Real-time clarification system and method for single virus harvest liquid of Vero cells

Abstract

The invention provides a system and a method for clarifying a single virus harvest solution of Vero cells in real time. Belongs to the technical field of biological product production. The method comprises the following steps: assembling and checking the system, and sterilizing the system; controlling the liquid level and starting clarification; filter element selection and parallel arrangement are carried out, and pressure monitoring and filter element switching are carried out; cooling and storing the clarified virus harvesting liquid; online cleaning is conducted, and the cleaning effect is monitored; the clarification process is monitored and recorded in real time; and recording data according to the monitoring system. Through multi-point temperature monitoring and real-time regulation and control, the temperature uniformity in the production process is ensured, adverse effects such as quality reduction of the virus harvesting liquid caused by temperature fluctuation are avoided, and the production safety is improved.

Description

Technical Field

[0001] The present invention provides a real-time clarification system and method for a single virus harvest solution of Vero cells, belonging to the technical field of biological product production. Background Art

[0002] In the large-scale production of biological products using Vero cells, such as the production of rabies vaccines, the clarification of virus harvest solutions is a key step. In the prior art, there are mainly two ways to clarify virus harvest solutions: one is to clarify each container of virus harvest solution separately after collection in a container, and the other is to use an intermediate bottle buffer for real-time clarification. However, both of these methods have obvious defects. The method of clarifying separately after container collection has defects such as too long storage time, unsatisfactory clarification effect, complex operation, and relatively high pollution risk. Since the processing time of the harvest solution during clarification is relatively long, it may cause virus degradation or quality decline, affecting the stability and safety of the final product. In addition, due to the cumbersome operation process, multiple operations and manual interventions are required, which easily introduce pollution risks, thus affecting the aseptic conditions of production.

[0003] Although the method of using an intermediate bottle buffer for real-time clarification can improve the DNA removal effect to a certain extent, it still faces problems such as the need to frequently replace filters and storage containers, increasing production costs and labor costs. Moreover, this method usually requires storing the harvest solution at room temperature, which may cause negative impacts of temperature fluctuations on the quality of the harvest solution, unable to ensure continuous temperature uniformity, and thus affecting the stability of the virus harvest solution and subsequent processing effects. Summary of the Invention

[0004] The present invention provides a real-time clarification method for a single virus harvest solution of Vero cells to solve the problems mentioned in the above background art: A real-time clarification method for a single virus harvest solution of Vero cells proposed by the present invention, the method comprising: S1. Assemble and inspect the system, and sterilize the system; S2. Control the liquid level and start clarification; S3. Select and set filters in parallel, and monitor the pressure and switch filters; S4. Cool and store the clarified virus harvest solution; S5. Perform online cleaning and monitor the cleaning effect; S6. Real-time monitor and record the clarification process; according to the data recorded by the monitoring system.

[0005] A real-time clarification system for a single virus harvest of Vero cells proposed by the present invention includes a memory, a processor, and a computer program stored on the memory and executable on the memory. The processor executes the program to implement a real-time clarification method for a single virus harvest of Vero cells as described in any one of the above.

[0006] Beneficial effects of the present invention: Through real-time temperature control and efficient temperature monitoring technology, the present invention can ensure that the harvest solution maintains a uniform temperature throughout the clarification process, thereby reducing the negative impact of temperature fluctuations on the stability and quality of the virus harvest solution, helping to better preserve the virus harvest solution, ensuring its stability, and improving the quality of the final product; By automatically adjusting the operating parameters of the temperature control module, the dependence on operators is reduced, the complexity of manual operation is lowered, the production efficiency is improved, and the risk of contamination caused by human factors is reduced; By adopting multi-point monitoring and PID control algorithm for precise temperature control, the need for frequent replacement of filters and storage containers can be reduced, the maintenance and replacement costs of equipment during the production process are reduced, and thus the overall production cost is lowered; Through multi-point temperature monitoring and real-time regulation, it helps to ensure the temperature uniformity during the production process, avoids adverse effects such as the reduction of the quality of the virus harvest solution caused by temperature fluctuations, and improves production safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 It is a flowchart of the method steps of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0008] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not intended to limit the present invention.

[0009] An embodiment of the present invention, as Figure 1 shown, a real-time clarification method for a single virus harvest of Vero cells, the method includes: Assemble and inspect the system, including assembling components such as a stainless steel buffer tank, a clarification filter, a harvest tank, a temperature control module, a weighing module, a pressure control module, and a conveying pipeline according to the design requirements, and conduct a comprehensive inspection to ensure that all components are tightly connected and there is no leakage; Before the preparation of the harvest solution starts, perform on-line cleaning (CIP) and sterilization (SIP) treatment on the entire clarification system. Use high-temperature steam to sterilize the inside of the system to ensure a sterile environment and avoid contamination.

[0010] After culturing Vero cells until virus infection, the virus harvest fluid is started to be harvested at a predetermined time (such as 68 hours); the culture fluid of Vero cells after virus infection is collected into a stainless-steel buffer tank by perfusion. An anti-foaming device is designed in the buffer tank to reduce the generation and accumulation of bubbles, preventing bubbles from blocking the filter element and affecting the clarification effect; the liquid level is controlled and clarification is started, including installing high and low liquid level gauges on the buffer tank to real-time feedback the liquid volume in the tank. When the liquid level exceeds the low liquid level, the clarification flow pump is automatically started to start the clarification process; when the liquid level exceeds the high liquid level, the clarification flow pump runs at an accelerated speed to ensure the clarification efficiency; Two parallel three-core clarification filters are used for the clarification filtration of the harvest fluid. Each filter is equipped with a filter element with a retention pore size of 0.8 + 0.65μm to increase the filtration area and improve the clarification efficiency. Pressure gauges are installed before and after the clarification filter to real-time monitor the filter element pressure; when the filter element pressure reaches the preset value (such as 0.2MPa) or after clarification for a certain time (such as 3 days), it is automatically switched to another group of clarification filters for clarification to reduce the impact of filter element blockage on the quality of the harvest fluid; manual switching can also be carried out according to the set requirements.

[0011] The clarified virus harvest fluid is transported to the harvest tank through a pipeline. A temperature control module is installed in the harvest tank to cool the liquid to 2 - 8°C for storage to reduce the impact of the normal temperature environment on the harvest fluid. After the preparation of the harvest fluid is completed, the harvest tank is pressurized for storage, and the liquid in the tank is protected by nitrogen purging to reduce the impact of CO2 in the air on the pH of the harvest fluid; After the preparation of the harvest fluid is completed, the system automatically enters the online cleaning mode and monitors the cleaning effect. During the online cleaning process, a conductivity meter is connected to real-time feedback the cleaning situation; when the cleaning component meets the cleaning conditions, the cleaning of the next component is automatically carried out; Through the intelligent monitoring system equipped in the clarification system, various parameters (such as liquid level, pressure, temperature, flow rate, etc.) during the clarification process are real-time monitored and recorded; according to the data recorded by the monitoring system, data analysis of the clarification process is carried out to find potential problems and optimization points. By continuously optimizing the operation process and parameter settings, the clarification efficiency and the quality of the harvest fluid are further improved.

[0012] The working principle and effects of the above technical solution are as follows: Through systematic design and operation, three-core clarification filters arranged in parallel are adopted, combined with an efficient pressure monitoring and filter element switching mechanism, which can maximize the clarification efficiency, avoid filter element blockage, ensure the high quality of the virus harvest fluid, enable the virus harvest fluid to continuously maintain a stable clarification effect, and reduce the fluctuations and unevenness problems during filtration; An intelligent monitoring system is introduced to monitor and record various parameters during the clarification process in real time, which can precisely control and optimize each link in the clarification process, improving the efficiency; Through data analysis, potential problems can be discovered in a timely manner and adjusted, thereby further improving the operation efficiency and product quality of the system; The automated design of the system, such as liquid level control, automatic start of the clarification flow pump, automatic switching of filter element pressure, etc., reduces manual intervention and human errors, improving the stability and safety of production; When necessary, for example, when automatic switching is required for switching, manual switching can also be carried out, increasing the system's adaptability; In addition, the pressurized preservation and nitrogen purging protection of the harvest fluid after storage further ensure the stability of the liquid during storage and reduce the interference of external factors; Through in-line cleaning (CIP) and sterilization (SIP) treatments, the system can maintain a sterile environment, avoid contamination, and ensure the safety of the production process. At the same time, the conductivity is monitored in real time during the cleaning process to ensure the cleaning effect, reducing the risk of cross-contamination and improving the usability and hygiene standards of the production equipment; Comprehensive inspection and assembly, liquid level control, and temperature control modules are adopted to ensure safety during the operation process, reduce the need for manual intervention, and improve the operation convenience and stability of the overall system; According to the monitoring data analysis, the operation parameters can be flexibly adjusted to optimize the production process; For any abnormal situation that may occur, it can be adjusted in a timely manner and corrective measures can be taken to further improve the clarification efficiency and product quality.

[0013] In one embodiment of the present invention, S1 includes: S11. Precisely position and fix the stainless steel buffer tank and the harvest tank on the equipment base to ensure that the tank body is placed horizontally to avoid affecting the liquid level control due to inclination; Then install the clarification filter, and tightly connect two three-core clarification filters arranged in parallel to the conveying pipeline through flanges; S12. Connect the temperature control module, the weighing module, and the pressure control module to the corresponding tank body and pipeline in sequence; The sensor of the temperature control module is accurately inserted into the specified position inside the tank body to monitor the liquid temperature in real time; The sensor of the weighing module is installed on the bottom support structure of the tank body to ensure accurate measurement of the liquid weight in the tank; The valves and pressure sensors of the pressure control module are firmly connected to the pipeline to ensure accurate pressure regulation; According to the process flow, lay the conveying pipeline, and reduce the number of elbows and valves in the pipeline direction to reduce the liquid flow resistance; High-quality sealing gaskets and bolts are used for fastening at the pipeline joints to ensure no leakage at the joints; S13. Adopt the pressure test method, fill compressed air or nitrogen with a certain pressure into the system, maintain for a certain period (such as 30 minutes), and check whether there is any leakage at each connection part; if there is leakage, mark and repair it in time; check whether the wiring of each electrical component is correct and firm, and whether the power supply voltage is stable; conduct a simulation operation test on the control system to ensure that each control instruction can be accurately executed; S14. Before starting the preparation of the harvest fluid, inject a cleaning fluid (such as an alkaline cleaning fluid) into the system, and conduct a circulating cleaning according to a preset cleaning program (including parameters such as cleaning time, flow rate, temperature, etc.); during the cleaning process, use the circulating pump in the pipeline to make the cleaning fluid fully contact the inner wall of the system and the surfaces of each component to remove impurities and dirt; S15. After the cleaning is completed, drain the cleaning fluid in the system and inject high-temperature steam; conduct a sterilization treatment on the inside of the system with the high-temperature steam (temperature ≥ 121 °C) generated by the steam generator, maintain for a certain period (such as 30 minutes) to ensure that the system reaches a sterile state; after the sterilization is over, slowly drain the steam and wait for the system to cool to an appropriate temperature.

[0014] The working principle and effects of the above technical solution are as follows: By accurately positioning and fixing the stainless steel buffer tank and the harvest tank, the inclination of the equipment is avoided, thereby ensuring the accuracy of the liquid level control system, avoiding liquid level fluctuations caused by equipment inclination, and enhancing the stability and reliability of the system; Through high-quality sealing gaskets and bolts for pipeline connection, the leakage risk is reduced to ensure the safety of system operation. At the same time, the temperature control module, weighing module and pressure control module are accurately installed and connected to ensure the monitoring and control accuracy and enhance the operation safety of the entire system; Through the circulating cleaning of the cleaning fluid and the high-temperature steam sterilization, impurities, dirt and microorganisms inside the system can be effectively removed to ensure the hygienic safety of the equipment, prevent pollution, which is particularly crucial for the safety of liquids or products; Through the pressure test and simulation operation test, it is ensured that there is no leakage at each connection part, and the wiring of the electrical components is correct, the power supply is stable, and the control system accurately executes commands, which helps to ensure the fault-free operation of the system in actual production; By reasonably designing the pipeline layout, the number of elbows and valves is reduced, the liquid flow resistance is lowered, thereby enhancing the fluid transmission efficiency, saving energy and improving production efficiency; The cleaning and sterilization processes not only ensure the cleanliness and hygiene after each use, but also help to extend the service life of the equipment, reduce equipment failures caused by pollution or corrosion, and ensure the long-term stable operation of the system.

[0015] In one embodiment of the present invention, the said S2 includes: S21. After the Vero cells are cultured until virus infection, collect the virus harvest fluid in a perfusion manner according to a predetermined time (such as 68 hours); pump the cell culture medium out of the cell culture container at a certain flow rate (such as 100 L / h) through a peristaltic pump and transport it to the stainless steel buffer tank through the pipeline; S22. An anti-foaming device is designed in the buffer tank. When the liquid enters the buffer tank, the anti-foaming device reduces the generation and accumulation of bubbles through mechanical stirring or gas injection, etc. At the same time, an exhaust port is provided at the top of the buffer tank to timely discharge the gas in the tank and prevent the bubbles from blocking the filter element and affecting the clarification effect. S23. Two liquid level gauges, a high one and a low one, are installed on the buffer tank to provide real-time feedback on the liquid volume in the tank. The liquid level gauges use high-precision sensors that can accurately measure the liquid level height in the tank and transmit the signals to the control system. S24. When the liquid level exceeds the low liquid level, the control system issues an instruction, and the clarification flow pump automatically starts to initiate the clarification process. The clarification flow pump transports the liquid in the buffer tank to the clarification filter for filtration according to the set flow parameters (such as 50 L / h). When the liquid level exceeds the high liquid level, the control system adjusts the operating frequency of the clarification flow pump to make it operate at an accelerated speed to ensure the clarification efficiency and avoid the overflow of the liquid in the buffer tank at the same time.

[0016] The working principle and effects of the above technical solution are as follows: The virus harvest fluid is collected by the perfusion method, and the liquid flow rate is controlled by the peristaltic pump, which can ensure the stable collection of the virus harvest fluid, improve the efficiency of virus harvest, and reduce the collection errors caused by improper operation or unstable flow rate; the anti-foaming device designed in the buffer tank effectively reduces the generation and accumulation of bubbles through mechanical stirring or gas injection, etc., avoiding the blockage of the filter element by bubbles and affecting, thus ensuring the smooth progress of the clarification process. The design of the exhaust port also ensures that the gas can be discharged in time, further improving the quality of the clarified liquid; the installation of the high and low liquid level gauges can monitor the liquid volume in the buffer tank in real time and feedback the data to the control system to ensure that the liquid level is kept within the set range. Precise liquid level control effectively avoids the risks of liquid overflow or shortage and improves the safety of the system; the control system automatically starts the clarification flow pump according to the liquid level change and adjusts the operating frequency of the flow pump according to the liquid level change to ensure that the clarification process always operates efficiently, avoiding the complexity of manual intervention, and improving the automation and efficiency of the production process; the control system automatically adjusts the operating frequency of the clarification flow pump according to the set liquid level parameters to make it operate at an accelerated speed at the high liquid level, thereby ensuring the clarification efficiency and avoiding the liquid from overflowing to other parts, ensuring the continuous and stable operation of the system; the design of this solution makes the entire virus harvest and clarification process more accurate and controllable, avoiding the fluctuations caused by improper human operation, ensuring the high efficiency and stability of virus harvest and clarification, and enhancing the overall reliability of the production line; through precise control of liquid delivery, clarification, and gas discharge, the entire virus harvest and clarification system operates more smoothly and efficiently during operation, reducing waste in the production process, and enhancing the output and production efficiency.

[0017] In an embodiment of the present invention, the S3 includes: S31. Use two parallel three - core clarification filters for the clarification and filtration of the harvest liquid; each filter is equipped with a filter element with a retention pore size of 0.8 + 0.65 μm; S32. Connect the inlets and outlets of the two clarification filters in parallel through pipelines respectively to ensure that the two filters can work simultaneously or alternately; install valves on the parallel pipelines to facilitate the maintenance or replacement of a single filter when needed; S33. Install pressure gauges before and after the clarification filters to monitor the filter element pressure in real - time; the pressure gauges use high - precision pressure sensors that can accurately measure the pressure difference before and after the filter element and transmit the signals to the control system; S34. When the filter element pressure reaches a preset value (such as 0.2 MPa) or after clarifying for a certain time (such as 3 days), the control system automatically judges whether the filter element is blocked; S35. If the filter element is blocked, the control system issues an instruction to close the inlet and outlet valves of the currently used filter, and at the same time open the inlet and outlet valves of the standby filter, automatically switching to another set of clarification filters for clarification; during the switching process, the system keeps running continuously to avoid production interruption caused by filter element replacement.

[0018] The working principle and effects of the above technical solution are as follows: By adopting two three-core clarification filters connected in parallel and combining the retention pore sizes of 0.8 + 0.65 μm of the filter elements, impurities and particles in the harvested liquid can be effectively removed. This combined filter element not only improves the clarification efficiency but also increases the filtration area, making the clarification process more efficient; the two clarification filters are connected in parallel to ensure that when one filter is being maintained or replaced, the other filter can continue to operate, guaranteeing the stability and continuity of the system and avoiding production stagnation caused by the failure of a single filter; by setting valves on the parallel pipelines, it is convenient to maintain or replace a single filter without affecting the normal operation of other filters; this design improves the maintainability of the equipment and reduces the downtime; high-precision pressure sensors are installed before and after the clarification filter to monitor the pressure change of the filter element in real time, which can accurately reflect whether the filter element is blocked; through the feedback of the pressure difference data to the control system, the system can automatically judge the working state of the filter element, improving the automation degree of the equipment; when the filter element is blocked, the system will automatically issue an instruction to close the inlet and outlet valves of the currently used filter and switch to the standby filter; in this way, the clarification process will not be interrupted, ensuring the continuity and efficiency of production; through the intelligent monitoring and control system, the maintenance and replacement of the filter become more efficient and accurate, reducing the need for manual intervention, enhancing the reliability of the system, and reducing the possibility of human errors; when the system switches filters, it maintains the continuity of the clarification process, avoids downtime caused by filter element replacement, ensures the uninterrupted production process, and thus improves the production efficiency; by automatically monitoring the pressure of the filter element and timely judging whether it is blocked, the control system can effectively avoid accelerating the damage of the filter element due to long-term high-load operation, extend the service life of the filter element, and reduce the maintenance cost.

[0019] In one embodiment of the present invention, the step S4 includes: S41. The clarified virus harvested liquid is transported to the harvest tank through a pipeline; a temperature control module is installed in the harvest tank, and the temperature control module uses an efficient heat exchanger to cool the harvested liquid by circulating cooling water or refrigerant. S42. Cool the harvested liquid to 2 - 8 °C for storage, and the control system adjusts the operating parameters of the temperature control module in real time according to the feedback signal of the temperature sensor. S43. After the preparation of the harvested liquid is completed, pressurize and preserve the harvest tank; by filling nitrogen with a certain pressure (such as 0.1 MPa) into the tank, prevent external air from entering the tank and ensure the quality of the harvested liquid. S44. Periodically purge the liquid in the tank with nitrogen. The nitrogen enters from the top of the tank through a pipeline and exits from the top of the tank to discharge the air in the tank and reduce the influence of CO2 in the air on the pH of the harvested liquid; during the purging process, control the flow rate and purging time of nitrogen to ensure the purging effect.

[0020] The working principle and effects of the above technical solution are as follows: Through an efficient heat exchanger temperature control module, the temperature of the harvested liquid can be accurately controlled and stabilized within the range of 2 - 8 °C. This temperature control mechanism effectively prevents the influence of temperature fluctuations on the quality of the harvested liquid, ensuring that the harvested liquid maintains good stability and activity during storage; By filling nitrogen and pressurizing in the harvesting tank, it can effectively prevent external air from entering the tank, avoiding the influence of oxygen and other pollutants in the air on the quality of the harvested liquid. Pressurized storage can effectively avoid contamination by bacteria or other microorganisms, helping to improve the safety of the harvested liquid; By regularly purging the liquid in the storage tank with nitrogen, the CO2 in the air in the tank can be removed, reducing the influence of CO2 on the pH of the harvested liquid and maintaining the stability of the liquid's acidity and alkalinity. This is crucial for the storage of viruses or other biological products, as pH fluctuations may affect their stability and activity; The control system can automatically adjust the operating parameters of the temperature control module by real-time feedback of the signals from the temperature sensors, thus ensuring precise control of the liquid temperature. This process is highly automated, reducing the need for human intervention and improving the accuracy and stability of the operation; Through regular purging and temperature control with nitrogen, the storage period of the harvested liquid can be significantly extended. This design ensures that the harvested liquid maintains stability for a long time in a low-temperature and oxygen-free environment, thus reducing quality degradation and loss of active ingredients during storage; Using the methods of nitrogen purging and pressurization can not only prevent external contamination but also reduce nitrogen waste, ensuring that the entire storage process is efficient and energy-saving. This helps to reduce operating costs while improving resource utilization; Through nitrogen protection and efficient temperature control technology, the risk of contamination is minimized to the greatest extent. The use of nitrogen effectively prevents microorganisms in the air from entering the storage tank, thus reducing the potential threat of the external environment to the quality of the liquid; The entire storage process of the harvested liquid ensures the consistency of product quality during storage through strict temperature and pressure control; It provides reliable quality assurance for subsequent processing and use, reducing the risk of unqualified products.

[0021] In one embodiment of the present invention, S42 includes: S421. Before the harvested liquid enters the harvesting tank, perform preliminary cooling treatment on the harvested liquid based on circulating cooling water. S422. Through the installed high-precision temperature sensor, real-time monitor the temperature of the pre-cooled harvested liquid; when the temperature reaches the set range, the system automatically controls the valve to open and convey the harvested liquid to the harvesting tank; if the temperature does not meet the requirements, the system adjusts the flow rate and temperature of the cooling water until the pre-cooling is qualified. S423. After the harvested liquid enters the harvesting tank, the temperature control module is automatically started; use cooling circulating water or refrigerant to cool down through the jacket of the tank. S424. The control system calculates the deviation between the actual temperature of the harvested liquid and the set storage temperature (2 - 8°C) in real time based on the feedback signal from the temperature sensor; based on the PID control algorithm, it automatically adjusts the operating parameters of the temperature control module, such as the flow rate and temperature of the cooling water or refrigerant, according to the deviation magnitude, to ensure that the temperature of the harvested liquid drops to the set range at the fastest speed and with the smallest overshoot; S425. During the cooling process, the system continuously monitors the change trend of the temperature of the harvested liquid; when the temperature is within the range of the set value ±0.5°C, when the temperature approaches the set range, it automatically switches to the fine-tuning mode to reduce the adjustment amplitude of the operating parameters of the temperature control module and avoid excessive temperature fluctuations; at the same time, a temperature buffer zone (such as ±0.2°C of the set temperature) is set, and when the temperature fluctuates within this zone, the temperature control module maintains the current operating parameters to ensure that the temperature of the harvested liquid is stable within the set range; S426. Install multiple temperature sensors in the harvesting tank, distributed at different positions, to monitor the temperature distribution of the harvested liquid in real time; based on the feedback signals of each sensor, analyze the temperature uniformity of the storage environment; if local temperature anomalies are found, the system automatically adjusts the operating parameters of the temperature control module to optimize the flow direction and flow rate of the cooling water or refrigerant to ensure that the temperature is uniform throughout the harvesting tank.

[0022] The working principle and effects of the above technical solutions are as follows: By using high-precision temperature sensors to monitor the temperature of the harvested liquid in real time and adjusting the system parameters according to the set range, precise temperature control is achieved. The application of the PID control algorithm makes the temperature control more intelligent, capable of quickly responding to temperature changes and ensuring that the temperature of the harvested liquid reaches the target storage temperature quickly and stably; by optimizing the flow rate, temperature, and flow direction of the cooling water or refrigerant, unnecessary energy waste is reduced and energy utilization efficiency is improved. The efficient design of the heat exchanger improves the heat exchange efficiency and reduces the energy loss during the cooling process; by installing multiple temperature sensors in the harvesting tank and monitoring the temperature distribution of the harvested liquid in real time, the operation of the cooling system can be dynamically optimized to ensure that the temperature is evenly distributed throughout the storage tank, avoiding local overheating or overcooling phenomena and further improving the quality retention effect of the harvested liquid; in traditional systems, a single temperature sensor is often used to monitor the overall temperature, which may cause temperature deviations in some local areas and cannot achieve uniform temperature control throughout the tank, thus affecting the quality of the harvested liquid. The system has a high degree of automation and can automatically adjust the operating parameters of the temperature control module at different stages to ensure the accuracy of temperature control. At the same time, the setting of the fine-tuning mode avoids excessive temperature fluctuations, ensures temperature stability, and improves the reliability of the storage process; existing systems may have a slow response speed during the temperature control process, resulting in the temperature of the harvested liquid not dropping quickly and accurately to the target temperature range; due to the hysteresis of temperature control, temperature overshoot or large fluctuations may occur.

[0023] An embodiment of the present invention, said S424 includes: S4241. Collect the temperature data of the harvested liquid through high-precision temperature sensors arranged at different key positions of the harvesting tank (such as the upper, middle, lower parts of the tank body and near the inlet and outlet of the heat exchanger), and quickly feedback the collected temperature data to the central control system through a high-speed data transmission line; S4242. After the central control system receives the data from each temperature sensor, use the multi-point average weighted algorithm, assign corresponding weights according to the importance degree of different positions to the overall temperature control, and calculate the actual average temperature of the harvested liquid; S4243. Subsequently, accurately compare this average temperature with the preset storage temperature (2 - 8 °C) to obtain a detailed temperature deviation value, and at the same time record the direction of the deviation (positive deviation or negative deviation) and the dynamic change rate of the deviation; S4244. According to the calculated temperature deviation value and its change rate, the control system combines the preset expert experience database and historical operation data to determine the initial proportional coefficient (P), integral time (I), and differential time (D) of the PID control algorithm; for example, when the temperature deviation is large and the change rate is fast, appropriately increase the proportional coefficient P to accelerate the response speed of the system; when there is a long-term accumulation trend of the deviation, reasonably adjust the integral time I to enhance the system's ability to eliminate the steady-state error; when the change rate of the deviation fluctuates, optimize the differential time D to improve the anti-interference performance of the system; S4245. During the control process, the proportional link adjusts the operating parameters of the temperature control module in real time according to the temperature deviation value at the current moment; when the temperature deviation is large, the proportional link quickly increases the control strength on the temperature control module, such as increasing the flow rate of cooling water or refrigerant to quickly reduce the temperature of the harvested liquid; when the temperature deviation decreases, the proportional link correspondingly reduces the control strength to avoid excessive temperature regulation; S4246. The integral link accumulatively calculates the temperature deviation and converts the accumulated error into an adjustment amount of the control quantity according to the integral time I; as the temperature deviation persists, the integral link continuously accumulates the error and adjusts the operating parameters of the temperature control module to eliminate the steady-state error of the system. For example, when the temperature of the harvested liquid is higher than the set temperature for a long time, the integral link gradually increases the supply of cooling water or refrigerant to make the temperature gradually approach the set value; S4247. The differential link predicts the future change trend of the temperature according to the change rate of the temperature deviation and adjusts the operating parameters of the temperature control module in advance; when the change rate of the temperature deviation increases, the differential link increases the control strength in advance to suppress the rapid rise or fall of the temperature; when the change rate of the temperature deviation decreases, the differential link correspondingly reduces the control strength to avoid excessive temperature regulation; for example, when the temperature is about to reach the set value, the differential link reduces the flow rate of cooling water or refrigerant in advance to prevent temperature overshoot; S4248. During the control process, the control system monitors in real time data such as temperature deviation, deviation change rate, and operating parameters of the temperature control module, and uses an adaptive optimization algorithm to analyze and process this data. According to the analysis results, the system automatically adjusts the proportional coefficient P, integral time I, and derivative time D of the PID control algorithm to adapt to different stages and working conditions of the harvested liquid temperature change. For example, during the temperature drop stage, the proportional coefficient P and integral time I are appropriately reduced, and the derivative time D is increased to improve the stability and regulation accuracy of the system. When the temperature is close to the set value, the control parameters are further optimized to quickly stabilize the temperature within the set range.

[0024] The working principle and effects of the above technical solution are as follows: By arranging high-precision temperature sensors at different key positions of the harvesting tank and combining the multi-point average weighted algorithm, the temperature data of the harvested liquid can be collected and calculated in real time, ensuring the accuracy of temperature control and effectively avoiding the impact of temperature fluctuations on the quality of the harvested liquid. During the change process of the harvested liquid temperature, the control system can dynamically adjust the proportional coefficient (P), integral time (I), and derivative time (D) of the PID control algorithm through the adaptive optimization algorithm, which helps to improve the response speed, anti-interference ability, and the ability to eliminate steady-state error of the system. According to the temperature deviation, deviation change rate, and historical operation data, the control system can adjust the operating parameters of the temperature control module in real time. When the temperature deviation is large, the system will quickly respond and increase the flow rate of cooling water or refrigerant. When the deviation decreases, the control intensity is reduced to avoid over-regulating the temperature. The PID control in the traditional system lacks effective monitoring and adjustment of the deviation change rate, and reacts laggingly in the face of emergencies, unable to achieve a fast and stable adjustment effect. By reasonably adjusting each link of the PID control, especially the detailed adjustment during the temperature change stage, the temperature control system maintains a high degree of stability and accuracy under different working conditions. Especially when the temperature is close to the set value, the system can optimize the control parameters to ensure that the temperature can quickly stabilize within the set range and avoid overshoot. The traditional PID control system uses fixed parameter configuration and fails to dynamically adjust the control strategy according to the operating conditions at different stages or the rate of temperature change, which results in the system responding too slowly or too quickly in some cases and unable to meet the rapidly changing temperature control requirements. By combining historical operation data and a preset expert experience database, the system can further improve the intelligence and accuracy of decision-making during the actual operation process, ensuring that the system performs well under different environments and operating states. The PID control algorithm of the existing technology may not fully combine historical operation data and the expert experience database, making the system lack the effective adaptability to complex working conditions.

[0025] An embodiment of the present invention: The S4212 includes: Establish an asynchronous data synchronization mechanism based on timestamps, and align the time stamps of each sensor data through the IEEE 1588 Precision Clock Protocol; establish a three-dimensional temperature field coordinate system according to the spatial topological structure, and map discrete sensor nodes to a virtual grid culture container model; Implement temperature change trend prediction based on LSTM, and compare the deviation between the measured value and the predicted value; construct a Gaussian mixture model (GMM) for abnormal data detection, and automatically isolate abnormal measurement points that deviate from the 3σ principle; Start the redundant sensor voting mechanism, and call the backup sensor for arbitration when data conflicts occur in a certain area; based on the hydrodynamic analysis of CFD simulation, determine the heat conduction sensitivity coefficient of different areas; Establish a heat exchange efficiency matrix in combination with the flow characteristics of the culture solution, and calculate the temperature characterization weight of each monitoring point; introduce the topological potential energy theory to quantify the centrality index of sensor nodes in the container thermal network; Calculate the magnitude of the temperature gradient vector of each monitoring point in real time, and dynamically increase the weight coefficient of the high-gradient area; evaluate the regional temperature stability based on the fuzzy inference system, and implement adaptive weight reduction for areas with frequent fluctuations; Establish a heat disturbance propagation model to predict the diffusion path of temperature fluctuations in the container, and pre-adjust the weights of downstream areas; Perform wavelet multi-resolution analysis to separate the fundamental frequency component and high-frequency disturbance component of the temperature signal; adopt an improved Kriging interpolation algorithm to fuse discrete measurement data and continuous space field information Construct a spherical harmonic function expansion of the temperature distribution to achieve the full-space domain analytical reconstruction of the three-dimensional temperature field; generate verification points through virtual sensor technology, and compare the compliance between the interpolation result and the actual physical model; apply the Monte Carlo method for uncertainty propagation analysis to evaluate the confidence interval of the average temperature value Establish an online parameter optimization module, and dynamically update the parameter of the weight allocation model in combination with real-time working condition data; generate a dynamic heat map to present the four-dimensional characteristics (three-dimensional space + time dimension) of the temperature distribution; identify potential heat aggregation areas and mark the risk level to provide spatial guidance for subsequent control strategies Output the cloud map of the temperature field gradient distribution to assist in judging the influence of the flow state of the culture solution on the temperature uniformity.

[0026] The working principle of the above technical solution is as follows: Through an asynchronous data synchronization mechanism based on timestamps, using the IEEE 1588 precise clock protocol, it ensures that the data timestamps of different sensor nodes can be accurately aligned; the system establishes a three-dimensional temperature field coordinate system according to the spatial topology of the culture container and maps each discrete sensor node into a virtual grid model to achieve the spatial positioning of temperature data; uses LSTM (Long Short-Term Memory Network) to predict the temperature change trend, helps compare the measured value with the predicted value, and evaluates the temperature prediction ability and accuracy of the system; constructs a Gaussian mixture model (GMM) to detect abnormal points in the temperature data, and automatically isolates these abnormal points when the measured data deviates from the normal value (i.e., deviates from the 3σ principle) to ensure the reliability of the system data; when data conflicts occur, the system will start a redundant sensor voting mechanism and arbitrate through backup sensors to ensure the accuracy and consistency of temperature data; uses computational fluid dynamics (CFD) to simulate and analyze the heat conduction sensitivity coefficients of different regions to provide a scientific basis for subsequent temperature regulation; combines the flow characteristics of the culture solution to establish a heat exchange efficiency matrix, and based on the temperature characterization weights of each monitoring point, dynamically adjusts the weight coefficients of the high-gradient region to optimize the uniformity of temperature distribution; evaluates the temperature stability of different regions through a fuzzy inference system, and implements adaptive weight reduction for regions with frequent fluctuations, so as to better control the temperature change; establishes a heat disturbance propagation model, predicts the diffusion path of temperature fluctuations in the container, and adjusts the weights of downstream regions in advance to prevent temperature runaway; applies wavelet multi-resolution analysis technology to separate the fundamental frequency component and high-frequency disturbance component of the temperature signal, thereby improving the temperature regulation ability of the system; adopts an improved Kriging interpolation algorithm, combines discrete measurement data with continuous space field information, constructs a spherical harmonic function expansion of the temperature distribution, and realizes the spatial analytical reconstruction of the three-dimensional temperature field; generates verification points through virtual sensor technology, and compares the conformity between the interpolation result and the actual physical model to verify the accuracy of the temperature field reconstruction; applies the Monte Carlo method for uncertainty propagation analysis, evaluates the confidence interval of temperature data, and further enhances the robustness of the system; establishes an online parameter optimization module, dynamically updates the weight allocation model in combination with real-time working condition data, and presents the four-dimensional characteristics (space + time) of the temperature distribution through a dynamic heat map; identifies potential heat accumulation regions, marks their risk levels, provides spatial guidance for subsequent temperature control strategies, and ensures the uniformity and stability of the temperature in the container; by outputting a cloud map of the temperature field gradient distribution, it helps to judge the impact of the flow state of the culture solution on the temperature uniformity, thereby further optimizing the flow temperature control system.

[0027] The effects of the above technical solutions are as follows: By means of an asynchronous data synchronization mechanism based on timestamps and using the IEEE 1588 Precision Clock Protocol to align the timestamps of each sensor data, the problem of time differences between different sensor nodes can be effectively solved, thus ensuring the temporal consistency of the data and providing a reliable basis for subsequent data analysis; Mapping discrete sensor nodes to a virtual grid culture container model and establishing a three-dimensional temperature field coordinate system based on the spatial topological structure can achieve the accurate spatial distribution reconstruction of temperature data, improving the coverage and accuracy of temperature monitoring; By introducing the Gaussian Mixture Model (GMM) for abnormal data detection and combining with the 3σ principle to automatically identify and isolate abnormal measurement points, the data quality can be improved and the interference of outliers on the analysis results can be reduced; The introduction of a redundant sensor voting mechanism helps to improve the reliability of the data. When data conflicts occur in a certain area, the backup sensor can arbitrate to ensure the accuracy and stability of the sensor data; The temperature change trend prediction based on LSTM can effectively predict the temperature change trend, detect temperature fluctuations in advance, and adjust the control strategy in a timely manner by comparing the deviation between the measured value and the predicted value, thus avoiding the occurrence of temperature anomalies; Through the hydrodynamic analysis of CFD simulation, determine the heat conduction sensitivity coefficients of different regions, and establish a heat exchange efficiency matrix in combination with the flow characteristics of the culture solution. This method helps to accurately evaluate the heat conduction efficiency, optimize the temperature control strategy, and improve the energy efficiency; By introducing the topological potential energy theory and the fuzzy inference system, combining the temperature gradient and regional stability, dynamically increase the weight coefficient of the high-gradient region and automatically reduce the weight of the region with frequent temperature fluctuations. This adaptive adjustment mechanism helps to improve the accuracy and stability of the overall temperature control; Through the spherical harmonic function expansion of the temperature distribution, realize the full-space domain analytical reconstruction of the three-dimensional temperature field, and generate verification points in combination with virtual sensor technology, which can effectively improve the accuracy and spatial analytical ability of the temperature field distribution; Apply the Monte Carlo method to conduct uncertainty propagation analysis, evaluate the confidence interval of the temperature value, provide a scientific basis for system optimization and risk management, and enhance the reliability of decision-making; Generate a dynamic heat map to present the four-dimensional characteristics of the temperature distribution (three-dimensional space + time dimension), and identify potential heat accumulation regions, providing spatial guidance for subsequent temperature uniformity control and risk warning; By outputting the temperature field gradient distribution cloud map, it is possible to assist in judging the influence of the culture solution flow state on the temperature uniformity and provide a reference basis for further optimizing the temperature control strategy.

[0028] In an embodiment of the present invention, the S426 includes: S4261. Inside the harvesting tank, based on the flow characteristics of the harvested liquid, the position of the heat exchanger, and the geometric shape of the tank body, temperature sensors are scientifically arranged in a layered and zoned manner. For example, multiple groups of sensors are evenly distributed along the radial and axial directions at the top, middle, and bottom of the tank body. At the same time, the sensor density is increased at positions prone to temperature gradients, such as near the inlet and outlet of the heat exchanger and the corners of the tank body, to form an all-round and multi-level temperature monitoring network. Temperature sensors with high precision, high stability, and fast response characteristics are selected, such as platinum resistance temperature sensors. Before installation, each sensor is strictly calibrated to ensure that its measurement error is within ±0.1°C. After installation, the sensors are regularly calibrated online, compared with a standard temperature source, and the measurement deviation of the sensors is corrected in a timely manner to ensure the accuracy of temperature data. The temperature sensors collect the temperature data of the harvested liquid in real time and transmit the data to the central control system through a high-speed and reliable data transmission line; S4262. After the central control system receives the data from each temperature sensor, based on three-dimensional modeling technology, a three-dimensional temperature field inside the harvesting tank is constructed. Through interpolation algorithms and spatial analysis methods, the discrete temperature data is converted into a continuous temperature distribution image to intuitively display the temperature changes at different positions inside the harvesting tank; S4263. Based on the temperature uniformity evaluation index system, including temperature standard deviation, temperature gradient, temperature deviation, etc.; through the analysis of the three-dimensional temperature field data, the evaluation indexes are calculated to quantitatively evaluate the temperature uniformity inside the harvesting tank. For example, the temperature standard deviation reflects the degree of dispersion of the temperature of the harvested liquid. The smaller the standard deviation, the better the temperature uniformity. The temperature gradient represents the rate of change of temperature in space. The smaller the gradient, the more uniform the temperature distribution; S4264. Based on the temperature uniformity evaluation index, a threshold range is set. When the temperature data of a certain area or several sensors exceeds the threshold range, the system automatically identifies it as an abnormal temperature area and issues a warning signal. At the same time, the abnormal temperature area is marked and located, and its specific position inside the harvesting tank is displayed to provide accurate information for subsequent adjustment measures; S4265. When an abnormal temperature area is detected, the system first analyzes and diagnoses the cause of the abnormality. Combining factors such as the flow state of the harvested liquid, the working parameters of the heat exchanger, the flow rate and temperature of cooling water or refrigerant, etc., using fault diagnosis algorithms and an expert experience knowledge base, the main cause of the abnormality is determined. For example, if the temperature of a certain area is too high, it may be caused by insufficient cooling water flow in this area, blockage of the heat exchanger, or poor flow of the harvested liquid, etc.

[0029] S4266. Develop a targeted local temperature control strategy based on the analysis result of the abnormal cause; if the abnormality is caused by insufficient cooling water flow, the system automatically adjusts the opening of the corresponding cooling water valve in this area to increase the cooling water flow; if the abnormality is caused by a blocked heat exchanger, the system starts the heat exchanger cleaning program to remove the blockage; if the abnormality is caused by poor flow of the harvested liquid, the system adjusts the rotational speed of the circulation pump of the harvested liquid to optimize the flow state of the harvested liquid.

[0030] S4267. While implementing the local temperature control strategy, the system takes into account the temperature uniformity inside the entire harvesting tank and collaboratively optimizes the global temperature control parameters; for example, when increasing the cooling water flow in a certain area, it may cause temperature changes in other areas, and the system balances the temperature changes in each area by adjusting parameters such as the overall cooling water or refrigerant flow and temperature to ensure uniform temperature inside the entire harvesting tank.

[0031] S4268. Use time series analysis methods and machine learning algorithms to predict the temperature change trend inside the harvesting tank; establish a temperature prediction model based on historical temperature data and current temperature data to predict the temperature changes in the next period of time; based on the prediction results, take corresponding temperature control measures in advance to avoid the occurrence of temperature abnormalities.

[0032] The working principle and effects of the above technical solution are as follows: By arranging temperature sensors in layers and zones, the temperature changes at different positions inside the harvesting tank can be comprehensively monitored. The high-precision, high-stability, and fast-response characteristics of the sensors ensure the accuracy of real-time temperature data, and can timely reflect the subtle temperature changes; Using three-dimensional modeling technology, the discrete temperature data is converted into a continuous temperature distribution image, helping the operator intuitively understand the temperature changes inside the harvesting tank, and providing scientific analysis and decision-making support; Through evaluation indicators such as temperature standard deviation and temperature gradient, the temperature uniformity inside the harvesting tank can be quantitatively analyzed and evaluated. In this way, the areas with uneven temperature can be identified in a timely manner, and data basis can be provided for optimizing the temperature control strategy; The system can monitor abnormal temperature areas in real time, and through the threshold judgment and early warning functions, automatically issue an alarm. By quickly locating the problem area, the system can timely adopt targeted temperature control strategies to ensure that the abnormal area is quickly adjusted; When abnormal temperature changes occur, the system can combine factors such as the flow state and the working state of the heat exchanger for intelligent analysis and fault diagnosis. This not only helps to accurately locate the cause of the abnormality, but also can formulate personalized adjustment strategies, such as adjusting the cooling water flow rate and starting the cleaning of the heat exchanger, to ensure the accuracy and efficiency of temperature control; The implementation of local temperature control measures will not affect the overall temperature uniformity. The system will adjust the temperature control strategies of other areas through collaborative optimization of parameters to ensure the uniform distribution of temperature throughout the tank body and avoid global temperature fluctuations caused by local control; Through time series analysis and machine learning methods, the system can predict the temperature change trend, early warn potential temperature abnormalities, provide support for taking effective temperature control measures in advance, and reduce the occurrence of emergencies; By regularly calibrating the sensors online, the measurement deviation can be corrected in a timely manner, so as to ensure the precise control of the system over temperature data and reduce the improper control caused by temperature errors.

[0033] In one embodiment of the present invention, the S4268 includes: Preprocess the temperature data collected in real time by each temperature sensor inside the harvesting tank, and extract the features related to temperature changes; For example, considering the flow state of the harvested liquid, extract features such as the flow rate and flow of the harvested liquid; Considering the working parameters of the heat exchanger, extract features such as the power and heat transfer efficiency of the heat exchanger; Considering external environmental factors, extract features such as environmental temperature and humidity; Based on time series decomposition technology, decompose the temperature data into trend components, seasonal components, and random components; Through decomposition, the change trend and periodic law of the temperature data can be clearly understood, providing a basis for subsequent temperature prediction. For example, use the STL decomposition method to decompose the temperature data into three parts: long-term trend, seasonal fluctuation, and irregular fluctuation, and analyze the change characteristics of each part respectively; Conduct an in-depth analysis of the decomposed trend components to determine the long-term trend of temperature changes; fit the trend curve based on polynomial regression to predict the overall future temperature change direction; for example, through linear regression analysis, it is found that the temperature shows an upward trend year by year, and the temperature increase amplitude in the future period is predicted according to the regression equation. Divide the preprocessed dataset into a training set and a test set, and use the training set to train multiple existing machine learning models; use the test set to evaluate the trained models, and use indicators such as mean squared error (MSE), mean absolute error (MAE), and coefficient of determination (R²) to evaluate the prediction accuracy and stability of the models; if the evaluation results of the models do not meet the requirements, further optimize and adjust the models, such as adding features, adjusting the model structure, etc., until the models achieve satisfactory performance. Use model fusion technology to fuse multiple machine learning models; for example, use the stacking method to fuse three models, namely SVM, random forest, and LSTM, take their prediction results as inputs, and train a new meta-model for the final prediction; on the basis of model fusion, further optimize the fused model; at the same time, in combination with the actual application scenario, update and adjust the model in real time. Utilize the trained temperature prediction model to predict the temperature change situation in the future period based on the current and historical temperature data and related features; the prediction results include information such as temperature values at different future time points, temperature change trends, and the uncertainty range of the prediction.

[0034] The working principle and effects of the above technical solution are as follows: By performing multi-level preprocessing and feature extraction on temperature data, combining the long-term trend, seasonal fluctuations of temperature changes, and the influence of environmental factors, the accuracy of temperature prediction can be significantly improved, avoiding errors in traditional methods when dealing with complex data; Based on time series decomposition technology, the long-term trend, seasonal fluctuations, and irregular fluctuations of temperature changes can be identified, providing a scientific basis for future temperature change trends and helping to predict more accurate temperature directions; Through the training and evaluation of multiple machine learning models, evaluation metrics such as mean squared error (MSE) and mean absolute error (MAE) are used to measure the performance of the models, enabling the models to be continuously optimized and adjusted. The model fusion technology further enhances the stability and reliability of the prediction results, enhancing the adaptability of the model to different data types and fluctuations; Real-time updates and adjustments are made according to the actual application scenario to ensure that the prediction model can always adapt to the changing temperature data and ensure the stability of the long-term operation of the system; By comprehensively considering different influencing factors (such as the flow rate of the harvesting fluid, ambient temperature, humidity, etc.), the complexity of temperature changes can be more comprehensively described, enhancing the interpretability and practical application value of the model; By accurately predicting future temperature changes, data support can be provided for decision-making such as temperature control and energy management in the production process, helping relevant personnel to adjust operations in a timely manner and optimize production efficiency.

[0035] In one embodiment of the present invention, the step S5 includes: S51. After the preparation of the harvesting fluid is completed, the system automatically enters the online cleaning mode; The control system starts each cleaning step in sequence according to the preset cleaning program. S52. During the online cleaning process, a conductivity meter is connected to provide real-time feedback on the cleaning situation; The conductivity meter is installed on the cleaning liquid discharge pipe and can accurately measure the conductivity of the cleaning liquid, reflecting the cleanliness of the cleaning liquid. S53. When the cleaning component meets the cleaning conditions, the control system automatically proceeds to clean the next component. S54. During the cleaning process, appropriate cleaning liquids and cleaning parameters are adopted according to the characteristics of different components; For example, for the inside of the pipeline, high-pressure water flow is used for flushing. S55. The control system records various parameters during the cleaning process (such as cleaning time, cleaning liquid flow rate, conductivity, etc.).

[0036] The working principle and effects of the above technical solution are as follows: The cleaning steps are automatically started by the control system, and the cleaning effect is real-time feedback based on the conductivity of the cleaning liquid, significantly reducing the need for manual intervention and improving the automation level of the cleaning process; By installing a conductivity meter on the cleaning liquid discharge pipe, the conductivity of the cleaning liquid can be monitored in real time, reflecting the cleanliness of the cleaning liquid. When the conductivity of the cleaning liquid reaches the set value, it indicates that the cleaning effect has reached the expected standard, and the system will automatically enter the next step; Through detailed parameter recording and analysis, the system can continuously optimize the cleaning process, accumulate empirical data, and provide improvement solutions for future cleaning processes, further improving the cleaning efficiency and quality; Through conductivity feedback, while ensuring the cleaning effect, it can avoid waste of the cleaning liquid; The use of the cleaning liquid is more precise and efficient, reducing unnecessary consumption of the cleaning liquid; According to the actual demand of the cleaning liquid, the system can accurately control the water flow and pressure during the cleaning process, avoid unnecessary energy consumption, and improve the overall cleaning efficiency; The customized cleaning solution can ensure that each component is properly cleaned according to its characteristics, reducing possible wear or corrosion to the equipment during the cleaning process, thus extending the service life of the equipment; Through effective cleaning, it can ensure that the equipment and pipelines in the production process maintain a good sanitary state, reduce the risk of product contamination, and ensure the stability of product quality; This intelligent adjustment mechanism can self-optimize according to the actual situation, further improving the adaptability and flexibility of cleaning.

[0037] In one embodiment of the present invention, the S6 includes: S61. Through the intelligent monitoring system equipped in the clarification system, various parameters (such as liquid level, pressure, temperature, flow rate, etc.) during the clarification process are monitored in real time; The monitoring system uses advanced sensors and data acquisition modules, which can accurately collect the parameter data and transmit it to the monitoring center through the network; S62. The monitoring system records the collected data in the database in real time, including information such as timestamps and parameter values. The recorded data can be used for subsequent analysis and query; S63. According to the data recorded by the monitoring system, data analysis is carried out on the clarification process; Statistical analysis methods and data mining techniques are used to find potential problems and optimization points; For example, analyze the liquid level change trend to judge whether the capacity of the buffer tank is appropriate; Analyze the pressure change situation to evaluate the service life and blockage situation of the filter element.

[0038] S64. According to the data analysis results, optimize the operation process and parameter settings of the clarification process; For example, adjust the liquid level control parameters to improve the clarification efficiency; Optimize the filter element switching time to reduce the impact of filter element blockage on the quality of the harvested liquid. Through continuous optimization, further improve the clarification efficiency and the quality of the harvested liquid, and reduce the production cost.

[0039] The working principle and effects of the above technical solution are as follows: By using an intelligent monitoring system to monitor various key parameters during the clarification process in real time (such as liquid level, pressure, temperature, flow rate, etc.), potential problems can be detected and adjusted in a timely manner to ensure that the clarification process is always in the best working state. The high precision and reliability of the sensors and data acquisition modules contribute to improving the stability and security of the system; the system records all monitored data (including timestamps, parameter values, etc.), realizing comprehensive recording and management of the data. These data provide valuable basis for subsequent analysis, optimization, fault troubleshooting, and quality control. The storage and management of data not only improve the transparency of the clarification process but also enhance the traceability of operations; by using statistical analysis methods and data mining techniques, the monitoring system can conduct in-depth analysis of parameter changes during the clarification process to detect potential problems in a timely manner. For example, through the analysis of the liquid level change trend, the system can judge whether the capacity of the buffer tank is reasonable; through the analysis of the pressure change situation, it can evaluate the usage status of the filter element and whether there is a blockage problem. This data-based analysis helps to detect problems early and take corresponding improvement measures; based on the data analysis results, the system can propose targeted operation optimization plans. For example, by adjusting liquid level control parameters, optimizing filter element switching times, etc., the clarification efficiency can be further improved, and resource waste can be reduced. This optimization can not only enhance the overall efficiency of the clarification process but also improve the quality of the harvested liquid and reduce production costs; through real-time monitoring and data analysis, operation parameters can be adjusted in a timely manner to avoid production interruptions caused by equipment failures or improper operations. The optimized operation process and parameter settings can make the clarification process more efficient, reduce the downtime of equipment, and thus improve the overall production efficiency; by introducing an intelligent monitoring system and data analysis means, the clarification process has changed from traditional manual control to a more automated and intelligent management method. The system can self-adjust according to real-time data, which not only reduces the complexity and errors of manual operations but also improves the adaptive ability of the system; by optimizing parameter settings and improving clarification efficiency, waste of raw materials and energy can be reduced. In addition, detecting and solving potential problems in a timely manner avoids production losses caused by equipment failures or operation mistakes, thus effectively reducing production costs; data analysis provides accurate basis for quality control, can monitor every detail during the clarification process, and ensure that the quality of the harvested liquid is always within a controllable range. By optimizing operations and reducing problems such as filter element blockage, the consistency and quality of the product are further improved.

[0040] An embodiment of the present invention, a real-time clarification system for a single Vero cell virus harvest solution, includes a memory, a processor, and a computer program stored on the memory and executable on the memory. The processor executes the program to implement a real-time clarification method for a single Vero cell virus harvest solution as described in any one of the above.

[0041] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A real-time clarification method for a single virus harvest solution of Vero cells, characterized in that, The method includes: S1. Assemble and inspect the system, and sterilize the system; S2. Control the liquid level and start clarification; S3. Select the filter element and set it in parallel, and monitor the pressure and switch the filter element; S4. Cool and store the clarified virus harvest fluid; S5. Conduct on-line cleaning and monitor the cleaning effect; S6. Monitor and record the clarification process in real time; according to the data recorded by the monitoring system.

2. The real-time clarification method for a single virus harvest solution of Vero cells according to claim 1, wherein The S2 includes: S21. Collect the virus harvest fluid and remove the impurities and particles generated during the preparation of the virus harvest fluid; S22. Conduct defoaming treatment; S23. Real-time feedback the liquid volume in the tank and transmit it to the control system; S24. Execute the clarification process.

3. The real-time clarification method for a single virus harvest solution of Vero cells according to claim 1, wherein, The S3 includes: S31. Select the filter element; S32. Connect the inlets and outlets of the two clarification filters in parallel through pipelines respectively; S33. Conduct pressure monitoring; S34. Automatically judge whether the filter element is blocked based on the monitoring result; S35. If the filter element is blocked, switch the filter element.

4. The real-time clarification method for a single virus harvest solution of Vero cells according to claim 1, characterized in that, The S4 includes: S41. Transport the clarified virus harvest fluid to the harvest tank through a pipeline; S42. Cool the harvest fluid to 2 - 8 °C for storage, and the control system adjusts the operating parameters of the temperature control module in real time according to the feedback signal of the temperature sensor; S43. After the preparation of the harvest fluid is completed, pressurize and store the harvest tank; S44. Periodically purge the liquid in the tank with nitrogen.

5. The real-time clarification method for a single virus harvest solution of Vero cells according to claim 4, wherein, The S42 includes: S421. Conduct preliminary cooling treatment on the harvest fluid based on the circulating cooling water; S422. Real-time monitor the temperature of the pre-cooled harvest fluid; S423. After the harvest fluid enters the harvest tank, the temperature control module is automatically started to cool the harvest fluid; S424. The control system calculates the deviation between the actual temperature and the set storage temperature of the harvest fluid in real time according to the feedback signal of the temperature sensor, and automatically adjusts the operating parameters of the temperature control module based on the PID control algorithm according to the size of the deviation; S425. The system continuously monitors the change trend of the harvest fluid temperature; when the temperature is within the range of the set value ±0.5 °C, it is automatically switched to the fine-tuning mode; at the same time, a temperature buffer range is set, and when the temperature fluctuates within this range, the temperature control module maintains the current operating parameters; S426. Based on multiple temperature sensors, monitor the temperature distribution of the harvest fluid in real time; analyze the temperature uniformity of the storage environment according to the feedback signals of each sensor, and if local temperature anomalies are found, automatically adjust the operating parameters of the temperature control module.

6. The real-time clarification method for a single virus harvest solution of Vero cells according to claim 4, wherein, The S424 includes: S4241. Obtain the temperature data of the harvest fluid and feedback the obtained temperature data to the central control system through the data transmission line; S4242. After the central control system receives the data of each temperature sensor, based on the multi-point average weighted algorithm, assign corresponding weights according to the importance degree of different positions to the overall temperature control, and calculate the actual average temperature of the harvest fluid; S4243. Compare the average temperature with the preset storage temperature to obtain the temperature deviation value, and record the direction of the deviation and the dynamic change rate of the deviation at the same time; S4244. Based on the calculated temperature deviation value and its change rate, the control system determines the initial proportional coefficient, integral time, and derivative time of the PID control algorithm by combining the preset expert experience database and historical operation data; S4245. During the control process, the proportional link adjusts the operation parameters of the temperature control module in real time according to the temperature deviation value at the current moment and the set proportional coefficient; S4246. The integral link accumulatively calculates the temperature deviation and converts the accumulated error into an adjustment amount of the control quantity according to the integral time; S4247. The derivative link predicts the future change trend of the temperature according to the change rate of the temperature deviation and adjusts the operation parameters of the temperature control module in advance; S4248. During the control process, the corresponding data is monitored in real time, and the corresponding data is analyzed and processed based on the adaptive optimization algorithm; according to the analysis results, the system automatically adjusts the proportional coefficient, integral time, and derivative time of the PID control algorithm.

7. A real-time clarification method for a single virus harvest of Vero cells according to claim 6, characterized in that, The S4212 includes: Aligning the time stamps of each sensor data; establishing a three-dimensional temperature field coordinate system according to the spatial topological structure, and mapping the discrete sensor nodes to the virtual grid culture container model; Comparing the deviation degree between the measured value and the predicted value; constructing a Gaussian mixture model for abnormal data detection; Starting the redundant sensor voting mechanism, and calling the spare sensor for arbitration when data conflicts occur in a certain area; determining the heat conduction sensitivity coefficient of different areas based on the CFD simulation-based hydrodynamic analysis; Calculating the temperature characterization weight of each monitoring point; quantifying the centrality index of the sensor node in the container thermal network; Calculating the modulus value of the temperature gradient vector of each monitoring point in real time, and dynamically increasing the weight coefficient of the high-gradient area; Establishing a heat disturbance propagation model, predicting the diffusion path of temperature fluctuations in the container, and pre-adjusting the weight of the downstream area; Separating the fundamental frequency component and the high-frequency disturbance component of the temperature signal; fusing the discrete measurement data and the continuous space field information; Comparing the conformity degree between the interpolation result and the actual physical model; performing uncertainty propagation analysis to evaluate the confidence interval of the average temperature value; Dynamically updating the parameters of the weight distribution model; generating a dynamic thermal map to present the four-dimensional characteristics of the temperature distribution; identifying potential heat accumulation areas and marking the risk level; Outputting a cloud map of the temperature field gradient distribution and judging the influence of the culture solution flow state on the temperature uniformity.

8. The real-time clarification method for a single virus harvest solution of Vero cells according to claim 4, wherein The S426 includes: Based on multiple temperature sensors, the temperature data of the harvested liquid is collected in real time, and the data is transmitted to the central control system through the data transmission line; After receiving the data of each temperature sensor, the central control system constructs a three-dimensional temperature field in the harvesting tank based on the three-dimensional modeling technology; through the interpolation algorithm and the spatial analysis method, the discrete temperature data is converted into a continuous temperature distribution image; Based on the temperature uniformity evaluation index system, the three-dimensional temperature field data is analyzed, the evaluation indexes are calculated, and the temperature uniformity in the harvesting tank is quantitatively evaluated; Based on the temperature uniformity evaluation index, a threshold range is set; when the temperature data of a certain area or several sensors exceeds the threshold range, the system automatically identifies it as an abnormal temperature area and issues a warning signal; When an abnormal temperature area is detected, analyze and diagnose the cause of the abnormality; use the fault diagnosis algorithm and the expert experience knowledge base to determine the main cause of the abnormality; According to the analysis result of the abnormal cause, formulate a targeted local temperature control strategy; While implementing the local temperature control strategy, cooperate and optimize the global temperature control parameters in combination with the temperature uniformity in the entire harvesting tank; Use the time series analysis method and machine learning algorithm to predict the temperature change trend in the harvesting tank; establish a temperature prediction model based on historical temperature data and current temperature data to predict the temperature change situation in the future for a period of time.

9. The real-time clarification method for a single virus harvest solution of Vero cells according to claim 1, wherein, The said S6 includes: S61. Monitor various parameters during the clarification process in real time; S62. Record the collected data in the database in real time; S63. Analyze the data of the clarification process; S64. Optimize the operation process and parameter settings of the clarification process.

10. A real-time clarification system for a single virus harvest solution of Vero cells, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the memory. The processor executes the program to implement a real-time clarification method for a single virus harvest solution of Vero cells as described in any one of claims 1-9.

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