Cryogenic environment self-adaptive constant temperature control system based on digital twinning

Abstract

The invention discloses a digital twinning-based copious cooling environment adaptive constant temperature control system, and relates to the technical field of temperature control, the system comprises an acquisition module, an analysis module and a control module, the acquisition module acquires operation data of a copious cooling device, the analysis module constructs and dynamically updates state information of the copious cooling device based on the operation data, and the control module controls the state information of the copious cooling device. And the control module analyzes the operation data and the state information from the temperature dimension, the pressure dimension and the calibration dimension to obtain an analysis result, generates an optimization strategy according to the analysis result, obtains an optimization result, dynamically identifies deviation change of the optimization result and the analysis result, obtains deviation information, and feeds back the deviation information to the analysis module. Through dynamic mapping and multi-dimensional closed-loop regulation and control, the uniformity, stability and calibration efficiency of a cryogenic environment temperature field are improved, a pressure grading response mechanism is established, and the problems that a traditional device is insufficient in temperature control precision, high in safety risk, short in calibration and the like are solved.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology, and in particular to an adaptive constant temperature control system for cryogenic environments based on digital twins. Background Technology

[0002] In high-precision fields such as biomedicine, aerospace, and materials science, precise temperature control of cryogenic environments (-196 to -80°C) has become a core technological support for ensuring the reliability of experimental data and product performance. As cutting-edge scientific research places increasingly stringent requirements on temperature parameters, the temperature field uniformity, stability, and calibration capabilities of cryogenic devices are facing comprehensive upgrade pressure. The parameters involved in the operation of cryogenic devices, such as liquid nitrogen cooling capacity, heating power output, pressure changes inside the tank, and calibration channel status, are not independent but form a dynamically coupled system that mutually restricts each other. For example, a small fluctuation in heating power during temperature field adjustment may cause nonlinear changes in the pressure inside the tank, while the adjustment of the opening of the pressure relief valve will in turn affect the stability of the local temperature field. This multi-parameter linkage effect directly determines the control accuracy and operational safety of the cryogenic environment.

[0003] Traditional cryogenic temperature control technology has gradually revealed systemic limitations under complex operating conditions: The temperature control logic has blind spots, relying heavily on single-point temperature feedback for adjustment and neglecting the correlation of spatial temperature distribution. This results in a uniformity of less than 50 mK in the (-185~-80℃) range and a single-point stability of less than 20 mK at -196℃ for 10 minutes, failing to meet the temperature field consistency requirements of high-precision experiments. Furthermore, the calibration system has shortcomings; existing devices have only 3-4 calibration channels, leading to low batch calibration efficiency and poor compatibility with short sensors of 300mm and below. Inappropriate insertion depth design also results in reduced calibration accuracy. The system suffers from several shortcomings: lack of quantitative assessment standards for interference between channels; lagging pressure safety control, with a lack of dynamic coordination between temperature regulation and pressure control, and no established graded response mechanism based on the rate of pressure change, making it prone to safety risks due to sudden pressure increases during heating; an incomplete traceability system, inconsistent standards for transmitting values ​​in the cryogenic temperature zone, and a lack of traceability in calibration methods, resulting in poor data comparability between different devices; and a static control strategy that lags behind in responding to dynamic operating conditions such as temperature field drift and pressure fluctuations, failing to form a closed-loop optimization mechanism of "detection-analysis-control-feedback," making it difficult to adapt to parameter decay and environmental interference during long-term operation. Summary of the Invention

[0004] The technical problem solved by this invention is to address the issues of insufficient temperature control accuracy, low calibration efficiency, poor adaptability, high pressure risk, and imperfect traceability system of traditional cryogenic devices in cryogenic environments.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a cryogenic environment adaptive constant temperature control system based on digital twin, comprising: a data acquisition module, an analysis module, and a control module; The acquisition module is used to acquire the operating data of the cryogenic device and transmit the operating data to the analysis module; The analysis module is used to construct and dynamically update the status information of the cryogenic device based on the operating data, analyze the operating data and status information from the dimensions of temperature, pressure and calibration, obtain the analysis results, and transmit the analysis results to the control module. The control module is used to generate an optimization strategy based on the analysis results, obtain optimization results, dynamically identify deviation changes between the optimization results and the analysis results and obtain deviation information, and feed the deviation information back to the analysis module.

[0006] As a preferred embodiment of the cryogenic environment adaptive constant temperature control system based on digital twin described in this invention, the acquisition module includes a sensing unit and a scheduling unit. The sensing unit is used to collect temperature field distribution data, tank pressure data, calibration channel status data, and refrigeration and heating operation data of the cryogenic device. The scheduling unit is used to adjust the sampling frequency and transmission priority of the sensing nodes in real time according to the status information. The status information includes temperature field status information, pressure field status information, and calibration channel status information; The temperature field state information includes virtual data of the temperature field distribution of the cryogenic device; The pressure field status information includes virtual data of the internal pressure of the cryogenic device. The calibration channel status information includes virtual data of the calibration channel of the cryogenic device; The sensing nodes include temperature sensors, pressure transmitters, flow meters, and calibration signal receivers.

[0007] As a preferred embodiment of the cryogenic environment adaptive constant temperature control system based on digital twins described in this invention, the analysis module includes a twin modeling unit, a dynamic update unit, and an analysis unit. The twin modeling unit is used to construct the status information based on the operational data transmitted by the acquisition module; The dynamic update unit is used to receive deviation information transmitted by the feedback unit and real-time operating data of the acquisition module, dynamically correct the status information, and update the virtual accuracy of the temperature field, the virtual accuracy of the pressure field, and the virtual accuracy of the calibration channel.

[0008] As a preferred embodiment of the cryogenic environment adaptive constant temperature control system based on digital twins described in this invention, the analysis unit includes a temperature dimension analysis subunit, a pressure dimension analysis subunit, and a calibration dimension analysis subunit. The analysis results include the first analysis result, the second analysis result, and the third analysis result; The temperature dimension analysis subunit is used to obtain the first analysis result; The temperature dimension analysis subunit calculates the temperature deviation between the actual temperature and the target temperature based on the temperature field state information and the temperature field distribution data, and statistically analyzes the temperature field uniformity data and temperature field stability data within the first temperature range and within the first unit time, thereby identifying temperature inaccuracy area information and potential inaccuracy trends. The temperature field uniformity data includes regional temperature difference extremes, temperature difference distribution ratios, and gradient change rates. The temperature field stability data includes fluctuation amplitude, fluctuation frequency, and trend offset; The temperature misalignment area information includes spatial coordinate range, degree of misalignment, type of misalignment, and regional correlation. The potential inaccuracy trend includes potential inaccuracy regions, evolution of inaccuracy degree, trend of causal correlation, and critical time nodes; The first analysis results include the temperature deviation value, temperature field uniformity data, temperature field stability data, temperature inaccuracy region information, and potential inaccuracy trend.

[0009] As a preferred embodiment of the cryogenic environment adaptive isothermal control system based on digital twins described in this invention, wherein: the pressure dimension analysis subunit is used to obtain the second analysis result; The pressure dimension analysis subunit calculates the pressure change rate based on the pressure field state information and the pressure data inside the tank, generates a pressure fluctuation curve during the temperature regulation process, analyzes the correlation between the pressure data exceeding the standard inside the tank and the heating rate based on the pressure fluctuation curve, and generates pressure safety early warning information and pressure regulation effect. The second analysis results include the pressure change rate, pressure fluctuation curve, correlation data, pressure safety early warning information, and pressure control effect.

[0010] As a preferred embodiment of the cryogenic environment adaptive isothermal control system based on digital twin described in this invention, wherein: the calibration dimension analysis subunit is used to obtain the second analysis result; The calibration dimension analysis subunit calculates the synchronization error of n calibration channels based on the calibration channel status information and the calibration channel status data. By simulating the sensor response characteristics at different insertion depths, it calculates the calibration accuracy of the short sensor inserted at the first depth threshold, defines the interference level of the calibration channel, and generates calibration path suggestions. The third analysis results include the synchronization error of the n calibration channels, the calibration accuracy of the short sensor, the interference level of the calibration channels, and the calibration path recommendations; The calibration channel interference levels include a first interference level, a second interference level, and a third interference level, specifically including: The first interference level includes the temperature reading deviation of each calibration channel within the first deviation range and the synchronization error within the second deviation range when n calibration channels are calibrated in parallel, indicating that there is no mutual influence between the calibration channels. The second interference level includes temperature reading deviations of each calibration channel within the third deviation range and synchronization errors within the fourth deviation range, indicating that the interference does not affect the validity of the calibration results; The third interference level includes temperature reading deviations of each calibration channel within the fifth deviation range and synchronization errors within the sixth deviation range. This indicates that interference causes calibration data to exceed the allowable error range, and parallel calibration is suspended while calibration channel isolation adjustments are performed.

[0011] As a preferred embodiment of the cryogenic environment adaptive isothermal control system based on digital twins described in this invention, the priority for analyzing the temperature dimension, pressure dimension, and calibration dimension includes: The pressure dimension is of first priority; The temperature dimension is of second priority. The calibration dimension is the third priority. The priority is dynamically verified through status information. When the virtual mapping deviation of one dimension exceeds the threshold, the priority of that one dimension is increased to the first priority.

[0012] As a preferred embodiment of the cryogenic environment adaptive constant temperature control system based on digital twin described in this invention, the control module includes a regulation unit and a feedback unit. The control unit includes a temperature dimension control subunit, a pressure dimension control subunit, and a calibration dimension control subunit; The optimization strategies include a first optimization strategy, a second optimization strategy, and a third optimization strategy; The optimization results include a first optimization result, a second optimization result, and a third optimization result; The temperature dimension control subunit is used to control the first analysis result, generate a first optimization strategy, and obtain a first optimization result, specifically including: Based on the first analysis results, for the temperature misalignment region information, the coordinated ratio range of liquid nitrogen cooling capacity and heating power is dynamically adjusted. A continuous gradient adjustment mode is adopted in the second temperature range, and a pulse fine-tuning mode is adopted in the third temperature threshold. The pressure dimension control subunit is used to control the second analysis result, generate a second optimization strategy, and obtain a second optimization result, specifically including: Based on the second analysis result, when the pressure data inside the tank approaches the safety threshold, a graded pressure reduction measure is triggered; The graded pressure reduction measures are implemented in stages according to the magnitude of the pressure increase, including Level 1 pressure reduction, Level 2 pressure reduction, and Level 3 pressure reduction, specifically including: The first-level pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a first preset range when the pressure data inside the tank reaches a first safety threshold. The secondary pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a second preset range when the pressure inside the tank reaches a second safety threshold, while simultaneously reducing the heating rate to a first heating rate. The three-stage pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a third preset range when the pressure inside the tank reaches a third safety threshold, while simultaneously reducing the heating rate to a second heating rate. The calibration dimension control subunit is used to control the third analysis result, generate a third optimization strategy, and obtain a third optimization result, specifically including: Based on the third analysis results, independent temperature control compensation is performed on the n calibration channels.

[0013] As a preferred embodiment of the cryogenic environment adaptive constant temperature control system based on digital twins described in this invention, the feedback unit includes a dynamic comparison subunit, a deviation identification subunit, and a feedback output subunit. The dynamic comparison subunit is used to receive the optimization results, compare them with the analysis results in real time, and establish a comparison matrix for temperature, pressure and calibration dimensions. The deviation identification subunit is used to identify deviation information based on the comparison matrix; Deviation information includes temperature-dimensional deviation information, pressure-dimensional deviation information, and calibration-dimensional deviation information; The feedback output subunit is used to transmit deviation information to the control unit and the dynamic update unit according to a preset priority. The pressure dimension deviation information is preferentially fed back to the control unit, the temperature dimension deviation information is preferentially fed back to the dynamic update unit, and the calibration dimension deviation is synchronously fed back to both the control unit and the dynamic update unit.

[0014] As a preferred embodiment of the cryogenic environment adaptive constant temperature control system based on digital twin described in this invention, wherein: the deviation information triggers the control unit to correct the optimization strategy, and at the same time drives the analysis module to update the mapping accuracy; The temperature dimension deviation information includes: the real-time temperature field deviation when the temperature deviation exceeds the limit, the coordinates of the temperature inaccuracy area, and the temperature field uniformity data and temperature field stability data after the control unit is executed, respectively, and the differences between the corresponding data in the temperature field state information. The pressure dimension deviation information includes: the difference between the tank pressure data when the pressure is close to the safety threshold and the safety threshold, the pressure rise rate and the pressure fluctuation curve after the control unit is executed, and the difference between the pressure change rate and the corresponding data in the pressure field state information. The calibration dimension deviation information includes: the error increment when the calibration channel interference level is upgraded, the calibration data of the affected sensor and the synchronization error of the calibration channel after the control unit is executed, and the difference between the calibration accuracy of the short sensor and the corresponding data in the calibration channel status information.

[0015] The beneficial effects of this invention are as follows: By coordinating the acquisition module, analysis module, and control module, dynamically updated cryogenic device status information is constructed, and optimization strategies are generated from multiple dimensions to form closed-loop control. This can improve the uniformity and stability of the temperature field in the cryogenic environment, increase calibration efficiency and adaptability of short sensors, establish a pressure-graded response mechanism, and solve problems such as insufficient temperature control accuracy, high safety risks, and calibration shortcomings of traditional devices, thus meeting the needs of high-precision fields. Attached Figure Description

[0016] Figure 1 This is a basic flowchart of a cryogenic environment adaptive constant temperature control system based on digital twin, provided as an embodiment of the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0018] Example, refer to Figure 1 A cryogenic environment adaptive constant temperature control system based on digital twin is provided, including: a data acquisition module, an analysis module and a control module; The acquisition module is used to collect the operating data of the cryogenic unit and transmit the operating data to the analysis module; The analysis module is used to build and dynamically update the status information of the cryogenic device based on the operating data. It analyzes the operating data and status information from the dimensions of temperature, pressure and calibration, obtains the analysis results, and transmits the analysis results to the control module. The control module is used to generate optimization strategies based on the analysis results, obtain optimization results, dynamically identify deviation changes between the optimization results and the analysis results and obtain deviation information, and feed the deviation information back to the analysis module.

[0019] In one embodiment, the acquisition module collects real-time temperature field distribution data (multi-point temperature values ​​in the range of -196℃ to -80℃), tank pressure data (real-time monitoring values ​​of 0.1~1.5MPa), calibration channel status data (synchronous response signals of 4 to 6 channels), and refrigeration and heating operation data (liquid nitrogen flow rate, heating power output value) of the cryogenic device, and transmits them to the analysis module. The analysis module performs progressive analysis according to the pressure dimension (first priority), temperature dimension (second priority), and calibration dimension (third priority): the pressure dimension calculates the rate of change (0.05MPa / min) based on the tank pressure data. The system generates pressure fluctuation curves during temperature regulation and analyzes the correlation between exceeding the limit and the heating rate (probability of pressure exceeding the limit at a heating rate of 0.5℃ / min). In the temperature dimension, it calculates the deviation between the actual and target temperatures using temperature field distribution data (actual temperature -150.3℃ when the target is -150℃, deviation -0.3℃), and statistically analyzes the temperature field uniformity (extreme temperature difference of 50mK) and stability over 10 minutes (fluctuation amplitude ±10mK) within the range of -180~-160℃. In the calibration dimension, it statistically analyzes the synchronization error (e.g., ±2mK) of 4 to 6 channels and simulates different insertion depths (e.g., 50mm, 100mm, 2...). The response characteristics of the short sensor at a depth of 00mm were analyzed, and the calibration accuracy (±3mK) at a depth of 150mm was calculated. Interference levels were defined (e.g., the indication deviation ≤5mK at the first interference level). After the analysis results were pushed to the control module, the control unit generated an optimization strategy: For the inaccuracy region (e.g., the coordinate region X100-Y200), the synergistic ratio of liquid nitrogen cooling capacity (e.g., from 5L / min to 4.5L / min) and heating power (e.g., from 200W to 220W) was dynamically adjusted. Continuous gradient adjustment was used in the range of -120~-100℃, and pulsed fine-tuning was used at the -196℃ threshold (each adjustment...). (The duration is 2 seconds); In terms of pressure, when the pressure inside the tank reaches 0.8MPa (first safety threshold), the opening of the release valve is adjusted to 20% (first preset range); when it reaches 1.0MPa (second safety threshold), the opening is adjusted to 50% and the heating rate is reduced to 0.3℃ / min (first heating rate); when it reaches 1.2MPa (third safety threshold), the opening is adjusted to 80% and the heating rate is reduced to 0.1℃ / min (second heating rate); In terms of calibration, independent temperature control compensation is implemented for 4 to 6 channels (e.g., channel 1 compensation +1mK), and the sensor is inserted at a depth of 150mm to optimize the temperature field and improve the adaptability of short sensors.The feedback unit compares the optimization results with the analysis results to establish a three-dimensional comparison matrix: the temperature dimension identifies the difference between the actual improvement value of temperature field uniformity (from 50mK to 30mK) and the virtual state information (20mK); the pressure dimension calculates the deviation between the fluctuation curve after decompression and the simulated curve (±0.02MPa); the calibration dimension calculates the difference between the optimized value of the synchronization error of the statistical channel (from ±2mK to ±1mK) and the virtual data (±1mK); the deviation information is fed back according to priority: pressure deviation is given priority to drive the control unit to correct the decompression strategy, temperature deviation is given priority to update the virtual accuracy of the temperature field, and calibration deviation is used to simultaneously optimize the control strategy and virtual accuracy, forming a "collection-analysis-optimization-feedback" closed loop to achieve adaptive constant temperature control in the cryogenic environment.

[0020] The data acquisition module includes a sensing unit and a scheduling unit; The sensing unit is used to collect temperature field distribution data, tank pressure data, calibration channel status data, and refrigeration and heating operation data of the cryogenic device; The scheduling unit is used to adjust the sampling frequency and transmission priority of the sensing nodes in real time based on the status information; Status information includes temperature field status information, pressure field status information, and calibration channel status information; Temperature field status information includes virtual data on the temperature field distribution of the cryogenic device; Pressure field status information includes virtual data on the tank pressure of the cryogenic unit; The calibration channel status information includes virtual data of the calibration channel for the cryogenic device; The sensing nodes include temperature sensors, pressure transmitters, flow meters, and calibration signal receivers.

[0021] The analysis module includes a twin modeling unit, a dynamic update unit, and an analysis unit; The twin modeling unit is used to construct status information based on the operational data transmitted by the acquisition module; The dynamic update unit is used to receive deviation information transmitted by the feedback unit and real-time operating data of the acquisition module, dynamically correct the status information, and update the virtual accuracy of the temperature field, the virtual accuracy of the pressure field, and the virtual accuracy of the calibration channel.

[0022] The analysis unit includes a temperature dimension analysis subunit, a pressure dimension analysis subunit, and a calibration dimension analysis subunit; The analysis results include the first analysis result, the second analysis result, and the third analysis result; The temperature dimension analysis subunit is used to obtain the first analysis result; The temperature dimension analysis subunit calculates the temperature deviation between the actual temperature and the target temperature based on the temperature field state information and the temperature field distribution data, and statistically analyzes the temperature field uniformity data and temperature field stability data within the first temperature range and within the first unit time, thereby identifying temperature inaccuracy areas and potential inaccuracy trends. Temperature field uniformity data includes regional temperature difference extremes, temperature difference distribution ratios, and gradient change rates; Temperature field stability data includes fluctuation amplitude, fluctuation frequency, and trend offset; Information on temperature inaccuracy regions includes spatial coordinate range, degree of inaccuracy, type of inaccuracy, and regional correlation. Potential inaccuracy trends include potential inaccuracy areas, evolution of inaccuracy levels, trends in the correlation of triggering factors, and critical time points; The first analysis results include temperature deviation values, temperature field uniformity data, temperature field stability data, information on temperature inaccuracy areas, and potential inaccuracy trends.

[0023] In one embodiment, a temperature dimension analysis is performed on the temperature field distribution data to obtain a first analysis result: First, the deviation between the actual temperature and the target temperature is calculated using the temperature field distribution data (such as real-time temperature measurements at multiple points within the -196℃ to -80℃ range in a cryogenic device). For example, if the target temperature is -150℃ and the actual temperature in a certain area is -150.2℃, the deviation is -0.2℃. Second, the temperature field uniformity data within a first temperature range (such as -180℃ to -160℃) is statistically analyzed, including the extreme temperature difference in the region (such as a maximum temperature difference of 40mK), the proportion of temperature difference distribution (such as 85% of the region having a temperature difference ≤20mK), and the gradient change rate (such as a temperature difference change of 5mK per centimeter). Simultaneously, the temperature within a first unit time (such as 10 minutes) is statistically analyzed. Field stability data includes fluctuation amplitude (e.g., ±10 mK), fluctuation frequency (e.g., 3 times per minute), and trend offset (e.g., temperature drift of 2 mK per hour). Furthermore, it identifies temperature inaccuracy areas, defining their spatial coordinate range (e.g., the area within the device from X0-Y50 to X30-Y80), degree of inaccuracy (e.g., deviation exceeding 50 mK), type of inaccuracy (e.g., localized overheating), and regional correlation (e.g., spatial correlation with pipeline leaks). Finally, it uses a digital twin to predict potential inaccuracy trends, including potential inaccuracy areas (e.g., the area near valves), the evolution of inaccuracy levels (e.g., the deviation is expected to increase to 60 mK within 1 hour), the trend of inducing factors (e.g., correlation with heating power fluctuations), and critical time points (e.g., the inaccuracy threshold is expected to be reached after 2 hours). The final analysis results, incorporating the above data, provide a precise basis for temperature control.

[0024] The pressure dimension analysis subunit is used to obtain the second analysis results; The pressure dimension analysis subunit calculates the pressure change rate based on the pressure field state information and the pressure data inside the tank, generates a pressure fluctuation curve during the temperature regulation process, analyzes the correlation between the pressure data exceeding the limit inside the tank and the heating rate based on the pressure fluctuation curve, and generates pressure safety early warning information and pressure regulation effect. The second analysis results include pressure change rate, pressure fluctuation curve, correlation data, pressure safety early warning information, and pressure control effect.

[0025] In one embodiment, pressure dimension analysis is performed on the tank pressure data to obtain a second analysis result: First, the pressure change rate (e.g., 0.05 MPa / min) is calculated based on real-time monitoring data of the tank pressure (e.g., dynamic change value from 0.1 MPa to 1.2 MPa); second, a pressure fluctuation curve is generated during the temperature regulation process, recording the pressure change over time under different heating powers (e.g., 200 W to 500 W); based on the fluctuation curve, the correlation data between the tank pressure exceeding the standard (e.g., exceeding the 0.8 MPa safety threshold) and the heating rate (e.g., 0.5 °C / min to 2 °C / min) is analyzed, and a "heating rate - pressure increase" correspondence model is established (e.g., for every 0.5 °C / min increase in the heating rate, the probability of pressure exceeding the standard increases by 20%); simultaneously, pressure safety early warning information is generated, including the warning level (e.g., a level one warning corresponds to a pressure of 0.7 MPa, and a level two warning corresponds to 0.8 MPa) and triggering conditions; the pressure regulation effect of different pressure reduction measures is simulated through a digital twin (e.g., the pressure drop rate is 0.03 MPa / min when the release valve opening is 20%). The final analysis results include pressure change rate, fluctuation curve, correlation data, early warning information, and simulation effects, providing quantitative support for pressure safety prevention and control.

[0026] The calibration dimension analysis subunit is used to obtain the second analysis results; The calibration dimension analysis subunit calculates the synchronization error of n calibration channels based on the calibration channel status information and the calibration channel status data. By simulating the sensor response characteristics at different insertion depths, it calculates the calibration accuracy of the short sensor inserted at the first depth threshold, defines the interference level of the calibration channel, and generates calibration path suggestions. The third analysis results include the synchronization error of n calibration channels, the calibration accuracy of short sensors, the interference level of calibration channels, and calibration path recommendations; The calibration channel interference levels include a first interference level, a second interference level, and a third interference level, specifically including: The first level of interference includes the temperature reading deviation of each calibration channel within the first deviation range and the synchronization error within the second deviation range when n calibration channels are calibrated in parallel, indicating that there is no mutual influence between calibration channels. The second level of interference includes temperature reading deviations in each calibration channel within the third deviation range and synchronization errors within the fourth deviation range, indicating that the interference does not affect the validity of the calibration results. The third level of interference includes temperature readings from each calibration channel falling within the fifth deviation range and synchronization errors falling within the sixth deviation range. This indicates that interference causes calibration data to exceed the allowable error range, requiring the suspension of parallel calibration and the isolation adjustment of the calibration channels.

[0027] In one embodiment, a calibration dimension analysis is performed on the calibration channel status data to obtain a third analysis result: First, based on the calibration channel status data (e.g., temperature response signals from 4 to 6 channels), the synchronization error is statistically analyzed, and the time difference between the temperature measurement value and the standard value of each channel is calculated (e.g., the synchronization error between channel 1 and channel 2 is ≤5ms); Second, the response characteristics of a short sensor (e.g., 300mm in length) at different insertion depths (e.g., 50mm, 100mm, 200mm) are simulated using a digital twin, and an "insertion depth - measurement deviation" curve is plotted; The calibration accuracy (e.g., ±3mK) at the first depth threshold (e.g., 150mm) is calculated; Based on the degree of mutual influence when each channel works in parallel, the interference level is defined: The first interference level is a temperature indication deviation ≤5mK and a synchronization error ≤10ms, with no mutual influence; the second interference level is an indication deviation of 6-10mK and a synchronization error of 11-20ms, which does not affect the validity of the results; the third interference level is an indication deviation >10mK and a synchronization error >20ms, requiring the parallel calibration to be paused. Simultaneously, calibration path suggestions are generated (such as prioritizing the use of channels with low interference levels for batch calibration). This ultimately results in a third set of analytical results, including synchronization error, calibration accuracy, interference level, and path suggestions, improving calibration efficiency and accuracy.

[0028] The priority for analyzing the temperature, pressure, and calibration dimensions includes: The pressure dimension is the highest priority; Temperature is the second priority. The calibration dimension is the third priority. Priority is dynamically verified through status information. When the virtual mapping deviation of one dimension exceeds the threshold, the priority of one dimension is increased to the first priority.

[0029] In one embodiment, the priority of multi-dimensional analysis follows the logic of "pressure dimension (first priority) → temperature dimension (second priority) → calibration dimension (third priority)": First, pressure dimension data is processed first. When the pressure inside the tank approaches the safety threshold (e.g., 0.7 MPa), pressure analysis is immediately initiated and an early warning is generated to prioritize system operation safety. Second, temperature dimension analysis is performed. After the pressure stabilizes (e.g., drops below 0.5 MPa), temperature field uniformity and stability data are calculated, and temperature control strategies are adjusted. Finally, calibration dimension analysis is performed. After the temperature field stabilizes (e.g., fluctuation amplitude ≤ 15 mK), channel synchronization error and interference level assessment are conducted. If an anomaly occurs in a certain dimension (e.g., temperature field virtual mapping deviation exceeds 30 mK), its priority is temporarily raised to first, and it is analyzed and corrected first (e.g., temperature control parameters are optimized first) to ensure that key indicators meet the standards first.

[0030] The control module includes a regulation unit and a feedback unit; The control unit includes a temperature dimension control subunit, a pressure dimension control subunit, and a calibration dimension control subunit; The optimization strategies include the first optimization strategy, the second optimization strategy, and the third optimization strategy; The optimization results include the first optimization result, the second optimization result, and the third optimization result; The temperature control subunit is used to control the first analysis result, generate the first optimization strategy, and obtain the first optimization result, specifically including: Based on the first analysis results, the coordinated ratio range of liquid nitrogen cooling capacity and heating power is dynamically adjusted for the temperature inaccuracy region information. A continuous gradient adjustment mode is adopted in the second temperature range, and a pulse fine-tuning mode is adopted in the third temperature threshold.

[0031] In one embodiment, optimization is performed based on the first analysis result in the temperature dimension to generate a first optimized result: For the temperature inaccuracy region (e.g., the X0-Y50 to X30-Y80 region, with a deviation of -0.2℃), the synergistic ratio of liquid nitrogen cooling capacity (e.g., from 5L / min to 4.8L / min) and heating power (e.g., from 300W to 320W) is dynamically adjusted to form a "cooling-heating" linkage regulation scheme; in the second temperature range (e.g., -120℃ to -100℃), a continuous gradient adjustment mode is adopted, gradually approaching the target temperature in increments of 5℃; at the third temperature threshold (e.g., -196℃), a pulse fine-tuning mode is adopted, with a 2-second cycle and ±5W power fluctuation for precise temperature control. Through the above strategies, the temperature field uniformity is optimized from 40mK to 25mK, and the stability is improved from ±10mK to ±5mK, forming the first optimized result.

[0032] The pressure dimension control subunit is used to control the second analysis results, generate a second optimization strategy, and obtain a second optimization result, specifically including: According to the second analysis results, when the pressure data inside the tank approaches the safety threshold, a graded pressure reduction measure is triggered. The graded pressure reduction measures are implemented according to the degree of pressure increase, including Level 1 pressure reduction, Level 2 pressure reduction, and Level 3 pressure reduction, specifically including: The first-level pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a first preset range when the pressure data inside the tank reaches the first safety threshold. The secondary pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a second preset range when the pressure inside the tank reaches a second safety threshold, while simultaneously reducing the heating rate to a first heating rate. The three-stage pressure reduction includes dynamically adjusting the opening of the pressure relief valve to the third preset range when the pressure inside the tank reaches the third safety threshold, while simultaneously reducing the heating rate to the second heating rate.

[0033] In one embodiment, optimization is performed based on the second analysis results of the pressure dimension to generate a second optimized result: when the pressure inside the tank reaches the first safety threshold of 0.8 MPa, a first-level pressure reduction is triggered, dynamically adjusting the opening of the pressure relief valve to 10%-20%; when it reaches the second safety threshold of 1.0 MPa, a second-level pressure reduction is triggered, adjusting the opening to 30%-50%, while simultaneously reducing the heating rate from 0.5℃ / min to 0.3℃ / min; when it reaches the third safety threshold of 1.2 MPa, a third-level pressure reduction is triggered, adjusting the opening to 60%-80%, and reducing the heating rate to 0.1℃ / min. Through these graded pressure reduction measures, the duration of pressure exceeding the limit is shortened from 5 minutes to 1 minute, and the pressure fluctuation amplitude is reduced from ±0.1 MPa to ±0.03 MPa, forming the second optimized result.

[0034] The calibration dimension control subunit is used to control the third analysis results, generate a third optimization strategy, and obtain the third optimization results, specifically including: Based on the third analysis results, independent temperature control compensation was implemented for the n calibration channels.

[0035] In one embodiment, optimization is performed based on the third analysis results of the calibration dimension to generate a third optimized result: independent temperature control compensation is implemented for 4 to 6 calibration channels, such as compensating +2mK for channel 2 and -1mK for channel 4, to reduce the inherent error between channels; for the first depth threshold of 150mm, the sensor insertion angle is optimized (e.g., at 30° to the horizontal) to reduce temperature field disturbances, improving the calibration accuracy of the short sensor from ±3mK to ±2mK; for channel 6, which has the second highest interference level, a time-sharing calibration mode is adopted (e.g., channel 6 operates from 0 to 10 minutes, and channel 7 operates from 11 to 20 minutes) to avoid mutual interference. The final result is a third optimized result that includes compensation parameters, insertion scheme, and time-sharing strategy.

[0036] The feedback unit includes a dynamic comparison subunit, a deviation identification subunit, and a feedback output subunit; The dynamic comparison subunit is used to receive the optimization results, compare them with the analysis results in real time, and establish comparison matrices for temperature, pressure and calibration dimensions. The deviation identification subunit is used to identify deviation information based on the comparison matrix; Deviation information includes temperature-dimensional deviation information, pressure-dimensional deviation information, and calibration-dimensional deviation information; The feedback output subunit is used to transmit deviation information to the control unit and the dynamic update unit according to preset priorities; Pressure deviation information is fed back to the control unit first, temperature deviation information is fed back to the dynamic update unit first, and calibration deviation is fed back to both the control unit and the dynamic update unit simultaneously.

[0037] In one embodiment, the feedback unit establishes a three-dimensional comparison matrix through a dynamic comparison subunit: In the temperature dimension, it compares the difference (15mK) between the optimized temperature field uniformity (25mK) and the analysis result (40mK); in the pressure dimension, it compares the deviation (±0.02MPa) between the actual decompression curve and the simulated curve; and in the calibration dimension, it compares the difference (2ms) between the optimized channel synchronization error value (3ms) and the virtual state information (5ms). The deviation identification subunit extracts deviation information from this matrix: in the temperature dimension, this includes a temperature field deviation of 15mK and a correction value for the coordinates of the misaligned area; in the pressure dimension, this includes a pressure difference of 0.05MPa from the safety threshold and a rate difference of 0.01MPa / min between the actual and simulated fluctuation curves; and in the calibration dimension, this includes an error increment of 2mK when the interference level is upgraded and a sensor calibration data deviation of 1mK. The feedback output subunit transmits data according to priority: pressure deviations are first sent to the control unit to correct the decompression strategy, temperature deviations are first sent to the dynamic update unit to optimize virtual accuracy, and calibration deviations are simultaneously transmitted to both units, achieving bidirectional optimization.

[0038] Deviation information triggers the control unit to correct the optimization strategy, and at the same time drives the analysis module to update the mapping accuracy; Temperature dimension deviation information includes: real-time temperature field deviation when temperature deviation exceeds the limit, coordinates of temperature inaccuracy area, and the differences between temperature field uniformity data and temperature field stability data after the control unit is executed, and the corresponding data in temperature field state information. Pressure dimension deviation information includes: the difference between the tank pressure data when the pressure is close to the safety threshold and the safety threshold, the pressure rise rate and the pressure fluctuation curve after the control unit is executed, and the difference between the pressure change rate and the corresponding data in the pressure field state information. The calibration dimension deviation information includes: the error increment when the calibration channel interference level is upgraded, the calibration data of the affected sensors and the synchronization error of the calibration channel after the control unit is executed, and the difference between the calibration accuracy of the short sensor and the corresponding data in the calibration channel status information.

[0039] In one embodiment, deviation information drives the system to form a closed-loop optimization: a temperature dimension deviation (e.g., 15 mK) triggers a dynamic update unit to adjust the thermal conductivity parameters of the virtual temperature field model (e.g., from 0.02 W / ( ) Corrected to 0.022W / ( The system improves virtual accuracy; pressure dimension deviations (e.g., 0.05 MPa) drive the control unit to lower the first-level decompression threshold from 0.8 MPa to 0.75 MPa, enhancing early warning timeliness; calibration dimension deviations (e.g., 2 ms) simultaneously prompt the control unit to optimize the time-sharing calibration interval (extending it from 10 minutes to 15 minutes) and drive the dynamic update unit to correct the channel interference model parameters. Through bidirectional feedback of deviation information, the system achieves continuous calibration of the "virtual model-physical system," resulting in a 30% improvement in overall temperature control accuracy, a 20% improvement in pressure safety response speed, and a 40% improvement in calibration efficiency.

[0040] This invention achieves a targeted breakthrough by using a digital twin-based cryogenic environment adaptive constant temperature control system to precisely address the shortcomings of traditional cryogenic temperature control technologies. Addressing the poor temperature field uniformity caused by traditional devices relying on single-point feedback, it constructs a virtual mapping of the entire temperature field and combines multi-dimensional dynamic adjustment to improve the uniformity in the -185 to -80℃ range from 50mK to within 25mK, and optimizes the single-point 10-minute stability at -196℃ from 20mK to ±5mK, completely resolving the pain point of high-precision experiments requiring consistent temperature field. Addressing the shortcomings of low efficiency and poor adaptability in calibration systems, it controls the synchronization error to within 3ms through parallel collaboration of 4 to 6 calibration channels and quantitative control of interference levels. Optimization of short sensor insertion depth (e.g., calibration accuracy of ±2mK at a 150mm threshold) significantly improves the adaptability of short sensors of 300mm and below, resolving the contradiction between efficiency and accuracy in batch calibration. Addressing the issue of lagging pressure safety control, a graded response mechanism based on the rate of pressure change is established, stabilizing pressure control accuracy at ±0.03MPa, avoiding the risk of sudden pressure increases during heating, and compensating for the lack of dynamic coordination between temperature and pressure regulation. Through a closed-loop process of "acquisition-analysis-optimization-feedback," traceability of cryogenic temperature range values ​​is achieved, solving the problem of poor data comparability in traditional devices. Simultaneously, it dynamically responds to operating conditions such as temperature field drift and pressure fluctuations, overcoming the limitations of static control strategies. Ultimately, the system fully meets the stringent requirements of high-precision fields such as biomedicine and aerospace for cryogenic environments, driving the upgrade of cryogenic temperature control technology from "experience-based regulation" to "precision regulation driven by digital twins."

[0041] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A cryogenic environment adaptive isothermal control system based on digital twin, characterized in that, include: The module consists of a data acquisition module, an analysis module, and a control module. The acquisition module is used to acquire the operating data of the cryogenic device and transmit the operating data to the analysis module; The analysis module is used to construct and dynamically update the status information of the cryogenic device based on the operating data, analyze the operating data and status information from the dimensions of temperature, pressure and calibration, obtain the analysis results, and transmit the analysis results to the control module. The control module is used to generate an optimization strategy based on the analysis results, obtain optimization results, dynamically identify deviation changes between the optimization results and the analysis results and obtain deviation information, and feed the deviation information back to the analysis module.

2. The cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 1, characterized in that, The acquisition module includes a sensing unit and a scheduling unit; The sensing unit is used to collect temperature field distribution data, tank pressure data, calibration channel status data, and refrigeration and heating operation data of the cryogenic device. The scheduling unit is used to adjust the sampling frequency and transmission priority of the sensing nodes in real time according to the status information. The status information includes temperature field status information, pressure field status information, and calibration channel status information; The temperature field state information includes virtual data of the temperature field distribution of the cryogenic device; The pressure field status information includes virtual data of the internal pressure of the cryogenic device. The calibration channel status information includes virtual data of the calibration channel of the cryogenic device; The sensing nodes include temperature sensors, pressure transmitters, flow meters, and calibration signal receivers.

3. The cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 2, characterized in that, The analysis module includes a twin modeling unit, a dynamic update unit, and an analysis unit; The twin modeling unit is used to construct the status information based on the operational data transmitted by the acquisition module; The dynamic update unit is used to receive deviation information transmitted by the feedback unit and real-time operating data of the acquisition module, dynamically correct the status information, and update the virtual accuracy of the temperature field, the virtual accuracy of the pressure field, and the virtual accuracy of the calibration channel.

4. The cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 3, characterized in that, The analysis unit includes a temperature dimension analysis subunit, a pressure dimension analysis subunit, and a calibration dimension analysis subunit; The analysis results include the first analysis result, the second analysis result, and the third analysis result; The temperature dimension analysis subunit is used to obtain the first analysis result; The temperature dimension analysis subunit calculates the temperature deviation between the actual temperature and the target temperature based on the temperature field state information and the temperature field distribution data, and statistically analyzes the temperature field uniformity data and temperature field stability data within the first temperature range and within the first unit time, thereby identifying temperature inaccuracy area information and potential inaccuracy trends. The temperature field uniformity data includes regional temperature difference extremes, temperature difference distribution ratios, and gradient change rates. The temperature field stability data includes fluctuation amplitude, fluctuation frequency, and trend offset; The temperature misalignment area information includes spatial coordinate range, degree of misalignment, type of misalignment, and regional correlation. The potential inaccuracy trend includes potential inaccuracy regions, evolution of inaccuracy degree, trend of causal correlation, and critical time nodes; The first analysis results include the temperature deviation value, temperature field uniformity data, temperature field stability data, temperature inaccuracy region information, and potential inaccuracy trend.

5. The cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 3, characterized in that, The pressure dimension analysis subunit is used to obtain the second analysis result; The pressure dimension analysis subunit calculates the pressure change rate based on the pressure field state information and the pressure data inside the tank, generates a pressure fluctuation curve during the temperature regulation process, analyzes the correlation between the pressure data exceeding the standard inside the tank and the heating rate based on the pressure fluctuation curve, and generates pressure safety early warning information and pressure regulation effect. The second analysis results include the pressure change rate, pressure fluctuation curve, correlation data, pressure safety early warning information, and pressure control effect.

6. The cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 4, characterized in that, The calibration dimension analysis subunit is used to obtain the second analysis result; The calibration dimension analysis subunit calculates the synchronization error of n calibration channels based on the calibration channel status information and the calibration channel status data. By simulating the sensor response characteristics at different insertion depths, it calculates the calibration accuracy of the short sensor inserted at the first depth threshold, defines the calibration channel interference level, and generates calibration path suggestions. The third analysis results include the synchronization error of the n calibration channels, the calibration accuracy of the short sensor, the interference level of the calibration channels, and the calibration path recommendations; The calibration channel interference levels include a first interference level, a second interference level, and a third interference level, specifically including: The first interference level includes the temperature reading deviation of each calibration channel within the first deviation range and the synchronization error within the second deviation range when n calibration channels are calibrated in parallel, indicating that there is no mutual influence between the calibration channels. The second interference level includes temperature reading deviations of each calibration channel within the third deviation range and synchronization errors within the fourth deviation range, indicating that the interference does not affect the validity of the calibration results; The third interference level includes temperature reading deviations of each calibration channel within the fifth deviation range and synchronization errors within the sixth deviation range. This indicates that interference causes calibration data to exceed the allowable error range, and parallel calibration is suspended while calibration channel isolation adjustments are performed.

7. The cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 4, characterized in that, The priority for analyzing the temperature, pressure, and calibration dimensions includes: The pressure dimension is of the highest priority. The temperature dimension is of second priority. The calibration dimension is the third priority. The priority is dynamically verified through status information. When the virtual mapping deviation of one dimension exceeds the threshold, the priority of that one dimension is increased to the first priority.

8. A cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 4, characterized in that, The control module includes a regulation unit and a feedback unit; The control unit includes a temperature dimension control subunit, a pressure dimension control subunit, and a calibration dimension control subunit; The optimization strategies include a first optimization strategy, a second optimization strategy, and a third optimization strategy; The optimization results include a first optimization result, a second optimization result, and a third optimization result; The temperature dimension control subunit is used to control the first analysis result, generate a first optimization strategy, and obtain a first optimization result, specifically including: Based on the first analysis results, for the temperature misalignment region information, the coordinated ratio range of liquid nitrogen cooling capacity and heating power is dynamically adjusted. A continuous gradient adjustment mode is adopted in the second temperature range, and a pulse fine-tuning mode is adopted in the third temperature threshold. The pressure dimension control subunit is used to control the second analysis result, generate a second optimization strategy, and obtain a second optimization result, specifically including: Based on the second analysis result, when the pressure data inside the tank approaches the safety threshold, a graded pressure reduction measure is triggered; The graded pressure reduction measures are implemented in stages according to the magnitude of the pressure increase, including Level 1 pressure reduction, Level 2 pressure reduction, and Level 3 pressure reduction, specifically including: The first-level pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a first preset range when the pressure data inside the tank reaches a first safety threshold. The secondary pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a second preset range when the pressure inside the tank reaches a second safety threshold, while simultaneously reducing the heating rate to a first heating rate. The three-stage pressure reduction includes dynamically adjusting the opening of the pressure relief valve to a third preset range when the pressure inside the tank reaches a third safety threshold, while simultaneously reducing the heating rate to a second heating rate. The calibration dimension control subunit is used to control the third analysis result, generate a third optimization strategy, and obtain a third optimization result, specifically including: Based on the third analysis results, independent temperature control compensation is performed on the n calibration channels.

9. A cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 8, characterized in that, The feedback unit includes a dynamic comparison subunit, a deviation identification subunit, and a feedback output subunit; The dynamic comparison subunit is used to receive the optimization results, compare them with the analysis results in real time, and establish a comparison matrix for temperature, pressure and calibration dimensions. The deviation identification subunit is used to identify deviation information based on the comparison matrix; Deviation information includes temperature-dimensional deviation information, pressure-dimensional deviation information, and calibration-dimensional deviation information; The feedback output subunit is used to transmit deviation information to the control unit and the dynamic update unit according to a preset priority. The pressure dimension deviation information is preferentially fed back to the control unit, the temperature dimension deviation information is preferentially fed back to the dynamic update unit, and the calibration dimension deviation is synchronously fed back to both the control unit and the dynamic update unit.

10. A cryogenic environment adaptive constant temperature control system based on digital twin as described in claim 9, characterized in that, The deviation information triggers the control unit to correct the optimization strategy and simultaneously drives the analysis module to update the mapping accuracy. The temperature dimension deviation information includes: the real-time temperature field deviation when the temperature deviation exceeds the limit, the coordinates of the temperature inaccuracy area, and the temperature field uniformity data and temperature field stability data after the control unit is executed, respectively, and the differences between the corresponding data in the temperature field state information. The pressure dimension deviation information includes: the difference between the tank pressure data when the pressure is close to the safety threshold and the safety threshold, the pressure rise rate and the pressure fluctuation curve after the control unit is executed, and the difference between the pressure change rate and the corresponding data in the pressure field state information. The calibration dimension deviation information includes: the error increment when the calibration channel interference level is upgraded, the calibration data of the affected sensor and the synchronization error of the calibration channel after the control unit is executed, and the difference between the calibration accuracy of the short sensor and the corresponding data in the calibration channel status information.

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