Clean space environment intelligent regulation and control method and system based on multi-level cooperative control

Abstract

The invention provides a clean space environment intelligent regulation and control method and system based on multi-level cooperative control. The method comprises the steps of obtaining real-time temperature and humidity monitoring data in a clean space; based on a comparison result of the real-time temperature and humidity monitoring data and a preset target range, a cooperative control instruction used for linkage control over the air conditioning unit, the humidification system and the axial flow fan is generated; wherein the cooperative control instruction dynamically determines start-stop combination and operation parameters of the air conditioning unit, the humidification system and the axial flow fan according to the type and degree of the environment parameters deviating from the preset target range; according to the cooperative control instruction, an air conditioning unit, a humidifying system and an axial flow fan are synchronously driven to be started and run according to the determined combination and parameters, so that the temperature and humidity of the clean space are subjected to integrated linkage adjustment; and when it is monitored that the real-time temperature and humidity data reach the preset target range, the air conditioning unit, the humidification system and the axial flow fan are controlled to stop running, and the regulation and control efficiency and the control precision are effectively improved through a cooperative control mode.

Description

Technical Field

[0001] This invention relates to the field of collaborative control technology, and in particular to an intelligent control method and system for clean space environment based on multi-level collaborative control. Background Technology

[0002] In the control of constant temperature and humidity environments in clean spaces, traditional control methods typically involve independently setting and controlling the start and stop of air conditioning units, humidification systems, and ventilation equipment. These devices operate independently based on single or local sensor signals, lacking a core control logic that performs unified analysis based on the overall environmental conditions and dynamically coordinates the collaborative operation of multiple devices.

[0003] This discrete control method makes it difficult for the system to respond accurately and in a coordinated manner to coupled changes in environmental parameters, and it is impossible to achieve high-efficiency and high-stability integrated regulation. Problems such as regulation lag, over-adjustment, or insufficient temperature and humidity control accuracy often occur. Summary of the Invention

[0004] This invention provides a method and system for intelligent regulation of clean space environment based on multi-level collaborative control, which solves the defects of poor regulation efficiency and control accuracy caused by discrete control methods in the prior art.

[0005] In a first aspect, the present invention provides a method for intelligent regulation and control of a clean space environment based on multi-level collaborative control, comprising: Acquire real-time temperature and humidity monitoring data within the clean space; Based on the comparison results between the real-time temperature and humidity monitoring data and the preset target range, a coordinated control command is generated for the linkage control of the air conditioning unit, the humidification system and the axial flow fan; wherein, the coordinated control command dynamically determines the start-stop combination and operating parameters of the air conditioning unit, the humidification system and the axial flow fan according to the type and degree of deviation of the environmental parameters from the preset target range; According to the coordinated control command, the air conditioning unit, the humidification system and the axial flow fan are synchronously driven to start and operate according to the determined combination and parameters, so as to perform integrated linkage regulation of the temperature and humidity of the clean space; When the real-time temperature and humidity data are detected to reach the preset target range, the air conditioning unit, the humidification system, and the axial flow fan are controlled to stop operating.

[0006] According to the present invention, a method for intelligent control of a clean space environment based on multi-level collaborative control is provided, wherein the step of synchronously driving the air conditioning unit, the humidification system, and the axial flow fan to start and operate according to a determined combination and parameters according to the collaborative control command includes: The coordinated control command is parsed to obtain the operating parameters specified for the air conditioning unit, the humidification system, and the axial flow fan, respectively. According to the device start / stop combination in the collaborative control instruction, a start command is sent to the corresponding device according to the preset start logic; The air conditioning unit, the humidification system, and the axial flow fan that have been started are controlled to operate according to the specified operating parameters.

[0007] According to the present invention, a method for intelligent control of a clean space environment based on multi-level collaborative control is provided, wherein sending a start command to the corresponding device according to a preset start logic includes: Generate and send a start command to the axial flow fan; Upon receiving feedback that the axial fan has started, a synchronous start command is generated and sent to the air conditioning unit and the humidification system.

[0008] According to the present invention, a method for intelligent control of a clean space environment based on multi-level collaborative control is provided, wherein the air conditioning unit, the humidification system, and the axial flow fan, which have been activated, operate according to specified operating parameters, including: The operating parameters are converted into control signals that can be recognized by the corresponding device; The control signals are sent to the controllers of the air conditioning unit, the humidification system, and the axial flow fan, respectively. Monitor the actual operating parameters of each device and compare them with the specified operating parameters. Adjust the control signal through closed-loop feedback to make the actual operating parameters approach the specified operating parameters.

[0009] The intelligent control method for clean space environment based on multi-level collaborative control provided by the present invention further includes: Real-time monitoring of the operating status of the air conditioning unit, the humidification system, and the axial flow fan, as well as the real-time temperature and humidity data of the clean space; Based on the operating status and real-time temperature and humidity data, the overall effectiveness of the current coordinated adjustment is determined. If the overall performance does not reach the preset threshold, the operating parameters in the collaborative control command are dynamically adjusted, and the control signals sent to each device are updated according to the adjusted command.

[0010] According to the present invention, a method for intelligent control of clean space environment based on multi-level collaborative control is provided. The method generates collaborative control commands for the coordinated control of air conditioning units, humidification systems, and axial flow fans based on the comparison results of real-time temperature and humidity monitoring data with preset target ranges. The commands include: The real-time temperature and humidity monitoring data are compared with the preset temperature target range and humidity target range respectively to determine whether the current temperature is too high, the temperature is too low, the humidity is too high, or the humidity is too low. Based on the determined state combination, the preset policy mapping table is queried to determine the corresponding device start / stop combination suggestion; Based on the degree to which the real-time temperature and humidity monitoring data deviates from the target range, the specific values ​​of the operating parameters are calculated and allocated.

[0011] According to the present invention, a method for intelligent control of a clean space environment based on multi-level collaborative control is provided, wherein when the real-time temperature and humidity data are detected to reach the preset target range, the method controls the air conditioning unit, the humidification system, and the axial flow fan to stop operating, comprising: When the real-time temperature and humidity data are monitored to remain stable within the preset target range for a first preset duration, a first stop command is generated to control the air conditioning unit and the humidification system to stop working. After the air conditioning unit and the humidification system stop working, the axial flow fan continues to run for the second preset time. After the second preset time period is reached, a second stop command is generated to control the axial flow fan to stop working.

[0012] According to the present invention, a method for intelligent control of cleanroom environment based on multi-level collaborative control is provided, wherein acquiring real-time temperature and humidity monitoring data within the cleanroom includes: Based on the layout of the process areas within the clean space, several key monitoring points were identified; Temperature and humidity sensors were deployed at the key monitoring points to collect temperature and humidity data. Data from multiple temperature and humidity sensors are fused to generate real-time temperature and humidity monitoring data that characterizes the overall environmental state of the clean space.

[0013] According to the present invention, a method for intelligent control of clean space environment based on multi-level collaborative control is provided, wherein dynamically determining the start-stop combination and operating parameters of the air conditioning unit, the humidification system and the axial flow fan includes: Record the start-stop combinations and operating parameters used under different environmental deviations during historical control processes, as well as the corresponding actual control effects; Based on historical records, a mapping relationship between environmental deviations and optimal control strategies is established using machine learning models. When generating the collaborative control instructions, the optimal control strategy recommended by the machine learning model is invoked first.

[0014] Secondly, the present invention provides a clean space environment intelligent control system based on multi-level collaborative control, comprising: The acquisition module is used to acquire real-time temperature and humidity monitoring data within the clean space; The generation module is used to generate coordinated control instructions for the air conditioning unit, humidification system and axial flow fan based on the comparison results between the real-time temperature and humidity monitoring data and the preset target range; wherein, the coordinated control instructions dynamically determine the start-stop combination and operating parameters of the air conditioning unit, the humidification system and the axial flow fan according to the type and degree of deviation of the environmental parameters from the preset target range; The coordination module is used to synchronously drive the air conditioning unit, the humidification system and the axial flow fan to start and operate according to a determined combination and parameters according to the coordination control command, so as to perform integrated linkage adjustment of the temperature and humidity of the clean space; The control module is used to control the air conditioning unit, the humidification system and the axial flow fan to stop operating when the real-time temperature and humidity data are detected to reach the preset target range.

[0015] Thirdly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the intelligent control method for clean space environment based on multi-level collaborative control as described above.

[0016] Fourthly, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the intelligent control method for clean space environment based on multi-level collaborative control as described above.

[0017] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the intelligent control method for clean space environment based on multi-level collaborative control as described above.

[0018] The present invention provides a method and system for intelligent control of clean space environment based on multi-level collaborative control. By dynamically generating collaborative instructions based on deviations in environmental parameters, it coordinates the operation of air conditioning units, humidification systems and axial flow fans, dynamically matches the optimal equipment combination and operating parameters, making the adjustment actions more targeted. This solves the problem of poor control efficiency and accuracy caused by independent operation of multiple devices in discrete control. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the intelligent control method for clean space environment based on multi-level collaborative control provided in this embodiment. Figure 2 This is a schematic diagram of the structure of the intelligent control system for clean space environment based on multi-level collaborative control provided in this embodiment; Figure 3 This is a schematic diagram of the structure of the electronic device provided in this embodiment. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0022] Figure 1 This is a flowchart illustrating the intelligent control method for clean space environment based on multi-level collaborative control provided in this embodiment.

[0023] like Figure 1 As shown in the embodiment of the present invention, the intelligent control method for clean space environment based on multi-level collaborative control is executed by a central control unit, and the method includes the following steps: 101. Obtain real-time temperature and humidity monitoring data within the clean space.

[0024] Specifically, the first step is to identify key monitoring points. Based on the layout characteristics of the cleanroom's process areas, core and peripheral zones are delineated. The core zone includes areas with extremely high requirements for temperature and humidity accuracy, such as core electronic workstations, aseptic pharmaceutical areas, and laboratory workbenches. The peripheral zone includes areas where environmental parameters are prone to fluctuation, such as near doors and windows and fresh air inlets. Monitoring points are densely distributed in the core zone to ensure accurate capture of temperature and humidity changes. In the peripheral zone, monitoring points are strategically placed according to the space size and airflow direction to avoid blind spots, ultimately forming a monitoring network covering the entire cleanroom.

[0025] Secondly, deploy temperature and humidity sensors. Fix the sensors at the preset monitoring points. The installation height of the sensors needs to be combined with the airflow distribution pattern of the clean space, such as avoiding areas where the ground is prone to moisture accumulation or where the airflow at the top is too fast, to ensure that the sensors can collect representative temperature and humidity data.

[0026] Next, temperature and humidity data are collected and fused. All temperature and humidity sensors are activated to collect raw temperature and humidity data from their respective monitoring points in real time. This data is then transmitted to the central control unit of the control layer via industrial Ethernet, with a transmission delay of ≤50ms to ensure real-time data transmission. After receiving raw data from multiple sensors, data preprocessing is performed to remove abnormal data caused by temporary sensor malfunctions or external interference. The remaining valid data is then fused, and different weights are assigned to each monitoring point based on its importance. Through weighted averaging or data fitting, real-time temperature and humidity monitoring data that comprehensively characterizes the overall environmental state of the clean space is generated, avoiding errors in subsequent control decisions due to incomplete data from a single monitoring point.

[0027] By scientifically deploying monitoring points, selecting suitable sensors, and performing data fusion processing, comprehensive, accurate, and real-time collection of temperature and humidity data in clean spaces has been achieved. This provides a reliable basis for generating subsequent collaborative control commands and solves the problems of incomplete and inaccurate data caused by unreasonable monitoring point deployment and poor sensor compatibility in traditional monitoring.

[0028] 102. Based on the comparison results between real-time temperature and humidity monitoring data and preset target range, generate coordinated control commands for the linkage control of air conditioning units, humidification systems and axial flow fans; wherein, the coordinated control commands dynamically determine the start-stop combination and operating parameters of air conditioning units, humidification systems and axial flow fans according to the type and degree of deviation of environmental parameters from the preset target range.

[0029] Specifically, first, the environmental state combination is determined. Real-time temperature and humidity monitoring data are compared one by one with the preset temperature target range and humidity target range. First, it is determined whether the temperature deviates from the target range, and then it is determined whether the humidity deviates from the target range. Finally, the current state combination of the clean space is determined. Possible state combinations include, but are not limited to: only high temperature, only low temperature, only high humidity, only low humidity, high temperature and high humidity, high temperature and low humidity, low temperature and high humidity, and low temperature and low humidity.

[0030] Secondly, determine the recommended equipment start-up and shutdown combinations. The central control unit has a pre-stored strategy mapping table. This table is pre-defined based on the cleanroom usage scenarios and equipment operating characteristics, clearly specifying the equipment start-up and shutdown combinations for each environmental state combination. For example, when the state combination is "high temperature and normal humidity," the corresponding start-up and shutdown combination is "start the air conditioning unit and axial fan, and shut down the humidification system." When the state combination is "low humidity and normal temperature," the corresponding start-up and shutdown combination is "start the humidification system and axial fan, and shut down the air conditioning unit." When the state combination is "high temperature and low humidity," the corresponding start-up and shutdown combination is "start the air conditioning unit, humidification system, and axial fan." Based on the determined state combinations, querying this strategy mapping table will yield the corresponding recommended equipment start-up and shutdown combinations.

[0031] Then, the specific values ​​of the operating parameters are calculated and assigned. After determining the equipment start-up and shutdown combinations, the central control unit calculates the specific values ​​of the operating parameters for each started device based on the degree to which real-time temperature and humidity data deviate from the target range. For example, if the temperature is only slightly higher than the target range, the operating power of the air conditioning unit can be set to a lower level; if the temperature is significantly higher than the target range, the operating power of the air conditioning unit will be set to a higher level. Similarly, the greater the deviation of humidity from the target range, the higher the humidification intensity of the humidification system will be set, and the fan speed of the axial flow fan can also be adjusted appropriately according to the degree of deviation to ensure that the operating parameters are accurately matched with the environmental deviation.

[0032] Simultaneously, machine learning models are used to optimize control strategies. Key information from historical control processes is automatically recorded, including the type and degree of environmental deviations (temperature / humidity) during each control operation, the equipment start / stop combinations used, the set operating parameters, and the final actual control effect. Based on these historical records, a machine learning model is trained to establish a mapping relationship between environmental deviations and optimal control strategies. When generating subsequent coordinated control commands, the central control unit prioritizes the optimal control strategy recommended by the machine learning model. If the model-recommended strategy does not match the strategy mapping table lookup result, the model-recommended optimal strategy takes precedence, further improving the accuracy and efficiency of control.

[0033] In addition, an architecture of central control unit + zone control sub-unit is adopted. The central control unit is responsible for global coordination, and the zone control sub-unit is responsible for local adjustment of the corresponding area. The two communicate through industrial Ethernet to ensure that the coordinated control commands are generated and transmitted efficiently and without delay, avoiding untimely control due to command lag.

[0034] Through state judgment, strategy query, parameter calculation and machine learning optimization, the generated collaborative control commands are highly targeted and can dynamically match the current environmental state. This solves the problems of independent equipment operation and blind control strategies in traditional discrete control, and provides a precise control basis for subsequent equipment linkage operation.

[0035] 103. According to the coordinated control instructions, the air conditioning unit, humidification system and axial flow fan are driven to start synchronously and operate according to the determined combination and parameters, so as to carry out integrated linkage regulation of temperature and humidity in the clean space.

[0036] Specifically, firstly, the collaborative control instructions are parsed. After receiving the collaborative control instructions sent by the central control unit, the instructions are broken down and parsed. On the one hand, the equipment start-stop combination is determined, i.e., which equipment needs to be started and which equipment remains off. On the other hand, the operating parameters specified for each started equipment are extracted, such as the operating mode of the air conditioning unit (cooling / heating) and heat exchange intensity, the humidification intensity of the humidification system, and the wind speed of the axial flow fan.

[0037] Secondly, start-up commands are sent according to a preset start-up logic. To ensure uniform and efficient control, a fixed equipment start-up logic can be preset, preventing all devices from starting simultaneously. The execution layer control module first generates a start-up command and sends it to the axial fan controller. Upon receiving the command, the axial fan starts running and sends a "started" signal back to the execution layer control module upon completion. Upon receiving this signal, the execution layer control module generates a synchronous start-up command and sends it simultaneously to the air conditioning unit controller and the humidification system controller, controlling both to start synchronously. This start-up logic ensures that the axial fan starts first, allowing the air in the clean space to circulate in advance. This allows the hot and cold air generated by the air conditioning unit and the moisture generated by the humidification system to spread more quickly and evenly throughout the space, preventing localized temperature or humidity concentrations that could lead to uneven control.

[0038] Then, the control signals are converted and sent. The execution layer integrates air conditioning units, dehumidifiers, fresh air valves, return air valves, supply fans, humidification systems, and axial fans, and all devices have a unified interface protocol and control logic. The parsed operating parameters of each device are converted into control signals that the corresponding device can recognize, such as voltage signals, current signals, or digital signals. These control signals are then sent to the controllers of each started device through a unified interface, ensuring that the devices can accurately receive operating commands.

[0039] Next, closed-loop feedback adjustment ensures operational accuracy. After each device starts up, its actual operating parameters are collected in real time, such as the actual heat exchange intensity of the air conditioning unit, the actual humidification capacity of the humidification system, and the actual wind speed of the axial fan. These actual operating parameters are then fed back to the execution layer control module. The actual operating parameters are compared in real time with the operating parameters specified in the collaborative control command. If a deviation is found, the control signal sent to the device is adjusted through the closed-loop feedback mechanism to gradually reduce the deviation, bringing the actual operating parameters of the device closer to the specified operating parameters, ensuring that the device operates strictly in accordance with the collaborative control command.

[0040] Simultaneously, operating parameters are dynamically adjusted. Throughout the entire control process, the execution layer control module monitors two key pieces of information in real time: first, the operating status of equipment such as air conditioning units, humidification systems, and axial flow fans, including whether malfunctions have occurred and whether they are operating normally; and second, the real-time temperature and humidity data of the clean space. Based on these two types of information, the module determines the overall effectiveness of the current coordinated adjustment, such as whether it is approaching the target range within a reasonable time, whether there is an over-adjustment trend during the control process, and whether the temperature and humidity are uniform. If it is determined that the overall effectiveness has not reached the preset threshold, the relevant information is fed back to the central control unit. The central control unit dynamically adjusts the operating parameters in the coordinated control command based on the feedback information, and the adjusted command is then sent back to the execution layer control module, which updates the control signals sent to each device, thereby achieving real-time optimization of the control strategy.

[0041] In addition, other equipment, such as fresh air valves, return air valves, rotary dehumidifiers, and supply fans, will operate in conjunction with the air conditioning unit, humidification system, and axial flow fan. For example, when the air conditioning unit is in cooling mode, the fresh air valves and return air valves will adjust their opening and closing degrees according to the indoor and outdoor air parameters and the global coordination instructions of the central control unit, controlling the amount of fresh air introduced and the proportion of return air, thus ensuring both cooling effect and energy saving. When the humidity is high, the rotary dehumidifier will start in conjunction with the air conditioning unit to help reduce humidity and improve dehumidification efficiency.

[0042] Through instruction parsing, orderly startup, signal conversion, closed-loop feedback, and dynamic adjustment, the integrated linkage operation of multiple devices is realized, avoiding the problems of independent device action and poor coordination in traditional discrete control. The control actions are more coordinated, the operating parameters are more accurate, and the temperature and humidity of the clean space can be adjusted quickly and evenly, greatly improving the control efficiency and accuracy.

[0043] 104. When the real-time temperature and humidity data are detected to reach the preset target range, control the air conditioning unit, humidification system and axial flow fan to stop operating.

[0044] Specifically, the first step is to determine when to stop. Temperature and humidity sensors continuously collect real-time temperature and humidity data from the cleanroom and transmit it to the central control unit. The central control unit continuously compares the real-time data with the preset target range. When the real-time temperature and humidity data remain consistently within the preset target range for a first preset time, it indicates that the temperature and humidity of the cleanroom have stabilized and met the standards. At this point, the stop conditions for the air conditioning unit and humidification system are satisfied. Setting the first preset time is to avoid misjudgments caused by temporary environmental fluctuations, such as a momentary reaching of the target range followed by a rapid deviation, ensuring stable control effects.

[0045] Secondly, the air conditioning unit and humidification system are controlled to stop working. The central control unit generates a first stop command and sends it to the execution layer control module via industrial Ethernet. The execution layer control module forwards the command to the controllers of the air conditioning unit and the humidification system, respectively, to control both to stop working simultaneously, avoiding local temperature and humidity fluctuations caused by one device stopping prematurely.

[0046] Then, the axial fan is controlled to stop with a delay. After the air conditioning unit and humidification system stop working, the axial fan will not stop immediately, but will continue to run at the current fan speed until the second preset time is reached. The reason for setting a delayed stop is that after the air conditioning unit and humidification system stop, there may be residual local hot or cold areas or uneven humidity in the clean space. The continued operation of the axial fan can promote continuous circulation of indoor air, evenly dispersing the residual hot or cold air and moisture, ensuring that the temperature and humidity of the entire clean space remain consistent, and avoiding situations where the local temperature and humidity exceed the target range.

[0047] Finally, the axial flow fan is stopped. After the axial flow fan has been running continuously for the second preset time, the central control unit generates a second stop command and sends it to the execution layer control module. The control module then forwards the command to the axial flow fan controller, which stops the axial flow fan. At this point, the entire control process is complete, and the cleanroom is maintained in a constant temperature and humidity closed environment.

[0048] By employing a delayed shutdown logic that first stops the air conditioning and humidification systems and then the axial flow fans, the stability of temperature and humidity in the clean space is ensured, preventing temperature and humidity rebounds after regulation. This achieves fully automatic maintenance of a constant temperature and humidity environment without human intervention, solving the environmental fluctuation problem caused by improper shutdown timing in traditional control systems.

[0049] Figure 2 This is a schematic diagram of the structure of the intelligent control system for clean space environment based on multi-level collaborative control provided in an embodiment of the present invention.

[0050] like Figure 2 As shown in the figure, this embodiment provides an intelligent control system for clean space environment based on multi-level collaborative control, including: The acquisition module 201 is used to acquire real-time temperature and humidity monitoring data in the clean space; The generation module 202 is used to generate coordinated control instructions for the air conditioning unit, humidification system and axial flow fan based on the comparison results between real-time temperature and humidity monitoring data and preset target range; wherein, the coordinated control instructions dynamically determine the start-stop combination and operating parameters of the air conditioning unit, humidification system and axial flow fan according to the type and degree of deviation of environmental parameters from the preset target range. The coordination module 203 is used to synchronously drive the air conditioning unit, humidification system and axial flow fan to start and operate according to the determined combination and parameters according to the coordination control command, so as to perform integrated linkage adjustment of temperature and humidity in the clean space. The control module 204 is used to control the air conditioning unit, humidification system and axial flow fan to stop operating when the real-time temperature and humidity data are detected to reach the preset target range.

[0051] Figure 3 This is a schematic diagram of the structure of the electronic device provided in this embodiment.

[0052] like Figure 3 As shown, the electronic device may include a processor 301, a communications interface 302, a memory 303, and a communication bus 304. The processor 301, communications interface 302, and memory 303 communicate with each other via the communication bus 304. The processor 301 can call logical instructions from the memory 303 to execute a cleanroom environment intelligent control method based on multi-level collaborative control.

[0053] Furthermore, the logical instructions in the aforementioned memory 303 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0054] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the intelligent control method for clean space environment based on multi-level collaborative control provided by the above methods.

[0055] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the intelligent control method for clean space environment based on multi-level collaborative control provided by the above methods.

[0056] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0057] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent regulation of a clean space environment based on multi-level cooperative control, characterized in that, include: Acquire real-time temperature and humidity monitoring data within the clean space; Based on the comparison results between the real-time temperature and humidity monitoring data and the preset target range, a coordinated control command is generated for the linkage control of the air conditioning unit, the humidification system and the axial flow fan; wherein, the coordinated control command dynamically determines the start-stop combination and operating parameters of the air conditioning unit, the humidification system and the axial flow fan according to the type and degree of deviation of the environmental parameters from the preset target range; According to the coordinated control command, the air conditioning unit, the humidification system and the axial flow fan are synchronously driven to start and operate according to the determined combination and parameters, so as to perform integrated linkage regulation of the temperature and humidity of the clean space; When the real-time temperature and humidity data are detected to reach the preset target range, the air conditioning unit, the humidification system, and the axial flow fan are controlled to stop operating.

2. The method of claim 1, wherein, The step of synchronously driving the air conditioning unit, the humidification system, and the axial flow fan to start and operate according to a determined combination and parameters based on the coordinated control command includes: The coordinated control command is parsed to obtain the operating parameters specified for the air conditioning unit, the humidification system, and the axial flow fan, respectively. According to the device start / stop combination in the collaborative control instruction, a start command is sent to the corresponding device according to the preset start logic; The air conditioning unit, the humidification system, and the axial flow fan that have been started are controlled to operate according to the specified operating parameters.

3. The method of claim 2, wherein, Sending a startup command to the corresponding device according to a preset startup logic includes: Generate and send a start command to the axial flow fan; Upon receiving feedback that the axial fan has started, a synchronous start command is generated and sent to the air conditioning unit and the humidification system.

4. The method of claim 3, wherein, The control unit, the humidification system, and the axial flow fan, which have been started, are operating according to specified operating parameters, including: The operating parameters are converted into control signals that can be recognized by the corresponding device; The control signals are sent to the controllers of the air conditioning unit, the humidification system, and the axial flow fan, respectively. Monitor the actual operating parameters of each device and compare them with the specified operating parameters. Adjust the control signal through closed-loop feedback to make the actual operating parameters approach the specified operating parameters.

5. The method of claim 4, wherein, Also includes: Real-time monitoring of the operating status of the air conditioning unit, the humidification system, and the axial flow fan, as well as the real-time temperature and humidity data of the clean space; Based on the operating status and real-time temperature and humidity data, the overall effectiveness of the current coordinated adjustment is determined. If the overall performance does not reach the preset threshold, the operating parameters in the collaborative control command are dynamically adjusted, and the control signals sent to each device are updated according to the adjusted command.

6. The method of claim 1, wherein, Based on the comparison results between the real-time temperature and humidity monitoring data and the preset target range, a coordinated control command is generated for the linkage control of the air conditioning unit, humidification system, and axial flow fan, including: The real-time temperature and humidity monitoring data are compared with the preset temperature target range and humidity target range respectively to determine whether the current temperature is too high, the temperature is too low, the humidity is too high, or the humidity is too low. Based on the determined state combination, the preset policy mapping table is queried to determine the corresponding device start / stop combination suggestion; Based on the degree to which the real-time temperature and humidity monitoring data deviates from the target range, the specific values ​​of the operating parameters are calculated and allocated.

7. The method of claim 1, wherein, When the real-time temperature and humidity data are detected to reach the preset target range, the control of the air conditioning unit, the humidification system, and the axial flow fan to stop operating includes: When the real-time temperature and humidity data are monitored to remain stable within the preset target range for a first preset duration, a first stop command is generated to control the air conditioning unit and the humidification system to stop working. After the air conditioning unit and the humidification system stop working, the axial flow fan continues to run for the second preset time. After the second preset time period is reached, a second stop command is generated to control the axial flow fan to stop working.

8. The method according to any one of claims 1 to 7, characterized in that, The acquisition of real-time temperature and humidity monitoring data within the clean space includes: Based on the layout of the process areas within the clean space, several key monitoring points were identified; Temperature and humidity sensors were deployed at the key monitoring points to collect temperature and humidity data. Data from multiple temperature and humidity sensors are fused to generate real-time temperature and humidity monitoring data that characterizes the overall environmental state of the clean space.

9. The method according to any one of claims 1-7, characterized in that, The dynamic determination of the start-stop combination and operating parameters of the air conditioning unit, the humidification system, and the axial flow fan includes: Record the start-stop combinations and operating parameters used under different environmental deviations during historical control processes, as well as the corresponding actual control effects; Based on historical records, a mapping relationship between environmental deviations and optimal control strategies is established using machine learning models. When generating the collaborative control instructions, the optimal control strategy recommended by the machine learning model is invoked first.

10. A clean space environment intelligent regulation system based on multi-level cooperative control, characterized in that, include: The acquisition module is used to acquire real-time temperature and humidity monitoring data within the clean space; The generation module is used to generate coordinated control instructions for the air conditioning unit, humidification system and axial flow fan based on the comparison results between the real-time temperature and humidity monitoring data and the preset target range; wherein, the coordinated control instructions dynamically determine the start-stop combination and operating parameters of the air conditioning unit, the humidification system and the axial flow fan according to the type and degree of deviation of the environmental parameters from the preset target range; The coordination module is used to synchronously drive the air conditioning unit, the humidification system and the axial flow fan to start and operate according to a determined combination and parameters according to the coordination control command, so as to perform integrated linkage adjustment of the temperature and humidity of the clean space; The control module is used to control the air conditioning unit, the humidification system and the axial flow fan to stop operating when the real-time temperature and humidity data are detected to reach the preset target range.

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