Clean room temperature and humidity automatic adjusting method and system, medium and program product

Abstract

The invention relates to a method and system for automatically adjusting the temperature and humidity of a clean room, a medium and a program product, and the method comprises the steps: obtaining a real-time monitoring video of the clean room; determining an experiment area where an experimenter is located; acquiring a temperature distribution diagram and a humidity distribution diagram, and judging whether the experimental temperatures of the experimental areas are the same or not; if not, a first instruction is sent to temperature control equipment, so that the temperature control equipment controls the experimental temperature to be the same as the indoor average temperature; judging whether the experimental humidity of the experimental area is the same; if not, a second instruction is sent to the humidity control equipment, so that the humidity control equipment controls the experiment humidity to be the same as the indoor average humidity; and if the experimental temperatures are the same and the experimental humidity is the same, controlling each temperature control device and each humidity control device to maintain the current operation parameters. The temperature and humidity parameters of the experimental area are accurately controlled, so that the environmental parameters of the experimental area meet the standard conditions, and the accuracy of the experimental result is further improved.

Description

Technical Field

[0001] The present application belongs to the field of environmental parameter control, and in particular, relates to a method, system, medium and program product for automatic adjustment of temperature and humidity in a clean room. Background Art

[0002] Clean rooms are special environments with low pollution levels and are widely used in places where strict control of environmental conditions is required, such as precision manufacturing, biomedical research, etc.

[0003] In related technologies, a temperature and humidity control sample set is collected, and then the functional relationship between temperature and humidity, temperature clean room variable control requirements, humidity clean room variable control requirements, and temperature and humidity set point acquisition values ​​is fitted, multiple data analysis channels are constructed, and the channels are connected to construct a data analysis optimization model, the current clean room control requirements are obtained and the parameter control requirements are decomposed, and the control parameters are optimized in the data analysis optimization model, and the temperature and humidity control scheme is obtained and sent to the controller for temperature and humidity control. By performing control mutual influence analysis, the control parameters are determined and modeled for parameter control optimization, reasonable planning of control energy is carried out, and control stability and accuracy are guaranteed.

[0004] However, the temperature and humidity data collected by the above technical solution are obtained based on the data measured by the sensor. Generally speaking, the temperature and humidity data measured by the sensor are parameters around the sensor, and there may be areas with different temperatures and humidities in the clean room. The areas that require standard environmental parameters may not meet the standard conditions. At this time, if experimental operations are performed, the accuracy of the experimental results may be reduced. At this time, the data collected by the temperature and humidity sensors still meet the standard conditions, and it is difficult for experimenters to find the problem. Summary of the invention

[0005] The present application provides a method, system, medium and program product for automatically adjusting the temperature and humidity of a clean room, which are used to accurately control the temperature and humidity parameters of an experimental area so that the environmental parameters of the experimental area meet standard conditions, thereby improving the accuracy of the experimental results.

[0006] In a first aspect, the present application provides a method for automatically adjusting the temperature and humidity of a clean room. When it is determined that the current environmental parameters of the clean room meet the preset environmental parameters, a real-time monitoring video of the clean room is obtained, and the current environmental parameters include the average indoor temperature and the average indoor humidity; Determine the experimental area where the experimenter is located based on the real-time monitoring video; Obtain a temperature distribution map and a humidity distribution map of the experimental area, and determine whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map; If the experimental temperature is different, determine the temperature control equipment that controls the temperature of the experimental area; Sending a first instruction to the temperature control device so that the temperature control device controls the experimental temperature to be the same as the indoor average temperature; Determine whether the experimental humidity in the experimental area is the same based on the humidity distribution diagram; If the experimental humidity is different, determine the humidity control equipment that controls the humidity in the experimental area; Sending a second instruction to the humidity control device to enable the humidity control device to control the experimental humidity to be the same as the average humidity in the room; If the experimental temperature and the experimental humidity are the same, each temperature control device and humidity control device is controlled to maintain the current operating parameters.

[0007] By adopting the above technical solution, first determine whether the overall environment of the clean room meets the standard. If so, further analyze the specific conditions of each experimental area. By obtaining real-time monitoring video to determine the location of personnel, and combining the temperature and humidity distribution map of the area, it can be found whether there is unevenness in the environmental parameters within the area. If it is found that the experimental temperature or humidity inside the experimental area is inconsistent, the method will automatically match the corresponding temperature control or humidity control equipment, and issue control instructions to adjust the parameters of the experimental area to be consistent with the average level of the clean room. When the internal environment of the experimental area is already uniform and stable, the current equipment operating parameters are maintained unchanged. Based on fine-grained real-time monitoring, a control strategy is customized for each experimental area to maximize energy saving while ensuring the experimental environment, and to achieve accurate control of the temperature and humidity parameters of the experimental area so that the environmental parameters of the experimental area meet standard conditions, thereby improving the accuracy of the experimental results.

[0008] In combination with some embodiments of the first aspect, in some embodiments, obtaining a temperature distribution map and a humidity distribution map of an experimental area, and judging whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map specifically includes: Determine the light source distribution, temperature distribution map and humidity distribution map of the experimental area based on the real-time monitoring video; Determine whether the light source in the clean room affects the temperature distribution diagram and humidity distribution diagram based on the light source distribution; If not, executing the step of determining whether the experimental temperatures of the experimental areas are the same according to the temperature distribution diagram; If there is an impact, adjust the light source so that it moves away from the experimental area.

[0009] By adopting the above technical solution, real-time monitoring video technology is utilized. By analyzing the video images, the system can accurately locate the distribution position of each light source and determine whether they will affect the environmental measurement of the experimental area. If the impact is not significant, the original temperature and humidity distribution map can be used directly. However, if the light source interference is serious, the method will automatically adjust the light source to keep it away from the experimental area to eliminate the measurement error. This correction method for light source interference is adaptive and does not require the installation of additional sensors, which greatly simplifies the implementation cost of the system. It ensures the data quality of the temperature and humidity distribution map and provides a reliable basis for environmental judgment in the experimental area.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after adjusting the light source so that the light source leaves the experimental area if affected, the method further includes: After adjusting the light source, determining an adjusted light source distribution after adjustment; Determine whether adjusting the light source distribution affects the temperature distribution map and the humidity distribution map; If there is no impact, the step of determining whether the experimental temperatures of the experimental areas are the same according to the temperature distribution diagram is performed; If so, determine the temperature compensation data and humidity compensation data of the experimental area; An updated temperature distribution map and humidity distribution map are determined according to the temperature compensation data and the humidity compensation data, and a step of judging whether the experimental temperatures of the experimental areas are the same is performed according to the temperature distribution map.

[0011] By adopting the above technical solution and introducing temperature and humidity compensation data, the interference factor of the light source can be eliminated in real time during the generation of the distribution map. The system will re-evaluate the impact of the light source on the environmental parameters after the light source is adjusted. If the impact still exists, the actual temperature and humidity data of the light source radiation area are measured, compared with the average level of the clean room, and the corresponding compensation value is calculated. Then these compensation data are substituted into the generation algorithm of the temperature and humidity distribution map to correct the measurement results of the light source area to make it as close as possible to the actual environmental parameters of the experimental area. This compensation strategy is equivalent to superimposing a layer of digital filtering on the basis of the original measurement. The suppression of light source interference is achieved in the post-processing stage through the software algorithm without the need to modify the hardware equipment. It is practical and economical.

[0012] In combination with some embodiments of the first aspect, in some embodiments, judging whether the light source of the clean room affects the temperature distribution diagram and the humidity distribution diagram according to the light source distribution specifically includes: Receiving temperature data within a preset range of a light source position detected by a thermal imager, where the light source distribution includes the light source position; Identify high temperature areas where temperature data differs from the average indoor temperature; Determine whether there is an overlapping area between the high temperature area and the experimental area. If there is, the light source of the clean room affects the temperature distribution diagram. If not, the light source of the clean room does not affect the temperature distribution diagram. Receiving humidity data within a preset range of the light source position detected by the humidity sensor; Identify high humidity areas where humidity data differs from the average indoor humidity; It is determined whether there is an overlapping area with high humidity. If so, the light source of the clean room affects the humidity distribution diagram. If not, the light source of the clean room does not affect the humidity distribution diagram.

[0013] By adopting the above technical solution, the impact of the light source on the experimental area environment can be quantitatively evaluated by comparing with the average level of the clean room. Among them, the thermal imager is a non-contact infrared imaging device that can monitor the temperature distribution on the surface of an object in real time. By imaging the light source and its surrounding area and combining the image processing algorithm, it is possible to identify areas that are significantly higher than the average temperature of the clean room, and then determine whether the thermal radiation of the light source will interfere with the experimental area. Similarly, the humidity sensor can be used for humidity monitoring in the area near the light source. Through the spatial interpolation analysis of a large amount of sensor data, the system can generate a humidity distribution cloud map of the area and identify high humidity areas that may be affected by the air flow disturbance of the light source. Furthermore, the method also considers the spatial superposition effect of the thermal radiation of the light source and the humidity disturbance. Only when the high temperature area and the high humidity area cover the experimental area at the same time, the light source interference is considered significant and position adjustment or compensation processing is required. This judgment logic avoids the one-sided analysis of a single factor and improves the comprehensiveness and accuracy of the light source interference assessment.

[0014] In combination with some embodiments of the first aspect, in some embodiments, if the influence is, determining the temperature compensation data and humidity compensation data of the experimental area specifically includes: Determine the impact area of ​​adjusting the light source distribution to affect the experimental area; Measure the effect of light source on temperature and humidity in the affected area; Control light source off and measure light source off temperature and light source off humidity in the affected area; The difference between the temperature affected by turning on the light source and the temperature affected by turning off the light source is determined as temperature compensation data; the difference between the humidity affected by turning on the light source and the humidity affected by turning off the light source is determined as humidity compensation data.

[0015] By adopting the above technical solution, through the switching light source experiment, the change in the environmental parameters of the interference area is measured and obtained, and it is used as the basis for subsequent correction. Specifically, the system first identifies the area that is significantly affected by the light source. In this area, the temperature and humidity data are measured when the light source is turned on and off, respectively. The difference between the two reflects the degree of interference of the light source and can be used as the temperature and humidity compensation. Since the compensation data comes from actual measurements rather than empirical estimates, the reliability and accuracy of its values ​​can be guaranteed. When the temperature and humidity distribution map is generated later, the system will automatically superimpose the compensation amount on the measurement results of the affected area. This is equivalent to a local correction of the distribution map, offsetting the influence of the light source interference, making it closer to the actual environmental parameters of the experimental area. In this way, even if the light source interference cannot be completely eliminated by hardware means, the equivalent effect can be achieved by software compensation to maximize the environmental stability of the experimental area.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, determining the impact area of ​​adjusting the light source distribution to impact the experimental area specifically includes: Receive real-time temperature data and real-time humidity data of the light source position when the light source is in the on state; Receive real-time shut-down temperature data and real-time shut-down humidity data of the light source position when the light source is in a shut-down state; Generate an opening temperature graph, an opening humidity graph, a closing temperature graph and a closing humidity graph according to the real-time opening temperature data, the real-time opening humidity data, the real-time closing temperature data and the real-time closing humidity data respectively; The on-temperature graph and the off-temperature graph, and the on-humidity graph and the off-humidity graph are compared to obtain an affected area where the temperature difference is greater than a preset temperature threshold and the humidity difference is greater than a preset humidity threshold.

[0017] By adopting the above technical solution, a series of temperature and humidity distribution images are obtained through the light source switch experiment, and the key difference information is extracted by using image processing technology to determine the spatial distribution of the affected area. First, the system uses thermal imagers, humidity sensors and other equipment to collect real-time temperature and humidity data at the light source position when the light source is turned on and off. After preprocessing such as coordinate mapping and spatial interpolation, these data can generate corresponding temperature maps and humidity maps, which intuitively reflect the distribution of environmental parameters in the area around the light source. Then, by performing difference calculations on the temperature maps and humidity maps under different states, the degree of influence of the light source switch on the environmental parameters of the area can be quantitatively evaluated. The temperature difference map reflects the thermal radiation effect of the light source, while the humidity difference map reflects its air flow disturbance. By superimposing and analyzing the two difference maps, the spatiotemporal distribution characteristics of the light source interference can be fully characterized. Finally, the system binarizes the difference map according to the preset temperature and humidity thresholds, and extracts the significant area where the difference exceeds the threshold as the influence area of ​​the light source. The boundary of this area represents the spatial range of the light source interference, which can be used for subsequent compensation control.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after sending a second instruction to the humidity control device so that the humidity control device controls the experimental humidity to be the same as the indoor average humidity, the method further includes: If the experimental temperature is not equal to the average indoor temperature when the temperature control device is running at any power, or the experimental humidity is not equal to the average indoor humidity when the humidity control device is running at any power, the control alarm device will issue a preset alarm message.

[0019] By adopting the above technical solution, after the temperature and humidity control task is completed, the system will reconfirm the execution status of the control device. Specifically, by changing the operating power of the control device, observe its impact on the environmental parameters of the experimental area. If the temperature or humidity in the experimental area cannot be stabilized at the target value at any power, it indicates that the control device may have a fault or abnormality and cannot play a normal regulatory role. Once the above abnormal situation is found, the system will immediately trigger the preset alarm mechanism. The alarm information can be pushed to on-site operators and managers in real time through various means such as sound and light, reminding them to take emergency measures in time to eliminate hidden dangers and avoid further deterioration of the problem. At the same time, the system will automatically generate a detailed abnormality analysis report, recording key information such as the time, location, and environmental parameters of the incident, and provide data support for subsequent cause analysis and improvement and optimization.

[0020] In the second aspect, an embodiment of the present application provides a clean room temperature and humidity automatic regulation system, the clean room temperature and humidity automatic regulation system comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable x to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a system, causes the system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer program product, characterized in that when the computer program product runs on a system, the system executes the method described in any possible implementation manner in the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The present application provides a method for automatically adjusting the temperature and humidity of a clean room. First, it is determined whether the overall environment of the clean room meets the standard. If so, the specific conditions of each experimental area are further analyzed. By obtaining real-time monitoring video to determine the location of personnel, and combining the temperature and humidity distribution map of the area, it can be found whether there is unevenness of environmental parameters inside the area. If it is found that the experimental temperature or humidity inside the experimental area is inconsistent, the method will automatically match the corresponding temperature control or humidity control equipment, and issue a control instruction to adjust the parameters of the experimental area to be consistent with the average level of the clean room. When the internal environment of the experimental area is already uniform and stable, the current equipment operating parameters are maintained unchanged. Based on fine-grained real-time monitoring, a control strategy is customized for each experimental area to maximize energy saving while ensuring the experimental environment, and the temperature and humidity parameters of the experimental area are accurately controlled so that the environmental parameters of the experimental area meet the standard conditions, thereby improving the accuracy of the experimental results.

[0024] 2. The present application provides a method for automatic adjustment of the temperature and humidity of a clean room. By introducing temperature and humidity compensation data, the interference factors of the light source are eliminated in real time during the generation of the distribution map. The system will re-evaluate the impact of the light source on the environmental parameters after the light source is adjusted. If the impact still exists, measure the actual temperature and humidity data of the light source radiation area, compare it with the average level of the clean room, and calculate the corresponding compensation value. These compensation data are then substituted into the generation algorithm of the temperature and humidity distribution map, and the measurement results of the light source area are corrected to make it as close as possible to the actual environmental parameters of the experimental area. This compensation strategy is equivalent to superimposing a layer of digital filtering on the basis of the original measurement. The suppression of light source interference is achieved in the post-processing stage through the software algorithm without the need to modify the hardware equipment. It is practical and economical.

[0025] 3. The present application provides a method for automatically adjusting the temperature and humidity of a clean room. Through a light source switch experiment, a series of temperature and humidity distribution images are obtained, and image processing technology is used to extract key difference information, thereby determining the spatial distribution of the affected area. First, the system uses a thermal imager, a humidity sensor and other equipment to collect real-time temperature and humidity data at the light source position when the light source is turned on and off. After preprocessing such as coordinate mapping and spatial interpolation, these data can generate corresponding temperature maps and humidity maps, which intuitively reflect the distribution of environmental parameters in the area around the light source. Then, by performing difference calculations on the temperature maps and humidity maps under different states, the degree of influence of the light source switch on the environmental parameters of the area can be quantitatively evaluated. The temperature difference map reflects the thermal radiation effect of the light source, while the humidity difference map reflects its air flow disturbance. By superimposing and analyzing the two difference maps, the spatiotemporal distribution characteristics of the light source interference can be fully characterized. Finally, the system binarizes the difference map according to the preset temperature and humidity thresholds, and extracts the significant area where the difference exceeds the threshold as the influence area of ​​the light source. The boundary of this area represents the spatial range of the light source interference, which can be used for subsequent compensation control. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a method for automatically adjusting the temperature and humidity of a clean room in an embodiment of the present application.

[0027] Figure 2 This is another flow chart of a method for automatically adjusting the temperature and humidity in a clean room according to an embodiment of the present application.

[0028] Figure 3 It is a schematic diagram of the physical device structure of a clean room temperature and humidity automatic adjustment system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0031] An application scenario of an embodiment of the present application is described below: In the cleanroom of a high-tech semiconductor chip manufacturing company, engineers are testing the performance of a batch of new chips. These chips have very strict requirements on environmental conditions. Slight fluctuations in temperature and humidity may lead to significant differences in chip performance, which in turn affects the yield and consistency of the product.

[0032] In order to ensure the stability and controllability of the test environment, engineers have specially designed a high-precision clean room environment control system. The system is equipped with multiple highly sensitive temperature and humidity sensors distributed in different areas of the workshop to collect environmental data in real time. At the same time, the central control unit will dynamically adjust the operating status of air conditioners, humidifiers and other equipment according to the preset standard parameters to ensure that the overall temperature and humidity of the workshop meet the requirements of chip testing.

[0033] However, during the actual testing process, engineers found that the performance of some chips showed certain abnormalities. After repeated investigations, they finally focused their attention on the local environment of the test area. Through on-site investigations, engineers found that the test area was in the corner of the workshop, surrounded by a large amount of equipment and materials, resulting in poor air circulation in the area. Although the temperature and humidity sensors showed that the environmental parameters of the area were still within the standard range, local temperature and humidity differences had actually formed.

[0034] This microenvironmental non-uniformity has an impact on the test results of the chips that cannot be ignored. The performance of chips in the high-temperature zone is generally lower than expected, while the performance of chips in the low-temperature zone is too good. At the same time, poor air circulation also exacerbates the temperature and humidity fluctuations in local areas, further worsening the discreteness of the test results. If these chips with abnormal performance flow into the subsequent packaging and application links, it will not only affect the reliability of the entire product, but may also cause safety accidents and cause immeasurable losses. In order to solve the above-mentioned technical problems, the present application provides a method for automatic adjustment of the room temperature and humidity in a clean room, which accurately controls the temperature and humidity parameters of the experimental area so that the environmental parameters of the experimental area meet the standard conditions, thereby improving the accuracy of the experimental results. The following is combined with Figure 1 , a method for automatically adjusting the room temperature and humidity of a clean room in an embodiment of the present application is described: See also Figure 1 , is a flow chart of a method for automatically adjusting the temperature and humidity in a clean room in an embodiment of the present application.

[0035] S101, when it is determined that the current environmental parameters of the clean room meet the preset environmental parameters, obtaining a real-time monitoring video of the clean room; When the system determines that the current environmental parameters of the clean room meet the preset environmental parameters, it obtains the real-time monitoring video of the clean room. The current environmental parameters include the average indoor temperature and the average indoor humidity. This step is the starting point of the automatic adjustment of the temperature and humidity of the clean room. The main purpose is to ensure that the subsequent environmental parameters are adjusted on a reasonable and safe basis.

[0036] First, the system needs to obtain the actual environmental parameters of the clean room, including the average temperature and humidity in the room. This process is usually achieved through a network of temperature and humidity sensors deployed in the clean room. The sensors collect temperature and humidity data at a certain time and space density and summarize them to the central control unit. Based on the summarized data, the system calculates the average temperature and humidity values ​​of the entire clean room as a basis for judging whether the environment meets the standards.

[0037] Then, the system compares the measured average temperature and humidity with the preset environmental parameter thresholds. The preset thresholds here are usually determined based on factors such as the cleanliness level and process requirements of the clean room, and represent the environmental conditions that the clean room should meet under normal operating conditions. For example, for a Class 100 clean room, the temperature threshold may be set at 22±1°C and the humidity threshold may be set at 50%±5%RH.

[0038] Only when the measured average temperature and humidity fall within the allowable range of the preset threshold value, the system will determine that the current environmental parameters meet the standards and enter the next step of the experimental area environmental adjustment process. This process can effectively avoid deviations caused by equipment failures, human errors, etc., and provide a stable and reliable initial state for subsequent refined control.

[0039] If the system finds that the current environmental parameters exceed the preset threshold, it will immediately trigger an early warning and take corresponding emergency measures according to the degree of deviation, such as adjusting the air conditioning cooling / heating capacity, humidifier humidification, etc., to control the environmental parameters within a safe range. At the same time, the system will also send a notification to the management personnel, prompting them to investigate the cause of the abnormality to prevent the problem from further deteriorating.

[0040] Once it is confirmed that the overall environment of the clean room meets the standards, the system will activate the camera and begin to obtain real-time monitoring video of the clean room, providing data support for subsequent experimental area determination, environmental visualization analysis and other functions.

[0041] S102, determining the experimental area where the experimenter is located according to the real-time monitoring video; After obtaining the real-time monitoring video of the clean room, the system needs to further determine the specific location of the experimenter to determine the target area for subsequent environmental parameter adjustment.

[0042] First, the system pre-processes the surveillance video, including image enhancement and noise removal, to improve the image quality and provide a good data basis for subsequent analysis. Then, the system scans the video frames frame by frame through a specially trained target detection model to identify the staff in the picture. Commonly used target detection algorithms such as YOLO and SSD can achieve high processing speed while ensuring detection accuracy to meet real-time requirements.

[0043] After detecting a human target, the system will further extract its characteristic information, such as clothing color, height, etc., and use tracking algorithms (such as Kalman filtering, particle filtering, etc.) to continuously track the target, and maintain the consistency and continuity of the target even in the event of occlusion, background interference, etc.

[0044] After the above processing, the system can obtain the spatial position coordinates (such as x, y, z) of each staff member. Combined with the known information of the area division in the clean room, the system can automatically determine the specific area (such as area A, area B, etc.) where each person is located.

[0045] S103, obtaining a temperature distribution map and a humidity distribution map of the test area, and judging whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map; The system obtains the temperature distribution map and humidity distribution map of the test area, and determines whether the experimental temperature of the experimental area is the same according to the temperature distribution map. The specific implementation method of this step will be described below and will not be repeated here.

[0046] S104, determining a temperature control device for controlling the temperature of the experimental area; If the experimental temperature is not the same, determine the temperature control device that controls the temperature of the experimental area. When the system detects that there is significant non-uniformity in the temperature of the experimental area, it is necessary to further clarify which temperature control devices cause this local deviation so that targeted parameter adjustments can be made.

[0047] First, the system retrieves the distribution location, specification parameters, control logic and other information of all temperature control equipment (such as air conditioners, radiation panels, fan coils, etc.) in the experimental area to form a complete equipment topology network. This process usually needs to be compared with the design drawings of HVAC, electrical and other professionals to ensure the accuracy and synchronization of the information.

[0048] Secondly, the system overlays and analyzes the device network information with the temperature distribution map generated in step S103. By matching the spatial coordinates, the system can determine which temperature control devices are distributed near each abnormal point such as the high temperature zone and the low temperature zone. Here, factors such as the range of action of the equipment and the airflow organization need to be considered to reasonably set the influence radius. If there are multiple devices within the influence range of a certain abnormal point, their relative importance needs to be further weighed. Sensitivity analysis, principal component analysis and other methods can be used to calculate the contribution rate of each device to the temperature at that location.

[0049] S105, sending a first instruction to the temperature control device so that the temperature control device controls the experimental temperature to be the same as the indoor average temperature; After clarifying the temperature control equipment corresponding to each abnormal point in the experimental area, the system needs to further formulate an optimization adjustment plan and send control instructions to the actuator to achieve uniformity of the temperature field.

[0050] First, the system will establish a mathematical and physical model of the experimental area based on the measured temperature distribution and target temperature requirements, using heat balance equations, fluid mechanics equations, etc. This model describes the formation mechanism of the temperature field from multiple aspects such as heat generation, transfer, and consumption, and takes into account various boundary conditions and disturbance sources such as air conditioning air supply, personnel heat dissipation, and equipment power consumption, which can more comprehensively reflect the actual working conditions. On this basis, the system will design an optimization objective function, such as minimizing the regional temperature variance, and at the same time list equipment energy consumption, cooling capacity, etc. as constraints to form a standard optimal control problem.

[0051] Next, the system will solve the optimization problem and find a set of optimal temperature control equipment parameter combinations through numerical iteration and other methods to minimize the temperature gradient while satisfying the constraints. Here, different optimization algorithms can be selected according to the complexity of the model and the real-time requirements, such as linear programming, convex optimization, and intelligent algorithms. The solution result is the temperature control command that needs to be issued, including the set temperature and wind speed of the air conditioner.

[0052] When issuing control instructions, the system will fully consider the dynamic characteristics and control accuracy of the equipment, reasonably set the execution cycle and amplitude threshold of the instructions, avoid too frequent or drastic parameter adjustments, and reduce nonlinear oscillations and energy waste. For equipment with high control accuracy requirements such as constant temperature and humidity units, PID, fuzzy control and other methods can be used to achieve smooth parameter adjustment. At the same time, the system will also collaboratively consider the coupling effects of multiple environmental parameters such as temperature, humidity, and cleanliness, and achieve multi-objective balanced optimization through decoupling control, multivariable control and other methods.

[0053] S106, judging whether the experimental humidity in the experimental area is the same according to the humidity distribution diagram; The system determines whether the experimental humidity in the experimental area is the same according to the humidity distribution diagram, which is the same as step S103 and will not be described in detail here.

[0054] S107, determining a humidity control device for controlling the humidity in the experimental area; If the experimental humidity is not the same, then determine the humidity control device that controls the humidity in the experimental area. This step is the same as step S104 and will not be described in detail here.

[0055] S108, sending a second instruction to the humidity control device so that the humidity control device controls the experimental humidity to be the same as the indoor average humidity; The system sends a second instruction to the humidity control device to enable the humidity control device to control the experimental humidity to be the same as the indoor average humidity, which is the same as step S105 and will not be repeated here.

[0056] S109, if the experimental temperature and the experimental humidity are the same, control each temperature control device and humidity control device to maintain the current operating parameters; If the experimental temperature and the experimental humidity are the same, the system controls each temperature control device and humidity control device to maintain the current operating parameters, which is sufficient to ensure that the environmental parameters of the experimental area meet the standards.

[0057] S110. If the experimental temperature is not equal to the average indoor temperature when the temperature control device is running at any power or the experimental humidity is not equal to the average indoor humidity when the humidity control device is running at any power, the alarm device is controlled to issue a preset alarm message.

[0058] If the experimental temperature is not equal to the average indoor temperature when the temperature control device is running at any power, or the experimental humidity is not equal to the average indoor humidity when the humidity control device is running at any power, it means that the temperature control device or the humidity control device has failed and is insufficient to maintain the experiment. Then the system controls the alarm device to issue a preset alarm message to prompt the staff to stop the test to avoid waste of experimental materials.

[0059] The above embodiments have the following beneficial effects: First, determine whether the overall environment of the clean room meets the standard. If so, further analyze the specific conditions of each experimental area. By obtaining real-time monitoring video to determine the location of personnel, and combining the temperature and humidity distribution map of the area, it can be found whether there is unevenness in the environmental parameters within the area. If it is found that the experimental temperature or humidity inside the experimental area is inconsistent, the method will automatically match the corresponding temperature control or humidity control equipment, and issue control instructions to adjust the parameters of the experimental area to be consistent with the average level of the clean room. When the internal environment of the experimental area is already uniform and stable, the current equipment operating parameters are maintained unchanged. Based on fine-grained real-time monitoring, a control strategy is customized for each experimental area to maximize energy savings while ensuring the experimental environment. It is achieved by accurately controlling the temperature and humidity parameters of the experimental area so that the environmental parameters of the experimental area meet standard conditions, thereby improving the accuracy of the experimental results.

[0060] After the temperature and humidity control task is completed, the system will reconfirm the execution status of the control device. Specifically, by changing the operating power of the control device, observe its impact on the environmental parameters of the experimental area. If the temperature or humidity of the experimental area cannot be stabilized at the target value at any power, it indicates that the control device may have a fault or abnormality and cannot play a normal regulatory role. Once the above abnormal situation is found, the system will immediately trigger the preset alarm mechanism. The alarm information can be pushed to on-site operators and managers in real time through various means such as sound and light, reminding them to take emergency measures in time to eliminate hidden dangers and avoid further deterioration of the problem. At the same time, the system will automatically generate a detailed abnormality analysis report, recording key information such as the time, location, and environmental parameters of the incident, and provide data support for subsequent cause analysis and improvement and optimization.

[0061] Another embodiment is used to describe the specific implementation method of obtaining the temperature distribution map and humidity distribution map of the test area in step S103 in the above embodiment, and judging whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map. Figure 2 , another method for automatically adjusting the room temperature and humidity of a clean room in an embodiment of the present application is described: See also Figure 2 , is another flow chart of a method for automatically adjusting the temperature and humidity of a clean room in an embodiment of the present application.

[0062] S201, determining light source distribution, temperature distribution map and humidity distribution map of the test area according to the real-time monitoring video; The system first uses industrial cameras to collect high-definition video images of the clean room in real time and performs preprocessing, such as image enhancement and noise removal, to improve image quality. On this basis, computer vision algorithms such as target detection and semantic segmentation are used to extract the location distribution information of key scene elements such as light sources and instruments from the video. At the same time, the system also needs to obtain real-time measurement data from a dense array of temperature and humidity sensors that are synchronized with the video.

[0063] Finally, the system maps and integrates the location distribution of scene elements with the temperature and humidity measurements at the corresponding locations, and uses spatial interpolation and other methods to fill in data blind spots, ultimately generating temperature and humidity distribution maps covering the entire clean room. Compared with discrete single-point detection, the distribution map intuitively shows the temperature and humidity levels and their spatial gradients inside the clean room, providing an important basis for evaluating environmental uniformity.

[0064] S202, judging whether the light source of the clean room affects the temperature distribution diagram and the humidity distribution diagram according to the light source distribution; The system determines whether the light source in the clean room affects the temperature distribution diagram and the humidity distribution diagram according to the light source distribution. Specifically, the system receives the temperature data within the preset range of the light source position detected by the thermal imager. The light source distribution includes the light source position. Identify high temperature areas where temperature data differs from the average indoor temperature; Determine whether there is an overlapping area between the high temperature area and the experimental area. If there is, the light source of the clean room affects the temperature distribution diagram. If not, the light source of the clean room does not affect the temperature distribution diagram. Receiving humidity data within a preset range of the light source position detected by the humidity sensor; Identify high humidity areas where humidity data differs from the average indoor humidity; It is determined whether there is an overlapping area with high humidity. If so, the light source of the clean room affects the humidity distribution diagram. If not, the light source of the clean room does not affect the humidity distribution diagram.

[0065] If there is any influence, the temperature compensation data and humidity compensation data of the experimental area are determined, including: Determine the impact area of ​​adjusting the light source distribution to affect the experimental area; Measure the effect of light source on temperature and humidity in the affected area; Control light source off and measure light source off temperature and light source off humidity in the affected area; The difference between the temperature affected by turning on the light source and the temperature affected by turning off the light source is determined as temperature compensation data; the difference between the humidity affected by turning on the light source and the humidity affected by turning off the light source is determined as humidity compensation data.

[0066] Among them, determining the impact area of ​​adjusting the light source distribution to affect the experimental area specifically includes: Receive real-time temperature data and humidity data of the light source position when the light source is in the on state; Receiving real-time closed temperature data and real-time closed humidity data of the light source position when the light source is in a closed state; Generate an opening temperature graph, an opening humidity graph, a closing temperature graph and a closing humidity graph according to the real-time opening temperature data, the real-time opening humidity data, the real-time closing temperature data and the real-time closing humidity data respectively; The on-temperature graph and the off-temperature graph, and the on-humidity graph and the off-humidity graph are compared to obtain an impact area where the temperature difference is greater than a preset temperature threshold and the humidity difference is greater than a preset humidity threshold.

[0067] First, use a thermal imager to measure the real-time temperature field within a certain range around the light source to identify areas where the temperature is significantly higher than the average indoor temperature. If this high temperature area overlaps with the test operation area, it means that the radiant heat of the light source has significantly affected the local temperature distribution.

[0068] Secondly, the system compares and analyzes the local humidity data when the light source is on and off. If the humidity value of the area near the light source is significantly lower than that of other areas when the light source is on, and lower than the humidity value of the same location when the light source is off, it means that the light causes local dryness. On the contrary, if the difference in local humidity between the light source on and off is not large, it can be determined that the effect of the light source on the humidity distribution diagram is negligible.

[0069] S203, adjusting the light source so that the light source leaves the experimental area; If there is an impact, adjust the light source so that it moves away from the experimental area, thus minimizing the impact of the light source on the experimental area.

[0070] S204, determining the adjusted light source distribution after adjustment; S205, determining whether adjusting the light source distribution affects the temperature distribution map and the humidity distribution map; The system determines whether adjusting the light source distribution affects the temperature distribution diagram and the humidity distribution diagram. The principle is the same as step S202 and will not be described in detail here.

[0071] If not, the step of determining whether the experimental temperatures of the experimental areas are the same according to the temperature distribution diagram is performed (step S106 ).

[0072] S206, determining temperature compensation data and humidity compensation data of the experimental area; If so, determine the temperature compensation data and humidity compensation data of the experimental area.

[0073] When it is confirmed that the adjusted light source distribution still has a significant impact on the local environment, the system needs to further quantify this impact, that is, determine the temperature compensation data and humidity compensation data. These two key parameters reflect the contribution of the light source to the local temperature and humidity, and are an indispensable basis for correcting the environmental model and guiding the optimization of regulation.

[0074] Specifically, the temperature compensation data reflects the degree of influence of the radiant heat effect of the light source on the local temperature. It is obtained by comparing the temperature difference when the light source is turned on and off. The system controls the light source to turn on, and uses a thermal imager to measure the real-time temperature of the affected area, which is recorded as the "light source turned on temperature"; then the light source is controlled to turn off, and the temperature is measured again, which is recorded as the "light source turned off temperature". The difference between the two is the temperature compensation data. For example, if the temperature of the affected area is 26.5℃ when turned on and 24.8℃ when turned off, the temperature compensation data is 1.7℃, which means that the current light source will increase the local temperature by 1.7℃.

[0075] Similarly, humidity compensation data reflects the degree of influence of light absorption on local relative humidity. The measurement method is similar to temperature compensation, which is the difference between "the influence of light source on humidity" and "the influence of light source off humidity". However, a humidity sensor is used instead of a thermal imager. For example, if the humidity in the affected area is 54% when it is turned on and rises to 58% when it is turned off, the humidity compensation data is -4%, which means that the current light source will reduce the local relative humidity by 4 percentage points.

[0076] S207: Determine an updated temperature distribution map and humidity distribution map according to the temperature compensation data and the humidity compensation data.

[0077] The system determines an updated temperature distribution map and humidity distribution map according to the temperature compensation data and the humidity compensation data, and executes a step of determining whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map (step S106 ).

[0078] The above embodiments have the following beneficial effects: Real-time monitoring video technology is used. By analyzing the video images, the system can accurately locate the distribution of each light source and determine whether they will affect the environmental measurement of the experimental area. If the impact is not significant, the original temperature and humidity distribution map can be used directly. However, if the light source interference is serious, the method will automatically adjust the light source to keep it away from the experimental area to eliminate the measurement error. This correction method for light source interference is adaptive and does not require the installation of additional sensors, which greatly simplifies the implementation cost of the system. It ensures the data quality of the temperature and humidity distribution map and provides a reliable basis for environmental judgment in the experimental area.

[0079] By introducing temperature and humidity compensation data, the interference factors of the light source are eliminated in real time during the generation of the distribution map. The system will re-evaluate the impact of the light source on the environmental parameters after the light source is adjusted. If the impact still exists, the actual temperature and humidity data of the light source radiation area are measured, compared with the average level of the clean room, and the corresponding compensation value is calculated. Then these compensation data are substituted into the generation algorithm of the temperature and humidity distribution map to correct the measurement results of the light source area to make it as close as possible to the actual environmental parameters of the experimental area. This compensation strategy is equivalent to superimposing a layer of digital filtering on the basis of the original measurement. The suppression of light source interference is achieved in the post-processing stage through the software algorithm without the need to modify the hardware equipment. It is practical and economical.

[0080] By comparing with the average level of the clean room, the impact of the light source on the experimental area environment is quantitatively evaluated. Among them, the thermal imager is a non-contact infrared imaging device that can monitor the temperature distribution on the surface of an object in real time. By imaging the light source and its surrounding area and combining it with the image processing algorithm, it is possible to identify areas that are significantly higher than the average temperature of the clean room, and then determine whether the thermal radiation of the light source will interfere with the experimental area. Similarly, humidity sensors can be used to monitor humidity in areas near the light source. Through spatial interpolation analysis of a large amount of sensor data, the system can generate a humidity distribution cloud map of the area and identify high humidity areas that may be affected by the air flow disturbance of the light source. Furthermore, this method also considers the spatial superposition effect of the thermal radiation of the light source and the humidity disturbance. Only when the high temperature area and the high humidity area cover the experimental area at the same time, the light source interference is considered significant and position adjustment or compensation processing is required. This judgment logic avoids the one-sided analysis of a single factor and improves the comprehensiveness and accuracy of the light source interference assessment.

[0081] Through the experiment of switching light sources, the change in environmental parameters in the interference area is measured and used as the basis for subsequent correction. Specifically, the system first identifies the area that is significantly affected by the light source. In this area, the temperature and humidity data are measured when the light source is turned on and off respectively. The difference between the two reflects the degree of interference of the light source and can be used as the temperature and humidity compensation. Since the compensation data comes from actual measurements rather than empirical estimates, the reliability and accuracy of its values ​​can be guaranteed. When the temperature and humidity distribution map is generated later, the system will automatically superimpose the compensation amount on the measurement results of the affected area. This is equivalent to a local correction of the distribution map, offsetting the influence of light source interference and making it closer to the actual environmental parameters of the experimental area. In this way, even if the light source interference cannot be completely eliminated by hardware means, the equivalent effect can be achieved through software compensation to maximize the environmental stability of the experimental area.

[0082] Through the light source switch experiment, a series of temperature and humidity distribution images are obtained, and the key difference information is extracted by using image processing technology to determine the spatial distribution of the affected area. First, the system uses thermal imagers, humidity sensors and other equipment to collect real-time temperature and humidity data at the light source position when the light source is turned on and off. After preprocessing such as coordinate mapping and spatial interpolation, these data can generate corresponding temperature maps and humidity maps, which intuitively reflect the distribution of environmental parameters in the area around the light source. Then, by performing difference calculations on the temperature and humidity maps under different states, the degree of influence of the light source switch on the environmental parameters of the area can be quantitatively evaluated. The temperature difference map reflects the thermal radiation effect of the light source, while the humidity difference map reflects its air flow disturbance. By superimposing and analyzing the two difference maps, the spatiotemporal distribution characteristics of the light source interference can be fully characterized. Finally, the system performs binarization processing on the difference map according to the preset temperature and humidity thresholds, and extracts the significant area where the difference exceeds the threshold as the influence area of ​​the light source. The boundary of this area represents the spatial range of the light source interference and can be used for subsequent compensation control.

[0083] The following describes the system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the physical device structure of a clean room temperature and humidity automatic adjustment system provided in an embodiment of the present application.

[0084] It should be noted that Figure 3 The structure of the system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0085] like Figure 3 As shown, the system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through a bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0086] The following components are connected to the I / O interface 305: an input section 306 including a camera, an infrared sensor, etc.; an output section 307 including a liquid crystal display (LCD) and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0087] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0088] It should be noted that the computer-readable medium shown in the embodiment of the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.

[0089] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0090] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the system described in the above embodiment; or may exist independently without being assembled into the system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of a system, the system implements the method provided in the above embodiment.

[0091] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0092] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0093] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0094] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for automatically adjusting the temperature and humidity of a clean room, characterized in that: include: When it is determined that the current environmental parameters of the clean room meet the preset environmental parameters, a real-time monitoring video of the clean room is obtained, wherein the current environmental parameters include an average indoor temperature and an average indoor humidity; Determine the experimental area where the experimenter is located according to the real-time monitoring video; Obtaining a temperature distribution map and a humidity distribution map of the experimental area, and judging whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map; If the experimental temperatures are not the same, determining a temperature control device for controlling the temperature of the experimental area; Sending a first instruction to the temperature control device to enable the temperature control device to control the experimental temperature to be the same as the indoor average temperature; Determining whether the experimental humidity of the experimental areas is the same according to the humidity distribution diagram; If the experimental humidity is not the same, determining a humidity control device for controlling the humidity of the experimental area; Sending a second instruction to the humidity control device to enable the humidity control device to control the experimental humidity to be the same as the indoor average humidity; If the experimental temperature is the same and the experimental humidity is the same, each temperature control device and humidity control device is controlled to maintain current operating parameters.

2. The method according to claim 1, characterized in that The step of obtaining a temperature distribution map and a humidity distribution map of the experimental area, and determining whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map, specifically includes: Determine the light source distribution, the temperature distribution map and the humidity distribution map of the experimental area according to the real-time monitoring video; Determining whether the light source of the clean room affects the temperature distribution diagram and the humidity distribution diagram according to the light source distribution; If not, executing the step of determining whether the experimental temperatures of the experimental areas are the same according to the temperature distribution diagram; If so, adjust the light source so that it leaves the experimental area.

3. The method according to claim 2, characterized in that After adjusting the light source so that the light source leaves the experimental area if affected, the method further includes: After adjusting the light source, determining an adjusted light source distribution after adjustment; Determining whether the adjustment of light source distribution affects the temperature distribution map and the humidity distribution map; If not, executing the step of determining whether the experimental temperatures of the experimental areas are the same according to the temperature distribution diagram; If so, determining the temperature compensation data and humidity compensation data of the experimental area; An updated temperature distribution map and humidity distribution map are determined according to the temperature compensation data and the humidity compensation data, and the step of judging whether the experimental temperatures of the experimental areas are the same according to the temperature distribution map is performed.

4. The method according to claim 2, characterized in that: The determining, according to the light source distribution, whether the light source of the clean room affects the temperature distribution diagram and the humidity distribution diagram specifically includes: Receiving temperature data detected by a thermal imager within a preset range of the light source position, wherein the light source distribution includes the light source position; Determine a high temperature area where the temperature data is different from the indoor average temperature; Determine whether the high temperature area has an overlapping area that overlaps with the experimental area, if so, the light source of the clean room affects the temperature distribution map, and if not, the light source of the clean room does not affect the temperature distribution map; Receiving humidity data within a preset range of the light source position detected by a humidity sensor; determining a high humidity area where the humidity data is different from the indoor average humidity; It is determined whether the overlapping area exists in the high humidity area. If so, the light source of the clean room affects the humidity distribution diagram. If not, the light source of the clean room does not affect the humidity distribution diagram.

5. The method according to claim 3, characterized in that: If the experiment area is affected, the temperature compensation data and humidity compensation data of the experiment area are determined, which specifically includes: Determine the impact area of ​​the experimental area caused by adjusting the light source distribution; Measuring the temperature affected by turning on the light source and the humidity affected by turning on the light source in the affected area; Controlling the light source to be turned off, and measuring the light source turned off temperature and the light source turned off humidity of the affected area; The difference between the temperature affected by turning on the light source and the temperature affected by turning off the light source is determined as temperature compensation data; the difference between the humidity affected by turning on the light source and the humidity affected by turning off the light source is determined as humidity compensation data.

6. The method according to claim 5, characterized in that: The determining the impact area of ​​the experimental area caused by adjusting the light source distribution specifically includes: Receiving real-time turn-on temperature data and real-time turn-on humidity data of the light source position when the light source is in the turn-on state; Receiving real-time closing temperature data and real-time closing humidity data of the light source position when the light source is in a closed state; Generate an opening temperature graph, an opening humidity graph, a closing temperature graph and a closing humidity graph according to the real-time opening temperature data, the real-time opening humidity data, the real-time closing temperature data and the real-time closing humidity data respectively; The opening temperature map and the closing temperature map, and the opening humidity map and the closing humidity map are compared to obtain an impact area where the temperature difference is greater than a preset temperature threshold and the humidity difference is greater than a preset humidity threshold.

7. The method according to claim 1, characterized in that After sending a second instruction to the humidity control device to enable the humidity control device to control the experimental humidity to be the same as the indoor average humidity, the method further includes: If the experimental temperature is not equal to the indoor average temperature when the temperature control device operates at any power, or if the experimental humidity is not equal to the indoor average humidity when the humidity control device operates at any power, the control alarm device issues a preset alarm message.

8. A clean room temperature and humidity automatic adjustment system, characterized in that: The system comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the system to execute the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a system, the system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a system, the system is caused to execute the method according to any one of claims 1 to 7.

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