A greenhouse environment feedback type intelligent cooling system and a control method thereof

Abstract

The application provides a greenhouse environment feedback type intelligent cooling system and a control method thereof, wherein an environment monitoring and control unit collects temperature, relative humidity and water mist or humidity concentration in the greenhouse at a preset sampling period to form a sampling data set, then compares the data of the sampling data set with a first temperature threshold, a first humidity threshold, a second humidity threshold and a water mist or humidity concentration upper limit value corresponding to an environment target parameter set respectively, judges whether to meet the spray cooling, then changes the spray pressure based on different evaporation potential levels to change the mist droplet particle size, predicts the water mist or humidity concentration change trend and the relative humidity change trend within a preset time after the spray is finished, and dynamically adjusts the related parameters of the next spray process according to the prediction result, so that the temperature and the relative humidity in the greenhouse are kept in a target range corresponding to the environment target parameter set to execute the next spray.

Description

Technical Field

[0001] This invention relates to the field of agricultural cultivation technology, specifically to an environmental feedback-type intelligent cooling system for greenhouses and its control method. Background Technology

[0002] Greenhouses, as an important form of facility agriculture, are widely used in the cultivation of vegetables, flowers, and other cash crops, as well as in the seed and seedling breeding process. During high-temperature seasons or in hot and humid climates, greenhouses are prone to problems such as excessively high temperatures and humidity, which not only affect the normal growth of crops but also easily induce pests and diseases, adversely affecting crop yield and quality. To cool down and control humidity inside greenhouses, high-pressure spray cooling, fan ventilation, and wet curtain fans are commonly used, which have advantages such as fast cooling speed and relatively simple equipment structure.

[0003] For example, Chinese patent application No. 202110542175.5, published on July 20, 2021, discloses a method and system for intelligent control of temperature and humidity in a greenhouse. The method includes comparing the current indoor-outdoor temperature difference of the target greenhouse with a preset indoor temperature difference, obtaining the comparison result, uploading the comparison result to a preset server terminal, detecting the indoor humidity of the target greenhouse, calculating the indoor dryness of the target greenhouse based on the indoor humidity and indoor temperature, feeding back the indoor dryness to the preset server terminal, and using the preset server terminal to determine whether it is necessary to adjust the external roller shutter or vent and whether it is necessary to humidify the air based on the comparison result and the indoor dryness. When it is determined that it is necessary to adjust the external roller shutter or vent and humidify the air, the control device of the external roller shutter or vent and the indoor air humidification device of the target greenhouse are activated to intelligently adjust the temperature and humidity.

[0004] The aforementioned literature addresses the issues of inefficient and delayed manual control by comparing indoor and outdoor temperature differences and humidity levels, enabling a pre-set server terminal to control external roller shutters and vents to adjust the temperature and humidity of the greenhouse in a timely manner. However, it does not consider the coordinated dynamic control of temperature, humidity, and water mist conditions to improve spray cooling efficiency and reduce the risk of moisture damage. Furthermore, it does not consider determining the evaporability of the environment for different crops, then performing appropriate spraying treatments, and finally dynamically predicting and adjusting humidity and temperature after spraying to ensure that temperature and humidity are in a suitable environment for the crops, thus ensuring reliable crop growth. Summary of the Invention

[0005] The purpose of this invention is to provide an environmental feedback-type intelligent cooling system and its control method for greenhouses, which can achieve coordinated dynamic control of temperature, humidity and water mist status, thereby improving the efficiency of spray cooling, reducing the risk of moisture damage, and enabling the system to achieve stable energy-saving operation.

[0006] To achieve the above objectives, the present invention provides a control method for an environmental feedback-based intelligent cooling system for greenhouses, comprising the following steps: S1. Collect temperature, relative humidity, and water mist or moisture concentration inside the greenhouse at a preset sampling period and form a sampling dataset. Select the corresponding environmental target parameter set from the preset parameter library based on crop type and crop growth period information. S2. Compare the data from the sampled dataset with the corresponding temperature threshold, humidity threshold, and upper limit of water mist or moisture concentration in the environmental target parameter set to determine whether the current environmental conditions meet the conditions for spray cooling. S3. Determine the maximum allowable total spray volume and the maximum allowable spray duration per spray based on the temperature, relative humidity and second humidity threshold of the environmental target parameter set of the sampled dataset. Dynamically determine the evaporation potential level based on the maximum allowable total spray volume and the maximum allowable spray duration per spray. Then change the droplet size within the target range based on different evaporation potential levels. S4. Based on the linear trend prediction of historical sampling datasets, predict the change trend of water mist or moisture concentration and relative humidity within a preset time after the spraying ends, and dynamically adjust the on / off state of the spraying unit, droplet size and spraying duration during the next spraying process according to the prediction results, so that the temperature and relative humidity in the greenhouse are kept within the target range corresponding to the environmental target parameter set.

[0007] The above method determines whether spraying is necessary based on sampled temperature and humidity, and the set of environmental target parameters including temperature and humidity thresholds. These environmental target parameters are determined according to different crop types and growth stages, ensuring that spraying operations can be tailored to specific crops and growth stages. Furthermore, by incorporating droplet size into the spraying control process and linking it to spray pressure, the spraying process can be precisely controlled according to the actual environmental conditions within the greenhouse. This satisfies cooling requirements while improving the evaporation efficiency of the sprayed water mist, reducing the risk of water mist deposition and moisture damage. Simultaneously, by introducing real-time monitoring and feedback adjustment of water mist or moisture concentration in addition to temperature and relative humidity, the method directly reflects the water mist distribution and moisture changes during spraying, avoiding reliance solely on temperature. The lag in humidity parameter regulation effectively reduces the likelihood of water mist retention, condensation, and disease occurrence in greenhouses. By collecting temperature, relative humidity, and humidity thresholds, the maximum allowable total spray volume and the maximum allowable single spray duration are determined to establish evaporation potential levels for different crops and environments. This allows for the use of different droplet sizes to achieve spraying operations under varying evaporation capacities (strong, weak, and moderate). The spray volume, spray duration, spray unit on / off status, and droplet size are dynamically adjusted based on the evaporation potential level, ensuring the spraying process matches the environmental evaporability. This avoids problems such as low spraying efficiency and moisture accumulation under high humidity or low evaporation conditions, improving the stability and controllability of the spray cooling process and ensuring the reliability of crop growth.

[0008] Furthermore, in step S1, the set of environmental target parameters includes the target temperature range, the target relative humidity range, and the upper limit of water mist or humidity concentration.

[0009] The above settings allow for the selection of different target ranges and corresponding parameters based on different crop types and their different growth stages, thus facilitating subsequent adjustments to the control of spraying, cooling, and ventilation dehumidification based on the selected parameters.

[0010] Furthermore, the temperature threshold includes a first temperature threshold, and the humidity threshold includes a first humidity threshold and a second humidity threshold. Step S2 further includes: When the temperature of the sampled dataset is greater than or equal to the first temperature threshold and the relative humidity of the sampled dataset is less than or equal to the first humidity threshold, the spray unit and the cooling unit are activated and the ventilation and dehumidification unit is turned on. When the relative humidity is equal to or greater than the second humidity threshold and the water mist or moisture concentration is greater than the preset upper limit, the spray unit reduces the spray intensity or stops spraying, while maintaining or increasing the intensity output of the ventilation and dehumidification unit. When both temperature and relative humidity are within the preset target range, the spray unit reduces spraying, the cooling unit reduces cooling intensity, and the ventilation and dehumidification unit operates normally to maintain ventilation.

[0011] The above settings allow for comparison between the data from the sampled dataset and the data corresponding to the environmental target parameter set, thereby determining whether adjustments to the temperature and humidity required for crops inside the greenhouse are necessary.

[0012] Furthermore, in step S3, determining the evaporation potential level includes the following steps: (a) Approximate calculation of saturated vapor pressure using Magnus empirical formula (1) , (1), In equation (1), T represents the temperature of the sampled dataset; (b) Based on the saturated vapor pressure es (T) The vapor pressure deficit (VPD) is calculated based on the relative humidity (RH) using the following formula (2). (2); (c) Calculate the maximum permissible moisture absorption W_avail per unit volume of air under the current temperature and humidity conditions, and without exceeding the second humidity threshold RH_lim for the crop, using the following formula (3). (3), In equation (3), RH represents the relative humidity of the current sampled dataset. R is the preset engineering approximation of the molar mass of water, R is the preset universal gas constant, TK is the thermodynamic temperature, TK = T + 273.15, and T is the temperature of the current sampled dataset; (d) Determine the maximum allowable total spray volume S for a single spraying cycle based on the maximum allowable moisture absorption W_avail and the greenhouse space volume V. S = W_avail × V (4). (e) The evaporation potential level is dynamically determined by comparing the maximum allowable total spray volume upper limit S with the preset spray flow rate Q, the maximum allowable spray duration t_max, and the classification boundary coefficient.

[0013] The above settings, through the air vapor pressure deficit (VPD) and the maximum allowable moisture absorption (W_avail) derived from the current temperature and humidity status and the target humidity limit, jointly characterize the evaporation potential level, so as to dynamically constrain the spray volume and accurately meet the humidity requirements of different crops.

[0014] Furthermore, in step (e), t_max is the maximum permissible spray duration for a single spray, t_min is the minimum response time, and k1 and k2 are both preset grading boundary coefficients. The formula for calculating t_max is as follows: (5), When S≥k1×Q×t_max, it is determined to be a strong evaporation potential level. The current droplet size is reduced to accelerate the evaporation rate. The refrigeration unit in the greenhouse maintains normal output, and the ventilation and dehumidification unit in the greenhouse operates normally. When S≥k2×Q×t_max and S<k1×Q×t_max, it is determined to be of medium evaporation potential level. The current droplet size remains unchanged, the refrigeration unit maintains normal output, and the ventilation and dehumidification unit operates normally. When S≥Q×t_min and S<k2×Q×t_max, it is judged as a weak evaporation potential level. The current droplet size is increased to reduce the probability of water mist retention, and the ventilation and dehumidification intensity of the ventilation and dehumidification unit is increased to accelerate the removal of moisture. When S < Q × t_min, it is determined that there is no effective evaporation margin in the air, so the spray unit stops operating. At the same time, the cooling unit outputs maximum power, and the ventilation and dehumidification unit operates at maximum power, and the combined operation accelerates the removal of moisture.

[0015] The above settings, through different levels of evaporation potential classification, can be dynamically adapted to changes in the set of environmental target parameters corresponding to different types of crops and different crop growth stages. This allows the evaporation potential classification results to directly reflect the actual amount of water vapor that can be absorbed in the greenhouse. As a result, humidity can be precisely controlled according to the crops planted in the greenhouse and their growth stage to meet the optimal humidity required for crop growth.

[0016] Furthermore, in step S4, the prediction process for the relative humidity change trend is as follows: (6), In equation (6), RH _pred Here, RH represents the relative humidity prediction, k is the slope of humidity change, and Δt is the prediction time interval. When the relative humidity is predicted to be RH _pred When the humidity exceeds 95% of the second humidity threshold RH_lim, the spray duration is reduced proportionally by a reduction factor of 1. And the RH after spraying does not exceed RH_lim; When the relative humidity is predicted to be RH _pred When the humidity exceeds the second humidity threshold RH_lim, the spray unit stops spraying.

[0017] The above settings prevent the relative humidity inside the greenhouse from exceeding the second humidity threshold after spraying, thus avoiding the risk of water mist accumulation or moisture damage.

[0018] Furthermore, in step S4, the prediction process for the trend of water mist or humidity concentration change is as follows: C_pred = C_cur + k_C × Δt (7), In Equation (7), C_pred is the predicted value of water mist or humidity concentration, C_cur is the water mist or humidity concentration of the current sampled dataset, k_C is the slope of concentration change, and Δt is the prediction time interval. When the predicted value of water mist or humidity concentration C_pred exceeds the preset upper limit threshold C_lim, the spray unit reduces or stops spraying, provided that the temperature and relative humidity do not exceed the corresponding thresholds.

[0019] The above settings avoid the risk of localized accumulation due to insufficient water mist diffusion after spraying.

[0020] Furthermore, in steps S3 and S4, the droplet size changes monotonically with the spray pressure, and the droplet size can be changed within the target range of 30 to 60 μm by changing the spray pressure.

[0021] The above settings, by adjusting the droplet size, achieve a balance between the evaporation rate and deposition probability of the droplets in the air, thereby reducing the risk of water mist deposition and moisture damage while meeting the cooling requirements.

[0022] Furthermore, it also includes step S5: When the spray stops but the temperature is still above the temperature threshold, both the cooling unit and the ventilation and dehumidification unit will output maximum power. If the temperature still cannot be reduced to the target temperature range, an alarm signal will be issued to allow for manual intervention and equipment inspection.

[0023] The above settings, through manual intervention via alarm signals, prevent sustained high temperatures inside the greenhouse due to equipment malfunction, thus avoiding impact on crop growth.

[0024] Another aspect of the present invention provides an environmental feedback-type intelligent cooling system for greenhouses, comprising a spray unit installed inside the greenhouse, a refrigeration unit connected to the spray unit, a ventilation and dehumidification unit, and an environmental monitoring and control unit. The spray unit includes a water tank, a high-pressure water pump connected to the water tank, a water pipe connected to the high-pressure water pump, and atomizing nozzles connected to the water pipe. The refrigeration unit includes a compressor refrigeration device and a cold circulation system connected to the compressor refrigeration device. The ventilation and dehumidification unit includes one or more supply fans, an exhaust fan, a ventilation channel and a dehumidification channel configured in conjunction with the greenhouse. The environmental monitoring and control unit includes a temperature sensor, a humidity sensor, a water mist or moisture concentration monitoring device, and a main controller. The main controller is connected to the temperature sensor, humidity sensor, water mist or moisture concentration monitoring device, and spray unit. The fogging unit, cooling unit, and ventilation and dehumidification unit are electrically connected. The main controller is used to determine the maximum allowable total spray volume and the maximum allowable duration of a single spray based on the temperature, relative humidity, and humidity threshold of the environmental target parameter set in the sampled dataset. It also dynamically determines the evaporation potential level based on the maximum allowable total spray volume and the maximum allowable duration of a single spray. Then, based on different evaporation potential levels, it changes the droplet size within the target range. Based on the linear trend of the historical sampled dataset, it predicts the trend of water mist or moisture concentration and relative humidity changes within a preset time after the spraying ends. Based on the prediction results, it dynamically adjusts the on / off state of the fogging unit, droplet size, and spraying duration during the next spraying process to keep the temperature and relative humidity in the greenhouse within the target range corresponding to the environmental target parameter set.

[0025] The above settings enable the environmental monitoring and control unit to sample data from the greenhouse environment and achieve real-time monitoring. Furthermore, based on differences in crop type and growth stage, and using the set of environmental target parameters required by the crop as a reference, the system can achieve coordinated dynamic regulation of different parameters within the greenhouse environment. This ensures a suitable growing environment for crops while improving the stability and energy efficiency of the system. Attached Figure Description

[0026] Figure 1 This is a flowchart of the process of the present invention.

[0027] Figure 2 This is a schematic diagram of the overall framework of the present invention.

[0028] Figure 3 This is a schematic diagram illustrating an application scenario of the present invention. Detailed Implementation

[0029] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0030] like Figure 2-3As shown, an environmental feedback-type intelligent cooling system for greenhouses includes a spray unit installed inside the greenhouse, a refrigeration unit connected to the spray unit, a ventilation and dehumidification unit, and an environmental monitoring and control unit. The spray unit includes a water storage tank, a high-pressure water pump connected to the water storage tank, a water pipe connected to the high-pressure water pump, and atomizing nozzles connected to the water pipe. There are two or more atomizing nozzles. The high-pressure water pump pressurizes the water in the water storage tank and delivers it to the atomizing nozzles through the water pipes. The atomizing nozzles atomize the pressurized water flow into fine droplets and spray them into the air inside the greenhouse. In this embodiment, a heat insulation or heat preservation layer is provided on the outside of the water pipe to reduce the heat transfer from the outside to the spray water, so that the spray water is kept as low as possible during the process of being delivered to the atomizing nozzles, thereby improving the ability of the spray water to maintain a low temperature before entering the atomizing nozzles and the evaporative cooling efficiency after spraying.

[0031] The refrigeration unit includes a compressor refrigeration device and a cold circulation system connected to the compressor refrigeration device. It pre-cools the spray water through the refrigeration effect, so that the temperature of the spray water is lower than the ambient air temperature, thereby improving the evaporation potential of the spray water.

[0032] The ventilation and dehumidification unit includes one or more supply fans, exhaust fans, ventilation channels and dehumidification channels that are designed in conjunction with the greenhouse. This allows for air circulation within the greenhouse and effectively removes moisture, water mist, and hot air. In this embodiment, the dehumidification channel includes a dehumidification outlet located at the top of the greenhouse and ventilation openings located on the side walls and bottom of the greenhouse. By combining top dehumidification with side or bottom air intake, a smooth discharge structure is formed that facilitates the upward discharge of hot and humid air.

[0033] The environmental monitoring and control unit includes a temperature sensor, a humidity sensor, a water mist or moisture concentration monitoring device, and a main controller installed inside the greenhouse. The main controller is electrically connected to the temperature sensor, humidity sensor, water mist or moisture concentration monitoring device, spray unit, cooling unit, and ventilation and dehumidification unit, respectively. Based on the parameters of the collected dataset, it can adjust the spray unit's on / off state, the high-pressure water pump pressure after the spray is turned on, the droplet size, the output power of the cooling unit, and the output power of the ventilation and dehumidification unit in a coordinated manner. At the same time, the main controller selects the corresponding set of environmental target parameters based on crop type and crop growth stage information, thereby realizing dynamic adjustment based on the collected environmental data feedback, and thus achieving differentiated cooling and dehumidification control for different crop needs.

[0034] like Figure 1 As shown, a control method for an environmental feedback-based intelligent cooling system for greenhouses includes the following specific steps: S1. Temperature, relative humidity, and water mist or moisture concentration inside the greenhouse are collected at a preset sampling period using temperature sensors, humidity sensors, and water mist or moisture concentration monitoring devices installed inside the greenhouse, forming a sampling dataset. Then, based on crop type and crop growth stage information, a corresponding set of environmental target parameters is selected from a preset parameter library. The environmental target parameter set includes a target temperature range, a target relative humidity range, a first temperature threshold, a first humidity threshold, a second humidity threshold, and a preset upper limit value for water mist or moisture concentration. In this embodiment, the sampling period can be 5–30 s to balance system control response speed and signal stability.

[0035] S2. Compare the parameters in the sampled data set with the first temperature threshold, the first humidity threshold, the second humidity threshold, and the upper limit of water mist or moisture concentration in the environmental target parameter set, and then determine whether the current environmental conditions meet the conditions for spray cooling. When the temperature of the sampled dataset is greater than or equal to the first temperature threshold and the relative humidity of the sampled dataset is less than or equal to the first humidity threshold, the spray unit and the cooling unit are activated and the ventilation and dehumidification unit is turned on. When the relative humidity is equal to or greater than the second humidity threshold and the water mist or moisture concentration is greater than the preset upper limit of water mist or moisture concentration, the spray unit reduces or stops spraying, while maintaining or increasing the output of the ventilation and dehumidification unit. When both temperature and relative humidity are within the preset target range, the spray unit reduces spraying, the cooling unit reduces cooling power, and the ventilation and dehumidification unit operates normally to maintain ventilation. By comparing the data from the aforementioned sampled dataset with the corresponding data from the environmental target parameter set, it can be determined whether the temperature and humidity required for crops in the greenhouse need to be adjusted. At the same time, different target ranges and corresponding parameters can be selected according to different crop types and their different growth stages, which facilitates subsequent adjustments to the control of spraying, cooling, and ventilation dehumidification based on the selected parameters.

[0036] S3. Dynamically determine the evaporation potential level based on the temperature, relative humidity, and the second humidity threshold of the environmental target parameter set in the sampled dataset. Determining the evaporation potential level includes the following steps: (a) Approximate calculation of saturated vapor pressure using the Magnus empirical formula , in 0 Within a 45℃ range, the deviation from the ASHRAE standard value is less than 0.15%, which meets the engineering accuracy requirements, as shown in the following formula (1). (1), In equation (1), T represents the temperature of the sampled dataset; (b) Based on the saturated vapor pressure es (T)The vapor pressure deficit (VPD) is calculated based on the relative humidity (RH) using the following formula (2). (2); (c) Calculate the maximum permissible moisture absorption W_avail per unit volume of air under the current temperature and humidity conditions, and without exceeding the second humidity threshold RH_lim for the crop, using the following formula (3). (3), In equation (3), RH represents the relative humidity of the current sampled dataset. This is an engineering approximation of the molar mass of water. = 18.0 g / mol, meeting engineering accuracy, R is the universal gas constant, R = 8.314 J / (mol·K), TK is the thermodynamic temperature, TK = T + 273.15, T is the temperature of the current sampled dataset; The evaporation potential level is characterized by the air vapor pressure deficit (VPD) in step (2) and the maximum allowable moisture absorption (W_avail) obtained in step (3) based on the current temperature and humidity status and the target humidity limit, so as to dynamically constrain the spray volume and accurately meet the humidity requirements of different crops. The maximum allowable moisture absorption capacity W_avail has been set to ensure that the RH after spraying does not exceed RH_lim. In this embodiment, for crops that are sensitive to moisture damage, RH_lim can be set to 5% to 10% lower than the actual moisture tolerance limit in order to reserve a safety margin for spraying. (d) Determine the maximum allowable total spray volume S for a single spraying cycle based on the maximum allowable moisture absorption W_avail and the greenhouse space volume V. S = W_avail × V (4). (e) The evaporation potential level is dynamically determined by comparing the product of the maximum allowable total spray volume S, the preset spray flow rate Q, the maximum allowable single spray duration t_max, and the classification boundary coefficient. Then, the droplet size is changed within the target range based on the different evaporation potential levels to match the spraying process with the evaporability of the environment. Here, t_min is the minimum response time, and k1 and k2 are classification boundary coefficients, which can be selected according to different crop types. In this embodiment, k1=20, k2=5, t_min is selected as 1~2 s, and the t_max calculation formula is as follows: (5), When S≥k1×Q×t_max, it is determined to be a strong evaporation potential level. At this time, the air evaporation margin is sufficient, the current droplet size is reduced to accelerate the evaporation rate, the refrigeration unit in the greenhouse maintains normal output, and the ventilation and dehumidification unit in the greenhouse operates normally. The reduction of the current droplet size can be determined according to the preset strong evaporation potential level and the corresponding reduction of droplet size.

[0037] When S≥k2×Q×t_max and S<k1×Q×t_max, it is determined to be of medium evaporation potential level. The current droplet size remains unchanged, the refrigeration unit maintains normal output, and the ventilation and dehumidification unit operates normally. When S≥Q×t_min and S<k2×Q×t_max, it is determined to be a weak evaporation potential level. At this time, the air evaporation margin is small. The current droplet size is increased to reduce the probability of water mist retention. At the same time, the ventilation and dehumidification intensity of the ventilation and dehumidification unit is increased to accelerate the removal of moisture. The increase in the current droplet size can be determined according to the preset strong evaporation potential level and the corresponding increase in droplet size.

[0038] When S < Q × t_min, it is determined that there is no effective evaporation margin in the air, so the spray unit stops operating. At the same time, the refrigeration unit outputs maximum power, and the ventilation and dehumidification unit operates at maximum power. The combined operation accelerates the removal of moisture. The maximum power of the refrigeration unit is the maximum power that the refrigeration unit can operate at.

[0039] The above-mentioned classification of evaporation potential at different levels allows for dynamic adaptation based on changes in greenhouse volume V, spray flow rate Q, and environmental target parameter sets corresponding to different types of crops and different crop growth stages. This enables the classification results of evaporation potential to directly reflect the actual amount of water vapor that can be absorbed in the greenhouse, thereby achieving precise humidity control based on the crops grown in the greenhouse and their growth stages, in order to meet the optimal humidity required for crop growth.

[0040] S4. Based on the linear trend prediction of historical sampling datasets, predict the trend of water mist or moisture concentration and relative humidity changes within a preset time after the spraying ends. The process for predicting the trend of relative humidity change is as follows: (6), In equation (6), RH _pred Here, RH represents the relative humidity prediction value, RH is the relative humidity of the current sampled dataset, and k is the slope of the humidity change, indicating the relative humidity at a given time (2...). The real-time rate of change within 5 minutes is obtained by the main controller through linear regression or least squares fitting of the continuous sampled data within the sampling period. The best fitting slope k_est at the current moment is output with the most recent N sampling points (N≥3) as input, and k_est is used as the predicted slope k, and Δt is the prediction time interval. When the relative humidity is predicted to be RH _pred When the humidity exceeds 95% of the second humidity threshold RH_lim, the spray duration is reduced proportionally by a reduction factor of 1. And the RH after spraying does not exceed RH_lim; When the relative humidity is predicted to be RH _pred When the relative humidity exceeds the second humidity threshold RH_lim, the spraying unit stops spraying to prevent the relative humidity inside the greenhouse from exceeding the second humidity threshold after spraying, which could lead to water mist accumulation or the risk of moisture damage. The prediction process for the trend of water mist or humidity concentration is as follows: C_pred = C_cur + k_C × Δt (7), In equation (7), C_pred is the predicted value of water mist or humidity concentration, C_cur is the water mist or humidity concentration of the current sampled dataset, and k_C is the slope of concentration change, calculated in the same way as the slope of humidity change k. k_C represents the concentration of water mist or humidity at a preset time (2 The real-time rate of change within 5 minutes, where Δt is the prediction time interval; When the predicted value of water mist or humidity concentration C_pred exceeds the preset upper limit threshold C_lim, the spray unit reduces or stops spraying under the condition that the temperature and relative humidity do not exceed the corresponding thresholds, so as to avoid the risk of insufficient water mist diffusion after spraying leading to local accumulation. When the relative humidity prediction error and water mist or moisture concentration prediction error of the above continuous sampling exceed the preset deviation threshold, the main controller performs prediction trend correction and re-updates the concentration change slope k_C and humidity change slope k based on the most recent N sampling points to improve prediction accuracy and reduce the risk of misjudgment. Then, based on the prediction results, the spray pressure, droplet size, and spray duration of the spray unit are dynamically adjusted during the next spraying process to keep the temperature and relative humidity inside the greenhouse within the target range corresponding to the environmental target parameter set.

[0041] When the S5 stops spraying and the temperature is higher than the first temperature threshold, both the cooling unit and the ventilation and dehumidification unit will output maximum power. If the temperature still cannot be reduced to the target temperature range, an alarm signal will be actively issued to allow manual intervention to check the equipment. This manual intervention through the alarm signal can prevent continuous high temperature conditions in the greenhouse due to equipment damage, which could affect crop growth.

[0042] In this embodiment, after judging the prediction result through step S4, step S3 is executed. If the predicted RH after spraying exceeds RH_lim, then the spraying is prohibited or shortened.

[0043] In steps S3 and S4, the droplet size generated by the atomizing nozzle is characterized by the droplet volume median diameter (D50). The volume median diameter represents the droplet size corresponding to 50% of the droplet volume in a volume distribution sense. Under the same nozzle structure conditions, the droplet size changes monotonically with spray pressure. By changing the spray pressure, the droplet size can be varied within the target range of 30–60 μm. By adjusting the droplet size, a balance is achieved between the evaporation rate and deposition probability of the droplets in the air, thereby reducing the risk of water mist deposition and moisture damage while meeting cooling requirements. In this embodiment, the spray pressure is achieved by adjusting the outlet pressure of the high-pressure water pump, which has an adjustment range of 1.2–2.0 MPa.

[0044] In step S2, the first humidity threshold is lower than the upper limit of the target relative humidity range to ensure sufficient humidity margin when the spray is started; the second humidity threshold is higher than the upper limit of the target relative humidity range as a safety protection boundary.

[0045] In step S4, when both temperature and relative humidity are within the preset target range corresponding to the set of environmental target parameters, the main controller switches the spray unit and cooling unit to maintenance mode or shuts them down, while retaining the ventilation and dehumidification unit to achieve moderate or intermittent ventilation. The operating interval of the ventilation and dehumidification unit can be 5 to 30 minutes, and the ventilation duration can be 1 to 10 minutes, so as to reduce water and electricity consumption.

[0046] In this embodiment, a greenhouse with an area of ​​500 m², a height of 4.5 m, an air volume of approximately 2250 m³, and a total system spray flow rate of approximately 40 g / s (estimated based on 40-50 nozzles, each with a flow rate of approximately 3 L / h) is used as an example. The explanation is based on three operating conditions: strong evaporation potential, medium evaporation potential, and weak evaporation potential, as detailed in Table 1 below:

[0047] From Table 1 above, we can conclude that: Operating Condition 1 (Strong Evaporation Potential Level, Strawberry, RH_lim=85%): T=38℃, RH=55%, VPD≈2.98 kPa, W_avail≈13.84 g / m³, final allowable spray volume≈31115 g (see Table 1 for details). The main controller calculates S=W_avail×V≈31115 g≥20×Q×t_max (=16000 g), which is determined to be a strong evaporation potential level. The droplet size is reduced to accelerate evaporation. The maximum duration of a single spray is 20 s (about 800 g), which is completed intermittently in multiple sprays. After a single spray, the RH increase is about 0.8% (from 55% to about 56%), which is far below the 85% safety limit.

[0048] Condition 2 (medium evaporation potential, tomato, RH_lim=88%): T=32℃, RH=72%, VPD≈1.33 kPa, W_avail≈5.40 g / m³, final allowable spray volume≈12150 g (see Table 1 for details). The main controller calculates S=W_avail×V≈12150 g, which meets 5×Q×t_max (=4000 g) but does not reach 20×Q×t_max (=16000 g), and is judged to be of medium evaporation potential level. The current droplet size remains unchanged. After a single 20-second spray (about 800 g), the RH rises by about 1.1% (from 72% to about 73%), which is lower than the 88% safety limit. The process is completed intermittently in multiple stages.

[0049] Operating Condition 3 (Weak Evaporation Potential, Leafy Vegetables, RH_lim=90%): T=30℃, RH=85%, VPD≈0.64 kPa, W_avail≈1.51 g / m³, final allowable spray volume≈3400 g (see Table 1 for details), total duration approximately 85 s, single duration constrained by a 20 s upper limit, completed in approximately 4 intermittent intervals. The main controller calculates S=W_avail×V≈3400 g, which satisfies Q×t_min (=40 g) but does not reach 5×Q×t_max (=4000 g), thus classifying it as a weak evaporation potential level. The droplet size is increased and ventilation and dehumidification are strengthened to constrain the spray volume. When RH=90%, S=W_avail×V≈0 g<Q×t_min, the main controller determines that there is no effective evaporation margin, stops the spray unit from spraying, and switches to a combined operation mode of maximum power output of the refrigeration unit and maximum power output of the enhanced ventilation and dehumidification unit. If the temperature still cannot be reduced to the target range, an alarm signal is output for manual intervention.

[0050] The working principle of this invention is as follows: An environmental monitoring and control unit installed inside the greenhouse collects temperature, relative humidity, and water mist or moisture concentration within the greenhouse at a preset sampling period to form a sampling dataset. Then, the data in the sampling dataset is compared with the first temperature threshold, first humidity threshold, second humidity threshold, and upper limit value of water mist or moisture concentration corresponding to the environmental target parameter set to determine whether the spray cooling is satisfied. Next, the spray pressure is changed based on different evaporation potential levels, thereby changing the droplet size to match the spray process with the evaporability of the environment. Within a preset time after the spray ends, the change trend of water mist or moisture concentration and relative humidity is predicted, and the relevant parameters for the next spray process are dynamically adjusted according to the prediction results to keep the temperature and relative humidity inside the greenhouse within the target range corresponding to the environmental target parameter set, so as to execute the next spray.

Claims

1. A control method for an environmental feedback-based intelligent cooling system for greenhouses, characterized in that: Includes the following steps: S1. Collect temperature, relative humidity, and water mist or moisture concentration inside the greenhouse at a preset sampling period and form a sampling dataset. Select the corresponding environmental target parameter set from the preset parameter library based on crop type and crop growth period. S2. Compare the data from the sampled dataset with the corresponding temperature threshold, humidity threshold, and upper limit of water mist or moisture concentration in the environmental target parameter set to determine whether the current environmental conditions meet the conditions for spray cooling. S3. Determine the maximum allowable total spray volume and the maximum allowable spray duration per spray based on the temperature, relative humidity and humidity threshold of the environmental target parameter set of the sampled dataset. Dynamically determine the evaporation potential level based on the maximum allowable total spray volume and the maximum allowable spray duration per spray. Then, change the droplet size within the target range based on different evaporation potential levels. S4. Based on the linear trend prediction of historical sampling datasets, predict the change trend of water mist or moisture concentration and relative humidity within a preset time after the spraying ends, and dynamically adjust the on / off state of the spraying unit, droplet size and spraying duration during the next spraying process according to the prediction results, so that the temperature and relative humidity in the greenhouse are kept within the target range corresponding to the environmental target parameter set.

2. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 1, characterized in that: In step S1, the set of environmental target parameters includes the target temperature range, the target relative humidity range, and the upper limit of water mist or moisture concentration.

3. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 1, characterized in that: The temperature threshold includes a first temperature threshold, and the humidity threshold includes a first humidity threshold and a second humidity threshold. Step S2 further includes: When the temperature of the sampled dataset is greater than or equal to the first temperature threshold and the relative humidity of the sampled dataset is less than or equal to the first humidity threshold, the spray unit and the cooling unit are activated and the ventilation and dehumidification unit is turned on. When the relative humidity is equal to or greater than the second humidity threshold and the water mist or moisture concentration is greater than the preset upper limit, the spray unit reduces the spray intensity or stops spraying, while maintaining or increasing the intensity output of the ventilation and dehumidification unit. When both temperature and relative humidity are within the preset target range, the spray unit reduces spraying, the cooling unit reduces cooling intensity, and the ventilation and dehumidification unit operates normally to maintain ventilation.

4. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 1, characterized in that: In step S3, determining the evaporation potential level includes the following steps: (a) Approximate calculation of saturated vapor pressure using Magnus empirical formula (1) , （1）， In equation (1), T represents the temperature of the sampled dataset; (b) Based on the saturated vapor pressure es (T) The vapor pressure deficit (VPD) is calculated based on the relative humidity (RH) using the following formula (2). （2）； (c) Calculate the maximum permissible moisture absorption W_avail per unit volume of air under the current temperature and humidity conditions, and without exceeding the second humidity threshold RH_lim for the crop, using the following formula (3). （3）， In equation (3), RH represents the relative humidity of the current sampled dataset. R is the preset engineering approximation of the molar mass of water, R is the preset universal gas constant, TK is the thermodynamic temperature, TK = T + 273.15, and T is the temperature of the current sampled dataset; (d) Determine the maximum allowable total spray volume S for a single spraying cycle based on the maximum allowable moisture absorption W_avail and the greenhouse space volume V. S = W_avail × V (4). (e) The evaporation potential level is dynamically determined by comparing the maximum allowable total spray volume upper limit S with the preset spray flow rate Q, the maximum allowable spray duration t_max, and the classification boundary coefficient.

5. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 4, characterized in that: In step (e), t_max is the maximum permissible spray duration for a single spray, t_min is the minimum response time, and k1 and k2 are both preset grading boundary coefficients. The formula for calculating t_max is as follows: （5）， When S≥k1×Q×t_max, it is determined to be a strong evaporation potential level. The current droplet size is reduced to accelerate the evaporation rate. The refrigeration unit in the greenhouse maintains normal output, and the ventilation and dehumidification unit in the greenhouse operates normally. When S≥k2×Q×t_max and S<k1×Q×t_max, it is determined to be of medium evaporation potential level. The current droplet size remains unchanged, the refrigeration unit maintains normal output, and the ventilation and dehumidification unit operates normally. When S≥Q×t_min and S<k2×Q×t_max, it is judged as a weak evaporation potential level. The current droplet size is increased to reduce the probability of water mist retention, and the ventilation and dehumidification intensity of the ventilation and dehumidification unit is increased to accelerate the removal of moisture. When S < Q × t_min, it is determined that there is no effective evaporation margin in the air, so the spray unit stops operating. At the same time, the cooling unit outputs maximum power, and the ventilation and dehumidification unit operates at maximum power, and the combined operation accelerates the removal of moisture.

6. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 1, characterized in that: In step S4, the prediction process for the relative humidity change trend is as follows: （6）， In equation (6), RH _pred Here, RH represents the relative humidity prediction, k is the relative humidity of the current sampled dataset, Δt is the slope of humidity change, and Δt is the prediction time interval. When the relative humidity is predicted to be RH _pred When the humidity exceeds 95% of the second humidity threshold RH_lim, the spray duration is reduced proportionally by a reduction factor of 1. And the RH after spraying does not exceed RH_lim; When the relative humidity is predicted to be RH _pred When the humidity exceeds the second humidity threshold RH_lim, the spray unit stops spraying.

7. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 1, characterized in that: In step S4, the prediction process for the trend of water mist or humidity concentration change is as follows: C_pred = C_cur + k_C × Δt (7), In Equation (7), C_pred is the predicted value of water mist or humidity concentration, C_cur is the water mist or humidity concentration of the current sampled dataset, k_C is the slope of concentration change, and Δt is the prediction time interval. When the predicted value of water mist or humidity concentration C_pred exceeds the preset upper limit threshold C_lim, the spray unit reduces or stops spraying, provided that the temperature and relative humidity do not exceed the corresponding thresholds.

8. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 1, characterized in that: In steps S3 and S4, the droplet size changes monotonically with the spray pressure. The droplet size can be changed within the target range of 30 to 60 μm by changing the spray pressure.

9. The control method for an environmental feedback-type intelligent cooling system for greenhouses according to claim 1, characterized in that: It also includes step S5: When the spray stops but the temperature is still above the temperature threshold, both the cooling unit and the ventilation and dehumidification unit will output maximum power. If the temperature still cannot be reduced to the target temperature range, an alarm signal will be issued to allow for manual intervention and equipment inspection.

10. An environmental feedback-type intelligent cooling system for greenhouses, characterized in that: The system includes a spray unit installed inside the greenhouse, a refrigeration unit connected to the spray unit, a ventilation and dehumidification unit, and an environmental monitoring and control unit. The spray unit includes a water tank, a high-pressure water pump connected to the water tank, a water pipe connected to the high-pressure water pump, and atomizing nozzles connected to the water pipe. The refrigeration unit includes a compressor refrigeration unit and a cold circulation system connected to the compressor refrigeration unit. The ventilation and dehumidification unit includes one or more supply fans, an exhaust fan, and ventilation and dehumidification channels configured in conjunction with the greenhouse. The environmental monitoring and control unit includes a temperature sensor, a humidity sensor, a water mist or moisture concentration monitoring device, and a main controller. The main controller is connected to the temperature sensor, humidity sensor, water mist or moisture concentration monitoring device, spray unit, refrigeration unit, and ventilation and dehumidification unit. The unit is electrically connected, and the main controller is used to determine the maximum allowable total spray volume and the maximum allowable duration of a single spray based on the temperature, relative humidity, and humidity threshold of the environmental target parameter set in the sampled dataset. It also dynamically determines the evaporation potential level based on the maximum allowable total spray volume and the maximum allowable duration of a single spray. Then, based on different evaporation potential levels, it changes the droplet size within the target range. Based on the linear trend of the historical sampled dataset, it predicts the trend of water mist or moisture concentration and relative humidity change within a preset time after the spray ends. Based on the prediction results, it dynamically adjusts the on / off state of the spray unit, droplet size, and spray duration during the next spraying process to keep the temperature and relative humidity in the greenhouse within the target range corresponding to the environmental target parameter set.

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