Full-automatic control system of incubator carbon dioxide constant-temperature shaking table

Abstract

The invention discloses a full-automatic control system of an incubator carbon dioxide constant-temperature shaking table, and belongs to the technical field of shaking table automatic control. Through multi-sensor data acquisition and cooperative work among modules, the system realizes accurate control on the temperature, humidity and carbon dioxide concentration of the incubator and the motion state of the shaking table, ensures that the system can dynamically adjust operation parameters, quickly responds to experiment requirements or environmental disturbance, and improves the experiment efficiency. Environment monitoring protection and experiment adaptability self-optimization functions are integrated, the change trend of the external environment can be predicted according to real-time data, a targeted regulation and control strategy can be generated, meanwhile, a parameter model is continuously optimized by learning experiment historical data, in the experiment operation process, the system can load optimal parameter configuration and dynamically adjust according to the experiment type, and the experiment efficiency is improved. It is ensured that the experiment environment is always kept in the optimal state, the success rate and repeatability of the experiment are improved, the disturbance source is decomposed, the combined inhibition scheme is generated, the external influence is reduced, and the experiment safety is improved.

Description

Technical Field

[0001] The invention relates to the technical field of automatic control of a shaking table, in particular to a full-automatic control system for a carbon dioxide constant temperature shaking table in an incubator. Background Art

[0002] In scientific fields such as biomedical research, microbial culture and cell experiments, incubators and shaker equipment are important tools for maintaining the stability of the experimental environment.

[0003] Traditional incubators and shakers usually rely on a single control system to adjust environmental parameters, such as single-point control or manual calibration of temperature and carbon dioxide concentration. However, this approach cannot meet the high requirements of modern complex experiments for environmental accuracy, dynamic adaptability, and diversified experimental needs. For example, microbial culture requires strict temperature and carbon dioxide concentration control, while cell experiments have higher precision requirements for environmental stability and the motion parameters of the shaker. In addition, external environmental disturbances, equipment aging, and the diversity of experimental conditions also increase the complexity of environmental control.

[0004] In the existing technology, some incubators have simple automation functions, but they often lack systematic module coordination and intelligent optimization capabilities, making it difficult to achieve high-precision dynamic control and long-term stable operation. At the same time, traditional equipment has insufficient adjustment capabilities when the external environment changes, which can easily lead to experimental failures or result errors. With the development of artificial intelligence and sensor technology, intelligent control systems that integrate multiple sensor data have gradually become a trend in the development of experimental equipment, but there are still problems such as complex design, low efficiency, or lack of dynamic adaptation capabilities for environmental data. Summary of the invention

[0005] The object of the present invention is to provide a fully automatic control system for a carbon dioxide constant temperature shaker in an incubator to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a fully automatic control system for a carbon dioxide constant temperature shaker in an incubator, characterized in that it comprises: Data acquisition module for: Collecting incubator operation data through a carbon dioxide concentration sensor, a humidity sensor, a temperature sensor, a displacement sensor and an acceleration sensor, wherein the incubator operation data includes carbon dioxide concentration data, incubator temperature data and shaker motion state data; Temperature control modules for: Acquire the incubator temperature data in real time, and dynamically adjust the temperature in the incubator according to the deviation between the incubator temperature data and the set temperature. When the temperature in the incubator exceeds the set value, an alarm is issued and a log is recorded. Carbon dioxide concentration control module for: Acquire carbon dioxide concentration data in real time, dynamically adjust the carbon dioxide concentration in the incubator according to the deviation between the carbon dioxide concentration data and the set concentration value, and dynamically adjust the gas input and emission rates based on the feedback signal of the carbon dioxide concentration sensor; Shaker motion control module for: Adjust the speed, amplitude and operation mode of the shaker, and perform self-check of the operation status based on the shaker motion status data; Environmental monitoring and protection module, used for: Monitor the ambient temperature and humidity parameters outside the incubator, estimate the impact on the inside of the incubator and take compensatory measures; Main control module, used for: Perform inter-module collaboration and global control, assign tasks to each module according to set priorities, integrate module data and analyze the current operating status of the incubator, determine whether parameters need to be adjusted, and dynamically adjust control strategies for different experimental conditions; User interaction module, used to: A user interface is generated for adjusting the incubator temperature, carbon dioxide concentration, and shaker mode setting values, interacting with the touch screen display and displaying the temperature, concentration, and shaker motion state parameters in real time.

[0007] Furthermore, the data acquisition module is also used for: The carbon dioxide concentration sensor detects the change of carbon dioxide concentration in the incubator in real time, converts the detected analog signal into a digital signal and transmits it to the main control module; The temperature sensor measures the incubator temperature data in real time, converts the temperature signal into a standard digital signal and transmits it to the main control module; The movement amplitude of the shaking table is recorded by the displacement sensor, and combined with the dynamic data captured by the acceleration sensor, the shaking table motion state data is generated through data fusion, and the shaking table motion state data is transmitted to the main control module.

[0008] Furthermore, the temperature control module comprises: Temperature regulating unit for: Compare the incubator temperature data with the set temperature value; When the incubator temperature data is lower than the set value, the incubator temperature is increased by driving the heating device; when the incubator temperature data exceeds the set value, the temperature is lowered by starting the refrigeration device; combined with the feedback signal of the temperature sensor, the incubator temperature control adjustment parameters are updated in real time; Temperature alarm recording unit for: Set a temperature safety threshold and monitor the incubator temperature data in real time. When the incubator temperature data exceeds the temperature safety threshold range, trigger an audible and visual alarm and send an alarm message to the user interaction module. At the same time, record the temperature abnormality, including the time of occurrence, temperature value and duration of the abnormality.

[0009] Furthermore, the carbon dioxide concentration control module includes: Concentration adjustment unit for: Compare the carbon dioxide concentration data with the set concentration value; When the carbon dioxide concentration data is lower than the set value, the gas input device is controlled to input carbon dioxide gas into the incubator at the set flow rate; when the carbon dioxide concentration data is higher than the set value, the gas exhaust device is turned on to reduce the carbon dioxide concentration; combined with the feedback signal of the carbon dioxide concentration sensor, the gas carbon dioxide adjustment parameters are updated in real time; Concentration alarm recording unit, used for: A safety threshold of carbon dioxide concentration is set, and the carbon dioxide concentration data in the incubator is monitored in real time. When the carbon dioxide concentration data in the incubator exceeds the safety threshold of carbon dioxide concentration, an audible and visual alarm is triggered and an alarm message is sent to the user interaction module. At the same time, the abnormal carbon dioxide concentration is recorded, and the content of the abnormal carbon dioxide concentration includes the time of occurrence, concentration value and duration of the abnormality.

[0010] Furthermore, the concentration adjustment unit comprises: A volume data extraction module, used to extract the volume of the incubator; A concentration difference extraction module is used to extract the concentration of carbon dioxide gas inside the incubator and the concentration difference between it and a set concentration value corresponding to carbon dioxide; The temperature value extraction module is used to extract the temperature value of the current incubator; A gas input coefficient acquisition module, used to obtain the gas input coefficient by using the concentration difference between the carbon dioxide gas concentration inside the incubator and the set concentration value corresponding to carbon dioxide in combination with the volume of the incubator and the current temperature value of the incubator; The gas input coefficient is obtained by the following formula:

[0011] Wherein, K represents the gas input coefficient; V represents the volume of the incubator; ΔC represents the concentration difference between the carbon dioxide gas concentration inside the incubator and the set concentration value corresponding to carbon dioxide; T represents the current temperature value of the incubator; A coefficient comparison module, used for comparing the gas input coefficient with a preset input coefficient threshold; A flow setting module, used for setting the flow when the gas input coefficient exceeds a preset input coefficient threshold; The gas input control module is used to input carbon dioxide gas into the incubator according to a preset initial flow rate when the gas input coefficient does not exceed a preset input coefficient threshold.

[0012] Furthermore, the flow setting module includes: An initial flow extraction module, used for extracting a preset initial flow when the gas input coefficient exceeds a preset input coefficient threshold; A gas property parameter acquisition module is used to input the viscosity value, density value and specific heat capacity value of the carbon dioxide gas; A gas property coefficient acquisition module, used to acquire the gas property coefficient using the viscosity value, density value and specific heat capacity value of the carbon dioxide gas to be input; The gas property coefficient is obtained by the following formula:

[0013] Where S represents the gas property coefficient; ρ represents the density value of the carbon dioxide gas to be input; C p represents the specific heat capacity of the carbon dioxide gas to be input; λ represents the viscosity of the carbon dioxide gas to be input; ρ v Indicates the gas density value of carbon dioxide gas inside the incubator; An attribute coefficient comparison module, used for comparing the gas attribute coefficient with a preset attribute coefficient threshold; The flow setting control module is used to set the flow rate according to the comparison result between the gas property coefficient and a preset property coefficient threshold.

[0014] Furthermore, the flow setting control module includes: A first flow setting model calling module, used for calling the first flow setting model when the gas property coefficient is lower than a preset property coefficient threshold; A first flow setting module, used to set the flow rate using the first flow setting model; Wherein, the structure of the first flow setting model is as follows:

[0015] Among them, G 01 represents the set flow rate obtained by the first flow setting model; S represents the gas property coefficient; S y represents the preset attribute coefficient threshold; T represents the current temperature value of the incubator; T c Indicates the preset temperature reference value; G0 indicates the preset initial flow rate; A second flow setting model retrieving module, used for retrieving the second flow setting model when the gas property coefficient is not lower than a preset property coefficient threshold; A second flow setting module, used for setting the flow rate by using the second flow setting model; Wherein, the structure of the second flow setting model is as follows:

[0016] Among them, G 02 represents the set flow rate obtained by the second flow setting model; S represents the gas property coefficient; S y represents the preset attribute coefficient threshold; T represents the current temperature value of the incubator; T c Indicates the preset temperature reference value; G0 indicates the preset initial flow rate.

[0017] Furthermore, the rocking table motion control module includes: Motion parameter adjustment unit, used for: Receive adjustment instructions transmitted by the main control module, and dynamically adjust the control shaker according to user settings and experimental requirements. The adjustment instructions include adjusting the target speed, adjusting the amplitude, and adjusting the operating mode. The operating mode includes a constant speed mode and a periodic speed change mode. The motion parameters of the shaker are adjusted by the drive motor, and closed-loop control is performed in combination with the real-time feedback of the data acquisition module; Movement abnormality monitoring unit, used for: The shaker motion status data is received in real time and compared with the set operating mode parameter threshold. When it is detected that the operating parameter exceeds the operating mode parameter threshold range, an audible and visual alarm is triggered and an alarm message is sent to the user interaction module. At the same time, the abnormal situation of the shaker is recorded, and the content of the abnormal situation of the shaker includes the occurrence time, deviation amplitude and duration.

[0018] Furthermore, the environmental monitoring and protection module includes: Multi-dimensional environmental prediction unit, used for: Interact with the detection components installed outside the incubator to collect real-time data on temperature, humidity, air pressure, and airflow changes outside the incubator, and combine the real-time data on carbon dioxide concentration, incubator temperature, and shaker motion status collected inside the incubator to generate an environmental status trend chart through multi-source data fusion; Based on the environmental state trend graph, use time series analysis to predict the future change trend of the external environment, make a logical response based on the prediction result and generate a dynamic control strategy, the dynamic control strategy includes pre-starting the heating device and adjusting the carbon dioxide input rate; Based on the prediction results, the dynamic control strategy is revised in real time after each environmental data update; Environmental disturbance suppression unit, used for: Detecting environmental disturbance sources and disturbance source intensity based on the fluctuation rate of data collected by sensors associated with the data collection module, and judging the disturbance source properties of the environmental disturbance sources in combination with the detection history records of the environmental disturbance sources, wherein the disturbance source properties include short-term fluctuations and continuous changes; Decompose the environmental disturbance sources into temperature, humidity and gas concentration subsystems, calculate the compensation requirements of each subsystem respectively, and dynamically adjust the control parameters of the corresponding subsystem to generate a joint suppression plan; Experimentally adaptive self-optimizing unit for: Collecting incubator environmental history data and experimental results after each experiment, the environmental history data includes temperature, humidity and carbon dioxide concentration, and is labeled and stored based on the experiment type, which includes microbial culture and high-precision cell experiments; Analyze environmental historical data and extract the optimal environmental parameter control model under different experimental types; Before the experiment starts, the corresponding optimal environmental parameter control model is automatically loaded according to the experiment type input by the user, and dynamic correction is performed in combination with real-time data during operation; If it is detected during operation that the experimental conditions deviate from the preset values ​​of the optimal environmental parameter control model, the internal parameters of the incubator are automatically calculated and adjusted, and real-time feedback is provided to the user interaction module.

[0019] Furthermore, the environmental disturbance suppression unit is also used for: Collect environmental data in real time through sensors associated with the data acquisition module; Dynamically analyze the collected real-time data, calculate the environmental disturbance change rate using a data fluctuation rate model, and extract characteristic parameters of the disturbance source signal, wherein the characteristic parameters include fluctuation amplitude, frequency, and duration; Combined with the detection history record database of environmental disturbance sources, the disturbance nature is judged by the disturbance classification algorithm; if the fluctuation period of the environmental disturbance source is short and the change amplitude is small, it is judged as a short-term fluctuation caused by external short-term environmental changes; if the fluctuation period of the environmental disturbance source is long and the change trend is obvious, it is judged as a continuous change caused by external climate change and abnormal equipment status; Based on the characteristic parameters of the disturbance source signal, the detected environmental disturbance is decomposed into three subsystems: temperature disturbance, humidity disturbance and gas concentration disturbance. Calculate the difference between the disturbance signal of each subsystem and the set environmental reference value to generate a disturbance deviation matrix, perform linear decomposition on the deviation matrix, and calculate the compensation requirements of each subsystem; Among them, the temperature compensation requirements of heating and cooling power are calculated by temperature change rate, the humidity compensation requirements of humidification and dehumidification operation time are calculated by humidity deviation, and the gas concentration compensation requirements of gas input and discharge rate are calculated by gas concentration deviation; According to the compensation requirements of each subsystem, the disturbance suppression objective function is constructed and the optimal compensation parameters are solved through dynamic optimization to generate a joint suppression scheme.

[0020] Furthermore, the experiment adaptive self-optimization unit is also used for: During the experiment, the environmental history data of the incubator is collected and stored in real time; After the experiment is over, the environmental history data is labeled in combination with the experiment type and the experiment results. The label information generated by the labeling process includes the experiment name, target environmental parameters, experiment duration and experiment success rate. The environmental history data of each experiment is associated with the experiment results and stored; Extract environmental data of the same type of experiments, calculate the statistical distribution of environmental parameters under different experimental types based on multidimensional data analysis, and extract the control range of the optimal environmental parameters; Constructing an optimal environmental parameter control model based on the control range of the optimal environmental parameters, wherein the content of the optimal environmental parameter control model includes a target temperature range, a target humidity range, upper and lower limits of carbon dioxide concentration, and a shaker motion parameter setting; Before the experiment starts, the corresponding optimal environmental parameter control model is automatically loaded from the historical database according to the experiment type input by the user; During the experiment, the incubator operation data is monitored in real time, and the real-time incubator operation data is compared with the control range of the optimal environmental parameters to obtain the model deviation value; the adjustment value is automatically calculated based on the model deviation value to update the incubator temperature, humidity and gas concentration control parameters; If the experimental requirements cannot be met after adjustment, abnormal information will be fed back to the user interaction module in real time; Based on the real-time incubator operation data and the model deviation value, the compensation parameters are calculated and dynamic adjustment instructions are generated, wherein the content of the dynamic adjustment instructions includes the power setting value of the heating device, the gas input or discharge rate and the shaking table movement parameters; The adjustment effect is evaluated, and the evaluation results include the stability after deviation correction and the recovery time of the experimental environment. The evaluation results are fed back to the user interaction module.

[0021] Compared with the prior art, the present invention has the following beneficial effects: 1. Through multi-sensor data acquisition and collaborative work between modules, the system of the present invention realizes precise control of the incubator temperature, humidity, carbon dioxide concentration and shaker motion state. The data acquisition module, high-sensitivity sensor and closed-loop feedback control mechanism ensure that the system can dynamically adjust the operating parameters and quickly respond to experimental requirements or environmental disturbances. The close cooperation of sub-modules such as temperature control, carbon dioxide concentration adjustment and shaker motion control provides stable and reliable support for complex experimental scenarios.

[0022] 2. The multi-level alarm and recording function of the present invention includes sound and light alarms for temperature, gas concentration and shaker abnormalities. Users can receive abnormal information in real time through the interactive module and check detailed operation logs. The user interface is intuitive and convenient, supporting target parameter setting and real-time status monitoring. The environmental disturbance suppression unit reduces external influences and improves experimental safety by decomposing the disturbance source and generating a joint suppression scheme. At the same time, the data analysis and recording functions provide strong support for experimental traceability and parameter optimization.

[0023] 3. The present invention integrates environmental monitoring protection and experimental adaptive self-optimization functions, can quickly identify the nature of external environmental disturbance sources, and generate targeted compensation strategies through decomposition and modeling. The detailed analysis of disturbance signals and the dynamic optimization mechanism ensure the precise regulation of key parameters such as temperature, humidity and gas concentration. This comprehensive intervention method effectively avoids the damage to the experimental environment by external factors and provides stable support for the experiment. Through in-depth analysis and labeled storage of historical experimental data, the optimal environmental parameter model for different experimental types is established. It can not only automatically load the corresponding parameter model according to experimental requirements, but also dynamically adjust the control strategy in combination with real-time data during operation to ensure that the experimental conditions are always in the best state. At the same time, the optimization experience can be summarized after each experiment, and the parameter control model can be continuously improved to provide more accurate setting suggestions for subsequent experiments. Through real-time feedback and adjustment, the system can quickly respond to abnormal situations and generate detailed correction plans, greatly improving the reliability and success rate of the experiment. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the module of the fully automatic control system of the constant temperature shaking table of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] See also Figure 1 , the present invention provides the following technical solutions: Incubator CO2 constant temperature shaker fully automatic control system, including: Data acquisition module for: The incubator operation data is collected through a carbon dioxide concentration sensor, a humidity sensor, a temperature sensor, a displacement sensor and an acceleration sensor. The incubator operation data includes carbon dioxide concentration data, incubator temperature data and shaker motion state data; Temperature control modules for: Acquire the incubator temperature data in real time, and dynamically adjust the temperature in the incubator according to the deviation between the incubator temperature data and the set temperature. When the temperature in the incubator exceeds the set value, an alarm is issued and a log is recorded. Carbon dioxide concentration control module for: Acquire carbon dioxide concentration data in real time, dynamically adjust the carbon dioxide concentration in the incubator according to the deviation between the carbon dioxide concentration data and the set concentration value, and dynamically adjust the gas input and emission rates based on the feedback signal of the carbon dioxide concentration sensor; Shaker motion control module for: Adjust the speed, amplitude and operation mode of the shaker, and perform self-check of the operation status based on the shaker motion status data; Environmental monitoring and protection module, used for: Monitor the ambient temperature and humidity parameters outside the incubator, estimate the impact on the inside of the incubator and take compensatory measures; Main control module, used for: Perform inter-module collaboration and global control, assign tasks to each module according to set priorities, integrate module data and analyze the current operating status of the incubator, determine whether parameters need to be adjusted, and dynamically adjust control strategies for different experimental conditions; User interaction module, used to: Generate a user interface for adjusting the incubator temperature, CO2 concentration, and shaker mode settings, interact with the touch screen display, and display temperature, concentration, and shaker motion status parameters in real time.

[0027] In the above embodiment, by integrating multiple functional modules, accurate control and dynamic adjustment of the culture environment are achieved, which can meet the diverse experimental needs. Relying on high-precision sensors to collect data, each submodule is coordinated and regulated through the main control module, which significantly improves the operating efficiency and control accuracy of the incubator. Its core advantages are reflected in real-time monitoring, intelligent adjustment and data feedback closed-loop control, which can effectively deal with complex disturbances in the culture environment and realize refined management of experimental conditions. Through the user interaction module, the experimenter can clearly grasp the real-time operating status of the incubator and adjust the target parameters according to the needs. The system can automatically match historical experimental data and optimize the configuration, reducing the complexity of the experimental setting and improving the convenience of operation. The combination of the environmental monitoring and protection module and the experimental adaptive self-optimization unit can not only suppress environmental disturbances, but also continuously optimize the parameter control strategy to ensure the long-term stability and high success rate of the experiment.

[0028] The data acquisition module is also used for: The carbon dioxide concentration sensor detects the change of carbon dioxide concentration in the incubator in real time, converts the detected analog signal into a digital signal and transmits it to the main control module; The temperature sensor measures the incubator temperature data in real time, converts the temperature signal into a standard digital signal and transmits it to the main control module; The movement amplitude of the shaking table is recorded by the displacement sensor, and combined with the dynamic data captured by the acceleration sensor, the shaking table motion state data is generated through data fusion, and the shaking table motion state data is transmitted to the main control module.

[0029] In the above embodiment, the multi-sensor fusion technology can not only capture the environmental parameters such as temperature, humidity, carbon dioxide concentration, etc. inside the incubator, but also comprehensively monitor the movement status of the shaker through displacement and acceleration sensors. This multi-dimensional data acquisition method makes the regulation of the culture environment more precise, and provides key data support for environmental disturbance suppression and experimental adaptability optimization. The module digitizes the collected data to ensure the reliability and consistency of signal transmission. Through the algorithm optimization of the main control module, the operating status of the incubator is monitored and recorded in real time, and anomalies can be quickly discovered and protective measures can be initiated.

[0030] Temperature control module, including: Temperature regulating unit for: Compare the incubator temperature data with the set temperature value; When the incubator temperature data is lower than the set value, the incubator temperature is increased by driving the heating device; when the incubator temperature data exceeds the set value, the temperature is lowered by starting the refrigeration device; combined with the feedback signal of the temperature sensor, the incubator temperature control adjustment parameters are updated in real time; Temperature alarm recording unit for: Set the temperature safety threshold and monitor the incubator temperature data in real time. When the incubator temperature data exceeds the temperature safety threshold, the sound and light alarm is triggered and the alarm information is sent to the user interaction module. At the same time, the temperature abnormality is recorded. The content of the temperature abnormality includes the time of occurrence, temperature value and duration of the abnormality.

[0031] In the above embodiment, dynamic control of the incubator temperature is achieved through precise temperature monitoring and adjustment functions. By working in conjunction with high-sensitivity temperature sensors, the output power of the heating and cooling equipment can be adjusted in real time, thereby quickly responding to temperature deviations and ensuring that the temperature in the incubator is always maintained within the set range. Even if the external environment changes drastically, the adjustment parameters can be corrected through a real-time feedback mechanism to maintain the stability of the experimental environment. When the temperature exceeds the safety threshold, the system can respond quickly, trigger an alarm and record abnormal information, providing users with a comprehensive operation log, which not only improves the safety of the experiment, but also facilitates subsequent data analysis and problem tracing.

[0032] Carbon dioxide concentration control module, including: Concentration adjustment unit for: Compare the carbon dioxide concentration data with the set concentration value; When the carbon dioxide concentration data is lower than the set value, the gas input device is controlled to input carbon dioxide gas into the incubator at the set flow rate; when the carbon dioxide concentration data is higher than the set value, the gas exhaust device is turned on to reduce the carbon dioxide concentration; combined with the feedback signal of the carbon dioxide concentration sensor, the gas carbon dioxide adjustment parameters are updated in real time; Concentration alarm recording unit, used for: Set a safety threshold for carbon dioxide concentration and monitor the carbon dioxide concentration data in the incubator in real time. When the carbon dioxide concentration data in the incubator exceeds the safety threshold for carbon dioxide concentration, an audible and visual alarm is triggered and an alarm message is sent to the user interaction module. At the same time, the abnormal carbon dioxide concentration is recorded. The content of the abnormal carbon dioxide concentration includes the time of occurrence, concentration value and duration of the abnormality.

[0033] In the above embodiment, precise control of carbon dioxide concentration is achieved through high-sensitivity gas sensors and dynamic adjustment units, and the carbon dioxide input and emission rates are automatically adjusted according to the set concentration values. The control strategy is optimized through a real-time feedback mechanism. The concentration alarm recording unit further enhances the safety of the system and promptly reminds users to handle abnormalities. It is suitable for a variety of experimental scenarios that require precise gas control, such as cell culture or microbial experiments, and effectively improves the experimental repeatability and success rate. The high precision and high responsiveness of concentration adjustment significantly reduce the necessity of manual intervention and reduce operational risks.

[0034] Specifically, the concentration adjustment unit includes: A volume data extraction module, used to extract the volume of the incubator; A concentration difference extraction module is used to extract the concentration of carbon dioxide gas inside the incubator and the concentration difference between it and a set concentration value corresponding to carbon dioxide; The temperature value extraction module is used to extract the temperature value of the current incubator; A gas input coefficient acquisition module, used to obtain the gas input coefficient by using the concentration difference between the carbon dioxide gas concentration inside the incubator and the set concentration value corresponding to carbon dioxide in combination with the volume of the incubator and the current temperature value of the incubator; The gas input coefficient is obtained by the following formula:

[0035] Wherein, K represents the gas input coefficient; V represents the volume of the incubator; ΔC represents the concentration difference between the carbon dioxide gas concentration inside the incubator and the set concentration value corresponding to carbon dioxide; T represents the current temperature value of the incubator; A coefficient comparison module, used for comparing the gas input coefficient with a preset input coefficient threshold; A flow setting module, used for setting the flow when the gas input coefficient exceeds a preset input coefficient threshold; The gas input control module is used to input carbon dioxide gas into the incubator according to a preset initial flow rate when the gas input coefficient does not exceed a preset input coefficient threshold.

[0036] The technical effect of the above technical solution is: through the volume data extraction module, the concentration difference extraction module and the temperature value extraction module, the system can obtain the volume of the incubator, the concentration difference between the internal carbon dioxide gas concentration and the set concentration value, and the current temperature in real time. This information is the key to accurately adjust the carbon dioxide concentration. The gas input coefficient acquisition module uses the above information to calculate the gas input coefficient through a specific formula, which directly reflects the gas input amount required to reach the set concentration. The coefficient comparison module compares the calculated gas input coefficient with the preset input coefficient threshold. This comparison mechanism enables the system to automatically adjust the gas input strategy according to the current conditions. When the gas input coefficient exceeds the threshold, the flow setting module sets the corresponding gas flow according to the size of the coefficient to ensure fast and accurate concentration adjustment. When the gas input coefficient does not exceed the threshold, the gas input control module inputs according to the preset initial flow, which helps to maintain a stable input when the concentration is close to the set value and avoid over-adjustment. Through real-time monitoring and adjustment, the technical solution can quickly respond to changes in the carbon dioxide concentration in the incubator, thereby improving the efficiency and accuracy of concentration adjustment. Through the adaptive gas input strategy, the system can reduce unnecessary energy consumption and gas waste while meeting the concentration requirements. The concentration adjustment unit integrates multiple modules, each of which is responsible for a specific function. This modular design makes the system more stable and reliable. Through the preset input coefficient threshold and initial flow setting, the system can cope with abnormal situations to a certain extent and improve the overall fault tolerance.

[0037] In summary, this technical solution achieves accurate, efficient and stable regulation of the carbon dioxide concentration in the incubator through precise monitoring, adaptive regulation and modular design, which helps to improve the success rate and accuracy of cell culture or other biological experiments.

[0038] Specifically, the flow setting module includes: An initial flow extraction module, used for extracting a preset initial flow when the gas input coefficient exceeds a preset input coefficient threshold; A gas property parameter acquisition module is used to input the viscosity value, density value and specific heat capacity value of the carbon dioxide gas; A gas property coefficient acquisition module, used to acquire the gas property coefficient using the viscosity value, density value and specific heat capacity value of the carbon dioxide gas to be input; The gas property coefficient is obtained by the following formula:

[0039] Where S represents the gas property coefficient; ρ represents the density value of the carbon dioxide gas to be input; C prepresents the specific heat capacity of the carbon dioxide gas to be input; λ represents the viscosity of the carbon dioxide gas to be input; ρ v Indicates the gas density value of carbon dioxide gas inside the incubator; An attribute coefficient comparison module, used for comparing the gas attribute coefficient with a preset attribute coefficient threshold; The flow setting control module is used to set the flow rate according to the comparison result between the gas property coefficient and a preset property coefficient threshold.

[0040] The technical effect of the above technical solution is that the initial flow extraction module can extract the preset initial flow value when needed as the basis for flow setting. The gas attribute parameter acquisition module and the gas attribute coefficient acquisition module provide a more refined basis for flow setting by acquiring the viscosity value, density value and specific heat capacity value of the carbon dioxide gas to be input and calculating the gas attribute coefficient. This flow setting method based on the physical properties of the gas can more accurately reflect the characteristics and requirements of the gas in the flow process. The attribute coefficient comparison module compares the calculated gas attribute coefficient with the preset attribute coefficient threshold. This comparison mechanism enables the flow setting to be adjusted based on the real-time gas attributes, thereby improving the accuracy of the flow setting. The flow setting control module sets the flow according to the comparison result to ensure that the flow can meet the gas input requirements and avoid excessive or insufficient situations. By introducing the gas attribute coefficient and the attribute coefficient comparison module, the technical solution enables the system to make adaptive adjustments according to the different attributes of the gas to be input, thereby enhancing the adaptability and flexibility of the system. At the same time, since the flow setting is based on the real-time gas attributes and comparison results, the system can respond to changes in gas input conditions more quickly, thereby improving the overall response speed. Through refined flow setting, the system can ensure that while meeting the gas input requirements, it can reduce unnecessary energy consumption and gas waste, thereby optimizing resource utilization and energy efficiency. The flow setting module integrates multiple functional modules, each of which is responsible for a specific function. This modular design makes the system more stable and reliable. Through the preset initial flow, attribute coefficient threshold and other parameter settings, the system can cope with abnormal situations to a certain extent and improve the overall fault tolerance.

[0041] In summary, this technical solution, by introducing gas property coefficients and comparison mechanisms, achieves refined setting and adaptive adjustment of carbon dioxide gas flow, improves the accuracy of flow setting and the adaptability and flexibility of the system as a whole. At the same time, this solution also helps to optimize resource utilization and energy efficiency, and improve the stability and reliability of the system.

[0042] Specifically, the flow setting control module includes: A first flow setting model calling module, used for calling the first flow setting model when the gas property coefficient is lower than a preset property coefficient threshold; A first flow setting module, used to set the flow rate using the first flow setting model; Wherein, the structure of the first flow setting model is as follows:

[0043] Among them, G 01 represents the set flow rate obtained by the first flow setting model; S represents the gas property coefficient; S y represents the preset attribute coefficient threshold; T represents the current temperature value of the incubator; T c Indicates the preset temperature reference value; G0 indicates the preset initial flow rate; A second flow setting model retrieving module, used for retrieving the second flow setting model when the gas property coefficient is not lower than a preset property coefficient threshold; A second flow setting module, used for setting the flow rate by using the second flow setting model; Wherein, the structure of the second flow setting model is as follows:

[0044] Among them, G 02 represents the set flow rate obtained by the second flow setting model; S represents the gas property coefficient; S y represents the preset attribute coefficient threshold; T represents the current temperature value of the incubator; T c Indicates the preset temperature reference value; G0 indicates the preset initial flow rate.

[0045] The technical effect of the above technical solution is: by introducing two different flow setting models (the first flow setting model and the second flow setting model), the system can flexibly adjust the flow setting strategy according to the different ranges of the gas property coefficient. This design enables the system to adapt to different gas input conditions more accurately and improves the flexibility and accuracy of flow setting. Both flow setting models consider the gas property coefficient (S) as one of the key parameters, which shows that the system can adjust the flow based on the physical properties of the carbon dioxide gas to be input (such as viscosity, density and specific heat capacity). This flow adjustment method based on gas properties can more accurately reflect the characteristics and requirements of the gas during the flow process, thereby improving the scientificity and rationality of the flow setting. Both flow setting models include the current incubator temperature value (T) and the preset temperature reference value (Tc) as parameters, which shows that the system can comprehensively consider the influence of temperature factors on flow setting. Temperature is one of the important factors affecting gas flow characteristics. By incorporating it into the flow setting model, the system can more accurately predict and adjust the gas flow to meet the needs under different temperature conditions. By using the preset initial flow rate (G0) as the basis for flow setting and combining gas property coefficients, temperature and other factors for comprehensive calculation, both flow setting models can provide more accurate and stable flow setting results. This helps to reduce flow fluctuations and errors and improve the stability and reliability of the system. Through precise flow setting and flexible adjustment strategies, the system can reduce unnecessary energy consumption and gas waste while meeting gas input requirements. This helps to optimize resource utilization and improve energy efficiency, reducing operating costs.

[0046] In summary, this technical solution achieves flexible, accurate and stable setting of carbon dioxide gas flow by introducing two flow setting models based on different gas property coefficient ranges. This design improves the adaptability and flexibility of the system, optimizes resource utilization and energy efficiency, and provides a more reliable gas environment control method for cell culture or other biological experiments.

[0047] Shaker motion control module, including: Motion parameter adjustment unit, used for: Receive adjustment instructions transmitted by the main control module, and dynamically adjust the control shaker according to the user's set value and experimental requirements. The adjustment instructions include adjusting the target speed, adjusting the amplitude, and adjusting the operating mode. The operating modes include constant speed mode and periodic speed change mode. The motion parameters of the shaker are adjusted by the drive motor, and closed-loop control is performed in combination with the real-time feedback of the data acquisition module; Movement abnormality monitoring unit, used for: The shaker motion status data is received in real time and compared with the set operating mode parameter threshold. When it is detected that the operating parameter exceeds the operating mode parameter threshold range, an audible and visual alarm is triggered and an alarm message is sent to the user interaction module. At the same time, the abnormal situation of the shaker is recorded. The content of the abnormal situation of the shaker includes the time of occurrence, deviation amplitude and duration.

[0048] In the above embodiment, the shaker motion control module provides a variety of operating modes, including constant speed and periodic speed change modes, which can meet the specific requirements of different experiments for shaker motion. Through the drive motor and closed-loop feedback control system, high-precision adjustment of the shaker speed, amplitude and motion mode is achieved, and operational deviations can be detected and corrected in real time. The motion abnormality monitoring unit can quickly detect abnormal deviations in operating parameters and send an alarm to the user interaction module to prevent the experiment from failing due to shaker abnormalities. At the same time, the motion abnormality information recorded by the module can be used for subsequent analysis and optimization, providing a guarantee for the long-term stable operation of the experimental equipment.

[0049] Environmental monitoring and protection module, including: Multi-dimensional environmental prediction unit, used for: Interact with the detection components installed outside the incubator to collect real-time data on temperature, humidity, air pressure, and airflow changes outside the incubator, and combine the real-time data on carbon dioxide concentration, incubator temperature, and shaker motion status collected inside the incubator to generate an environmental status trend chart through multi-source data fusion; Based on the environmental status trend graph, time series analysis is used to predict the future change trend of the external environment, and logical responses are made based on the prediction results to generate dynamic control strategies, which include pre-starting the heating device and adjusting the carbon dioxide input rate; Based on the prediction results, the dynamic control strategy is revised in real time after each environmental data update; Environmental disturbance suppression unit, used for: Detect environmental disturbance sources and disturbance source intensity based on the fluctuation rate of data collected by sensors associated with the data acquisition module, and judge the disturbance source properties of the environmental disturbance sources in combination with the detection history records of the environmental disturbance sources. The disturbance source properties include short-term fluctuations and continuous changes. Decompose the environmental disturbance sources into temperature, humidity and gas concentration subsystems, calculate the compensation requirements of each subsystem respectively, and dynamically adjust the control parameters of the corresponding subsystem to generate a joint suppression plan; Experimentally adaptive self-optimizing unit for: Collect incubator environmental history data and experimental results after each experiment. Environmental history data includes temperature, humidity, and carbon dioxide concentration, and is stored in a labeled manner based on the experiment type, which includes microbial culture and high-precision cell experiments. Analyze environmental historical data and extract the optimal environmental parameter control model under different experimental types; Before the experiment starts, the corresponding optimal environmental parameter control model is automatically loaded according to the experiment type input by the user, and dynamic correction is performed in combination with real-time data during operation; If it is detected during operation that the experimental conditions deviate from the preset values ​​of the optimal environmental parameter control model, the internal parameters of the incubator are automatically calculated and adjusted, and real-time feedback is provided to the user interaction module.

[0050] In the above embodiment, a complete multi-source data fusion model is constructed by collecting the external environmental data of the incubator in real time and combining it with the internal operating data of the incubator. It can effectively predict the potential impact of the external environment on the culture conditions and respond quickly through dynamic control strategies. The predictive control method greatly improves the success rate and stability of the experiment. Through the precise decomposition of external environmental disturbances and the optimization of subsystem compensation strategies, the impact of external changes on the experimental environment is minimized. The dynamic optimization solution mechanism ensures the high precision and real-time performance of the compensation parameters, further improving the environmental adaptability of the system.

[0051] Environmental disturbance suppression unit is also used for: Collect environmental data in real time through sensors associated with the data acquisition module; Dynamically analyze the collected real-time data, use the data fluctuation rate model to calculate the environmental disturbance change rate, and extract the characteristic parameters of the disturbance source signal, including fluctuation amplitude, frequency and duration; Combined with the detection history record database of environmental disturbance sources, the disturbance nature is judged by the disturbance classification algorithm; if the fluctuation period of the environmental disturbance source is short and the change amplitude is small, it is judged as a short-term fluctuation caused by external short-term environmental changes; if the fluctuation period of the environmental disturbance source is long and the change trend is obvious, it is judged as a continuous change caused by external climate change and abnormal equipment status; Based on the characteristic parameters of the disturbance source signal, the detected environmental disturbance is decomposed into three subsystems: temperature disturbance, humidity disturbance and gas concentration disturbance. Calculate the difference between the disturbance signal of each subsystem and the set environmental reference value to generate a disturbance deviation matrix, perform linear decomposition on the deviation matrix, and calculate the compensation requirements of each subsystem; Among them, the temperature compensation requirements of heating and cooling power are calculated by temperature change rate, the humidity compensation requirements of humidification and dehumidification operation time are calculated by humidity deviation, and the gas concentration compensation requirements of gas input and discharge rate are calculated by gas concentration deviation; According to the compensation requirements of each subsystem, the disturbance suppression objective function is constructed and the optimal compensation parameters are solved through dynamic optimization to generate a joint suppression scheme.

[0052] In the above embodiment, the environmental disturbance suppression unit can quickly identify the nature of the external environmental disturbance source, and generate targeted compensation strategies through decomposition and modeling. The detailed analysis and dynamic optimization mechanism of the disturbance signal ensure the precise control of key parameters such as temperature, humidity and gas concentration. This comprehensive intervention method effectively avoids the damage to the experimental environment by external factors and provides stable support for the experiment.

[0053] Experimental adaptive self-optimization unit, also used for: During the experiment, the environmental history data of the incubator is collected and stored in real time; After the experiment is over, the environmental history data is labeled based on the experiment type and experimental results. The label information generated by the labeling process includes the experiment name, target environmental parameters, experiment duration and experiment success rate. The environmental history data of each experiment is associated with the experimental results and stored; Extract environmental data of the same type of experiments, calculate the statistical distribution of environmental parameters under different experimental types based on multidimensional data analysis, and extract the control range of the optimal environmental parameters; An optimal environmental parameter control model is constructed based on the control range of the optimal environmental parameters. The content of the optimal environmental parameter control model includes the target temperature range, the target humidity range, the upper and lower limits of the carbon dioxide concentration, and the shaking table motion parameter settings; Before the experiment starts, the corresponding optimal environmental parameter control model is automatically loaded from the historical database according to the experiment type input by the user; During the experiment, the incubator operation data is monitored in real time, and the real-time incubator operation data is compared with the control range of the optimal environmental parameters to obtain the model deviation value; the adjustment value is automatically calculated based on the model deviation value to update the incubator temperature, humidity and gas concentration control parameters; If the experimental requirements cannot be met after adjustment, abnormal information will be fed back to the user interaction module in real time; Based on the real-time incubator operation data and the model deviation value, the compensation parameters are calculated and dynamic adjustment instructions are generated, and the content of the dynamic adjustment instructions includes the power setting value of the heating device, the gas input or discharge rate and the shaking table movement parameters; Evaluate the adjustment effect, including the stability after deviation correction and the recovery time of the experimental environment, and feed the evaluation results back to the user interaction module In the above embodiment, through in-depth analysis and labeled storage of historical experimental data, the optimal environmental parameter model for different experimental types is established. Not only can the corresponding parameter model be automatically loaded according to the experimental requirements, but the control strategy can also be dynamically adjusted in combination with real-time data during operation to ensure that the experimental conditions are always in the best state. At the same time, the optimization experience can be summarized after each experiment, and the parameter control model can be continuously improved to provide more accurate setting suggestions for subsequent experiments. Through real-time feedback and adjustment, the system can respond quickly to abnormal situations and generate detailed correction plans, greatly improving the reliability and success rate of the experiment.

[0054] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The fully automatic control system of the carbon dioxide constant temperature shaker in the incubator is characterized by: include: Data acquisition module for: Collecting incubator operation data through a carbon dioxide concentration sensor, a humidity sensor, a temperature sensor, a displacement sensor and an acceleration sensor, wherein the incubator operation data includes carbon dioxide concentration data, incubator temperature data and shaker motion state data; Temperature control modules for: Acquire the incubator temperature data in real time, and dynamically adjust the temperature in the incubator according to the deviation between the incubator temperature data and the set temperature; Carbon dioxide concentration control module for: Obtain carbon dioxide concentration data in real time, and dynamically adjust the carbon dioxide concentration in the incubator according to the deviation between the carbon dioxide concentration data and the set concentration value; Shaker motion control module for: Adjust the shaker's speed, amplitude, and operating mode; Environmental monitoring and protection module, used for: Monitor the ambient temperature and humidity parameters outside the incubator, estimate the impact on the inside of the incubator and take compensation measures, detect the source of environmental disturbance, calculate the compensation demand based on the source of environmental disturbance, and dynamically adjust the control parameters to generate a joint suppression plan. Generate an optimal environmental parameter control model based on the historical data of the incubator environment and the experimental results of each experiment. The optimal environmental parameter control model is used to dynamically correct the incubator in combination with real-time data during operation; Main control module, used for: Perform collaborative work and global control between modules, assign tasks to each module according to set priorities, integrate data from each module and analyze the current operating status of the incubator; User interaction module, used to: A user interface is generated for adjusting incubator temperature, carbon dioxide concentration, and shaker mode set points.

2. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 1, characterized in that: The data acquisition module is also used for: The carbon dioxide concentration sensor detects the change of carbon dioxide concentration in the incubator in real time, converts the detected analog signal into a digital signal and transmits it to the main control module; The temperature sensor measures the incubator temperature data in real time, converts the temperature signal into a standard digital signal and transmits it to the main control module; The movement amplitude of the shaking table is recorded by the displacement sensor, and combined with the dynamic data captured by the acceleration sensor, the shaking table motion state data is generated through data fusion, and the shaking table motion state data is transmitted to the main control module.

3. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 1, characterized in that: The temperature control module comprises: Temperature regulating unit for: Compare the incubator temperature data with the set temperature value; When the incubator temperature data is lower than the set value, the incubator temperature is increased by driving the heating device; when the incubator temperature data exceeds the set value, the temperature is lowered by starting the refrigeration device; combined with the feedback signal of the temperature sensor, the incubator temperature control adjustment parameters are updated in real time; Temperature alarm recording unit for: Set a temperature safety threshold and monitor the incubator temperature data in real time. When the incubator temperature data exceeds the temperature safety threshold range, trigger an audible and visual alarm and send an alarm message to the user interaction module. At the same time, record the temperature abnormality, including the time of occurrence, temperature value and duration of the abnormality.

4. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 1, characterized in that: The carbon dioxide concentration control module comprises: Concentration adjustment unit for: Compare the carbon dioxide concentration data with the set concentration value; When the carbon dioxide concentration data is lower than the set value, the gas input device is controlled to input carbon dioxide gas into the incubator at the set flow rate; when the carbon dioxide concentration data is higher than the set value, the gas exhaust device is turned on to reduce the carbon dioxide concentration; combined with the feedback signal of the carbon dioxide concentration sensor, the gas carbon dioxide adjustment parameters are updated in real time; Concentration alarm recording unit, used for: A safety threshold of carbon dioxide concentration is set, and the carbon dioxide concentration data in the incubator is monitored in real time. When the carbon dioxide concentration data in the incubator exceeds the safety threshold of carbon dioxide concentration, an audible and visual alarm is triggered and an alarm message is sent to the user interaction module. At the same time, the abnormal carbon dioxide concentration is recorded, and the content of the abnormal carbon dioxide concentration includes the time of occurrence, concentration value and duration of the abnormality.

5. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 1, characterized in that: The concentration adjustment unit comprises: A volume data extraction module, used to extract the volume of the incubator; A concentration difference extraction module is used to extract the concentration of carbon dioxide gas inside the incubator and the concentration difference between it and a set concentration value corresponding to carbon dioxide; The temperature value extraction module is used to extract the temperature value of the current incubator; A gas input coefficient acquisition module, used to obtain the gas input coefficient by using the concentration difference between the carbon dioxide gas concentration inside the incubator and the set concentration value corresponding to carbon dioxide in combination with the volume of the incubator and the current temperature value of the incubator; The gas input coefficient is obtained by the following formula: ; Wherein, K represents the gas input coefficient; V represents the volume of the incubator; ΔC represents the concentration difference between the carbon dioxide gas concentration inside the incubator and the set concentration value corresponding to carbon dioxide; T represents the current temperature value of the incubator; A coefficient comparison module, used for comparing the gas input coefficient with a preset input coefficient threshold; A flow setting module, used for setting the flow when the gas input coefficient exceeds a preset input coefficient threshold; The gas input control module is used to input carbon dioxide gas into the incubator according to a preset initial flow rate when the gas input coefficient does not exceed a preset input coefficient threshold.

6. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 5, characterized in that: The flow setting module comprises: An initial flow extraction module, used for extracting a preset initial flow when the gas input coefficient exceeds a preset input coefficient threshold; A gas property parameter acquisition module is used to input the viscosity value, density value and specific heat capacity value of the carbon dioxide gas; A gas property coefficient acquisition module, used to acquire the gas property coefficient using the viscosity value, density value and specific heat capacity value of the carbon dioxide gas to be input; The gas property coefficient is obtained by the following formula: ; Where S represents the gas property coefficient; ρ represents the density value of the carbon dioxide gas to be input; C p represents the specific heat capacity of the carbon dioxide gas to be input; λ represents the viscosity of the carbon dioxide gas to be input; ρ v Indicates the gas density value of carbon dioxide gas inside the incubator; An attribute coefficient comparison module, used for comparing the gas attribute coefficient with a preset attribute coefficient threshold; The flow setting control module is used to set the flow rate according to the comparison result between the gas property coefficient and a preset property coefficient threshold.

7. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 6, characterized in that: The flow setting control module comprises: A first flow setting model calling module, used for calling the first flow setting model when the gas property coefficient is lower than a preset property coefficient threshold; A first flow setting module, used to set the flow rate using the first flow setting model; Wherein, the structure of the first flow setting model is as follows: ; Among them, G 01 represents the set flow rate obtained by the first flow setting model; S represents the gas property coefficient; S y represents the preset attribute coefficient threshold; T represents the current temperature value of the incubator; T c Indicates the preset temperature reference value; G0 indicates the preset initial flow rate; A second flow setting model retrieving module, used for retrieving the second flow setting model when the gas property coefficient is not lower than a preset property coefficient threshold; A second flow setting module, used for setting the flow rate by using the second flow setting model; Wherein, the structure of the second flow setting model is as follows: ; Among them, G 02 represents the set flow rate obtained by the second flow setting model; S represents the gas property coefficient; S y represents the preset attribute coefficient threshold; T represents the current temperature value of the incubator; T c Indicates the preset temperature reference value; G0 indicates the preset initial flow rate.

8. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 1, characterized in that: The shaking table motion control module comprises: Motion parameter adjustment unit, used for: Receive adjustment instructions transmitted by the main control module, and dynamically adjust the control shaker according to user settings and experimental requirements. The adjustment instructions include adjusting the target speed, adjusting the amplitude, and adjusting the operating mode. The operating mode includes a constant speed mode and a periodic speed change mode. The motion parameters of the shaker are adjusted by the drive motor, and closed-loop control is performed in combination with the real-time feedback of the data acquisition module; Movement abnormality monitoring unit, used for: The shaker motion status data is received in real time and compared with the set operating mode parameter threshold. When it is detected that the operating parameter exceeds the operating mode parameter threshold range, an audible and visual alarm is triggered and an alarm message is sent to the user interaction module. At the same time, the abnormal situation of the shaker is recorded, and the content of the abnormal situation of the shaker includes the occurrence time, deviation amplitude and duration.

9. The incubator carbon dioxide constant temperature shaker fully automatic control system as claimed in claim 1, characterized in that: The environmental monitoring and protection module includes: Multi-dimensional environmental prediction unit, used for: Interact with the detection components installed outside the incubator to collect real-time data on temperature, humidity, air pressure, and airflow changes outside the incubator, and combine the real-time data on carbon dioxide concentration, incubator temperature, and shaker motion status collected inside the incubator to generate an environmental status trend chart through multi-source data fusion; Based on the environmental state trend graph, use time series analysis to predict the future change trend of the external environment, make a logical response based on the prediction result and generate a dynamic control strategy, the dynamic control strategy includes pre-starting the heating device and adjusting the carbon dioxide input rate; Based on the prediction results, the dynamic control strategy is revised in real time after each environmental data update; Environmental disturbance suppression unit, used for: Detecting environmental disturbance sources and disturbance source intensity based on the fluctuation rate of data collected by sensors associated with the data collection module, and judging the disturbance source properties of the environmental disturbance sources in combination with the detection history records of the environmental disturbance sources, wherein the disturbance source properties include short-term fluctuations and continuous changes; Decompose the environmental disturbance sources into temperature, humidity and gas concentration subsystems, calculate the compensation requirements of each subsystem respectively, and dynamically adjust the control parameters of the corresponding subsystem to generate a joint suppression plan; Experimentally adaptive self-optimizing unit for: Collecting incubator environmental history data and experimental results after each experiment, the environmental history data includes temperature, humidity and carbon dioxide concentration, and is labeled and stored based on the experiment type, which includes microbial culture and high-precision cell experiments; Analyze environmental historical data and extract the optimal environmental parameter control model under different experimental types; Before the experiment starts, the corresponding optimal environmental parameter control model is automatically loaded according to the experiment type input by the user, and dynamic correction is performed in combination with real-time data during operation; If it is detected during operation that the experimental conditions deviate from the preset values ​​of the optimal environmental parameter control model, the internal parameters of the incubator are automatically calculated and adjusted, and real-time feedback is provided to the user interaction module.

10. The incubator carbon dioxide constant temperature shaker fully automatic control system according to claim 9, characterized in that: The environmental disturbance suppression unit is further used for: Collect environmental data in real time through sensors associated with the data acquisition module; Dynamically analyze the collected real-time data, calculate the environmental disturbance change rate using a data fluctuation rate model, and extract characteristic parameters of the disturbance source signal, wherein the characteristic parameters include fluctuation amplitude, frequency, and duration; Combined with the detection history record database of environmental disturbance sources, the disturbance nature is judged by the disturbance classification algorithm; if the fluctuation period of the environmental disturbance source is short and the change amplitude is small, it is judged as a short-term fluctuation caused by external short-term environmental changes; if the fluctuation period of the environmental disturbance source is long and the change trend is obvious, it is judged as a continuous change caused by external climate change and abnormal equipment status; Based on the characteristic parameters of the disturbance source signal, the detected environmental disturbance is decomposed into three subsystems: temperature disturbance, humidity disturbance and gas concentration disturbance. Calculate the difference between the disturbance signal of each subsystem and the set environmental reference value to generate a disturbance deviation matrix, perform linear decomposition on the deviation matrix, and calculate the compensation requirements of each subsystem; Among them, the temperature compensation requirements of heating and cooling power are calculated by temperature change rate, the humidity compensation requirements of humidification and dehumidification operation time are calculated by humidity deviation, and the gas concentration compensation requirements of gas input and discharge rate are calculated by gas concentration deviation; According to the compensation requirements of each subsystem, the disturbance suppression objective function is constructed and the optimal compensation parameters are solved through dynamic optimization to generate a joint suppression scheme; The experimental adaptive self-optimization unit is also used for: During the experiment, the environmental history data of the incubator is collected and stored in real time; After the experiment is over, the environmental history data is labeled in combination with the experiment type and the experiment results. The label information generated by the labeling process includes the experiment name, target environmental parameters, experiment duration and experiment success rate. The environmental history data of each experiment is associated with the experiment results and stored; Extract environmental data of the same type of experiments, calculate the statistical distribution of environmental parameters under different experimental types based on multidimensional data analysis, and extract the control range of the optimal environmental parameters; Constructing an optimal environmental parameter control model based on the control range of the optimal environmental parameters, wherein the content of the optimal environmental parameter control model includes a target temperature range, a target humidity range, upper and lower limits of carbon dioxide concentration, and a shaker motion parameter setting; Before the experiment starts, the corresponding optimal environmental parameter control model is automatically loaded from the historical database according to the experiment type input by the user; During the experiment, the incubator operation data is monitored in real time, and the real-time incubator operation data is compared with the control range of the optimal environmental parameters to obtain the model deviation value; the adjustment value is automatically calculated based on the model deviation value to update the incubator temperature, humidity and gas concentration control parameters; If the experimental requirements cannot be met after adjustment, abnormal information will be fed back to the user interaction module in real time; Based on the real-time incubator operation data and the model deviation value, the compensation parameters are calculated and dynamic adjustment instructions are generated, wherein the content of the dynamic adjustment instructions includes the power setting value of the heating device, the gas input or discharge rate and the shaking table movement parameters; The adjustment effect is evaluated, and the evaluation results include the stability after deviation correction and the recovery time of the experimental environment. The evaluation results are fed back to the user interaction module.

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