Intelligent humidification method and device for air-cooled outdoor unit

Abstract

The invention relates to the field of air-cooled outdoor units, in particular to an intelligent humidification method and device for an air-cooled outdoor unit. Environmental parameters are obtained, and whether the outdoor unit meets humidification conditions or not is judged according to the environmental parameters; when the outdoor unit meets the humidifying condition, working parameters of the outdoor unit are generated according to the environment parameters, and the working parameters are used for controlling the humidifying end to humidify the outdoor unit to reach the preset target humidity; humidity change parameters of the outdoor unit are obtained in real time, and the deviation value between the current humidity and the target humidity is calculated according to the humidity change parameters; generating compensation data of the working parameters according to the deviation value; and adjusting the working parameters based on the compensation data. By calculating the deviation value between the humidity and the target humidity, the humidification amount is automatically adjusted, humidity fluctuation caused by external environment changes or sensor errors is compensated, and it is ensured that the indoor humidity is always kept within a comfortable range.

Description

Technical Field

[0001] The present application relates to the technical field of air-cooled outdoor units, and in particular to an intelligent humidification method and device for an air-cooled outdoor unit. Background Art

[0002] The humidification system of the air-cooled outdoor unit is usually used to adjust the air humidity under specific environmental conditions to ensure the stability and comfort of indoor temperature and humidity control. When the air-cooled system is running, the external air exchanges heat and moisture through the air-cooled unit. Sometimes it is necessary to adjust the humidity by humidification. By adding a spray module at the air inlet of the outdoor unit, the humidity of the air can be increased before it enters the condenser. This humidification method can effectively increase the indoor air humidity and improve the operation effect of the air conditioner through proper design and control, especially in dry environments.

[0003] In the temperature and humidity control system of the air-cooled room, the existing technology usually relies on the internal sensor of the external unit to detect the humidity of the outdoor air, and adjust the humidification amount or perform dehumidification operation accordingly. However, this approach has some significant defects. First, the humidity sensor inside the external unit is usually located at the air inlet of the external unit to directly monitor the humidity exchanged with the outdoor air. However, the external humidity sensor may be affected by airflow, temperature fluctuations, equipment location, etc., resulting in inaccurate measurement results. This sensor error will cause the system to misjudge the actual indoor humidity. Secondly, the response to humidity changes is usually not immediate. It is necessary to add atomized humidified air at the air inlet to increase the humidity before the air enters the condenser. Therefore, when the system adjusts the humidification or dehumidification amount, there may be a certain lag in the change of humidity level. The reasons for this hysteresis effect include the working delay of the humidification or dehumidification equipment, the propagation process of moisture in the air, and the response time after the equipment is adjusted. The existence of hysteresis may cause a certain deviation between the actual humidity and the target humidity after the humidity is adjusted. For example, when a humidifier is turned on, the indoor humidity level will not change immediately within a short period of time. This lag may cause the humidity control system to "overcompensate" or "undercompensate" for a period of time, resulting in humidity fluctuations and increasing the difficulty of control.

[0004] Therefore, the prior art has defects and needs to be improved. Summary of the invention

[0005] In order to solve one or several problems in the prior art, the main purpose of the present application is to provide an intelligent humidification method and device for an air-cooled outdoor unit.

[0006] In order to achieve the above-mentioned invention object, the present application proposes an intelligent humidification method for an air-cooled outdoor unit, the method comprising:

[0007] Acquire environmental parameters, and determine whether the external unit meets the humidification condition according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate;

[0008] When the external machine meets the humidification conditions, the working parameters of the external machine are generated according to the environmental parameters, and the working parameters are used to control the humidification end to humidify the external machine to reach a preset target humidity;

[0009] Acquire the humidity change parameter of the outdoor unit in real time, and calculate the deviation value between the current humidity and the target humidity according to the humidity change parameter;

[0010] generating compensation data of the working parameter according to the deviation value;

[0011] The operating parameter is adjusted based on the compensation data.

[0012] The embodiment of the present application also provides an intelligent humidification device for an air-cooled outdoor unit, comprising:

[0013] An acquisition module, used for acquiring environmental parameters, and judging whether the external unit meets the humidification condition according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate;

[0014] A first generating module is used to generate working parameters of the external machine according to the environmental parameters when the external machine meets the humidification conditions, and the working parameters are used to control the humidification end to humidify the external machine to reach a preset target humidity;

[0015] A calculation module, used for obtaining the humidity change parameter of the outdoor unit in real time, and calculating the deviation value between the current humidity and the target humidity according to the humidity change parameter;

[0016] A second generating module, used for generating compensation data of the working parameter according to the deviation value;

[0017] An adjustment module is used to adjust the operating parameters based on the compensation data.

[0018] The present application also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0019] The present application also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0020] The intelligent humidification method and device of the air-cooled outdoor unit of the embodiment of the present application dynamically determines whether the humidification conditions are met by accurately obtaining parameters such as the external temperature, humidity and air flow rate. This process avoids unnecessary humidification operations and ensures that the humidification function is only started when environmental conditions require it. Based on the real-time humidity changes and deviation values, the system generates corresponding working parameters and accurately adjusts the humidification amount by calculating compensation data. This method ensures the efficiency and accuracy of the humidification process and avoids excessive or insufficient humidification that may occur in traditional systems. By calculating the deviation value between the humidity and the target humidity, the humidification amount is automatically adjusted to compensate for humidity fluctuations caused by changes in the external environment or sensor errors, ensuring that the indoor humidity is always maintained within a comfortable range. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A schematic flow chart of an intelligent humidification method for an air-cooled outdoor unit according to an embodiment of the present application;

[0022] Figure 2 A schematic flow chart of an intelligent humidification method for an air-cooled outdoor unit according to an embodiment of the present application;

[0023] Figure 3 This is a schematic block diagram of the structure of an intelligent humidification device for an air-cooled outdoor unit according to an embodiment of the present application;

[0024] Figure 4 A schematic block diagram of the structure of a computer device according to an embodiment of the present application.

[0025] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0027] Reference Figure 1 In an embodiment of the present application, a smart humidification method for an air-cooled outdoor unit is provided, the method comprising:

[0028] S1. Acquire environmental parameters, and determine whether the external unit meets the humidification conditions according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate;

[0029] S2. When the external machine meets the humidification conditions, the operating parameters of the external machine are generated according to the environmental parameters, and the operating parameters are used to control the humidification end to humidify the external machine to reach a preset target humidity;

[0030] S3, obtaining the humidity change parameter of the outdoor unit in real time, and calculating the deviation value between the current humidity and the target humidity according to the humidity change parameter;

[0031] S4, generating compensation data of the working parameter according to the deviation value;

[0032] S5. Adjust the operating parameters based on the compensation data.

[0033] As described in the above steps S1-S3, environmental parameters include temperature, humidity and air flow rate, etc., which are key data used to describe external environmental conditions. By obtaining these parameters, the system can determine whether the current environment is suitable for humidification operation. These data help the system determine whether to start the humidification system. For example, if the outside temperature is too high or the humidity is too low, the humidification system needs to be started to prevent the indoor environment from becoming too dry, thereby maintaining comfort and equipment safety. Temperature, humidity and air flow rate are core indicators of air quality, and they directly affect the demand for humidification. For example, in dry winter or in places where air conditioners work frequently, the air humidity is usually low, and the humidity needs to be increased to improve air comfort. Changes in air flow rate can also affect the efficiency of air exchange, thereby affecting the demand for humidification. Whether the outdoor unit needs humidification is determined by a series of environmental parameters (such as outdoor temperature, humidity and flow rate). The system will only start the humidification function when the environmental parameters meet a specific threshold. Avoid unnecessary humidification operations, save energy, and improve system efficiency. When it is determined that humidification is needed, the system will generate a set of working parameters based on environmental parameters such as temperature, humidity and air flow rate. These operating parameters guide the specific operation of the humidification end, such as humidification amount, humidification intensity, etc., so as to achieve the preset target humidity during the operation of the outdoor unit. The generated operating parameters can accurately control the operating state of the humidification end to ensure that the humidity is within the predetermined range, thereby providing a comfortable indoor environment. Changes in environmental parameters directly affect the control of air humidity in the outdoor unit. When the temperature or humidity changes, the control system must adjust the humidification amount according to the current environmental data. For example, a higher air flow rate may accelerate the change of humidity, so the humidification amount needs to be increased; when the temperature is high, the evaporation rate is faster, and more humidification may also be required.

[0034] As described in the above steps S4-S5, the humidity change parameter refers to the real-time change data of the humidity inside the outdoor unit. These data reflect the deviation of the humidity inside the outdoor unit from the current value to the target value, as well as the speed and trend of the humidity change. By monitoring the humidity change in real time, the current humidity can be accurately calculated, reducing the error caused by the interference of the humidity sensor. This can ensure that the humidity adjustment process is more sensitive and efficient. The outdoor unit directly exchanges heat and humidity with the outdoor air, and the humidity and temperature changes in the external environment may cause large fluctuations in indoor humidity. Since the sensor in the outdoor unit may cause measurement errors due to factors such as air flow and temperature changes, obtaining the humidity change parameter can help the system more accurately calculate the adjustment required for humidification and avoid inaccuracies caused by sensor errors. By calculating the deviation between the current humidity and the target humidity, the system can know whether the current humidity adjustment has reached the predetermined target. The deviation value represents the direction and amplitude that the humidity control system needs to correct. The deviation value serves as feedback to help the control system understand the accuracy of the humidity adjustment for subsequent compensation adjustments. This process makes the humidification control more accurate and avoids deviations from the target humidity. The target value of humidity may be affected by fluctuations in the external environment. By calculating the deviation between humidity and target humidity, the system can adjust the humidification amount in real time to keep the indoor humidity at the most suitable level. For example, during the humidification process, the system may encounter a situation where the humidity is too low or too high, and the deviation value can correct this problem in time. Compensation data is the adjustment data generated after calculating the humidity deviation value, which is used to correct the working parameters. That is, according to the current humidity deviation, the operating state of the humidification equipment is automatically adjusted to achieve accurate humidification. Compensation data can compensate for the influence of sensor errors or other external interferences, ensure that the humidity reaches the target value, and improve the stability and accuracy of the system. Since the humidity measurement of the air-cooled outdoor unit may be affected by factors such as air flow rate and temperature, compensation data helps to correct the response of the humidification system to avoid inaccurate humidity adjustment due to sensor errors, so as to better achieve the target humidity. The compensation function can also reduce the risk of over- or under-humidification and provide more stable control. The system adjusts the working parameters in real time based on the compensation data to accurately control the humidification amount. This process is based on the aforementioned humidity deviation to ensure that the humidification operation continues to adapt to environmental changes. Dynamically adjust working parameters to ensure that the humidification process is not too fast or too slow, avoid increased energy consumption or excessive humidity due to over-humidification, and ensure a comfortable air environment.

[0035] As mentioned above, by accurately obtaining parameters such as external temperature, humidity, and air flow rate, it is dynamically determined whether the humidification conditions are met. This process avoids unnecessary humidification operations and ensures that the humidification function is only started when environmental conditions require it. Based on real-time humidity changes and deviation values, the system generates corresponding working parameters and accurately adjusts the humidification amount by calculating compensation data. This method ensures the efficiency and accuracy of the humidification process and avoids excessive or insufficient humidification that may occur in traditional systems. By calculating the deviation value between the humidity and the target humidity, the humidification amount is automatically adjusted to compensate for humidity fluctuations caused by changes in the external environment or sensor errors, ensuring that the indoor humidity is always maintained in a comfortable range.

[0036] It is worth mentioning that the addition of a humidification function to the outdoor unit of an air-cooled air conditioner is to release moisture through a spray system. For example, ultrasonic atomization, a spray pump, or a water cooling plate system can be used to spray water mist or water vapor into the air flowing through the condenser. This process can increase the moisture in the air and bring the moisture into the room through the airflow. During the humidification process, the moisture needs to be fully in contact with the air, and excessive moisture should be avoided to affect the heat exchange efficiency of the outdoor unit. The position of the air inlet and the spray port can be optimized by design to ensure that the water mist is evenly distributed in the air flow. Special attention should be paid to the control of the spray volume to avoid excessive moisture adhering to the surface of the condenser and affecting the heat dissipation effect. Specifically, first, a water tank needs to be added to the outdoor unit or connected to an external water source. Water is led to the humidification module through a pipe. A nozzle (such as an ultrasonic atomization nozzle or a high-pressure nozzle) is designed at the air inlet to atomize and spray the water into the incoming air flow. This ensures that the air entering the outdoor unit is humidified, thereby affecting the indoor humidity. Then, the intelligent microcontroller can automatically adjust the humidification amount according to the data of the external humidity sensor to avoid over-humidification or under-humidification.

[0037] Reference Figure 2 In one embodiment, after the step of adjusting the operating parameters based on the compensation data, the method comprises:

[0038] S51, obtaining historical environmental data;

[0039] S52, identifying environmental change characteristics according to the historical environmental data, including humidity change cycles and humidity change patterns;

[0040] S53, obtaining future meteorological data, inputting the current environmental parameters, meteorological data and environmental change characteristics into a preset prediction model, and predicting future environmental parameters through the prediction model;

[0041] S54, obtaining historical working parameters corresponding to the historical environment data, and establishing a mapping relationship between the historical working parameters and the historical environment data according to the historical working parameters and the historical environment data;

[0042] S55. Generate working parameters corresponding to the predicted environmental parameters according to the mapping relationship and the predicted environmental parameters.

[0043] As described in the above steps, by collecting historical environmental data (such as external temperature and humidity in the past certain period of time), basic data is provided for subsequent analysis. The collection of historical data helps to understand the working performance of the system and the humidification requirements under different environmental conditions. Through a large amount of historical data, the prediction model can better learn the relationship between the environment and humidification, and improve the accuracy of the prediction. For environmental features that cannot be collected in real-time data (such as humidity changes under extreme weather conditions), historical data can be used as a supplement to avoid unstable performance of the system in unknown environments. Identify environmental change characteristics, including the periodicity and regularity of humidity changes. By analyzing the humidity change pattern in historical data, the time periodicity and regularity of environmental changes can be extracted. The humidity change cycle refers to the fluctuation law of humidity level over time, while the humidity change law is the fixed pattern of humidity as external meteorological conditions change. By identifying the periodic change law of humidity, the system can predict the humidity change trend in advance, such as seasonal changes, day and night changes, etc., and then adjust the response strategy of the humidification system. The identification of humidity change law can help avoid misjudgment, especially in environmental conditions with obvious periodic changes (such as tropical climate or monsoon climate), it can more reasonably judge whether humidification is needed. If the system detects that humidity changes significantly in the fall and winter every year, the prediction model will automatically learn this pattern, so that the humidification strategy can be adjusted more accurately during this period. By obtaining meteorological data (such as weather forecast information, temperature and humidity data for the next few hours or days), the system is provided with expectations of future environmental changes. This data usually comes from meteorological service providers and covers key information such as temperature, humidity, and precipitation. Combining meteorological forecast data with real-time and historical data, the system can predict future environmental changes and adjust humidification parameters in advance to cope with upcoming humidity fluctuations. For example, if it is predicted that humidity will suddenly increase in the future, the system can reduce the amount of humidification to avoid wasting energy, or prevent over-humidification. Assuming that the meteorological data for the next week predicts that there will be large-scale precipitation, the system can predict the trend of increasing air humidity, thereby reducing unnecessary humidification and saving energy. By inputting current environmental parameters, meteorological data, and identified environmental change characteristics into a preset prediction model, the system can predict environmental parameters (such as future humidity, temperature, etc.) for a certain period in the future. The model may be based on machine learning algorithms, such as regression analysis, time series prediction, and other technologies. Through the prediction of future environment by machine learning model, the system can flexibly adjust the humidification strategy in a dynamically changing environment and improve the accuracy of humidification control. Accurate prediction of future environmental parameters means that the system can take action before the environment changes, thereby maximizing comfort and efficiency. If the prediction model recognizes that dry weather is about to occur (humidity drops sharply), it will increase the humidification amount in advance to avoid the discomfort caused by the dry environment.Obtain the correspondence between historical environmental data and actual system operating parameters (such as the working intensity of the humidification system at a specific humidity), and establish a mapping relationship between historical environment and working parameters. This helps the system understand which specific working parameters the humidification system should adopt under certain specific environmental conditions. Through historical data mapping, the system can accurately know how to adjust the humidification parameters in a specific environment to achieve the best results. Through the mapping of historical data, the system can avoid over-humidification and ensure that humidification is only performed when necessary, thereby saving energy. In the historical data, if it is found that the humidifier working intensity is 50% when the temperature is 25°C and the humidity is 40%, the system can automatically select this working parameter in similar environments. By matching the historical environmental data with the corresponding working parameters, a mapping relationship is established, which helps to predict the required working parameters under similar environmental conditions. The mapping relationship is usually learned and optimized through data analysis or machine learning algorithms. The mapping relationship can provide support for real-time adjustments to ensure that the system can operate according to the optimal strategy under each environmental condition. The automated mapping relationship eliminates the need for manual adjustments, improves the automation level of the system, and reduces the complexity of manual intervention. For example, when the system learns that the humidifier needs to operate at 60% power when the humidity is 45%, the system will automatically match this mapping relationship and implement the corresponding humidification operation. After obtaining the mapping relationship between historical working parameters and environmental data and the predicted environmental parameters, the system generates corresponding working parameters based on the predicted environmental parameters. This enables the system to quickly and accurately adjust the working state of the humidification equipment in the face of future environmental conditions. The system can make advance adjustments based on future environmental forecasts to reduce adaptability problems caused by sudden environmental changes. Adjusting working parameters in advance helps avoid excessive or low humidity and improve indoor comfort. If the ambient humidity is predicted to drop, the system will generate an appropriate humidification intensity based on the historical mapping relationship to ensure that the humidity is always in the optimal range.

[0044] In one embodiment, after the step of generating working parameters corresponding to the predicted environmental parameters according to the mapping relationship and the predicted environmental parameters, the method includes:

[0045] Acquire environmental data in real time, and verify whether the predicted environmental data has errors based on the environmental data;

[0046] When there is no error in the predicted environmental data, the humidification end is controlled to humidify the external unit based on the working parameters corresponding to the predicted environmental parameters;

[0047] When an error occurs in the predicted environmental data, compensation data is generated according to the current environmental parameters and the predicted working parameters;

[0048] The predicted operating parameter is adjusted based on the compensation data.

[0049] As mentioned above, by acquiring environmental data in real time, the system can dynamically monitor changes in the external environment, ensure that the operation of the humidification equipment responds to the current environmental conditions in a timely manner, and avoid system failure caused by hysteresis or environmental changes. Error detection helps to determine the accuracy of the model and whether error correction or compensation is required. By comparing the predicted data with the actual data, the system can identify the deviation of the prediction model and take corresponding measures to correct it, so as to avoid inaccurate working parameters caused by prediction errors and affect the humidification effect. For example: Suppose the system predicts that the humidity of a certain environmental area will reach 75% in the next 10 minutes, but the real-time data obtained shows 72%. At this time, the system needs to verify whether the predicted data deviates from the actual situation, so as to make corresponding error corrections. If the difference between the predicted environmental data and the actual environmental data is small after verification, the predicted environmental parameters can be directly used to control the humidification equipment. This means that the prediction model is relatively accurate and can continue to operate according to the original prediction parameters without making too many adjustments. Under accurate prediction environmental parameters, the adjustment time and energy consumption of the system are minimized, and the response efficiency of the humidification system is improved. At the same time, instability caused by frequent adjustments can be avoided. For example, when the predicted humidity is not much different from the actual humidity, the output of the humidification equipment can be adjusted directly according to the predicted value, so that the predetermined target humidity can be quickly reached to avoid over-humidification or under-humidification. When there is a significant error between the predicted data and the actual data, the system will generate compensation data based on the current environmental data and the predicted working parameters, and then adjust the working parameters. This process can correct the negative impact of the prediction error on the operation of the equipment and ensure that the humidification equipment can still operate in the optimal state. The generation of compensation data and the adjustment of working parameters can help the system self-correct and maintain the efficient operation and control accuracy of the equipment. This process can flexibly adjust the operation strategy according to the changes in the actual environmental data to avoid excessive or insufficient humidification due to prediction errors. Assuming that the system predicts that the humidity will reach 75% in the next 10 minutes, but the actual humidity suddenly rises, the system can generate compensation data based on the current humidity and predicted working parameters to adjust the output intensity of the humidification equipment to avoid excessive humidity. After generating the compensation data, the system readjusts the working parameters based on the compensation data, thereby correcting the original working settings to ensure that the operating status of the equipment is consistent with the environmental requirements. When unexpected environmental changes occur, the compensation adjustment ensures that the system can respond in time to prevent the working parameters from not matching the actual requirements. This can improve the operating efficiency of the humidification equipment and avoid waste of resources.

[0050] In one embodiment, the method of generating compensation data of the operating parameter according to the deviation value includes:

[0051] Analyzing the humidity compensation amount of the working parameter according to the deviation value;

[0052] Acquiring the humidity change parameter, and determining the humidity change rate of the outdoor unit according to the humidity change parameter;

[0053] In constructing the analysis model, the current environmental parameters, humidity change rate and humidity compensation amount are input into the analysis model, the compensation frequency corresponding to the humidity compensation amount is analyzed by the analysis model, and the analysis result is output;

[0054] Compensation data is generated based on the humidity compensation amount and the corresponding compensation frequency.

[0055] As mentioned above, in actual work, there is usually a deviation between the predicted environmental parameters and the real-time environmental data. The deviation value is a key indicator to measure the gap between the predicted and actual data. According to the deviation value, the system needs to analyze the humidity compensation amount, that is, the amount of humidification that needs to be increased or decreased, to correct this deviation and ensure that the device output matches the actual demand. By accurately analyzing the humidity compensation amount, it can effectively compensate for the impact caused by the prediction error or environmental changes, ensure that the humidity is maintained within the expected range, and avoid over-humidity or over-dryness. Assuming that the predicted humidity is 60%, but the actual measured humidity is 55%, the system will analyze how much humidification needs to be increased according to the deviation value (5%) to ensure that the humidity can be restored to the target value in time. The humidity change parameter reflects the speed and direction of change of the ambient humidity. For example, the rate of increase or decrease of humidity affects the adjustment strategy of the humidification device. If the humidity changes too quickly, the humidification device needs to respond quickly; if the change is slow, a slower adjustment method can be adopted. By accurately measuring the humidity change rate, the system can predict the change trend of humidity and adjust the humidification amount and compensation frequency accordingly. This helps to avoid excessive or insufficient humidification caused by slow or fast response. If the rate of change of external humidity is high, the system will recognize this in advance and take more frequent adjustments to respond to humidity changes in time to avoid excessive wetting or drying. The analytical model combines current environmental parameters (such as temperature, humidity), humidity change rate and humidity compensation to model the humidification needs under different conditions. This modeling can provide a multi-dimensional perspective, taking into account the interaction of multiple variables, thereby generating a more accurate compensation strategy. By building an analytical model, scientific predictions can be made for complex environmental changes to ensure that both the compensation amount and the compensation frequency can be optimally adjusted according to real-time changes. This improves the intelligence and dynamic adaptability of the system and avoids blind adjustments. For example, in an environment where humidity changes are very unstable, the analytical model can calculate the most appropriate humidification amount and adjustment frequency through real-time data input (such as humidity change rate and current ambient humidity), rather than relying solely on a single environmental data or prediction model. The compensation frequency refers to the frequency of humidification adjustment, which is closely related to the humidity change rate and humidity compensation amount. Through the analytical model, the system can determine the most suitable compensation frequency based on the humidity change rate and the current humidification demand. This frequency may change under different environmental conditions, for example, when the humidity changes quickly, frequent adjustments are required, while when the humidity changes slowly, the adjustment frequency can be reduced. By determining the compensation frequency, the system can optimize the working mode of the humidifier. Too frequent adjustments may lead to waste of resources, while too low a frequency may not be able to respond to humidity changes in time. The right compensation frequency can ensure that the system can operate efficiently without excessive energy consumption.For example, in an environment where humidity changes slowly, the system may choose to adjust the humidifier every 10 minutes, while in an environment where humidity changes rapidly, the adjustment frequency may be increased to once a minute to ensure that the humidity always remains within the ideal range. Compensation data is the input data that is ultimately used to adjust the operating parameters of the humidification device. These data are generated based on the humidity compensation amount and the compensation frequency, with the aim of ensuring that the humidification amount and the adjustment frequency match the current environmental conditions, thereby optimizing the humidification effect. The compensation data may include information such as the target humidification amount, the humidifier output frequency, and the timing of adjustment. The generation of compensation data ensures that the humidification device can automatically adjust according to the changes in the real-time environment, and the adjustment of the humidification amount and frequency can accurately match the humidity requirements. This not only improves the humidification efficiency, but also extends the service life of the equipment and avoids overworking or improper operation of the equipment. Assuming that the current environmental humidity is 50% through analysis, and the target humidity needs to be 60%, based on the humidity change rate and the humidity compensation amount, the compensation data may include humidification every 30 seconds, and the humidification amount is 3% each time. This ensures that the humidity is increased at an appropriate rate and eventually reaches the target humidity.

[0056] In one embodiment, the method of generating compensation data of the operating parameter according to the deviation value further includes:

[0057] Obtain historical humidity change parameters, and analyze the deviation between the historical humidity change parameters and the target humidity parameters according to the time series;

[0058] Extracting the change trend of the historical humidity change parameter, and determining the duration of the humidity deviation according to the change trend analysis and deviation value of the historical humidity change parameter;

[0059] generating a humidity compensation strategy according to the duration of the humidity deviation;

[0060] Compensation data is generated based on the humidity compensation strategy, the humidity compensation amount and the corresponding compensation frequency.

[0061] As mentioned above, the historical humidity change parameters reflect the changes in ambient humidity over a period of time. Through time series analysis, these parameters can reveal the laws and trends of humidity changes. By analyzing historical data, the system can more accurately understand the long-term performance of humidity deviations, thereby making more accurate compensation decisions in future adjustments. This process helps to avoid excessive or insufficient adjustments caused by short-term fluctuations and improve the stability and predictability of humidity adjustment. Humidity change trends refer to the increase or decrease rules or patterns of humidity over a certain period of time. By extracting the change trends of historical humidity change parameters, the system can understand the changing characteristics of humidity (such as whether it is steadily increasing, decreasing, or cyclically fluctuating). Combined with the humidity deviation value (the gap between the target humidity and the actual humidity), the system can analyze how long the humidity deviation will last, thereby predicting the time required for the humidity to return to the target value. Analyzing the duration of humidity deviation helps determine the priority and intensity of humidification adjustment. For example, if the humidity deviation has lasted for a long time, it means that the urgency of humidity adjustment is high and a large humidity compensation amount is required; if the deviation is short, it can be adjusted moderately to avoid excessive humidification. Assuming that historical data shows that humidity trends in certain seasons show long-term fluctuations, the system can identify these periodic fluctuations in advance, so that when humidity deviations occur, it can promptly determine their duration and decide whether to make large adjustments or only fine-tuning. The humidity compensation strategy refers to formulating specific humidification amounts and adjustment frequencies based on the duration of the humidity deviation. Humidity deviations that last longer may require a wider range of humidity compensation, while deviations that last shorter may only require slight adjustments. The humidity compensation strategy needs to consider the long-term and short-term nature of the deviation and formulate a reasonable compensation plan to achieve stable humidity control. Generating a humidity compensation strategy based on the duration of the humidity deviation can help the system make more refined adjustment decisions. If the humidity deviation lasts for a long time, the system can gradually return to the target humidity by gradually increasing the humidification amount; if the duration is short, smaller adjustment measures can be taken to reduce the impact of frequent humidifier operation on the equipment. If the system detects that the humidity deviation has lasted for 30 minutes and the trend indicates that the humidity will drop further, the compensation strategy may include increasing the humidification amount and shortening the humidification frequency until the humidity returns to the target value. Compensation data is a set of parameters that the humidifier needs to follow during operation, including humidity compensation amount, compensation frequency, humidification timing, etc. These data are based on the decision output of the humidity compensation strategy, with the purpose of accurately adjusting the humidity. By combining the duration of humidity deviation and the changing trend of the environment, the compensation data generated by the system can dynamically adjust the working mode of the equipment to ensure the efficiency and accuracy of humidity control. The generation of compensation data ensures that the humidifier is accurately adjusted according to the humidity change trend, duration and humidity compensation strategy analyzed by the system. This helps to reduce unnecessary energy consumption and adjust the humidity to the target value more quickly.Appropriate compensation data generation can also improve the response speed and adaptability of the system and ensure long-term stability of environmental humidity.

[0062] In one embodiment, the method of generating a humidity compensation strategy according to the duration of the humidity deviation includes:

[0063] Obtaining the duration of the humidity deviation;

[0064] When the duration of the humidity deviation is greater than a preset time threshold, setting an initial humidification increment for the initial stage of the humidity compensation amount;

[0065] A humidity compensation strategy is derived based on the initial humidification increment.

[0066] As mentioned above, the duration of humidity deviation refers to the time that the difference between actual humidity and target humidity exists and lasts. By obtaining this time, the system can identify the "persistence" of humidity deviation. Humidity deviations that last longer may mean that the environment has changed significantly or that the humidification system has failed to respond in time, while short-term deviations may be caused by short-term environmental fluctuations. Obtaining the duration of humidity deviation provides the basis for the system's subsequent decision-making. By analyzing this duration, it can be determined whether a larger or faster adjustment of humidity is required. For example, long-term humidity deviations may require strong intervention, while short-term deviations can be corrected by fine-tuning. When the duration of humidity deviation exceeds the preset threshold, the system will start a special adjustment mechanism to set a larger humidification increment in the initial stage. This "time threshold" is usually set according to the actual application environment or experimental data to distinguish between short-term and long-term humidity fluctuations. If the humidity deviation lasts for a long time, it means that the humidity fluctuations in the environment may be continuous and cannot be ignored, and need to be adjusted through stronger humidification intervention. By setting the initial humidification increment, the system can respond to humidity deviations more quickly and effectively, preventing excessive humidity differences from affecting environmental stability. Especially when the humidity deviation lasts for a long time, by increasing the initial humidification amount, the humidity can be restored to the target range as soon as possible, thereby avoiding the adverse effects of humidity abnormalities on the environment, equipment or personnel. Based on the initial humidification increment, the system will generate a specific humidity compensation strategy. This strategy determines the humidification method, frequency, and intensity based on the duration of the humidity deviation and the set humidification increment. Usually, when the initial humidification increment is large, the system will adopt a gradually decreasing humidification strategy to ensure that there will be no over-humidification during the humidity recovery process and to avoid frequent energy waste caused by starting the humidifier. The compensation strategy generated based on the initial humidification increment can ensure that the humidity is fully corrected when the deviation lasts for a long time. As the humidity approaches the target value, the decreasing humidification amount helps maintain system stability and reduces the possibility of over-adjustment. This strategy can not only effectively deal with long-term humidity deviations, but also avoid excessive humidity fluctuations or equipment overloads caused by overcompensation. Assume that in a humidification system, the ambient humidity in a room is already low and lasts for a long time (for example, more than 30 minutes). The system determines that this is a long-term humidity deviation and decides to start a larger humidification increment to quickly increase the humidity based on the set time threshold. This process ensures that the humidity returns to the target value quickly, avoiding long-term humidity deviations that have a negative impact on the environment (such as affecting the comfort of personnel or equipment operation). As the humidity approaches the target value, the system will reduce the humidification increment to ensure that the humidity gradually stabilizes within the target range without over-humidification causing other problems (such as over-humidification causing equipment failure).

[0067] In one embodiment, the working parameters include humidification parameters and wind speed parameters. Humidification parameters refer to key factors that control the operation of the humidification system, including humidification amount, humidification speed, humidifier type, humidification cycle, etc. These parameters determine how the system adds moisture to the environment to maintain or adjust the humidity level. The setting of humidification parameters directly affects the effect and response speed of humidity control. If the humidification amount is too large, it may cause over-humidification, resulting in excessive humidity, condensation of equipment, and even deterioration of air quality; if the humidification amount is insufficient, it may not be possible to effectively increase the humidity to the target level. The humidification amount can be the percentage of humidity increased per hour, or the volume of water vapor released per unit time; the humidification speed may include how long it takes to adjust the humidity from the current value to the target value. Adjusting these humidification parameters can finely control the humidity level. The wind speed parameter controls the speed of air flow, usually combined with the operation of air conditioners, ventilation systems, fans and other equipment, to determine the efficiency of air exchange and humidity distribution. The wind speed can be adjusted by the speed of the fan or the opening and closing degree of the vent. The wind speed parameter is crucial to the distribution and uniformity of humidity. Too low wind speed may cause moisture to accumulate in local areas, affecting the uniformity of humidity distribution. The role of humidification parameters and wind speed parameters in the humidity control system is closely related, and their cooperation can ensure that the system operates efficiently in different environments and working conditions. Reasonable adjustment of these two parameters can improve air quality, save energy and improve system stability while ensuring that the humidity accurately reaches the target.

[0068] Reference Figure 3 In an embodiment of the present application, there is also provided an intelligent humidification device for an air-cooled outdoor unit, comprising:

[0069] An acquisition module 1 is used to acquire environmental parameters and determine whether the external unit meets the humidification condition according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate;

[0070] The first generating module 2 is used to generate the working parameters of the external machine according to the environmental parameters when the external machine meets the humidification conditions, and the working parameters are used to control the humidification end to humidify the external machine to reach a preset target humidity;

[0071] A calculation module 3 is used to obtain the humidity change parameter of the outdoor unit in real time, and calculate the deviation value between the current humidity and the target humidity according to the humidity change parameter;

[0072] A second generating module 4, used to generate compensation data of the working parameter according to the deviation value;

[0073] The adjustment module 5 is used to adjust the working parameters based on the compensation data.

[0074] As described above, it can be understood that the various components of the intelligent humidification device for the air-cooled outdoor unit proposed in the present application can realize the functions of any one of the intelligent humidification methods for the air-cooled outdoor unit described above, and the specific structure will not be repeated.

[0075] Reference Figure 4 In an embodiment of the present application, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as monitoring data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an intelligent humidification method for an air-cooled outdoor unit is implemented.

[0076] The above-mentioned processor executes the above-mentioned intelligent humidification method for the air-cooled outdoor unit, including: obtaining environmental parameters, and judging whether the outdoor unit meets the humidification conditions according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate; when the outdoor unit meets the humidification conditions, generating the working parameters of the outdoor unit according to the environmental parameters, and the working parameters are used to control the humidification end to humidify the outdoor unit to reach a preset target humidity; obtaining the humidity change parameters of the outdoor unit in real time, and calculating the deviation value between the current humidity and the target humidity according to the humidity change parameters; generating compensation data for the working parameters according to the deviation value; and adjusting the working parameters based on the compensation data.

[0077] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, an intelligent humidification method for an air-cooled outdoor unit is implemented, comprising the following steps: obtaining environmental parameters, and judging whether the outdoor unit meets humidification conditions according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate; when the outdoor unit meets the humidification conditions, generating working parameters of the outdoor unit according to the environmental parameters, and the working parameters are used to control the humidification end to humidify the outdoor unit to reach a preset target humidity; obtaining humidity change parameters of the outdoor unit in real time, and calculating a deviation value between the current humidity and the target humidity according to the humidity change parameters; generating compensation data for the working parameters according to the deviation value; and adjusting the working parameters based on the compensation data.

[0078] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0079] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, device, article or method including the element.

[0080] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An intelligent humidification method for an air-cooled outdoor unit, characterized in that: The method comprises: Acquire environmental parameters, and determine whether the external unit meets the humidification condition according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate; When the external machine meets the humidification conditions, the working parameters of the external machine are generated according to the environmental parameters, and the working parameters are used to control the humidification end to humidify the external machine to reach a preset target humidity; Acquire the humidity change parameter of the outdoor unit in real time, and calculate the deviation value between the current humidity and the target humidity according to the humidity change parameter; generating compensation data of the working parameter according to the deviation value; The operating parameter is adjusted based on the compensation data.

2. The intelligent humidification method for an air-cooled outdoor unit according to claim 1, characterized in that: After the step of adjusting the operating parameters based on the compensation data, the method comprises: Access historical environmental data; Identifying environmental change characteristics based on the historical environmental data, including humidity change cycles and humidity change patterns; Acquire future meteorological data, input the current environmental parameters, meteorological data and environmental change characteristics into a preset prediction model, and predict future environmental parameters through the prediction model; Acquire historical working parameters corresponding to the historical environment data, and establish a mapping relationship between the historical working parameters and the historical environment data according to the historical working parameters and the historical environment data; According to the mapping relationship and the predicted environmental parameters, working parameters corresponding to the predicted environmental parameters are generated.

3. The intelligent humidification method for an air-cooled outdoor unit according to claim 2, characterized in that: After the step of generating working parameters corresponding to the predicted environmental parameters according to the mapping relationship and the predicted environmental parameters, the method includes: Acquire environmental data in real time, and verify whether the predicted environmental data has errors based on the environmental data; When there is no error in the predicted environmental data, the humidification end is controlled to humidify the external unit based on the working parameters corresponding to the predicted environmental parameters; When an error occurs in the predicted environmental data, compensation data is generated according to the current environmental parameters and the predicted working parameters; The predicted operating parameter is adjusted based on the compensation data.

4. The intelligent humidification method for an air-cooled outdoor unit according to claim 1, characterized in that: The method of generating compensation data of the working parameter according to the deviation value comprises: Analyzing the humidity compensation amount of the working parameter according to the deviation value; Acquiring the humidity change parameter, and determining the humidity change rate of the outdoor unit according to the humidity change parameter; In constructing the analysis model, the current environmental parameters, humidity change rate and humidity compensation amount are input into the analysis model, the compensation frequency corresponding to the humidity compensation amount is analyzed by the analysis model, and the analysis result is output; Compensation data is generated based on the humidity compensation amount and the corresponding compensation frequency.

5. The intelligent humidification method for an air-cooled outdoor unit according to claim 4, characterized in that: The method further comprises generating compensation data of the working parameter according to the deviation value: Obtain historical humidity change parameters, and analyze the deviation between the historical humidity change parameters and the target humidity parameters according to the time series; Extracting the change trend of the historical humidity change parameter, and determining the duration of the humidity deviation according to the change trend analysis and deviation value of the historical humidity change parameter; generating a humidity compensation strategy according to the duration of the humidity deviation; Compensation data is generated based on the humidity compensation strategy, the humidity compensation amount and the corresponding compensation frequency.

6. The intelligent humidification method for an air-cooled outdoor unit according to claim 4, characterized in that: The method of generating a humidity compensation strategy according to the duration of the humidity deviation comprises: Obtaining the duration of the humidity deviation; When the duration of the humidity deviation is greater than a preset time threshold, setting an initial humidification increment for the initial stage of the humidity compensation amount; A humidity compensation strategy is derived based on the initial humidification increment.

7. The intelligent humidification method for an air-cooled outdoor unit according to claim 1, characterized in that: The working parameters include humidification parameters and wind speed parameters.

8. An intelligent humidifying device for an air-cooled outdoor unit, characterized in that: include: An acquisition module, used for acquiring environmental parameters, and judging whether the external unit meets the humidification condition according to the environmental parameters, wherein the environmental parameters include temperature parameters, humidity parameters and air flow rate; A first generating module is used to generate working parameters of the external machine according to the environmental parameters when the external machine meets the humidification conditions, and the working parameters are used to control the humidification end to humidify the external machine to reach a preset target humidity; A calculation module, used for obtaining the humidity change parameter of the outdoor unit in real time, and calculating the deviation value between the current humidity and the target humidity according to the humidity change parameter; A second generating module, used for generating compensation data of the working parameter according to the deviation value; An adjustment module is used to adjust the operating parameters based on the compensation data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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