Dynamic adjustment method and system suitable for balanced air supply of high and large space air conditioning

Abstract

The application discloses a dynamic adjustment method and system suitable for balanced air supply of high and large space air conditioners, and the method comprises the following steps: obtaining an initial control strategy item from a seasonal control database based on current outdoor temperature and humidity data, current indoor temperature and humidity data and target control parameters, so as to perform automatic air supply control on the air conditioner; obtaining an adjusted control strategy item from the seasonal control database based on the outdoor temperature and humidity data, the indoor temperature and humidity data and the target control parameters after a preset time interval, so as to perform automatic air supply control on the air conditioner; obtaining an optimized control strategy item by analyzing and processing the indoor temperature and humidity data after air supply of the air conditioner, the target control parameters and all outdoor temperature and humidity data through a preset seasonal control model, performing automatic air supply control on the air conditioner by using the optimized control strategy item, and continuously optimizing the control parameters automatically by using a machine self-learning optimization control algorithm, so that the consistency of the high and large space air conditioner control is realized.

Description

Technical Field

[0001] This invention relates to the field of air conditioning air supply control technology, and more specifically, to a dynamic adjustment method and system suitable for equalizing air supply in large spaces. Background Technology

[0002] The cigarette factory's packaging workshop has a height of over 6 meters, with a single air conditioning duct having a delivery distance of 240 meters. Each duct has 24 swirling air outlets, and the entire packaging workshop is 420 meters long. It is equipped with six 120,000 cubic meter / hour central air conditioning units, providing the workshop with both cooling and heating sources, making it a typical high-ceilinged space. However, achieving balanced airflow in such high spaces has always been a major challenge for the air conditioning industry. Many professional organizations have conducted research on achieving balanced airflow in central air conditioning systems for high spaces, but currently, no control system has been designed that can automatically and dynamically adjust the airflow according to different seasons and varying external temperature and humidity conditions. Therefore, it is impossible to achieve balanced temperature and humidity in the workshop under different seasons and external temperature and humidity environments.

[0003] Therefore, there is an urgent need to develop a dynamic adjustment method, system, electronic device, and storage medium suitable for equalizing air supply in large spaces to solve the aforementioned problems. Summary of the Invention

[0004] One objective of this invention is to provide a new technical solution for a dynamic adjustment method and system suitable for equalizing air supply in air conditioning systems in large spaces.

[0005] According to a first aspect of the present invention, a dynamic adjustment method suitable for equalizing airflow in air conditioning systems in large spaces is provided, the method comprising:

[0006] Step S1: Determine the corresponding seasonal control database and preset seasonal control model based on the preset seasonal mode information of the air conditioner after startup;

[0007] Step S2: Based on the acquired current outdoor temperature and humidity data, current indoor temperature and humidity data, and the set target control parameters, an initial control strategy entry is obtained from the seasonal control database, so as to realize the automatic air supply control of the air conditioner by using the initial control strategy entry.

[0008] Step S3: Based on the outdoor temperature and humidity data, indoor temperature and humidity data obtained after a preset time interval, and the target control parameters, the adjustment control strategy entries are matched from the seasonal control database to achieve automatic air supply control of the air conditioner.

[0009] Step S4: Analyze and process the indoor temperature and humidity data collected after the air conditioner starts supplying air, the target control parameters, and all acquired outdoor temperature and humidity data through the preset seasonal control model to generate optimized control strategy entries, and save the optimized control strategy entries to the seasonal control database so as to execute automatic air supply control of the air conditioner using the optimized control strategy entries.

[0010] Optionally, in step S1, the preset seasonal control model is a winter control model, a summer control model, or a spring / autumn control model.

[0011] Optionally, in step S1, the step of establishing the preset seasonal control model specifically includes:

[0012] Step 01: Obtain air conditioning operation data, outdoor temperature and humidity data, and indoor temperature and humidity data at different coordinate points under the preset seasonal mode. The preset seasonal mode is winter heating mode, summer cooling mode, or spring and autumn mode.

[0013] Step 02: Pre-construct a temperature and humidity field model of the workshop using 3D modeling technology and CFD dynamic simulation technology;

[0014] Step 03: Use the air conditioning operation data, outdoor temperature and humidity data, and indoor temperature and humidity data at different coordinate points obtained under the preset seasonal mode to train the temperature and humidity field model to obtain the preset seasonal control model.

[0015] Optionally, in step 01, the air conditioning operation data includes: supply and return air temperature and humidity data, wind speed data, opening degree data, flow rate data, and flow rate data of each air outlet valve and water vapor valve;

[0016] When the preset seasonal mode is winter heating mode or summer cooling mode, the air conditioner operation data also includes air outlet wind speed data and temperature and humidity data when all air outlet valves are fully open, high wind speed and temperature and humidity data at a preset height above the ground, and air outlet wind speed data and temperature and humidity data when all air outlet valves are 50% open, as well as high wind speed and temperature and humidity data at a preset height above the ground.

[0017] Optionally, in step S1, the seasonal control database contains multiple control strategy entries, which are obtained by the preset seasonal control model through automatic optimization based on indoor temperature and humidity data collected after air conditioning is supplied under different outdoor environmental temperatures and humidity conditions.

[0018] According to a second aspect of the present invention, a dynamic adjustment system suitable for equalizing air supply in large spaces is provided, the system comprising a data storage server and an artificial intelligence analysis and processing server;

[0019] The data storage server is configured to store the preset seasonal mode information of the air conditioner, the set target control parameters, all outdoor temperature and humidity data, and all indoor temperature and humidity data.

[0020] The artificial intelligence analysis and processing server specifically includes:

[0021] The determination module is configured to determine the corresponding seasonal control database and preset seasonal control model based on the preset seasonal mode information of the air conditioner after it is turned on;

[0022] The strategy matching module is configured to match an initial control strategy entry from the seasonal control database based on the acquired current outdoor temperature and humidity data, current indoor temperature and humidity data, and set target control parameters, so as to implement automatic air supply control of the air conditioner using the initial control strategy entry; and to match an adjustment control strategy entry from the seasonal control database based on the outdoor temperature and humidity data, indoor temperature and humidity feedback data, and the target control parameters acquired after a preset time interval, so as to implement automatic air supply control of the air conditioner using the adjustment control strategy entry.

[0023] The optimization module is configured to analyze and process the indoor temperature and humidity data collected after the air conditioner supplies air, the target control parameters, and all acquired outdoor temperature and humidity data through the preset seasonal control model, so as to generate optimized control strategy entries and save the optimized control strategy entries to the seasonal control database, so as to execute automatic air supply control of the air conditioner using the optimized control strategy entries.

[0024] Optionally, the system further includes multiple temperature and humidity sensors connected to the data storage server, with the multiple temperature and humidity sensors respectively installed at different coordinate points outside the workshop, inside the workshop, and inside the air conditioning duct.

[0025] Optionally, the system further includes a computation execution server connected to the artificial intelligence analysis and processing server. The computation execution server processes the optimized control strategy items to obtain an execution instruction set and sends the execution instruction set to the feedback execution mechanism to realize the automatic air supply control of the air conditioner.

[0026] According to a third aspect of the present invention, an electronic device is provided, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the dynamic adjustment method for equalizing air supply in air conditioning in large spaces as described in the first aspect of the present invention.

[0027] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the dynamic adjustment method for equalizing air supply in air conditioning systems suitable for large spaces as described in the first aspect of the present invention.

[0028] According to an embodiment disclosed in this invention, the following beneficial effects are achieved:

[0029] The dynamic adjustment method of the present invention for equalizing air supply in air conditioning systems in large spaces uses a machine self-learning optimization control algorithm. It only needs to provide basic parameters once to continuously and automatically optimize the control parameters, so that the control effect is infinitely close to the target effect. At the same time, through intelligent control algorithm, it achieves the most energy-efficient operation while achieving the control effect. It can be applied to the balanced air supply regulation of all air conditioning systems in large spaces, and achieves the consistency of air conditioning control in large spaces.

[0030] Other features and advantages of the invention will become clear from the following detailed description of exemplary embodiments of the invention with reference to the accompanying drawings. Attached Figure Description

[0031] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the invention and, together with their description, serve to explain the principles of the invention.

[0032] Figure 1 This is a flowchart illustrating a dynamic adjustment method for equalizing air supply in air conditioning systems in large spaces, according to an embodiment.

[0033] Figure 2 This is a schematic diagram illustrating the construction process of a pre-set seasonal control model in a dynamic adjustment method for equalizing air supply in a high-ceilinged space, according to an embodiment.

[0034] Figure 3 This is a structural block diagram of a dynamic adjustment system suitable for equalizing air supply in tall spaces, provided according to an embodiment.

[0035] Figure 4 This is a structural block diagram of an electronic device according to an embodiment. Detailed Implementation

[0036] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention.

[0037] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0038] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0039] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0040] Example 1:

[0041] See Figure 1 As shown, this embodiment provides a dynamic adjustment method suitable for equalizing airflow in large spaces, the method comprising:

[0042] Step S1: Determine the corresponding seasonal control database and preset seasonal control model based on the preset seasonal mode information of the air conditioner after startup;

[0043] It should be noted that the preset seasonal mode information in this embodiment is winter heating mode, summer cooling mode, or spring and autumn mode. Of course, it may also include other air conditioning operating parameter information, such as: set target temperature, etc., which will not be listed here. In this embodiment, the seasonal control database is a winter control database, a summer control database, or a spring and autumn control database. Each seasonal control database includes multiple control strategy entries obtained through preset seasonal model analysis.

[0044] Step S2: Based on the acquired current outdoor temperature and humidity data, current indoor temperature and humidity data, and the set target control parameters, the initial control strategy entries are matched from the seasonal control database to achieve automatic air supply control of the air conditioner.

[0045] In this embodiment, after the air conditioner is turned on, an initial control strategy entry is first obtained from the corresponding seasonal control data based on the current indoor and outdoor temperature and humidity data and the set target control parameters. The air conditioner is then automatically controlled using this initial control strategy entry. In this embodiment, the target control parameters include the target indoor temperature and humidity that need to be achieved.

[0046] Step S3: Based on the outdoor temperature and humidity data, indoor temperature and humidity data, and target control parameters obtained after a preset time interval, the adjustment control strategy entries are matched from the seasonal control database to achieve automatic air supply control of the air conditioner.

[0047] In this embodiment, after the air conditioner has been running for a preset time, the outdoor temperature and humidity data at that time, as well as the indoor temperature and humidity data fed back after the air conditioner delivers air, are acquired. Combined with the target control parameters, an adjustment control strategy entry is then selected from the corresponding seasonal control data. This adjustment control strategy entry is used to automatically control the air conditioner. It should be noted that the preset time interval in this embodiment can be 1 hour, 2 hours, or 3 hours, etc., and of course, other time intervals can also be used, set according to actual needs. These will not be listed here. Furthermore, step S3 in this embodiment is a repetitive step; the control strategy entry is adjusted once every preset time interval.

[0048] Step S4: Analyze and process the indoor temperature and humidity data, target control parameters, and all acquired outdoor temperature and humidity data collected after the air conditioner starts supplying air using a preset seasonal control model to generate optimized control strategy entries. Save the optimized control strategy entries to the seasonal control database so that the automatic air supply control of the air conditioner can be executed using the optimized control strategy entries.

[0049] In this embodiment, a pre-set seasonal control model is used to intelligently analyze the indoor temperature and humidity data fed back after the air conditioner delivers air, combined with the target control parameters and all acquired outdoor temperature and humidity data. This optimizes the data to obtain a new control strategy entry, which is then saved to the corresponding seasonal control database. This continuously enriches the seasonal control database with data acquired through the automatic control process of the air conditioner.

[0050] Optionally, in step S1 of the dynamic adjustment method for equalizing air supply in tall spaces, the preset seasonal control model is a winter control model, a summer control model, or a spring / autumn control model.

[0051] Optionally, see Figure 2 As shown, in step S1 of the dynamic adjustment method for equalizing air supply in large spaces, the establishment of a preset seasonal control model specifically includes:

[0052] Step 01: Obtain the air conditioner operation data, outdoor temperature and humidity data, and indoor temperature and humidity data at different coordinate points under the preset seasonal mode. The preset seasonal mode is winter heating mode, summer cooling mode, or spring and autumn mode.

[0053] Step 02: Pre-construct a temperature and humidity field model of the workshop using 3D modeling technology and CFD dynamic simulation technology;

[0054] Step 03: Use the air conditioning operation data, outdoor temperature and humidity data, and indoor temperature and humidity data at different coordinate points obtained under the preset seasonal mode to train the temperature and humidity field model to obtain the preset seasonal control model.

[0055] Optionally, in step 01 of the dynamic adjustment method for equalizing air supply in air conditioning in large spaces in this embodiment, the air conditioning operation data includes: supply and return air temperature and humidity data, wind speed data, opening degree data, flow rate data, and flow rate data of each air outlet valve and water vapor valve.

[0056] When the preset seasonal mode is winter heating mode or summer cooling mode, the air conditioning operation data also includes air outlet wind speed data and temperature and humidity data when all air outlet valves are fully open, high wind speed and temperature and humidity data at the preset height above the ground, and air outlet wind speed data and temperature and humidity data when all air outlet valves are 50% open, as well as high wind speed and temperature and humidity data at the preset height above the ground.

[0057] Optionally, in step S1 of the dynamic adjustment method for equalizing air supply in tall spaces, the seasonal control database contains multiple control strategy entries. These control strategy entries are automatically optimized by a preset seasonal control model based on indoor temperature and humidity data collected after air supply in different outdoor environments.

[0058] The following is a detailed explanation using specific examples:

[0059] The process of establishing the winter control model is as follows:

[0060] 1. Manually / automatically collect air outlet wind speed data, temperature and humidity data, and high wind speed data and temperature and humidity data at 1.7 meters above the ground when the air valves of each air outlet of the air conditioning unit are fully open in winter heating mode, and automatically record them into the data storage server.

[0061] 2. Manually / automatically collect air outlet wind speed data, temperature and humidity data, and air speed data and temperature and humidity data at a height of 1.7 meters above the ground when the air valve of each air outlet is 50% open, and automatically record them to the storage server.

[0062] 3. Collect air conditioning unit operating data, including: supply and return air temperature and humidity data, wind speed data, opening data, flow rate data and flow rate data of each air outlet valve and water vapor valve, etc., and automatically store them to the data storage server.

[0063] 4. Collect outdoor ambient temperature and humidity data through outdoor ambient temperature and humidity sensors and transmit them to the data storage server;

[0064] 5. Store the indoor temperature and humidity data collected by temperature and humidity sensors at different coordinate points in the workshop to the data storage server;

[0065] 6. A temperature and humidity field model is provided for the workshop supply and return air control using 3D modeling and CFD dynamic simulation technology. A winter control model is designed based on data from different locations at the same time point.

[0066] 7. After the air conditioner automatically controls the air supply, the winter control model can automatically optimize the control parameters based on the temperature and humidity data fed back from different coordinate points in the room until the target temperature and humidity can be fully met. This set of control strategies is then stored in the winter control database.

[0067] 8. Automatically optimize and adjust multiple winter control strategy entries for different outdoor environmental temperatures and humidity, and store them in the winter control database.

[0068] The process of establishing the summer control model is as follows:

[0069] 1. Manually / automatically collect air outlet wind speed data, temperature and humidity data, and high wind speed data and temperature and humidity data at 1.7 meters above the ground when the air valves of each air outlet of the air conditioning unit are fully open in summer cooling mode, and automatically record them to the data storage server.

[0070] 2. Manually / automatically collect air outlet wind speed data, temperature and humidity data, and air speed data and temperature and humidity data at a height of 1.7 meters above the ground when the air valve of each air outlet is 50% open, and automatically record them to the storage server.

[0071] 3. Collect air conditioning unit operating data, including: supply and return air temperature and humidity data, wind speed data, opening data, flow rate data and flow rate data of each air outlet valve and water vapor valve, etc., and automatically store them to the data storage server.

[0072] 4. Collect outdoor ambient temperature and humidity data through outdoor ambient temperature and humidity sensors and transmit them to the data storage server;

[0073] 5. Store the indoor temperature and humidity data collected by temperature and humidity sensors at different coordinate points in the workshop to the data storage server;

[0074] 6. A temperature and humidity field model is provided for the workshop supply and return air control using 3D modeling and CFD dynamic simulation technology. A summer control model is designed based on data from different locations at the same time point.

[0075] 7. After the air conditioner automatically controls the air supply, the summer control model can automatically optimize the control parameters based on the temperature and humidity data fed back from different coordinate points in the room until the target temperature and humidity can be fully met. This set of control strategies is then stored in the summer control database.

[0076] 8. Automatically optimize and adjust multiple winter control strategy entries for different outdoor temperature and humidity conditions, and store them in the summer control database.

[0077] The process of establishing the control model for spring and autumn is as follows:

[0078] 1. Collect air conditioning unit operating data, including supply and return air temperature and humidity data, wind speed data, opening data, flow rate data, and flow rate data of each air outlet valve and water vapor valve, and automatically store them to the data storage server.

[0079] 2. Outdoor ambient temperature and humidity data are collected by an outdoor ambient temperature and humidity sensor and transmitted to a data storage server;

[0080] 3. Store the indoor temperature and humidity data collected by temperature and humidity sensors at different coordinate points in the workshop to the data storage server;

[0081] 4. A temperature and humidity field model is provided for the supply and return air control in the workshop using 3D modeling and CFD dynamic simulation technology. Based on data from different locations at the same time point, a control model for spring and autumn is designed.

[0082] 5. After the air conditioner automatically controls the air supply, the spring and autumn control model can automatically optimize the control parameters based on the temperature and humidity data fed back from different coordinate points in the room until the target temperature and humidity can be fully met. This set of control strategies is then stored in the spring and autumn control database.

[0083] 6. Automatically optimize and adjust multiple sets of spring and autumn control strategy entries for different outdoor environmental temperatures and humidity, and store them in the spring and autumn control database.

[0084] In this embodiment, the pre-set seasonal control model (winter control model, summer control model, and spring / autumn control model) employs a machine self-learning optimization control algorithm, which runs on an artificial intelligence computing server. Based on the pre-set control model, the artificial intelligence computing server reads data from the data server, compares the control target parameters and feedback data, as well as historical data, and issues execution instructions to the PLCs on-site by executing services. It continuously attempts to optimize the control parameters and analyzes and compares the feedback data after each optimization, automatically analyzing the gains and losses of the control parameters to provide data for the next optimization. Based on the delayed feedback characteristics of air conditioning control, the control mechanism action time is no more than 15 minutes. Through multiple human-like optimizations of machine control parameters, a set of control strategy bars is obtained. As the control strategy bars are continuously enriched, the intelligent control becomes more and more accurate, and the control feedback and control target become closer and closer until they are approximately consistent. The air conditioning automatic optimization and control strategy, through the collection of data from no less than three key seasons and the automatic control strategy optimization and storage, forms a complete intelligent high-ceiling space air conditioning equalization control system.

[0085] Dynamic adjustment process of air conditioning air supply control:

[0086] 1. When the air conditioner is turned on, it will automatically detect the seasonal status of the air conditioner operation in order to select the corresponding seasonal control database and preset seasonal control model;

[0087] 2. Based on outdoor ambient temperature and humidity data and the set target control parameters, automatically match and obtain control strategy entries, and execute automatic control;

[0088] 3. Based on changes in outdoor temperature and humidity, the control strategy entries are automatically adjusted every hour, and an automatic control adjustment is performed once.

[0089] 4. Based on the indoor temperature and humidity data and the set target temperature and humidity, automatically optimize and execute control strategy entries, and store them as new entries on the storage server;

[0090] 5. Under the condition that the target temperature and humidity are fully met, the control parameters are further automatically optimized to organically combine energy-saving operation and control target, so as to realize the energy-saving and intelligent operation of the air conditioning system.

[0091] In summary, the dynamic adjustment method for balanced air supply in air conditioning systems in large spaces according to the embodiments of the present invention uses a machine self-learning optimization control algorithm. It only needs to provide basic parameters once to continuously and automatically optimize the control parameters, so that the control effect is infinitely close to the target effect. At the same time, through intelligent control algorithm, it achieves the most energy-efficient operation while achieving the control effect. It can be applied to the balanced air supply regulation of all air conditioning systems in large spaces, and achieves the consistency of air conditioning control in large spaces.

[0092] Example 2:

[0093] See Figure 3 As shown, this embodiment provides a dynamic adjustment system 100 suitable for equalizing air supply in large spaces. The system includes a data storage server 1 and an artificial intelligence analysis and processing server 2.

[0094] Data storage server 1 is configured to store the preset seasonal mode information of the air conditioner, the set target control parameters, all outdoor temperature and humidity data, and all indoor temperature and humidity data.

[0095] The artificial intelligence analysis and processing server 2 specifically includes:

[0096] The determination module is configured to determine the corresponding seasonal control database and preset seasonal control model based on the preset seasonal mode information of the air conditioner after it is turned on;

[0097] The strategy matching module is configured to match an initial control strategy entry from the seasonal control database based on the acquired current outdoor temperature and humidity data, current indoor temperature and humidity data, and set target control parameters, so as to achieve automatic air supply control of the air conditioner using the initial control strategy entry; and to match an adjustment control strategy entry from the seasonal control database based on the outdoor temperature and humidity data, indoor temperature and humidity feedback data, and target control parameters acquired after a preset time interval, so as to achieve automatic air supply control of the air conditioner using the adjustment control strategy entry.

[0098] The optimization module is configured to analyze and process the indoor temperature and humidity data, target control parameters, and all acquired outdoor temperature and humidity data collected after the air conditioner supplies air through a preset seasonal control model, in order to generate optimized control strategy entries and save the optimized control strategy entries to the seasonal control database, so as to execute automatic air supply control of the air conditioner using the optimized control strategy entries.

[0099] Optionally, the dynamic adjustment system 100 suitable for equalizing air supply in large spaces in this embodiment also includes multiple temperature and humidity sensors 3 connected to the data storage server 1. The multiple temperature and humidity sensors 3 are respectively set at different coordinate points outside the workshop, inside the workshop, and inside the air conditioning duct.

[0100] Optionally, the dynamic adjustment system 100 suitable for equalizing air supply in large spaces in this embodiment further includes a computation execution server 4 connected to the artificial intelligence analysis and processing server 2. The computation execution server 4 processes the optimized control strategy items to obtain an execution instruction set and sends the execution instruction set to the feedback execution mechanism 5 to realize automatic air supply control of the air conditioner.

[0101] Optionally, the dynamic adjustment system 100 suitable for equalizing air supply in large spaces in this embodiment also includes a web publishing server 6 connected to the execution server 4. The web publishing server 6 displays stored data, analysis reports, execution status, feedback status, etc., through a web page. Control operators 7 in different departments can browse, view, and download data resources within their permissions via the network. The web publishing server is the interaction channel between the execution server, data storage server, artificial intelligence server, and remote operators. Data, calculation results, execution status, and feedback status from each server are executed and fed back to the remote operator workstation through the web publishing server. With operating permissions, operators can complete system detection and execution from a single workstation on the industrial intranet.

[0102] Specifically, the dynamic adjustment system for equalizing air supply in large spaces, as described in this embodiment, mainly consists of a data acquisition section, a feedback execution section, a database storage, analysis and processing section, and a manual duty section.

[0103] Data acquisition section: mainly consists of outdoor temperature and humidity sensors, temperature and humidity sensors distributed according to coordinate points in the workshop, temperature and humidity sensors in the air conditioning ducts, as well as air conditioner anemometers, chilled water / steam flow meters, fan frequency meters, speed meters, and data acquisition equipment in the control cabinet.

[0104] Feedback execution section: mainly consists of proportional-integral actuators distributed and installed on each air outlet, proportional-integral actuators installed on the main air duct, valve opening actuators for chilled water, steam, and humidification devices, frequency converters for fan motors, and PLC control units, etc.

[0105] Database storage, analysis, and processing section: mainly consists of data storage servers, artificial intelligence analysis and processing servers, computation execution servers, and web publishing servers;

[0106] Operator control section: mainly consists of the control operator workstation in the duty room and the remote monitoring operator workstation, etc.

[0107] In this system, sensor and instrument data from the data acquisition section are uniformly converted into TCP / IP protocol data via local data acquisition equipment and transmitted to the data storage server via a wired network. The execution server then sends execution instructions to the PLC controllers of each execution unit via the wired network. The PLCs convert these server instructions into machine instructions, controlling various execution components such as the proportional-integral valves of the ductwork, the chilled water / steam valves, and the fan operating frequency. An AI analysis and processing server performs intelligent self-learning analysis on the data storage server's data and sends the analysis results to the execution server. A web publishing server displays stored data, analysis reports, execution status, and feedback through a web page, allowing control operators in different departments to browse, view, and download data resources within their authorized access via the network. The functional sections are not completely physically separated; the four types of servers are categorized by function and are not necessarily separate, single physical servers. Depending on the project scope, each type of server can be one or more, or a single server can perform multiple functions. All system components are connected via control cables or the Industrial Internet, forming an organically unified and complete system.

[0108] In summary, the dynamic adjustment system for balanced air supply in large spaces, as described in this invention, mainly comprises multiple temperature and humidity sensors distributed at different coordinate points in the workshop, temperature and humidity sensors located outdoors, an electric proportional damper actuator installed on each air outlet damper, an actuator control system, a control system capable of dynamically adjusting the air supply temperature and humidity and air supply speed of the air conditioning unit, and a machine-learning intelligent dynamic control algorithm. This system collects air conditioning operation data, as well as different opening speeds, temperature, and humidity data from each air outlet. Through system modeling, control simulation, and automatic control simulation, it achieves intelligent balance control of all air conditioning and air outlet parameters, ultimately achieving balanced temperature and humidity across different air supply areas throughout the workshop.

[0109] Example 3:

[0110] This invention discloses an electronic device. The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the dynamic adjustment method for equalizing air supply in air conditioning in large spaces, as described in any of the embodiments of this invention.

[0111] Figure 4 This is a structural diagram of an electronic device according to an embodiment of the present invention, such as... Figure 4 As shown, the electronic device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, Near Field Communication (NFC), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0112] Those skilled in the art will understand that Figure 4 The structure shown is merely a structural diagram of the part related to the technical solution of this disclosure and does not constitute a limitation on the electronic device to which the solution of this application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0113] Example 4:

[0114] This invention discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the dynamic adjustment method for equalizing airflow in air conditioning systems suitable for large spaces, as described in any of Embodiment 1 of this invention.

[0115] Please note that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. The above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

[0116] The embodiments of the subject matter and functional operation described in this specification can be implemented in the following ways: digital electronic circuits, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or combinations thereof. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible, non-transitory program carrier for execution by a data processing apparatus or for controlling the operation of a data processing apparatus. Alternatively or additionally, the program instructions may be encoded on artificially generated propagation signals, such as machine-generated electrical, optical, or electromagnetic signals, which are generated to encode information and transmit it to a suitable receiving device for execution by the data processing apparatus. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or combinations thereof.

[0117] The processing and logic flow described in this specification can be executed by one or more programmable computers that execute one or more computer programs to perform corresponding functions by operating on input data and generating output. The processing and logic flow can also be executed by dedicated logic circuitry—such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application-Specific Integrated Circuits), and the device can also be implemented as dedicated logic circuitry.

[0118] Suitable computers for executing computer programs include, for example, general-purpose and / or special-purpose microprocessors, or any other type of central processing unit. Typically, the central processing unit receives instructions and data from read-only memory and / or random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as disks, magneto-optical disks, or optical disks, or the computer will be operatively coupled to such mass storage devices to receive data from or transfer data to them, or both. However, a computer is not required to have such devices. Furthermore, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0119] Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, such as semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. Processors and memory may be supplemented by or incorporated into dedicated logic circuitry.

[0120] While this specification contains numerous specific implementation details, these should not be construed as limiting the scope of any invention or the scope of the claims, but rather are primarily intended to describe features of specific embodiments of a particular invention. Certain features described in the various embodiments herein may also be implemented in combination in a single embodiment. Conversely, various features described in a single embodiment may also be implemented separately in various embodiments or in any suitable sub-combination. Furthermore, while features may function in certain combinations as described above and even initially claimed in this way, one or more features from a claimed combination may be removed from that combination in some cases, and a claimed combination may refer to a sub-combination or a variation thereof.

[0121] Similarly, although the operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring these operations to be performed in the specific order shown or sequentially, or requiring all illustrated operations to be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system modules and components in the above embodiments should not be construed as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0122] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings are not necessarily shown in a specific order or sequence to achieve the desired result. In some implementations, multitasking and parallel processing may be advantageous.

[0123] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0124] While specific embodiments of the invention have been described in detail by way of examples, those skilled in the art should understand that the examples are for illustrative purposes only and not intended to limit the scope of the invention. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of the invention. The scope of the invention is defined by the appended claims.

Claims

1. A dynamic adjustment method suitable for equalizing airflow in air conditioning systems in large spaces, characterized in that, The method includes: Step S1: Determine the corresponding seasonal control database and preset seasonal control model based on the preset seasonal mode information of the air conditioner after startup; Step S2: Based on the acquired current outdoor temperature and humidity data, current indoor temperature and humidity data, and the set target control parameters, an initial control strategy entry is obtained from the seasonal control database, so as to realize the automatic air supply control of the air conditioner by using the initial control strategy entry. Step S3: Based on the outdoor temperature and humidity data, indoor temperature and humidity data obtained after a preset time interval, and the target control parameters, the adjustment control strategy entries are matched from the seasonal control database to achieve automatic air supply control of the air conditioner. Step S4: Analyze and process the indoor temperature and humidity data collected after the air conditioner starts supplying air, the target control parameters, and all acquired outdoor temperature and humidity data through the preset seasonal control model to generate optimized control strategy entries, and save the optimized control strategy entries to the seasonal control database so as to execute automatic air supply control of the air conditioner using the optimized control strategy entries. In step S1, the establishment of the preset seasonal control model specifically includes: Step 01: Obtain air conditioning operation data, outdoor temperature and humidity data, and indoor temperature and humidity data at different coordinate points under the preset seasonal mode. The preset seasonal mode is winter heating mode, summer cooling mode, or spring and autumn mode. Step 02: Pre-construct a temperature and humidity field model of the workshop using 3D modeling technology and CFD dynamic simulation technology; Step 03: Use the air conditioning operation data, outdoor temperature and humidity data, and indoor temperature and humidity data at different coordinate points obtained under the preset seasonal mode to train the temperature and humidity field model to obtain the preset seasonal control model. In step 01, the air conditioning operation data includes: supply and return air temperature and humidity data, wind speed data, opening degree data, flow rate data, and flow rate data of each air outlet valve and water vapor valve; When the preset seasonal mode is winter heating mode or summer cooling mode, the air conditioner operation data also includes air outlet wind speed data and temperature and humidity data when all air outlet valves are fully open, high wind speed and temperature and humidity data at a preset height above the ground, and air outlet wind speed data and temperature and humidity data when all air outlet valves are 50% open, as well as high wind speed and temperature and humidity data at a preset height above the ground.

2. The dynamic adjustment method for equalizing airflow in air conditioning systems in large spaces according to claim 1, characterized in that, In step S1, the preset seasonal control model is a winter control model, a summer control model, or a spring / autumn control model.

3. The dynamic adjustment method for equalizing air supply in air conditioning systems in large spaces according to claim 1, characterized in that, In step S1, the seasonal control database contains multiple control strategy entries. These control strategy entries are automatically optimized by the preset seasonal control model based on indoor temperature and humidity data collected after the air conditioner supplies air under different outdoor environmental temperatures and humidity conditions.

4. A dynamic adjustment system suitable for equalizing airflow in large spaces, wherein the system employs the method described in any one of claims 1-3, characterized in that, The system includes a data storage server and an artificial intelligence analysis and processing server; The data storage server is configured to store the preset seasonal mode information of the air conditioner, the set target control parameters, all outdoor temperature and humidity data, and all indoor temperature and humidity data. The artificial intelligence analysis and processing server specifically includes: The determination module is configured to determine the corresponding seasonal control database and preset seasonal control model based on the preset seasonal mode information of the air conditioner after it is turned on; The strategy matching module is configured to match an initial control strategy entry from the seasonal control database based on the acquired current outdoor temperature and humidity data, current indoor temperature and humidity data, and set target control parameters, so as to implement automatic air supply control of the air conditioner using the initial control strategy entry; and to match an adjustment control strategy entry from the seasonal control database based on the outdoor temperature and humidity data, indoor temperature and humidity feedback data, and the target control parameters acquired after a preset time interval, so as to implement automatic air supply control of the air conditioner using the adjustment control strategy entry. The optimization module is configured to analyze and process the indoor temperature and humidity data collected after the air conditioner supplies air, the target control parameters, and all acquired outdoor temperature and humidity data through the preset seasonal control model, so as to generate optimized control strategy entries and save the optimized control strategy entries to the seasonal control database, so as to execute automatic air supply control of the air conditioner using the optimized control strategy entries.

5. The dynamic adjustment system for balanced air supply in large spaces according to claim 4, characterized in that, The system also includes multiple temperature and humidity sensors connected to the data storage server. These multiple temperature and humidity sensors are respectively installed at different coordinate points outside the workshop, inside the workshop, and inside the air conditioning duct.

6. The dynamic adjustment system for balanced air supply in large spaces according to claim 4, characterized in that, The system also includes a computation execution server connected to the artificial intelligence analysis and processing server. The computation execution server processes the optimized control strategy items to obtain an execution instruction set, and sends the execution instruction set to the feedback execution mechanism to realize the automatic air supply control of the air conditioner.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, it implements the steps in the dynamic adjustment method for equalizing air supply in air conditioning in tall spaces as described in any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the dynamic adjustment method for equalizing air supply in air conditioning systems suitable for tall spaces, as described in any one of claims 1 to 3.

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