Carbon dioxide self-adaptive control system based on multi-parameter feedback and regulation and control method

Abstract

The invention discloses a carbon dioxide adaptive control system based on multi-parameter feedback and a regulation and control method, the system comprises a sensor module, a control module and a man-machine interaction module, the sensor module comprises a carbon dioxide sensor, an illumination sensor and a temperature and humidity sensor which are deployed in a distributed manner, and the sensor module communicates with the control module through an RS495 bus; the control module comprises a PLC (Programmable Logic Controller) integrated with an MODBUS protocol analysis module and a dynamic threshold algorithm; the opening degree of the electromagnetic valve is adjustable from 0% to 100%, the response time is smaller than or equal to 100 ms, and a valve body is made of aluminum alloy. The man-machine interaction module comprises a touch screen supporting parameter threshold setting and real-time data display, and the storage capacity of the touch screen is 30 GB. The invention relates to the technical field of agricultural environment regulation and control, in particular to a carbon dioxide self-adaptive control system based on multi-parameter feedback and a regulation and control method. 2, optimizing a self-adaptive strategy; 3, whole-process data tracing; and 4, high-reliability hardware design.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural environment regulation, and particularly to a multi-parameter feedback-based carbon dioxide adaptive control system and a regulation method. Background Art

[0002] With the development of smart agriculture, the traditional carbon dioxide regulation system has gradually exposed technical bottlenecks:

[0003] Firstly, it relies on the regulation of a single CO2 concentration parameter and does not combine multiple environmental factors such as light, temperature and humidity for collaborative optimization, resulting in a gas fertilizer utilization rate of less than 70% and limited photosynthetic efficiency;

[0004] Secondly, the control strategy is fixed and cannot dynamically adjust the threshold according to the crop growth cycle. For example, when the CO2 demand during the tomato fruiting period is 200 - 300 ppm higher than that during the seedling stage, the fixed parameters are still used, causing a supply deviation;

[0005] Thirdly, it lacks a real-time data acquisition and long-term analysis mechanism and is difficult to optimize the regulation strategy through historical data. It is statistically shown that the regulation efficiency can be increased by 18% through three consecutive years of data analysis, while the traditional system only provides a simple numerical display;

[0006] Fourthly, the hardware has weak anti-interference ability. When the RS495 bus exceeds 800 meters, the signal attenuation rate reaches 15%, and the misjudgment rate increases. Summary of the Invention

[0007] In view of this, the present invention aims to provide a multi-parameter feedback-based carbon dioxide adaptive control system and a regulation method to achieve real-time and accurate interaction between the physical entity and the virtual model of the weak current system, and improve the intelligent level and operation and maintenance efficiency of the system.

[0008] The technical solution of the embodiment of the present invention is implemented as follows:

[0009] A multi-parameter feedback-based carbon dioxide adaptive control system includes: a sensor module, a control module and a human-computer interaction module. The sensor module includes a distributed carbon dioxide sensor, a light sensor and a temperature and humidity sensor, and communicates with the control module through an RS495 bus;

[0010] The control module includes a PLC controller integrating a MODBUS protocol parsing module and a dynamic threshold algorithm;

[0011] The solenoid valve has an adjustable opening degree of 0 - 100%, a response time ≤ 100 ms, and the valve body material is aluminum alloy;

[0012] The human-computer interaction module includes a touch screen supporting parameter threshold setting and real-time data display, and a data recorder with a storage capacity of 30 GB, supporting RS495 communication and dual storage medium backup.

[0013] Preferably, the PLC controller incorporates a dynamic threshold algorithm, and the calculation formula is: CO2 target value = base value × light compensation coefficient × temperature and humidity correction factor, where the light compensation coefficient is positively correlated with the light intensity, and the temperature and humidity correction factor is dynamically adjusted in combination with temperature and humidity changes.

[0014] Preferably, the sensor module is connected using shielded twisted pair wires, the bus length ≤ 1200 meters, a signal repeater is configured every 500 meters, and a lightning protection module with a through-current ≥ 10 kA is integrated.

[0015] Preferably, the solenoid valve is isolated and controlled from the PLC controller through a solid-state relay, the control signal is a DC0 - 10V analog quantity, and an opening position feedback sensor is equipped.

[0016] Preferably, the control cabinet integrates a surge protector, a power filter, and a redundant power module, and the protection level is IP54.

[0017] A carbon dioxide adaptive regulation method based on multi-parameter feedback, characterized in that it is applied to the system according to any one of claims 1 - 5, and includes the following steps:

[0018] Data acquisition: The sensor module obtains CO2 concentration, light intensity, and temperature and humidity parameters in real time and transmits them to the PLC controller through the RS495 bus;

[0019] Dynamic calculation: The PLC controller calculates the CO2 target value according to a preset formula, and the formula includes a light compensation coefficient and a temperature and humidity correction factor;

[0020] Intelligent control: When the measured CO2 concentration is lower than the lower limit of the target value (target value × 0.95), the solenoid valve is opened, and when it is higher than the upper limit (target value × 1.05), it is closed, and the control period is 30 seconds;

[0021] Data storage: The data recorder stores environmental parameters and control instructions through the RS495 bus, and the storage interval is adjustable from 1 to 60 minutes.

[0022] Preferably, in the dynamic calculation step, the light compensation coefficient is set as: when the light intensity ≥ 1000 μmol / m 2 ·s, the CO2 target value is increased by 15%; the temperature and humidity correction factor is: for every 1°C increase in temperature, the target value increases by 20 ppm; for every 10% increase in humidity, the target value decreases by 10 ppm.

[0023] Preferably, the PLC controller incorporates an adaptive learning module to optimize the PID control parameters through historical data to adapt to different crop growth cycles.

[0024] Preferably, the data storage step supports USB flash drive export, remote FTP download, and dual storage medium backup, and the data traceability period is ≥ 2 years.

[0025] Preferably, the system supports manual emergency control, and the emergency adjustment of the CO2 supply amount is realized through the manual switch on the solenoid valve body.

[0026] Due to the above technical solutions adopted in the embodiments of the present invention, it has the following advantages:

[0027] 1. Multi-parameter collaborative control: Integrate light, temperature, and humidity parameters to dynamically calculate the CO2 target value (formula: CO2 target value = base value × light compensation coefficient × temperature and humidity correction factor), so that the gas fertilizer supply amount is accurately matched with the photosynthesis demand, the utilization rate is increased by more than 20%, and the photosynthetic efficiency is increased by 15%.

[0028] 2. Adaptive strategy optimization: Built-in PID parameter self-learning module, automatically adjust the threshold according to the crop growth cycle, and the control accuracy is improved from ±100 ppm to ±50 ppm.

[0029] 3. Full-process data traceability: Integrate the RS495 bus data recorder, support the storage of environmental parameters for more than 2 years, and provide the functions of USB flash drive export / remote FTP download, providing data support for the optimization of control strategies, and reducing manual intervention by 50% is expected.

[0030] 4. High-reliability hardware design: Adopt shielded twisted pair + repeater + lightning protection module, extend the effective transmission distance of the RS495 bus to 1200 meters, control the signal attenuation rate within 5%, and reduce the false alarm rate by 70%.

[0031] The above summary is only for the purpose of the specification and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the present invention will be readily apparent by reference to the drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 is the system architecture diagram of the present invention;

[0034] Figure 2 is the control flow chart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0035] In the following text, only some exemplary embodiments are briefly described. As those skilled in the art can recognize, the described embodiments can be modified in various different ways without departing from the spirit or scope of the present invention. Therefore, the drawings and the description are considered to be exemplary in nature rather than restrictive.

[0036] It should be noted that terms such as "first", "second", "symmetric", "array", etc. are only used for the purpose of distinguishing descriptions and position descriptions, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "symmetric", etc. can explicitly or implicitly include one or more of such features; similarly, when certain features are not limited in quantity by words such as "two", "three", etc., it should be noted that such features also belong to explicitly or implicitly including one or more feature quantities;

[0037] In the present invention, unless otherwise clearly specified and defined, terms such as "installation", "connection", "fixation", etc. should be understood in a broad sense; for example, it can be a fixed connection, a detachable connection, or an integrally formed one; it can be a mechanical connection, a direct connection, a welding connection, or an indirect connection through an intermediate medium, and can be the communication inside two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood in combination with the drawings of the specification and specific circumstances.

[0038] The embodiments of the present invention will be described in detail below with reference to the drawings.

[0039] As Figure 1-2 shown, the present invention provides a carbon dioxide adaptive control system based on multi-parameter feedback, including: a sensor module, a control module, and a human-computer interaction module. The sensor module includes a distributed carbon dioxide sensor, a light sensor, and a temperature and humidity sensor, and communicates with the control module through an RS495 bus;

[0040] The control module includes a PLC controller integrating a MODBUS protocol parsing module and a dynamic threshold algorithm;

[0041] The solenoid valve has an adjustable opening degree of 0 - 100%, a response time ≤ 100 ms, and the valve body material is aluminum alloy;

[0042] The human-computer interaction module includes a touch screen supporting parameter threshold setting and real-time data display, and a data recorder with a storage capacity of 30 GB, supporting RS495 communication and dual storage medium backup.

[0043] In this embodiment, specifically, the PLC controller incorporates a dynamic threshold algorithm, and the calculation formula is: CO2 target value = base value × light compensation coefficient × temperature and humidity correction factor. The light compensation coefficient is positively correlated with the light intensity, and the temperature and humidity correction factor is dynamically adjusted in combination with temperature and humidity changes. The sensor module is connected using shielded twisted pair wires, with a bus length ≤ 1200 meters. A signal repeater is configured every 500 meters, and a lightning protection module with a through-current ≥ 10 kA is integrated.

[0044] In this embodiment, specifically, the solenoid valve and the PLC controller are isolated and controlled through a solid-state relay. The control signal is a DC0 - 10V analog quantity, and an opening position feedback sensor is equipped. The control cabinet integrates a surge protector, a power filter, and a redundant power supply module, with an IP54 protection level.

[0045] In this embodiment, specifically, the carbon dioxide adaptive regulation method based on multi-parameter feedback includes the following steps:

[0046] Data acquisition: The sensor module continuously obtains CO2 concentration, light intensity, and temperature and humidity parameters, and transmits them to the PLC controller via the RS495 bus.

[0047] Dynamic calculation: The PLC controller calculates the CO2 target value according to a preset formula, which includes a light compensation coefficient and a temperature and humidity correction factor.

[0048] Intelligent control: When the measured CO2 concentration is lower than the lower limit of the target value (target value × 0.95), the solenoid valve is opened; when it is higher than the upper limit (target value × 1.05), it is closed. The control period is 30 seconds.

[0049] Data storage: The data recorder stores environmental parameters and control instructions via the RS495 bus, and the storage interval is adjustable from 1 to 60 minutes.

[0050] In this embodiment, specifically, in the dynamic calculation step, the light compensation coefficient is set as follows: when the light intensity ≥ 1000 μmol / m 2 ·s, the CO2 target value is increased by 15%; the temperature and humidity correction factor is: for every 1°C increase in temperature, the target value increases by 20 ppm; for every 10% increase in humidity, the target value decreases by 10 ppm.

[0051] In this embodiment, specifically, the PLC controller incorporates an adaptive learning module to optimize PID control parameters through historical data, adapting to different crop growth cycles. The data storage step supports U disk export, remote FTP download, and dual storage medium backup, with a data traceability period ≥ 2 years.

[0052] In this embodiment, specifically, the system supports manual emergency control to achieve emergency adjustment of the CO2 supply volume through the manual switch on the solenoid valve body.

[0053] When the present invention is in operation: in a greenhouse or a plant factory, a carbon dioxide sensor with an accuracy of ±50 ppm, a light sensor with a range of 0 - 2000 μmol / m 2 ·s, and a temperature and humidity sensor with an accuracy of ±0.5 °C / ±3% RH are evenly distributed 0.5 meters above the crop canopy through a stainless steel bracket, with a spacing of 5 - 10 meters. They are connected to a PLC controller using shielded twisted pair wire of RVVP2×1.0mm 2 . The bus length is ≤1200 meters, and a repeater and a lightning protection module are configured. The PLC calculates the required value in real time through a dynamic threshold algorithm (CO2 target value = base value × light compensation coefficient × temperature and humidity correction factor). When the measured CO2 concentration is lower than the lower limit of the target value (0.95 times), a solenoid valve with an adjustable opening of 0 - 100% is controlled to open and the flow rate is adjusted. When it is higher than the upper limit (1.05 times), it is closed, and the control period is 30 seconds. Human - machine interaction is achieved through a 7 - inch touch screen, enabling parameter setting (CO2 target value with a ±10% floating range) and real - time data display. The data recorder stores environmental parameters at intervals of 1 - 60 minutes and supports dual - medium backup. The system is built - in with an adaptive learning module to optimize PID parameters to adapt to the crop growth cycle. At the same time, a surge protector and a power filter are integrated to ensure stable operation in a high - humidity and dusty environment. During maintenance, the sensors are calibrated every 6 months, and the response time of the solenoid valve (≤100 ms) is checked annually. The CO2 regulation accuracy reaches ±50 ppm, the utilization rate of gas fertilizer is increased by more than 20%, and the yield is increased by 10 - 15%.

[0054] The following are several specific embodiments of applying the present invention:

[0055] Embodiment 1: Regulation of tomato planting in a greenhouse

[0056] System configuration

[0057] Sensor deployment: A carbon dioxide sensor with an accuracy of ±50 ppm, a light sensor with a range of 0 - 2000 μmol / m 2 ·s, and a temperature and humidity sensor with an accuracy of ±0.5 °C / ±3% RH are installed distributively at an 8 - meter interval. The bus length is ≤1000 meters, and 1 repeater is configured.

[0058] Control module: Siemens S7 - 1200 PLC, SMCVX2120 solenoid valve (flow rate 200 L / min), control period 30 seconds.

[0059] Gas source type: Bottled liquid CO2, pressure 0.8 MPa.

[0060] Parameter setting

[0061] Base value: 800 ppm at the seedling stage, 1000 ppm at the fruiting stage.

[0062] Compensation rule: when the light intensity ≥ 1000 μmol / m 2 ·s, the target value increases by 15%; for every 1°C increase in temperature, it increases by 20 ppm, and for every 10% increase in humidity, it decreases by 10 ppm.

[0063] Control strategy

[0064] When the humidity in the rainy season > 80%, automatically reduce the CO2 target value by 20 ppm to inhibit gray mold.

[0065] During the peak light period from 10:00 to 14:00 every day during the fruiting period, open the solenoid valve to 80% opening.

[0066] Expected effect

[0067] The CO2 utilization rate is increased by 22%, the yield per plant is increased by 13%, and the rate of deformed fruits is decreased by 8%.

[0068] Example 2: Regulation of vertical planting of cucumbers in a plant factory

[0069] System configuration

[0070] Sensor deployment: high-density deployment at 5-meter intervals, bus length ≤ 800 meters, integrated solar power supply unit with 100W solar panel + 12V / 50Ah lithium battery.

[0071] Control module: Mitsubishi FX5U PLC, SMCVX3130 solenoid valve (flow rate 500 L / min), control cycle 15 seconds.

[0072] Gas source type: industrial waste gas recycled CO2 (purity ≥ 99%).

[0073] Parameter setting

[0074] Base value: 900 ppm throughout the growth period (LED light intensity 1200 μmol / m 2 ·s).

[0075] Compensation rule: light compensation coefficient fixed at 1.15, temperature correction coefficient +15 ppm / °C, humidity correction coefficient -5 ppm / 10%.

[0076] Control strategy

[0077] Combined with the LED light formula (red: blue = 4:1), alternately adjust the CO2 target value (±50 ppm) every hour to simulate natural environmental fluctuations.

[0078] At night (22:00 - 6:00), turn off the CO2 supply and turn on the dehumidification fan at the same time.

[0079] Expected effect

[0080] The CO2 consumption cost is reduced by 35%, the cucumber growth cycle is shortened by 5 days, and the vitamin C content is increased by 10%.

[0081] Example 3: Hydroponic regulation of leafy vegetables in intelligent greenhouse

[0082] System configuration

[0083] Sensor deployment: Deployed at a spacing of 10 meters, the bus length ≤ 1200 meters, equipped with a surge protector (DEHNDPS230).

[0084] Control module: Delta AS300PLC, SMCVX1110 solenoid valve (flow rate 100L / min), control period 60 seconds.

[0085] Gas source type: Liquid CO2 cylinder, equipped with a manual emergency switch.

[0086] Parameter setting

[0087] Base value: 600ppm for lettuce, 700ppm for spinach.

[0088] Compensation rule: The light compensation coefficient is only activated (+10%) when ≥ 800 μmol / m 2 ·s, and the humidity correction coefficient is -10ppm / 10%.

[0089] Control strategy

[0090] Dynamically adjust the CO2 target value in combination with the nutrient solution EC value (1.2 - 1.5 mS / cm for lettuce). For every 0.1 mS / cm increase in the EC value, the CO2 target value increases by 50 ppm.

[0091] Automatically switch to the low-power mode on rainy and cloudy days, and extend the control period to 90 seconds.

[0092] Expected effect

[0093] The nitrate content of leafy vegetables is reduced by 15%, the leaf thickness is increased by 12%, and the irrigation water utilization rate is increased by 20%.

[0094] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various changes or substitutions, and these should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A carbon dioxide adaptive control system based on multi-parameter feedback, characterized in that, Including: A sensor module, a control module, and a human-machine interaction module. The sensor module includes a distributedly deployed carbon dioxide sensor, a light sensor, and a temperature and humidity sensor, which communicate with the control module through an RS495 bus. The control module includes a PLC controller integrating a MODBUS protocol parsing module and a dynamic threshold algorithm. The solenoid valve has an adjustable opening degree of 0-100%, a response time ≤ 100 ms, and the valve body is made of aluminum alloy. The human-machine interaction module includes a touch screen supporting parameter threshold setting and real-time data display, and a data recorder with a storage capacity of 30 GB, supporting RS495 communication and dual storage medium backup.

2. The carbon dioxide adaptive control system based on multi-parameter feedback according to claim 1, wherein: The PLC controller has a built-in dynamic threshold algorithm, and the calculation formula is: CO2 target value = base value × light compensation coefficient × temperature and humidity correction factor, where the light compensation coefficient is positively correlated with the light intensity, and the temperature and humidity correction factor is dynamically adjusted in combination with temperature and humidity changes.

3. The carbon dioxide adaptive control system based on multi-parameter feedback according to claim 1, characterized in that: The sensor module is connected by shielded twisted pair, the bus length ≤ 1200 meters, a signal repeater is configured every 500 meters, and a lightning protection module with a through-current ≥ 10 kA is integrated.

4. The carbon dioxide adaptive control system based on multi-parameter feedback according to claim 1, wherein: The solenoid valve is isolated and controlled by the PLC controller through a solid-state relay, the control signal is a DC0-10V analog quantity, and an opening position feedback sensor is equipped.

5. The carbon dioxide adaptive control system based on multi-parameter feedback according to claim 1, characterized in that: The control box integrates a surge protector, a power filter, and a redundant power module, and the protection level is IP54.

6. A carbon dioxide adaptive regulation method based on multi-parameter feedback, characterized in that Applied to the system described in any one of claims 1-5, it includes the following steps: Data acquisition: The sensor module acquires CO2 concentration, light intensity, and temperature and humidity parameters in real time and transmits them to the PLC controller through the RS495 bus. Dynamic calculation: The PLC controller calculates the CO2 target value according to a preset formula, and the formula includes a light compensation coefficient and a temperature and humidity correction factor. Intelligent control: When the measured CO2 concentration is lower than the lower limit of the target value, the solenoid valve is opened, and when it is higher than the upper limit of the target value, it is closed, and the control period is 30 seconds. Data storage: The data recorder stores environmental parameters and control instructions through the RS495 bus, and the storage interval is adjustable from 1 to 60 minutes.

7. The carbon dioxide adaptive regulation method based on multi-parameter feedback according to claim 6, characterized in that: In the dynamic calculation step, the light compensation coefficient is set as follows: when the light intensity ≥ 1000 μmol / m 2 ·s, the CO2 target value is increased by 15%; the temperature and humidity correction factor is: for every 1°C increase in temperature, the target value increases by 20 ppm; for every 10% increase in humidity, the target value decreases by 10 ppm.

8. The carbon dioxide self-adaptive regulation method based on multi-parameter feedback according to claim 6, characterized in that: The PLC controller has a built-in adaptive learning module, which optimizes PID control parameters through historical data to adapt to different crop growth cycles.

9. The carbon dioxide adaptive regulation method based on multi-parameter feedback according to claim 6, characterized in that: The data storage step supports U disk export, remote FTP download, and dual storage medium backup, and the data traceability period ≥ 2 years.

10. The carbon dioxide adaptive regulation method based on multi-parameter feedback according to claim 6, wherein: The system supports manual emergency control, and the emergency adjustment of the CO2 supply amount is realized through the manual switch on the solenoid valve body.

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