plant. The fringe projection device is installed on a movable track, supporting multiple measurements at different time points or different positions to realize dynamic monitoring of plant growth. Based on the three-dimensional topography map, the leaf surface area is accurately calculated, providing data support for evaluating the growth state of the plant. Combining Fourier transform and the principle of triangulation, automatic extraction and calculation of height information are realized, improving the measurement efficiency.

[0048] In an optional embodiment, the relational expression for determining each environmental control parameter based on the real-time tomato plant leaf area index and the real-time greenhouse environment data described in S150 above includes: S1501. Determine the sensible heat exchange amount between the tomato plants and the environment, the ventilation heat between the glass greenhouse and the outside, and the solar radiation heat respectively based on the real-time tomato plant leaf area index and the real-time greenhouse environment data.

[0049] Collect real-time greenhouse environment data in real time, including temperature, humidity, light intensity, wind speed, etc. Predict the leaf area index of tomato plants in real time through the above tomato plant growth model.

[0050] The sensible heat exchange amount between the tomato plants and the environment is determined by the following formula: where, is the sensible heat exchange amount between the tomato plants and the environment, is the leaf area index of tomato plants, is the air density, is the specific heat capacity of air, is the tomato canopy temperature, is the temperature inside the greenhouse, is the aerodynamic resistance of tomato leaves.

[0051] The real-time greenhouse environment data includes the heat transfer coefficient of greenhouse glass, the area of the glass greenhouse wall for heat exchange with the outside air, the surface temperature of the glass greenhouse wall, the air temperature, the average air velocity on the surface of the glass greenhouse wall, and the thickness of the greenhouse glass. During the growth process of tomato plants, the surface temperature of the glass greenhouse wall, the air temperature, and the average air velocity on the surface of the glass greenhouse wall are monitored daily through temperature sensors and wind speed sensors.

[0052] The ventilation heat between the glass greenhouse and the outside is determined by the following formula: where, is the ventilation heat between the glass greenhouse and the outside, is the heat transfer coefficient of greenhouse glass, is the area of the glass greenhouse wall for heat exchange with the outside air, is the surface temperature of the glass greenhouse wall, is the air temperature, is the average air velocity on the surface of the glass greenhouse wall, is the thickness of the greenhouse glass.

[0053] Calculate the solar radiation heat according to the daily solar illumination situation monitored , is the solar radiation intensity, is the glass transmittance, is the surface area of the glass greenhouse.

[0054] S1502. Determine the supply heat based on the sensible heat exchange amount between the tomato plants and the environment, the ventilation heat between the glass greenhouse and the outside, and the solar radiation heat.

[0055] Integrate the sensible heat exchange amount between the tomato plants and the environment, the ventilation heat between the glass greenhouse and the outside, and the solar radiation heat calculated above. At the same time, considering the thermal inertia of the greenhouse structure and the target environmental temperature, determine the supply heat required to maintain a suitable environment inside the greenhouse. The supply heat here actually refers to the heat effect achieved by jointly heating with a warm air blower and regulating the air flow by a blower to balance the heat income and expenditure inside the greenhouse. The total heat remains unchanged, and calculate the supply heat. 。

[0056] Among them, is the air density, is the air volume inside the greenhouse, is the specific heat capacity of air, is the working duration, is the temperature inside the greenhouse at time is the ventilation heat between the glass greenhouse and the outside at time is the solar radiation heat at time is the sensible heat exchange amount between the tomato plants and the environment at time is the supply heat at time

[0057] S1503. Determine the relationship between the various environmental control parameters based on the supply heat.

[0058] The supply heat is provided by the fan and the warm air blower inside the glass greenhouse. The various environmental control parameters include the fan air speed and the warm air blower temperature.

[0059] Obtain the thermal power of the warm air blower, the air volume of the warm air blower, the fan power, and the fan blade length. According to the supply heat, the thermal power of the warm air blower, the air volume of the warm air blower, the fan power, and the fan blade length, determine the relationship between the fan air speed and the warm air blower temperature through the following formula: Among them, is the supply heat, is the fan power, is the thermal power of the warm air blower, is the working duration, is the air density, is the sweeping area, is the wind speed of the fan, is the length of the fan blade, is the air volume of the heater, is the temperature of the heater, is the initial temperature.

[0060] By monitoring the environmental parameters in the greenhouse and the performance parameters of the heater in real time, the present invention can more accurately calculate the combination of the fan wind speed and the heater temperature that meets the target supply heat, thereby improving the control accuracy of the greenhouse environment. By precisely controlling the fan wind speed and the heater temperature, unnecessary energy waste can be avoided and the greenhouse operation cost can be reduced. The suitable greenhouse environment can significantly improve the growth rate and quality of tomatoes, thereby increasing the yield and economic benefits. By establishing a relational expression and realizing automatic control, manual intervention can be reduced and the automation level of greenhouse management can be improved. At the same time, this also provides a basis for the intelligent control of the greenhouse environment.

[0061] In an optional embodiment, the three-dimensional CFD model is: wherein, is the air density, is the working duration, is the divergence operation, is the fan wind speed, is the momentum density, is the pressure, is the viscous stress tensor, is the gravitational acceleration, is the total energy density, is the total energy per unit mass, is the thermal conductivity, is the heater temperature, is the viscous dissipation term.

[0062] The process of inputting the relational expression into the three-dimensional numerical model and solving the target environmental control parameters is as follows: S210. Referring to Figure 3 as shown, using ICEM software, according to the actual sizes and positions of the glass greenhouse, agricultural facilities and tomato plants, a high-precision three-dimensional numerical model of tomatoes is established. The model is imported into ICEM software, and structured grids are divided to ensure that the grid quality meets the CFD calculation requirements (such as grid orthogonality, smoothness, etc.).

[0063] S220. Set the physical parameters of the model in Fluent software, including: the density, thermal conductivity ( ) of tomato plants, air, and glass greenhouse, specific heat capacity, etc. The tomato is set as a porous medium model. Set the fluid domain as air, considering its compressibility and viscosity.

[0064] S230. Set boundary conditions: Set the glass greenhouse walls and roof as "wall" (walls), and define their heat conduction and radiation properties. Set the windows inside the greenhouse as "interior" (internal interfaces) for simulating air flow and heat exchange. Set initial conditions, including the initial temperature, etc.

[0065] S240. Real-time predict the temperature distribution inside the glass greenhouse: Use the SIMPLE algorithm (Semi-Implicit Method for Pressure-Linked Equations) to solve the above three-dimensional CFD model, and iteratively calculate the pressure field and velocity field. Through iterative solution, find the environmental control parameters that meet the constraint conditions and are closest to the optimization goal, and obtain the temperature distribution, velocity field, and pressure field inside the greenhouse. The optimization goal is to maximize the photosynthesis efficiency to promote plant growth, or to minimize energy consumption to improve energy utilization efficiency. The constraint conditions are preset, which include setting the ranges of environmental parameters such as the temperature of the heater, humidity, and the wind speed of the fan, as well as setting the equipment operation limits (such as the range of fan rotation speed, the range of heater temperature setting). According to the CFD simulation results, dynamically adjust parameters such as the wind speed of the fan and the temperature of the heater, and implement the optimal environmental control strategy.

[0066] The present invention accurately predicts complex climate conditions such as the temperature distribution inside the greenhouse through CFD numerical simulation, ensuring that the environmental control parameters match the growth requirements of plants. According to real-time environmental data and plant growth models, dynamically adjust the boundary conditions of the CFD simulation to improve the dynamic adaptability of environmental control. Achieve precise regulation of the greenhouse environment and avoid the problem of disconnection between environmental control and plant requirements in traditional methods. Through CFD simulation and optimization algorithms, reduce unnecessary energy consumption (such as overheating and excessive ventilation). On the premise of ensuring the growth requirements of plants, reduce production costs and improve economic benefits. Use CFD technology to predict and optimize the distribution of climate conditions inside the greenhouse to ensure environmental uniformity and stability. By predicting changes in climate conditions, adjust the environmental control strategy in advance to avoid adverse effects of environmental fluctuations on plant growth.

[0067] The present invention sets the above optimization goals as maximizing photosynthesis efficiency and minimizing energy consumption. Promote the healthy growth of plants, improve yield and quality by maximizing photosynthesis efficiency. By minimizing energy consumption, reduce the operating energy consumption of equipment such as fans and heaters, and reduce production costs.

[0068] Based on the above optimization goals and combined with the three-dimensional CFD model, a multi-objective optimization function can be set, which combines photosynthesis efficiency, energy consumption, and environmental constraint conditions.

[0069] Photosynthesis efficiency ( ), related to light intensity, concentration, and temperature, the photosynthesis efficiency model can be expressed by the following formula: Where: is the light intensity, is concentration, is the temperature inside the greenhouse.

[0070] Energy consumption ( ) mainly includes the energy consumption of the fan and the heater, and the energy consumption model can be expressed by the following formula: Environmental parameters (relative humidity and carbon dioxide concentration ) need to meet the following constraints: Wherein, and are the minimum relative humidity value and the maximum relative humidity value allowed in the greenhouse environment, and are the minimum carbon dioxide concentration value and the maximum carbon dioxide concentration value allowed in the greenhouse environment.

[0071] Combining the photosynthesis efficiency and energy consumption, an optimization function is set: Where: and are weight coefficients used to balance the importance of photosynthesis efficiency and energy consumption. represents the reciprocal of minimizing the photosynthesis efficiency (i.e., maximizing the photosynthesis efficiency). represents the supplied energy, that is, the total energy consumption.

[0072] The optimization problem needs to meet the following constraints: ① 3D CFD model: ② Environmental parameter range: ③ Equipment operation limit: Wherein, and are the minimum and maximum temperatures allowed for the operation of the heater, and are the minimum and maximum wind speeds allowed for the operation of the fan.

[0073] The present invention combines the photosynthesis efficiency and energy consumption through a weighted summation method to achieve target optimization. According to the optimization results, the wind speed of the fan, the temperature of the heater, and environmental parameters such as concentration are dynamically adjusted to set the optimal control parameters for agricultural facilities and provide the best conditions for plant growth. On the premise of meeting the environmental constraints, the energy consumption is minimized and the production cost is reduced. By adjusting the weight coefficients and , different production goals and energy costs can be adapted. By setting the optimization objective function and combining the photosynthesis efficiency model, energy consumption model, and environmental constraints, precise control of the greenhouse environment and energy consumption optimization are achieved. This method provides a scientific environmental regulation strategy for the growth of tomato plants, reduces the production cost at the same time, and has important practical application value.

[0074] The present invention considers the growth process of tomato plants in a glass greenhouse. Taking each day as a time node, a fringe projection device is installed in the glass greenhouse to be able to monitor and calculate the three-dimensional morphology map of the plants in real time every day, which is easy to popularize and has low cost. Combining with the numerical simulation of the glass greenhouse to form a dynamic growth model of tomato plants (i.e., the above three-dimensional CFD model), and considering the solar heat radiation and ventilation heat exchange process at the same time, the energy consumption is dynamically calculated for the growth process of tomato plants to improve the utilization rate of agricultural facilities. Considering the growth model of tomato plants and the problem of greenhouse energy consumption, the changes of environmental parameters such as temperature and air flow are simulated, and the dynamic adjustment function is stronger. The CFD simulation uses structured grids to divide the glass greenhouse, and the calculation results are more accurate and precise than those of unstructured grids.

[0075] The following describes the CFD-based glass greenhouse tomato plant growth environment control device provided by the present invention. The CFD-based glass greenhouse tomato plant growth environment control device described below can be correspondingly referred to the CFD-based glass greenhouse tomato plant growth environment control method described above.

[0076] The CFD-based glass greenhouse tomato plant growth environment control device provided by the present invention, as shown in Figure 4 includes: A data acquisition module 310, configured to acquire the deformed fringe data on the surface of the tomato plant collected by the fringe projection device, and generate a three-dimensional morphology map of the plant based on the deformed fringe data; An index calculation module 320, configured to determine the leaf area index of the tomato plant according to the three-dimensional morphology map of the plant; The model fitting module 330 is configured to obtain greenhouse environment data at different times, and fit a tomato plant growth model based on the greenhouse environment data at different times and the corresponding leaf area index of the tomato plant; The index prediction module 340 is configured to obtain real-time environmental temperature data, input the real-time environmental temperature data into the tomato plant growth model, and predict the real-time leaf area index of the tomato plant; The relationship determination module 350 is configured to determine the relationship formula between the environmental control parameters based on the real-time leaf area index of the tomato plant and the real-time greenhouse environment data; The parameter solving module 360 is configured to input the relationship formula between the environmental control parameters into a pre-constructed three-dimensional CFD model, and solve the three-dimensional CFD model based on a pre-set optimization target and constraint conditions to obtain the target environmental control parameters.

[0077] Figure 5 An example of the physical structure diagram of an electronic device is shown in Figure 5 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440. Among them, the processor 410, the communication interface 420, and the memory 430 complete mutual communication through the communication bus 440. The processor 410 can call the logical instructions in the memory 430 to execute the CFD glass greenhouse tomato plant growth environment control method.

[0078] In addition, when the logical instructions in the above-mentioned memory 430 are implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical disks, etc., which can store program codes.

[0079] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the CFD-based glass greenhouse tomato plant growth environment control method provided by the above-mentioned various methods.

[0080] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the CFD-based glass greenhouse tomato plant growth environment control method provided by the above-mentioned various methods.

[0081] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0082] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or equivalently replace some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the growth environment of tomato plants in a CFD glass greenhouse, characterized in that, Including: Obtain the deformed stripe data on the surface of the tomato plant collected by the stripe projection device, and generate a three-dimensional morphology map of the plant based on the deformed stripe data; Determine the leaf area index of the tomato plant according to the three-dimensional morphology map of the plant; Obtain the greenhouse environment data at different times, and fit a tomato plant growth model based on the greenhouse environment data at different times and the corresponding leaf area index of the tomato plant; Obtain the real-time environmental temperature data, input the real-time environmental temperature data into the tomato plant growth model, and predict the real-time leaf area index of the tomato plant; Determine the relationship between each environmental control parameter based on the real-time leaf area index of the tomato plant and the real-time greenhouse environment data; Input the relationship between each environmental control parameter into a pre-constructed three-dimensional CFD model, and solve the three-dimensional CFD model based on the preset optimization objective and constraint conditions to obtain the target environmental control parameter.

2. The CFD-based method for controlling the growth environment of tomato plants in a glass greenhouse according to claim 1, characterized in that, The deformed stripe data is a deformed stripe pattern; generating a three-dimensional morphology map of the plant based on the deformed stripe data includes: Obtain the original stripe pattern, and use the Fourier transform method to extract the phase difference between the original stripe pattern and the deformed stripe pattern; Determine the height of the tomato plant according to the phase difference, and generate a three-dimensional morphology map of the plant according to the deformed stripe pattern and the height of the tomato plant.

3. The CFD-based method for controlling the growth environment of tomato plants in a glass greenhouse according to claim 1, wherein Determining the relationship between each environmental control parameter based on the real-time leaf area index of the tomato plant and the real-time greenhouse environment data includes: Respectively determine the sensible heat exchange amount between the tomato plant and the environment, the ventilation heat between the glass greenhouse and the outside, and the solar radiation heat based on the real-time leaf area index of the tomato plant and the real-time greenhouse environment data; Determine the supplied heat according to the sensible heat exchange amount between the tomato plant and the environment, the ventilation heat between the glass greenhouse and the outside, and the solar radiation heat; Determine the relationship between each environmental control parameter according to the supplied heat.

4. The method for controlling the growth environment of tomato plants in a CFD glass greenhouse according to claim 3, characterized in that, The real-time greenhouse environment data includes the heat transfer coefficient of the greenhouse glass, the area of the glass greenhouse wall for heat exchange with the outside air, the surface temperature of the glass greenhouse wall, the air temperature, the average air velocity on the surface of the glass greenhouse wall, and the thickness of the greenhouse glass; The ventilation heat between the glass greenhouse and the outside is determined by the following formula: Among them, is the ventilation heat between the glass greenhouse and the outside is the heat transfer coefficient of the greenhouse glass is the area of heat exchange between the glass greenhouse wall and the outside air is the surface temperature of the glass greenhouse wall is the air temperature is the average air velocity on the surface of the glass greenhouse wall is the thickness of the greenhouse glass 5. The method for controlling the growth environment of tomato plants in a CFD glass greenhouse according to claim 3, wherein The supplied heat is provided by the fan and the heater in the glass greenhouse, and each environmental control parameter includes the fan air velocity and the heater temperature; Determining the relationship between each environmental control parameter according to the supplied heat includes: Obtain the heat power of the heater, the air volume of the heater, the fan power, and the fan blade length; According to the supplied heat, the heat power of the heater, the air volume of the heater, the fan power, and the fan blade length, determine the relationship between the fan air velocity and the heater temperature by the following formula: Among them, is the supplied heat,[ is the fan power,[ is the thermal power of the heater,[ is the working duration,[ is the air density,[ is the sweeping area,[ is the fan wind speed,[ is the fan blade length,[ is the air volume of the heater,[ is the heater temperature,[ is the initial temperature.[ 6. The CFD glass greenhouse tomato plant growth environment control method according to claim 1, wherein The three-dimensional CFD model is: Among them, is the air density, is the working duration, is the divergence operation, is the wind speed of the fan, is the momentum density, is the pressure, is the viscous stress tensor, is the gravitational acceleration, is the total energy density, is the total energy per unit mass, is the thermal conductivity, is the temperature of the heater, is the viscous dissipation term.

7. A CFD-based control device for the growth environment of tomato plants in a glass greenhouse, characterized in that, Including: A data acquisition module for obtaining the deformed stripe data on the surface of the tomato plant collected by the stripe projection device, and generating a three-dimensional morphology map of the plant based on the deformed stripe data; An index calculation module for determining the leaf area index of the tomato plant according to the three-dimensional morphology map of the plant; A model fitting module, configured to obtain greenhouse environment data at different times, and fit a tomato plant growth model based on the greenhouse environment data at different times and the corresponding leaf area index of the tomato plant; An index prediction module, configured to obtain real-time environmental temperature data, input the real-time environmental temperature data into the tomato plant growth model, and predict the real-time leaf area index of the tomato plant; A relationship determination module, configured to determine the relationship formula between each environmental control parameter based on the real-time leaf area index of the tomato plant and the real-time greenhouse environment data; A parameter solving module, configured to input the relationship formula between each environmental control parameter into a pre-constructed three-dimensional CFD model, and solve the three-dimensional CFD model based on a pre-set optimization target and constraint conditions to obtain target environmental control parameters.

8. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the CFD-based tomato plant growth environment control method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the CFD-based tomato plant growth environment control method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the CFD-based tomato plant growth environment control method according to any one of claims 1 to 6.

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