Ventilation wall intelligent control method and system

Abstract

The invention belongs to the technical field of ventilation and air conditioning, and discloses an intelligent ventilation wall control method and system.The intelligent ventilation wall control method comprises the steps that real-time airflow parameters and temperature parameters of an indoor area are obtained; identifying a potential hot pressure difference disturbance area according to the airflow parameters; acquiring a disturbance response level of the potential hot pressure difference disturbance area at each moment according to the airflow direction change and the temperature gradient stability of the potential hot pressure difference disturbance area at adjacent moments in the analysis time period; screening a high-priority control region based on the disturbance response level; according to the disturbance response level of the high-priority control area at each moment and the temperature parameter of the high-priority control area at the same moment, obtaining an adjustment guidance index of the corresponding control area; the air supply amount and the air supply direction of the ventilation wall are dynamically adjusted based on the adjustment guidance index, so that transient hot pressure difference disturbance in the area is responded in real time; and the energy-saving effect of the ventilation wall system is greatly improved.

Description

Technical Field

[0001] This invention relates to the field of ventilation and air conditioning technology, and more specifically, to an intelligent control method and system for wind walls. Background Technology

[0002] With the ever-increasing demands for energy efficiency management and equipment operating environment in modern data centers, the air wall system, as a core facility for hot and cold air exchange and temperature regulation in data center IT rooms, directly affects the energy efficiency and equipment reliability of data center IT rooms.

[0003] Traditional airflow control systems mostly rely on segmented PID control based on empirical rules. They only respond to airflow changes by pre-setting fixed operating parameters (such as single control thresholds for low load and high load). This makes it difficult to capture transient heat load fluctuations in the IT equipment area, and even more difficult to achieve precise positioning and differentiated adjustment of the disturbance area. Ultimately, this results in control lag, serious waste of cooling capacity, and low temperature control accuracy.

[0004] In view of the above, this invention proposes an intelligent control method and system for wind walls to solve the aforementioned problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a wind wall intelligent control method, comprising: Step S1: Obtain real-time airflow and temperature parameters for the indoor area; Step S2: Identify potential thermal pressure difference disturbance regions based on the fluctuation amplitude of airflow parameters and the rate of change of temperature parameters; Step S3: Based on the changes in airflow direction and temperature gradient stability of the potential thermal pressure difference disturbance region at adjacent moments within the analysis period, obtain the disturbance response level of the potential thermal pressure difference disturbance region at each moment; and filter high-priority control regions based on the disturbance response level. Step S4: Based on the disturbance response level of the high-priority control area at each moment and its temperature parameter at the same moment, obtain the adjustment guidance index of the corresponding control area; dynamically adjust the air supply volume and air supply direction of the air wall based on the adjustment guidance index to respond to transient thermal pressure difference disturbances in the area in real time.

[0006] Furthermore, the method for identifying the potential thermal pressure difference disturbance region includes: The airflow parameters within the region are tracked point by point at all times to obtain the airflow velocity at each monitoring point within the region at each time. Based on the differences in direction, velocity, and temperature of the airflow vectors between any two monitoring points, the degree of difference in flow performance between the two monitoring points is obtained. The connected domain formed by the monitoring points corresponding to the flow performance differences within the region that are less than the preset difference threshold is denoted as the local airflow region; the local airflow region is expanded to obtain the potential thermal pressure difference disturbance region.

[0007] Furthermore, the high-priority control region is a potential thermal pressure difference disturbance region where the disturbance response level is higher than a preset response threshold.

[0008] Furthermore, the process of expanding the local airflow region to obtain a potential thermal pressure difference disturbance region includes: The ratio of the maximum to the minimum number of monitoring points in any two local airflow regions is recorded as the number ratio; preset expansion conditions are included, such as: the shortest path between the corresponding expansion point is less than a preset path threshold and the number ratio between the corresponding expansion point and the corresponding expansion point is greater than a preset number difference threshold. Choose any local airflow region as the starting region, use the starting region as the expansion point to expand the region, and use other local airflow regions other than the expansion point that meet the preset expansion conditions as new expansion points to expand the region, until all other local airflow regions except all the new expansion points no longer meet the expansion conditions, and stop the expansion, thus obtaining the corresponding potential thermal pressure difference disturbance region.

[0009] Furthermore, obtaining the disturbance response level of the potential thermal pressure difference disturbance region at each moment includes: The airflow parameters within the region are tracked point by point at all times to obtain the airflow vector of each monitoring point within the region at each time. The number of times the directional difference between the airflow vectors of the monitoring points in the same potential thermal pressure difference disturbance area in the region of adjacent time periods within each analysis time period is greater than a preset difference threshold is counted and recorded as the airflow instability value of each potential thermal pressure difference disturbance area in the region at each time period; The cumulative change of temperature parameters at monitoring points in the same potential thermal pressure difference disturbance area within the region at all times during the analysis period at each time moment is calculated as the temperature fluctuation value of each potential thermal pressure difference disturbance area within the region at each time moment. The distance between monitoring points in the same potential thermal pressure difference disturbance area within the region at two endpoints within the analysis period at each time moment is taken as the spatial displacement of each potential thermal pressure difference disturbance area within the region at each time moment. The ratio of the spatial displacement to the temperature fluctuation value is calculated, and the airflow instability value is mapped in a decreasing manner. The product of the mapping result and the ratio is standardized to obtain the disturbance response level of each potential thermal pressure difference disturbance region.

[0010] Furthermore, the method for obtaining the adjustment guidance indicators for the high-priority control region includes: Determine the associated regions of temperature parameters of each high-priority control region within each time zone at the same time, and extract flow features from the associated regions to obtain an airflow distribution matrix; obtain flow feature indices of the airflow distribution matrix, including airflow distribution uniformity, airflow direction consistency, airflow velocity gradient, and temperature gradient; Based on the disturbance response level and airflow distribution uniformity of each high-priority control area within the region, obtain the response characteristic value of the corresponding control area; The response characteristic value of each high-priority control area within the region, together with other flow characteristic indicators except for the uniformity, constitutes the adjustment guidance index for the corresponding control area.

[0011] Furthermore, determining the associated region of the temperature parameters of each high-priority control region within the region at each time moment includes: The temperature parameters of each high-priority control region are compiled into a temperature vector. The similarity between different temperature vectors is calculated. Temperature vectors with similarity greater than a preset similarity threshold are marked as associated temperatures. The high-priority control regions corresponding to the temperature vectors marked as associated temperatures are taken as associated regions.

[0012] Furthermore, the dynamic adjustment of the airflow volume and direction of the air wall based on the adjustment guidance index includes: Obtain reference guidance indicators for predefined wind wall adjustment strategies; The matching degree of the adjustment guidance indicators of each high priority control area with all reference guidance indicators is compared, and the adjustment strategy corresponding to the maximum matching degree is taken as the real-time adjustment scheme of the corresponding control area. The air volume and direction of the air wall are gradually adjusted according to the real-time adjustment scheme until the airflow parameters in the area reach a preset stable state.

[0013] Furthermore, the method for tracking airflow parameters within the region point by point at all times is a time-by-time tracking process based on sensor sequences, which achieves time-by-time updates through parameter correlation between continuous monitoring points.

[0014] A smart wind wall control system includes: Data acquisition module: Acquires real-time airflow and temperature parameters for the indoor area; Region identification module: Identifies potential thermal pressure difference disturbance regions based on the fluctuation amplitude of airflow parameters and the rate of change of temperature parameters; Region filtering module: Based on the changes in airflow direction and temperature gradient stability of potential thermal pressure difference disturbance regions at adjacent moments within the analysis period, obtain the disturbance response level of the potential thermal pressure difference disturbance region at each moment; and filter high-priority control regions based on the disturbance response level; Control and adjustment module: Based on the disturbance response level of the high-priority control area at each moment and its temperature parameter at the same moment, obtain the adjustment guidance index of the corresponding control area; dynamically adjust the air supply volume and air supply direction of the air wall based on the adjustment guidance index to respond to transient thermal pressure difference disturbances in the area in real time.

[0015] The technical effects and advantages of the intelligent wind wall control method and system of the present invention are as follows: By acquiring real-time airflow and temperature parameters within the indoor area, and identifying potential thermal pressure difference disturbance regions based on airflow fluctuation amplitude and temperature change rate, the disturbance response level is calculated, enabling timely detection and precise location of transient thermal pressure difference disturbances. Traditional methods, relying primarily on fixed monitoring points and preset thresholds, cannot capture the specific area where the disturbance occurs in real time, leading to control lag. By introducing a disturbance response level index for high-priority control region screening, the problem of traditional control systems being unable to determine control priorities when multiple areas experience simultaneous thermal pressure difference disturbances is solved. Compared to the existing approach of uniformly adjusting the entire area, this invention provides targeted adjustment for high-priority control regions, significantly improving control efficiency and reducing unnecessary energy consumption. The adjustment guidance index based on the disturbance response level and temperature parameters of high-priority control regions enables the wind wall system to implement differentiated control strategies according to the specific characteristics of the disturbance, avoiding the one-size-fits-all simple compensation control of traditional systems. By tracking airflow parameters point-by-point and analyzing flow performance differences, combined with the connectivity expansion of local airflow regions, accurate identification of thermal pressure difference disturbance regions is achieved. Based on the extraction of flow characteristics and analysis of airflow distribution matrices in associated regions, the system can adaptively select the most suitable adjustment strategy and dynamically adjust the airflow volume and direction of the air wall until the airflow parameters in the region reach a preset stable state. Compared with traditional piecewise PID control based on empirical rules, the intelligent control method proposed in this invention has a shorter response time and can implement precise intervention in the early stage of thermal pressure difference disturbance formation, significantly reducing the propagation range and duration of the disturbance. Through optimized region identification and response level calculation methods, this system can automatically adjust control parameters under different seasons and temperature differences, adapting to complex and changing actual operating conditions, and significantly improving the energy-saving effect and environmental control quality of the air wall system. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the intelligent wind wall control method of the present invention; Figure 2 This is a schematic diagram of the intelligent wind wall control system of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1 Please see Figure 1 As shown in this embodiment, a smart windbreak control method includes: Step S1: Obtain real-time airflow and temperature parameters for the indoor area.

[0019] In this embodiment, a distributed sensor network is used to collect real-time airflow and temperature parameters in the data center IT room. Airflow parameters include airflow velocity, airflow direction, and airflow humidity; temperature parameters include real-time temperature values, temperature change rates, and temperature gradients at each monitoring point. The sensor deployment density is determined based on the area and airflow complexity of the data center IT room, typically with one sensor node placed every 5 to 10 square meters to form a grid-like monitoring network. The data acquisition frequency is set to 5 times per second to ensure the capture of transient thermal pressure disturbances. The collected data is transmitted wirelessly to the central control system, which preprocesses the data, including outlier removal, smoothing, and data standardization, to obtain standardized airflow and temperature parameters for subsequent analysis.

[0020] Step S2: Identify potential thermal pressure difference disturbance regions based on the fluctuation amplitude of airflow parameters and the rate of change of temperature parameters.

[0021] Preferably, in some possible implementations of the embodiments of the present invention, the method for identifying potential thermal pressure difference disturbance regions includes: tracking the airflow parameters within the region point by point at all times to obtain the airflow velocity at each monitoring point within the region at each time; obtaining the flow performance difference degree between any two monitoring points based on the directional difference, velocity difference, and temperature difference of the airflow vectors between the two monitoring points; defining the connected domain formed by the monitoring points within the region whose flow performance difference degree is less than a preset difference threshold as a local airflow region; and expanding the local airflow region to obtain the potential thermal pressure difference disturbance region.

[0022] In specific implementation, for any two monitoring points i and Calculate the difference in their flow performance: ;in, Indicates the degree of difference in flow performance. and They represent monitoring points respectively. and The direction and angle of the airflow and They represent monitoring points respectively. and airflow speed, and They represent monitoring points respectively. and Temperature value; , and This is a weighting coefficient used to balance the contribution of different physical quantities to the degree of difference. In this embodiment, based on the analysis of a large amount of experimental data, it is set... It is 0.5. It is 0.3. The weighting coefficients are set to 0.2. These weighting coefficients are based on experimental observations that the change in airflow direction is generally more important than the change in velocity in thermal pressure disturbances, and the change in velocity is more important than the change in temperature.

[0023] The preset difference threshold is determined based on the airflow characteristics and thermal pressure difference intensity of the data center IT room. In this embodiment, the difference threshold is set to 3.5. This value is obtained by statistical analysis of the airflow parameters of the data center IT room under different seasons and different indoor and outdoor temperature differences, which can effectively distinguish between normal airflow fluctuations and disturbances caused by thermal pressure differences.

[0024] When the difference in flow behavior between two monitoring points is less than a preset difference threshold, the two monitoring points are considered to be in similar airflow states and belong to the same local airflow region. By performing connectivity analysis on all monitoring points, multiple local airflow regions can be obtained.

[0025] Next, the local airflow region needs to be expanded to obtain the potential thermal pressure difference disturbance region. The specific method for region expansion is as follows: the ratio of the maximum to the minimum number of monitoring points in any two local airflow regions is recorded as the number ratio; preset expansion conditions are set, including: the shortest path to the corresponding expansion point is less than a preset path threshold and the number ratio to the corresponding expansion point is greater than a preset number difference threshold; any local airflow region is randomly selected as the starting region, and the starting region is used as the expansion point for region expansion. Other local airflow regions that meet the preset expansion conditions, except for the expansion point, are used as new expansion points for region expansion, until all other local airflow regions except for all new expansion points no longer meet the expansion conditions, at which point the expansion stops, and the corresponding potential thermal pressure difference disturbance region is obtained.

[0026] The preset path threshold is set to 3 meters, meaning the spatial distance between two local airflow regions should not exceed 3 meters. This setting is based on the characteristic that thermal pressure difference disturbances are typically spatially continuous. The preset quantity difference threshold is set to 0.3, meaning the ratio of the number of monitoring points in two local airflow regions should not be less than 0.3, to avoid excessively small areas being incorrectly included in the disturbance area. These thresholds are set based on experimental research and professional experience regarding the thermal pressure difference disturbance characteristics of data center IT rooms.

[0027] Step S3: Based on the changes in airflow direction and temperature gradient stability of the potential thermal pressure difference disturbance area at adjacent moments within the analysis period, obtain the disturbance response level of the potential thermal pressure difference disturbance area at each moment; and filter high-priority control areas based on the disturbance response level.

[0028] Preferably, in this embodiment of the invention, the high-priority control area is a potential thermal differential pressure disturbance area in the data center IT room whose disturbance response level is higher than a preset response threshold. The preset response threshold is set to 0.65, which is determined by evaluating the thermal differential pressure disturbance control effect in the data center IT room, and can effectively distinguish between strong disturbance areas that require urgent handling and weak disturbance areas that can be handled later.

[0029] The method for obtaining the disturbance response level includes: tracking the airflow parameters in the region point by point at all times to obtain the airflow vector of each monitoring point in the region at each time; counting the number of times the directional difference between the airflow vectors of the monitoring points in the same potential thermal pressure difference disturbance region in the region at adjacent times within the analysis period of each time is greater than a preset difference threshold, and recording it as the airflow instability value of each potential thermal pressure difference disturbance region in the region at each time; calculating the cumulative change of the temperature parameters of the monitoring points in the same potential thermal pressure difference disturbance region in the region at all times within the analysis period of each time, and using it as the temperature fluctuation value of each potential thermal pressure difference disturbance region in the region at each time; taking the distance between the monitoring points in the same potential thermal pressure difference disturbance region in the region at two endpoint times within the analysis period of each time as the spatial displacement of each potential thermal pressure difference disturbance region in the region at each time; calculating the ratio of the spatial displacement to the temperature fluctuation value, performing a decreasing mapping on the airflow instability value, and standardizing the product of the mapping result and the ratio to obtain the disturbance response level of each potential thermal pressure difference disturbance region.

[0030] In this embodiment, the analysis period is set to a continuous 60 seconds. This setting is based on statistical analysis of the duration of thermal differential pressure disturbances in the IT room of the data center, which can cover the complete process of most thermal differential pressure disturbance events.

[0031] Specifically, for each moment Potential thermal pressure difference disturbance region The cumulative change in its temperature parameter is the sum of the temperature changes at each monitoring point during the analysis period. The method for mapping the airflow instability value using a non-linear decreasing mapping, specifically an exponential decay function in this embodiment, maps high instability values ​​to values ​​close to 1 and low instability values ​​to values ​​close to 0. The mapping result is a scalar value representing the contribution of instability to the disturbance response level. Its disturbance response level... The calculation is as follows: ;in, For the region At any moment Spatial displacement, For the region At any moment Temperature fluctuation value, For the region At any moment The airflow instability value, These are adjustment parameters used to control the degree to which airflow instability affects the disturbance response level. This is a standardization function used to standardize the disturbance response level to the [0,1] interval. In this embodiment, The value is 0.15, which was obtained by fitting a large amount of experimental data and can reasonably reflect the nonlinear relationship between airflow instability and disturbance response level.

[0032] Step S4: Based on the disturbance response level of the high-priority control area at each moment and its temperature parameters at the same moment, obtain the adjustment guidance index for the corresponding control area; dynamically adjust the air supply volume and air supply direction of the air wall based on the adjustment guidance index to respond to transient thermal pressure difference disturbances in the area in real time.

[0033] Preferably, in this embodiment of the invention, the method for obtaining the adjustment guidance index of a high-priority control area includes: determining the associated region of temperature parameters of each high-priority control area within the region at each time moment; extracting flow features from the associated region to obtain an airflow distribution matrix; obtaining flow feature indices of the airflow distribution matrix, wherein the flow feature indices include airflow distribution uniformity, airflow direction consistency, airflow velocity gradient, and temperature gradient; obtaining the response feature value of the corresponding control area based on the disturbance response level and the airflow distribution uniformity of each high-priority control area within the region; and constructing the adjustment guidance index of the corresponding control area by combining the response feature value of each high-priority control area within the region with the remaining flow feature indices excluding the uniformity.

[0034] The method for determining the associated regions is as follows: Temperature parameters of each high-priority control region are compiled into temperature vectors. The similarity between different temperature vectors is calculated. Temperature vectors with similarity greater than a preset similarity threshold are marked as associated temperatures. The high-priority control regions corresponding to these temperature vectors are then designated as associated regions. The preset similarity threshold is set to 0.85. This value is determined based on statistical analysis of the similarity of temperature distribution in thermal pressure difference disturbance regions, effectively identifying regions with similar temperature characteristics.

[0035] The airflow distribution matrix is ​​obtained by interpolating and gridding the airflow data of monitoring points in the associated area. The airflow distribution uniformity is obtained by calculating the ratio of the standard deviation to the mean of the airflow distribution matrix. The response characteristic value is obtained by weighted combination of the disturbance response level and the airflow distribution uniformity.

[0036] The method for dynamically adjusting the air volume and direction of the air wall based on adjustment guidance indicators includes: obtaining reference guidance indicators for predefined air wall adjustment strategies; comparing the matching degree of the adjustment guidance indicators of each high-priority control area with all reference guidance indicators, and taking the adjustment strategy corresponding to the maximum matching degree as the real-time adjustment scheme for the corresponding control area; and gradually adjusting the air volume and direction of the air wall according to the real-time adjustment scheme until the airflow parameters in the area reach a preset stable state.

[0037] The predefined airflow control strategy includes various combinations of air volume and direction, each corresponding to a set of reference guidelines. The degree of matching is determined by calculating the Euclidean distance between the adjustment guidelines and the reference guidelines; the smaller the distance, the higher the degree of matching. For example, the airflow control strategy numbered S01 is described as increasing the air volume by 25% and adjusting the airflow angle downward by 10 degrees; the reference guidelines are {response characteristic value: 0.75-0.85, airflow distribution uniformity: less than 0.3, airflow direction consistency: greater than 0.7, airflow velocity gradient: greater than 1.5m / s / m, temperature gradient: greater than 1℃ / m}. The preset steady state is defined as follows: the average airflow velocity fluctuation in the area does not exceed 0.2 m / s, the average temperature fluctuation does not exceed 0.5℃, and the duration is not less than 30 seconds. This definition is determined based on the energy consumption optimization objectives of the data center IT room.

[0038] It should be noted that the method for tracking airflow parameters within the region at all times in the steps is a time-by-time tracking process based on sensor sequences. This process achieves time-by-time updates through parameter correlation between continuous monitoring points. Specifically, the system records the parameter changes of each monitoring point at continuous time points, and establishes a correlation mapping between monitoring points through parameter change trends and spatial location relationships, thereby achieving accurate tracking of airflow parameters.

[0039] Analysis of the two high-priority control zones yielded their adjustment guidelines. The adjustment guidelines for the first zone showed the highest match with the predefined adjustment strategy of "increasing the airflow volume by 25% and adjusting the airflow angle downwards by 10 degrees," while the adjustment guidelines for the second zone showed the highest match with the predefined adjustment strategy of "maintaining the airflow volume unchanged and adjusting the airflow direction outwards by 15 degrees." The control system progressively adjusted the airwall parameters based on these two immediate adjustment schemes, first adjusting the first zone (with a higher disturbance response level), and then adjusting the second zone. During the adjustment process, the system continuously monitored the airflow and temperature parameters within each zone until a preset stable state was reached. Ultimately, the average airflow velocity fluctuation in each zone decreased to 0.15 m / s, and the average temperature fluctuation decreased to 0.3℃, remaining stable for over 45 seconds, completing the intelligent control process for this thermal pressure difference disturbance.

[0040] This embodiment acquires real-time airflow and temperature parameters of the indoor area, identifies potential thermobaric disturbance areas based on airflow fluctuation amplitude and temperature change rate, and calculates the disturbance response level, achieving timely detection and accurate location of transient thermobaric disturbances. Traditional methods, relying mainly on fixed monitoring points and preset thresholds, cannot capture the specific area where the disturbance occurs in real time, leading to control lag. By introducing a disturbance response level index to screen high-priority control areas, this solves the problem of traditional control systems being unable to determine control priorities when multiple areas experience simultaneous thermobaric disturbances. Compared to the existing approach of uniformly adjusting the entire area, this invention performs targeted adjustment of high-priority control areas, significantly improving control efficiency and reducing unnecessary energy consumption. The adjustment guidance index based on the disturbance response level and temperature parameters of high-priority control areas enables the wind wall system to implement differentiated control strategies according to the specific characteristics of the disturbance, avoiding the one-size-fits-all simple compensation control of traditional systems. By tracking airflow parameters point-by-point and analyzing flow performance differences, combined with the connectivity expansion of local airflow regions, accurate identification of thermal pressure difference disturbance regions is achieved. Based on the extraction of flow characteristics and analysis of airflow distribution matrices in associated regions, the system can adaptively select the most suitable adjustment strategy and dynamically adjust the airflow volume and direction of the air wall until the airflow parameters in the region reach a preset stable state. Compared with traditional piecewise PID control based on empirical rules, the intelligent control method proposed in this invention has a shorter response time and can implement precise intervention in the early stage of thermal pressure difference disturbance formation, significantly reducing the propagation range and duration of the disturbance. Through optimized region identification and response level calculation methods, this system can automatically adjust control parameters under different seasons and temperature differences, adapting to complex and changing actual operating conditions, and significantly improving the energy-saving effect and environmental control quality of the air wall system.

[0041] Example 2 Please see Figure 2As shown, parts not described in detail in this embodiment are described in Embodiment 1. A smart wind wall control system is provided, including: Data acquisition module: Acquires real-time airflow and temperature parameters for the indoor area; Region identification module: Identifies potential thermal pressure difference disturbance regions based on the fluctuation amplitude of airflow parameters and the rate of change of temperature parameters; Region filtering module: Based on the changes in airflow direction and temperature gradient stability of potential thermal pressure difference disturbance regions at adjacent moments within the analysis period, obtain the disturbance response level of the potential thermal pressure difference disturbance region at each moment; and filter high-priority control regions based on the disturbance response level; Control and adjustment module: Based on the disturbance response level of the high-priority control area at each moment and its temperature parameter at the same moment, obtain the adjustment guidance index of the corresponding control area; dynamically adjust the air supply volume and air supply direction of the air wall based on the adjustment guidance index to respond to transient thermal pressure difference disturbances in the area in real time.

[0042] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0043] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0044] In the description of this invention, it should be understood that the terms "first," "second," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0045] In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0046] In the description of this invention, "several" means one or more, and "a large number" means two or more.

[0047] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0048] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0049] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for intelligent control of a windbreak wall, characterized in that, include: Step S1: Obtain real-time airflow and temperature parameters for the indoor area; Step S2: Identify potential thermal pressure difference disturbance regions based on the fluctuation amplitude of airflow parameters and the rate of change of temperature parameters; Step S3: Based on the changes in airflow direction and temperature gradient stability of the potential thermal pressure difference disturbance region at adjacent moments within the analysis period, obtain the disturbance response level of the potential thermal pressure difference disturbance region at each moment; and filter high-priority control regions based on the disturbance response level. Step S4: Based on the disturbance response level of the high-priority control area at each moment and its temperature parameter at the same moment, obtain the adjustment guidance index of the corresponding control area; dynamically adjust the air supply volume and air supply direction of the air wall based on the adjustment guidance index to respond to transient thermal pressure difference disturbances in the area in real time.

2. The intelligent control method for windbreak walls according to claim 1, characterized in that, The method for identifying the potential thermal pressure differential disturbance region includes: The airflow parameters within the region are tracked point by point at all times to obtain the airflow vector of each monitoring point within the region at each time. Based on the differences in direction, velocity, and temperature of the airflow vectors between any two monitoring points, the degree of difference in flow performance between the two monitoring points is obtained. The connected domain formed by the monitoring points corresponding to the flow performance differences within the region that are less than the preset difference threshold is denoted as the local airflow region; the local airflow region is expanded to obtain the potential thermal pressure difference disturbance region.

3. The intelligent control method for windbreak walls according to claim 2, characterized in that, The high-priority control region is the potential thermal pressure difference disturbance region where the disturbance response level is higher than the preset response threshold.

4. The intelligent control method for windbreak walls according to claim 3, characterized in that, The process of expanding the local airflow region to obtain a potential thermal pressure difference disturbance region includes: The ratio of the maximum to the minimum number of monitoring points in any two local airflow regions is recorded as the number ratio; preset expansion conditions are included, such as: the shortest path between the corresponding expansion point is less than a preset path threshold and the number ratio between the corresponding expansion point and the corresponding expansion point is greater than a preset number difference threshold. Choose any local airflow region as the starting region, use the starting region as the expansion point to expand the region, and use other local airflow regions other than the expansion point that meet the preset expansion conditions as new expansion points to expand the region, until all other local airflow regions except all the new expansion points no longer meet the expansion conditions, and stop the expansion, thus obtaining the corresponding potential thermal pressure difference disturbance region.

5. The intelligent control method for a windbreak wall according to claim 4, characterized in that, The process of obtaining the disturbance response level of the potential thermal pressure difference disturbance region at each moment includes: The airflow parameters within the region are tracked point by point at all times to obtain the airflow vector of each monitoring point within the region at each time. The number of times the directional difference between the airflow vectors of the monitoring points in the same potential thermal pressure difference disturbance area in the region of adjacent time periods within each analysis time period is greater than a preset difference threshold is counted and recorded as the airflow instability value of each potential thermal pressure difference disturbance area in the region at each time period; The cumulative change of temperature parameters at monitoring points in the same potential thermal pressure difference disturbance area within the region at all times during the analysis period at each time moment is calculated as the temperature fluctuation value of each potential thermal pressure difference disturbance area within the region at each time moment. The distance between monitoring points in the same potential thermal pressure difference disturbance area within the region at two endpoints within the analysis period at each time moment is taken as the spatial displacement of each potential thermal pressure difference disturbance area within the region at each time moment. The ratio of the spatial displacement to the temperature fluctuation value is calculated, and the airflow instability value is mapped in a decreasing manner. The product of the mapping result and the ratio is standardized to obtain the disturbance response level of each potential thermal pressure difference disturbance region.

6. The intelligent control method for windbreak walls according to claim 5, characterized in that, The method for obtaining the adjustment guidance indicators for the high-priority control area includes: Determine the associated regions of temperature parameters of each high-priority control region within each time zone at the same time, and extract flow features from the associated regions to obtain an airflow distribution matrix; obtain flow feature indices of the airflow distribution matrix, including airflow distribution uniformity, airflow direction consistency, airflow velocity gradient, and temperature gradient; Based on the disturbance response level and airflow distribution uniformity of each high-priority control area within the region, obtain the response characteristic value of the corresponding control area; The response characteristic value of each high-priority control area within the region, together with other flow characteristic indicators except for the uniformity, constitutes the adjustment guidance index for the corresponding control area.

7. The intelligent control method for windbreak walls according to claim 6, characterized in that, The determination of the associated region of temperature parameters of each high-priority control region within the region at each time moment includes: The temperature parameters of each high-priority control region are compiled into a temperature vector. The similarity between different temperature vectors is calculated. Temperature vectors with similarity greater than a preset similarity threshold are marked as associated temperatures. The high-priority control regions corresponding to the temperature vectors marked as associated temperatures are taken as associated regions.

8. The intelligent control method for windbreak walls according to claim 7, characterized in that, The dynamic adjustment of the air supply volume and direction of the air wall based on the adjustment guidance indicators includes: Obtain reference guidance indicators for predefined wind wall adjustment strategies; The matching degree of the adjustment guidance indicators of each high priority control area with all reference guidance indicators is compared, and the adjustment strategy corresponding to the maximum matching degree is taken as the real-time adjustment scheme of the corresponding control area. The air volume and direction of the air wall are gradually adjusted according to the real-time adjustment scheme until the airflow parameters in the area reach a preset stable state.

9. The intelligent control method for windbreak walls according to claim 8, characterized in that, The method for tracking airflow parameters within the region point by point at all times is a time-by-time tracking process based on sensor sequences. This process achieves time-by-time updates through parameter correlation between continuous monitoring points.

10. A wind wall intelligent control system, used to implement the wind wall intelligent control method according to any one of claims 1 to 9, characterized in that, include: Data acquisition module: Acquires real-time airflow and temperature parameters for the indoor area; Region identification module: Identifies potential thermal pressure difference disturbance regions based on the fluctuation amplitude of airflow parameters and the rate of change of temperature parameters; Region filtering module: Based on the changes in airflow direction and temperature gradient stability of potential thermal pressure difference disturbance regions at adjacent moments within the analysis period, obtain the disturbance response level of the potential thermal pressure difference disturbance region at each moment; and filter high-priority control regions based on the disturbance response level; Control and adjustment module: Based on the disturbance response level of the high-priority control area at each moment and its temperature parameter at the same moment, obtain the adjustment guidance index of the corresponding control area; dynamically adjust the air supply volume and air supply direction of the air wall based on the adjustment guidance index to respond to transient thermal pressure difference disturbances in the area in real time.

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