Intelligent production control system for dark tea extract

Abstract

The invention discloses a dark tea extract intelligent production control system, and relates to the technical field of plant extraction, the system comprises a data acquisition and monitoring module, an intelligent control module, an analysis optimization module and a visualization module; the data acquisition and monitoring module acquires environmental data and eurotium cristatum growth data in real time; the intelligent control module automatically adjusts the temperature, the humidity and the oxygen concentration in the fermentation process based on the environmental data and the eurotium cristatum growth data; the analysis and optimization module predicts and adjusts production conditions in real time by using a neural network and an optimization model; the visualization module provides real-time monitoring and remote operation functions through a graphical user interface, so that an operator can monitor the state of the system in real time. According to the method, the growth environment of eurotium cristatum can be accurately controlled, the fermentation and extraction processes are optimized, the quality consistency and production efficiency of dark green tea are improved, and the problems of quality fluctuation and inaccurate control in a traditional production method are solved.

Description

Technical Field

[0001] The invention relates to the technical field of plant extraction, and in particular to an intelligent production control system for a dark tea extract. Background Art

[0002] Dark tea is a post-fermented tea, a unique type of tea in my country. It is produced in Sichuan, Yunnan, Hunan, Hubei and other places, and has a long history and rich cultural connotations. It uses a unique fermentation process and pressing method. After multiple aging, the quality of the tea is improved. The role of the special microorganism "Golden Flower Fungus" is utilized in the fermentation process of dark tea, such as Fuzhuan Tea and Jinhua Tibetan Tea. The Golden Flower Fungus reproduces under a specific temperature and humidity environment and forms golden flowers in the tea leaves, which improves the taste, aroma and health components of the tea leaves. The presence of the Golden Flower Fungus gives Fuzhuan Tea, Jinhua Tibetan Tea and other dark teas a unique flavor and health-care effect, making them an important category of dark tea.

[0003] At present, the production of Fuzhuan tea still mainly relies on traditional technology, and the control of golden flower fungi during the fermentation process relies more on manual experience. Although the role of golden flower fungi in tea is very important, since its growth is affected by environmental factors such as temperature, humidity, and oxygen concentration, traditional manual control often leads to the inability to stably control environmental conditions during the production process, which in turn affects the quality and stability of Fuzhuan tea. In addition, in the existing Fuzhuan tea production, the cultivation of golden flower fungi and the adjustment of fermentation conditions lack an accurate intelligent monitoring system, which makes it difficult to accurately match the growth state and fermentation conditions of golden flower fungi during each fermentation process, affecting the consistency of the product and the standardization of quality. These problems are particularly prominent in the mass production process of Fuzhuan tea, and effective technical means are needed to solve them.

[0004] In view of the above problems, the present invention provides an intelligent production control system for black tea extract, which aims to accurately control the fermentation and extraction process in the production process of Fuzhuan tea through intelligent means. Through systematic environmental data collection and monitoring, intelligent control, real-time optimization and other technologies, the present invention can accurately adjust the growth environment of golden flower fungi, automatically adjust environmental factors such as temperature, humidity, and oxygen concentration during the fermentation process, ensure that golden flower fungi grow under optimal conditions, and thus improve the quality consistency and stability of Fuzhuan tea. Summary of the invention

[0005] In view of the above problems, the present invention provides an intelligent production control system for black tea extract to solve the problems of inaccurate control of the growth environment of golden flower fungus and difficulty in standardization of the fermentation and extraction processes in the prior art of Fuzhuan tea production.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent production control system for black tea extract, comprising: A data acquisition module, which is used to collect environmental data and golden flower fungus growth data during the production process in real time, wherein the environmental data includes temperature, humidity, and oxygen concentration, and the golden flower fungus growth data includes parameters related to its growth status; An intelligent control module, which is connected to the data acquisition module and automatically controls the temperature, humidity, and oxygen concentration of the fermentation process, as well as the temperature, pressure, and extraction time of the extraction process based on the collected environmental data and the growth data of the golden flower fungus; An analysis and optimization module, which is connected to the data acquisition module and the intelligent control module, and uses a neural network and an optimization model to analyze and predict production conditions based on historical data, environmental data, and golden flower fungus growth data, analyze the extract components after each round of extraction, and adjust subsequent extraction conditions based on the analysis results; An extract quality control module, which interacts with the data acquisition module. After each round of extraction, the extract quality is analyzed based on the environmental data and the growth data of the golden flower fungus, and the extraction conditions are adjusted according to the analysis results; The visualization module is connected to each module and enables the operator to monitor the system status in real time and display environmental data and golden flower bacteria growth data through a graphical user interface. The operator can remotely control the system through a cloud platform and receive real-time data and analysis results to adjust the production process.

[0007] The data acquisition module includes: an environmental data acquisition unit, a golden flower fungus growth data acquisition unit and a data transmission unit; The environmental data acquisition unit collects environmental data related to the production process in real time through a temperature sensor, a humidity sensor and an oxygen concentration sensor, wherein the environmental data includes temperature, humidity and oxygen concentration; The golden flower fungus growth data acquisition unit collects and monitors the growth data of the golden flower fungus through a microscopic imaging system and image recognition technology, wherein the growth data of the golden flower fungus includes morphology, quantity and growth rate; The data transmission unit transmits the collected environmental data and golden flower fungus growth data to the central control system in real time through the wireless sensor network, and stores them in the cloud platform for data backup; the central control system is responsible for receiving real-time data from the data acquisition and monitoring module, analyzing the current production status, coordinating the intelligent control module to adjust the control conditions of the fermentation process and the extraction process according to data feedback, and monitoring and scheduling the operation status of each module.

[0008] The intelligent control module includes: a fermentation process control unit, an extraction process control unit and a data feedback unit; The fermentation process control unit automatically adjusts the environmental conditions in the fermentation process by receiving the temperature, humidity, and oxygen concentration data provided by the environmental data acquisition unit; based on the real-time temperature data, the temperature in the fermentation process is adjusted using a Gaussian temperature-dependent model to obtain the target growth rate of the golden flower fungus, as shown in the formula: in, For temperature The growth rate of golden flower fungus under is the maximum growth rate, is the actual temperature, is the optimal growth temperature of golden flower fungus. To control the rate at which the growth rate decreases as the temperature deviates from the optimal value; The extraction process control unit adjusts the temperature, pressure and extraction time during the extraction process according to the data provided by the environmental data acquisition unit and the golden flower fungus growth data acquisition unit; The data feedback unit automatically adjusts the environmental control and extraction conditions in the production process according to the data provided by the environmental data collection unit and the golden flower fungus growth data collection unit, and feeds back the data to the central control system to update the control parameters in the fermentation and extraction process.

[0009] The analysis and optimization module includes: a data analysis unit, a production parameter prediction unit and an adjustment control unit; The data analysis unit receives the environmental data and the growth data of the golden flower fungus from the data acquisition and monitoring module, and the control parameters provided by the intelligent control module, and uses the Monod model to analyze the relationship between the growth rate of the golden flower fungus and the environmental factors, as shown in the formula: in, is the growth rate, is the maximum growth rate, is the substrate concentration, is the half-saturation constant of substrate concentration; The production parameter prediction unit uses a long short-term memory network and combines the relationship between the growth rate of golden flower fungus and environmental factors analyzed by the data analysis unit to obtain predicted production parameters, which will guide the control conditions in the fermentation process and the extraction process; The adjustment control unit dynamically adjusts the control parameters through a state space model, and the model consists of the following parts: System Status : Specifically, the data of the environmental data acquisition unit and the golden flower fungus growth data acquisition unit; Control Input : Environmental adjustment instructions, which are specifically control parameters of the data feedback unit; Output : Extract quality index; According to the current state and control input, the state at the next moment is predicted by the state equation, as shown in the formula: in, is the state at the next moment, is the system status, is the control input, is the actual output, , , , is the system matrix; Combined with the quality objective function, the model predictive control algorithm is used to generate control instructions to adjust the fermentation and extraction conditions in real time. The quality objective function is shown in the formula: in, is the quality objective function, To actually measure the concentration of target ingredients, including caffeine and tea polyphenols, To estimate the target component concentration; compare the actual production data with the predicted results, and update the model parameter matrix through the least squares method.

[0010] The extract quality control module includes: a quality analysis unit, a data comparison unit and a process adjustment unit; The quality analysis unit analyzes the target components in the extract in real time and evaluates the quality of the extract by receiving the control parameters provided by the intelligent control module; The data comparison unit compares the quality data of the extract with a preset quality standard according to the analysis result provided by the quality analysis unit. The quality standard is a quality benchmark set according to the concentration, purity and stability factors of the target components of the extract to determine whether the extract meets the quality requirements. If the data deviates from the standard, an alarm will be generated and adjustment suggestions will be provided. The adjustment suggestions include adjusting the temperature, pressure and extraction time; The process adjustment unit adjusts the control parameters in the intelligent control module, including extraction time, temperature, and pressure, based on the gradient descent method according to the comparison result of the data comparison unit, to ensure that various indicators in the extraction process meet the specified quality standards, as shown in the formula: in, is the updated control parameter, is the current control parameter, is the learning rate, is the gradient of the objective function with respect to the control parameters.

[0011] The visualization module includes: a data display unit, a remote control unit and a real-time monitoring unit; The data display unit displays various environmental data and extraction process parameters in the production process, including temperature, humidity, oxygen concentration, extraction time and pressure, by receiving real-time data provided by the data acquisition and monitoring module and the analysis and optimization module, and displays them in a graphical manner so that operators can understand the production status in real time; The remote control unit realizes remote control of the production process through the support of the cloud platform and the data transmission unit. The operator can adjust the environment and extract control parameters in the system on the remote device through a graphical interface; The real-time monitoring unit monitors the changes of various data in the production process in real time. If it is found that the parameters exceed the preset range or an abnormality occurs, the operator is notified immediately and corresponding adjustment suggestions or a plan for automatically adjusting the production conditions are provided to ensure that the production process meets the predetermined standards.

[0012] Compared with the prior art, the present invention has the following beneficial effects: The present invention realizes the full intelligent control of the black tea extract production process through the close collaboration of the data acquisition module, the intelligent control module and the analysis and optimization module, and automatically adjusts the key parameters of temperature, humidity, oxygen concentration and pressure in the fermentation and extraction process according to the real-time collected data, thereby significantly improving the accuracy and efficiency of the production process.

[0013] The present invention models the relationship between the growth rate of golden flower fungus and environmental factors through the Monod model, and can adjust the fermentation conditions in real time, so that the golden flower fungus can reproduce under optimal growth conditions, thereby improving the activity of the golden flower fungus and its positive effect on the quality of tea extract. At the same time, based on the prediction of extraction parameters based on the Bayesian optimization algorithm, the conditions for each round of extraction are further optimized to ensure the efficient extraction of target components.

[0014] The present invention uses the gradient descent method to adjust the time, temperature and pressure control parameters in the extraction process in real time, so that each link in the extraction process can maximize the extraction efficiency, avoid insufficient extraction or waste due to lack of experience, and thus ensure the consistency of the extract quality.

[0015] The present invention realizes multi-factor integrated optimization of environmental control and extraction processes through state-space models and real-time feedback units. It can not only adjust control parameters according to real-time data, but also make adjustments according to feedback data at any stage, ensuring that various controls in the production process always meet the set standards and avoiding the impact of environmental fluctuations on product quality.

[0016] The extract quality control module of the present invention combines a quality analysis unit, a data comparison unit and a process adjustment unit. It automatically adjusts the extraction conditions by real-time analysis of the concentrations of tea polyphenols and caffeine components in the extract, thereby providing real-time and automatic quality control and significantly improving the consistency and stability of the extract.

[0017] The visualization module of the present invention provides a graphical user interface that can display various environmental data and extraction parameters in the production process in real time, allowing operators to quickly identify problems and make adjustments. By supporting remote control through the cloud platform, operators can monitor and adjust production conditions in real time anywhere, further improving the flexibility of the system and the ease of operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It is understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 It is a system architecture diagram of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 making creative work belong to the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but is only for selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0021] Please refer to Figure 1 This is a schematic diagram of a dark tea extract intelligent production control system provided by an embodiment of the present invention, comprising: A data acquisition module, which is used to collect environmental data and golden flower fungus growth data during the production process in real time, wherein the environmental data includes temperature, humidity, and oxygen concentration, and the golden flower fungus growth data includes parameters related to its growth status; An intelligent control module, which is connected to the data acquisition module and automatically controls the temperature, humidity, and oxygen concentration of the fermentation process, as well as the temperature, pressure, and extraction time of the extraction process based on the collected environmental data and the growth data of the golden flower fungus; An analysis and optimization module, which is connected to the data acquisition module and the intelligent control module, and uses a neural network and an optimization model to analyze and predict production conditions based on historical data, environmental data, and golden flower fungus growth data, analyze the extract components after each round of extraction, and adjust subsequent extraction conditions based on the analysis results; An extract quality control module, which interacts with the data acquisition module. After each round of extraction, the extract quality is analyzed based on the environmental data and the growth data of the golden flower fungus, and the extraction conditions are adjusted according to the analysis results; The visualization module is connected to each module and enables the operator to monitor the system status in real time and display environmental data and golden flower bacteria growth data through a graphical user interface. The operator can remotely control the system through a cloud platform and receive real-time data and analysis results to adjust the production process.

[0022] The data acquisition module includes: an environmental data acquisition unit, a golden flower fungus growth data acquisition unit and a data transmission unit; The environmental data acquisition unit collects environmental data related to the production process in real time through a temperature sensor, a humidity sensor and an oxygen concentration sensor, wherein the environmental data includes temperature, humidity and oxygen concentration; The golden flower fungus growth data acquisition unit collects and monitors the growth data of the golden flower fungus through a microscopic imaging system and image recognition technology, wherein the growth data of the golden flower fungus includes morphology, quantity and growth rate; The data transmission unit transmits the collected environmental data and golden flower fungus growth data to the central control system in real time through the wireless sensor network, and stores them in the cloud platform for data backup; the central control system is responsible for receiving real-time data from the data acquisition and monitoring module, analyzing the current production status, coordinating the intelligent control module to adjust the control conditions of the fermentation process and the extraction process according to data feedback, and monitoring and scheduling the operation status of each module.

[0023] The intelligent control module includes: a fermentation process control unit, an extraction process control unit and a data feedback unit; The fermentation process control unit automatically adjusts the environmental conditions in the fermentation process by receiving the temperature, humidity, and oxygen concentration data provided by the environmental data acquisition unit; based on the real-time temperature data, the temperature in the fermentation process is adjusted using a Gaussian temperature-dependent model to obtain the target growth rate of the golden flower fungus, as shown in the formula: in, For temperature The growth rate of golden flower fungus under is the maximum growth rate, is the actual temperature, is the optimal growth temperature of golden flower fungus. To control the rate at which the growth rate decreases as the temperature deviates from the optimal value; The extraction process control unit adjusts the temperature, pressure and extraction time during the extraction process according to the data provided by the environmental data acquisition unit and the golden flower fungus growth data acquisition unit; The data feedback unit automatically adjusts the environmental control and extraction conditions in the production process according to the data provided by the environmental data collection unit and the golden flower fungus growth data collection unit, and feeds back the data to the central control system to update the control parameters in the fermentation and extraction process.

[0024] The analysis and optimization module includes: a data analysis unit, a production parameter prediction unit and an adjustment control unit; The data analysis unit receives the environmental data and the growth data of the golden flower fungus from the data acquisition and monitoring module, and the control parameters provided by the intelligent control module, and uses the Monod model to analyze the relationship between the growth rate of the golden flower fungus and the environmental factors, as shown in the formula: in, is the growth rate, is the maximum growth rate, is the substrate concentration, is the half-saturation constant of substrate concentration; The production parameter prediction unit uses a long short-term memory network and combines the relationship between the growth rate of golden flower fungus and environmental factors analyzed by the data analysis unit to obtain predicted production parameters, which will guide the control conditions in the fermentation process and the extraction process; The adjustment control unit dynamically adjusts the control parameters through a state space model, and the model consists of the following parts: System Status : Specifically, the data of the environmental data acquisition unit and the golden flower fungus growth data acquisition unit; Control Input : Environmental adjustment instructions, which are specifically control parameters of the data feedback unit; Output : Extract quality index; According to the current state and control input, the state at the next moment is predicted by the state equation, as shown in the formula: in, is the state at the next moment, is the system status, is the control input, is the actual output, , , , is the system matrix; Combined with the quality objective function, the model predictive control algorithm is used to generate control instructions to adjust the fermentation and extraction conditions in real time. The quality objective function is shown in the formula: in, is the quality objective function, To actually measure the concentration of target ingredients, including caffeine and tea polyphenols, To estimate the target component concentration; compare the actual production data with the predicted results, and update the model parameter matrix through the least squares method.

[0025] It should be noted that the Monod model was originally used to describe the growth rate of microorganisms under changing substrate concentrations. In the traditional Monod model, the growth rate mainly depends on the substrate concentration. However, in the fermentation and growth process of golden flower fungi, in addition to substrate concentration, environmental factors such as temperature, humidity and oxygen concentration also have a significant impact on the growth rate of golden flower fungi. Therefore, the present invention expands the Monod model and models the growth rate in combination with environmental factors, thereby more accurately describing the growth process of golden flower fungi in a dynamic fermentation environment.

[0026] In order to apply the Monod model to the relationship between the growth rate of M. chrysanthemi and environmental factors, it is first necessary to introduce environmental factors as additional influencing variables, assuming that the growth rate of M. chrysanthemi is not only related to the substrate concentration but also to the environmental factors.

[0027] Temperature is an important factor in the growth of microorganisms. The growth rate of golden flower fungi will change significantly at different temperatures. Within a certain temperature range, temperature promotes the growth of golden flower fungi, but when the temperature is too high or too low, the growth rate of the fungi will decrease or even stop growing. Humidity is also a key environmental factor affecting the growth of golden flower fungi. Golden flower fungi have a strong adaptability to humidity, but they can only grow well within a certain humidity range. Too low humidity may cause the fungi to dry out and grow slowly; while too high humidity may also cause problems such as mildew.

[0028] Oxygen concentration is also crucial to the growth of golden flower fungus. Golden flower fungus is an aerobic microorganism that requires sufficient oxygen for metabolism and growth. Too low oxygen concentration will cause the bacteria to grow slowly or even stop growing.

[0029] In actual operation, the system can monitor environmental factors such as temperature, humidity, and oxygen concentration in real time through the data acquisition and monitoring module, and combine it with the substrate concentration data and input it into the extended version of the Monod model to calculate the real-time growth rate of the golden flower fungus. The system adjusts the environmental conditions during the fermentation process based on these real-time data to ensure that the golden flower fungus is fermented under the optimal growth conditions, thereby improving the quality of tea extract.

[0030] The extract quality control module includes: a quality analysis unit, a data comparison unit and a process adjustment unit; The quality analysis unit analyzes the target components in the extract in real time and evaluates the quality of the extract by receiving the control parameters provided by the intelligent control module; The data comparison unit compares the quality data of the extract with a preset quality standard according to the analysis result provided by the quality analysis unit. The quality standard is a quality benchmark set according to the concentration, purity and stability factors of the target components of the extract to determine whether the extract meets the quality requirements. If the data deviates from the standard, an alarm will be generated and adjustment suggestions will be provided. The adjustment suggestions include adjusting the temperature, pressure and extraction time; The process adjustment unit adjusts the control parameters in the intelligent control module, including extraction time, temperature, and pressure, based on the gradient descent method according to the comparison result of the data comparison unit, to ensure that various indicators in the extraction process meet the specified quality standards, as shown in the formula: in, is the updated control parameter, is the current control parameter, is the learning rate, is the gradient of the objective function with respect to the control parameters.

[0031] The visualization module includes: a data display unit, a remote control unit and a real-time monitoring unit; The data display unit displays various environmental data and extraction process parameters in the production process, including temperature, humidity, oxygen concentration, extraction time and pressure, by receiving real-time data provided by the data acquisition and monitoring module and the analysis and optimization module, and displays them in a graphical manner so that operators can understand the production status in real time; The remote control unit realizes remote control of the production process through the support of the cloud platform and the data transmission unit. The operator can adjust the environment and extract control parameters in the system on the remote device through a graphical interface; The real-time monitoring unit monitors the changes of various data in the production process in real time. If it is found that the parameters exceed the preset range or an abnormality occurs, the operator is notified immediately and corresponding adjustment suggestions or a plan for automatically adjusting the production conditions are provided to ensure that the production process meets the predetermined standards.

[0032] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention has various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A dark tea extract intelligent production control system, characterized in that: include: A data acquisition module, which is used to collect environmental data and golden flower fungus growth data during the production process in real time, wherein the environmental data includes temperature, humidity, and oxygen concentration, and the golden flower fungus growth data includes parameters related to its growth status; An intelligent control module, which is connected to the data acquisition module and automatically controls the temperature, humidity, and oxygen concentration of the fermentation process, as well as the temperature, pressure, and extraction time of the extraction process based on the collected environmental data and the growth data of the golden flower fungus; An analysis and optimization module, which is connected to the data acquisition module and the intelligent control module, and uses a neural network and an optimization model to analyze and predict production conditions based on historical data, environmental data, and golden flower fungus growth data, analyze the extract components after each round of extraction, and adjust subsequent extraction conditions based on the analysis results; An extract quality control module, which interacts with the data acquisition module. After each round of extraction, the extract quality is analyzed based on the environmental data and the growth data of the golden flower fungus, and the extraction conditions are adjusted according to the analysis results; The visualization module is connected to each module and enables the operator to monitor the system status in real time and display environmental data and golden flower bacteria growth data through a graphical user interface. The operator can remotely control the system through a cloud platform and receive real-time data and analysis results to adjust the production process.

2. The intelligent production control system of a dark tea extract according to claim 1, characterized in that: The data acquisition module includes: an environmental data acquisition unit, a golden flower fungus growth data acquisition unit and a data transmission unit; The environmental data acquisition unit collects environmental data related to the production process in real time through a temperature sensor, a humidity sensor and an oxygen concentration sensor, wherein the environmental data includes temperature, humidity and oxygen concentration; The golden flower fungus growth data acquisition unit collects and monitors the growth data of the golden flower fungus through a microscopic imaging system and image recognition technology, wherein the growth data of the golden flower fungus includes morphology, quantity and growth rate; The data transmission unit transmits the collected environmental data and golden flower fungus growth data to the central control system in real time through the wireless sensor network, and stores them in the cloud platform for data backup; the central control system is responsible for receiving real-time data from the data acquisition and monitoring module, analyzing the current production status, coordinating the intelligent control module to adjust the control conditions of the fermentation process and the extraction process according to data feedback, and monitoring and scheduling the operating status of each module.

3. The intelligent production control system of a dark tea extract according to claim 1, characterized in that: The intelligent control module includes: a fermentation process control unit, an extraction process control unit and a data feedback unit; The fermentation process control unit automatically adjusts the environmental conditions in the fermentation process by receiving the temperature, humidity, and oxygen concentration data provided by the environmental data acquisition unit; based on the real-time temperature data, the temperature in the fermentation process is adjusted using a Gaussian temperature-dependent model to obtain the target growth rate of the golden flower fungus, as shown in the formula: in, For temperature The growth rate of golden flower fungus under is the maximum growth rate, is the actual temperature, is the optimal growth temperature of golden flower fungus. To control the rate at which the growth rate decreases as the temperature deviates from the optimal value; The extraction process control unit adjusts the temperature, pressure and extraction time during the extraction process according to the data provided by the environmental data acquisition unit and the golden flower fungus growth data acquisition unit; The data feedback unit automatically adjusts the environmental control and extraction conditions in the production process according to the data provided by the environmental data collection unit and the golden flower fungus growth data collection unit, and feeds back the data to the central control system to update the control parameters in the fermentation and extraction process; The central control system is responsible for receiving real-time data from the data acquisition and monitoring module, analyzing the current production status, coordinating the intelligent control module to adjust the control conditions in the fermentation process and the extraction process according to data feedback, and monitoring and scheduling the operating status of each module.

4. The intelligent production control system of dark tea extract according to claim 1, characterized in that: The analysis and optimization module includes: a data analysis unit, a production parameter prediction unit and an adjustment control unit; The data analysis unit receives the environmental data and the growth data of the golden flower fungus from the data acquisition and monitoring module, and the control parameters provided by the intelligent control module, and uses the Monod model to analyze the relationship between the growth rate of the golden flower fungus and the environmental factors, as shown in the formula: in, is the growth rate, is the maximum growth rate, is the substrate concentration, is the half-saturation constant of substrate concentration; The production parameter prediction unit uses a long short-term memory network and combines the relationship between the growth rate of golden flower fungus and environmental factors analyzed by the data analysis unit to obtain predicted production parameters, which will guide the control conditions in the fermentation process and the extraction process; The adjustment control unit dynamically adjusts the control parameters through a state space model, and the model consists of the following parts: System Status : Specifically, the data of the environmental data acquisition unit and the golden flower fungus growth data acquisition unit; Control Input : Environmental adjustment instructions, which are specifically control parameters of the data feedback unit; Output : Extract quality index; According to the current state and control input, the state at the next moment is predicted by the state equation, as shown in the formula: in, is the state at the next moment, is the system status, is the control input, is the actual output, , , , is the system matrix; Combined with the quality objective function, the model predictive control algorithm is used to generate control instructions to adjust the fermentation and extraction conditions in real time. The quality objective function is shown in the formula: in, is the quality objective function, To actually measure the concentration of target ingredients, including caffeine and tea polyphenols, To estimate the target component concentration; compare the actual production data with the predicted results, and update the model parameter matrix through the least squares method.

5. The intelligent production control system of dark tea extract according to claim 1, characterized in that: The extract quality control module includes: a quality analysis unit, a data comparison unit and a process adjustment unit; The quality analysis unit analyzes the target components in the extract in real time and evaluates the quality of the extract by receiving the control parameters provided by the intelligent control module; The data comparison unit compares the quality data of the extract with a preset quality standard according to the analysis result provided by the quality analysis unit. The quality standard is a quality benchmark set according to the concentration, purity and stability factors of the target components of the extract to determine whether the extract meets the quality requirements. If the data deviates from the standard, an alarm will be generated and adjustment suggestions will be provided. The adjustment suggestions include adjusting the temperature, pressure and extraction time; The process adjustment unit adjusts the control parameters in the intelligent control module, including extraction time, temperature, and pressure, based on the gradient descent method according to the comparison result of the data comparison unit, to ensure that various indicators in the extraction process meet the specified quality standards, as shown in the formula: in, is the updated control parameter, is the current control parameter, is the learning rate, is the gradient of the objective function with respect to the control parameters.

6. The intelligent production control system of dark tea extract according to claim 1, characterized in that: The visualization module includes: a data display unit, a remote control unit and a real-time monitoring unit; The data display unit displays various environmental data and extraction process parameters in the production process, including temperature, humidity, oxygen concentration, extraction time and pressure, by receiving real-time data provided by the data acquisition and monitoring module and the analysis and optimization module, and displays them in a graphical manner so that operators can understand the production status in real time; The remote control unit realizes remote control of the production process through the support of the cloud platform and the data transmission unit. The operator can adjust the environment and extract control parameters in the system on the remote device through a graphical interface; The real-time monitoring unit monitors the changes of various data in the production process in real time. If it is found that the parameters exceed the preset range or an abnormality occurs, the operator is notified immediately and corresponding adjustment suggestions or a plan for automatically adjusting the production conditions are provided to ensure that the production process meets the predetermined standards.

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