Energy-saving control method, system, medium and equipment for dehumidifier

Abstract

A dehumidifier energy-saving control method, system, medium and equipment relate to the field of dehumidification equipment. The method comprises: acquiring node position data, node air flow velocity data, node humidity data and node temperature data in space by arranging sensor nodes, and establishing an air flow model by using a fluid dynamics model in combination with three-dimensional space data. Based on the model, a moisture distribution map is generated and a target area where the moisture concentration exceeds a preset threshold is determined, and then the optimal target airflow channel is determined according to the position of the target area, and the fan is controlled to turn so that its suction direction is consistent with the airflow direction of the target airflow channel. The fan target wind speed is set according to the channel airflow speed, and the compressor operating frequency and the electronic expansion valve opening are coordinated and adjusted in combination with the target area humidity value, the target wind speed and the dehumidifier operating parameters, so as to realize precise dehumidification control based on the spatial moisture distribution, improve the dehumidification efficiency of the dehumidifier, and thus improve the energy-saving ability of the dehumidifier.

Description

Technical Field

[0001] The present application relates to the field of dehumidification equipment, and in particular to an energy-saving control method, system, medium and equipment for a dehumidifier. Background Art

[0002] In the regulation of indoor environment, the dehumidification system plays a vital role. As the core equipment, the dehumidifier processes the moisture in the air through the refrigeration system, and plays an irreplaceable role in regulating indoor humidity, improving air quality, and protecting equipment and facilities. With the development of smart home and office environment, people have higher and higher requirements for indoor air quality. How to effectively improve dehumidification efficiency and energy saving level has become an important technical challenge facing the industry.

[0003] At present, traditional dehumidifiers generally use a fixed wind direction and fixed wind speed air supply method to deal with indoor moisture. This method does not take into account the actual distribution of moisture in the space. In the prior art, due to the influence of factors such as human activities and door and window openings, the indoor air flow is complex and the moisture distribution often shows the characteristics of local accumulation. The dehumidification method with fixed wind direction and wind speed cannot deal with these moisture accumulation areas in a targeted manner, resulting in low dehumidification efficiency, which not only prolongs the dehumidification time, but also causes unnecessary energy waste. Summary of the invention

[0004] The present application provides an energy-saving control method, system, medium and equipment for a dehumidifier, which can improve the dehumidification efficiency of the dehumidifier, thereby improving the energy-saving capability of the dehumidifier.

[0005] In a first aspect, the present application provides an energy-saving control method for a dehumidifier, the method comprising:

[0006] Acquire three-dimensional spatial data in a space where a dehumidifier is located and sensor node data acquired by sensor nodes arranged in the space, wherein the sensor node data includes node position data, node air velocity data, node humidity data, and node temperature data;

[0007] Using a fluid dynamics model, combining the sensor node data and the three-dimensional space data, to establish an air flow model;

[0008] generating a moisture distribution map in the space according to the air flow model, and determining a target area where the moisture concentration exceeds a preset threshold based on the moisture distribution map;

[0009] Determine a target airflow channel for moisture transport and an airflow velocity of the target airflow channel according to the position of the target area in the air flow model, and control the direction of the fan of the dehumidifier so that the air suction direction of the fan is consistent with the airflow direction of the target airflow channel;

[0010] Determining a target wind speed of the fan according to the air flow speed of the target air flow channel, and controlling the fan to operate according to the target wind speed;

[0011] The operating parameters of the dehumidifier are obtained, and the operating frequency of the compressor and the opening of the electronic expansion valve of the dehumidifier are adjusted according to the humidity value of the target area, the target wind speed and the operating parameters.

[0012] By adopting the above technical solution, sensor nodes are arranged in the space to obtain node position data, node air velocity data, node humidity data and node temperature data, and combined with three-dimensional space data, an accurate air flow model is established using a fluid dynamics model, so that the air flow distribution state in the space can be grasped in real time. The moisture distribution map generated based on the air flow model can accurately identify the target area where the moisture concentration exceeds the preset threshold, and determine the optimal target air flow channel by analyzing the position of the target area in the air flow model. By keeping the air suction direction of the dehumidifier fan consistent with the air flow direction of the target air flow channel, and setting the target wind speed of the fan according to the air flow speed of the target air flow channel, the original air flow field in the space can be fully utilized to assist moisture transport and improve dehumidification efficiency. At the same time, the compressor operating frequency and the electronic expansion valve opening are coordinated and adjusted according to the humidity value of the target area, the target wind speed and the operating parameters of the dehumidifier, which not only ensures the dehumidification effect, but also avoids the ineffective operation of the refrigeration system, thereby achieving the purpose of energy saving and consumption reduction. Since the control method of the present application dynamically adjusts the working state of the dehumidifier based on the actual airflow distribution characteristics in the space, compared with the traditional dehumidification method with fixed wind direction and fixed wind speed, it can more efficiently deal with the problem of local moisture accumulation, and significantly improve the operating efficiency and energy saving level of the dehumidifier.

[0013] Optionally, the use of a fluid dynamics model, in combination with the sensor node data and the three-dimensional space data, to establish an air flow model includes:

[0014] Dividing the space into a preset number of regular grid units, each of the grid units having a unique three-dimensional coordinate identifier;

[0015] Mapping the sensor node data to corresponding grid cells according to the node position data;

[0016] Calculating the grid unit data of the undeployed sensor nodes based on the distance weighted interpolation method, wherein the distance weighted interpolation method includes selecting a preset number of sensor nodes closest to the target grid unit, using the inverse of the distance from each sensor node to the target grid unit as a weight coefficient, and performing weighted processing on the sensor node data of each sensor node to obtain the grid unit data of the undeployed sensor nodes;

[0017] Substituting the grid unit data into the Navier-Stokes equations to establish a fluid control equation group including a mass conservation equation and a momentum conservation equation, wherein the coefficient of the mass conservation equation is determined by the airflow velocity data of the grid unit, and the coefficient of the momentum conservation equation is determined by the airflow velocity data, temperature data and pressure data of the grid unit;

[0018] The fluid control equations are solved by a numerical iteration method to obtain a model describing the gas flow.

[0019] By adopting the above technical scheme, the space is divided into regular grid units with unique three-dimensional coordinate identifiers, and the sensor node data is accurately mapped to the corresponding grid units, which provides a basic data framework for air flow modeling. For grid units without sensor nodes, a distance-weighted interpolation method is adopted. By selecting the nearest preset number of sensor nodes and using the inverse of their distance as the weight coefficient for weighted processing, effective supplementation and smooth transition of spatial data are achieved. By substituting the complete grid unit data into the Navier-Stokes equation, a fluid control equation group including the mass conservation equation and the momentum conservation equation is established, in which the coefficient of the mass conservation equation is determined by the airflow velocity data of the grid unit, and the coefficient of the momentum conservation equation is determined by the airflow velocity data, temperature data and pressure data of the grid unit, thereby theoretically ensuring the physical accuracy of the model. Finally, the numerical iteration method is used to solve the fluid control equation group, and an air flow model that can accurately describe the characteristics of airflow movement in space is obtained, which provides a reliable theoretical basis for subsequent target area identification and control strategy optimization. This modeling method achieves discretization through grid division and data mapping, ensures data continuity through distance-weighted interpolation, and then establishes control equations based on the basic laws of fluid mechanics, ultimately obtaining an air flow model with high precision and practicality.

[0020] Optionally, generating a moisture distribution map in the space according to the air flow model includes:

[0021] Calculating the diffusion path of moisture in each grid unit based on the air flow model;

[0022] Acquire grid unit humidity data of each grid unit, and construct a moisture distribution map according to the diffusion path and the grid unit humidity data;

[0023] A continuous area in the moisture distribution map whose humidity value is higher than a preset humidity value threshold is determined as the target area.

[0024] By adopting the above technical solution, the diffusion path of moisture in each grid unit is calculated based on the air flow model, and the movement law of moisture in the space is accurately grasped. On this basis, combined with the grid unit humidity data of each grid unit, the moisture distribution map constructed according to the diffusion path and the grid unit humidity data not only reflects the humidity distribution state at the current moment, but also includes the dynamic change trend of moisture. By determining the continuous area with humidity values ​​higher than the preset humidity value threshold in the moisture distribution map as the target area, the accurate identification of moisture accumulation areas that need to be focused on is achieved. This moisture distribution analysis method based on the air flow model combines the moisture diffusion law with the measured humidity data, which not only takes into account the influence of air flow on moisture transport, but also ensures the real-time accuracy of the analysis results, providing a scientific decision-making basis for the subsequent dehumidification control strategy, so as to achieve more accurate and efficient dehumidification control.

[0025] Optionally, the calculating the diffusion path of moisture in each grid unit based on the air flow model includes:

[0026] Establishing a state parameter matrix of each grid unit based on the air flow model, wherein the state parameter matrix includes a grid temperature, a grid humidity, a grid airflow velocity, and a grid airflow direction of each grid unit;

[0027] The migration trend of moisture in each grid unit is calculated using a convection diffusion equation, wherein the convection term in the convection diffusion equation adopts the grid airflow velocity and the grid airflow direction, and the diffusion coefficient is determined according to the grid temperature of the grid unit;

[0028] Calculating the state parameter difference between adjacent grid cells according to the state parameter matrix of each of the grid cells, and calculating the boundary flux based on the state parameter difference between the adjacent grid cells, wherein the boundary flux represents the transfer rate of moisture through the grid cell interface;

[0029] A time evolution equation of moisture concentration is established according to the migration trend and the boundary flux, and the diffusion path of moisture in each grid unit is obtained by numerically solving the time evolution equation.

[0030] By adopting the above technical solution, a state parameter matrix including grid temperature, grid humidity, grid airflow velocity and grid airflow direction is established based on the air flow model, so as to achieve a complete characterization of the state of each grid unit. On this basis, the migration trend of moisture in the grid unit is calculated using the convection diffusion equation, in which the convection term uses the grid airflow velocity and grid airflow direction, and the diffusion coefficient is determined according to the grid temperature, which accurately describes the movement characteristics of moisture under the action of airflow. By calculating the difference in state parameters between adjacent grid units and determining the boundary flux based on this, the moisture transfer rate on the grid unit interface is quantified, thereby achieving an accurate characterization of the moisture transmission process across the grid. Finally, the time evolution equation of moisture concentration is established based on the migration trend and boundary flux, and the diffusion path of moisture in each grid unit is obtained by numerical solution, which not only reflects the instantaneous state of moisture diffusion, but also predicts its future change trend. This analysis method combining fluid mechanics theory and numerical calculation method can achieve an accurate grasp of the law of moisture movement in space, and provide a reliable theoretical basis for the subsequent construction of moisture distribution map and identification of target areas.

[0031] Optionally, determining a target airflow channel for moisture transport according to a position of the target area in the air flow model includes:

[0032] Acquiring airflow data at the location of the target area;

[0033] Based on the center position of the target area, sectors are divided along the radial direction within a preset radius, the angle between adjacent sectors is a preset angle value, the outer arc length of each sector is equal to the width of the air inlet of the dehumidifier, and the area of ​​each sector is set as a channel to be selected;

[0034] The air flow model is used to obtain airflow characteristic parameters in each of the channels to be selected, wherein the airflow characteristic parameters include an airflow velocity characteristic value and an airflow direction characteristic value, the airflow velocity characteristic value is the arithmetic mean of the airflow velocity detected by the sensor nodes located in the channel area to be selected, and the airflow direction characteristic value is the weighted average of the airflow directions detected by the sensor nodes located in the channel area to be selected, and the weight coefficient of the weighted average is proportional to the corresponding airflow velocity value;

[0035] Based on the airflow characteristic parameters in each of the candidate channels, each of the candidate channels is comprehensively scored to obtain a comprehensive score for each of the candidate channels, and the candidate channel with the highest comprehensive score is determined as the target airflow channel.

[0036] By adopting the above technical solution, by obtaining the airflow data at the location of the target area, and taking the center position of the target area as the reference, the sector division is performed within the preset radius, wherein the angle between adjacent sectors is the preset angle value, and the length of the outer arc of each sector is equal to the width of the air inlet of the dehumidifier. This division method ensures the matching of the selected channel and the air inlet of the dehumidifier. By using the air flow model to obtain the airflow characteristic parameters in each selected channel, including the airflow velocity characteristic value obtained by the arithmetic mean of the airflow velocity detected by the sensor node, and the airflow direction characteristic value obtained by the weighted average of the airflow direction calculated using the airflow velocity value as the weight coefficient, a comprehensive characterization of the airflow characteristics of the selected channel is achieved. The method of comprehensively scoring the airflow characteristic parameters in the selected channel and selecting the selected channel with the highest comprehensive score as the target airflow channel not only takes into account the actual characteristics of the airflow field, but also ensures that the selected channel has the optimal moisture transport conditions. This channel selection method based on sector division and airflow characteristic evaluation not only meets the working requirements of the dehumidifier, but also makes full use of the original airflow field characteristics in the space, thereby achieving more efficient moisture transport.

[0037] Optionally, determining the target wind speed of the fan according to the air flow speed of the target air flow channel includes:

[0038] If the air flow speed is less than the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the preset reference wind speed, wherein the preset reference wind speed is the air inlet speed of the dehumidifier under rated working conditions;

[0039] If the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the difference between the preset reference wind speed and the airflow speed.

[0040] By adopting the above technical solution, the air inlet speed of the dehumidifier under rated working conditions is set to the preset reference wind speed, and the target wind speed of the fan is dynamically adjusted based on this. When the airflow speed of the target airflow channel is less than the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the preset reference wind speed, ensuring that the dehumidifier has sufficient air intake to maintain the basic dehumidification effect; when the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the difference between the preset reference wind speed and the airflow speed. This setting method makes full use of the existing airflow speed in the space, and the insufficient wind speed is supplemented by the fan, which not only ensures the dehumidification effect, but also avoids the additional power consumption of the fan. This wind speed adjustment method based on the comparison of airflow speed and preset reference wind speed achieves the optimal matching of the fan operation state and the airflow characteristics of the space, while ensuring the dehumidification effect and minimizing energy consumption.

[0041] Optionally, the operating parameters include the surface temperature of the heat exchanger, the inlet and outlet temperature difference of the heat exchanger, the high and low pressure values ​​of the system, the exhaust temperature of the compressor and the superheat of the refrigerant; and adjusting the compressor operating frequency and the opening of the electronic expansion valve of the dehumidifier according to the humidity value of the target area, the target wind speed and the operating parameters includes:

[0042] When the humidity value of the target area is greater than the first preset threshold value, if the exhaust temperature of the compressor is lower than the second preset threshold value, and the high and low pressure values ​​of the system are within the preset range, the operating frequency of the compressor is increased and the opening of the electronic expansion valve is reduced, wherein the increase in the operating frequency of the compressor is determined according to the target wind speed and the inlet and outlet temperature difference of the heat exchanger, and the decrease in the opening of the electronic expansion valve is determined according to the superheat of the refrigerant; if the exhaust temperature of the compressor is higher than the second preset threshold value, or the high and low pressure values ​​of the system exceed the preset range, the operating frequency of the compressor is reduced and the opening of the electronic expansion valve is increased, wherein the decrease in the operating frequency of the compressor is determined according to the temperature difference of the compressor exhaust temperature exceeding the second preset threshold value, and the increase in the opening of the electronic expansion valve is determined according to the pressure difference of the high and low pressure values ​​of the system deviating from the preset range;

[0043] When the humidity value of the target area is less than the first preset threshold value, if the refrigerant superheat is higher than the third preset threshold value, the compressor operating frequency is reduced and the electronic expansion valve opening is increased, wherein the reduction amount of the compressor operating frequency is determined according to the deviation value between the heat exchanger surface temperature and the preset temperature, and the increase amount of the electronic expansion valve opening is determined according to the high and low pressure values ​​of the system; if the refrigerant superheat is lower than the third preset threshold value, the compressor operating frequency is reduced and the electronic expansion valve opening is further increased, wherein the reduction amount of the compressor operating frequency is determined according to the temperature difference when the refrigerant superheat is lower than the third preset threshold value, and the increase amount of the electronic expansion valve opening is determined according to the deviation between the refrigerant superheat and the third preset threshold value.

[0044] By adopting the above technical solution, the air inlet speed of the dehumidifier under rated working conditions is set to the preset reference wind speed, and the target wind speed of the fan is dynamically adjusted based on this. When the airflow speed of the target airflow channel is less than the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the preset reference wind speed, ensuring that the dehumidifier has sufficient air intake to maintain the basic dehumidification effect; when the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the difference between the preset reference wind speed and the airflow speed. This setting method makes full use of the existing airflow speed in the space, and the insufficient wind speed is supplemented by the fan, which not only ensures the dehumidification effect, but also avoids the additional power consumption of the fan. This wind speed adjustment method based on the comparison of airflow speed and preset reference wind speed achieves the optimal matching of the fan operation state and the airflow characteristics of the space, while ensuring the dehumidification effect and minimizing energy consumption.

[0045] In a second aspect of the present application, there is provided an energy-saving control system for a dehumidifier, the system comprising:

[0046] An image extraction module is used to obtain the video stream currently corresponding to each sub-area of ​​the new energy station, and extract the frame image set in each of the video streams;

[0047] A model retrieval module, used to determine the work identifier corresponding to each of the sub-areas, and retrieve the corresponding defect detection model based on each of the work identifiers;

[0048] A defect detection module, used to perform defect detection on the frame image set based on the defect detection model to obtain defect detection results corresponding to each of the sub-regions;

[0049] The regional early warning module is used to perform secondary verification on the defect detection result, obtain the target sub-region with defects, and issue an early warning for the target sub-region.

[0050] In a third aspect of the present application, a computer storage medium is provided, wherein the computer storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the above method steps.

[0051] In a fourth aspect of the present application, an electronic device is provided, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above-mentioned method steps.

[0052] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0053] The present application obtains node position data, node air velocity data, node humidity data and node temperature data by arranging sensor nodes in the space, and uses the fluid dynamics model to establish an accurate air flow model in combination with the three-dimensional space data, so as to be able to grasp the air flow distribution state in the space in real time. The moisture distribution map generated based on the air flow model can accurately identify the target area where the moisture concentration exceeds the preset threshold, and determine the optimal target air flow channel by analyzing the position of the target area in the air flow model. By keeping the air suction direction of the dehumidifier fan consistent with the air flow direction of the target air flow channel, and setting the target wind speed of the fan according to the air flow speed of the target air flow channel, the original air flow field in the space can be fully utilized to assist the moisture transport and improve the dehumidification efficiency. At the same time, the compressor operating frequency and the electronic expansion valve opening are coordinated and adjusted according to the humidity value of the target area, the target wind speed and the operating parameters of the dehumidifier, which not only ensures the dehumidification effect, but also avoids the ineffective operation of the refrigeration system, thereby achieving the purpose of energy saving and consumption reduction. Since the control method of the present application dynamically adjusts the working state of the dehumidifier based on the actual airflow distribution characteristics in the space, compared with the traditional dehumidification method with fixed wind direction and fixed wind speed, it can more efficiently deal with the problem of local moisture accumulation, and significantly improve the operating efficiency and energy saving level of the dehumidifier. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of an energy-saving control method for a dehumidifier provided in an embodiment of the present application;

[0055] Figure 2 It is a module schematic diagram of an energy-saving control system for a dehumidifier provided in an embodiment of the present application;

[0056] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0057] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0058] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0059] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0060] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0061] The following will provide a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0062] Please refer to Figure 1 , a flow chart of an energy-saving control method for a dehumidifier is proposed. The method can be implemented by a computer program, can be implemented by a single-chip microcomputer, or can be run on an energy-saving control system for a dehumidifier. The computer program can be integrated in a computer device, or can be run as an independent tool application. Specifically, the method is applied to a non-fixed fan dehumidifier. Specifically, the method includes steps 10 to 60, and the above steps are as follows:

[0063] Step 10: Acquire three-dimensional spatial data in the space where the dehumidifier is located and sensor node data acquired by sensor nodes arranged in the space, wherein the sensor node data includes node position data, node air flow rate data, node humidity data and node temperature data;

[0064] Specifically, this step requires obtaining three-dimensional spatial data that can characterize the geometric features of the space. Specifically, a three-dimensional laser scanner is used to scan the space where the dehumidifier is located to obtain geometric dimension data such as the length, width, and height of the space, and to record the spatial coordinates of fixed objects in the space. These three-dimensional spatial data are the basic elements for the subsequent construction of the air flow model.

[0065] Next, sensor nodes are arranged in the space. Each sensor node consists of three parts: a thermistor temperature sensor, a capacitive humidity sensor, and an ultrasonic wind speed sensor. The thermistor temperature sensor measures the node temperature data by using the characteristic that its resistance value changes with temperature. The capacitive humidity sensor measures the node humidity data by sensing the change of the dielectric constant of the material with the air humidity. The ultrasonic wind speed sensor measures the node air velocity data by using the change of the propagation time of ultrasonic waves in the air. Each sensor node is equipped with a wireless transmission module to transmit the collected data to the central controller in real time. At the same time, each sensor node determines its precise position in space through the positioning system to form node position data.

[0066] This step constructs a geometric model of the space by acquiring three-dimensional spatial data. Through the node temperature data, node humidity data, node air flow rate data and node position data collected by the sensor nodes, real-time monitoring of the environmental parameters in the space is achieved, laying a data foundation for the subsequent establishment of an accurate air flow model.

[0067] Step 20: using a fluid dynamics model, combining the sensor node data and the three-dimensional space data, to establish an air flow model;

[0068] Specifically, first, an air flow model is established based on the three-dimensional space data and sensor node data to fully grasp the moisture flow state in the space. Directly using a unified mathematical model will lead to inaccurate descriptions of the airflow state in different regions and different locations, thus affecting the subsequent fan control and dehumidification effect. The specific approach is to first divide the space into a preset number of regular grid units, each grid unit is assigned a unique three-dimensional coordinate identifier, and then the data of each sensor node is mapped to the corresponding grid unit according to the node position data, and the distance weighted interpolation method is used to supplement the data of the grid unit where the sensor node is not deployed, and then combined with the fluid dynamics model for solution to ensure that the established air flow model accurately reflects the airflow state while not causing excessive computational complexity. In this way, a complete model reflecting the characteristics of spatial airflow can be obtained, which is conducive to accurately grasping the moisture distribution in different regions, improving the accuracy of dehumidification control, and achieving effective regulation of humidity in the space.

[0069] Based on the above embodiment, as an optional embodiment, the air flow model is established by using a fluid dynamics model in combination with the sensor node data and the three-dimensional space data, including:

[0070] S210, dividing the space into a preset number of regular grid units, each of the grid units having a unique three-dimensional coordinate identifier;

[0071] Specifically, the present application divides the entire space into a preset number of regular grid units according to the three-dimensional space data, which is achieved by evenly dividing the space in the three directions of x, y, and z. The size of each grid unit is determined according to the overall size of the space and the preset number of grids. Each grid unit is assigned a unique three-dimensional coordinate identifier, which consists of the serial number of the grid unit in the x, y, and z directions, and is used to accurately locate the position of each grid unit in space. This regular grid-based spatial division method provides a basic calculation unit for subsequent fluid dynamics calculations. At the same time, the unique three-dimensional coordinate identifier ensures the effective correspondence and accurate indexing of each grid unit data, laying a spatial foundation for establishing an air flow model.

[0072] S220, mapping the sensor node data to corresponding grid units according to the node position data;

[0073] Specifically, this step assigns the actual data collected by the sensor node to the corresponding grid unit. According to the known node location data, the three-dimensional coordinates of each sensor node are traversed and located in the corresponding grid unit through coordinate matching. For each successfully located sensor node, the node air velocity data, node humidity data, and node temperature data collected are used as the basic data of the grid unit. This data mapping method establishes the corresponding relationship between the sensor measured data and the spatial grid, so that the grid unit obtains the real physical parameters, providing reliable data support for subsequent interpolation calculations and model construction.

[0074] S230, calculating the grid unit data of the undeployed sensor nodes based on the distance weighted interpolation method, wherein the distance weighted interpolation method includes selecting a preset number of sensor nodes closest to the target grid unit, using the inverse of the distance from each sensor node to the target grid unit as a weight coefficient, and performing weighted processing on the sensor node data of each sensor node to obtain the grid unit data of the undeployed sensor nodes;

[0075] Specifically, this step supplements the grid unit data where sensor nodes are not deployed through the distance weighted interpolation method. For each grid unit where sensor nodes are not deployed, calculate its spatial distance to all sensor nodes, and select the preset number of sensor nodes closest to it as reference points. The inverse of the distance from each reference point to the target grid unit is used as the weight coefficient, so that the closer the sensor node is, the greater the impact on the target grid unit data. The node air velocity data, node humidity data, and node temperature data of these reference points are weighted averaged to obtain the complete data of the target grid unit. This distance weighted interpolation method fully considers the impact of spatial position relationships on physical parameters, so that grid units without sensor nodes can obtain reasonable data estimates, ensuring the continuity and accuracy of the air flow model.

[0076] S240, substituting the grid unit data into the Navier-Stokes equations to establish a fluid control equation group including a mass conservation equation and a momentum conservation equation, wherein the coefficient of the mass conservation equation is determined by the airflow velocity data of the grid unit, and the coefficient of the momentum conservation equation is determined by the airflow velocity data, temperature data, and pressure data of the grid unit;

[0077] Specifically, this step substitutes the grid unit data into the basic fluid mechanics equations to establish a mathematical model of air flow. First, a mass conservation equation is established, which reflects the conservation characteristics of airflow mass, and its coefficient is directly determined by the airflow velocity data of the grid unit. Then a momentum conservation equation is established, which describes the law of change of airflow momentum, and its coefficient needs to comprehensively consider the airflow velocity data, temperature data and pressure data of the grid unit. These two types of equations constitute a complete set of fluid control equations, the Navier-Stokes equations, which contain the basic physical laws of fluid motion. This modeling method based on the basic laws of fluid mechanics realizes a strict mathematical description of the laws of airflow motion in space, and provides a theoretical basis for the subsequent solution of the air flow model.

[0078] S250, using a numerical iteration method to solve the fluid control equations to obtain a model describing the gas flow.

[0079] Specifically, this step uses a numerical iteration method to solve the fluid control equations to obtain an air flow model. The fluid control equations are differentially discretized to convert the continuous partial differential equations into discrete algebraic equations. The iterative calculation method is used to gradually correct the calculation results starting from the initial value until the error between two adjacent iterations is less than a preset threshold. Finally, an air flow model that describes the distribution of airflow velocity field and pressure field in space is obtained. The model accurately reflects the movement law of airflow in space and provides a basis for the subsequent analysis of the diffusion characteristics of moisture.

[0080] Step 30: generating a moisture distribution map in the space according to the air flow model, and determining a target area where the moisture concentration exceeds a preset threshold based on the moisture distribution map;

[0081] Specifically, the air flow model is used to calculate the diffusion path of moisture in each grid unit, which reflects the movement trend of moisture under the action of airflow. Then the humidity data of each grid unit is obtained, and these data are combined with the calculated diffusion path to construct a moisture distribution map that characterizes the humidity distribution state of the entire space. Finally, by setting a preset humidity value threshold, the continuous area in the moisture distribution map with humidity values ​​higher than the threshold is determined as the target area that needs to be focused on. This analysis method based on the air flow model realizes the accurate description of the spatial moisture distribution and the precise identification of the target area, providing a clear goal for subsequent dehumidification control.

[0082] Based on the above embodiment, as an optional embodiment, generating the moisture distribution map in the space according to the air flow model includes:

[0083] S310, calculating a diffusion path of moisture in each grid unit based on the air flow model;

[0084] Specifically, the diffusion path of moisture in each grid unit is calculated through the air flow model. Based on the air flow velocity field in the air flow model, the transfer relationship of moisture between grid units is determined, and the moisture flux through the grid unit interface per unit time is calculated. Combined with the temperature gradient of the grid unit, the moisture diffusion effect caused by the temperature difference is calculated. By superimposing the convection transport and diffusion effects, a diffusion path describing the migration law of moisture between grid units is obtained, which provides dynamic change information for the subsequent construction of the moisture distribution map. This calculation method based on the fluid mechanics model accurately describes the movement trend of moisture in space.

[0085] Based on the above embodiment, as an optional embodiment, the calculation of the diffusion path of moisture in each grid unit based on the air flow model includes:

[0086] S311, establishing a state parameter matrix of each of the grid units based on the air flow model, wherein the state parameter matrix includes a grid temperature, a grid humidity, a grid airflow velocity, and a grid airflow direction of each grid unit;

[0087] Specifically, the basic physical parameters of each grid unit are extracted based on the air flow model, including grid temperature, grid humidity, grid airflow velocity and grid airflow direction, and these parameters are organized into a state parameter matrix. The grid temperature and grid humidity in the matrix reflect the thermal and humid state of the air in the grid unit, and the grid airflow velocity and grid airflow direction describe the characteristics of airflow movement. This matrixed data organization method provides complete initial conditions for the subsequent calculation of the moisture diffusion path.

[0088] S312, calculating the migration trend of moisture in each of the grid cells using a convection diffusion equation, wherein the convection term in the convection diffusion equation adopts the grid airflow velocity and the grid airflow direction, and the diffusion coefficient is determined according to the grid temperature of the grid cell;

[0089] Specifically, this step uses the convection-diffusion equation to calculate the changing pattern of moisture in each grid unit. The grid airflow velocity and grid airflow direction of each grid unit are substituted into the convection term of the convection-diffusion equation, which describes the transport effect of airflow on moisture. The diffusion coefficient is determined according to the grid temperature of the grid unit, which reflects the molecular diffusion capacity of moisture. By solving the convection-diffusion equation containing convection terms and diffusion terms, the migration trend of moisture in each grid unit is obtained, which reflects the movement pattern of moisture under the combined influence of airflow and temperature difference. This analysis method combining convection and diffusion mechanisms accurately describes the transfer characteristics of moisture in space.

[0090] S313, calculating the state parameter difference between adjacent grid cells according to the state parameter matrix of each of the grid cells, and calculating the boundary flux based on the state parameter difference between the adjacent grid cells, wherein the boundary flux represents the transfer rate of moisture through the grid cell interface;

[0091] Specifically, this step requires calculating the amount of moisture transferred between grid cells. The grid temperature difference, grid humidity difference, grid airflow velocity difference, and grid airflow direction difference between adjacent grid cells are calculated based on the state parameter matrix. These differences reflect the physical state differences between adjacent grid cells. Substitute the obtained difference into the boundary flux calculation formula to obtain the boundary flux that characterizes the rate of moisture transfer through the grid cell interface. This flux describes the amount of moisture flowing through the grid cell interface per unit time. This flux calculation method based on state parameter difference realizes the quantitative characterization of the moisture transfer process between grid cells.

[0092] S314, establishing a time evolution equation of moisture concentration according to the migration trend and the boundary flux, and obtaining the diffusion path of moisture in each grid unit by numerically solving the time evolution equation.

[0093] Specifically, this step establishes a kinetic equation describing the change of moisture concentration over time based on the above calculation results. Combining the moisture migration trend within the grid unit and the boundary flux at the grid unit interface, a time evolution equation for moisture concentration is established, which reflects the change of moisture concentration over time. The time evolution equation is solved by numerical calculation method to obtain the change of moisture distribution over time, thereby determining the diffusion path of moisture in each grid unit. This analysis method based on the kinetic model realizes the dynamic tracking of the moisture diffusion process and provides the necessary dynamic information for constructing the moisture distribution map.

[0094] S320, obtaining grid unit humidity data of each grid unit, and constructing a moisture distribution map according to the diffusion path and the grid unit humidity data;

[0095] Specifically, this step needs to combine the actual humidity value of the grid unit and the theoretical diffusion path to construct a moisture distribution map. Obtain the grid unit humidity data of each grid unit, which comes from actual measurement and interpolation calculation. Combine these humidity data with the diffusion path calculated in the previous step to draw a moisture distribution map that characterizes the spatial humidity distribution state. The humidity data reflects the humidity value at the current moment, and the diffusion path characterizes the movement trend of moisture. The moisture distribution map composed of the two not only shows the static distribution of spatial humidity, but also contains dynamic information on moisture movement, providing a comprehensive basis for the subsequent identification of target areas.

[0096] S330: Determine a continuous area in the humidity distribution map whose humidity value is higher than a preset humidity value threshold as the target area.

[0097] Specifically, this step requires accurate identification of the areas that need to be focused on from the moisture distribution map. First, a preset humidity value threshold is set, which is determined according to the space humidity control requirements. Then, grid cells with humidity values ​​higher than the threshold are retrieved from the moisture distribution map, and adjacent high-humidity grid cells are combined into a continuous area, and the continuous area is determined as the target area. This threshold-based screening method realizes the automatic identification of moisture accumulation areas and determines a clear scope of action for subsequent dehumidification control.

[0098] Step 40: determining a target airflow channel for moisture transport and an airflow velocity of the target airflow channel according to the position of the target area in the air flow model, and controlling the fan of the dehumidifier to turn so that the air suction direction of the fan is consistent with the airflow direction of the target airflow channel;

[0099] Specifically, first obtain the air inlet speed of the dehumidifier under rated working conditions as the preset reference wind speed, which represents the minimum wind speed value required for the normal operation of the dehumidifier. Then determine the relationship between the airflow speed of the target airflow channel and the preset reference wind speed. When the airflow speed is less than the preset proportional coefficient of the preset reference wind speed, set the target wind speed to the preset reference wind speed to ensure that the dehumidifier has sufficient air intake; when the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, set the target wind speed to the difference between the preset reference wind speed and the airflow speed. At this time, only the insufficient wind speed needs to be supplemented. Finally, control the fan to operate at the determined target wind speed. This dynamic adjustment method based on airflow speed realizes the coordination of fan operation and spatial airflow, reducing the energy consumption of the fan while ensuring the dehumidification effect.

[0100] Based on the above embodiment, as an optional embodiment, determining the target air flow channel for moisture transport according to the position of the target area in the air flow model includes:

[0101] S410, acquiring airflow data at the location of the target area;

[0102] Specifically, this step extracts the airflow information of the target area from the air flow model. Based on the coordinates of the target area in space, the airflow data such as the airflow speed and airflow direction in the area are obtained. These airflow data reflect the characteristics of the airflow field around the target area and provide basic data support for determining the appropriate moisture transport channel. This targeted data acquisition method ensures the accuracy of subsequent channel planning.

[0103] S420, based on the center position of the target area, sector division is performed along the radial direction within a preset radius, the angle between adjacent sectors is a preset angle value, the outer arc length of each sector is equal to the width of the air inlet of the dehumidifier, and the area of ​​each sector is set as a channel to be selected;

[0104] Specifically, this step requires dividing potential moisture transport channels around the target area. Taking the center of the target area as the origin, sector-shaped areas are divided within a preset radius. The angle between each sector is set to a preset angle value, and the outer arc length of each sector is matched with the width of the dehumidifier's air inlet. This match ensures the adaptability of the airflow channel to the dehumidifier's air inlet. Each divided sector-shaped area is set as a candidate channel, which covers different directions around the target area and provides candidate solutions for the subsequent selection of the optimal transport path. This sector-based division method takes into account the comprehensiveness of the direction and ensures the practicality of the channel size.

[0105] S430, using the air flow model to obtain airflow characteristic parameters in each of the channels to be selected, wherein the airflow characteristic parameters include an airflow velocity characteristic value and an airflow direction characteristic value, the airflow velocity characteristic value is an arithmetic mean of the airflow velocity detected by the sensor nodes located in the channel area to be selected, and the airflow direction characteristic value is a weighted average of the airflow directions detected by the sensor nodes located in the channel area to be selected, and the weight coefficient of the weighted average is proportional to the corresponding airflow velocity value;

[0106] Specifically, this step requires evaluating the airflow characteristics of each candidate channel. The air flow model is used to obtain the airflow characteristic parameters in each candidate channel, including the airflow velocity characteristic value and the airflow direction characteristic value. The airflow velocity characteristic value is calculated using the arithmetic mean of the airflow velocity detected by all sensor nodes in the candidate channel, reflecting the average flow velocity level in the channel. The airflow direction characteristic value is calculated by weighted averaging, and the airflow direction detected by each sensor node is weighted by the airflow velocity, so that the direction with a larger airflow velocity occupies a larger proportion in the final direction characteristic value. This feature extraction method based on measured data accurately reflects the airflow field characteristics of the candidate channel and provides a quantitative basis for channel evaluation.

[0107] S440, based on the airflow characteristic parameters in each of the candidate channels, comprehensively score each of the candidate channels to obtain a comprehensive score for each of the candidate channels, and determine the candidate channel with the highest comprehensive score as the target airflow channel.

[0108] Specifically, this step determines the optimal moisture transport channel through a comprehensive evaluation of the channels to be selected. Each channel to be selected is comprehensively scored based on its airflow characteristic parameters, and the scoring indicators include the size of the airflow velocity characteristic value, the consistency of the airflow direction characteristic value and the channel axis, etc. The channel to be selected with the highest comprehensive score is determined as the target airflow channel, which has the airflow conditions that are most conducive to moisture transport. This selection method based on multi-dimensional scoring ensures the superiority of the selected channel in terms of airflow characteristics and provides the best path for achieving efficient moisture transport.

[0109] Step 50: determining a target wind speed of the fan according to the air flow speed of the target air flow channel, and controlling the fan to operate according to the target wind speed;

[0110] Specifically, first obtain the air inlet speed of the dehumidifier under rated working conditions as the preset reference wind speed, which represents the minimum wind speed value required for the normal operation of the dehumidifier. Then determine the relationship between the airflow speed of the target airflow channel and the preset reference wind speed. When the airflow speed is less than the preset proportional coefficient of the preset reference wind speed, set the target wind speed to the preset reference wind speed to ensure that the dehumidifier has sufficient air intake; when the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, set the target wind speed to the difference between the preset reference wind speed and the airflow speed. At this time, only the insufficient wind speed needs to be supplemented. Finally, control the fan to operate at the determined target wind speed. This dynamic adjustment method based on airflow speed realizes the coordination of fan operation and spatial airflow, reducing the energy consumption of the fan while ensuring the dehumidification effect.

[0111] Based on the above embodiment, as an optional embodiment, determining the target wind speed of the fan according to the air flow speed of the target air flow channel includes:

[0112] S510, if the air flow speed is less than a preset proportional coefficient of a preset reference wind speed, setting the target wind speed to the preset reference wind speed, wherein the preset reference wind speed is the air inlet speed of the dehumidifier under rated working conditions;

[0113] Specifically, this step determines the fan operating wind speed according to the relationship between the airflow speed of the target airflow channel and the preset reference wind speed. When the airflow speed of the target airflow channel is less than the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the preset reference wind speed, where the preset reference wind speed is the air inlet speed value of the dehumidifier under rated working conditions. This setting method based on the minimum wind speed requirement ensures that the dehumidifier has sufficient air intake to ensure a basic dehumidification effect.

[0114] S520: If the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the difference between the preset reference wind speed and the airflow speed.

[0115] Specifically, this step sets the fan speed for the case where the airflow speed of the target airflow channel is relatively large. When the airflow speed of the target airflow channel is greater than or equal to the preset proportional coefficient of the preset reference speed, the target speed is set to the difference between the preset reference speed and the airflow speed. This setting method makes full use of the existing airflow speed in the channel, and the fan only needs to supplement the insufficient wind speed, thus achieving effective use of the existing airflow, ensuring the dehumidification effect and reducing the fan energy consumption.

[0116] Step 60: Acquire the operating parameters of the dehumidifier, and adjust the compressor operating frequency and the opening of the electronic expansion valve of the dehumidifier according to the humidity value of the target area, the target wind speed and the operating parameters.

[0117] Specifically, efficient operation of the refrigeration system is achieved by adjusting the compressor operating frequency and the opening of the electronic expansion valve of the dehumidifier. First, the operating parameters of the dehumidifier are obtained, including the surface temperature of the heat exchanger, the inlet and outlet temperature difference of the heat exchanger, the high and low pressure values ​​of the system, the compressor exhaust temperature and the refrigerant superheat. When the humidity value of the target area is greater than the first preset threshold value, when the compressor exhaust temperature is lower than the second preset threshold value and the system high and low pressure values ​​are within the preset range, the increase in the compressor operating frequency is determined according to the target wind speed and the inlet and outlet temperature difference of the heat exchanger, and the decrease in the opening of the electronic expansion valve is determined according to the refrigerant superheat; if the compressor exhaust temperature is higher than the second preset threshold value or the system high and low pressure values ​​exceed the preset range, the decrease in the compressor operating frequency is determined according to the temperature difference of the compressor exhaust temperature exceeding the second preset threshold value, and the increase in the opening of the electronic expansion valve is determined according to the pressure difference of the system high and low pressure values ​​deviating from the preset range. When the humidity value of the target area is less than the first preset threshold, and the refrigerant superheat is higher than the third preset threshold, the reduction in the compressor operating frequency is determined according to the deviation between the heat exchanger surface temperature and the preset temperature, and the increase in the electronic expansion valve opening is determined according to the system high and low pressure values; when the refrigerant superheat is lower than the third preset threshold, the reduction in the compressor operating frequency is determined according to the temperature difference between the refrigerant superheat and the third preset threshold, and the increase in the electronic expansion valve opening is determined according to the deviation between the refrigerant superheat and the third preset threshold. This multi-parameter-based collaborative control method ensures the optimal coordination of various components of the refrigeration system and improves the system operation efficiency.

[0118] Based on the above embodiment, as an optional embodiment, the operating parameters include the surface temperature of the heat exchanger, the inlet and outlet temperature difference of the heat exchanger, the high and low pressure values ​​of the system, the compressor exhaust temperature and the refrigerant superheat; the compressor operating frequency and the electronic expansion valve opening of the dehumidifier are adjusted according to the humidity value of the target area, the target wind speed and the operating parameters, including:

[0119] S610, when the humidity value of the target area is greater than a first preset threshold value, if the exhaust temperature of the compressor is lower than a second preset threshold value, and the high and low pressure values ​​of the system are within a preset range, the operating frequency of the compressor is increased and the opening of the electronic expansion valve is reduced, wherein the increase in the operating frequency of the compressor is determined according to the target wind speed and the inlet and outlet temperature difference of the heat exchanger, and the decrease in the opening of the electronic expansion valve is determined according to the superheat of the refrigerant; if the exhaust temperature of the compressor is higher than the second preset threshold value, or the high and low pressure values ​​of the system exceed the preset range, the operating frequency of the compressor is reduced and the opening of the electronic expansion valve is increased, wherein the decrease in the operating frequency of the compressor is determined according to the temperature difference of the compressor exhaust temperature exceeding the second preset threshold value, and the increase in the opening of the electronic expansion valve is determined according to the pressure difference of the high and low pressure values ​​of the system deviating from the preset range;

[0120] Specifically, this step performs collaborative control on the refrigeration system based on the humidity value of the target area. When the humidity value of the target area is greater than the first preset threshold, control is performed in two cases: the first case is that the compressor exhaust temperature is lower than the second preset threshold and the system high and low pressure values ​​are within the preset range. At this time, the compressor operating frequency is increased and the electronic expansion valve opening is reduced. The increase in the compressor operating frequency is determined by the target wind speed and the inlet and outlet temperature difference of the heat exchanger, and the reduction in the electronic expansion valve opening is determined by the refrigerant superheat; the second case is that the compressor exhaust temperature is higher than the second preset threshold or the system high and low pressure values ​​exceed the preset range. At this time, the compressor operating frequency is reduced and the electronic expansion valve opening is increased. The reduction in the compressor operating frequency is determined by the temperature difference of the compressor exhaust temperature exceeding the second preset threshold, and the increase in the electronic expansion valve opening is determined by the pressure difference of the system high and low pressure values ​​deviating from the preset range. This collaborative control strategy based on the operating state achieves the optimal coordination of various components of the refrigeration system. It should be noted that the definitions of the system's high and low pressure values ​​are: high pressure value: refers to the pressure on the exhaust side of the compressor in the refrigeration system (i.e. the inlet side of the condenser); low pressure value: refers to the pressure on the suction side of the compressor in the refrigeration system (i.e. the outlet side of the evaporator). The system's high and low pressure values ​​usually refer to the combined state of the two pressures: high pressure value and low pressure value.

[0121] S620, when the humidity value of the target area is less than the first preset threshold, if the refrigerant superheat is higher than the third preset threshold, reduce the compressor operating frequency and increase the electronic expansion valve opening, wherein the reduction in the compressor operating frequency is determined according to the deviation between the heat exchanger surface temperature and the preset temperature, and the increase in the electronic expansion valve opening is determined according to the high and low pressure values ​​of the system; if the refrigerant superheat is lower than the third preset threshold, reduce the compressor operating frequency and further increase the electronic expansion valve opening, wherein the reduction in the compressor operating frequency is determined according to the temperature difference when the refrigerant superheat is lower than the third preset threshold, and the increase in the electronic expansion valve opening is determined according to the deviation between the refrigerant superheat and the third preset threshold.

[0122] Specifically, this step is a refrigeration system control strategy when the target area humidity value decreases. When the target area humidity value is less than the first preset threshold, it is controlled in two situations according to the refrigerant superheat: when the refrigerant superheat is higher than the third preset threshold, the compressor operating frequency is reduced and the electronic expansion valve opening is increased. The reduction in the compressor operating frequency is determined by the deviation between the heat exchanger surface temperature and the preset temperature, and the increase in the electronic expansion valve opening is determined by the high and low pressure values ​​of the system; when the refrigerant superheat is lower than the third preset threshold, the compressor operating frequency is further reduced and the electronic expansion valve opening is increased. The reduction in the compressor operating frequency is determined by the temperature difference between the refrigerant superheat and the third preset threshold, and the increase in the electronic expansion valve opening is determined by the deviation between the refrigerant superheat and the third preset threshold. This hierarchical control strategy avoids excessive dehumidification of the system and achieves energy-saving operation.

[0123] See also Figure 2 , is a module schematic diagram of an energy-saving control system for a dehumidifier provided in an embodiment of the present application, and the energy-saving control system for the dehumidifier may include: a data acquisition module, a model building module, a target area determination module, an air intake direction determination module, an air intake speed determination module, and an operation parameter determination module, wherein:

[0124] A data acquisition module, used to acquire three-dimensional spatial data in the space where the dehumidifier is located and sensor node data acquired by sensor nodes arranged in the space, wherein the sensor node data includes node position data, node air flow rate data, node humidity data and node temperature data;

[0125] A model building module, used to build an air flow model by using a fluid dynamics model in combination with the sensor node data and the three-dimensional space data;

[0126] a target area determination module, configured to generate a moisture distribution map in the space according to the air flow model, and determine a target area where the moisture concentration exceeds a preset threshold based on the moisture distribution map;

[0127] an air suction direction determination module, for determining a target air flow channel for moisture transport and an air flow velocity of the target air flow channel according to the position of the target area in the air flow model, and controlling the fan of the dehumidifier to turn the air suction direction of the fan to be consistent with the air flow direction of the target air flow channel;

[0128] An air intake speed determination module, used to determine a target wind speed of the fan according to the air flow speed of the target air flow channel, and control the fan to operate according to the target wind speed;

[0129] The operating parameter determination module is used to obtain the operating parameters of the dehumidifier and adjust the compressor operating frequency and the electronic expansion valve opening of the dehumidifier according to the humidity value of the target area, the target wind speed and the operating parameters.

[0130] Optionally, the model building module is further used to divide the space into a preset number of regular grid units, each of which has a unique three-dimensional coordinate identifier; map the sensor node data to the corresponding grid unit according to the node position data; calculate the grid unit data of the undeployed sensor nodes based on the distance weighted interpolation method, wherein the distance weighted interpolation method includes selecting a preset number of sensor nodes closest to the target grid unit, using the inverse of the distance from each sensor node to the target grid unit as a weight coefficient, and weighting the sensor node data of each sensor node to obtain the grid unit data of the undeployed sensor nodes; substitute the grid unit data into the Navier-Stokes equation to establish a fluid control equation group including a mass conservation equation and a momentum conservation equation, wherein the coefficient of the mass conservation equation is determined by the airflow velocity data of the grid unit, and the coefficient of the momentum conservation equation is determined by the airflow velocity data, temperature data and pressure data of the grid unit; and use a numerical iteration method to solve the fluid control equation group to obtain a model describing the airflow.

[0131] Optionally, the target area determination module is also used to calculate the diffusion path of moisture in each grid unit based on the air flow model; obtain grid unit humidity data of each grid unit, and construct a moisture distribution map based on the diffusion path and the grid unit humidity data; and determine the continuous area in the moisture distribution map whose humidity value is higher than a preset humidity value threshold as the target area.

[0132] Optionally, the inhalation direction determination module is further used to obtain airflow data at the location of the target area;

[0133] Based on the center position of the target area, sectors are divided along the radial direction within a preset radius, the angle between adjacent sectors is a preset angle value, the outer arc length of each sector is equal to the width of the air inlet of the dehumidifier, and the area of ​​each sector is set as a candidate channel; the air flow model is used to obtain the airflow characteristic parameters in each candidate channel, wherein the airflow characteristic parameters include an airflow velocity characteristic value and an airflow direction characteristic value, the airflow velocity characteristic value is the arithmetic mean of the airflow velocity detected by the sensor node located in the candidate channel area, and the airflow direction characteristic value is the weighted average of the airflow direction detected by the sensor node located in the candidate channel area, and the weight coefficient of the weighted average is proportional to the corresponding airflow velocity value; based on the airflow characteristic parameters in each candidate channel, each candidate channel is comprehensively scored to obtain a comprehensive score of each candidate channel, and the candidate channel with the highest comprehensive score is determined as the target airflow channel.

[0134] Optionally, the air intake speed determination module is further configured to set the target wind speed to the preset reference wind speed if the air flow speed is less than a preset proportional coefficient of a preset reference wind speed, wherein the preset reference wind speed is the air intake speed of the dehumidifier under rated working conditions;

[0135] If the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the difference between the preset reference wind speed and the airflow speed.

[0136] Optionally, the operating parameter determination module is further configured to, when the humidity value of the target area is greater than a first preset threshold value, if the exhaust temperature of the compressor is lower than a second preset threshold value, and the high and low pressure values ​​of the system are within a preset range, increase the operating frequency of the compressor and reduce the opening of the electronic expansion valve, wherein the increase in the operating frequency of the compressor is determined according to the target wind speed and the inlet and outlet temperature difference of the heat exchanger, and the decrease in the opening of the electronic expansion valve is determined according to the superheat of the refrigerant;

[0137] If the exhaust temperature of the compressor is higher than the second preset threshold, or the high and low pressure values ​​of the system exceed the preset range, the operating frequency of the compressor is reduced and the opening of the electronic expansion valve is increased, wherein the reduction amount of the compressor operating frequency is determined according to the temperature difference of the compressor exhaust temperature exceeding the second preset threshold, and the increase amount of the electronic expansion valve opening is determined according to the pressure difference of the high and low pressure values ​​of the system deviating from the preset range;

[0138] When the humidity value of the target area is less than the first preset threshold, if the refrigerant superheat is higher than the third preset threshold, the compressor operating frequency is reduced and the electronic expansion valve opening is increased, wherein the reduction amount of the compressor operating frequency is determined according to the deviation value between the heat exchanger surface temperature and the preset temperature, and the increase amount of the electronic expansion valve opening is determined according to the high and low pressure values ​​of the system;

[0139] If the refrigerant superheat is lower than the third preset threshold, the compressor operating frequency is reduced and the electronic expansion valve opening is further increased, wherein the reduction amount of the compressor operating frequency is determined according to the temperature difference between the refrigerant superheat and the third preset threshold, and the increase amount of the electronic expansion valve opening is determined according to the deviation between the refrigerant superheat and the third preset threshold.

[0140] It should be noted that: when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0141] An embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded by a processor and executing an energy-saving control method for a dehumidifier in the above embodiment. The specific execution process can be found in the specific description of the above embodiment and will not be repeated here.

[0142] Please refer to Figure 3 The application also discloses an electronic device. Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0143] The communication bus 302 is used to realize the connection and communication between these components.

[0144] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0145] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0146] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0147] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of an energy-saving control method for a dehumidifier.

[0148] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the application program storing a method for energy-saving control of a dehumidifier in the memory 305. When executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited to the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0149] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0150] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0151] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0152] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0153] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0154] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0155] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A dehumidifier energy-saving control method, characterized in that: The method is applied to a non-fixed fan dehumidifier, and the method comprises: Acquire three-dimensional spatial data in a space where a dehumidifier is located and sensor node data acquired by sensor nodes arranged in the space, wherein the sensor node data includes node position data, node air velocity data, node humidity data, and node temperature data; Using a fluid dynamics model, combining the sensor node data and the three-dimensional space data, to establish an air flow model; using a fluid dynamics model, combining the sensor node data and the three-dimensional space data, to establish an air flow model, includes: Dividing the space into a preset number of regular grid units, each of the grid units having a unique three-dimensional coordinate identifier; Mapping the sensor node data to corresponding grid cells according to the node position data; Calculating the grid unit data of the undeployed sensor nodes based on the distance weighted interpolation method, wherein the distance weighted interpolation method includes selecting a preset number of sensor nodes closest to the target grid unit, using the inverse of the distance from each sensor node to the target grid unit as a weight coefficient, and performing weighted processing on the sensor node data of each sensor node to obtain the grid unit data of the undeployed sensor nodes; Substituting the grid unit data into the Navier-Stokes equations to establish a fluid control equation group including a mass conservation equation and a momentum conservation equation, wherein the coefficient of the mass conservation equation is determined by the airflow velocity data of the grid unit, and the coefficient of the momentum conservation equation is determined by the airflow velocity data, temperature data and pressure data of the grid unit; Solving the fluid control equations by numerical iteration method to obtain a model describing the air flow; Generate a moisture distribution map in the space according to the air flow model, and determine a target area where the moisture concentration exceeds a preset threshold value based on the moisture distribution map; the generating of the moisture distribution map in the space according to the air flow model includes: calculating a diffusion path of moisture in each grid unit based on the air flow model; acquiring grid unit humidity data of each grid unit, and constructing a moisture distribution map according to the diffusion path and the grid unit humidity data; determining a continuous area in the moisture distribution map where the humidity value is higher than a preset humidity value threshold as the target area; Determine a target airflow channel for moisture transport and an airflow velocity of the target airflow channel according to the position of the target area in the air flow model, and control the direction of the fan of the dehumidifier so that the air suction direction of the fan is consistent with the airflow direction of the target airflow channel; Determining a target wind speed of the fan according to the air flow speed of the target air flow channel, and controlling the fan to operate according to the target wind speed; The operating parameters of the dehumidifier are obtained, and the operating frequency of the compressor and the opening of the electronic expansion valve of the dehumidifier are adjusted according to the humidity value of the target area, the target wind speed and the operating parameters.

2. The method according to claim 1, characterized in that The calculating the diffusion path of moisture in each grid unit based on the air flow model includes: Establishing a state parameter matrix of each grid unit based on the air flow model, wherein the state parameter matrix includes a grid temperature, a grid humidity, a grid airflow velocity, and a grid airflow direction of each grid unit; The migration trend of moisture in each grid unit is calculated using a convection diffusion equation, wherein the convection term in the convection diffusion equation adopts the grid airflow velocity and the grid airflow direction, and the diffusion coefficient is determined according to the grid temperature of the grid unit; Calculating the state parameter difference between adjacent grid cells according to the state parameter matrix of each of the grid cells, and calculating the boundary flux based on the state parameter difference between the adjacent grid cells, wherein the boundary flux represents the transfer rate of moisture through the grid cell interface; A time evolution equation of moisture concentration is established according to the migration trend and the boundary flux, and the diffusion path of moisture in each grid unit is obtained by numerically solving the time evolution equation.

3. The method according to claim 1, characterized in that The step of determining a target airflow channel for moisture transport according to a position of the target area in the air flow model comprises: Acquiring airflow data at the location of the target area; Based on the center position of the target area, sectors are divided along the radial direction within a preset radius, the angle between adjacent sectors is a preset angle value, the outer arc length of each sector is equal to the width of the air inlet of the dehumidifier, and the area of ​​each sector is set as a channel to be selected; The air flow model is used to obtain airflow characteristic parameters in each of the channels to be selected, wherein the airflow characteristic parameters include an airflow velocity characteristic value and an airflow direction characteristic value, the airflow velocity characteristic value is the arithmetic mean of the airflow velocity detected by the sensor nodes located in the channel area to be selected, and the airflow direction characteristic value is the weighted average of the airflow directions detected by the sensor nodes located in the channel area to be selected, and the weight coefficient of the weighted average is proportional to the corresponding airflow velocity value; Based on the airflow characteristic parameters in each of the candidate channels, each of the candidate channels is comprehensively scored to obtain a comprehensive score for each of the candidate channels, and the candidate channel with the highest comprehensive score is determined as the target airflow channel.

4. The method according to claim 1, characterized in that: The step of determining the target wind speed of the fan according to the air flow speed of the target air flow channel includes: If the air flow speed is less than the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the preset reference wind speed, wherein the preset reference wind speed is the air inlet speed of the dehumidifier under rated working conditions; If the airflow speed is greater than or equal to the preset proportional coefficient of the preset reference wind speed, the target wind speed is set to the difference between the preset reference wind speed and the airflow speed.

5. The method according to claim 1, characterized in that The operating parameters include the surface temperature of the heat exchanger, the inlet and outlet temperature difference of the heat exchanger, the high and low pressure values ​​of the system, the exhaust temperature of the compressor and the superheat of the refrigerant; the adjusting the compressor operating frequency and the opening of the electronic expansion valve of the dehumidifier according to the humidity value of the target area, the target wind speed and the operating parameters includes: When the humidity value of the target area is greater than the first preset threshold value, if the exhaust temperature of the compressor is lower than the second preset threshold value, and the high and low pressure values ​​of the system are within the preset range, the operating frequency of the compressor is increased and the opening of the electronic expansion valve is reduced, wherein the increase in the operating frequency of the compressor is determined according to the target wind speed and the inlet and outlet temperature difference of the heat exchanger, and the decrease in the opening of the electronic expansion valve is determined according to the superheat of the refrigerant; if the exhaust temperature of the compressor is higher than the second preset threshold value, or the high and low pressure values ​​of the system exceed the preset range, the operating frequency of the compressor is reduced and the opening of the electronic expansion valve is increased, wherein the decrease in the operating frequency of the compressor is determined according to the temperature difference of the compressor exhaust temperature exceeding the second preset threshold value, and the increase in the opening of the electronic expansion valve is determined according to the pressure difference of the high and low pressure values ​​of the system deviating from the preset range; When the humidity value of the target area is less than the first preset threshold value, if the refrigerant superheat is higher than the third preset threshold value, the compressor operating frequency is reduced and the electronic expansion valve opening is increased, wherein the reduction amount of the compressor operating frequency is determined according to the deviation value between the heat exchanger surface temperature and the preset temperature, and the increase amount of the electronic expansion valve opening is determined according to the high and low pressure values ​​of the system; if the refrigerant superheat is lower than the third preset threshold value, the compressor operating frequency is reduced and the electronic expansion valve opening is further increased, wherein the reduction amount of the compressor operating frequency is determined according to the temperature difference when the refrigerant superheat is lower than the third preset threshold value, and the increase amount of the electronic expansion valve opening is determined according to the deviation between the refrigerant superheat and the third preset threshold value.

6. The system of the energy-saving control method of a dehumidifier according to claim 1, characterized in that: The system comprises: A data acquisition module, used to acquire three-dimensional spatial data in the space where the dehumidifier is located and sensor node data acquired by sensor nodes arranged in the space, wherein the sensor node data includes node position data, node air flow rate data, node humidity data and node temperature data; A model building module is used to establish an air flow model by using a fluid dynamics model in combination with the sensor node data and the three-dimensional space data; the air flow model is established by using a fluid dynamics model in combination with the sensor node data and the three-dimensional space data, including: Dividing the space into a preset number of regular grid units, each of the grid units having a unique three-dimensional coordinate identifier; Mapping the sensor node data to corresponding grid cells according to the node position data; Calculating the grid unit data of the undeployed sensor nodes based on the distance weighted interpolation method, wherein the distance weighted interpolation method includes selecting a preset number of sensor nodes closest to the target grid unit, using the inverse of the distance from each sensor node to the target grid unit as a weight coefficient, and performing weighted processing on the sensor node data of each sensor node to obtain the grid unit data of the undeployed sensor nodes; Substituting the grid unit data into the Navier-Stokes equations to establish a fluid control equation group including a mass conservation equation and a momentum conservation equation, wherein the coefficient of the mass conservation equation is determined by the airflow velocity data of the grid unit, and the coefficient of the momentum conservation equation is determined by the airflow velocity data, temperature data and pressure data of the grid unit; Solving the fluid control equations by numerical iteration method to obtain a model describing the air flow; a target area determination module, for generating a moisture distribution map in the space according to the air flow model, and determining a target area where the moisture concentration exceeds a preset threshold value based on the moisture distribution map; the generating of the moisture distribution map in the space according to the air flow model comprises: calculating a diffusion path of moisture in each grid unit based on the air flow model; acquiring grid unit humidity data of each grid unit, and constructing a moisture distribution map according to the diffusion path and the grid unit humidity data; determining a continuous area in the moisture distribution map where the humidity value is higher than a preset humidity value threshold value as the target area; an air suction direction determination module, for determining a target air flow channel for moisture transport and an air flow velocity of the target air flow channel according to the position of the target area in the air flow model, and controlling the fan of the dehumidifier to turn the air suction direction of the fan to be consistent with the air flow direction of the target air flow channel; An air intake speed determination module, used to determine a target wind speed of the fan according to the air flow speed of the target air flow channel, and control the fan to operate according to the target wind speed; The operating parameter determination module is used to obtain the operating parameters of the dehumidifier and adjust the compressor operating frequency and the electronic expansion valve opening of the dehumidifier according to the humidity value of the target area, the target wind speed and the operating parameters.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 5.

8. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-5.

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