Low-temperature and low-humidity environment air water generator optimization system and safety control method

Abstract

The invention relates to the technical field of air water production, in particular to a low-temperature and low-humidity environment air water production machine optimization system and a safety control method. The data acquisition module is used for detecting parameters of temperature, humidity and frosting degree and importing the parameters into the adjusting assembly; the optimization adjustment module is connected with an adjustment assembly port and adjusts the refrigerant flow and the defrosting period according to the feedback parameters of the data acquisition module; and the equipment protection module is connected with an adjusting assembly port, and realizes adaptive adjustment of equipment flow and power in combination with environmental parameters fed back by the data acquisition module. The fuzzy logic control and PID control technology is adopted, and the adaptability and stability of the system in the environment with the large temperature difference and the low temperature are improved. The refrigerant flow and the defrosting period are dynamically adjusted by monitoring the temperature, the humidity and the defrosting data in real time, so that the efficiency of producing water from air is improved, the energy consumption is reduced, and the service life of equipment is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of air water production, and in particular to an optimization system and safety control method for an air water production machine in a low-temperature and low-humidity environment. Background Art

[0002] As a new way to obtain water resources, air water production machines are of great significance in remote areas such as islands, cold regions, and water-scarce areas. However, in a low-temperature environment, air water production machines face special challenges, such as low air humidity and large temperature fluctuations, which pose higher requirements for their efficiency and stability. The existing air water production machine technology has insufficient adaptability in a low-temperature environment, resulting in unstable water production efficiency and difficulty in meeting the demand for efficient and stable water source supply.

[0003] Although the existing technology has improved the efficiency of air water production machines to a certain extent, in extremely cold and low-temperature regions, there are still many technical bottlenecks, such as the defrosting problem not being effectively solved and inaccurate temperature and humidity control. The existence of these problems limits the actual application effect of air water production machines in a low-temperature environment.

[0004] Therefore, there is a need for an optimization system and safety control method for an air water production machine in a low-temperature and low-humidity environment that can improve the adaptability and stability of the system in a large temperature difference and low-temperature environment. By real-time monitoring of temperature, humidity, and defrosting data, dynamically adjusting the refrigerant flow rate and defrosting cycle, thereby improving air water production efficiency, reducing energy consumption, and extending the service life of the equipment to meet the current environmental needs. Summary of the Invention

[0005] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this part, the abstract, and the title. However, such simplifications or omissions shall not be used to limit the scope of the present invention.

[0006] In view of the above-mentioned existing technology, there are still many technical bottlenecks in the efficiency of air water production machines in extremely cold and low-temperature regions, the defrosting problem has not been effectively solved, the temperature and humidity control is inaccurate, and the application effect is limited.

[0007] Therefore, the technical problem to be solved by the present invention is to design an optimization system and safety control method for an air water production machine in a low-temperature and low-humidity environment that can improve the adaptability and stability of the system in a large temperature difference and low-temperature environment. By real-time monitoring of temperature, humidity, and defrosting data, dynamically adjusting the refrigerant flow rate and defrosting cycle, thereby improving air water production efficiency, reducing energy consumption, and extending the service life of the equipment to meet the current environmental needs.

[0008] To solve the above technical problems, the present invention provides the following technical solutions: An optimization system for an air water production machine in a low-temperature and low-humidity environment, including,

[0009] A data acquisition module that imports and adjusts the parameters of temperature, humidity, and frosting degree into the total assembly;

[0010] An optimization adjustment module that connects to the port of the adjustment total assembly and adjusts the refrigerant flow rate and defrosting cycle according to the feedback parameters of the data acquisition module;

[0011] An equipment protection module that connects to the port of the adjustment total assembly and, in combination with the environmental parameters fed back by the data acquisition module, realizes the adaptive adjustment of the equipment flow rate and power.

[0012] As an improvement of the present invention,

[0013] The data acquisition module includes a temperature and humidity sensing unit and a frosting sensing unit;

[0014] The temperature and humidity sensing unit detects the air temperature and humidity parameters, and the frosting sensing unit detects the frosting parameters of the equipment condensation system;

[0015] The temperature and humidity sensing unit and the frosting sensing unit transmit data to the adjustment total assembly for data analysis.

[0016] As an improvement of the present invention,

[0017] The optimization adjustment module is connected to the adjustment total assembly;

[0018] The optimization adjustment module includes a fuzzy logic control unit and a PID control unit;

[0019] The fuzzy logic control unit sets the refrigerant flow rate according to the data of the temperature and humidity sensing unit;

[0020] The fuzzy logic control unit obtains the initial defrosting cycle according to the data of the frosting sensing unit;

[0021] The initial defrosting cycle parameter is imported into the PID control unit, and the PID control unit is connected to the defrosting control unit.

[0022] As an improvement of the present invention,

[0023] The equipment protection module defines an equipment power consumption optimization function, including:

[0024] A water output model function and a power consumption model function;

[0025] The water output model function is expressed as:

[0026] W = a 1 T + a 2 H + a 3 Q + a 4 N + b

[0027] Among them, the water output is W, the temperature T, humidity H, refrigerating capacity flow Q, and fan speed N are environmental parameters, a1, a2, a3, a4 are coefficients, reflecting the influence degree of each factor on the water output, and b is a constant term;

[0028] The power consumption model function is expressed as:

[0029] P = p comp (Q) + p fan (N)

[0030] The equipment power consumption is P, the compressor power is Pcomp, and the fan power is Pfan.

[0031] As an improvement of the present invention,

[0032] Assume that the relationship between the compressor power and the refrigerant flow is:

[0033] P comp = c 1 Q + c 2

[0034] The relationship between the fan power and the fan speed is:

[0035] P fan = c 3 N + c 4

[0036] Comprehensively, the equipment power consumption formula can be obtained:

[0037] P = c 1 Q + c 2 + c 3 N + c 4

[0038] c1, c2, c3, c4 are correlation coefficients.

[0039] As an improvement of the present invention,

[0040] Construct the power consumption optimization function:

[0041]

[0042] Calculate the gradients of the power consumption optimization function J with respect to the refrigerant flow Q and the fan speed N:

[0043]

[0044] Iteratively update the parameters Q and N:

[0045]

[0046] Among them, K is the number of iterations, and α is the learning rate, which is used to control the step size of parameter update to obtain the power consumption optimization function.

[0047] A safety control method

[0048] The adjustment assembly forms the operating conditions of the equipment protection module (3) according to the environmental parameters fed back by the data acquisition module (1);

[0049] When the temperature is too low, the equipment protection module (3) reduces the refrigerant flow rate and refrigeration power;

[0050] When the humidity is too high, the equipment protection module (3) reduces the defrosting cycle and defrosting frequency.

[0051] As an improvement of the present invention,

[0052] When determining the temperature,

[0053] Set the over-temperature threshold of the environmental temperature to -10°C;

[0054] When the temperature sampling detection value exceeds the over-temperature threshold, the equipment protection module (3) reduces the refrigerant flow rate and refrigeration power and enters the low-temperature start mode, indicating that the temperature is too low;

[0055] The operating power in the low-temperature start mode gradually increases from low to the stable power.

[0056] As an improvement of the present invention,

[0057] When determining the humidity,

[0058] Set the over-humidity threshold of the environmental humidity to 90% RH;

[0059] When the humidity sampling detection value exceeds the over-humidity threshold, the equipment protection module (3) reduces the defrosting cycle and defrosting frequency, indicating that the humidity is too high.

[0060] The beneficial effects of the present invention are as follows: By adopting fuzzy logic control and PID control technologies, the adaptability and stability of the system in environments with large temperature differences and low temperatures are improved. By real-time monitoring of temperature, humidity, and defrosting data, the refrigerant flow rate and defrosting cycle are dynamically adjusted, thereby improving the air-to-water production efficiency, reducing energy consumption, and extending the service life of the equipment. Description of the Drawings

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only 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. Among them:

[0062] Figure 1This is the operation logic diagram of the optimization system and safety control method for the air water maker in low-temperature and low-humidity environments of the present invention. Detailed implementation manners

[0063] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe in detail the specific implementation manners of the present invention with reference to the accompanying drawings of the specification.

[0064] Example 1

[0065] Referring to Figure 1 , this embodiment provides an optimization system for an air water maker in a low-temperature and low-humidity environment.

[0066] The optimization system for the air water maker in a low-temperature and low-humidity environment aims to improve the adaptability and stability of the water-making system in a low-temperature and low-humidity environment by intelligently adjusting the refrigerant flow rate and defrosting cycle, and achieve efficient and energy-saving air moisture collection.

[0067] The data acquisition module 1 includes a temperature sensor, a humidity sensor, and a frosting degree sensor, which can detect the ambient temperature, humidity, and frosting degree in real time. The temperature sensor and the humidity sensor respectively detect the ambient temperature and humidity, and the frosting degree sensor detects the frosting condition inside the water maker. Multiple sensors transmit the measurement data to the adjustment assembly.

[0068] The optimization adjustment module 2 includes a refrigerant flow rate regulating valve, a hot gas bypass valve, and a controller. The optimization adjustment module 2 is directly connected to the adjustment assembly, and is used to process the control signals generated by the data acquisition module 1, perform real-time analysis, generate control signals according to a preset algorithm, and be used to adjust the refrigerant flow rate and defrosting cycle.

[0069] After receiving the control signals generated by the data acquisition module 1, the optimization adjustment module 2 can analyze the environmental changes through a fuzzy logic control (FLC) strategy, adjust the opening degree of the refrigerant flow rate regulating valve to change the refrigerant flow rate. At the same time, according to the feedback of the frosting degree sensor, control the opening and closing of the hot gas bypass valve to achieve the adjustment of the defrosting cycle.

[0070] The equipment protection module 3 is composed of a flow sensor, a power sensor, and an adaptive adjustment unit, and can combine the environmental parameters fed back by the data acquisition module 1 to achieve the adaptive adjustment of the equipment flow rate and power, protect the normal operation of the equipment. The flow sensor and the power sensor respectively detect the refrigerant flow rate and the equipment power, and transmit the data to the adaptive adjustment unit. The adaptive adjustment unit adjusts the refrigerant flow rate and the equipment power according to the environmental parameters and the equipment operation status to ensure the stable operation of the equipment in a low-temperature and low-humidity environment and extend the service life of the equipment.

[0071] In the optimization system of this embodiment, the air water maker can operate efficiently and stably in a low-temperature and low-humidity environment, significantly improving the air water production efficiency while reducing energy consumption. The system realizes precise adjustment of operating parameters through an intelligent adjustment device, optimizes the water production rate and extends the service life of the equipment, providing an efficient and energy-saving air moisture collection solution for users.

[0072] In a low-temperature and low-humidity environment, the data acquisition module 1 detects that the ambient temperature is lower than the set threshold, the humidity is low, and the frosting degree is high. After receiving the control signal, the optimization adjustment module 2 reduces the opening degree of the refrigerant flow regulating valve, reduces the refrigerant flow rate, and at the same time opens the hot gas bypass valve for defrosting operation. The equipment protection module 3 adjusts the equipment power according to the feedback of the flow sensor and the power sensor to ensure the stable operation of the equipment. When the ambient temperature and humidity are appropriate, the data acquisition module 1 detects that the frosting degree is low. The optimization adjustment module 2 keeps the refrigerant flow rate stable, closes the hot gas bypass valve, and reduces the defrosting operation. The equipment protection module 3 adjusts the refrigerant flow rate and the equipment power according to the equipment operation status to achieve efficient water production.

[0073] Through the detailed description of the above embodiments, the technical solution of the present invention and its application in the optimization system of the air water maker in a low-temperature and low-humidity environment can be clearly understood.

[0074] Embodiment 2

[0075] Refer to Figure 1 , this embodiment is based on the previous embodiment, and the difference from the previous embodiment is:

[0076] The optimization adjustment module 2 includes a fuzzy logic control unit 21 and a PID control unit 22;

[0077] The fuzzy logic control unit 21 sets the refrigerant flow rate according to the data of the temperature and humidity sensing unit 11. The fuzzy logic control unit receives the data of the temperature and humidity sensing unit and the defrosting sensing unit, and analyzes through the built-in fuzzy logic algorithm. According to the change of the ambient temperature and humidity, the opening degree of the refrigerant flow regulating valve is adjusted to change the refrigerant flow rate.

[0078]

[0079] For example, when the temperature sensor detects that the ambient temperature is -5°C and the humidity sensor detects that the humidity is 80% RH, according to the table, the fuzzy logic controller will adjust the refrigerant flow rate to a high flow rate.

[0080] The fuzzy logic control unit 21 obtains the initial defrosting cycle according to the data of the defrosting sensing unit 12;

[0081]

[0082] Suppose the defrost sensor detects that the evaporator is in the "severe frosting" state, and at this time the ambient temperature is -5°C and the humidity is 90% RH. According to this table, the fuzzy logic controller will adjust the defrost cycle from the "medium cycle" to the "short cycle".

[0083] At the start of defrosting, the PID control unit 22 reads the evaporator temperature through the temperature sensor. According to the preset fixed value of the defrost end temperature, the PID control unit 22 calculates the temperature deviation value before and after defrosting. Based on the temperature deviation value, the PID control unit 22 adjusts the delay time of the initially set defrost cycle to ensure the accuracy and efficiency of the defrost operation.

[0084] The initially set defrost cycle parameters are imported into the PID control unit 22, and the PID control unit 22 is connected to the defrost control unit 24 to optimize the result of the fuzzy logic control during the defrost cycle adjustment. Taking a defrost process as an example, when defrosting starts, the evaporator temperature is -10°C, and the set defrost end temperature is 5°C. As defrosting progresses, the temperature change and the PID control adjustment process are shown in the following table.

[0085]

[0086] The device protection module 3 defines the device power consumption optimization function, including the water output model function and the power consumption model function;

[0087] The water output model function is expressed as:

[0088] W = a 1 T + a 2 H + a 3 Q + a 4 N + b

[0089] Among them, the water output is W, the temperature T, humidity H, refrigeration capacity flow Q, and fan speed N are environmental parameters, a1, a2, a3, a4 are coefficients, reflecting the influence degree of each factor on the water output, and b is a constant term.

[0090] The power consumption model function is expressed as:

[0091] P = p comp (Q) + p fan (N)

[0092] The device power consumption is P, the compressor power is Pcomp, and the fan power is Pfan.

[0093] Suppose the relationship between the compressor power and the refrigerant flow is:

[0094] P comp = c 1 Q + c 2

[0095] The relationship between the fan power and the fan speed is as follows:

[0096] P fan = c 3 N + c 4

[0097] Combining them, the power consumption formula of the equipment can be obtained:

[0098] P = c 1 Q + c 2 + c 3 N + c 4

[0099] c1, c2, c3, and c4 are correlation coefficients.

[0100] Construct the power consumption optimization function:

[0101]

[0102] Calculate the gradients of the power consumption optimization function J with respect to the refrigerant flow rate Q and the fan speed N:

[0103]

[0104] Iteratively update the parameters Q and N:

[0105]

[0106] where K is the number of iterations, and α is the learning rate, which is used to control the step size of parameter update, to obtain the power consumption optimization function. The above adaptive algorithm adjusts the system working parameters in real time according to the current operating state of the equipment and environmental changes to ensure the optimization of the water output and the equipment power consumption.

[0107] Example 3

[0108] Referring to Figure 1 , this example is based on the previous example, and the difference from the previous example is:

[0109] The data acquisition module 1 continuously monitors the environmental temperature and humidity and transmits the data to the adjustment assembly in real time. After receiving the data, the adjustment assembly analyzes and forms the operating conditions of the equipment protection module 3.

[0110] The safety control process when the temperature is too low: Set the over-temperature threshold of the environmental temperature to -10°C. When the temperature sensor detects that the environmental temperature is lower than -10°C, the equipment protection module (3) immediately reduces the refrigerant flow rate and the refrigeration power to reduce the burden on the condensation system, and the system enters the "low-temperature start mode". In this mode, the operating power gradually increases from low power to stable power to avoid the impact on the equipment caused by sudden high-power operation.

[0111] Operating parameter monitoring: Through the built-in sensors of the device, when the ambient temperature reaches the set low-temperature threshold, the system automatically activates the low-temperature protection mechanism. The refrigerant flow rate decreases from the initial 5 L / min to 3 L / min within 1 minute, and the refrigeration power decreases from 800 W to 500 W. In the low-temperature start-up mode, after the device operates at a low power for 5 minutes, the operating load is gradually increased, with the power increasing by 50 W every 2 minutes until the stable operating power of 650 W is reached.

[0112] Observation of frosting condition and device status: When the low-temperature protection function is not activated, after operating for 30 minutes, the frosting thickness on the evaporator surface reaches 3 mm, resulting in a significant decrease in heat exchange efficiency, a 30% reduction in water production efficiency, and abnormal vibration of some components due to low temperature. After activating the low-temperature protection function and operating for 1 hour, the frosting thickness on the evaporator surface is only 1 mm, the device operates smoothly, the water production efficiency is stable, and no component damage occurs.

[0113] Evaluation of the impact on device life: According to the device fatigue life calculation model, assuming that the fatigue life loss rate of key components (such as compressors) during normal operation of the device is 1% / 1000 hours. In a low-temperature environment without protection, due to frosting and abnormal stress on components, the fatigue life loss rate increases to 5% / 1000 hours. After activating the low-temperature protection function, the fatigue life loss rate is controlled within 2% / 1000 hours. Calculated based on 2000 hours of operation per year, the key components of the device are expected to be replaced every 2 years without protection, and with the low-temperature protection function, the expected service life can be extended to 5 years.

[0114] Safety control process when humidity is too high: The over-wet threshold of the ambient humidity is set at 90% RH. When the humidity sensor detects that the ambient humidity exceeds 90% RH, the device protection module 3 reduces the defrosting cycle and defrosting frequency to reduce the increased energy consumption and device wear caused by frequent defrosting.

[0115] Monitoring of defrosting cycle and frequency adjustment: In a high-humidity environment, the system automatically adjusts the defrosting cycle from 60 minutes in a normal environment to 30 minutes, and the defrosting frequency increases from once every 2 hours to once every hour. At the same time, the refrigerant flow rate is adjusted from 4 L / min to 3.5 L / min, and the compressor operating speed is reduced from 2800 r / min to 2500 r / min.

[0116] Observation of condenser frosting and water collection efficiency: When the high-humidity protection function is not activated, after operating for 1 hour, the condenser surface is severely frosted, with a frosting thickness reaching 4 mm, and the water collection efficiency is reduced by 40%. After activating the high-humidity protection function and operating for the same time, the frosting thickness on the condenser surface is controlled within 2 mm, and the water collection efficiency only decreases by 10%.

[0117] Evaluation of the impact on equipment life: In a high-humidity environment, without protection measures, due to frequent frosting and defrosting, the corrosion rate of components such as condensers will increase. After testing, the monthly corrosion thickness of the metal components of the condenser without protection increases by 0.05 mm. After the high-humidity protection function is activated, the monthly corrosion thickness increase is controlled within 0.02 mm. Calculated according to the designed service life of the condenser being 10 years (scrapped when the corrosion thickness reaches 2 mm), the condenser is expected to be replaced after 40 months without protection. With the high-humidity protection function, the expected service life can be extended to 100 months.

[0118] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A low temperature and low humidity ambient air water making machine optimization system, characterized by: include, A data acquisition module (1) detects parameters of temperature, humidity and frost and imports them into the adjustment assembly; An optimization and adjustment module (2) is connected to the adjustment assembly port and adjusts the refrigerant flow rate and defrost cycle according to the feedback parameters of the data acquisition module (1); The equipment protection module (3) is connected to the adjustment assembly port and combines the environmental parameters fed back by the data acquisition module (1) to achieve adaptive adjustment of equipment flow and power.

2. The low temperature and low humidity ambient air water making machine optimization system according to claim 1, characterized in that: The data acquisition module (1) comprises a temperature and humidity sensing unit (11) and a defrosting sensing unit (12); The temperature and humidity sensing unit (11) detects air temperature and humidity parameters, and the defrost sensing unit (12) detects frost parameters of the equipment condensation system; The temperature and humidity sensing unit (11) and the defrosting sensing unit (12) transmit data to the regulating assembly for data analysis.

3. The low temperature and low humidity environment air water making machine optimization system according to claim 1, characterized in that: The optimization adjustment module (2) is connected to the adjustment assembly; The optimization and adjustment module (2) comprises a fuzzy logic control unit (21) and a PID control unit (22); The fuzzy logic control unit (21) sets the refrigerant flow rate according to the data of the temperature and humidity sensor unit (11); The fuzzy logic control unit (21) obtains an initial defrost cycle according to data from the defrost sensor unit (12); Initially set defrost cycle parameters are introduced into the PID control unit (22), and the PID control unit (22) is connected to the defrost control unit (24).

4. The low temperature and low humidity environment air water making machine optimization system according to claim 3, characterized in that: The PID control unit (22) reads the evaporator temperature when defrosting starts; The PID control unit (22) sets a fixed temperature value when defrosting is completed; The PID control unit (22) adjusts the initial defrost cycle delay time according to the temperature deviation value before and after defrosting; The PID control unit (22) adjusts the hot gas bypass flow rate through the defrost control unit (24) according to the temperature deviation value before and after defrosting.

5. The low temperature and low humidity ambient air water making machine optimization system according to claim 4, characterized in that: The device protection module (3) defines the device power consumption optimization function, including: Water output model function and power consumption model function; The water output model function sets temperature, humidity, cooling capacity flow, and fan speed as environmental parameters, and combines the corresponding coefficients to obtain the output water volume; The power consumption model function sets the compressor power and fan power as environmental parameters to obtain the preliminary equipment power consumption.

6. The low temperature and low humidity ambient air water making machine optimization system according to claim 5, characterized in that: The refrigerant flow rate is combined with the corresponding coefficient to obtain the compressor power; The fan speed is combined with the corresponding coefficient to obtain the fan power; The actual device power consumption is obtained by combining the power consumption model function and the preliminary device power consumption.

7. The low temperature and low humidity environment air water making machine optimization system according to claim 6, characterized in that: Construct power consumption optimization function; Calculate the gradient of the power consumption optimization function with respect to the refrigerant flow rate and the fan speed; Iteratively update the refrigerant flow and fan speed parameters: By combining the number of iterations and the learning rate, the parameter update step size is controlled and the power consumption optimization function is obtained.

8. A safety control method, characterized in that: The invention comprises the low temperature and low humidity ambient air water making machine optimization system as claimed in claim 7, and The regulating assembly forms the operating conditions of the equipment protection module (3) according to the environmental parameters fed back by the data acquisition module (1); If the temperature is too low, the equipment protection module (3) reduces the refrigerant flow rate and the refrigeration power; If the humidity is too high, the equipment protection module (3) reduces the defrost cycle and defrost frequency.

9. The safety control method according to claim 8, characterized in that: When determining the temperature, Set the over-temperature threshold of the ambient temperature to -10°C; If the temperature sampling detection value exceeds the over-temperature threshold, the equipment protection module (3) reduces the refrigerant flow and refrigeration power and enters the low-temperature start-up mode, then the temperature is too low; In low temperature start-up mode, the operating power gradually increases from low to stable power.

10. The safety control method according to claim 9, characterized in that: When determining humidity, Set the over-humidity threshold of the ambient humidity to 90% RH; If the humidity sampling detection value exceeds the over-humidity threshold, the equipment protection module (3) reduces the defrosting cycle and defrosting frequency, and the humidity is too high.

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