A method, system, medium and product for operating control of large-capacity liquid helium storage

Abstract

A large-capacity liquid helium storage operation control method, system, medium and product, relating to the field of fixed-capacity gas storage tanks, the method comprising: collecting temperature data and pressure data of multiple height positions in the liquid helium storage tank, and constructing a temperature field distribution model; dividing the storage tank space of the liquid helium storage tank into grid units of a predetermined size, calculating the temperature gradient value of the temperature difference and distance between each grid unit and the adjacent unit; when the temperature gradient value of the target grid unit exceeds the preset gradient threshold value within a preset time length, determining the target area; based on the area position and temperature gradient value of the target area, calculating the adjustment parameter of the refrigeration power; controlling the refrigeration power output of the cold screen device in the target area, so that the temperature gradient value is reduced to below the preset gradient threshold value; set the current refrigeration power as the reference power value of the target area. The application can improve the adjustment accuracy of the refrigeration power, ensure the liquid helium storage effect while reducing energy consumption.

Description

TECHNICAL FIELD

[0001] The application relates to the field of fixed-volume gas storage tanks, in particular to a large-capacity liquid helium storage operation control method, system, medium and product. BACKGROUND

[0002] Liquid helium, as an important cryogenic refrigerant, is increasingly widely used in high-end manufacturing, medical imaging, scientific research and other fields. Due to the scarcity and high price of liquid helium resources, the leakage detection and recovery problem in the storage process has always been the focus of the industry. Near-zero evaporation technology realizes the long-term stable storage of liquid helium by liquefying the evaporated gas through a dynamic refrigeration system.

[0003] In related technologies, a near-zero evaporation system mainly consists of a cold screen device and a re-liquefaction device. The cold screen device cools the evaporated gas at the top of the storage tank to liquid helium temperature through a coil, and the re-liquefaction device re-liquefies and recovers these gases through a refrigeration cycle system. The system is equipped with a network of temperature and pressure sensors, which is adjusted in real time by a control system to maintain the pressure of the storage tank within a preset range (usually 0.1-1.2 MPa). This scheme has proven its effectiveness in small storage tanks.

[0004] However, when the volume of the storage tank increases, the temperature and pressure distribution in the large storage tank will be significantly uneven. This temperature unevenness will cause local pressure fluctuations, making it difficult for the refrigeration system to accurately determine the required refrigeration power. If the refrigeration power is too large, it will cause local overcooling and energy waste; if the refrigeration power is insufficient, it will not be able to compensate for heat leakage in time, resulting in continuous loss of liquid helium. SUMMARY

[0005] The application provides a large-capacity liquid helium storage operation control method, system, medium and product, which is used to improve the adjustment accuracy of refrigeration power and reduce energy consumption while ensuring the storage effect of liquid helium.

[0006] In a first aspect, the application provides a working control method for large-capacity liquid helium storage, applied to a liquid helium storage system. The method comprises: collecting temperature data and pressure data of multiple height positions in a liquid helium storage tank, and constructing a temperature field distribution model based on the temperature data and the pressure data; dividing the storage tank space of the liquid helium storage tank into grid units of a preset size, and calculating the ratio of the temperature difference and the distance between each grid unit and the adjacent unit as a temperature gradient value based on the temperature field distribution model; when the temperature gradient value of a target grid unit exceeds a preset gradient threshold value within a preset time length, determining a combination area of the target grid unit and adjacent threshold-exceeding grid units as a target area; calculating an adjustment parameter of the refrigeration power based on the area position and the temperature gradient value of the target area; controlling the refrigeration power output of the cold screen device in the target area according to the adjustment parameter, so that the temperature gradient value of the target area is reduced to below the preset gradient threshold value; and setting the current refrigeration power as a reference power value of the target area when the temperature gradient value of the target area does not exceed the preset gradient threshold value within a preset time length.

[0007] In the above embodiment, the liquid helium storage system constructs a temperature field model by collecting temperature and pressure data in the storage tank in real time, identifies the temperature gradient abnormal area based on grid analysis, and adjusts the refrigeration power accordingly, thereby achieving accurate monitoring and adjustment of the temperature distribution in the large-capacity liquid helium storage tank. The system can adaptively determine the reference refrigeration power of each area, which not only ensures the storage effect but also avoids energy waste, thereby significantly improving the operation efficiency of the liquid helium storage system.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of controlling the refrigeration power output of the cold screen device in the target area according to the adjustment parameter, so that the temperature gradient value of the target area is reduced to below the preset gradient threshold value, specifically comprises: determining the adjustment direction of the refrigeration power according to the positive and negative nature of the temperature gradient change rate, and calculating the corresponding correction coefficient based on the absolute value of the temperature gradient change rate; determining a new refrigeration power output value according to the current refrigeration power and the correction coefficient, and controlling the cold screen device to operate according to the refrigeration power output value; and repeatedly executing the steps of obtaining the temperature gradient change rate and adjusting the refrigeration power until the absolute value of the temperature gradient value of the target area is less than the preset gradient threshold value for a continuous preset number of times.

[0009] In the above embodiment, the liquid helium storage system monitors the change trend of the temperature gradient of the target area, dynamically adjusts the refrigeration power in combination with the change rate and direction, and uses a continuous monitoring and iterative optimization method to ensure that the temperature gradient is stable within the threshold range. This closed-loop feedback control mechanism enables the system to quickly respond to temperature abnormalities while avoiding excessive adjustment, thereby achieving accurate control of the refrigeration power.

[0010] In some embodiments of the first aspect, based on the target region position and the temperature gradient value, the step of calculating the adjustment parameter of the refrigeration power specifically comprises: calculating the spatial distance from each grid unit in the target region to the corresponding cold shield device based on the coordinate information of the target region; obtaining the temperature gradient value of each grid unit, and performing spatial weighting calculation on the temperature gradient value according to the spatial distance to obtain a weighted temperature gradient value; and determining the adjustment parameter of the refrigeration power according to the weighted temperature gradient value and a preset gradient threshold.

[0011] In the above embodiments, the liquid helium storage system processes the temperature gradient data by a spatial weighting calculation method, considers the relative position relationship between the grid unit and the cold shield device, and reasonably allocates the refrigeration resources. This power adjustment strategy based on spatial characteristics improves the uniformity of the refrigeration effect and reduces the local overcooling or undercooling phenomenon.

[0012] In some embodiments of the first aspect, after the step of determining the target region as the combined region of the target grid unit and the adjacent super-threshold grid unit, the method further comprises: obtaining the pressure value of each grid unit in the target region, calculating the pressure difference between the average pressure value of the target region and a preset standard pressure; when the pressure difference exceeds a preset pressure difference threshold, calculating a pressure relief rate parameter based on the pressure difference; controlling the pressure relief valve corresponding to the target region to release gas at the pressure relief rate parameter based on the pressure relief rate parameter; and recovering the released gas and transporting the released gas to a reliquefaction device for cooling and liquefaction.

[0013] In the above embodiments, the liquid helium storage system realizes accurate adjustment of the pressure in the storage tank by real-time monitoring of the pressure distribution and calculating the pressure difference, combined with an intelligent pressure relief control strategy. At the same time, through the gas recovery and reliquefaction process, the loss of liquid helium is minimized, and the resource utilization efficiency of the system is improved.

[0014] In some embodiments of the first aspect, the step of calculating the pressure relief rate parameter based on the pressure difference specifically comprises: obtaining the position of the grid unit with the maximum pressure value in the target region as a pressure relief priority region; calculating the flow resistance coefficient of the gas in the pipeline based on the distance from the pressure relief priority region to the nearest pressure relief valve, and calculating the theoretical pressure relief rate according to the pressure difference and the flow resistance coefficient; and selecting the minimum value of the theoretical pressure relief rate and a preset safe pressure relief rate as the pressure relief rate parameter.

[0015] In the above embodiments, the liquid helium storage system optimizes the pressure relief rate parameter by identifying the region with the maximum pressure and considering the pipeline resistance, to ensure the safety and controllability of the pressure relief process. This intelligent pressure relief scheme based on pressure distribution not only ensures the safety of the system, but also improves the pressure relief efficiency.

[0016] In some embodiments of the first aspect, after the step of recovering the relief gas and transporting the relief gas to the reliquefaction device for cooling and liquefaction, the method further comprises: obtaining real-time refrigeration power and liquefaction efficiency parameters of the reliquefaction device, calculating a minimum required refrigeration power based on the relief pressure rate parameter; when the real-time refrigeration power is less than the minimum required refrigeration power, starting a backup refrigeration unit and adjusting the power distribution ratio of each refrigeration unit according to the liquefaction efficiency parameter.

[0017] In the above embodiments, the liquid helium storage system intelligently allocates the work load of the refrigeration units by monitoring the operating state of the reliquefaction device, ensuring that the system has sufficient refrigeration capacity. This dynamic load distribution mechanism improves the reliability and efficiency of the system.

[0018] In some embodiments of the first aspect, after the step of starting the backup refrigeration unit and adjusting the power distribution ratio of each refrigeration unit according to the liquefaction efficiency parameter, the method further comprises: collecting the input power and output temperature of the refrigeration unit group after starting, calculating the energy efficiency ratio of each refrigeration unit, determining the refrigeration efficiency decay coefficient based on the deviation of the energy efficiency ratio from the nominal value; classifying each refrigeration unit according to the refrigeration efficiency decay coefficient, marking the refrigeration unit whose decay degree exceeds a preset threshold as an optimization object, and calculating the contribution rate of the optimization object to the total refrigeration capacity of the system; under the premise of ensuring that the total refrigeration capacity of the system meets the demand, determining the backup switching order of the optimization object based on the contribution rate, and gradually transferring the refrigeration load of the optimization object to the high-efficiency unit that is not the optimization object according to the backup switching order.

[0019] In the above embodiments, the liquid helium storage system optimizes the scheduling of the refrigeration equipment by evaluating the energy efficiency of the refrigeration units, ensuring that the system can still operate efficiently under equipment performance degradation. This preventive maintenance strategy prolongs the service life of the equipment and reduces the operation and maintenance cost.

[0020] In the second aspect, the embodiments of the present application provide a liquid helium storage system, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors invoke the computer instructions to enable the liquid helium storage system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0021] In the third aspect, the embodiments of the present application provide a computer program product comprising instructions, which, when executed on a liquid helium storage system, cause the liquid helium storage system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0022] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, including instructions, when the instructions are run on a liquid helium storage system, causing the liquid helium storage system to perform the method as described in the first aspect and any possible implementation manner of the first aspect.

[0023] It can be understood that the liquid helium storage system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved are referable to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] The one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0025] 1. Due to the adoption of the multi-point temperature and pressure data acquisition and the grid temperature field analysis method, combined with the adaptive refrigeration power adjustment mechanism, the system can accurately identify the temperature abnormal area in the storage tank and realize accurate refrigeration control, effectively solving the problems of uneven temperature distribution in the large-capacity storage tank and difficult accurate adjustment of refrigeration power in the prior art, thereby realizing uniform and stable distribution of the temperature field in the storage tank, improving the refrigeration efficiency, reducing the energy consumption, and ensuring long-term stable storage of liquid helium. The accurate control strategy based on grid analysis enables the system to avoid excessive refrigeration while ensuring the storage effect, achieving the optimal balance between the storage effect and energy efficiency.

[0026] 2. Due to the adoption of the temperature gradient change rate monitoring and dynamic power adjustment mechanism, combined with the continuous monitoring and iterative optimization closed-loop control strategy, the system can timely adjust the refrigeration power according to the temperature change trend, realize rapid and accurate temperature control, effectively solve the temperature fluctuation problem caused by the refrigeration power adjustment lag and untimely response in the prior art, and thereby realize stable control of the temperature gradient and avoid excessive adjustment and energy waste. This dynamic adjustment mechanism based on the change rate not only improves the response speed of the system, but also ensures the stability and accuracy of the temperature control.

[0027] 3. Due to the adoption of the real-time pressure monitoring and intelligent pressure relief control strategy, combined with the gas recovery and reliquefaction processing mechanism, the system can timely discover and handle pressure abnormalities, and maximize the recovery and utilization of released gas, effectively solving the problems of inaccurate pressure control and serious loss of liquid helium in the prior art, and thereby realizing accurate adjustment of the storage tank pressure and efficient utilization of liquid helium resources. This integrated pressure control and resource recovery scheme not only ensures the safety of the system, but also significantly improves the economic benefits, embodying the comprehensive advantages of the technical solution. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1is a flowchart of a working control method of the large-capacity liquid helium storage in the embodiment of the present application;

[0029] Figure 2 is another flowchart of a working control method of the large-capacity liquid helium storage in the embodiment of the present application;

[0030] Figure 3 is a schematic diagram of an entity device structure of the liquid helium storage system in the embodiment of the present application. DETAILED DESCRIPTION

[0031] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to be limiting of the present application. As used in the specification, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or" as used herein refer to any or all possible combinations of one or more of the associated listed items.

[0032] Hereinafter, the terms "first" and "second" are only for the purpose of description, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0033] To facilitate understanding, the application scenarios of the embodiments of the present application are introduced as follows.

[0034] A large particle accelerator institute needs to store a large amount of liquid helium for a long time for cooling superconducting magnets. The institute uses a 10000 liter liquid helium storage tank, which is internally installed with 20 groups of temperature sensors and 12 groups of pressure sensors, and 8 sets of cold screen devices. In daily operation, due to changes in external environment temperature and fluctuations in equipment operating state, temperature distribution in the storage tank is often uneven. Especially in the hot summer weather, the temperature gradient in some areas may suddenly rise to 0.8K / m, far exceeding the safety threshold of 0.3K / m. Such uneven temperature field not only increases the evaporation loss of liquid helium, but also may cause a sudden increase in local pressure, threatening the safety of the storage tank. The traditional refrigeration control mode is difficult to find and handle these local abnormalities in time, resulting in low system operation efficiency and safety hazards.

[0035] In the related art, the temperature control of the liquid helium storage tank can be realized by using a fixed measuring point temperature monitoring and a simple threshold control method. This method only monitors the temperature at a limited measuring point position, and increases the refrigeration power of the corresponding cold screen device when the temperature of the measuring point exceeds the preset threshold, which cannot realize accurate control of the temperature field of the entire storage tank space. The following introduces the scene of using the working control method of large-capacity liquid helium storage in the related art.

[0036] The institute initially adopted a temperature monitoring scheme based on fixed measuring points. Temperature sensors are arranged inside the tank, and when the temperature of a certain measuring point exceeds the threshold, the refrigeration power of the nearby cold screen device is increased. For example, when the temperature of the top measuring point is detected to rise, the power of the top cold screen is increased from 2kW to 3kW. However, due to the limited number of measuring points, the temperature field distribution cannot be fully grasped. At the same time, the simple temperature threshold judgment method cannot reflect the change characteristics of the temperature gradient, and often there are problems of refrigeration adjustment lag or excessive adjustment. In an actual operation, although all the measuring point temperatures are within the limit, a significant temperature gradient still forms between two adjacent measuring points, causing a sudden increase in local pressure, triggering a safety relief, and causing a loss of about 50 liters of liquid helium.

[0037] And by using the working control method of large-capacity liquid helium storage in the embodiments of the present application, the storage tank space is divided into grid cells of a preset size, the temperature gradient value of each grid cell is calculated based on the temperature field distribution model, and the temperature field distribution is accurately monitored and evaluated by combining the spatial distance for weighted calculation, which not only can timely find local temperature abnormalities, but also can realize accurate adjustment of the refrigeration power. The following introduces the scene of using the working control method of large-capacity liquid helium storage in the present application.

[0038] After applying the present scheme, the system uses a gridding analysis method to divide the storage tank space into 1000 grid cells, and constructs a complete temperature field model based on existing sensor data. When the system detects that the temperature gradient of a certain area continuously exceeds 0.3K / m, it immediately starts the accurate refrigeration control. For example, in a temperature abnormality event, the system found that a temperature gradient of 0.5K / m appeared in the middle of the storage tank. By calculating the spatial distance of this area to the surrounding cold screen devices, the system automatically adjusted the power distribution of the three related cold screens, so that the temperature gradient was reduced to a safe level within 15 minutes. At the same time, the system also monitors the pressure change in real time, and timely starts the intelligent relief and gas recovery to minimize the evaporation loss. One month of operation data shows that the liquid helium loss rate of the system is reduced by 30%, and the refrigeration energy consumption is reduced by 25%.

[0039] It can be seen that, by using the large-capacity liquid helium storage work control method in the embodiments of the present application, the problem of being unable to timely discover and handle local temperature abnormalities under the traditional fixed monitoring point monitoring mode can be effectively solved while realizing accurate monitoring of the temperature field, thereby realizing stable control of the temperature field of the liquid helium storage tank and improving the storage efficiency.

[0040] For ease of understanding, the method provided by the present embodiment is described in the flow below in combination with the above scenario. Please refer to Figure 1 A flowchart of the large-capacity liquid helium storage work control method in the embodiments of the present application is shown.

[0041] S101, temperature data and pressure data of multiple height positions in the liquid helium storage tank are collected, and a temperature field distribution model is constructed based on the temperature data and the pressure data.

[0042] The liquid helium storage tank represents a special container for storing liquid helium, has an adiabatic structure and a multi-layer shielding design, and usually adopts a vacuum sandwich structure to reduce heat loss; the temperature data refers to the temperature values measured at different height positions in the tank, with the unit of Kelvin (K); the pressure data represent the gas pressure values measured at the corresponding positions, with the unit of mega Pascal (MPa); and the temperature field distribution model refers to a mathematical model describing the spatial distribution characteristics of the temperature in the tank, which can be constructed by using a three-dimensional interpolation algorithm.

[0043] After the liquid helium storage system is started and runs, the temperature and pressure states in the tank need to be monitored in real time. Specifically, the liquid helium storage system first synchronously collects temperature and pressure data according to a preset sampling frequency (such as once every 5 seconds) through temperature sensors and pressure sensors pre-installed at different height positions in the tank. For a large-capacity storage tank, 4-8 sensors are usually arranged uniformly on each cross section, and a group of sensors is arranged every 0.5-1 meters along the height direction. After the collected data is filtered and calibrated, it is input into a pre-trained temperature field modeling algorithm to construct a three-dimensional temperature field model reflecting the temperature distribution state in the current tank.

[0044] In some embodiments, the construction of the temperature field distribution model can be achieved in various ways: optionally, the liquid helium storage system can adopt a radial basis function (RBF) based spatial interpolation method, first taking the collected discrete temperature data as interpolation nodes, then calculating the spatial distance matrix between each point, combining the Gaussian kernel function to generate the interpolation coefficient, and finally obtaining the continuous temperature field function; optionally, the liquid helium storage system can also adopt a polynomial regression method, taking the spatial coordinates as the independent variable and the temperature as the dependent variable, and fitting the temperature field polynomial expression by the least squares method. It can be understood that other interpolation or fitting methods can also be used to realize temperature field modeling, which is not limited here. In order to improve the accuracy of the model, it is recommended to select a suitable interpolation basis function according to the size of the storage tank and the arrangement of the sensors, and determine the optimal model parameters through cross-validation.

[0045] During the temperature field modeling process, the problem of data missing caused by sensor failure may be encountered. For this purpose, the liquid helium storage system adopts a data compensation mechanism: first, the abnormal sensor position is identified, then a local temperature change rule model is established based on the historical data of adjacent sensors, and the missing data is estimated combined with the physical constraint conditions (such as temperature gradient continuity). At the same time, the system will mark the compensated data points, appropriately reduce their weight in subsequent analysis, and ensure the reliability of the model. For example, when a sensor at a certain height position fails, the data of the upper and lower adjacent position sensors can be used to compensate the data by linear interpolation or spline interpolation method.

[0046] S102, dividing the storage tank space of the liquid helium storage tank into grid units of a preset size, and calculating the ratio of the temperature difference and the distance between each grid unit and the adjacent unit based on the temperature field distribution model as the temperature gradient value.

[0047] Wherein, the preset size represents the pre-set grid unit size parameter, which is usually determined according to the size of the storage tank and the accuracy requirement; the grid unit refers to the smallest space unit obtained by uniformly dividing the storage tank space according to the preset size, which is described by a three-dimensional rectangular coordinate system; the temperature difference refers to the difference between the temperature values of the center points of adjacent grid units; the distance refers to the spatial distance between the center points of adjacent grid units; the temperature gradient value represents the temperature change rate per unit distance, reflecting the degree of change of the temperature field.

[0048] After obtaining the temperature field distribution model, the liquid helium storage system needs to accurately divide the storage tank space for subsequent analysis and control. Specifically, the liquid helium storage system first sets appropriate grid division sizes (such as 0.1 m in radial direction, 15 degrees in circumferential direction, and 0.2 m in axial direction) according to the geometric size of the storage tank and the temperature field variation characteristics, and divides the entire storage tank space into a regular three-dimensional grid structure. Then, the liquid helium storage system calculates the temperature value of the center point of each grid cell using the established temperature field distribution model. For each grid cell, the temperature difference with the six adjacent cells (up, down, front, back, left, and right) is calculated respectively, and divided by the corresponding spatial distance to obtain the temperature gradient value in six directions. Finally, the maximum temperature gradient value is selected as the characteristic value of the grid cell.

[0049] In some embodiments, grid division and temperature gradient calculation can be implemented in various ways: optionally, the liquid helium storage system can use an adaptive grid division method, using smaller grid sizes in areas with rapid temperature changes and larger grid sizes in areas with slow temperature changes, and implementing dynamic management of grids by constructing a quadtree or octree data structure; optionally, the liquid helium storage system can also use a finite difference method, using a central difference format to calculate the temperature gradient and introducing a weighted average mechanism to handle non-uniform grid situations. It can be understood that other grid division and gradient calculation methods can also be used, which are not limited here. In addition, the selection of grid size needs to balance the calculation accuracy and efficiency, and it is recommended to determine the optimal grid parameters through experiments.

[0050] In practical applications, grid division may encounter problems in handling the boundaries of the storage tank. For this purpose, the liquid helium storage system adopts a special boundary handling strategy: for grid cells close to the wall surface of the storage tank, considering the heat conduction characteristics of the wall surface, a boundary layer correction factor is introduced when calculating the temperature gradient. By analyzing the thermal physical parameters of the wall surface material and the external environment temperature, a boundary temperature gradient correction model is established to ensure the accuracy of the temperature gradient calculation of the boundary grid cells. For example, for grid cells in contact with the metal wall surface, the temperature gradient calculation formula can be adjusted according to the thermal conductivity of the wall surface to avoid calculation errors caused by boundary effects.

[0051] S103、In the case where the temperature gradient value of the target grid cell exceeds the preset gradient threshold value within the preset time length, the combination area of the target grid cell and the adjacent threshold-exceeding grid cell is determined as the target area.

[0052] wherein, the preset time length represents the duration requirement of the system monitoring the temperature gradient anomaly, usually set to 5-30 minutes; the preset gradient threshold value refers to the standard value for determining whether the temperature gradient is abnormal, determined according to the safety requirements of liquid helium storage; the target grid cell refers to the grid cell whose temperature gradient value continuously exceeds the threshold value; the super-threshold grid cell refers to the grid cell adjacent to the target cell and whose temperature gradient value also exceeds the threshold value; and the target area refers to the continuous spatial area that needs to be temperature-regulated.

[0053] After the grid temperature gradient calculation is completed, the liquid helium storage system needs to identify and determine the area that needs to be focused on regulating. Specifically, the liquid helium storage system first continuously monitors the temperature gradient value of each grid cell and records its change history. When it is found that the temperature gradient value of a certain grid cell continuously exceeds the preset threshold value (such as 0.5K / m) for a preset time length, it is marked as a target grid cell. Then, the liquid helium storage system checks the 26 adjacent cells around the target grid cell (considering all adjacency relationships in three-dimensional space) to find out the grid cells that also exceed the threshold value. Finally, these connected super-threshold grid cells are combined into a continuous spatial area as the target area for temperature regulation.

[0054] In some embodiments, the determination of the target area can be achieved in various ways: alternatively, the liquid helium storage system can use a region growing algorithm, taking the target grid cell as the seed point, gradually adding eligible adjacent cells to the region until the boundary cell with normal temperature gradient is encountered, and recording the temperature gradient exceeding time of each added cell during this period; alternatively, the liquid helium storage system can also use a clustering analysis method to group all super-threshold grid cells according to spatial position and temperature gradient characteristics, and ensure the continuity of the region by setting a minimum distance threshold. It can be understood that other region identification and merging methods can also be used, which are not limited here. It is recommended to consider the regularity of the shape of the region in the implementation process to avoid the appearance of too scattered or irregularly shaped target areas.

[0055] In the target area determination process, the problem of multiple abnormal areas affecting each other may be encountered. For this purpose, the liquid helium storage system uses a priority management mechanism: first, the comprehensive risk degree of each abnormal area is calculated, considering factors such as temperature gradient exceeding degree, duration, area size, etc. Then, based on the risk degree ranking, the processing priority is determined. For multiple abnormal areas adjacent in space, the system analyzes their correlation and determines whether they need to be merged for processing. For example, when the boundary temperature gradient of two abnormal areas presents a continuous change feature, they can be merged into a larger target area and a unified regulation strategy is adopted. At the same time, the system predicts the temperature evolution trend of each area and dynamically adjusts the processing order to ensure optimal allocation of system resources.

[0056] S104、based on the region position of the target region and the temperature gradient value, calculate the adjustment parameter of the refrigeration power.

[0057] Wherein, the region position represents the three-dimensional coordinate range and geometric characteristics of the target region in the storage tank space; the temperature gradient value includes a set of temperature gradient data of each grid cell in the region; the refrigeration power represents the refrigeration output size of the cold screen device, with the unit of watt (W); the adjustment parameter refers to the specific value for controlling the refrigeration power, including power size, adjustment rate and duration, etc.

[0058] After determining the target region, the liquid helium storage system needs to accurately calculate the required refrigeration power parameter. Specifically, the liquid helium storage system first obtains the spatial information of the target region and analyzes its relative position relationship with the surrounding cold screen devices. Then, the system statistically analyzes the temperature gradient value in the region, calculates the average gradient value, the maximum gradient value and the gradient distribution characteristics. Based on these data, combined with the heat conduction model, the system calculates the total refrigeration amount required to reduce the temperature gradient to below the preset threshold. Considering the hysteresis and spatial decay characteristics of heat transfer, the system also needs to compensate the refrigeration power according to the distance from the target region to the cold screen device, and finally obtain the specific power adjustment parameter.

[0059] In some embodiments, the calculation of the refrigeration power parameter can be realized in various ways: alternatively, the liquid helium storage system can use the heat balance method to first estimate the heat load of the target region, including external heat leakage, internal heat convection and phase change latent heat, etc., then combine the temperature gradient exceeding degree, calculate the required refrigeration power through the heat conduction equation, and consider the refrigeration efficiency loss for correction; alternatively, the liquid helium storage system can also use the data-driven method to establish a mapping relationship model between temperature gradient and refrigeration power based on historical operation data, and predict the optimal power parameter through machine learning algorithm. It can be understood that other power calculation methods can also be used, which are not limited here. It is recommended to consider the dynamic characteristics of the system when calculating the power, and to reserve appropriate adjustment margin.

[0060] During the calculation of the refrigeration power parameter, the problem of multiple cold screen devices cooperating control may be encountered. For this purpose, the liquid helium storage system adopts a power distribution optimization strategy: first, build an influence model of the cold screen devices around the target region, considering factors such as spatial distance, heat conduction path and equipment performance characteristics. Then use a multi-objective optimization algorithm to reasonably distribute the power output of each cold screen device under the premise of meeting the total refrigeration demand. For example, when the target region is affected by multiple cold screen devices at the same time, the system will dynamically adjust the power distribution ratio according to the position advantage and current load state of each device, ensuring the refrigeration effect and avoiding local overcooling. At the same time, the system also considers factors such as equipment life and energy consumption to achieve optimal allocation of refrigeration resources.

[0061] S105, control the refrigeration power output of the cold screen device in the target region according to the adjustment parameter, so that the temperature gradient value of the target region is reduced to below the preset gradient threshold.

[0062] Wherein, the cold screen device represents a low-temperature refrigeration device for providing refrigeration capacity, including components such as refrigeration head, cooling pipeline, etc.; the refrigeration power output refers to the actual refrigeration effect of the cold screen device; the temperature gradient value reduction refers to the process of making the temperature distribution tend to be uniform through refrigeration adjustment; the preset gradient threshold value represents the standard value for the system to determine the stability of the temperature field.

[0063] After obtaining the refrigeration power adjustment parameter, the liquid helium storage system needs to accurately perform temperature regulation operation. Specifically, the liquid helium storage system first sets the working state of each cold screen device according to the power adjustment parameter, including the start sequence, power increment and adjustment rate. The system adopts a step-by-step adjustment strategy, first uses a large power to quickly respond to reduce the temperature gradient, and then uses a small power to fine-tune when approaching the target value, avoiding overshoot. During the adjustment process, the system continuously monitors the temperature field changes of the target region, calculates the temperature gradient value in real time, and compares it with the preset threshold value. If it is found that the temperature gradient reduction rate is abnormal or there is local fluctuation, the system will timely adjust the refrigeration strategy to ensure the stability of the regulation process.

[0064] In some embodiments, the accurate control of refrigeration power can be achieved in various ways: optionally, the liquid helium storage system can use model predictive control method, predict the temperature change trend in the future period of time based on the temperature field dynamic model, calculate the optimal power adjustment sequence through rolling optimization, and realize the smooth reduction of temperature gradient; optionally, the liquid helium storage system can also use adaptive PID control strategy, dynamically adjust the control parameters according to the change characteristics of temperature gradient deviation, and realize the unity of fast response and stable control. It can be understood that other control methods can also be used to realize the adjustment of temperature gradient, which is not limited here. It is recommended to add anti-saturation and anti-disturbance mechanism in the control algorithm to improve the robustness of the system.

[0065] During the refrigeration adjustment process, control oscillation problems caused by temperature field response lag may occur. For this, the liquid helium storage system adopts an intelligent anti-vibration strategy: first, a temperature response characteristic model is established to analyze the time constant and transfer characteristics of the system. Based on these characteristic parameters, the system designs a power adjustment mechanism with a dead zone and variable rate. When it is detected that the change trend of temperature gradient fluctuates, the system will automatically reduce the adjustment sensitivity and prolong the adjustment period. For example, during the high-power adjustment stage, the system will reserve enough observation time and wait for the temperature field to fully respond before the next adjustment. At the same time, the system also records the response characteristics in the previous adjustment process, continuously optimizes the control parameters, and improves the accuracy and stability of the adjustment. In this way, the effective control of the temperature gradient is ensured, and the over-adjustment of the system is avoided.

[0066] S106、in the target area, the temperature gradient value does not exceed the preset gradient threshold value within the preset time length, the current refrigeration power is set as the reference power value of the target area.

[0067] Wherein, the preset time length represents the observation period required to verify the temperature field stability, usually 1-2 hours; the temperature gradient value does not exceed the preset threshold value indicates that the temperature field reaches a stable and uniform state; the reference power value refers to the standard refrigeration power required to maintain the stability of the target area temperature field, which serves as a reference basis for subsequent operation.

[0068] After the temperature gradient control of the liquid helium storage system is completed, the stable operation parameters need to be determined and recorded. Specifically, the liquid helium storage system continuously monitors the temperature gradient value of the target area, and starts timing when it is observed that the temperature gradient remains stable below the preset threshold value. The system will record the refrigeration power data during this period, including the power output value and operating state of each cold screen device. If the temperature gradient remains stable throughout the preset time length, the system calculates the average refrigeration power during this period and sets it as the reference power value of the target area. This reference power value will serve as the standard parameter for the daily operation of this area, which will be used for subsequent refrigeration control and energy efficiency optimization.

[0069] In some embodiments, the determination of the reference power value can be achieved in various ways: alternatively, the liquid helium storage system can use statistical analysis methods to collect power data during the stable period, and through the processing of removing outliers, calculating weighted average, etc., to obtain a more representative reference power value, while establishing a power fluctuation range model for subsequent operation monitoring; alternatively, the liquid helium storage system can also use an adaptive reference value method to dynamically adjust the reference power value according to changes in environmental temperature, storage capacity and other operating conditions, and establish a power reference system under multiple working conditions. It can be understood that other methods can also be used to determine the reference power value, which is not limited here. It is recommended to consider seasonal changes and equipment aging and other long-term factors when determining the reference power.

[0070] During the determination of the reference power value, power fluctuations caused by external environmental changes may occur. For this purpose, the liquid helium storage system adopts an environmental compensation mechanism: first, an environmental factor influence model is established to analyze the influence law of external temperature, air pressure and other parameters on refrigeration demand. Then, a compensation coefficient is introduced in the calculation of the reference power value, which dynamically corrects the reference value according to the actual environmental conditions. For example, when the ambient temperature is detected to rise, the system will correspondingly increase the correction coefficient of the reference power value to ensure the stability of the storage tank temperature field. At the same time, the system also establishes a seasonal variation model of the reference power value to predict and adjust the control parameters in advance, realizing stable operation throughout the year. Through this adaptive mechanism, the accuracy of the reference power value is guaranteed, and the adaptability of the system operation is improved.

[0071] In the above embodiment, the temperature field control method based on gridding analysis is mainly described. In actual application, the grid size can be adjusted according to specific needs, the temperature gradient threshold can be modified, or other control parameters can be added to make the control scheme better adapt to different sizes and types of liquid helium storage systems. The scenarios of the present embodiment are supplemented as follows.

[0072] After further optimization, the system added device efficiency evaluation and adaptive control functions. The system found that the efficiency of two refrigeration machines had declined by continuously monitoring the energy efficiency ratio of the refrigeration unit. Through intelligent scheduling algorithm, the system gradually transferred the load of these two machines to other high-efficiency units, and arranged a peak-shaving maintenance plan. Before a large-scale experiment, the system predicted that there would be a peak of refrigeration demand, and started the standby refrigeration unit preheating 12 hours in advance, and optimized the cold screen power distribution scheme. During the experiment, the temperature field in the storage tank remained stable even when the refrigeration load reached the peak, and the maximum temperature gradient was not more than 0.2K / m. During the entire experiment, the total energy consumption of the system was reduced by 40% compared with the traditional operation mode, fully demonstrating the advantages of the present scheme in large-scale and long-term operation.

[0073] After combining the above scenarios, the method provided by the present embodiment is further described in more detail. Please refer to Figure 2 , another flowchart of the working control method of large-capacity liquid helium storage in the present embodiment.

[0074] S201, collect temperature data and pressure data at multiple height positions in the liquid helium storage tank, and construct a temperature field distribution model based on the temperature data and pressure data.

[0075] Referring to step S101, the liquid helium storage system will collect temperature and pressure data through multiple sensors to establish a temperature distribution model in the storage tank.

[0076] S202, divide the storage tank space of the liquid helium storage tank into grid units of a predetermined size, and calculate the temperature difference to distance ratio between each grid unit and adjacent units based on the temperature field distribution model as the temperature gradient value.

[0077] Referring to step S102, the liquid helium storage system will grid the storage tank space and calculate the temperature gradient between adjacent grids.

[0078] S203, when the temperature gradient value of the target grid unit exceeds the preset gradient threshold value within a predetermined time period, the combination area of the target grid unit and the adjacent threshold value grid unit is determined as the target area.

[0079] Referring to step S103, the liquid helium storage system will monitor and identify the area with abnormal temperature gradient as the control target.

[0080] S204, obtain the pressure value of each grid unit in the target area, and calculate the pressure difference between the average pressure value of the target area and the preset standard pressure.

[0081] Wherein, the pressure value represents the measured gas pressure data in each grid unit; the average pressure value refers to the arithmetic mean of the pressure values of all grid units in the target area; the preset standard pressure represents the standard working pressure when the liquid helium storage tank is in normal operation; the pressure difference refers to the deviation value between the actual pressure and the standard pressure.

[0082] After determining the target area, the liquid helium storage system needs to evaluate the pressure state in the area. Specifically, the liquid helium storage system first reads the pressure sensor data of all grid units in the target area, and performs data preprocessing to remove outliers. Then the average pressure value in the area is calculated, and the uniformity of the pressure distribution is analyzed. The system compares the calculated average pressure value with the pre-set standard pressure value (such as 0.15 MPa) to obtain the pressure difference value. This pressure difference value will be used as the basis for determining whether to perform pressure relief operation.

[0083] In some embodiments, pressure evaluation can be achieved in various ways: alternatively, the liquid helium storage system can use a weighted average method to assign different weights to the pressure values according to the location and representation of each grid unit, to obtain more accurate regional pressure characteristics; alternatively, the liquid helium storage system can also use statistical analysis method to evaluate the uniformity of pressure distribution by calculating pressure standard deviation and coefficient of variation. It can be understood that other pressure evaluation methods can also be used, which are not limited here. It is recommended to consider the static pressure effect caused by liquid level height when calculating pressure.

[0084] During the pressure evaluation process, data distortion problems caused by pressure sensor failure may occur. For this purpose, the liquid helium storage system adopts a data verification mechanism: first, a pressure gradient model is established to analyze the pressure relationship between adjacent grid units and identify abnormal data points. For suspicious data, the system will refer to historical data and physical models for reasonableness verification, and if necessary, use interpolation method for data correction. For example, when the pressure value of a certain grid unit deviates significantly from the surrounding units, the system will re-estimate the pressure value of this point based on the principle of liquid static pressure and the surrounding reliable data.

[0085] S205, when the pressure difference exceeds the preset pressure difference threshold, calculate the pressure relief rate parameter based on the pressure difference.

[0086] Wherein, the preset pressure difference threshold represents the pressure deviation standard value that triggers the pressure relief operation; the pressure relief rate parameter includes the pressure relief flow and the pressure relief duration; the pressure difference refers to the difference between the actual pressure and the standard pressure, which is used to determine the pressure relief amount.

[0087] After detecting that the pressure difference exceeds the threshold, the liquid helium storage system needs to accurately calculate the pressure relief parameters. Specifically, the liquid helium storage system first determines the degree to which the pressure difference exceeds the threshold, and divides different pressure relief levels according to the size of the overpressure. Then, the system calculates the total amount of gas that needs to be released in combination with parameters such as the volume of the storage tank and the density of the gas. For safety considerations, the system adopts a segmented pressure relief strategy, dividing the pressure relief process into two stages: rapid pressure relief and slow pressure relief. The pressure relief rate and duration of each stage are calculated to ensure a smooth and controllable pressure relief process.

[0088] In some embodiments, the pressure relief parameter calculation can be achieved in various ways: optionally, the liquid helium storage system can use a gas state equation to calculate the pressure relief amount in combination with temperature and pressure data, and determine the appropriate pressure relief rate based on the characteristics of the pipeline; optionally, the liquid helium storage system can also use an empirical model method to establish a correspondence between pressure difference and pressure relief parameters based on historical pressure relief data to achieve rapid parameter determination. It can be understood that other parameter calculation methods can also be used, which are not limited here. It is recommended to consider the dynamic response characteristics of the system when calculating parameters.

[0089] During the pressure relief parameter calculation process, complex situations such as multiple points simultaneously exceeding pressure may occur. For this purpose, the liquid helium storage system adopts a coordinated pressure relief strategy: first, analyze the spatial distribution and pressure gradient of each overpressure point, and establish a pressure propagation model. Then, according to the model, predict the influence of the pressure relief operation on each region, and develop the optimal pressure relief scheme. For example, when multiple regions need to be relieved at the same time, the system will consider the layout and capacity of the pressure relief pipeline, reasonably arrange the pressure relief sequence and rate, and avoid local pressure fluctuations.

[0090] In some embodiments, the liquid helium storage system will accurately control the pressure relief rate, that is, the liquid helium storage system will obtain the position of the grid cell with the maximum pressure value in the target region as the pressure relief priority area; based on the distance from the pressure relief priority area to the nearest pressure relief valve, calculate the flow resistance coefficient of the gas in the pipeline, and calculate the theoretical pressure relief rate according to the pressure difference and the flow resistance coefficient; select the minimum value of the theoretical pressure relief rate and the preset safe pressure relief rate as the pressure relief rate parameter.

[0091] wherein the grid cell with the maximum pressure value represents the local pressure peak position in the target region; the pressure relief priority area refers to the spatial position that needs to be preferentially relieved; the pressure relief valve refers to an electrically adjustable device for controlling gas discharge; the flow resistance coefficient refers to a physical quantity that describes the size of the flow resistance of the gas in the pipeline; the theoretical pressure relief rate refers to the ideal pressure relief flow rate calculated based on the physical model; and the preset safe pressure relief rate refers to the maximum allowable pressure relief rate to ensure safe operation of the system.

[0092] Before performing the pressure relief operation, the liquid helium storage system needs to determine the optimal pressure relief scheme. Specifically, the liquid helium storage system first scans the pressure data of all grid cells in the target area to find the maximum pressure value and its position coordinates. Then, the system analyzes the distance from the position to all surrounding pressure relief valves and selects the closest pressure relief valve as the main pressure relief channel. For the selected pressure relief channel, the system considers the geometric characteristics of the pipeline (including pipe diameter, number of bends, pipeline length, etc.) to calculate the gas flow resistance coefficient. Combined with the pressure difference value and the resistance coefficient, the theoretical pressure relief rate is calculated through the fluid mechanics equation. Finally, the system compares the theoretical value with the preset safety rate and selects the smaller value as the actual executed pressure relief rate parameter to ensure that the pressure relief process is both efficient and safe.

[0093] In some embodiments, the determination of the pressure relief parameters can be achieved in various ways: optionally, the liquid helium storage system can use a dynamic pressure field analysis method to first establish a pressure distribution model in the storage tank, analyze the propagation characteristics of the pressure gradient, then combine the spatial layout of the pressure relief channel to calculate the optimal pressure relief path and rate through the fluid network algorithm, and finally determine the pressure relief parameters considering system safety constraints; optionally, the liquid helium storage system can also use a multi-objective optimization method to consider multiple objectives such as pressure relief efficiency, system safety, and energy loss to calculate the best pressure relief scheme by establishing an optimization model. It can be understood that other pressure relief parameter determination methods can also be used, which are not limited here. It is recommended to consider the gas state equation and phase change characteristics when calculating the parameters.

[0094] During the determination of the pressure relief parameters, complex situations may occur where multiple pressure peaks coexist. For this purpose, the liquid helium storage system uses a coordinated pressure relief control strategy: first, topological analysis is performed on the pressure field to identify all local pressure peak points and evaluate their mutual influence relationship. Then, a multi-channel pressure relief model is established to calculate the system response characteristics under different pressure relief schemes. Based on the model prediction results, the system can determine the optimal pressure relief sequence and the pressure relief rate allocation scheme for each channel. For example, when there are two nearby pressure peak points, the system analyzes the pressure coupling effect between them and may choose to first relieve the main peak point and use the pressure diffusion effect to naturally alleviate the pressure of the secondary peak point, thereby improving the pressure relief efficiency and reducing system disturbance.

[0095] S206、based on the pressure relief rate parameter, controlling the pressure relief valve corresponding to the target area to release gas at the pressure relief rate parameter.

[0096] wherein the pressure relief valve represents an electrically controlled regulating valve for controlling gas discharge; the pressure relief rate parameter includes specific control parameters such as valve opening degree and opening time; and the gas release refers to the process of controlled release of overpressure gas in the storage tank.

[0097] After determining the pressure relief parameters, the liquid helium storage system needs to accurately perform the pressure relief operation. Specifically, the liquid helium storage system first selects the nearest pressure relief valve group according to the location of the target area and checks the state of the pressure relief channel. Then, the system realizes the accurate release of gas by controlling the opening degree and opening timing of the pressure relief valve according to the calculated pressure relief rate parameters. During the pressure relief process, the system monitors the pressure change in real time and dynamically adjusts the pressure relief parameters according to the actual situation to ensure the safety and controllability of the pressure relief process.

[0098] In some embodiments, pressure relief control can be achieved in various ways: optionally, the liquid helium storage system can adopt a staged pressure relief strategy, first quickly reduce the pressure with a large opening degree, and when the target pressure is approached, switch to fine adjustment with a small opening degree, and realize smooth pressure relief by adjusting the valve opening degree in real time; optionally, the liquid helium storage system can also adopt a multi-valve cooperative control mode, simultaneously controlling multiple pressure relief valves, and reasonably distributing the pressure relief flow according to the position of each valve and the channel characteristics. It can be understood that other pressure relief control methods can also be used, which are not limited here.

[0099] During the pressure relief execution process, the pressure relief rate may not meet the expected value. For this purpose, the liquid helium storage system adopts an adaptive control mechanism: first, the pressure sensor is used to monitor the pressure relief effect in real time, and the deviation between the actual pressure relief rate and the target value is calculated. Then, based on the deviation, the valve opening degree is dynamically adjusted: if the pressure relief rate is too slow, the opening degree is appropriately increased; if the rate is too fast, the opening degree is decreased. For example, when it is detected that the pressure relief rate deviates from the target value by more than 10%, the system will immediately start the correction program, and adjust the valve opening degree through the PID control algorithm to ensure that the pressure relief process meets the expected requirements.

[0100] S207, recovering the released gas and transporting the released gas to a reliquefaction device for cooling and liquefaction.

[0101] Among them, recovering the released gas means collecting the released helium gas during the pressure relief process; the reliquefaction device means a low-temperature device for converting gaseous helium into liquid helium; cooling and liquefaction means the process of re-liquefying helium by cooling and pressurizing.

[0102] The liquid helium storage system needs to realize efficient recovery and utilization of gas while performing the pressure relief operation. Specifically, the liquid helium storage system first introduces the released gas into the recovery system through a special pipeline and performs impurity removal and purification treatment. Then, the system adjusts the gas delivery rate according to the working state and processing capacity of the reliquefaction device to ensure that the recovered gas can be processed in time. During the liquefaction process, the system monitors the temperature, pressure and flow parameters of the gas in real time, and adjusts the refrigeration power and compression ratio to optimize the liquefaction efficiency.

[0103] In some embodiments, the gas recovery liquefaction can be achieved in various ways: optionally, the liquid helium storage system can adopt a multi-stage compression pre-cooling scheme to improve the liquefaction efficiency by gradually increasing the pressure and reducing the temperature; optionally, the liquid helium storage system can also adopt a hybrid refrigeration cycle scheme to realize energy cascade utilization by combining different temperature zone refrigeration equipment. It can be understood that other gas liquefaction methods can also be used, which are not limited here. It is recommended to focus on energy recovery and system efficiency optimization during the recovery process.

[0104] During the gas recovery liquefaction process, the problem of insufficient purity of the recovered gas may be encountered. For this purpose, the liquid helium storage system adopts an intelligent purification control strategy: first, the composition of the recovered gas is monitored by an online gas analyzer, and when the impurities are detected to be excessive, the enhanced purification program is automatically started. The system will select the appropriate adsorbent and working temperature according to the type of impurities, and by adjusting the gas flow rate and regeneration period, the purity of the liquefied gas can be ensured to meet the requirements. For example, when the nitrogen content is detected to be too high, the system will reduce the gas flow rate, extend the adsorption time, and if necessary, start the standby purification device.

[0105] In some embodiments, the liquid helium storage system intelligently adjusts the working state of the refrigeration unit, that is, the liquid helium storage system acquires the real-time refrigeration power and liquefaction efficiency parameters of the reliquefaction device, calculates the minimum required refrigeration power based on the depressurization rate parameter; when the real-time refrigeration power is less than the minimum refrigeration power, the standby refrigeration unit is started, and the power distribution ratio of each refrigeration unit is adjusted according to the liquefaction efficiency parameter.

[0106] wherein the reliquefaction device represents a low-temperature equipment system that converts the released gas back into a liquid state; the real-time refrigeration power refers to the actual refrigeration output of the current reliquefaction device; the liquefaction efficiency parameter is used to represent the amount of gas liquefaction that can be achieved per unit of input power; the minimum refrigeration power represents the minimum refrigeration requirement to meet the current depressurized gas processing demand; the standby refrigeration unit refers to the refrigeration equipment in standby state; the power distribution ratio refers to the refrigeration load share of each refrigeration unit.

[0107] When the liquid helium storage system performs the gas recovery liquefaction process, it needs to ensure that the refrigeration capacity meets the processing demand. Specifically, the liquid helium storage system first acquires the operating parameters of the reliquefaction device in real time through a sensor network, including the refrigeration temperature at each stage, the compressor power, the cooling water temperature, etc., and calculates the current refrigeration power output value. At the same time, the system calculates the actual liquefaction efficiency based on the temperature, pressure and flow rate data of the inlet and outlet gases. Based on the known depressurization rate parameter, the system can calculate the theoretical refrigeration power required to completely liquefy the released gas, and determine the minimum refrigeration power requirement considering the actual liquefaction efficiency. When the system judges that the current refrigeration power is insufficient, the appropriate number of standby refrigeration units will be started according to the gap size, and the refrigeration load will be optimally distributed based on the liquefaction efficiency characteristics of each unit.

[0108] In some embodiments, the coordinated control of refrigeration capacity can be achieved in various ways: optionally, the liquid helium storage system can adopt a staged start strategy, first establish a refrigeration demand prediction model, analyze the dynamic characteristics of the pressure relief process, then develop a phased refrigeration unit start plan according to the prediction results, gradually increase the refrigeration capacity to meet the processing demand, while considering the equipment preheating and transition process; optionally, the liquid helium storage system can also adopt an adaptive load distribution method, real-time monitoring of the operating state and efficiency characteristics of each refrigeration unit, continuously optimizing the load distribution scheme through dynamic programming algorithm, to ensure the highest overall operating efficiency of the system. It can be understood that other refrigeration control methods can also be used, which are not limited here.

[0109] During the coordinated control of refrigeration capacity, the problem of insufficient processing capacity caused by the response lag of the refrigeration unit may be encountered. For this, the liquid helium storage system adopts a prediction compensation control strategy: first, a dynamic response model of the refrigeration unit is established to analyze the time delay characteristics from the start command to the stable refrigeration output. Then the system will predict the refrigeration demand trend in the pressure relief process in advance, and start the standby unit in advance before the refrigeration demand increases. For example, when it is predicted that the refrigeration demand will increase significantly after 15 minutes, the system will start the standby unit to preheat 10 minutes in advance to ensure that sufficient refrigeration capacity can be provided in time when the demand increases. At the same time, the system also monitors the real-time changes of liquefaction efficiency, and compensates for the temporary capacity deficiency caused by the response lag of the equipment by dynamically adjusting the power distribution ratio.

[0110] In some embodiments, the liquid helium storage system will monitor and optimize the operating efficiency of each refrigeration unit, that is, the liquid helium storage system will collect the input power and output temperature of the refrigeration unit group after starting, calculate the energy efficiency ratio of each refrigeration unit, determine the refrigeration efficiency decay coefficient based on the deviation of the energy efficiency ratio from the nominal value; according to the refrigeration efficiency decay coefficient, the refrigeration units are classified into grades, the refrigeration units whose decay degree exceeds the preset threshold are marked as optimization objects, and the contribution rate of the optimization objects to the total refrigeration capacity of the system is calculated; on the premise of ensuring that the total refrigeration capacity of the system meets the demand, the standby switching order of the optimization objects is determined based on the contribution rate, and the refrigeration load of the optimization objects is gradually transferred to the high-efficiency units that are not optimization objects according to the standby switching order.

[0111] The input power represents the power of the electric energy consumed by the refrigeration unit; the output temperature refers to the temperature of the low-temperature refrigeration medium generated by the refrigeration unit; the energy efficiency ratio is used to represent the refrigeration capacity generated per unit of input power, reflecting the operating efficiency of the device; the nominal value refers to the theoretical performance parameters of the device under normal working conditions; the refrigeration efficiency decay coefficient represents the degree of degradation of the actual performance of the device relative to the nominal performance; the to-be-optimized object refers to the low-efficiency refrigeration unit that needs to be maintained or replaced; and the contribution rate represents the proportion of the refrigeration unit to the total refrigeration capacity of the system.

[0112] During continuous operation of the liquid helium storage system, the performance state of the refrigeration device needs to be monitored and optimized. Specifically, the liquid helium storage system records the electric energy consumption of each refrigeration unit in real time through an energy metering device, and simultaneously collects temperature data at the refrigeration output end. The system calculates the actual energy efficiency ratio of each refrigeration unit based on these data, and compares it with the nominal value of the device at the factory, to obtain the efficiency decay coefficient. Then, the system classifies the refrigeration units based on a preset efficiency threshold value, and marks the units with severe decay as to-be-optimized objects. For these to-be-optimized objects, the system calculates the proportion of refrigeration load they currently bear, and evaluates the impact of replacement or shutdown maintenance on the overall refrigeration capacity of the system. Under the premise of ensuring that the system refrigeration capacity meets the demand, the system formulates an optimization scheme for gradually transferring the load, and gradually transfers the load of the low-efficiency units to the high-efficiency units.

[0113] In some embodiments, device performance optimization can be achieved in various ways: optionally, the liquid helium storage system can adopt a gradual load transfer strategy, first build a performance model of the refrigeration unit group, analyze the efficiency characteristics of each unit under different loads, then formulate a step-by-step load adjustment plan, and achieve smooth transfer of the load through multiple small adjustments, during which the stability and response characteristics of the system are continuously monitored; optionally, the liquid helium storage system can also adopt an intelligent scheduling optimization method, establish a multi-objective optimization model considering device life, maintenance cost and operating efficiency, and calculate the optimal device use scheme and load distribution strategy through a dynamic programming algorithm. It can be understood that other device optimization methods can also be used, which are not limited here.

[0114] In the process of optimizing the performance of the device, the problem of system instability caused by load transfer may be encountered. To this end, the liquid helium storage system adopts an adaptive control strategy: first, a dynamic characteristic model of the refrigeration system is established, and the influence of load change on the stability of the temperature field is analyzed. Then a load transfer controller with feedback compensation is designed to monitor the system response in real time when performing load adjustment. For example, when a high-efficiency unit receives additional load, if fluctuations in its output temperature are detected, the system will automatically reduce the load transfer rate and, if necessary, start a backup unit to provide temporary support. At the same time, the system records experience data for each load transfer, continuously optimizes control parameters, and improves the accuracy and reliability of load adjustment. This approach not only ensures the continuous and stable operation of the system, but also improves the overall efficiency of the device.

[0115] In some embodiments, the liquid helium storage system calculates the required refrigeration power parameters according to the characteristics of the target region.

[0116] Referring to step S104, the liquid helium storage system calculates the required refrigeration power parameters according to the characteristics of the target region.

[0117] In some embodiments, the liquid helium storage system calculates the required refrigeration power parameters according to the characteristics of the target region.

[0118] wherein the coordinate information represents the position data of the target region in the three-dimensional space of the storage tank, including the center coordinates of each grid cell; the grid cell refers to the smallest spatial calculation unit after uniform division of the storage tank space; the spatial distance is used to represent the three-dimensional Euclidean distance from the center point of the grid cell to the corresponding cold screen device; the cold screen device represents a low-temperature device component that provides refrigeration effect; the spatial weighted calculation refers to different degrees of weight distribution of the temperature gradient value according to the distance; the adjustment parameter represents the specific value used to control the refrigeration power of the cold screen device.

[0119] After determining the target area, the liquid helium storage system needs to consider the spatial position factor to accurately calculate the refrigeration power parameter. Specifically, the liquid helium storage system first establishes a three-dimensional coordinate system, obtains the position coordinates of all grid elements in the target area and the corresponding cold screen device coordinates. Then, the spatial distance from each grid element to the corresponding cold screen device is calculated, and a distance matrix is established. Based on the distance matrix, the system designs an inverse proportional weight function, and the weight decreases as the distance increases. Multiply these weights by the temperature gradient values of each grid element to obtain the weighted temperature gradient values considering the spatial effect. Finally, the system compares the weighted temperature gradient values with the preset threshold value to determine the final refrigeration power adjustment parameter through a nonlinear mapping relationship.

[0120] In some embodiments, spatial weighting calculation can be achieved in various ways: optionally, the liquid helium storage system can use a weighting method based on a physical model, first establish a heat conduction attenuation model, analyze the attenuation law of the refrigeration effect of the cold screen device with distance, then calculate the weight coefficient of each position based on the heat diffusion equation, and finally obtain the weighted result combined with the temperature gradient value; optionally, the liquid helium storage system can also use an adaptive weight method, by analyzing historical operation data, establishing a statistical relationship model between distance and refrigeration effect, dynamically adjusting the weight calculation formula, to achieve more accurate spatial weighting. It can be understood that other weighting calculation methods can also be used, which are not limited here. It is recommended to consider the geometric structure characteristics and material thermal conductivity of the storage tank when calculating the weight.

[0121] During the spatial weighting calculation process, the refrigeration effect evaluation deviation problem caused by local shielding may occur. For this purpose, the liquid helium storage system uses a path analysis mechanism: first, a three-dimensional heat conduction network model of the inside of the storage tank is constructed to analyze the actual heat conduction path from the cold screen device to each grid element. Then, according to the complexity and blocking of the path, the weight coefficient is corrected, and the weight is appropriately reduced for the path with shielding. For example, when there is a metal support structure between a certain grid element and the cold screen device, the system will consider the thermal conductivity characteristics of the support structure, adjust the weight calculation method of the element, and ensure that the weighted result is more consistent with the actual situation.

[0122] S209、According to the positive and negative of the temperature gradient change rate, determine the adjustment direction of the refrigeration power, and calculate the corresponding correction coefficient based on the absolute value of the temperature gradient change rate.

[0123] Wherein, the positive and negative of the change rate indicates whether the temperature gradient is increasing or decreasing; the adjustment direction indicates whether the refrigeration power needs to be increased or decreased; the correction coefficient is a proportional factor for adjusting the size of the refrigeration power.

[0124] After obtaining the temperature gradient change characteristics, the liquid helium storage system needs to determine the precise power adjustment strategy. Specifically, the liquid helium storage system first determines the sign of the change rate. A positive value indicates that the temperature gradient is increasing, and the refrigeration power needs to be increased. A negative value indicates that the temperature gradient is decreasing, and the refrigeration power can be appropriately reduced. Then, the system calculates the correction coefficient according to the absolute value of the change rate using a nonlinear mapping relationship. The larger the change rate, the larger the correction coefficient, ensuring that the adjustment intensity matches the temperature field change degree.

[0125] In some embodiments, the calculation of the correction coefficient can be achieved in various ways: optionally, the liquid helium storage system can use a piecewise linear mapping method to set different correction coefficient calculation formulas according to different intervals of the change rate, achieving fine adjustment; optionally, the liquid helium storage system can also use a fuzzy control method to fuzz the temperature gradient change rate and determine the appropriate correction coefficient through rule-based reasoning. It can be understood that other correction coefficient calculation methods can also be used, which are not limited here.

[0126] During the calculation of the correction coefficient, the problem of over-adjustment caused by system response lag may occur. For this purpose, the liquid helium storage system uses a prediction compensation mechanism: first, a temperature field response model is established to predict the influence of current adjustment on future temperature field. Then, a prediction compensation term is introduced in the calculation of the correction coefficient. When the adjustment effect is about to appear, the correction coefficient is appropriately reduced to avoid over-adjustment. For example, if it is predicted that the temperature gradient will rapidly decrease in a short time, the system will reduce the correction coefficient in advance to prevent oscillation.

[0127] In some embodiments, the liquid helium storage system can adjust the relevant control parameters according to specific needs: optionally, for different sizes of storage tanks, the grid division size can be adjusted. Large storage tanks use larger grids to reduce computational load, and small storage tanks use fine grids to improve control accuracy; optionally, the temperature gradient threshold can be modified according to actual application requirements. A more stringent threshold standard is used in situations where temperature control is required, and the threshold requirement can be appropriately relaxed in situations where temperature fluctuations are allowed to be larger; optionally, other control parameters such as pressure change rate and liquid level fluctuation can be added to construct a multi-parameter collaborative control strategy, making the control scheme better adapt to different sizes and types of liquid helium storage systems. It can be understood that the specific parameter settings need to be continuously optimized in combination with actual operation experience, which are not limited here. It is recommended to conduct sufficient parameter adaptability tests during system debugging.

[0128] S210, determine a new refrigeration power output value according to the current refrigeration power and the correction coefficient, and control the cold screen device to operate according to the refrigeration power output value.

[0129] Wherein, the current refrigeration power refers to the current operating power of the cold shield device; the correction coefficient is a regulation ratio calculated based on the temperature field variation characteristics; and the new refrigeration power output value refers to the target power value after correction.

[0130] After determining the correction coefficient, the liquid helium storage system needs to accurately calculate and execute power regulation. Specifically, the liquid helium storage system first obtains the actual operating power of the cold shield device, multiplies it by the correction coefficient to obtain the power regulation amount. Then, the system considers the power limit and regulation characteristics of the cold shield device to ensure that the new power output value is within the safe operating range of the device. Finally, the system gradually adjusts the power of the cold shield device to the target value through step-by-step regulation to avoid sudden changes that may impact the system.

[0131] In some embodiments, power regulation can be achieved in various ways: optionally, the liquid helium storage system can use a gradual regulation strategy to divide a large power adjustment into multiple small step adjustments, and observe the system response after each adjustment; optionally, the liquid helium storage system can also use a predictive control method to predict the system response under different power outputs based on a temperature field model, and select the optimal regulation path. It can be understood that other power regulation methods can also be used, which are not limited here.

[0132] During power regulation, the problem of mutual influence between multiple cold shield devices may be encountered. To this end, the liquid helium storage system uses a collaborative control strategy: first, a thermal coupling model between the cold shield devices is established to analyze the superposition relationship of the refrigeration effect of each device. Then, according to the model prediction, the power regulation timing and amplitude of each device are coordinated to avoid mutual interference. For example, when adjacent cold shield devices need to be adjusted at the same time, the system will consider their spatial positional relationship and reasonably arrange the adjustment order to ensure smooth transition of the temperature field.

[0133] S211, repeat the temperature gradient change rate acquisition step and the refrigeration power regulation step until the absolute value of the temperature gradient value of the target region is less than the preset gradient threshold value for a continuous preset number of times.

[0134] Wherein, the preset number of times represents the number of continuous observations required to determine the stability of the temperature field; the preset gradient threshold value is the determination standard for the stability of the temperature field; and the continuous value less than the threshold value means that the temperature field has reached a stable state.

[0135] After completing a power regulation, the liquid helium storage system needs to continuously monitor the regulation effect and perform iterative optimization. Specifically, the liquid helium storage system continues to monitor the temperature gradient change at a preset time interval and records the gradient value of each measurement. The system sets a counter, and when the temperature gradient is observed to be lower than the preset threshold value for a continuous number of times (such as 10 times), it is considered that the temperature field has reached a stable state, and the regulation process can be ended. If the gradient value exceeds the threshold value during the period, the counter will start counting again.

[0136] In some embodiments, the termination of the adjustment process can be achieved in various ways: optionally, the liquid helium storage system can use a trend analysis method to predict the stability of the temperature gradient by fitting the change curve of the temperature gradient, and end the unnecessary adjustment in advance; optionally, the liquid helium storage system can also use a comprehensive evaluation method to consider multiple indicators such as temperature gradient value, change rate and energy consumption, and establish a more comprehensive termination criterion. It can be understood that other termination judgment methods can also be used, which are not limited here.

[0137] In the iterative adjustment process, local oscillation may be encountered and it is difficult to converge. For this, the liquid helium storage system adopts an intelligent convergence strategy: first analyze the fluctuation characteristics of the temperature gradient, and identify whether there is periodic oscillation. If oscillation is found, the system will automatically adjust the control parameters, such as increasing the dead zone range or reducing the response sensitivity, to promote the system to reach a stable state as soon as possible. For example, when the temperature gradient is repeatedly fluctuated around a certain value, the system will appropriately relax the judgment condition, and as long as the fluctuation amplitude is within an acceptable range, it is considered to have reached a stable state.

[0138] S212、In the target area, the temperature gradient value does not exceed the preset gradient threshold value within a preset time length, and the current refrigeration power is set as the reference power value of the target area.

[0139] Referring to step S106, the liquid helium storage system will determine the reference refrigeration power of the region after the temperature gradient is stable.

[0140] Among them, the preset time length represents the observation period for determining the stability of the temperature field; the reference power value refers to the standard refrigeration power required to maintain the stability of the temperature field of the target area, which is used as a reference value for subsequent operation; the preset gradient threshold value refers to the standard value for determining the stability of the temperature field.

[0141] After completing the temperature field stability control, the liquid helium storage system needs to determine the standard parameters for long-term operation. Specifically, the liquid helium storage system first verifies whether the temperature gradient value of the target area remains below the threshold value throughout the preset time length. Then, the system calculates the average refrigeration power during this stable period, and after considering a certain margin, sets it as the reference power value of the region. This reference power value will be used as a reference standard for the daily operation of the region, for subsequent refrigeration control and energy efficiency optimization.

[0142] In some embodiments, the determination of the reference power value can be achieved in various ways: optionally, the liquid helium storage system can adopt a statistical analysis method to process the power data in the stable period, remove the outliers, and calculate the weighted average value as the reference power value; optionally, the liquid helium storage system can also adopt an adaptive reference value method to establish a dynamic reference power value system according to the changes of operating conditions such as environmental temperature and storage capacity. It can be understood that other reference power determination methods can also be used, which are not limited here.

[0143] During the determination of the reference power value, power fluctuations caused by external condition changes may be encountered. For this purpose, the liquid helium storage system adopts an environmental compensation mechanism: first, an environmental factor influence model is established to analyze the influence law of external temperature, air pressure and other parameters on the refrigeration demand. Then, a compensation coefficient is introduced in the calculation of the reference power value to dynamically correct the reference value according to the actual environmental conditions. For example, when the environmental temperature is detected to rise, the system will correspondingly increase the correction coefficient of the reference power value to ensure the stability of the storage tank temperature field. At the same time, the system also establishes a seasonal variation model of the reference power value to predict and adjust the control parameters in advance, realizing stable operation throughout the year.

[0144] In the embodiments of the present application, due to the adoption of innovative technical means such as grid temperature field analysis, spatial weighted calculation, intelligent pressure relief control and device efficiency optimization, comprehensive monitoring and accurate regulation of the temperature field distribution in the liquid helium storage tank can be realized, effectively solving the problems of large temperature field monitoring blind area, inaccurate refrigeration regulation, extensive pressure relief control, low device efficiency and other problems in the prior art, thereby realizing the safe and stable operation and high efficiency and energy saving of the liquid helium storage system. Specifically, the system realizes accurate modeling of the temperature field through the grid analysis method, ensures reasonable distribution of refrigeration power through spatial weighted calculation, reduces liquid helium loss through intelligent pressure relief control, and improves the overall operation efficiency of the system through device efficiency evaluation and load optimization.

[0145] The liquid helium storage system in the embodiments of the present application will be described from the perspective of hardware processing. Please refer to Figure 3 , which is a schematic diagram of an entity device structure of the liquid helium storage system in the embodiments of the present application.

[0146] It should be noted that Figure 3 The structure of the liquid helium storage system shown is only an example and should not impose any limitation on the functions and use range of the embodiments of the present application.

[0147] As Figure 3As shown, the liquid helium storage system includes a CPU 301 which can perform various appropriate actions and processes in accordance with a program stored in a ROM 302 or a program loaded into a RAM 303 from the storage section 308, for example, to perform the method described in the above-described embodiments. In the RAM 303, various programs and data required for operation of the system are also stored. The CPU 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An I / O interface 305 is also connected to the bus 304.

[0148] Connected to the I / O interface 305 are an input section 306 including an audio input device, a push button switch, and the like; an output section 307 including a Liquid Crystal Display (LCD), an audio output device, an indicator, and the like; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as necessary. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 310 as necessary, so that a computer program read therefrom is installed in the storage section 308 as necessary.

[0149] In particular, the processes described above with reference to the flow charts can be implemented as computer software programs in accordance with embodiments of the present application. For example, embodiments of the present application include a computer program product which includes a computer program carried on a computer readable medium, the computer program containing computer programs for executing the methods illustrated by the flow charts. In such embodiments, the computer program can be downloaded and installed from a network by the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the CPU 301, various functions defined in the present application are performed.

[0150] The flow charts and block diagrams in the drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flow charts or block diagrams can represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved.

[0151] Specifically, the liquid helium storage system of the embodiment includes a processor and a memory, and the memory stores a computer program. When the computer program is executed by the processor, the working control method for large-capacity liquid helium storage provided by the above embodiment is realized.

[0152] As another aspect, the application further provides a computer-readable storage medium. The storage medium can be included in the liquid helium storage system described in the above embodiments, or can exist independently without being assembled into the liquid helium storage system. The storage medium carries one or more computer programs. When the one or more computer programs are executed by a processor of the liquid helium storage system, the liquid helium storage system realizes the working control method for large-capacity liquid helium storage provided by the above embodiments.

[0153] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

[0154] In the above embodiments, according to the context, the term "when" can be interpreted as meaning "if" or "after" or "in response to determining" or "in response to detecting". Similarly, according to the context, the phrase "upon determining" or "if detecting (the stated condition or event)" can be interpreted as meaning "if determining" or "in response to determining" or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)".

Claims

1. A method for operating control of large-capacity liquid helium storage, characterized by, The method is applied to a liquid helium storage system, and the method comprises: Collecting temperature data and pressure data at multiple height positions in a liquid helium storage tank, and constructing a temperature field distribution model based on the temperature data and the pressure data; Dividing a storage space of the liquid helium storage tank into grid units of a preset size, and calculating a temperature gradient value as a ratio of a temperature difference between each grid unit and an adjacent unit to a distance between them based on the temperature field distribution model; When the temperature gradient value of a target grid unit exceeds a preset gradient threshold value within a preset time period, determining a combined area of the target grid unit and adjacent threshold-exceeding grid units as a target area; Calculating an adjustment parameter of a refrigeration power based on a region position and a temperature gradient value of the target area; Controlling a refrigeration power output of a cold screen device in the target area according to the adjustment parameter, so that the temperature gradient value of the target area is reduced to below the preset gradient threshold value; When the temperature gradient value of the target area does not exceed the preset gradient threshold value within the preset time period, setting a current refrigeration power as a reference power value of the target area.

2. The method of claim 1, wherein, The step of controlling the refrigeration power output of the cold screen device in the target area according to the adjustment parameter, so that the temperature gradient value of the target area is reduced to below the preset gradient threshold value, specifically comprises: Determining an adjustment direction of the refrigeration power according to a positive or negative nature of a temperature gradient change rate, and calculating a corresponding correction coefficient based on an absolute value of the temperature gradient change rate; Determining a new refrigeration power output value according to a current refrigeration power and the correction coefficient, and controlling the cold screen device to operate according to the refrigeration power output value; Repeating the steps of obtaining the temperature gradient change rate and adjusting the refrigeration power until the absolute value of the temperature gradient value of the target area is less than the preset gradient threshold value for a preset number of consecutive times.

3. The method of claim 1, wherein, The step of calculating the adjustment parameter of the refrigeration power based on the region position and the temperature gradient value of the target area specifically comprises: Calculating a spatial distance from each grid unit in the target area to a corresponding cold screen device based on coordinate information of the target area; Obtaining a temperature gradient value of each grid unit, and performing spatial weighting calculation on the temperature gradient value according to the spatial distance to obtain a weighted temperature gradient value; Determining the adjustment parameter of the refrigeration power according to the weighted temperature gradient value and the preset gradient threshold value.

4. The method of claim 1, wherein, After the step of determining the combined area of the target grid unit and the adjacent threshold-exceeding grid units as the target area, the method further comprises: Obtaining a pressure value of each grid unit in the target area, and calculating a pressure difference between an average pressure value of the target area and a preset standard pressure; When the pressure difference exceeds a preset pressure difference threshold value, calculating a pressure relief rate parameter based on the pressure difference; Controlling a pressure relief valve corresponding to the target area to perform gas relief at the pressure relief rate parameter based on the pressure relief rate parameter; Recovering the relieved gas and transporting the relieved gas to a re-liquefaction device for cooling and liquefaction.

5. The method of claim 4, wherein, The step of calculating the pressure relief rate parameter based on the pressure difference specifically comprises: Obtaining a position of a grid unit with the maximum pressure value in the target area as a pressure relief priority area; calculating a flow resistance coefficient of the gas in the pipeline based on the distance from the pressure relief priority area to the nearest pressure relief valve, and calculating a theoretical pressure relief rate based on the pressure difference and the flow resistance coefficient; selecting a minimum value of the theoretical pressure relief rate and a preset safe pressure relief rate as a pressure relief rate parameter.

6. The method of claim 4, wherein, After the step of recovering the released gas and transporting the released gas to the reliquefaction device for cooling and liquefaction, the method further comprises: obtaining real-time refrigeration power and liquefaction efficiency parameters of the reliquefaction device, and calculating a minimum required refrigeration power based on the pressure relief rate parameter; when the real-time refrigeration power is less than the minimum required refrigeration power, starting a backup refrigeration unit and adjusting a power distribution ratio of each refrigeration unit according to the liquefaction efficiency parameter.

7. The method of claim 6, wherein, After the step of starting the backup refrigeration unit and adjusting the power distribution ratio of each refrigeration unit according to the liquefaction efficiency parameter, the method further comprises: collecting input power and output temperature of the refrigeration unit group after starting, calculating energy efficiency ratios of each refrigeration unit, and determining a refrigeration efficiency decay coefficient based on a deviation of the energy efficiency ratio from a nominal value; grading each refrigeration unit according to the refrigeration efficiency decay coefficient, marking a refrigeration unit whose decay degree exceeds a preset threshold as an optimization object, and calculating a contribution rate of the optimization object to total refrigeration capacity of the system; on the premise that the total refrigeration capacity of the system meets the demand, determining a backup switching order of the optimization object based on the contribution rate, and gradually transferring refrigeration load of the optimization object to a high-efficiency unit that is not an optimization object according to the backup switching order.

8. A liquid helium storage system, characterized by, The liquid helium storage system comprises one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is configured to store computer program code, the computer program code comprising computer instructions, and the one or more processors invoke the computer instructions to cause the liquid helium storage system to perform the method of any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions run on the liquid helium storage system, the liquid helium storage system performs the method of any one of claims 1-7.

10. A computer program product, characterised in that, When the computer program product runs on the liquid helium storage system, the liquid helium storage system performs the method of any one of claims 1-7.

Images