Intelligent control method and system for rotating wheel dehumidification unit and storage medium

Abstract

The intelligent control method comprises the steps that a plurality of sensors and frequency converters are installed and used for monitoring the air temperature and humidity, the moisture content and the front-back pressure difference of a fresh air filter in real time; regulating and controlling the rotating speed of an air feeder, the rotating speed of a regeneration fan and the rotating speed of a rotating wheel through a frequency converter, obtaining sensor data under corresponding rotating speeds, and establishing an air supply quantity model, a fresh air quantity model and a rotating wheel dehumidification quantity model; the power of an air feeder, the front-back pressure difference of a fresh air filter and air parameter data are collected in real time, and the current dehumidification load is calculated according to a fan air supply amount model, a fresh air amount model and a preset formula; and selecting a preset control strategy to dynamically adjust the rotating speed of the rotating wheel, the rotating speed of the regeneration fan and the regeneration temperature according to the current dehumidification load and / or the rotating wheel dehumidification amount model so as to realize indoor humidity control. Start and stop can be automatically controlled and the dehumidification amount can be matched according to the actual wet load, excessive dehumidification or idle work is avoided, and the dehumidification efficiency is improved through multi-parameter cooperative control.

Description

Technical Field

[0001] The present invention relates to the technical field of dehumidification energy-saving control, in particular to an intelligent control method, system and storage medium for a rotary dehumidification unit. Background Art

[0002] The basic principle of rotary dehumidification is that during the process of using a solid adsorbent for moisture absorption, the regenerated adsorbent after moisture absorption is synchronously regenerated and dehydrated, so that the solid adsorbent can be recycled, and the entire moisture absorption work can be carried out continuously, overcoming the disadvantages that static solid adsorption cannot continuously dehumidify and refrigeration condensation dehumidification is powerless under low temperature and low humidity conditions, and can exert its characteristics of continuous stability and large amount of dehumidification under low temperature and low humidity conditions.

[0003] At present, the control of the dehumidification capacity of the rotary dehumidification unit air handling unit in the market mainly focuses on the regulation of the regeneration temperature. During most of the actual operation time of the rotary dehumidification unit, the dehumidification performance coefficient of the rotary wheel is relatively low, or the efficiency of the rotary wheel is relatively low. Moreover, the existing control strategies basically only adjust the dehumidification capacity by increasing or decreasing the regeneration temperature. This control method has an unsatisfactory effect on the regulation of indoor humidity, and there are often situations of excessive dehumidification or no dehumidification. In particular, under the working conditions where indoor dehumidification is not required, the regeneration fan and the rotary wheel still consume electric energy to do useless work, and cannot automatically control the start and stop and match the dehumidification capacity according to the actual indoor moisture load, which causes a large amount of energy waste.

[0004] That is, the existing intelligent control methods for rotary dehumidification units have problems of high energy consumption and low efficiency. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides an intelligent control method for a rotary dehumidification unit, which includes the following steps: installing a plurality of sensors and frequency converters for real-time monitoring of air temperature and humidity, moisture content, and pressure difference before and after the fresh air filter. The sensors at least include a fresh air parameter sensor, an air parameter sensor before the front surface cooler and after the rear surface cooler, a supply air parameter sensor, a return air parameter sensor, an air parameter sensor after steam heating, an exhaust air parameter sensor, and a fresh air filter differential pressure sensor. The frequency converters at least include a supply fan frequency converter, a regeneration fan frequency converter, and a rotary wheel frequency converter;

[0006] Regulating the rotation speeds of the supply fan, the regeneration fan, and the rotary wheel through the frequency converters, obtaining and establishing a supply air volume model, a fresh air volume model, and a rotary wheel dehumidification capacity model based on the sensor data at the corresponding rotation speeds;

[0007] Real-time collecting the supply fan power, the pressure difference before and after the fresh air filter, and the air parameter data, and calculating the current dehumidification load according to the supply air volume model of the fan, the fresh air volume model, and a preset formula;

[0008] According to the current dehumidification load and / or the rotary wheel dehumidification capacity model, a preset control strategy is selected to dynamically adjust the rotary wheel speed, the regeneration fan speed, and the regeneration temperature to achieve indoor humidity control.

[0009] Optionally, the preset control strategy at least includes a no-load control mode, a low-load control mode, a standard-load control mode, and a high-load control mode;

[0010] If the current dehumidification load is less than the preset dehumidification load minimum value, the no-load control mode is selected;

[0011] If the current dehumidification load is greater than or equal to the preset dehumidification load maximum value, the maximum regeneration temperature and the optimal rotary wheel speed corresponding to the current dehumidification load are obtained, the regeneration fan speed is calculated according to the rotary wheel dehumidification capacity model, and the preset control strategy is selected according to the regeneration fan speed;

[0012] If the regeneration fan speed is less than or equal to the first preset minimum speed, the low-load control mode is selected;

[0013] If the regeneration fan speed is between the first preset minimum speed and the first preset maximum speed, the standard-load control mode is selected;

[0014] If the regeneration fan speed is greater than or equal to the first preset maximum speed, the high-load control mode is selected.

[0015] Optionally, in the no-load control mode, the regeneration fan, the rotary wheel, and the regeneration heating valve are turned off;

[0016] In the low-load control mode, the regeneration fan operates at the first preset minimum speed, the rotary wheel operates at the optimal rotary wheel speed, and the indoor return air dew point is controlled by regeneration temperature proportional-integral control;

[0017] In the standard-load control mode, the rotary wheel operates at the optimal rotary wheel speed, the regeneration temperature remains at the maximum value, and the indoor return air dew point is controlled by regeneration fan speed proportional-integral control;

[0018] In the high-load control mode, the rotary wheel operates at the optimal rotary wheel speed, the regeneration fan operates at the first preset maximum speed, and the indoor return air dew point is controlled by regeneration temperature proportional-integral control.

[0019] Optionally, the optimal rotary wheel speed is determined according to the comparison result and the preset speed after comparing the current dehumidification load with the preset range;

[0020] If the current dehumidification load is within the first preset range, the optimal runner speed is the first preset runner speed; if the current dehumidification load is within the second preset range, the optimal runner speed is the first preset runner speed; if the current dehumidification load is within the third preset range, the optimal runner speed is the third preset runner speed; if the current dehumidification load is within the fourth preset range, the optimal runner speed is the fourth preset runner speed; if the current dehumidification load is within the fifth preset range, the optimal runner speed is the fifth preset runner speed.

[0021] Optionally, the mathematical expression of the air supply volume model is specifically as follows:

[0022] Qs = (a1 * N 2 + b1 * N + c1)P 2 +(a2 * N 2 + b2 * N + c2)P + (a3 *

[0023] N 2 + b3 * N + c3);

[0024] Among them, Qs is the air supply volume, N is the speed of the air supply fan, P is the real-time power of the air supply fan, and a1, b1, c1, a2, b2, c2, a3, b3, c3 are all model coefficients;

[0025] The mathematical expression of the fresh air volume model is specifically as follows:

[0026] Qx = (a1 * Δp 2 + b1 * Δp + c1)P 2 +(a2 * Δp 2 + b2 * Δp + c2)P +

[0027] (a3 * Δp 2 + b3 * Δp + c3);

[0028] Among them, Qx is the fresh air volume, and Δp is the pressure difference before and after the fresh air filter;

[0029] The mathematical expression of the runner dehumidification capacity model is specifically as follows:

[0030] D = aS 2 + bT 2 + cN′ 2 + dST + eSN′ + fTN′ + gS + hT + iN′ + j;

[0031] Among them, D is the runner dehumidification capacity, S is the runner speed, N′ is the speed of the regeneration fan, T is the regeneration temperature, and a, b, c, d, e, f, g, h, i, and j are all model coefficients.

[0032] Optionally, calculating the current dehumidification load according to the fan air supply volume model, fresh air volume model and a preset formula, at least including the following steps:

[0033] Calculating the air supply volume and fresh air volume according to the fan air supply volume model and the fresh air volume model;

[0034] Calculating the return air volume according to the air supply volume and the fresh air volume;

[0035] Calculating the current dehumidification load according to the return air volume and the preset formula.

[0036] Optionally, the air parameter data includes the moisture content after the front surface cooler of the fresh air and the moisture content of the return air;

[0037] The preset formula is as follows:

[0038] D’ = Qh(d1 - dsp) + Qx(d2 - dsp);

[0039] Wherein, D’ is the current dehumidification load, Qh is the return air volume, d1 is the moisture content of the return air, dsp is the preset value of the moisture content of the return air, Qx is the fresh air volume, and d2 is the moisture content after the front surface cooler of the fresh air;

[0040] d1 is obtained through the return air parameter sensor, and d2 is obtained through the air parameter sensor after the front surface cooler.

[0041] Optionally, the fresh air parameter sensor is used to monitor the temperature, humidity and moisture content of outdoor fresh air, the air parameter sensor after the front surface cooler is used to monitor the temperature, humidity and moisture content after the front surface cooler, the air supply parameter sensor is used to monitor the temperature, humidity, dew point and moisture content of the air supply, the return air parameter sensor is used to monitor the temperature, humidity, dew point and moisture content of the return air, the air parameter sensor after steam heating is used to monitor the regeneration temperature after the steam heater, the exhaust air parameter sensor is used to monitor the temperature and moisture content of the exhaust air, and the fresh air filter differential pressure sensor is used to monitor the differential pressure before and after the fresh air filter; the fan frequency converter is used to regulate the speed of the fan, the regeneration fan frequency converter is used to regulate the speed of the regeneration fan, and the runner frequency converter is used to regulate the speed of the runner.

[0042] Corresponding to the intelligent control method of the rotary wheel dehumidification unit, the present invention provides an intelligent control system for a rotary wheel dehumidification unit, which includes:

[0043] A monitoring module, which installs a plurality of sensors and frequency converters, and is used to monitor the air temperature, humidity, moisture content and the differential pressure before and after the fresh air filter in real time. The sensors at least include a fresh air parameter sensor, an air parameter sensor after the front surface cooler, an air supply parameter sensor, a return air parameter sensor, an air parameter sensor after steam heating, an exhaust air parameter sensor and a fresh air filter differential pressure sensor, and the frequency converters at least include a fan frequency converter, a regeneration fan frequency converter and a runner frequency converter;

[0044] A model establishment module, which is used to regulate the rotational speeds of the supply fan, the regeneration fan and the runner through a frequency converter, obtain the sensor data at the corresponding rotational speeds, and establish a supply air volume model, a fresh air volume model and a runner dehumidification capacity model;

[0045] A data acquisition module, which is used to collect the power of the supply fan, the pressure difference before and after the fresh air filter and the air parameter data in real time, and calculate the current dehumidification load according to the supply air volume model of the fan, the fresh air volume model and a preset formula;

[0046] An intelligent control module, which is used to select a preset control strategy according to the current dehumidification load and / or the runner dehumidification capacity model, and dynamically adjust the rotational speed of the runner, the rotational speed of the regeneration fan and the regeneration temperature, so as to realize the indoor humidity control.

[0047] In addition, to achieve the above object, the present invention also provides a computer-readable storage medium, on which a runner dehumidification unit intelligent control program is stored. When the runner dehumidification unit intelligent control program is executed by a processor, the steps of the runner dehumidification unit intelligent control method as described above are realized.

[0048] By installing a plurality of sensors and frequency converters, the present invention monitors the air temperature and humidity, moisture content and the pressure difference before and after the fresh air filter in real time, and combines the supply air volume model, the fresh air volume model and the runner dehumidification capacity model to dynamically adjust the rotational speed of the runner, the rotational speed of the regeneration fan and the regeneration temperature, thereby realizing the precise control of the indoor humidity. Compared with the prior art, the present invention can not only automatically control the start and stop and match the dehumidification capacity according to the actual moisture load, avoiding over-dehumidification or useless work, but also improves the dehumidification efficiency and reduces the energy consumption through multi-parameter collaborative control, effectively solving the problems of high energy consumption and low efficiency existing in the prior art of the intelligent control method for runner dehumidification units.

[0049] By setting four control modes of no load, low load, standard load and high load, the present invention can automatically switch the control mode according to the current dehumidification load, realizing the refined control of different moisture load conditions. This flexible mode switching avoids the problems of energy consumption waste and inaccurate control caused by the fixed control strategy in the prior art, and at the same time optimizes the operation state of the equipment, further reducing the energy consumption.

[0050] Under different load modes, through specific control strategies, such as turning off the regeneration fan and the runner in the no-load mode to avoid useless work, operating the regeneration fan at the minimum rotational speed in the low-load mode and controlling the return air dew point through proportional-integral control to ensure the dehumidification effect while reducing the energy consumption, and dynamically adjusting the optimal rotational speeds of the runner and the regeneration fan in the standard load and high load modes to ensure the efficient operation of the equipment, the present invention realizes the balance between energy saving and efficient dehumidification.

[0051] By comparing the current dehumidification load with a preset range, the present invention dynamically determines the optimal rotational speed of the rotary wheel, further improving the dehumidification efficiency and control accuracy. This method of dynamically adjusting the rotational speed of the rotary wheel ensures that the equipment operates in an optimal state, avoiding energy consumption waste caused by a fixed rotational speed. At the same time, segmented control improves the control accuracy and energy efficiency.

[0052] By establishing an air supply volume model, a fresh air volume model, and a rotary wheel dehumidification volume model, the present invention realizes the precise prediction and control of the equipment operation parameters. The introduction of mathematical models makes the prediction of equipment operation parameters more precise, providing a scientific basis for dynamic adjustment. At the same time, the comprehensive analysis of multiple parameters ensures the comprehensiveness and effectiveness of the control strategy.

[0053] By collecting the power of the air supply fan, the pressure difference before and after the fresh air filter, and air parameter data in real time, the present invention calculates the current dehumidification load, providing reliable data support for dynamic adjustment. Real-time monitoring and calculation ensure the precise grasp of the moisture load, avoiding control errors caused by insufficient monitoring. The dynamic adjustment based on real-time data improves the response speed and accuracy of control.

[0054] By calculating the current dehumidification load through a preset formula, the present invention further improves the accuracy of calculation and the scientific nature of control. The preset formula comprehensively considers parameters such as the return air volume, fresh air volume, and moisture content, ensuring the reliability of the calculation result. Based on the accurate calculation result, the control strategy is dynamically adjusted to further optimize the equipment operation state.

[0055] By the collaborative work of multiple sensors and frequency converters, the present invention realizes the comprehensive monitoring of air parameters and the precise control of equipment operation. The setting of multiple sensors ensures the comprehensive monitoring of air parameters, and the introduction of frequency converters realizes the precise control of equipment operation. The collaborative optimization of multiple parameters ensures that the equipment can operate efficiently under different working conditions. Description of the Drawings

[0056] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0057] Figure 1 is a flow diagram of an embodiment of the intelligent control method for the rotary wheel dehumidification unit of the present invention;

[0058] Figure 2 is a framework diagram of an embodiment of the intelligent control system for the rotary wheel dehumidification unit of the present invention. Detailed Embodiments

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0060] As Figure 1 shown, an intelligent control method for a rotary wheel dehumidification unit of the present invention includes the following steps: installing a plurality of sensors and frequency converters for real-time monitoring of air temperature and humidity, moisture content, and pressure difference before and after the fresh air filter. The sensors at least include a fresh air parameter sensor, an air parameter sensor behind the front surface cooler, a supply air parameter sensor, a return air parameter sensor, an air parameter sensor after steam heating, an exhaust air parameter sensor, and a fresh air filter differential pressure sensor. The frequency converters at least include a supply fan frequency converter, a regeneration fan frequency converter, and a rotary wheel frequency converter;

[0061] Adjusting the speeds of the supply fan, regeneration fan, and rotary wheel through the frequency converters, obtaining and establishing a supply air volume model, a fresh air volume model, and a rotary wheel dehumidification volume model based on the sensor data at the corresponding speeds;

[0062] Real-time collecting the power of the supply fan, the pressure difference before and after the fresh air filter, and air parameter data, and calculating the current dehumidification load according to the supply air volume model of the fan, the fresh air volume model, and a preset formula;

[0063] Selecting a preset control strategy to dynamically adjust the rotary wheel speed, regeneration fan speed, and regeneration temperature according to the current dehumidification load and / or the rotary wheel dehumidification volume model to achieve indoor humidity control.

[0064] By installing a plurality of sensors and frequency converters, the present invention can real-time monitor air temperature and humidity, moisture content, and pressure difference before and after the fresh air filter, and dynamically adjust the rotary wheel speed, regeneration fan speed, and regeneration temperature in combination with the supply air volume model, fresh air volume model, and rotary wheel dehumidification volume model, thereby achieving precise control of indoor humidity. Compared with the prior art, the present invention can not only automatically control the start and stop and match the dehumidification volume according to the actual wet load, avoiding over-dehumidification or useless work, but also improve the dehumidification efficiency and reduce energy consumption through multi-parameter coordinated control, effectively solving the problems of high energy consumption and low efficiency existing in the intelligent control method of the existing rotary wheel dehumidification unit.

[0065] In this embodiment, the preset control strategies at least include a no-load control mode, a low-load control mode, a standard-load control mode, and a high-load control mode;

[0066] If the current dehumidification load is less than the minimum value of the preset dehumidification load, the no-load control mode is selected;

[0067] If the current dehumidification load is greater than or equal to the maximum value of the preset dehumidification load, obtain the maximum regeneration temperature and the optimal runner speed corresponding to the current dehumidification load, calculate the regeneration fan speed according to the runner dehumidification amount model, and select the preset control strategy according to the regeneration fan speed;

[0068] If the regeneration fan speed is less than or equal to the first preset minimum speed, the low-load control mode is selected;

[0069] If the regeneration fan speed is between the first preset minimum speed and the first preset maximum speed, the standard-load control mode is selected;

[0070] If the regeneration fan speed is greater than or equal to the first preset maximum speed, the high-load control mode is selected.

[0071] Preferably, the minimum value of the preset dehumidification load can be 0 or a number slightly larger than 0 (which can be specifically set according to actual needs). The closer the minimum value of the preset dehumidification load is to 0, the more stringent the conditions for entering the no-load mode are.

[0072] In this embodiment, the maximum regeneration temperature is determined according to the temperature of the steam.

[0073] Preferably, the first preset minimum speed and the first preset maximum speed of the regeneration fan are determined by the equipment operating parameters of the regeneration fan.

[0074] By setting four control modes of no-load, low-load, standard-load and high-load, the present invention can automatically switch the control mode according to the current dehumidification load, realizing the refined control of different wet-load conditions. This flexible mode switching avoids the problems of energy consumption waste and inaccurate control caused by the fixed control strategy in the prior art, optimizes the equipment operation state, and further reduces the energy consumption.

[0075] In this embodiment, in the no-load control mode, the regeneration fan, the runner and the regeneration heating valve are turned off;

[0076] In the low-load control mode, the regeneration fan runs at the first preset minimum speed, the runner runs at the optimal runner speed, and the indoor return air dew point is controlled by the proportional-integral control of the regeneration temperature;

[0077] In the standard-load control mode, the runner runs at the optimal runner speed, the regeneration temperature remains at the maximum value, and the indoor return air dew point is controlled by the proportional-integral control of the regeneration fan speed;

[0078] In the high-load control mode, the runner runs at the optimal runner speed, the regeneration fan runs at the first preset maximum speed, and the indoor return air dew point is controlled by the proportional-integral control of the regeneration temperature.

[0079] It should be noted that the regeneration temperature proportional integral is calculated by comparing the error (difference) between the return air dew point (actual value) and the set value of the current chamber. Calculation logic: If the return air dew point of the current chamber is higher than the set value, it indicates that the moisture load removed by the rotary wheel at this time is insufficient, that is, the dehumidification capacity of the rotary wheel is insufficient, and the regeneration temperature needs to be increased; if the return air dew point of the current chamber is lower than the set value, the moisture load removed by the rotary wheel at this time is excessive, that is, the dehumidification capacity of the rotary wheel is too strong, and the regeneration temperature needs to be decreased to avoid excessive dehumidification. The greater the error of the proportional part of the regeneration temperature, the greater the amplitude of adjusting the regeneration temperature; the longer the time for the integral part of the error to accumulate, the greater the adjusting amplitude will also be to eliminate the long-term deviation.

[0080] The proportional integral of the regeneration fan speed is calculated by comparing the error between the return air dew point of the current chamber and the set value. Calculation logic: If the return air dew point of the current chamber is higher than the set value, it indicates that the speed of the regeneration fan needs to be increased to discharge the moisture of the fresh air absorbed by the rotary wheel to the outside through the regeneration fan; if the return air dew point of the current chamber is lower than the set value, it indicates that the fan speed needs to be decreased to reduce the discharge speed of moisture and avoid excessive dehumidification. The greater the error of the proportional part of the regeneration fan speed, the greater the adjustment amplitude of the fan speed; the longer the time for the integral part of the error to accumulate, the greater the adjustment amplitude of the fan speed will also be to eliminate the long-term deviation.

[0081] In different load modes, the present invention realizes the balance between energy saving and efficient dehumidification through specific control strategies, such as shutting down the regeneration fan and the rotary wheel in the no-load mode to avoid useless work, operating the regeneration fan at the minimum speed in the low-load mode and controlling the return air dew point through proportional integral to ensure the dehumidification effect while reducing energy consumption, and dynamically adjusting the optimal rotary wheel speed and regeneration fan speed in the standard load and high-load modes to ensure the efficient operation of the equipment.

[0082] In this embodiment, the optimal rotary wheel speed is determined according to the comparison result and the preset speed after comparing the current dehumidification load with the preset range;

[0083] If the current dehumidification load is within the first preset range, the optimal rotary wheel speed is the first preset rotary wheel speed; if the current dehumidification load is within the second preset range, the optimal rotary wheel speed is the first preset rotary wheel speed; if the current dehumidification load is within the third preset range, the optimal rotary wheel speed is the third preset rotary wheel speed; if the current dehumidification load is within the fourth preset range, the optimal rotary wheel speed is the fourth preset rotary wheel speed; if the current dehumidification load is within the fifth preset range, the optimal rotary wheel speed is the fifth preset rotary wheel speed.

[0084] It can be understood that the first preset rotary wheel speed < the second preset rotary wheel speed < the third preset rotary wheel speed < the fourth preset rotary wheel speed < the fifth preset rotary wheel speed, and the specific values can be preset according to actual needs.

[0085] Preferably, the first preset range is: greater than or equal to the minimum preset dehumidification load and less than or equal to the preset first initial load value; the second preset range is greater than the preset first initial load value and less than or equal to the preset second initial load value; the third preset range is greater than the preset second initial load value and less than or equal to the preset third initial load value; the fourth preset range is greater than or equal to the preset third initial load value and less than or equal to the preset fourth initial load value; the fifth preset range is greater than or equal to the preset fourth initial load value and less than or equal to the preset fifth initial load value.

[0086] It can be understood that the preset first initial load value < the preset second initial load value < the preset third initial load value < the preset fourth initial load value < the preset fifth initial load value, and the specific values can be preset according to actual needs.

[0087] By comparing the current dehumidification load with the preset range, the present invention dynamically determines the optimal rotational speed of the runner, further improving the dehumidification efficiency and control accuracy. This way of dynamically adjusting the rotational speed of the runner ensures that the equipment operates in an optimal state, avoids energy consumption waste caused by a fixed rotational speed, and at the same time, the segmented control improves the control accuracy and energy efficiency.

[0088] In this embodiment, the mathematical expression of the air supply volume model is specifically as follows:

[0089] Qs = (a1 * N 2 + b1 * N + c1)P 2 +(a2 * N 2 + b2 * N + c2)P + (a3 *

[0090] N 2 + b3 * N + c3);

[0091] Wherein, Qs is the air supply volume, N is the rotational speed of the air supply fan, P is the real-time power of the air supply fan, and a1, b1, c1, a2, b2, c2, a3, b3, c3 are all model coefficients;

[0092] The mathematical expression of the fresh air volume model is specifically as follows:

[0093] Qx = (a1 * Δp 2 + b1 * Δp + c1)P 2 +(a2 * Δp 2 + b2 * Δp + c2)P +

[0094] (a3 * Δp 2 + b3 * Δp + c3);

[0095] Wherein, Qx is the fresh air volume, and Δp is the pressure difference before and after the fresh air filter;

[0096] The mathematical expression of the wheel dehumidification capacity model is specifically as follows:

[0097] D = aS 2 + bT 2 + cN′ 2 + dST + eSN′ + fTN′ + gS + hT + iN′ + j;

[0098] Among them, D is the wheel dehumidification capacity, S is the wheel rotation speed, N′ is the rotation speed of the regeneration fan, T is the regeneration temperature, and a, b, c, d, e, f, g, h, i, and j are all model coefficients.

[0099] It should be noted that all model coefficients are obtained by using the data processing methods provided by existing AI tools (the data processing methods are generated by existing AI tools according to the provided air supply fan rotation speed, regeneration fan rotation speed, wheel rotation speed, sensor data at the corresponding rotation speed, and the establishment requirements of the air supply volume model, fresh air volume model, and wheel dehumidification capacity model), and further using statistical software (the sklearn library of Python) for multiple regression analysis to fit the above model coefficients.

[0100] For example, the data processing methods provided by the existing AI tools mainly include the following steps:

[0101] 1) Data preprocessing

[0102] Missing value processing: Check the integrity of the provided data and delete or fill in the missing values (such as filling with the mean or median).

[0103] Outlier processing: Use box plots, Z - score, or IQR methods to identify outliers and correct or delete them according to the situation.

[0104] 2) Exploratory data analysis (EDA)

[0105] Visualization analysis: Plot scatter plots of the wheel dehumidification capacity D against the variables (wheel rotation speed, regeneration fan rotation speed, and regeneration temperature) to observe potential trends (linear, non - linear); plot a correlation heat map between variables and calculate the Pearson / Spearman correlation coefficient.

[0106] Multicollinearity test: Calculate the variance inflation factor (VIF). If VIF > 10, it indicates severe collinearity and needs to be processed (such as removing variables or performing principal component analysis).

[0107] 3) Model construction

[0108] Multiple linear regression:

[0109] Model form:

[0110] D = aX2 +bY 2 +cZ 2 +dXY + eXZ + fYZ + gX + hY + iZ + j; where X represents the rotational speed of the runner, Y represents the rotational speed of the regeneration fan, and Z represents the regeneration temperature;

[0111] Estimate the model parameters (a, b, c, d, e, f, g, h, i, and j) using the least squares method; determine whether each parameter is significant through t-tests and p-values (usually p-value < 0.05).

[0112] Evaluate the model:

[0113] R 2 (Coefficient of determination): Measures the ability of the model to explain the data (the closer the value is to 1, the stronger the explanatory power of the model).

[0114] Adjusted R 2 : Consider the adjustment of the number of variables on R 2 to avoid overfitting.

[0115] F-test: Tests the overall significance of the model (p-value < 0.05 indicates that the model is overall significant).

[0116] 4) Model diagnosis and validation

[0117] Residual analysis: Plot a scatter plot of the residuals (the difference between the actual value and the predicted value) against the predicted value to check whether the residuals are randomly distributed (homoscedasticity).

[0118] Q-Q plot: Plot the Q-Q plot of the residuals to check whether the residuals follow a normal distribution (whether the points are close to the diagonal).

[0119] Cross-validation:

[0120] Divide the data into a training set (e.g., 70%) and a test set (e.g., 30%); train the model on the training set and validate the generalization ability of the model on the test set; calculate MSE and RMSE to evaluate the accuracy of the model prediction.

[0121] 5) Model determination and interpretation

[0122] Finally, select the model with high R 2 , small cross-validation error, and residuals that satisfy the assumptions.

[0123] Output the final mathematical expression, such as:

[0124] D = 2.1X 2 + 0.8Y 2 + 1.2Z 2 − 0.3XY + 0.5XZ + 2.5YZ + 0.7X − 1.3Y + 0.6Z + 2.4;

[0125] Coefficient meaning: "When X increases by 1 unit, while keeping other variables constant, Z increases by an average of 0.7 units"; the coefficients of quadratic terms (such as X2) and interaction terms (such as XY) represent the non-linear relationship or interaction between variables.

[0126] The other data processing steps (S15, S28) of the present invention are similar to the above process and can all be achieved through existing technologies, so they will not be elaborated.

[0127] The present invention realizes the accurate prediction and control of equipment operation parameters by establishing an air supply volume model, a fresh air volume model, and a rotary dehumidification capacity model. The introduction of the mathematical model makes the prediction of equipment operation parameters more accurate, provides a scientific basis for dynamic adjustment, and at the same time, the comprehensive analysis of multiple parameters ensures the comprehensiveness and effectiveness of the control strategy.

[0128] In this embodiment, by changing the rotational speed of the air supply fan, the corresponding air supply fan power, air supply volume, fresh air volume, and pressure difference before and after the fresh air filter (hereinafter referred to as pressure difference) at different rotational speeds are obtained; then, based on the above data, a mathematical model of air supply volume with respect to fan power and fan speed, and a mathematical model of fresh air volume with respect to fan power and pressure difference are established.

[0129] Specifically, establishing the air supply volume model and the fresh air volume model at least includes the following steps:

[0130] S11. Fix the rotational speed of the air supply fan at the maximum rotational speed of the air supply fan and fully open the air supply valve;

[0131] S12. Measure the air supply volume and fresh air volume with a handheld hot-wire anemometer, record the real-time power of the air supply fan through the air supply fan frequency converter, and record the pressure difference before and after the fresh air filter through the fresh air filter pressure difference sensor;

[0132] S13. Adjust the opening degree of the air supply valve, fix the rotational speed of the air supply fan at the minimum rotational speed of the air supply fan, and repeat step S12 to obtain the air supply volume, fresh air volume, real-time power, and pressure difference of the fan at the minimum rotational speed of the air supply fan;

[0133] S14. According to the minimum rotational speed and the maximum rotational speed of the air supply fan, preset three fixed rotational speeds of the air supply fan according to a linear relationship, and respectively adjust the opening degree of the air supply valve, and repeat step S12 to obtain the corresponding air supply volume, fresh air volume, real-time power, and pressure difference of the fan at the three fixed rotational speeds of the air supply fan;

[0134] S15. Perform data processing on the data obtained in S12 - S14 to obtain a mathematical model of air supply volume with respect to the real-time power of the air supply fan and the fan rotational speed, and a mathematical model of fresh air volume with respect to the real-time power of the air supply fan and the pressure difference before and after the fresh air filter.

[0135] Preferably, both the maximum speed and the minimum speed of the air supply fan are determined by the equipment operating parameters of the air supply fan and the minimum fresh air volume in the room.

[0136] In this embodiment, establishing the wheel dehumidification capacity model includes at least the following steps:

[0137] S21. Fix the speed of the regeneration fan at the maximum speed of the air supply fan, and keep the opening degree of the chilled water valve of the front surface cooler unchanged;

[0138] S22. Fix the speed of the wheel at the maximum speed of the wheel (determined by the equipment operating parameters of the wheel), and fix the speed of the regeneration fan at the first preset maximum speed;

[0139] S23. By adjusting the regeneration temperature, record the changes in air parameters at different regeneration temperatures. The data to be recorded includes at least the moisture content of the fresh air, the moisture content of the exhaust air, the regeneration temperature, and the regeneration air volume;

[0140] S24. Fix the speed of the wheel at the maximum speed of the wheel, fix the speed of the regeneration fan at the first preset minimum speed, and repeat step S23;

[0141] S25. Fix the speed of the wheel at the maximum speed of the wheel. According to the first preset maximum speed and the first preset minimum speed, preset three fixed speeds of the regeneration fan according to a linear relationship, and repeat step S23;

[0142] S26. Fix the speed of the wheel at the minimum speed of the wheel, fix the speed of the regeneration fan at the first preset maximum speed, and repeat step S23;

[0143] S27. Fix the speed of the regeneration fan at the first preset maximum speed. According to the maximum speed and the minimum speed of the wheel, preset three fixed speeds of the wheel according to a linear relationship, and repeat step S23;

[0144] S28. Process the data obtained in S23 - S27 to obtain a mathematical model of the wheel dehumidification capacity with respect to the regeneration temperature, the regeneration fan speed, and the wheel speed.

[0145] In this embodiment, calculating the current dehumidification load according to the air supply fan model, the fresh air volume model, and the preset formula includes at least the following steps:

[0146] Calculate the air supply volume and the fresh air volume according to the air supply fan model and the fresh air volume model;

[0147] Calculate the return air volume according to the air supply volume and the fresh air volume;

[0148] Calculate the current dehumidification load according to the return air volume and the preset formula.

[0149] In this embodiment, the air parameter data includes the moisture content of the fresh air after the front surface cooler and the moisture content of the return air;

[0150] The preset formula is as follows:

[0151] D’ = Qh(d1 - dsp) + Qx(d2 - dsp);

[0152] Wherein, D’ is the current dehumidification load, Qh is the return air volume, d1 is the moisture content of the return air, dsp is the preset value of the moisture content of the return air, Qx is the fresh air volume, and d2 is the moisture content of the fresh air before the surface cooler and after the surface cooler;

[0153] d1 is obtained through the return air parameter sensor, and d2 is obtained through the air parameter sensor before and after the surface cooler.

[0154] It can be understood that the fresh air volume + the return air volume = the supply air volume, so the return air volume Qh = Qs - Qx.

[0155] The present invention calculates the current dehumidification load by collecting the data of the power of the supply fan, the pressure difference before and after the fresh air filter, and the air parameter data in real time, providing reliable data support for dynamic adjustment. Real-time monitoring and calculation ensure the accurate grasp of the wet load, avoiding control errors caused by insufficient monitoring. The dynamic adjustment based on real-time data improves the response speed and accuracy of control.

[0156] In this embodiment, the fresh air parameter sensor is used to monitor the temperature, humidity and moisture content of the outdoor fresh air, the air parameter sensor before and after the surface cooler is used to monitor the temperature, humidity and moisture content before and after the surface cooler, the supply air parameter sensor is used to monitor the temperature, humidity, dew point and moisture content of the supply air, the return air parameter sensor is used to monitor the temperature, humidity, dew point and moisture content of the return air, the air parameter sensor after steam heating is used to monitor the regeneration temperature after the steam heater, the exhaust air parameter sensor is used to monitor the temperature and moisture content of the exhaust air, and the fresh air filter differential pressure sensor is used to monitor the pressure difference before and after the fresh air filter; the supply fan frequency converter is used to regulate the speed of the supply fan, the regeneration fan frequency converter is used to regulate the speed of the regeneration fan, and the runner frequency converter is used to regulate the speed of the runner.

[0157] Through the collaborative work of a variety of sensors and frequency converters, the present invention realizes the comprehensive monitoring of air parameters and the precise control of equipment operation. The setting of a variety of sensors ensures the comprehensive monitoring of air parameters, the introduction of frequency converters realizes the precise control of equipment operation, and the collaborative optimization of multiple parameters ensures the efficient operation of the equipment under different working conditions.

[0158] Such as Figure 2As shown in the figure, the present invention also correspondingly provides an intelligent control system for a rotary wheel dehumidification unit, which includes: a monitoring module 10, which installs a plurality of sensors and frequency converters, and is used to monitor the air temperature and humidity, moisture content, and the pressure difference before and after the fresh air filter in real time. The sensors at least include a fresh air parameter sensor, an air parameter sensor after the front surface cooler and before the rear surface cooler, a supply air parameter sensor, a return air parameter sensor, an air parameter sensor after steam heating, an exhaust air parameter sensor, and a pressure difference sensor for the fresh air filter;

[0159] A model establishment module 20, which is used to regulate the rotational speeds of the supply fan, the regeneration fan, and the rotary wheel through the frequency converter, obtain the sensor data at the corresponding rotational speeds, and establish a supply air volume model, a fresh air volume model, and a rotary wheel dehumidification volume model;

[0160] A data acquisition module 30, which is used to collect the power of the supply fan, the pressure difference before and after the fresh air filter, and the air parameter data in real time, and calculate the current dehumidification load according to the supply air volume model of the fan, the fresh air volume model, and a preset formula;

[0161] An intelligent control module 40, which is used to select a preset control strategy according to the current dehumidification load and / or the rotary wheel dehumidification volume model, and dynamically adjust the rotational speed of the rotary wheel, the rotational speed of the regeneration fan, and the regeneration temperature to achieve indoor humidity control.

[0162] The embodiment of the present invention also provides a computer-readable storage medium. The computer-readable storage medium can be the computer-readable storage medium included in the memory in the above embodiment; it can also exist independently and is not assembled into the device. At least one instruction is stored in the computer-readable storage medium, and the instruction is loaded and executed by a processor to implement Figure 1 the intelligent control method for the rotary wheel dehumidification unit shown in the figure. The computer-readable storage medium can be a read-only memory, a magnetic disk, an optical disc, etc.

[0163] It should be noted that the various embodiments in this specification are all described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same and similar parts among the various embodiments can be referred to each other. For the system embodiment and the storage medium embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment.

[0164] Also, in this document, the terms "comprise", "include" or any other variation thereof are intended to cover non-exclusive inclusion, such that a process, method, article or apparatus that comprises a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or apparatus. Without further limitation, an element qualified by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or apparatus that comprises the element.

[0165] The above description illustrates and describes the preferred embodiments of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be altered within the scope of the inventive concept herein through the above teachings or the skills or knowledge in the relevant field. Any alterations and changes made by those skilled in the art that do not depart from the spirit and scope of the present invention shall fall within the protection scope of the appended claims of the present invention.

Claims

1. A method for intelligent control of a rotary dehumidifier unit, characterized in that: The following steps are involved: Install multiple sensors and frequency converters for real-time monitoring of air temperature and humidity, moisture content, and pressure difference before and after the fresh air filter. The sensors include at least a fresh air parameter sensor, a front surface cooling air parameter sensor, a supply air parameter sensor, a return air parameter sensor, a steam heating air parameter sensor, an exhaust air parameter sensor, and a fresh air filter pressure difference sensor. The frequency converter includes at least a supply fan frequency converter, a regeneration fan frequency converter, and a rotor frequency converter; The speed of the supply fan, the regeneration fan and the rotor are controlled by the frequency converter, and the air supply volume model, the fresh air volume model and the rotor dehumidification volume model are established by obtaining and using the sensor data at the corresponding speed; Collect the fan power, pressure difference before and after the fresh air filter and air parameter data in real time, and calculate the current dehumidification load according to the fan air volume model, fresh air volume model and preset formula; According to the current dehumidification load and / or the wheel dehumidification capacity model, a preset control strategy is selected to dynamically adjust the wheel speed, regeneration fan speed and regeneration temperature to achieve indoor humidity control.

2. The intelligent control method of a rotary dehumidifier unit according to claim 1, characterized in that: The preset control strategy includes at least a no-load control mode, a low-load control mode, a standard load control mode and a high-load control mode; If the current dehumidification load is less than the preset minimum dehumidification load, the no-load control mode is selected; If the current dehumidification load is greater than or equal to the preset maximum dehumidification load, the optimal rotor speed corresponding to the maximum regeneration temperature and the current dehumidification load is obtained, the regeneration fan speed is calculated according to the rotor dehumidification capacity model, and the preset control strategy is selected according to the regeneration fan speed; If the regeneration fan speed is less than or equal to the first preset minimum speed, the low load control mode is selected; If the regeneration fan speed is between the first preset minimum speed and the first preset maximum speed, the standard load control mode is selected; If the regeneration fan speed is greater than or equal to the first preset maximum speed, the high load control mode is selected.

3. The intelligent control method of the rotary dehumidifier unit according to claim 2 is characterized in that: In no-load control mode, turn off the regeneration fan, rotor and regeneration heating valve; In the low load control mode, the regeneration fan is operated at the first preset minimum speed, the rotor is operated at the optimal rotor speed, and the indoor return air dew point is controlled by the regeneration temperature proportional integral; In the standard load control mode, the rotor is operated at the optimal rotor speed, the regeneration temperature is kept at the maximum value, and the indoor return air dew point is controlled by the proportional integral of the regeneration fan speed; In the high load control mode, the rotor is operated at the optimal rotor speed, the regeneration fan is operated at the first preset maximum speed, and the indoor return air dew point is controlled by the regeneration temperature proportional integral.

4. The intelligent control method of a rotary dehumidifier unit according to claim 3, characterized in that: The optimal wheel speed is determined by comparing the current dehumidification load with the preset range and based on the comparison result and the preset speed; If the current dehumidification load is within the first preset range, the optimal wheel speed is the first preset wheel speed; if the current dehumidification load is within the second preset range, the optimal wheel speed is the first preset wheel speed; if the current dehumidification load is within the third preset range, the optimal wheel speed is the third preset wheel speed; if the current dehumidification load is within the fourth preset range, the optimal wheel speed is the fourth preset wheel speed; if the current dehumidification load is within the fifth preset range, the optimal wheel speed is the fifth preset wheel speed.

5. The intelligent control method of a rotary dehumidifier unit according to claim 1, characterized in that: The mathematical expression of the air supply model is as follows: <h2 style=";text-align:left;direction:ltr">Qs=(a1*N<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +b1*N+c1)P<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +(a2*N<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +b2*N+c2)P+(a3* N 2 +b3*N+c3); Among them, Qs is the air supply volume, N is the speed of the blower, P is the real-time power of the blower, and a1, b1, c1, a2, b2, c2, a3, b3, and c3 are all model coefficients; The mathematical expression of the fresh air volume model is as follows: Qx=(a1*Δp 2 +b1*Δp+c1)P 2 +(a2*Δp 2 +b2*Δp+c2)P+ (a3*Δp 2 +b3*Δp+c3); Among them, Qx is the fresh air volume, Δp is the pressure difference before and after the fresh air filter; The mathematical expression of the rotary dehumidification capacity model is as follows: D=aS 2 +bT 2 +cN′ 2 +dST+eSN′+fTN′+gS+hT+iN′+j; Wherein, D is the dehumidification capacity of the rotor, S is the rotor speed, N′ is the regeneration fan speed, T is the regeneration temperature, and a, b, c, d, e, f, g, h, i and j are all model coefficients.

6. The intelligent control method of a rotary dehumidifier unit according to claim 1, characterized in that: Calculating the current dehumidification load according to the fan air supply volume model, the fresh air volume model and the preset formula includes at least the following steps: Calculate the supply air volume and fresh air volume based on the fan supply air volume model and fresh air volume model; Calculate the return air volume based on the supply air volume and fresh air volume; Calculate the current dehumidification load based on the return air volume and the preset formula.

7. The intelligent control method of a rotary dehumidifier unit according to claim 6, characterized in that: Air parameter data include humidity content before fresh air and after surface cooling and humidity content of return air; The preset formula is as follows: D'=Qh(d1-dsp)+Qx(d2-dsp); Where D' is the current dehumidification load, Qh is the return air volume, d1 is the return air humidity, dsp is the return air humidity preset value, Qx is the fresh air volume, d2 is the fresh air humidity before and after cooling; d1 is obtained through the return air parameter sensor, and d2 is obtained through the front-end cooling rear air parameter sensor.

8. The intelligent control method of a rotary dehumidifier unit according to claim 1, characterized in that: The fresh air parameter sensor is used to monitor the temperature, humidity and moisture content of the outdoor fresh air. The air parameter sensor after front surface cooling is used to monitor the temperature, humidity and moisture content after front surface cooling. The supply air parameter sensor is used to monitor the supply air temperature, humidity, dew point and moisture content. The return air parameter sensor is used to monitor the return air temperature, humidity, dew point and moisture content. The air parameter sensor after steam heating is used to monitor the regeneration temperature after the steam heater. The exhaust air parameter sensor is used to monitor the exhaust air temperature and moisture content. The fresh air filter pressure difference sensor is used to monitor the pressure difference before and after the fresh air filter; the supply fan inverter is used to control the speed of the supply fan, the regeneration fan inverter is used to control the speed of the regeneration fan, and the rotor inverter is used to control the speed of the rotor.

9. An intelligent control system for a rotary dehumidifier unit, characterized in that: include: A monitoring module, which is equipped with multiple sensors and frequency converters for real-time monitoring of air temperature and humidity, moisture content, and pressure difference before and after the fresh air filter. The sensors include at least a fresh air parameter sensor, a front surface cooling air parameter sensor, a supply air parameter sensor, a return air parameter sensor, a steam heating air parameter sensor, an exhaust air parameter sensor, and a fresh air filter pressure difference sensor. The frequency converter includes at least a blower frequency converter, a regeneration blower frequency converter, and a rotor frequency converter; A model building module is used to control the speed of the supply fan, the speed of the regeneration fan and the speed of the rotor through the frequency converter, and to obtain and establish the supply air volume model, the fresh air volume model and the rotor dehumidification volume model through the sensor data at the corresponding speed; The data acquisition module is used to collect the power of the fan, the pressure difference before and after the fresh air filter, and the air parameter data in real time, and calculate the current dehumidification load according to the fan air volume model, the fresh air volume model and the preset formula; The intelligent control module is used to select a preset control strategy to dynamically adjust the wheel speed, regeneration fan speed and regeneration temperature according to the current dehumidification load and / or the wheel dehumidification capacity model to achieve indoor humidity control.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a rotary dehumidifier unit intelligent control program, and when the rotary dehumidifier unit intelligent control program is executed by the processor, the steps of the rotary dehumidifier unit intelligent control method according to any one of claims 1 to 8 are implemented.

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