Anti-condensation control method and device of air conditioner, server, air conditioner and medium

Abstract

The application discloses a condensation control method and device of an air conditioner, a server, the air conditioner and a medium, and relates to the technical field of air conditioners. After receiving prediction request information, the method inputs a first air conditioner model, a current operation mode, a current evaporator temperature, a current indoor temperature, a current indoor fan speed and a current indoor humidity into a condensation prediction model to obtain a first prediction result. When the first prediction result indicates that the first air conditioner is about to condense, the first air conditioner adjusts the compressor speed to reduce the temperature of the evaporator of the first air conditioner, thereby reducing the risk of condensation of the air conditioner. When the second air conditioner condenses, the second air conditioner sends condensation state information to the server, and the server updates the condensation prediction model based on the condensation state information to improve the prediction accuracy.

Description

Technical Field

[0001] This application relates to the field of air conditioning technology, and in particular to an anti-condensation control method, device, server, air conditioner, and medium for an air conditioner. Background Technology

[0002] During operation, air conditioners are prone to condensation due to the combined effects of indoor temperature, evaporator temperature, indoor humidity, and the air conditioner's mechanical structure. This condensation can manifest as water dripping from the surface of structural components or water droplets being blown out by the circulating air, resulting in a poor user experience. Current solutions typically adjust the air conditioner's operation only after condensation is detected. There is a pressing need for an anti-condensation control method that can predict condensation in air conditioners. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes an anti-condensation control method, device, server, air conditioner, and medium for an air conditioner, capable of predicting whether condensation is about to occur in the air conditioner, thereby adjusting the compressor speed in a timely manner and reducing the risk of condensation.

[0004] According to the first aspect of the present application, the anti-condensation control method for an air conditioner is applied to a server, the server being communicatively connected to multiple air conditioners, and the server being deployed with a pre-trained condensation prediction model.

[0005] The method includes:

[0006] Receive prediction request information sent by the first air conditioner; the prediction request information includes the model of the first air conditioner, the current operating mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor humidity;

[0007] The first air conditioner model, current operating mode, current evaporator temperature, current indoor temperature, current indoor fan speed, and current indoor humidity are input into the condensation prediction model to obtain the first prediction result;

[0008] The first prediction result is sent to the first air conditioner so that when the first prediction result indicates that the air conditioner is about to condense, the first air conditioner adjusts the compressor speed of the first air conditioner to increase the temperature of the evaporator of the first air conditioner.

[0009] receive pre-condensation state information, the pre-condensation state information being sent by the second air conditioner when condensation occurs, the pre-condensation state information including a second air conditioner model, a pre-condensation operation mode, a pre-condensation evaporator temperature, a pre-condensation indoor temperature, a pre-condensation indoor fan speed, and a pre-condensation indoor humidity;

[0010] input the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity into the condensation prediction model to obtain a second prediction result;

[0011] calculate a loss value based on the second prediction result and a loss function;

[0012] update the condensation prediction model based on the loss value.

[0013] The condensation prediction model is updated, and the prediction accuracy of the condensation prediction model can be continuously improved. Therefore, the air conditioner can be predicted whether to occur condensation, and the prediction accuracy is high. When it is predicted that the air conditioner will occur condensation, the compressor speed of the air conditioner is adjusted in time, so that the risk of condensation of the air conditioner is reduced.

[0014] According to some embodiments of the first aspect of the present application, the condensation prediction model includes a feature extraction module, a residual module, a long short-term memory module, and a classifier.

[0015] The inputting the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity into the condensation prediction model to obtain a second prediction result includes:

[0016] constructing a first input vector based on the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity;

[0017] performing feature extraction processing on the first input vector by the feature extraction module to obtain a first input feature;

[0018] performing residual processing on the first input feature by the residual module to obtain a first residual feature;

[0019] inputting the first residual feature into the long short-term memory module to obtain a first updated feature;

[0020] inputting the first updated feature into the classifier to obtain the second prediction result.

[0021] The second aspect embodiment of the application provides a condensation prevention control method of an air conditioner, applied to the air conditioner, the air conditioner being in communication connection with a server, and the server being deployed with a pre-trained condensation prediction model;

[0022] The method comprises:

[0023] periodically acquiring an air conditioner model, a current operation mode, a current evaporator temperature, a current indoor temperature, a current indoor fan speed and a current indoor temperature of the air conditioner;

[0024] generating prediction request information based on the air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor temperature;

[0025] sending the prediction request information to the server, so that the server inputs the air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor temperature into the condensation prediction model to obtain a first prediction result;

[0026] receiving the first prediction result sent by the server, and adjusting the compressor speed of the air conditioner to reduce the temperature of the evaporator of the air conditioner in the case where it is detected that the first prediction result indicates that the air conditioner is about to condense.

[0027] According to some embodiments of the first aspect of the application, the method further comprises:

[0028] In response to detecting that the air conditioner condenses, acquiring a pre-condensation evaporator temperature, a pre-condensation operation mode, a pre-condensation indoor temperature, a pre-condensation indoor fan speed and a pre-condensation indoor humidity before a preset time period.

[0029] generate pre-condensation state information based on the air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity;

[0030] send the pre-condensation state information to the server, so that the server updates the condensation prediction model based on the air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity.

[0031] According to some embodiments of the second aspect of the application, the adjusting the compressor speed of the air conditioner comprises:

[0032] determining a reference temperature based on the current indoor temperature and a preset temperature coefficient;

[0033] calculating a temperature difference between the current evaporator temperature and the reference temperature to obtain a temperature difference value;

[0034] obtaining a current compressor speed of the air conditioner, and determining a target speed based on the current evaporator temperature, the reference temperature, and the current compressor speed;

[0035] setting the speed of the compressor of the air conditioner to the target speed.

[0036] According to some embodiments of the second aspect of the application, after the setting the speed of the compressor of the air conditioner to the target speed, the method comprises:

[0037] in a case where the target speed is greater than a preset threshold, reducing the speed of the indoor fan of the air conditioner;

[0038] controlling the air outlet direction of the air conditioner to be upward air outlet.

[0039] The third aspect of the application provides a condensation prevention control device of an air conditioner, applied to a server, the server being in communication connection with a plurality of air conditioners, and the server being deployed with a pre-trained condensation prediction model;

[0040] The control device comprises:

[0041] a first receiving unit configured to receive prediction request information sent by a first air conditioner, the prediction request information comprising a first air conditioner model, a current operation mode, a current evaporator temperature, a current indoor temperature, a current indoor fan speed, and a current indoor humidity;

[0042] The first input unit is configured to input the first air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor humidity into the condensation prediction model to obtain a first prediction result.

[0043] The first generating unit is configured to send the first prediction result to the first air conditioner, so that the first air conditioner adjusts the compressor speed of the first air conditioner to increase the temperature of the evaporator of the first air conditioner when it is detected that the first prediction result indicates that the air conditioner is about to condense.

[0044] The second receiving unit receives condensation-before state information, which is sent by the second air conditioner when condensation occurs, and includes a second air conditioner model, a condensation-before operation mode, a condensation-before evaporator temperature, a condensation-before indoor temperature, a condensation-before indoor fan speed and a condensation-before indoor humidity.

[0045] The second input unit is configured to input the second air conditioner model, the condensation-before operation mode, the condensation-before evaporator temperature, the condensation-before indoor temperature, the condensation-before indoor fan speed and the condensation-before indoor humidity into the condensation prediction model to obtain a second prediction result.

[0046] The loss function unit is configured to calculate a loss value based on the second prediction result and a loss function.

[0047] The updating unit is configured to update the condensation prediction model based on the loss value.

[0048] The fourth aspect embodiment of the present application provides a server, which includes a first memory and a first processor, the first memory stores a computer program, and the first processor implements the anti-condensation control method of the air conditioner of any one of the first aspect embodiments when executing the computer program.

[0049] The fifth aspect embodiment of the present application provides an air conditioner, which includes a second memory and a second processor, the second memory stores a computer program, and the second processor implements the anti-condensation control method of the air conditioner of any one of the second aspect embodiments when executing the computer program.

[0050] The sixth aspect embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the anti-condensation control method of the air conditioner of any one of the first aspect embodiments or the second aspect embodiments.

[0051] Additional aspects and advantages of the present application will be made apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0052] The present application will be further described with reference to the drawings and examples, wherein:

[0053] Figure 1 A system structure schematic diagram for applying the anti-condensation control method of the air conditioner of the present application;

[0054] Figure 2 A step flow schematic diagram of the anti-condensation control method of the air conditioner of the first aspect embodiment of the present application;

[0055] Figure 3 Another part of the step flow schematic diagram of the anti-condensation control method of the air conditioner of the first aspect embodiment of the present application;

[0056] Figure 4 A structure schematic diagram of the condensation prediction model of the embodiment of the present application;

[0057] Figure 5 A step flow schematic diagram of the anti-condensation control method of the air conditioner of the second aspect embodiment of the present application;

[0058] Figure 6 A function unit block diagram of the anti-condensation control device of the air conditioner of the embodiment of the present application;

[0059] Figure 7 A hardware structure schematic diagram of the server of the embodiment of the present application;

[0060] Figure 8 A hardware structure schematic diagram of the air conditioner of the embodiment of the present application. DETAILED DESCRIPTION

[0061] The embodiments of the present application will be described in detail below, examples of which are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary, only for explaining the present application, and cannot be understood as limiting the present application.

[0062] In the description of the present application, it is to be understood that the orientation description, such as the orientation or position relationship indicated by up, down, front, back, left, right, etc. is based on the orientation or position relationship shown in the drawings, only for the convenience of describing the present application and simplifying the description, and is not intended to indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0063] In the description of the present application, the meaning of several is more than one, the meaning of multiple is more than two, greater than, less than, more than, etc. are understood as not including the number, above, below, etc. are understood as including the number. If it is described as first, second, it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features or the sequence of indicated technical features.

[0064] In the description of the present application, unless otherwise explicitly limited, the words such as setting, installing, connecting, etc. should be broadly understood, and those skilled in the art can reasonably determine the specific meaning of the above words in the present application in combination with the specific content of the technical solution.

[0065] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "exemplary embodiment", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in combination with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the exemplary description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0066] In the running process of the air conditioner, under the joint action of indoor temperature, evaporator temperature of the air conditioner, indoor humidity, and specific mechanical structure of the air conditioner and other factors, condensation and dripping water is prone to occur, such as condensation and dripping of water on the surface of the air conditioner structure, or blowing out of water droplets with circulating air during the running process, causing bad experience to the user. In the related art, the solution is usually to control the running of the air conditioner after detecting the condensation and dripping water of the air conditioner. Moreover, since the environment of each air conditioner is different, the specific mechanical structure of different models of air conditioners also has slight differences, therefore, it is difficult to predict the condensation of different models of air conditioners and timely adjust the running of the air conditioner. At present, there is an urgent need for a control method that can prevent condensation of different models of air conditioners.

[0067] Based on this, the embodiments of the present application provide an air conditioner condensation prevention control method, device, server, air conditioner and medium, which realizes prediction on different models of air conditioners through a condensation prevention prediction model to predict whether the air conditioner is about to condense, and timely adjusts the compressor speed of the air conditioner when it is predicted that the air conditioner is about to condense, thereby reducing the risk of condensation of the air conditioner. Moreover, during the running process of multiple air conditioners, when the air conditioner condenses, the server updates the condensation prediction model according to the condensation state information of the air conditioner before condensation, so that the condensation prediction model is constantly updated, which can constantly improve the prediction accuracy of the condensation prediction model.

[0068] Refer to Figure 1 , Figure 1 A system structure schematic diagram for applying the anti-condensation control method of the air conditioner is shown in FIG. 1. The system includes a server and a plurality of air conditioners. The server can be a server or a central computer. The server is in communication connection with the plurality of air conditioners. For example, an Internet module such as a Wi-Fi module can be provided in the air conditioner, and the air conditioner is connected to the server through the Internet module. Each air conditioner periodically generates prediction request information, and then the air conditioner sends the prediction request information to the server. The server obtains a first prediction result based on the prediction request information through a condensation prediction model. The first prediction result represents whether the air conditioner will soon condense. In this application, the condensation prediction model is deployed in the server, that is, the prediction process of the model is performed in the server, and the complex calculation involved in the prediction process is performed in the server. One server serves multiple air conditioners at the same time. In this way, the air conditioner does not need to perform complex calculations and does not need to consume a lot of computing resources, which can reduce the cost of the air conditioner.

[0069] It should be noted that the server can be a server, which refers to a computer system that can provide certain services to the air conditioner. Compared with ordinary terminals, the server has higher requirements in stability, security, performance, etc. The server can be a high-performance computer in a network platform, a cluster of multiple high-performance computers, a part of a high-performance computer (such as a virtual machine), a combination of parts of multiple high-performance computers (such as virtual machines), etc.

[0070] The first aspect embodiment of the present application provides an anti-condensation control method of an air conditioner, which is applied to Figure 1 A schematic server is shown in FIG. 1. Refer to Figure 2 and Figure 3 , Figure 2 A step flowchart of the anti-condensation control method of the air conditioner of the first aspect embodiment of the present application is shown in FIG. 2. Figure 3 Another part of the step flowchart of the anti-condensation control method of the air conditioner of the first aspect embodiment of the present application is shown in FIG. 3.

[0071] Figure 2 The step flowchart shown in FIG. 2 includes steps S210 to S230.

[0072] Step S210, receiving prediction request information sent by a first air conditioner; the prediction request information includes a first air conditioner model, a current running mode, a current evaporator temperature, a current indoor temperature, a current indoor fan speed, and a current indoor humidity;

[0073] It is worth noting that the first air conditioner is one of a plurality of air conditioners in communication connection with the server. Generally, different air conditioners are not of the same model, and different models of air conditioners have different mechanical structures. The first air conditioner model refers to the air conditioner model of the first air conditioner. The first air conditioner model is taken as an input of the condensation prediction model, which can improve the accuracy of the condensation prediction model. The current operation mode refers to the current working mode of the first air conditioner; the current evaporator temperature refers to the current surface temperature of the evaporator of the first air conditioner; the current indoor temperature refers to the current temperature of the room where the first air conditioner is located; the current indoor fan speed refers to the speed of the indoor fan of the first air conditioner; and the current indoor humidity refers to the current humidity of the room where the first air conditioner is located.

[0074] In step S220, the first air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor humidity are input into the condensation prediction model to obtain a first prediction result.

[0075] In step S230, the first prediction result is sent to the first air conditioner, so that the first air conditioner adjusts the compressor speed of the first air conditioner to increase the temperature of the evaporator of the first air conditioner when detecting that the first prediction result indicates that the air conditioner is about to condense. For example, increasing the compressor speed of the first air conditioner can reduce the risk of condensation of the air conditioner.

[0076] Figure 3 The step flowchart shown in FIG. 3 includes steps S310 to S340.

[0077] In step S310, condensation-before-state information is received. The condensation-before-state information is sent by the second air conditioner when condensation occurs. The condensation-before-state information includes a second air conditioner model, a condensation-before-operation mode, a condensation-before-evaporator temperature, a condensation-before-indoor temperature, a condensation-before-indoor fan speed, and a condensation-before-indoor humidity.

[0078] It is worth noting that the second air conditioner is one of a plurality of air conditioners in communication connection with the server.

[0079] In some embodiments, the second air conditioner is provided with a sensor for detecting whether the air outlet drips water, for example, a humidity sensor for detecting the humidity of the relevant structure surface of the air outlet. When the humidity sensor detects that the humidity is greater than a preset humidity threshold, it indicates that the air conditioner has condensation. Furthermore, the evaporator temperature before the condensation occurs is obtained as the pre-condensation evaporator temperature, the indoor temperature before the condensation occurs is obtained as the pre-condensation indoor temperature, the indoor fan speed before the condensation occurs is obtained as the pre-condensation indoor fan speed, the indoor humidity before the condensation occurs is obtained as the pre-condensation indoor humidity, and the operation mode before the condensation occurs is obtained as the pre-condensation operation mode. For example, the preset time period is 3 minutes, and the evaporator temperature before 3 minutes of the condensation occurs is obtained as the pre-condensation evaporator temperature, the indoor temperature before 3 minutes of the condensation occurs is obtained as the pre-condensation indoor temperature, the indoor fan speed before 3 minutes of the condensation occurs is obtained as the pre-condensation indoor fan speed, the indoor humidity before 3 minutes of the condensation occurs is obtained as the pre-condensation indoor humidity, and the operation mode before 3 minutes of the condensation occurs is obtained as the pre-condensation operation mode.

[0080] It should be noted that the preset time period is not limited in the embodiments of the present application, and the value of the preset time period can be set according to actual conditions by those skilled in the art.

[0081] In other embodiments, when the user finds that the second air conditioner has condensation and dripping water, the user operates the terminal connected to the second air conditioner. The terminal responds to the operation instruction of the user to obtain the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity from the air conditioner, and then the terminal sends the pre-condensation state information including the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity to the server. The terminal can be a mobile phone, a notebook computer, a tablet computer, a smart watch or the like.

[0082] In step S320, the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity are input into the condensation prediction model to obtain a second prediction result.

[0083] In step S330, a loss value is calculated based on the second prediction result and a loss function.

[0084] In step S340, the condensation prediction model is updated based on the loss value.

[0085] It is worth noting that the anti-condensation control method of the air conditioner of the embodiment of the present application, through the above steps S210 to S230, after receiving the prediction request information from the first air conditioner, the server inputs the first air conditioner model, the current running mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor humidity into the condensation prediction model to obtain the first prediction result. The first prediction result is used to represent whether the first air conditioner is about to condense. When the first prediction result represents that the first air conditioner is about to condense, the first air conditioner adjusts the compressor speed to reduce the temperature of the evaporator of the first air conditioner, thereby reducing the risk of condensation of the air conditioner. Through the above steps S310 to S340, when the second air conditioner condenses, the second air conditioner sends the condensation state information to the server, the server inputs the second air conditioner model, the condensation running mode, the condensation evaporator temperature, the condensation indoor temperature, the condensation indoor fan speed and the condensation indoor humidity into the condensation prediction model to obtain the second prediction result; the loss value is calculated based on the second prediction result and the loss function; the condensation prediction model is updated based on the loss value. In this way, the update of the condensation prediction model is realized, which can continuously improve the prediction accuracy of the condensation prediction model. Therefore, the present application can predict whether the air conditioner is about to condense, and the prediction accuracy is high. When it is predicted that the air conditioner is about to condense, the compressor speed of the air conditioner is adjusted in time, thereby reducing the risk of condensation of the air conditioner.

[0086] In some embodiments, the initial condensation prediction model is pre-trained based on test data and real labels corresponding to the test data. The test data can be obtained by relevant personnel executing different running instructions on different air conditioners, and the real labels are used to represent that the air conditioner is about to condense or that the air conditioner will not condense. The test data includes air conditioner model, running mode, evaporator temperature, indoor temperature, indoor fan speed and indoor humidity. The test data is input into the condensation prediction model to obtain a training result. The training result and the real label corresponding to the test data are input into a loss function to obtain a training loss value, and the condensation prediction model is updated based on the training loss value. In this way, the parameter set of the condensation prediction model is repeatedly updated iteratively until the number of updates reaches a preset iteration threshold, and the obtained condensation prediction model is a pre-trained condensation prediction model.

[0087] In some embodiments, the loss function adopts a cross-entropy loss function.

[0088] In some embodiments, with reference to Figure 4 , Figure 4 is a structural diagram of the condensation prediction model. The condensation prediction model includes a feature extraction module, a residual module, a long short-term memory module and a classifier. Step S320 specifically includes steps S410 to S450.

[0089] Step S410, based on the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity, a first input vector is constructed. The second air conditioner model refers to the air conditioner model of the second air conditioner.

[0090] It is worth noting that since the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity cannot be directly used as the input of the neural network model, it is necessary to convert the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity into a sequence vector, so as to construct the first input vector, and the subsequent process inputs the first input vector to the condensation prediction model.

[0091] Step S420, the first input vector is subjected to feature extraction processing by a feature extraction module to obtain a first input feature;

[0092] It is worth noting that the feature extraction module can be a convolution block, and the first input vector is subjected to convolution processing by the convolution block, so as to realize the feature extraction processing and obtain the first input feature.

[0093] Step S430, the first input feature is subjected to residual processing by a residual module to obtain a first residual feature;

[0094] In some embodiments, the residual module includes a plurality of residual blocks connected in sequence, and the residual processing is a residual connection processing of the plurality of residual blocks in sequence. It should be noted that the residual block is mainly used to solve the gradient vanishing and degradation problem in the training of a deep neural network. Its structure includes a convolution layer, a batch normalization, an activation function and a skip connection. The skip connection directly adds the input to the output to form a residual mapping, so that the network is easier to learn the identity mapping, thereby alleviating the gradient vanishing. When the input and output dimensions are the same, they are directly added; when the dimensions are different, a 1x1 convolution is used to adjust the input dimension to ensure matching. The activation function is usually applied after addition to enhance the non-linear expression ability. The residual block learns the difference between the input and the output through residual learning, which reduces the optimization difficulty, supports the training of a deeper network, and improves the performance. The number of residual blocks is not specifically limited in the present application, and the number of residual blocks can be set according to the actual situation by those skilled in the art.

[0095] Step S440, the first residual feature is input to a long short-term memory module to obtain a first updated feature;

[0096] It should be noted that the Long Short-Term Memory (LSTM) is a special recurrent neural network (RNN) designed to solve the long-term dependency problem encountered by RNN when processing long sequence data. LSTM is a time recurrent neural network that can memorize values of indefinite length and effectively handle long-term dependencies in time series data through its unique structural design. LSTM controls information storage and deletion through the introduction of three gating mechanisms (forget gate, input gate, and output gate) and a memory cell (also known as cell state). These gating mechanisms are composed of sigmoid and tanh functions, which produce a real number vector between 0 and 1, determining the degree of information passing. Through the design of gating mechanisms and cell state, LSTM effectively solves the gradient vanishing or explosion problem encountered by RNN when processing long sequence data, thereby capturing long-term dependencies in sequences. Although the first input vector in the embodiment of the present application is a non-time sequence, the first input vector in the embodiment of the present application includes a large amount of information (second air conditioner model, pre-condensation running mode, pre-condensation evaporator temperature, pre-condensation indoor temperature, pre-condensation indoor fan speed, and pre-condensation indoor humidity), and these information has context information and dependency relationship. The first input vector can be regarded as a long time sequence, so the to-be-extracted vector in the embodiment of the present application is suitable for regression prediction by LSTM, and the dependency relationship between the second air conditioner model, the pre-condensation running mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity can be captured by LSTM.

[0097] In step S450, the first updated feature is input to the classifier to obtain a second prediction result.

[0098] In an embodiment, a Softmax function is used as the classifier. The Softmax function can convert the original output into a probability distribution, so that the output value of each class is between 0 and 1, and the sum of the probabilities of all classes is 1. Compared with other normalization methods such as simple maximum normalization, the Softmax function is more stable in numerical value. When the input value is large or small, the Softmax function can avoid the problem of numerical overflow or underflow, thereby ensuring the stability and accuracy of the model. The calculation of the Softmax function is relatively simple and can be efficiently calculated through vectorization. This makes it possible to reduce the calculation time and resource consumption when training large-scale data sets.

[0099] Correspondingly, in step S330, the second prediction result and the true label representing that the air conditioner is about to condense are input to the cross-entropy loss function to obtain a loss value, and the condensation prediction model is updated based on the loss value.

[0100] The second aspect embodiment of the present application provides a condensation prevention control method of an air conditioner. The condensation prevention control method of the air conditioner of the second aspect embodiment is applied to Figure 1 any one of the air conditioners shown in the figures. Referring to Figure 5 , Figure 5 FIG. 2 is a flowchart of the steps of the condensation prevention control method of the air conditioner of the second aspect embodiment of the present application. The condensation prevention control method of the air conditioner of the second aspect embodiment includes but is not limited to steps S510 to S540.

[0101] In step S510, the air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor temperature of the air conditioner are periodically obtained.

[0102] It should be noted that the present application does not make specific limitations on the periodic interval, and those skilled in the art can set the periodic interval according to the actual situation. The condensation prevention control method of the air conditioner of the second aspect embodiment is applied to Figure 1 any one of the air conditioners shown in the figures, for example, the air conditioner can be the first air conditioner or the second air conditioner described above. When the air conditioner is the first air conditioner, the air conditioner model in step S510 is the first air conditioner model. When the air conditioner is the second air conditioner, the air conditioner model in step S510 is the second air conditioner model.

[0103] In step S520, the predicted request information is generated based on the air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor temperature.

[0104] In step S530, the predicted request information is sent to the server, so that the server inputs the air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor temperature into the condensation prediction model to obtain the first prediction result.

[0105] In step S540, the first prediction result sent by the server is received, and in the case where it is detected that the first prediction result represents that the air conditioner is about to condense, the compressor speed of the air conditioner is adjusted to increase the temperature of the evaporator of the air conditioner.

[0106] In some implementations, when it is detected that the first prediction result represents that the air conditioner will not condense, the original operation state of the air conditioner is maintained.

[0107] It is worth noting that the anti-condensation control method of the air conditioner of the second aspect of the present application periodically generates prediction request information through steps S510 to S540, sends the prediction request information to the server, so that the server inputs the air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor temperature into the condensation prediction model to obtain the first prediction result, receives the first prediction result sent by the server, and adjusts the compressor speed of the air conditioner in the case where it is detected that the first prediction result represents that the air conditioner is about to condense, so as to reduce the temperature of the evaporator of the air conditioner, thereby realizing the reduction of the risk of condensation of the air conditioner.

[0108] In some embodiments, the anti-condensation control method of the air conditioner of the second aspect of the present application further comprises steps S610 to S630.

[0109] Step S610, in response to detecting that the air conditioner condenses, obtaining the pre-condensation evaporator temperature, the pre-condensation operation mode, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity before a preset time period;

[0110] Step S620, generating pre-condensation state information based on the air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity;

[0111] Step S630, sending the pre-condensation state information to the server, so that the server updates the condensation prediction model based on the air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity.

[0112] Through the above steps S610 to S630, when it is detected that the air conditioner condenses, the pre-condensation state information is sent to the server, so that the server can update the condensation prediction model based on the pre-condensation state information, thereby improving the accuracy of the condensation prediction model.

[0113] In some embodiments, the adjustment of the compressor speed of the air conditioner in step S540 comprises steps S710 to S730.

[0114] Step S710, determining a reference temperature based on the current indoor temperature and a preset temperature coefficient;

[0115] Step S720, obtaining the current compressor speed of the air conditioner, and determining a target speed based on the current evaporator temperature, the reference temperature and the current compressor speed;

[0116] Step S730, setting the speed of the compressor of the air conditioner to the target speed.

[0117] Specifically, the reference temperature is DCTUYU, and if the current evaporator temperature < DCTUYU, then f1 = f0 - fx;

[0118] f1 = f0 - fx;

[0119] If the current evaporator temperature < (DCTUYU + TUYUDC1), TUYUDC1 is a first preset coefficient, then f1 = f0 - fx;

[0120] f1 = f0;

[0121] If (DCTUYU + TUYUDC2) > current evaporator temperature > (DCTUYU + TUYUDC1), TUYUDC2 is a second preset coefficient, then f1 = f0 + fx;

[0122] f1 = f0 + fx;

[0123] If the current evaporator temperature > (DCTUYU + TUYUDC2), then f1 = 120;

[0124] f1 = 120;

[0125] f1 is the target rotating speed, f0 is the current compressor rotating speed, and fx is a preset value. The reference temperature is calculated as follows:

[0126] DCTUYU = ATUYU + BTUYU * TR;

[0127] wherein ATUYU is a temperature constant, BTUYU is a temperature coefficient, and TR is the current indoor temperature.

[0128] In some embodiments, if the current indoor temperature is greater than 27 degrees Celsius, TR is fixed as 27.

[0129] In an embodiment, TUYUDC1 = 0, TUYUDC2 = 2, and fx = 3. Those skilled in the art can set the values of TUYUDC1, TUYUDC2, fx, ATUYU, and BTUYU according to actual needs.

[0130] In some embodiments, after the rotating speed of the compressor of the air conditioner is set as the target rotating speed, steps S810 and S820 are included;

[0131] S810, if it is detected that the target rotating speed is greater than a preset threshold, the rotating speed of the indoor fan of the air conditioner is reduced;

[0132] S820, the air outlet direction of the air conditioner is controlled to be upward air outlet.

[0133] Exemplarily, in the refrigeration mode, since the target rotating speed is greater than the preset threshold value, it indicates that the refrigeration capacity of the current air conditioner is relatively strong, at this time, the cold wind blown by the air conditioner can cause human body discomfort, therefore, the rotating speed of the indoor fan of the air conditioner is reduced, and the air outlet direction of the air conditioner is controlled to be upward air outlet, so as to avoid that the cold wind causes human body discomfort.

[0134] The third aspect embodiment of the present application provides a condensation control device of an air conditioner, applied to Figure 1 The schematic service end; refer to Figure 6 , Figure 6 The functional unit block diagram of the condensation control device of the air conditioner of the embodiment of the present application.

[0135] The control device comprises:

[0136] The first receiving unit 610 is configured to receive the prediction request information sent by the first air conditioner; the prediction request information comprises the first air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor humidity;

[0137] The first input unit 620 is configured to input the first air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor humidity into the condensation prediction model to obtain the first prediction result;

[0138] The first generating unit 630 is configured to send the first prediction result to the first air conditioner, so that the first air conditioner adjusts the compressor rotating speed of the first air conditioner to increase the temperature of the evaporator of the first air conditioner when detecting that the first prediction result represents that the air conditioner is about to condense;

[0139] The second receiving unit 640 receives the pre-condensation state information, the pre-condensation state information is sent by the second air conditioner when the condensation occurs, and the pre-condensation state information comprises the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity;

[0140] The second input unit 650 is configured to input the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity into the condensation prediction model to obtain the second prediction result;

[0141] The loss function unit 660 is configured to calculate a loss value based on the second prediction result and the loss function;

[0142] The updating unit 670 is configured to update the condensation prediction model based on the loss value.

[0143] It is worth noting that the anti-condensation control device of the air conditioner of the third aspect embodiment is used to execute the anti-condensation control method of the air conditioner of the first aspect embodiment. When the method is executed, after receiving the prediction request information from the first air conditioner, the first air conditioner model, the current operation mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed and the current indoor humidity are input into the condensation prediction model to obtain a first prediction result. The first prediction result is used to represent whether the first air conditioner is about to condense. When the first prediction result represents that the first air conditioner is about to condense, the first air conditioner adjusts the compressor speed to reduce the temperature of the evaporator of the first air conditioner, thereby reducing the risk of condensation of the air conditioner. And when the second air conditioner condenses, the second air conditioner sends the pre-condensation state information to the server, the server inputs the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed and the pre-condensation indoor humidity into the condensation prediction model to obtain a second prediction result; the loss value is calculated based on the second prediction result and the loss function; the condensation prediction model is updated based on the loss value. In this way, the update of the condensation prediction model is realized, and the prediction accuracy of the condensation prediction model can be continuously improved. Therefore, the present application can predict whether the air conditioner is about to condense, and the prediction accuracy is high. When it is predicted that the air conditioner is about to condense, the compressor speed of the air conditioner is adjusted in time, thereby reducing the risk of condensation of the air conditioner.

[0144] The fourth aspect embodiment of the present application provides a server. The server comprises a first memory and a first processor. The first memory stores a computer program. The first processor executes the computer program to implement the anti-condensation control method of the air conditioner of any one of the first aspect embodiments. For details, refer to the method embodiment of the first aspect. Figure 7 , Figure 7 The figure is a hardware structure schematic diagram of the server of the embodiment of the present application. The server comprises:

[0145] The first processor 701 can be implemented in the form of a general CPU (Central Processing Unit, central processor), a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute related programs to implement the technical solutions provided by the embodiments of the present application;

[0146] The first memory 702 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The first memory 702 can store an operating system and other application programs. When the technical solutions provided in the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the first memory 702 and are invoked and executed by the first processor 701 to implement the anti-condensation control method of the air conditioner according to the first aspect of the present application.

[0147] The first input / output interface 703 is configured to realize information input and output.

[0148] The first communication interface 704 is configured to realize the communication interaction between the device and other devices. The communication can be realized by a wired manner (for example, a USB, a network cable, etc.) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.).

[0149] The first bus 705 is configured to transmit information between various components (for example, the first processor 701, the first memory 702, the first input / output interface 703, and the first communication interface 704) of the device.

[0150] The first processor 701, the first memory 702, the first input / output interface 703, and the first communication interface 704 are connected to each other through the first bus 705 to realize the communication connection between the device.

[0151] The fifth aspect of the present application provides an air conditioner. The air conditioner comprises a second memory and a second processor. The second memory stores a computer program. The second processor implements the anti-condensation control method of the air conditioner according to any one of the second aspect of the present application when executing the computer program. For details, refer to the description of the second aspect of the present application. Figure 8 , Figure 8 The air conditioner according to the embodiments of the present application is shown in the hardware structure diagram. The air conditioner comprises:

[0152] The second processor 801 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc. The second processor 801 is configured to execute related programs to implement the technical solutions provided in the embodiments of the present application.

[0153] The second memory 802 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The second memory 802 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the second memory 802 and are called and executed by the second processor 801 to implement the anti-condensation control method of the air conditioner of the second aspect of the present application;

[0154] The second input / output interface 803 is configured to realize information input and output.

[0155] The second communication interface 804 is configured to realize the communication interaction between the device and other devices. The communication can be realized by a wired manner (for example, a USB, a network cable, etc.) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.).

[0156] The second bus 805 is configured to transmit information between various components (for example, the second processor 801, the second memory 802, the second input / output interface 803, and the second communication interface 804) of the device.

[0157] The second processor 801, the second memory 802, the second input / output interface 803, and the second communication interface 804 are connected to each other through the second bus 805 to realize the communication connection between the device.

[0158] The computer readable storage medium of the sixth aspect of the present application stores a computer program. When the computer program is executed by a processor, the anti-condensation control method of the air conditioner of any one of the first aspect or the second aspect of the present application is realized.

[0159] The memory is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0160] The embodiments described in the specification are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0161] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than shown in the figures, or combine certain steps, or different steps.

[0162] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, i.e., can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0163] Those skilled in the art can understand that all or some of the steps in the above disclosed method, the functional modules / units in the system and the device can be implemented as software, firmware, hardware and their appropriate combinations.

[0164] The terms "first", "second", "third", "fourth" and the like (if any) in the specification and above-described drawings of the present application are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0165] It should be understood that in the application, "at least one" refers to one or more, and "multiple" refers to two or more. "And / or" is used to describe the mapping relationship of the mapping object, which means that there can be three relationships, for example, "A and / or B" can represent three cases: only A, only B, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the front and rear mapping objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0166] In several embodiments provided in the application, it should be understood that the disclosed system and method can be implemented in other ways. For example, the system embodiments described above are only illustrative, for example, the division of the above units is only a logical functional division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0167] The units described above as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0168] In addition, each functional unit in each embodiment of the application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0169] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0170] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A method for preventing condensation in an air conditioner, characterized in that, The application is on the server side, which is connected to multiple air conditioners and is equipped with a pre-trained condensation prediction model. The method includes: Receive prediction request information sent by the first air conditioner; the prediction request information includes the model of the first air conditioner, the current operating mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor humidity; The first air conditioner model, the current operating mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor humidity are input into the condensation prediction model to obtain the first prediction result; The first prediction result is sent to the first air conditioner so that when the first prediction result indicates that the air conditioner is about to condense, the first air conditioner adjusts the compressor speed of the first air conditioner to increase the temperature of the evaporator of the first air conditioner. The system receives pre-condensation status information, which is sent by the second air conditioner when condensation occurs. The pre-condensation status information includes the model of the second air conditioner, the pre-condensation operating mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity. The process of acquiring the pre-condensation status information is as follows: in response to detecting condensation on the air conditioner, the system acquires the pre-condensation evaporator temperature, pre-condensation operating mode, pre-condensation indoor temperature, pre-condensation indoor fan speed, and pre-condensation indoor humidity before a preset time period. The second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity are input into the condensation prediction model to obtain the second prediction result. The loss value is calculated based on the second prediction result and the loss function. The condensation prediction model is updated based on the loss value.

2. The anti-condensation control method for air conditioners according to claim 1, characterized in that, The condensation prediction model includes a feature extraction module, a residual module, a long short-term memory module, and a classifier; The second air conditioner model, the pre-condensation operating mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity are input into the condensation prediction model to obtain a second prediction result, including: Based on the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity, a first input vector is constructed. The feature extraction module performs feature extraction processing on the first input vector to obtain the first input features; The first input feature is processed by the residual module to obtain the first residual feature; The first residual feature is input into the long short-term memory module to obtain the first updated feature; The first updated feature is input into the classifier to obtain the second prediction result.

3. The anti-condensation control method for an air conditioner according to claim 1, characterized in that, Adjusting the compressor speed of the first air conditioner includes: A reference temperature is determined based on the current indoor temperature and a preset temperature coefficient. Obtain the current compressor speed of the first air conditioner, and determine the target speed based on the current evaporator temperature, the reference temperature, and the current compressor speed; The compressor speed of the first air conditioner is set to the target speed.

4. The anti-condensation control method for an air conditioner according to claim 3, characterized in that, After setting the compressor speed of the first air conditioner to the target speed, the process includes: If the target rotation speed is detected to be greater than a preset threshold, the rotation speed of the indoor fan of the first air conditioner is reduced; The air outlet direction of the first air conditioner is controlled to be upward.

5. An anti-condensation control device for an air conditioner, characterized in that, The application is on the server side, which is connected to multiple air conditioners and is equipped with a pre-trained condensation prediction model. The control device includes: The first receiving unit is used to receive prediction request information sent by the first air conditioner; the prediction request information includes the model of the first air conditioner, the current operating mode, the current evaporator temperature, the current indoor temperature, the current indoor fan speed, and the current indoor humidity. The first input unit is used to input the first air conditioner model, current operating mode, current evaporator temperature, current indoor temperature, current indoor fan speed and current indoor humidity into the condensation prediction model to obtain a first prediction result; The first generating unit is configured to send the first prediction result to the first air conditioner, so that when the first air conditioner detects that the first prediction result indicates that the air conditioner is about to condense, it adjusts the compressor speed of the first air conditioner to increase the temperature of the evaporator of the first air conditioner. The second receiving unit receives pre-condensation status information, which is sent by the second air conditioner when condensation occurs. The pre-condensation status information includes the model of the second air conditioner, the pre-condensation operating mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity. The process of acquiring the pre-condensation status information is as follows: in response to detecting condensation on the air conditioner, the pre-condensation evaporator temperature, pre-condensation operating mode, pre-condensation indoor temperature, pre-condensation indoor fan speed, and pre-condensation indoor humidity are acquired before a preset time period. The second input unit is used to input the second air conditioner model, the pre-condensation operation mode, the pre-condensation evaporator temperature, the pre-condensation indoor temperature, the pre-condensation indoor fan speed, and the pre-condensation indoor humidity into the condensation prediction model to obtain the second prediction result. The loss function unit is used to calculate the loss value based on the second prediction result and the loss function. An update unit is used to update the condensation prediction model based on the loss value.

6. A server-side component, characterized in that, The server includes a first memory and a first processor. The first memory stores a computer program, and when the first processor executes the computer program, it implements the anti-condensation control method for the air conditioner according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the anti-condensation control method for the air conditioner according to any one of claims 1 to 4.

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