Large central air conditioner AI intelligent control method and system

Abstract

The invention discloses a large central air conditioner AI intelligent control method and system, and relates to the technical field of large central air conditioner AI intelligent control. The system comprises a central air conditioner data acquisition module, a central air conditioner data processing module, a central air conditioner data analysis module and a central air conditioner execution module. The central air conditioner data acquisition module acquires Freon data, real-time outdoor weather data of carbon dioxide concentration and real-time indoor environment data by utilizing a Freon detector, a carbon dioxide collector, a weather forecast system and a sensor; the central air conditioner data processing module obtains a Freon concentration summary sheet, a carbon dioxide concentration curve graph, an outdoor weather data display platform and a climate self-adaptive mode of the system according to the processed and collected data; the central air conditioner data analysis module analyzes the processed data and transmits an abnormal signal to the central air conditioner execution module; and the central air conditioner execution module receives the abnormal signal and takes measures to deal with the abnormity.

Description

Technical Field

[0001] The present invention relates to the technical field of AI intelligent control of large central air conditioners, and specifically to an AI intelligent control method and system for large central air conditioners. Background Art

[0002] The AI ​​intelligent control method and system for large central air conditioners is an innovative solution that integrates cutting-edge technology and intelligent management. The system uses high-sensitivity sensors throughout the building to collect environmental data in real time and transmit it to the central processor through a high-speed network. Based on deep learning algorithms, the AI ​​system can intelligently analyze this data, predict user needs, and automatically adjust the air conditioner working mode to achieve precise temperature control and energy-saving optimization. In addition, the system also has learning capabilities and can continuously optimize control strategies based on user habits to provide a more personalized comfort experience. In short, the AI ​​intelligent control method and system for large central air conditioners is gradually becoming the mainstream trend of modern building environmental control with its intelligent, adaptive and efficient energy-saving characteristics. Although the existing large-scale central air-conditioning AI intelligent control methods and systems have made great progress, there are still some problems that need to be optimized. Under normal circumstances, the consumption of Freon inside the central air-conditioning is not easy for users to observe, which makes it difficult to find the reason why the central air-conditioning does not cool; secondly, when the central air-conditioning is used for a long time in large enclosed spaces and crowded places, the concentration of carbon dioxide produced by human breathing increases, causing users to have hypoxia symptoms such as dizziness, drowsiness, and even fainting; in addition, when the central air-conditioning AI intelligent control system is used in areas with frequent extreme weather, it cannot automatically adjust the parameters of the central air-conditioning according to real-time weather changes, causing the indoor environment to make users feel uncomfortable. If the human body is in an uncomfortable environment for a long time, it will pose a threat to its health. Summary of the invention

[0003] In order to solve the above problems, the present invention provides a large-scale central air-conditioning AI intelligent control system, including a central air-conditioning data acquisition module, a central air-conditioning data processing module, a central air-conditioning data analysis module and a central air-conditioning execution module; The central air conditioning data acquisition module obtains the freon data in the central air conditioning equipment through the freon detector; uses the carbon dioxide collector to obtain the indoor carbon dioxide concentration; the central air conditioning AI intelligent control system wirelessly connects to the weather forecast system, obtains the real-time outdoor weather data of the central air conditioning application area through data entry, and uses the internal sensors of the air conditioning system to obtain real-time indoor environment data; The central air conditioning data processing module converts the electrical signal carrying the Freon data into a digital signal and inputs it into the computer to obtain the Freon concentration data, and obtains the Freon concentration summary table; obtains the carbon dioxide concentration curve through the collected carbon dioxide concentration data; obtains the outdoor weather data display platform and the system climate adaptive mode through the real-time outdoor weather data and indoor environment data of the central air conditioning application area; The central air conditioning data analysis module analyzes the Freon concentration summary table, the carbon dioxide concentration curve chart and the outdoor weather data display platform, and transmits abnormal signals in the analysis results to the central air conditioning execution module; The central air conditioning execution module receives the abnormal signal and takes corresponding measures to deal with the abnormality.

[0004] Furthermore, the process of the central air conditioning data acquisition module acquiring the freon data in the central air conditioning equipment, the indoor carbon dioxide concentration, the real-time outdoor weather data and indoor environmental data of the central air conditioning application area includes: The Freon detector has built-in infrared sensors and photoelectric detectors. The infrared sensor emits infrared light of a specific wavelength to penetrate the Freon gas. Freon absorbs specific infrared light. The higher the Freon concentration, the more significant the weakening of the light intensity. The photoelectric detector receives the weakened infrared light. The photosensitive material in the photoelectric detector generates electron-hole pairs through the photoelectric effect. Under the action of the electric field, the electrons and holes separate and move in opposite directions to form a photocurrent. The photocurrent flows through the load resistor to generate a voltage drop. The greater the intensity of the electrical signal, the higher the Freon concentration. The electrical signal carrying the Freon concentration information is obtained. The carbon dioxide collector has built-in infrared sensors, narrowband filters, infrared detectors and microprocessors. The infrared sensor emits infrared light to penetrate the indoor space. The narrowband filter selects infrared light with characteristic absorption wavelengths of carbon dioxide to pass through. The carbon dioxide in the indoor space absorbs infrared light. The higher the carbon dioxide concentration, the more significant the weakening of light intensity. The infrared detector receives the weakened infrared light and converts the light intensity of the infrared light into an electrical signal. The electrical signal is then input into the microprocessor to amplify and filter the signal. The carbon dioxide concentration value is calculated using the built-in algorithm and lookup table of the microprocessor. The central air-conditioning AI intelligent control system has a built-in WIFI module, which searches for the WIFI network connected to the application area. The central air-conditioning AI intelligent control system sends data requests to the weather forecast system at the same time interval. After receiving the request, the weather forecast system responds to the request and transmits the real-time outdoor weather data to the central air-conditioning AI intelligent control system through the WIFI network. The central air-conditioning AI intelligent control system parses the weather data, converts it into a format that the system can recognize, and obtains the real-time outdoor weather data of the application area through data entry; the internal sensors of the air-conditioning system are used to collect real-time indoor environmental data, and the temperature sensor, humidity sensor, wind speed sensor and air pressure sensor are used to collect indoor temperature data, humidity data, wind speed data and air pressure data to obtain real-time indoor environmental data.

[0005] Furthermore, the process of obtaining the Freon concentration summary table by the central air conditioning data processing module includes: The analog electrical signal carrying the Freon data is input into the ADC analog-to-digital converter, and converted into a digital signal through sampling, quantization and encoding. The digital signal is then input into a computer, and the computer decodes the received digital signal to obtain the Freon concentration data, draws a summary table of the Freon collection time-Freon concentration, fills the Freon concentration data into the summary table, and obtains the Freon concentration summary table.

[0006] Furthermore, the process of obtaining the carbon dioxide concentration curve diagram by the central air conditioning data processing module includes: A two-dimensional coordinate system is established, with the horizontal axis representing time and the vertical axis representing carbon dioxide concentration. The collected carbon dioxide concentration is mapped to the coordinate system to obtain a carbon dioxide concentration curve graph.

[0007] Furthermore, the process of the central air conditioning data processing module acquiring the outdoor weather data display platform and the system climate adaptive mode includes: The real-time outdoor weather data and indoor environmental data are cleaned, formatted and cached, and the existing weather data display platform is called. Responsive front-end technology is used to switch the device and adjust the screen size. The user interface is designed, and dynamic charts and animation effects are used to display the changing trend of outdoor weather data. A back-end server is established to store and process outdoor weather data, and the real-time data update mechanism is improved. Functional testing, performance testing and security testing are then performed on the display platform functions, and vulnerabilities are fixed during the testing process to obtain an outdoor weather data display platform. The random forest algorithm is used to set random forest parameters. The data set consists of real-time outdoor weather data and real-time indoor environmental data. The data set is divided into a training set, a validation set and a test set. Samples are extracted from the training set for training to obtain a preliminary random forest model. The validation set is input into the random forest model, and the parameters are adjusted to improve the model fit. The test set is then input into the adjusted random forest model to evaluate the model performance, and a climate adaptive algorithm is obtained. The central air-conditioning AI intelligent control system receives the algorithm and obtains the system climate adaptive mode.

[0008] Furthermore, the central air conditioning data analysis module analyzes the Freon concentration summary table, the carbon dioxide concentration curve chart and the outdoor weather data display platform, and transmits the abnormal signal in the analysis result to the central air conditioning execution module, including: According to the Freon concentration suitable range when the central air conditioner is running is 3kg~5kg, according to the Freon concentration summary table, when the Freon concentration is 3kg~5kg, the central air conditioner operates normally, when the Freon concentration is lower than 3kg, the insufficient Freon concentration leads to insufficient refrigerant pressure, and the cooling effect of the central air conditioner deteriorates, when the Freon concentration is higher than 5kg, it may cause Freon leakage and the central air conditioner operation load to increase, and the cooling effect deteriorates, and the above abnormal signal is transmitted to the central air conditioner execution module; During the user's daily activities, the normal concentration of carbon dioxide is below 1500ppm. When the carbon dioxide concentration is below 1500ppm, the carbon dioxide concentration in the user's environment will not affect the human body. When the carbon dioxide concentration is higher than 1500ppm, the carbon dioxide concentration in the user's environment is too high, which may cause the user to have hypoxia symptoms such as dizziness, drowsiness, or even fainting, and the abnormal signal is transmitted to the central air conditioning execution module; Through the outdoor weather data display platform, real-time weather data and future weather forecasts are analyzed. Combined with real-time indoor environmental data, the central air-conditioning AI intelligent control system uses a climate adaptive algorithm to determine whether the central air-conditioning indoor environmental data conforms to changes in outdoor weather. If it does not conform to changes in outdoor weather, the abnormal signal is transmitted to the central air-conditioning execution module.

[0009] Furthermore, the central air conditioning execution module receives an abnormal signal and takes corresponding measures to deal with the abnormality, and the process includes: The central air-conditioning execution module receives the abnormal Freon concentration signal. When the Freon concentration is too low, the central air-conditioning AI intelligent control system is mobilized to send a Freon shortage signal to the client, reminding the maintenance personnel to check and replenish Freon; when the Freon concentration is too high, the central air-conditioning AI intelligent control system is mobilized to adjust the compressor working state and the condenser fan speed, reduce the Freon pressure, and send a Freon concentration too high signal to the client and control the central air-conditioning to automatically shut down, reminding the maintenance personnel to check and discharge excess Freon; The central air conditioning execution module receives the abnormal carbon dioxide concentration signal and mobilizes the central air conditioning AI intelligent control system to start the intelligent exhaust function to discharge the high concentration of carbon dioxide outdoors; The central air-conditioning execution module receives abnormal signals indicating that the indoor and outdoor environments are not in compliance, and mobilizes the central air-conditioning AI intelligent control system to switch to the system climate adaptive mode. When the outdoor temperature rises and the indoor temperature is too low, the central air-conditioning AI intelligent control system appropriately increases the cooling degree. When the outdoor humidity increases and the indoor humidity is too high, the central air-conditioning AI intelligent control system strengthens the dehumidification function.

[0010] Furthermore, a large central air conditioner AI intelligent control method is characterized by comprising the following steps: S1. Use the Freon detector and the carbon dioxide collector to obtain Freon data and carbon dioxide concentration respectively. The central air-conditioning AI intelligent control system is wirelessly connected to the weather forecast system, data entry is used to obtain real-time outdoor weather data, and the internal sensors of the air-conditioning system are called to obtain real-time indoor environment data; S2. Process the acquired Freon data and carbon dioxide concentration to obtain a Freon concentration summary table and a carbon dioxide concentration curve chart, process the real-time outdoor weather data to obtain an outdoor weather data display platform, and combine the indoor environment data to obtain a system climate adaptive model through the random forest method; S3, analyzing the Freon concentration summary table, the carbon dioxide concentration curve chart and the outdoor weather data display platform, and transmitting the abnormal signals in the analysis results to the central air conditioning execution module; S4. Receive abnormal signals and take corresponding measures to deal with the abnormalities.

[0011] Beneficial effects of the present invention: Compared with the traditional large-scale central air-conditioning AI intelligent control method and system, the large-scale central air-conditioning AI intelligent control method and system of the present invention is closely integrated with the central air-conditioning AI intelligent control technology in the system described in the present invention and modern information technology, integrating a variety of sensor technologies, infrared sensing technologies, wireless transmission technologies and data entry technologies, accurately capturing Freon concentration data, carbon dioxide concentration data and real-time outdoor weather data and indoor environmental data in the central air-conditioning application area, and through random forest algorithm and big data analysis technology, achieving real-time and comprehensive monitoring of the large-scale central air-conditioning AI intelligent control system, through the Freon concentration summary table, carbon dioxide concentration curve, outdoor weather data display platform and system climate adaptive model obtained after data processing The method can analyze the concentration of Freon, carbon dioxide and the adaptability of outdoor weather to indoor environment in real time during the operation of central air-conditioning, monitor anomalies in real time, and respond to anomalies generated during the operation of the system in a timely manner. It solves the problems that it is difficult to find the cause of the central air-conditioning failure to cool, human breathing in indoor spaces increases the concentration of carbon dioxide, causing user discomfort, and the central air-conditioning AI intelligent control system cannot automatically adjust according to real-time weather changes when applied in areas with frequent extreme weather. It ensures that the method in the present invention can refine the dynamic monitoring standards of large-scale central air-conditioning AI intelligent control systems within a more precise range, so that the monitored data becomes a more accurate indicator under the same conditions. The development and application of this method have significantly enhanced the degree of intelligence in the working process of large-scale central air-conditioning AI intelligent control systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a block diagram of a large central air-conditioning AI intelligent control system; Figure 2 The figure is a flow chart of an AI intelligent control method for large central air conditioners. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] like Figure 1 and Figure 2 As shown, the present invention provides a technical solution: a large central air-conditioning AI intelligent control system, including a central air-conditioning data acquisition module, a central air-conditioning data processing module, a central air-conditioning data analysis module and a central air-conditioning execution module; The central air-conditioning data acquisition module uses a Freon detector to obtain Freon data in the central air-conditioning equipment; uses a carbon dioxide collector to obtain indoor carbon dioxide concentration; the central air-conditioning AI intelligent control system is wirelessly connected to the weather forecast system to obtain real-time outdoor weather data in the central air-conditioning application area through data entry, and uses the internal sensors of the air-conditioning system to obtain real-time indoor environment data; The central air conditioning data processing module converts the electrical signal carrying the Freon data into a digital signal and inputs it into the computer to obtain the Freon concentration data and obtain the Freon concentration summary table; obtains the carbon dioxide concentration curve through the collected carbon dioxide concentration data; obtains the outdoor weather data display platform and the system climate adaptive mode through the real-time outdoor weather data and indoor environment data of the central air conditioning application area; The central air conditioning data analysis module analyzes the Freon concentration summary table, carbon dioxide concentration curve chart and outdoor weather data display platform, and transmits abnormal signals in the analysis results to the central air conditioning execution module; The central air conditioning execution module receives abnormal signals and takes corresponding measures to deal with the abnormalities.

[0015] The central air conditioning data acquisition module acquires the freon data in the central air conditioning equipment, the indoor carbon dioxide concentration, the real-time outdoor weather data and indoor environmental data of the central air conditioning application area, including: The Freon detector has built-in infrared sensors and photoelectric detectors. The infrared sensor emits infrared light of a specific wavelength to penetrate the Freon gas. Freon absorbs specific infrared light. The higher the Freon concentration, the more significant the weakening of the light intensity. The photoelectric detector receives the weakened infrared light. The photosensitive material in the photoelectric detector generates electron-hole pairs through the photoelectric effect. Under the action of the electric field, the electrons and holes separate and move in opposite directions to form a photocurrent. The photocurrent flows through the load resistor to generate a voltage drop. The greater the intensity of the electrical signal, the higher the Freon concentration. The electrical signal carrying the Freon concentration information is obtained. The carbon dioxide collector has built-in infrared sensors, narrowband filters, infrared detectors and microprocessors. The infrared sensor emits infrared light to penetrate the indoor space. The narrowband filter selects infrared light with characteristic absorption wavelengths of carbon dioxide to pass through. The carbon dioxide in the indoor space absorbs infrared light. The higher the carbon dioxide concentration, the more significant the weakening of light intensity. The infrared detector receives the weakened infrared light and converts the light intensity of the infrared light into an electrical signal. The electrical signal is then input into the microprocessor to amplify and filter the signal. The carbon dioxide concentration value is calculated using the built-in algorithm and lookup table of the microprocessor. The central air-conditioning AI intelligent control system has a built-in WIFI module, which searches for the WIFI network connected to the application area. The central air-conditioning AI intelligent control system sends data requests to the weather forecast system at the same time interval. After receiving the request, the weather forecast system responds to the request and transmits the real-time outdoor weather data to the central air-conditioning AI intelligent control system through the WIFI network. The central air-conditioning AI intelligent control system parses the weather data, converts it into a format that the system can recognize, and obtains the real-time outdoor weather data of the application area through data entry; the internal sensors of the air-conditioning system are used to collect real-time indoor environmental data, and the temperature sensor, humidity sensor, wind speed sensor and air pressure sensor are used to collect indoor temperature data, humidity data, wind speed data and air pressure data to obtain real-time indoor environmental data.

[0016] The process of obtaining the Freon concentration summary table in the central air conditioning data processing module includes: The analog electrical signal carrying the Freon data is input into the ADC analog-to-digital converter, and converted into a digital signal through sampling, quantization and encoding. The digital signal is then input into a computer, and the computer decodes the received digital signal to obtain the Freon concentration data, draws a summary table of the Freon collection time-Freon concentration, fills the Freon concentration data into the summary table, and obtains the Freon concentration summary table.

[0017] The process of obtaining the carbon dioxide concentration curve of the central air conditioning data processing module includes: A two-dimensional coordinate system is established, with the horizontal axis representing time and the vertical axis representing carbon dioxide concentration. The collected carbon dioxide concentration is mapped to the coordinate system to obtain a carbon dioxide concentration curve graph.

[0018] The central air conditioning data processing module obtains the outdoor weather data display platform and the system climate adaptive mode process including: The real-time outdoor weather data and indoor environmental data are cleaned, formatted and cached, and the existing weather data display platform is called. Responsive front-end technology is used to switch the device and adjust the screen size. The user interface is designed, and dynamic charts and animation effects are used to display the changing trend of outdoor weather data. A back-end server is established to store and process outdoor weather data, and the real-time data update mechanism is improved. Functional testing, performance testing and security testing are then performed on the display platform functions, and vulnerabilities are fixed during the testing process to obtain an outdoor weather data display platform. The random forest algorithm is used to set random forest parameters. The data set consists of real-time outdoor weather data and real-time indoor environmental data. The data set is divided into a training set, a validation set and a test set. Samples are extracted from the training set for training to obtain a preliminary random forest model. The validation set is input into the random forest model, and the parameters are adjusted to improve the model fit. The test set is then input into the adjusted random forest model to evaluate the model performance, and a climate adaptive algorithm is obtained. The central air-conditioning AI intelligent control system receives the algorithm and obtains the system climate adaptive mode.

[0019] The central air conditioning data analysis module analyzes the Freon concentration summary table, the carbon dioxide concentration curve and the outdoor weather data display platform, and transmits the abnormal signal in the analysis result to the central air conditioning execution module. The process includes: According to the Freon concentration suitable range when the central air conditioner is running is 3kg~5kg, according to the Freon concentration summary table, when the Freon concentration is 3kg~5kg, the central air conditioner operates normally, when the Freon concentration is lower than 3kg, the insufficient Freon concentration leads to insufficient refrigerant pressure, and the cooling effect of the central air conditioner deteriorates, when the Freon concentration is higher than 5kg, it may cause Freon leakage and the central air conditioner operation load to increase, and the cooling effect deteriorates, and the above abnormal signal is transmitted to the central air conditioner execution module; During the user's daily activities, the normal concentration of carbon dioxide is below 1500ppm. When the carbon dioxide concentration is below 1500ppm, the carbon dioxide concentration in the user's environment will not affect the human body. When the carbon dioxide concentration is higher than 1500ppm, the carbon dioxide concentration in the user's environment is too high, which may cause the user to have hypoxia symptoms such as dizziness, drowsiness, or even fainting, and the abnormal signal is transmitted to the central air conditioning execution module; Through the outdoor weather data display platform, real-time weather data and future weather forecasts are analyzed. Combined with real-time indoor environmental data, the central air-conditioning AI intelligent control system uses a climate adaptive algorithm to determine whether the central air-conditioning indoor environmental data conforms to changes in outdoor weather. If it does not conform to changes in outdoor weather, the abnormal signal is transmitted to the central air-conditioning execution module.

[0020] The central air conditioning execution module receives abnormal signals and takes corresponding measures to deal with the abnormal process, including: The central air-conditioning execution module receives the abnormal Freon concentration signal. When the Freon concentration is too low, the central air-conditioning AI intelligent control system is mobilized to send a Freon shortage signal to the client, reminding the maintenance personnel to check and replenish Freon; when the Freon concentration is too high, the central air-conditioning AI intelligent control system is mobilized to adjust the compressor working state and the condenser fan speed, reduce the Freon pressure, and send a Freon concentration too high signal to the client and control the central air-conditioning to automatically shut down, reminding the maintenance personnel to check and discharge excess Freon; The central air conditioning execution module receives the abnormal carbon dioxide concentration signal and mobilizes the central air conditioning AI intelligent control system to start the intelligent exhaust function to discharge the high concentration of carbon dioxide outdoors; The central air-conditioning execution module receives abnormal signals indicating that the indoor and outdoor environments are not in compliance, and mobilizes the central air-conditioning AI intelligent control system to switch to the system climate adaptive mode. When the outdoor temperature rises and the indoor temperature is too low, the central air-conditioning AI intelligent control system appropriately increases the cooling degree. When the outdoor humidity increases and the indoor humidity is too high, the central air-conditioning AI intelligent control system strengthens the dehumidification function.

[0021] A large central air conditioner AI intelligent control method, characterized by comprising the following steps: S1. Use the Freon detector and the carbon dioxide collector to obtain Freon data and carbon dioxide concentration respectively. The central air-conditioning AI intelligent control system is wirelessly connected to the weather forecast system, data entry is used to obtain real-time outdoor weather data, and the internal sensors of the air-conditioning system are called to obtain real-time indoor environment data; S2. Process the acquired Freon data and carbon dioxide concentration to obtain a Freon concentration summary table and a carbon dioxide concentration curve chart, process the real-time outdoor weather data to obtain an outdoor weather data display platform, and combine the indoor environment data to obtain a system climate adaptive model through the random forest method; S3, analyzing the Freon concentration summary table, the carbon dioxide concentration curve chart and the outdoor weather data display platform, and transmitting the abnormal signals in the analysis results to the central air conditioning execution module; S4. Receive abnormal signals and take corresponding measures to deal with the abnormalities.

[0022] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions. The sentence "includes an element defined by ... does not exclude the existence of other identical elements in the process, method, article or device including the element".

[0023] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A large-scale central air-conditioning AI intelligent control system, comprising a central air-conditioning data acquisition module, a central air-conditioning data processing module, a central air-conditioning data analysis module and a central air-conditioning execution module, characterized in that: The central air conditioning data acquisition module obtains the freon data in the central air conditioning equipment through the freon detector; uses the carbon dioxide collector to obtain the indoor carbon dioxide concentration; the central air conditioning AI intelligent control system wirelessly connects to the weather forecast system, obtains the real-time outdoor weather data of the central air conditioning application area through data entry, and uses the internal sensors of the air conditioning system to obtain real-time indoor environment data; The central air conditioning data processing module converts the electrical signal carrying the Freon data into a digital signal and inputs it into the computer to obtain the Freon concentration data, and obtains the Freon concentration summary table; obtains the carbon dioxide concentration curve through the collected carbon dioxide concentration data; obtains the outdoor weather data display platform and the system climate adaptive mode through the real-time outdoor weather data and indoor environment data of the central air conditioning application area; The central air conditioning data analysis module analyzes the Freon concentration summary table, the carbon dioxide concentration curve chart and the outdoor weather data display platform, and transmits abnormal signals in the analysis results to the central air conditioning execution module; The central air conditioning execution module receives the abnormal signal and takes corresponding measures to deal with the abnormality.

2. According to claim 1, a large central air-conditioning AI intelligent control system is characterized by: The process of the central air conditioning data acquisition module acquiring the freon data in the central air conditioning equipment, the indoor carbon dioxide concentration, the real-time outdoor weather data and the indoor environment data of the central air conditioning application area includes: The Freon detector has built-in infrared sensors and photoelectric detectors. The infrared sensor emits infrared light of a specific wavelength to penetrate the Freon gas. Freon absorbs specific infrared light. The higher the Freon concentration, the more significant the weakening of the light intensity. The photoelectric detector receives the weakened infrared light. The photosensitive material in the photoelectric detector generates electron-hole pairs through the photoelectric effect. Under the action of the electric field, the electrons and holes separate and move in opposite directions to form a photocurrent. The photocurrent flows through the load resistor to generate a voltage drop. The greater the intensity of the electrical signal, the higher the Freon concentration. The electrical signal carrying the Freon concentration information is obtained. The carbon dioxide collector has built-in infrared sensors, narrowband filters, infrared detectors and microprocessors. The infrared sensor emits infrared light to penetrate the indoor space. The narrowband filter selects infrared light with characteristic absorption wavelengths of carbon dioxide to pass through. The carbon dioxide in the indoor space absorbs infrared light. The higher the carbon dioxide concentration, the more significant the weakening of light intensity. The infrared detector receives the weakened infrared light and converts the light intensity of the infrared light into an electrical signal. The electrical signal is then input into the microprocessor to amplify and filter the signal. The carbon dioxide concentration value is calculated using the built-in algorithm and lookup table of the microprocessor. The central air-conditioning AI intelligent control system has a built-in WIFI module, which searches for the WIFI network connected to the application area. The central air-conditioning AI intelligent control system sends data requests to the weather forecast system at the same time interval. After receiving the request, the weather forecast system responds to the request and transmits the real-time outdoor weather data to the central air-conditioning AI intelligent control system through the WIFI network. The central air-conditioning AI intelligent control system parses the weather data, converts it into a format that the system can recognize, and obtains the real-time outdoor weather data of the application area through data entry; the internal sensors of the air-conditioning system are used to collect real-time indoor environmental data, and the temperature sensor, humidity sensor, wind speed sensor and air pressure sensor are used to collect indoor temperature data, humidity data, wind speed data and air pressure data to obtain real-time indoor environmental data.

3. A large central air-conditioning AI intelligent control system according to claim 2, characterized in that: The process of obtaining the Freon concentration summary table by the central air conditioning data processing module includes: The analog electrical signal carrying the Freon data is input into the ADC analog-to-digital converter, and converted into a digital signal through sampling, quantization and encoding. The digital signal is then input into a computer, and the computer decodes the received digital signal to obtain the Freon concentration data, draws a summary table of the Freon collection time-Freon concentration, fills the Freon concentration data into the summary table, and obtains the Freon concentration summary table.

4. According to claim 3, a large central air-conditioning AI intelligent control system is characterized in that: The process of obtaining the carbon dioxide concentration curve diagram by the central air conditioning data processing module includes: A two-dimensional coordinate system is established, with the horizontal axis representing time and the vertical axis representing carbon dioxide concentration. The collected carbon dioxide concentration is mapped to the coordinate system to obtain a carbon dioxide concentration curve graph.

5. According to claim 4, a large central air-conditioning AI intelligent control system is characterized in that: The process of the central air conditioning data processing module acquiring the outdoor weather data display platform and the system climate adaptive mode includes: The real-time outdoor weather data and indoor environmental data are cleaned, formatted and cached, and the existing weather data display platform is called. Responsive front-end technology is used to switch the device and adjust the screen size. The user interface is designed, and dynamic charts and animation effects are used to display the changing trend of outdoor weather data. A back-end server is established to store and process outdoor weather data, and the real-time data update mechanism is improved. Functional testing, performance testing and security testing are then performed on the display platform functions, and vulnerabilities are fixed during the testing process to obtain an outdoor weather data display platform. The random forest algorithm is used to set random forest parameters. The data set consists of real-time outdoor weather data and real-time indoor environmental data. The data set is divided into a training set, a validation set and a test set. Samples are extracted from the training set for training to obtain a preliminary random forest model. The validation set is input into the random forest model, and the parameters are adjusted to improve the model fit. The test set is then input into the adjusted random forest model to evaluate the model performance, and a climate adaptive algorithm is obtained. The central air-conditioning AI intelligent control system receives the algorithm and obtains the system climate adaptive mode.

6. According to claim 5, a large central air-conditioning AI intelligent control system is characterized in that: The central air conditioning data analysis module analyzes the Freon concentration summary table, the carbon dioxide concentration curve chart and the outdoor weather data display platform, and transmits the abnormal signal in the analysis result to the central air conditioning execution module. The process includes: According to the Freon concentration suitable range when the central air conditioner is running is 3kg~5kg, according to the Freon concentration summary table, when the Freon concentration is 3kg~5kg, the central air conditioner operates normally, when the Freon concentration is lower than 3kg, the insufficient Freon concentration leads to insufficient refrigerant pressure, and the cooling effect of the central air conditioner deteriorates, when the Freon concentration is higher than 5kg, it may cause Freon leakage and the central air conditioner operation load to increase, and the cooling effect deteriorates, and the above abnormal signal is transmitted to the central air conditioner execution module; During the user's daily activities, the normal concentration of carbon dioxide is below 1500ppm. When the carbon dioxide concentration is below 1500ppm, the carbon dioxide concentration in the user's environment will not affect the human body. When the carbon dioxide concentration is higher than 1500ppm, the carbon dioxide concentration in the user's environment is too high, which may cause the user to have hypoxia symptoms such as dizziness, drowsiness, or even fainting, and the abnormal signal is transmitted to the central air conditioning execution module; Through the outdoor weather data display platform, real-time weather data and future weather forecasts are analyzed. Combined with real-time indoor environmental data, the central air-conditioning AI intelligent control system uses a climate adaptive algorithm to determine whether the central air-conditioning indoor environmental data conforms to changes in outdoor weather. If it does not conform to changes in outdoor weather, the abnormal signal is transmitted to the central air-conditioning execution module.

7. A large central air-conditioning AI intelligent control system according to claim 6, characterized in that: The central air conditioning execution module receives an abnormal signal and takes corresponding measures to deal with the abnormality, and the process includes: The central air-conditioning execution module receives the abnormal Freon concentration signal. When the Freon concentration is too low, the central air-conditioning AI intelligent control system is mobilized to send a Freon shortage signal to the client, reminding the maintenance personnel to check and replenish Freon; when the Freon concentration is too high, the central air-conditioning AI intelligent control system is mobilized to adjust the compressor working state and the condenser fan speed, reduce the Freon pressure, and send a Freon concentration too high signal to the client and control the central air-conditioning to automatically shut down, reminding the maintenance personnel to check and discharge excess Freon; The central air conditioning execution module receives the abnormal carbon dioxide concentration signal and mobilizes the central air conditioning AI intelligent control system to start the intelligent exhaust function to discharge the high concentration of carbon dioxide outdoors; The central air-conditioning execution module receives abnormal signals indicating that the indoor and outdoor environments are not in compliance, and mobilizes the central air-conditioning AI intelligent control system to switch to the system climate adaptive mode. When the outdoor temperature rises and the indoor temperature is too low, the central air-conditioning AI intelligent control system appropriately increases the cooling degree. When the outdoor humidity increases and the indoor humidity is too high, the central air-conditioning AI intelligent control system strengthens the dehumidification function.

8. A large central air conditioner AI intelligent control method, characterized by: It consists of the following steps: S1. Use the Freon detector and the carbon dioxide collector to obtain Freon data and carbon dioxide concentration respectively. The central air-conditioning AI intelligent control system is wirelessly connected to the weather forecast system, data entry is used to obtain real-time outdoor weather data, and the internal sensors of the air-conditioning system are called to obtain real-time indoor environment data; S2. Process the acquired Freon data and carbon dioxide concentration to obtain a Freon concentration summary table and a carbon dioxide concentration curve chart, process the real-time outdoor weather data to obtain an outdoor weather data display platform, and combine the indoor environment data to obtain a system climate adaptive model through the random forest method; S3, analyzing the Freon concentration summary table, the carbon dioxide concentration curve chart and the outdoor weather data display platform, and transmitting the abnormal signals in the analysis results to the central air conditioning execution module; S4. Receive abnormal signals and take corresponding measures to deal with the abnormalities.

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