Self-adaptive ventilation cooling control system and method

Abstract

The invention belongs to the technical field of aeration cooling, and provides a self-adaptive aeration cooling control system and method. The method comprises the following steps: S10, determining a region attribute of a target region, and determining a matched wind speed range according to the region attribute; s20, calculating the temperature difference between the real-time temperature and the standard temperature of the target area, and predicting a first wind speed generated by using the ventilation cooling equipment which is currently in an activated state to deal with the temperature difference; s30, if the first wind speed does not exceed the wind speed range, the ventilation cooling equipment in the activated state at present is used for reducing the temperature difference; and S40, if the first wind speed exceeds the wind speed range, determining and using a group of new ventilation cooling equipment to reduce the temperature difference according to a second wind speed in the wind speed range. During ventilation and cooling, high-speed airflow can be prevented from interfering links such as precision assembly and test of the motor, and the problems of deviation of parts, dust adsorption, misalignment of test and the like are prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of ventilation and cooling, and in particular, to an adaptive ventilation and cooling control system and method. Background Art

[0002] By means of ventilation and cooling, the temperature inside the shaded-pole motor production workshop is always maintained within a suitable range, so as to ensure the production quality of shaded-pole motors and the working comfort of operators at the same time.

[0003] Traditional ventilation control methods mostly adopt fixed ventilation modes or adjustment strategies triggered by single parameters. On the one hand, when the workshop temperature exceeds the standard, the control system blindly increases the ventilation speed to quickly cool down. However, high-speed airflows are likely to interfere with the assembly process of precision components of shaded-pole motors, causing problems such as winding positioning deviation and uneven coating of insulating materials, resulting in an increase in product defect rate. On the other hand, in order to avoid the interference of airflows on production, some workshops adopt low-speed constant-speed ventilation. However, during high-temperature periods or when equipment is operating at high loads, this method is difficult to meet the rapid cooling requirements.

[0004] It can be seen that the existing ventilation and cooling control methods cannot meet the actual needs of shaded-pole motor production workshops. There is an urgent need for a control method that can adaptively adjust the ventilation strategy according to the actual situation of shaded-pole motor workshops, so as to achieve efficient and energy-saving ventilation and cooling effects without affecting the production process. Summary of the Invention

[0005] In view of this, the present invention provides an adaptive ventilation and cooling control method, system, electronic device, computer storage medium, and computer program product to solve at least one of the above technical problems.

[0006] In the first aspect of the present invention, an adaptive ventilation and cooling control method is provided, including the following method steps: S10, determining the regional attribute of the target area, and determining the matching wind speed range according to the regional attribute; wherein, the target area is any area in the shaded-pole motor production workshop.

[0007] S20, calculating the temperature difference between the real-time temperature and the standard temperature of the target area, predicting the first wind speed generated by using the currently activated ventilation and cooling equipment to cope with the temperature difference, and comparing the first wind speed with the wind speed range.

[0008] S30, if the first wind speed does not exceed the wind speed range, using the currently activated ventilation and cooling equipment to reduce the temperature difference.

[0009] S40. If the first wind speed exceeds the wind speed range, determine a new set of ventilation and cooling devices, and use this set of ventilation and cooling devices to reduce the temperature difference at the second wind speed; wherein, the second wind speed is within the wind speed range.

[0010] In the second aspect of the present invention, an adaptive ventilation and cooling control system is provided. The system includes a processing unit and a storage unit. The processing unit calls and executes a computer program stored in the storage unit to implement the following steps: S10. Determine the area attribute of the target area, and determine the matching wind speed range according to the area attribute; wherein, the target area is any area in the shaded pole motor production workshop.

[0011] S20. Calculate the temperature difference between the real-time temperature and the standard temperature of the target area, predict the first wind speed generated by using the currently activated ventilation and cooling devices to cope with the temperature difference, and compare the first wind speed with the wind speed range.

[0012] S30. If the first wind speed does not exceed the wind speed range, use the currently activated ventilation and cooling devices to reduce the temperature difference.

[0013] S40. If the first wind speed exceeds the wind speed range, determine a new set of ventilation and cooling devices, and use this set of ventilation and cooling devices to reduce the temperature difference at the second wind speed; wherein, the second wind speed is within the wind speed range.

[0014] In the third aspect of the present invention, an electronic device is provided. The electronic device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor. When the computer program is executed by the processor, it implements the method described in any one of the foregoing.

[0015] In the fourth aspect of the present invention, a computer storage medium is provided. The computer storage medium stores a computer program that can be executed by a processor to implement the method described in any one of the foregoing.

[0016] In the fifth aspect of the present invention, a computer program product is provided. The computer program product includes a computer program that can be executed by a processor to implement the method described in any one of the foregoing.

[0017] By determining the area attribute to match the wind speed range, when the first wind speed exceeds the limit, the ventilation equipment group is optimized and adjusted to operate at an appropriate wind speed. This can not only avoid the interference of high-speed air flow on the precision assembly, testing and other links of the motor, prevent problems such as component offset, dust adsorption, and testing inaccuracy, but also ensure effective cooling in each area, guarantee the stability of the production environment, improve product quality and production efficiency, and achieve the balance between ventilation and cooling and production quality. Description of the Drawings

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0019] Figure 1 is a schematic flowchart of an adaptive ventilation and cooling control method disclosed in an embodiment of the present invention.

[0020] Figure 2 is a schematic structural diagram of a wind speed prediction model disclosed in an embodiment of the present invention.

[0021] Figure 3 is a schematic structural diagram of an adaptive ventilation and cooling control system disclosed in an embodiment of the present invention. Specific Embodiments

[0022] The following specific embodiments illustrate the implementation manners of the present application. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope protected by the present application.

[0023] In addition, the technical features involved in different implementation manners of the present application described below can be combined with each other as long as they do not conflict with each other.

[0024] As Figure 1 shown, an embodiment of the present invention discloses an adaptive ventilation and cooling control method, including the following method steps: S10, determining the regional attribute of the target area, and determining the matching wind speed range according to the regional attribute; wherein, the target area is any area in the shaded-pole motor production workshop.

[0025] The production workshop of the shaded-pole motor can be divided into multiple areas according to production tasks, equipment types, etc. The production activities, equipment distribution, and wind speed tolerance in different areas are not the same. The regional attribute includes whether the target area is for the precision assembly of motor components, for the storage of raw materials, or for the testing area of the motor, etc. For example, in the winding area of the motor winding and the painting area of insulating materials, due to the fineness of the operation, the requirements for wind speed are relatively strict; while in the raw material storage area, the requirements for wind speed are relatively loose.

[0026] Correspondingly configured wind speed ranges are pre-set for different area attributes. For the precision assembly area, the upper limit of the wind speed range is smaller to avoid interference of high-speed airflows on the assembly, painting, testing, etc. of components; while for some areas that are not sensitive to airflows, the upper limit of the wind speed range can be appropriately expanded.

[0027] S20. Calculate the temperature difference between the real-time temperature and the standard temperature of the target area, predict the first wind speed generated by using the currently activated ventilation and cooling equipment to cope with the temperature difference, and compare the first wind speed with the wind speed range.

[0028] In each area of the shaded-pole motor production workshop, a set of temperature sensors are arranged. Through these temperature sensors, the real-time temperature of the corresponding target area can be obtained. At the same time, an appropriate temperature, that is, the above-mentioned standard temperature, is also pre-set for the target area according to the shaded-pole motor production process and the comfort requirements of the operators. When the real-time temperature is higher than this standard temperature (for example, the temperature difference reaches a predetermined value), it is determined that there is a ventilation requirement (or an enhanced ventilation requirement), and then the target area is ventilated and cooled to maintain it near the standard temperature.

[0029] In the target area, multiple ventilation and cooling equipment are arranged. Under normal circumstances, only a part of them are activated for conventional ventilation and cooling. Therefore, according to the equipment parameters of the currently activated ventilation and cooling equipment (such as the power and air volume of the fan), as well as factors such as the space size and heat load of the target area, predict the wind speed generated in the target area when using these equipment to reduce the above temperature difference, that is, the first wind speed.

[0030] Compare the predicted first wind speed with the wind speed range matched to the target area to determine whether the wind speed generated by the currently activated ventilation and cooling equipment in coping with the temperature difference is within the appropriate range.

[0031] S30. If the first wind speed does not exceed the wind speed range, use the currently activated ventilation and cooling equipment to reduce the temperature difference.

[0032] S40. If the first wind speed exceeds the wind speed range, determine a new set of ventilation and cooling equipment, and use this set of ventilation and cooling equipment to reduce the temperature difference at the second wind speed; where the second wind speed is within the wind speed range.

[0033] When the first wind speed does not exceed the matched wind speed range, it means that the currently activated ventilation and cooling equipment can meet the demand for reducing the temperature difference and will not have an adverse impact on the production activities in the target area. At this time, directly use these ventilation and cooling equipment for ventilation and cooling, which can not only ensure the normal progress of production but also avoid unnecessary equipment adjustment and energy waste.

[0034] When the first wind speed exceeds the matching wind speed range, it means that the currently activated ventilation and cooling equipment needs to significantly increase the rotational speed to reduce the temperature in the target area to the standard temperature. However, the resulting excessive wind speed will have an adverse impact on the production of shaded pole motors in the target area. Therefore, a new set of ventilation and cooling equipment needs to be re-determined, mainly considering factors such as the power of the ventilation equipment, the type of the ventilation equipment, and the distribution location of the ventilation equipment.

[0035] After determining a new set of ventilation and cooling equipment, control these ventilation and cooling equipment to operate at a second wind speed within the wind speed range. This can ensure effective reduction of the temperature difference while avoiding interference with production caused by high-speed airflows, thereby achieving adaptive ventilation and cooling control and meeting the actual needs of the shaded pole motor production workshop.

[0036] The present invention determines the wind speed range matching the regional attributes. When the first wind speed exceeds the limit, it optimizes the ventilation equipment group and adjusts it to operate at an appropriate wind speed. This can not only avoid interference with precision assembly, testing and other processes of the motor by high-speed airflows, prevent problems such as component offset, dust adsorption, and inaccurate testing, but also ensure effective cooling in each area, guarantee the stability of the production environment, improve product quality and production efficiency, and achieve the balance between ventilation and cooling and production quality.

[0037] As an example, determining the regional attributes of the target area and determining the matching wind speed range according to the regional attributes includes: determining the regional attributes of the target area, and judging whether there is a preset wind speed range matching the regional attributes by querying the database. If it exists, determine this preset wind speed range as the matching wind speed range; if not, extract several production element features of the shaded pole motor from the high-definition video data of the target area, predict the production process of the shaded pole motor based on each production element feature, query the database based on this production process, obtain the preset wind speed range corresponding to this production process, and determine it as the matching wind speed range.

[0038] Multiple preset wind speed ranges are stored in the database, and each preset wind speed range corresponds to a specific production process. As shown in Table 1 below.

[0039] Table 1:

[0040] Staff can pre-enter or associate the corresponding production processes in the area attributes of each target area. In this way, the wind speed range of the target area can be determined by querying Table 1 in the database above. If the area attribute of the target area does not enter or associate the corresponding production process, image recognition technology is used to actively analyze the production process currently implemented in the target area. Specifically as follows: Call the high-definition video data captured by the high-definition camera in the target area, and extract the production element features of the shaded-pole motor from it, such as the type of parts, the shape of parts, operation actions, etc. Predict the production process based on these features, and then find the preset wind speed range corresponding to this production process by querying the database, and determine it as the range matched by the target area, which can solve the problem of determining the wind speed range in special cases.

[0041] Predicting the production process based on the features of each production element can be achieved through a pre-constructed model. This model can be based on neural network algorithms and their variants, or a fusion algorithm can be used, such as the fusion algorithm of deep reinforcement learning (DRL) and adaptive fuzzy control (AFC), the integrated learning algorithm combined with the Bayesian optimization algorithm, etc. The present invention does not make specific limitations.

[0042] As an example, the prediction uses the currently activated ventilation and cooling equipment to deal with the first wind speed generated by the temperature difference, including: constructing a wind speed prediction model, including a feature extraction module based on InfiniteFormer and an optimization module based on Proximal Policy Optimization; the feature extraction module extracts features from the input data, and the input data includes the equipment parameters and installation locations of the currently activated ventilation and cooling equipment, the spatial structure information of the target area, and the cooling duration; the optimization module performs prediction processing on the feature data output by the feature extraction module to obtain the first wind speed.

[0043] The present invention uses a model to process the equipment parameters, installation locations of the currently activated ventilation and cooling equipment, and the spatial structure information of the target area, and accordingly predicts the first wind speed generated in the target area when using the currently activated ventilation and cooling equipment to deal with the temperature difference. This first wind speed can be the local maximum wind speed that will be generated in the target area at that time. However, the ventilation and cooling equipment parameters, installation locations, and the spatial structure of the target area, etc. are very complex information, and it is difficult for conventional algorithms to extract features related to wind speed from them. To address the above technical difficulties, the present invention constructs the above-mentioned wind speed prediction model based on InfiniteFormer and Proximal Policy Optimization (PPO). This model includes a feature extraction module based on InfiniteFormer and an optimization module based on Proximal Policy Optimization, as Figure 2 shown.

[0044] The self-attention mechanism of the InfiniteFormer can automatically learn the long-term dependencies in the input data. For complex information such as the parameters of ventilation and cooling equipment, the layout positions, and the spatial structure of the target area, it can effectively capture the key features. At the same time, the self-attention mechanism of the InfiniteFormer can also process these input data efficiently in parallel, quickly identifying the influence degree of ventilation equipment at different positions on the wind speed in a specific area, and how obstacles in the spatial structure change the air flow direction and speed.

[0045] The optimization module based on PPO has optimized the policy network after training. In the prediction stage, it can directly use the learned policy for fast inference, reducing the computational amount and decision-making time, and can timely provide wind speed prediction information for relevant applications.

[0046] The prediction processing process of the wind speed prediction model is generally as follows: 1. Data input.

[0047] Collect and organize the equipment parameters, layout positions of the currently activated ventilation and cooling equipment, the spatial structure information of the target area, and the cooling duration. Among them, the equipment parameters include fan power, air volume, blade angle, rotation speed, etc.; there are also the layout positions of the equipment, such as the specific coordinates and heights of the equipment in the target area.

[0048] The spatial structure information of the target area includes the length, width, and height of the target area, the positions, sizes, and numbers of ventilation openings, the distribution of obstacles, etc. The spatial structure information of the target area determines the air flow path in the area and the possible obstacles, and has an important impact on the formation and distribution of wind speed.

[0049] The cooling duration is the time required to achieve the cooling target. Different cooling durations will have different requirements for the operating intensity of the ventilation equipment and the wind speed. The cooling duration can be a fixed value, which can be obtained according to the regional attributes or production stages. For example, the cooling duration of the target area for performing precision assembly operations is lower, that is, when the temperature rises abnormally, the temperature needs to be reduced to the standard temperature at a faster speed, and the details will not be elaborated here.

[0050] 2. Feature extraction (feature extraction module based on InfiniteFormer).

[0051] Preprocess the input data, including data cleaning (removing outliers, handling missing values) and normalization (unifying data with different ranges and dimensions into the same interval, such as [0,1]).

[0052] Convert the preprocessed input data into a low-dimensional vector representation. Different types of input features (i.e., equipment parameters, layout positions, spatial structure information, cooling duration) are respectively converted through different embedding matrices to increase the data expression ability.

[0053] Multi-Head Self-Attention Mechanism: It is the core part of the Infinite Former. Through multiple parallel attention heads, it focuses on different parts of the input sequence from different subspaces. The specific operations are as follows: (1) Multiply the output of the embedding layer by three learnable weight matrices respectively to obtain the Query, Key, and Value matrices.

[0054] (2) Calculate the dot product of the Query matrix and the Key matrix to obtain the attention scores. Through scaling and masking operations, the rationality and effectiveness of the scores are ensured.

[0055] (3) Use the Softmax function to convert the attention scores into attention weights, which represent the degree of attention of each time step to other time steps.

[0056] (4) Multiply the attention weights by the Value matrix and sum them to obtain the context vector for each time step. In this way, the wind speed prediction model can effectively capture the key features in the complex information of the ventilation and cooling equipment parameters, layout positions, target area spatial structures, and cooling durations.

[0057] Feed-Forward Neural Network Processing: Input the output of the multi-head self-attention mechanism into the feed-forward neural network for non-linear transformation. The feed-forward neural network usually consists of two fully connected layers and an activation function (such as ReLU) to further extract deep feature representations.

[0058] Layer Normalization and Residual Connection: After the multi-head self-attention mechanism and the feed-forward neural network, layer normalization operations are used respectively to stabilize the training of the model. At the same time, the input is directly added to the output through the residual connection to alleviate the problem of gradient disappearance and improve the training efficiency of the model. Finally, the feature extraction module outputs feature data containing key information.

[0059] 3. Prediction Processing (Optimization Module Based on Proximal Policy Optimization).

[0060] State Input: Use the feature data output by the feature extraction module as the state input of the optimization module.

[0061] Policy Network Decision: The policy network of the optimization module outputs the probability distribution of actions according to the current state. Among them, the action refers to an adjustment strategy for the prediction result. Since the policy network has been optimized during the training phase, the learned policy can be directly used for inference during the prediction phase.

[0062] Prediction Result Generation: According to the action probability distribution output by the policy network, sample specific actions, further process and adjust the feature data, and finally generate the predicted first wind speed. Among them, the first wind speed refers to the maximum local wind speed predicted during ventilation and cooling in the target area.

[0063] 4. Result output.

[0064] The wind speed prediction model outputs the predicted first wind speed as the final result.

[0065] As an example, the determination of a set of new ventilation and cooling devices includes: screening out multiple ventilation and cooling schemes by using the permutation and combination method, where the number and layout positions of the ventilation and cooling devices included in each ventilation and cooling scheme are different; using CFD simulation software to perform simulation analysis on each ventilation and cooling scheme, and screening out the ventilation and cooling schemes that can reduce the temperature of the target area to the standard temperature within the cooling time and the wind speed is always within the matching wind speed range; using the wind speed prediction model to predict the third wind speed corresponding to each ventilation and cooling scheme, and screening out the ventilation and cooling schemes where the third wind speed is within the wind speed range.

[0066] Multiple ventilation and cooling devices are arranged at different positions in the target area, and the types and device parameters of these devices can be the same or different. The types of devices include axial flow fans, centrifugal fans, air conditioning units, etc., and the device parameters include power, air volume, air pressure, etc. Usually, only some ventilation and cooling devices are activated to work to handle ventilation and cooling under normal temperature conditions, while when the temperature rises abnormally, it is necessary to re-determine which ventilation and cooling devices to activate to ensure both rapid cooling and no excessive wind speed in the target area.

[0067] By means of permutation and combination, all ventilation and cooling devices are combined with different numbers and different layout positions to generate multiple ventilation and cooling schemes.

[0068] Then, the present invention inputs the detailed information of each ventilation and cooling scheme (i.e., device type, quantity, layout position, etc.) and the relevant parameters of the target area (such as spatial structure, real-time temperature, heat load distribution, etc.) into CFD (Computational Fluid Dynamics) simulation software. Based on the basic principles of fluid mechanics, the CFD software can simulate physical phenomena such as air flow and heat transfer in the target area through numerical calculation methods, so as to simulate the temperature change over time and the wind speed distribution in the target area under each ventilation and cooling scheme. According to the preset cooling time and standard temperature, those ventilation and cooling schemes that can reduce the temperature of the target area to the standard temperature within the specified time and the wind speed is always maintained within the wind speed range matching the target area attributes are screened out.

[0069] However, the simulation of the CFD software depends on the setting of boundary conditions (such as inlet wind speed, temperature), and these conditions may fluctuate during actual operation. In addition, the selection of the turbulence model, grid accuracy, etc. will also introduce certain errors. Therefore, the above-mentioned qualified ventilation and cooling schemes obtained by its simulation may not be feasible.

[0070] To solve this technical problem, based on the solutions screened by CFD simulation, the present invention further uses a wind speed prediction model to perform a secondary prediction on the wind speed corresponding to each ventilation and cooling solution. This wind speed prediction model can accurately predict the third wind speed in the target area under each solution according to information such as the parameters of the ventilation and cooling equipment, the layout position, and the spatial structure of the target area. The specific prediction process is the same as the foregoing and will not be elaborated here. According to the predicted third wind speed, the ventilation and cooling solutions with the third wind speed within the previously determined matching wind speed range are screened again.

[0071] Through this embodiment, it can be ensured that the finally determined ventilation and cooling solution can not only meet the cooling requirements, but also the wind speed fully complies with the specified range, thereby providing a more accurate and reliable ventilation and cooling effect for the target area.

[0072] It should be noted that the simulation analysis of the CFD software actually takes a relatively long time. Therefore, the step of using the CFD simulation software to perform a simulation analysis on each ventilation and cooling solution can be pre-implemented to obtain multiple qualified ventilation and cooling solutions corresponding to different real-time temperatures (or temperature differences) associated with the target area. When there is an abnormal temperature rise, only the third wind speed corresponding to each qualified ventilation and cooling solution is predicted by the wind speed prediction model, and the rapid screening of the ventilation and cooling solutions can be achieved.

[0073] As an example, the screening of the ventilation and cooling solutions with the third wind speed within the wind speed range includes: predicting the future short-term temperature rise trend based on several recorded real-time temperatures of the target area, and calculating the predicted temperature rise intensity according to this trend; determining the screening quantity according to the predicted temperature rise intensity and the corresponding positive correlation relationship, and screening the corresponding number of ventilation and cooling solutions with the third wind speed within the wind speed range according to this screening quantity.

[0074] The foregoing embodiments are all implemented based on real-time temperatures. However, during the implementation of the ventilation and cooling solution, the temperature of the target area may continue to rise, which may cause the implemented ventilation and cooling solution to not be able to reduce the temperature of the target area to the standard temperature. To this end, the present invention sets up alternative ventilation and cooling solutions, that is, screens out multiple qualified ventilation and cooling solutions. If a certain ventilation and cooling solution fails to achieve the cooling target, other alternative ventilation and cooling solutions are switched in time, thereby increasing the probability of achieving the cooling target when the temperature continues to rise.

[0075] Specifically, based on several recorded real-time temperature data of the target area, time series analysis or machine learning algorithms (such as ARIMA, LSTM) are used to predict the future short-term temperature change trend. Accordingly, the predicted temperature rise intensity is calculated. For example, by calculating quantitative indicators such as the temperature rise amplitude and slope per unit time, the severity of the temperature rise is measured.

[0076] Pre - establish a positive - correlation mapping relationship (such as a linear function, piece - wise function) between the predicted temperature - rise intensity and the number of screened options. When the predicted temperature - rise intensity is higher, it indicates that the risk of continuous temperature rise during the cooling process is greater, and the existing solutions may not be able to meet the cooling requirements. Therefore, more eligible ventilation and cooling solutions need to be screened to reserve sufficient selection space for subsequent switching of solutions.

[0077] According to the determined number of screened options, select the corresponding number of solutions from all the solutions that can reduce the temperature of the target area to the standard temperature within the cooling time and the wind speed is within the matching range. It can be understood that these solutions that meet the above conditions actually have different cooling intensities. During the actual cooling process, if the temperature continues to rise, it is possible to switch to a solution with a higher cooling intensity in a timely manner (the corresponding wind speed is still within the wind - speed range, but the wind speed is usually higher), ensuring that the temperature of the target area is controllable. It can be understood that at the initial stage of dealing with the temperature difference, it is preferred to use a solution with a lower cooling intensity, unless the abnormal temperature rise is relatively serious (i.e., the temperature difference is too large), so as to minimize the probability of the cooling wind speed exceeding the standard.

[0078] Among them, the cooling intensity of each ventilation and cooling solution that meets the conditions = (total ventilation volume (sum the ventilation volumes of each device in the ventilation and cooling solution) × specific heat capacity of air × temperature difference of the target area (i.e., the temperature difference between the real - time temperature and the standard temperature) ÷ heat load of the target area. The present invention does not make specific limitations on this. The above calculation method is only for illustrative purposes. In fact, it does not consider the dynamic changes of the heat load of the target area, air humidity, atmospheric pressure, etc. However, the roughly calculated cooling intensity using it is sufficient to evaluate the cooling intensity of each ventilation and cooling solution.

[0079] As Figure 3 shown, an embodiment of the present invention also provides an adaptive ventilation and cooling control system. The system includes a processing unit (101) and a storage unit (102). The processing unit (101) calls and executes the computer program stored in the storage unit (102) to implement the following steps: S10, determine the regional attributes of the target area, and determine the matching wind - speed range according to the regional attributes; wherein, the target area is any area in the shaded - pole motor production workshop.

[0080] S20, calculate the temperature difference between the real - time temperature and the standard temperature of the target area, predict the first wind speed generated by using the currently activated ventilation and cooling equipment to cope with the temperature difference, and compare the first wind speed with the wind - speed range.

[0081] S30, if the first wind speed does not exceed the wind - speed range, use the currently activated ventilation and cooling equipment to reduce the temperature difference.

[0082] S40. If the first wind speed exceeds the wind speed range, determine a new set of ventilation and cooling devices, and use this set of ventilation and cooling devices to reduce the temperature difference at the second wind speed; wherein, the second wind speed is within the wind speed range.

[0083] An embodiment of the present invention also provides an electronic device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor. When the computer program is executed by the processor, the method described in any one of the foregoing items is implemented.

[0084] An embodiment of the present invention also provides a computer storage medium, which stores a computer program executable by a processor to implement the method described in any one of the foregoing items.

[0085] An embodiment of the present invention also provides a computer program product, which includes a computer program executable by a processor to implement the method described in any one of the foregoing items.

[0086] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but this implementation should not be considered to exceed the scope of the present invention.

[0087] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An adaptive ventilation and cooling control method, characterized in that: The method steps are as follows: S10, determine the regional attribute of the target area, and determine the matching wind speed range according to the regional attribute; wherein, the target area is any area in the shaded pole motor production workshop; S20, calculate the temperature difference between the real-time temperature and the standard temperature of the target area, predict the first wind speed generated by using the currently activated ventilation and cooling equipment to cope with the temperature difference, and compare the first wind speed with the wind speed range; S30, if the first wind speed does not exceed the wind speed range, use the currently activated ventilation and cooling equipment to reduce the temperature difference; S40, if the first wind speed exceeds the wind speed range, determine a new set of ventilation and cooling equipment, and use this set of ventilation and cooling equipment to reduce the temperature difference at the second wind speed; wherein, the second wind speed is within the wind speed range.

2. The adaptive ventilation and cooling control method according to claim 1, characterized in that: Determining the regional attribute of the target area and determining the matching wind speed range according to the regional attribute includes: determining the regional attribute of the target area, querying the database to determine whether there is a preset wind speed range matching the regional attribute, if so, determining the preset wind speed range as the matching wind speed range; if not, extracting several production element features of the shaded pole motor from the high-definition video data of the target area, predicting the production link of the shaded pole motor based on each production element feature, querying the database based on this production link, obtaining the preset wind speed range corresponding to this production link, and determining it as the matching wind speed range.

3. An adaptive ventilation and cooling control method according to claim 1, characterized in that: Predicting the first wind speed generated by using the currently activated ventilation and cooling equipment to cope with the temperature difference includes: constructing a wind speed prediction model, including a feature extraction module based on InfiniteFormer and an optimization module based on Proximal Policy Optimization; the feature extraction module extracts features from the input data, and the input data includes the equipment parameters and installation positions of the currently activated ventilation and cooling equipment, the spatial structure information of the target area, and the cooling duration; the optimization module performs prediction processing on the feature data output by the feature extraction module to obtain the first wind speed.

4. An adaptive ventilation and cooling control method according to claim 3, characterized in that: Determining a new set of ventilation and cooling equipment includes: using the permutation and combination method to screen out multiple ventilation and cooling schemes, where the number and installation positions of the ventilation and cooling equipment included in each ventilation and cooling scheme are different; using CFD simulation software to perform simulation analysis on each ventilation and cooling scheme, and screening out the ventilation and cooling scheme that can reduce the temperature of the target area to the standard temperature within the cooling time and the wind speed is always within the matching wind speed range; using the wind speed prediction model to predict the third wind speed corresponding to each ventilation and cooling scheme, and screening out the ventilation and cooling schemes with the third wind speed within the wind speed range.

5. An adaptive ventilation and cooling control method according to claim 4, characterized in that: Screening out the ventilation and cooling schemes with the third wind speed within the wind speed range includes: predicting the warming trend in the near future based on the recorded real-time temperatures of the target area, and calculating the predicted warming intensity according to this warming trend; determining the screening quantity according to the predicted warming intensity and the corresponding positive correlation relationship, and screening out the corresponding number of ventilation and cooling schemes with the third wind speed within the wind speed range according to this screening quantity.

6. An adaptive ventilation and cooling control system, characterized in that, The system includes a processing unit and a storage unit. The processing unit calls and executes the computer program stored in the storage unit to implement the following steps: S10, determining the regional attribute of the target area, and determining the matching wind speed range according to the regional attribute; wherein, the target area is any area in the shaded-pole motor production workshop; S20, calculating the temperature difference between the real-time temperature and the standard temperature of the target area, predicting the first wind speed generated by using the currently activated ventilation and cooling equipment to cope with the temperature difference, and comparing the first wind speed with the wind speed range; S30, if the first wind speed does not exceed the wind speed range, using the currently activated ventilation and cooling equipment to reduce the temperature difference; S40, if the first wind speed exceeds the wind speed range, determining a new set of ventilation and cooling equipment, and using this set of ventilation and cooling equipment to reduce the temperature difference at the second wind speed; wherein, the second wind speed is within the wind speed range.

7. An adaptive ventilation and cooling control system according to claim 6, characterized in that: Determining the regional attribute of the target area and determining the matching wind speed range according to the regional attribute includes: determining the regional attribute of the target area, judging whether there is a preset wind speed range matching the regional attribute by querying the database. If there is, determining the preset wind speed range as the matching wind speed range; if not, extracting several production element features of the shaded-pole motor from the high-definition video data of the target area, predicting the production link of the shaded-pole motor based on each production element feature, querying the database based on this production link, obtaining the preset wind speed range corresponding to this production link, and determining it as the matching wind speed range.

8. An electronic device, characterized in that: The electronic device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor. When the computer program is executed by the processor, it implements the method according to any one of claims 1-5.

9. A computer storage medium, characterized in that: The computer storage medium stores a computer program that can be executed by a processor to implement the method according to any one of claims 1-5.

10. A computer program product, characterized in that: The computer program product includes a computer program that can be executed by a processor to implement the method according to any one of claims 1-5.

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