A control method and system for accelerating cooling of a conductive high-temperature superconducting magnet

Abstract

The present invention discloses a control method and system for accelerating the cooling of a conductive high-temperature superconducting magnet, which includes: obtaining historical cooling operation data of a cooling system and temperature change data of a high-temperature superconducting magnet, and analyzing and determining cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet in the historical cooling operation data; constructing a temperature change prediction model based on the cooling operation parameters and the temperature change data, and predicting and obtaining temperature change prediction data; analyzing the temperature change prediction data of the high-temperature superconducting magnet to divide the stages, and determining the temperature change characteristics of each stage; obtaining a cooling performance evaluation value based on a comprehensive analysis and evaluation of the temperature change characteristics of each stage; determining an adjustment coefficient according to the cooling performance evaluation value, and adjusting and controlling the real-time cooling operation parameters according to the adjustment coefficient. The present invention can improve the cooling efficiency of the cooling system, accelerate the cooling of the high-temperature superconducting magnet, and provide important support for the safe operation of the high-temperature superconducting magnet.

Description

Technical Field

[0001] The present invention relates to the technical field of high-temperature superconducting magnets, and in particular to a control method and system for accelerating the cooling of a conductive high-temperature superconducting magnet. Background Art

[0002] In recent years, high-temperature superconducting magnets have been increasingly used in energy, medical treatment, scientific research and other fields. However, high-temperature superconducting magnets will be affected by heat accumulation during long-term operation, so effective cooling is required to maintain their stable operation. The accelerated conduction high-temperature superconducting magnet cooling control method has emerged, aiming to accelerate the cooling speed of the magnet, improve the cooling efficiency, and reduce energy consumption by optimizing the control strategy of the cooling system, thereby ensuring the stability and performance of the high-temperature superconducting magnet.

[0003] Traditional high-temperature superconducting magnet cooling control methods often have problems such as slow cooling speed, high energy consumption, and poor stability. In order to solve these problems, control methods to accelerate the cooling of conduction-type high-temperature superconducting magnets have emerged. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a control method and system for accelerating the cooling of a conductive high-temperature superconducting magnet, comprising:

[0005] Acquire historical cooling operation data of the cooling system and temperature change data of the high-temperature superconducting magnet, analyze the historical cooling operation data and the temperature change data, and determine the cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet in the historical cooling operation data;

[0006] A temperature change prediction model is constructed based on the cooling operation parameters and the temperature change data, and the real-time cooling operation parameters of the cooling system are obtained, and the temperature change prediction model predicts the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters;

[0007] Analyze the temperature change prediction data of the high-temperature superconducting magnet, divide the temperature change prediction data into several stages, and determine the temperature change characteristics of the high-temperature superconducting magnet in each stage;

[0008] Based on comprehensive analysis and evaluation of the temperature variation characteristics of the high-temperature superconducting magnet in each stage, the cooling performance evaluation value of the cooling system is obtained;

[0009] The adjustment coefficient is determined according to the cooling performance evaluation value, and the real-time cooling operation parameters of the cooling system are adjusted and controlled according to the adjustment coefficient.

[0010] Furthermore, the acquisition of historical cooling operation data of the cooling system and temperature change data of the high-temperature superconducting magnet, and analysis of the historical cooling operation data and the temperature change data to determine the cooling operation parameters in the historical cooling operation data that affect the temperature change of the high-temperature superconducting magnet include:

[0011] Divide the historical cooling operation data into several cooling operation parameter data groups according to parameter types, and analyze the correlation between each cooling operation parameter data group and the temperature change data;

[0012] Selecting a cooling operation parameter data group with a correlation greater than a preset value as a candidate cooling operation parameter affecting the temperature change of the high-temperature superconducting magnet in the historical cooling operation data;

[0013] For each candidate cooling operation parameter, screening the temperature change data of the high temperature superconducting magnet when other candidate cooling operation parameters are the same, and determining the change amount of the temperature change data of the high temperature superconducting magnet;

[0014] The candidate cooling operation parameters whose variation is greater than a preset value are selected and determined as the cooling operation parameters that affect the temperature variation of the high-temperature superconducting magnet in the historical cooling operation data.

[0015] Furthermore, the temperature change prediction model is constructed based on the cooling operation parameters and the temperature change data, and the real-time cooling operation parameters of the cooling system are obtained, and the temperature change prediction model predicts the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters, including:

[0016] Acquire cooling operation parameters and temperature change data of high-temperature superconducting magnets, and preprocess the cooling operation parameters and temperature change data, the preprocessing includes removing erroneous data points and duplicate data points, filling missing data points, and standardizing the data;

[0017] Building a data set based on the preprocessed cooling operation parameters and the temperature change data of the high-temperature superconducting magnet, and inputting the data set into a preset neural network model to build an initial model for predicting the temperature change of the high-temperature superconducting magnet;

[0018] The data set is divided into a training set and a test set according to a preset ratio, and the training set and the test set are input into an initial model for predicting temperature changes of high-temperature superconducting magnets;

[0019] Training and testing the initial model for predicting the temperature change of the high-temperature superconducting magnet until the initial model for predicting the temperature change of the high-temperature superconducting magnet meets a preset convergence condition, thereby obtaining the temperature change prediction model of the high-temperature superconducting magnet;

[0020] The real-time cooling operation parameters of the high-temperature superconducting magnet are obtained, and the real-time cooling operation parameters are input into the temperature change prediction model of the high-temperature superconducting magnet for prediction, so as to obtain the temperature change prediction data of the high-temperature superconducting magnet.

[0021] Furthermore, the temperature change prediction data of the high temperature superconducting magnet is analyzed, the temperature change prediction data is divided into several stages, and the temperature change characteristics of the high temperature superconducting magnet in each stage are determined, including:

[0022] Acquire temperature change prediction data, and draw a temperature change-time curve graph based on the temperature change prediction data;

[0023] Determining a slope change of a curve segment from a temperature change-time curve graph, and dividing the temperature change-time curve graph into a plurality of stages according to a preset slope change amount;

[0024] The slope value and the average value of the temperature change in each stage are calculated respectively, and the slope value and the average value of the temperature change corresponding to each stage are determined as the temperature change characteristics of the high-temperature superconducting magnet in each stage.

[0025] Furthermore, the cooling performance evaluation value of the cooling system is obtained based on a comprehensive analysis and evaluation of the temperature variation characteristics of the high temperature superconducting magnet in each stage, including:

[0026] Obtain the temperature variation characteristics of the high temperature superconducting magnet in each stage, and determine the slope value and the average value of the temperature variation corresponding to each stage;

[0027] Calculate the average of the slope values ​​of all stages, and calculate the ratio of the slope value corresponding to each stage to the average value, and use the ratio as the weight corresponding to each stage;

[0028] The average value of the temperature change corresponding to each stage is evaluated and the evaluation value corresponding to each stage is obtained;

[0029] A comprehensive calculation is performed based on the weights and evaluation values ​​corresponding to each stage to obtain the cooling performance evaluation value of the cooling system.

[0030] Furthermore, the calculation formula of the cooling performance evaluation value of the cooling system is:

[0031] S= ,

[0032] Among them, S is the cooling performance evaluation value of the cooling system, ai is the weight corresponding to the i-th stage, and Pi is the evaluation value corresponding to the i-th stage.

[0033] Further, determining the adjustment coefficient according to the cooling performance evaluation value, and adjusting and controlling the real-time cooling operation parameters of the cooling system according to the adjustment coefficient, includes:

[0034] A correspondence relationship between the adjustment coefficient and the cooling performance evaluation value interval is preset, and the correspondence relationship between the adjustment coefficient and the cooling performance evaluation value interval is associated with a corresponding adjustment coefficient for each cooling performance evaluation value interval;

[0035] Acquire a cooling performance evaluation value, and based on a mapping relationship between a cooling performance evaluation value interval to which the cooling performance evaluation value belongs and an adjustment coefficient corresponding to the cooling performance evaluation value interval, select an adjustment coefficient corresponding to the cooling performance evaluation value interval;

[0036] Each parameter in the real-time cooling operation parameter is multiplied according to the adjustment coefficient to complete the adjustment control of the real-time cooling operation parameter of the cooling system.

[0037] The present invention also provides a control system for accelerating the cooling of a conductive high-temperature superconducting magnet, comprising:

[0038] An acquisition module is used to acquire historical cooling operation data of the cooling system and temperature change data of the high-temperature superconducting magnet, and analyze the historical cooling operation data and temperature change data to determine cooling operation parameters in the historical cooling operation data that affect the temperature change of the high-temperature superconducting magnet;

[0039] A prediction module is used to build a temperature change prediction model based on cooling operation parameters and temperature change data, and obtain real-time cooling operation parameters of the cooling system, and the temperature change prediction model predicts the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters;

[0040] A determination module is used to analyze the temperature change prediction data of the high-temperature superconducting magnet, divide the temperature change prediction data into several stages, and determine the temperature change characteristics of the high-temperature superconducting magnet in each stage;

[0041] An evaluation module, used to obtain a cooling performance evaluation value of the cooling system based on a comprehensive analysis and evaluation of the temperature variation characteristics of the high-temperature superconducting magnet in each stage;

[0042] The control module is used to determine the adjustment coefficient according to the cooling performance evaluation value, and adjust and control the real-time cooling operation parameters of the cooling system according to the adjustment coefficient.

[0043] Compared with the prior art, the control method and system for accelerating the cooling of a conductive high-temperature superconducting magnet according to the embodiment of the present invention has the following beneficial effects:

[0044] The present invention determines the main cooling operation parameters that affect the temperature change of high-temperature superconducting magnets, providing an important basis for understanding the working mechanism of the cooling system;

[0045] The present invention constructs a temperature change prediction model based on historical data and cooling operation parameters, which can predict the temperature change of the high-temperature superconducting magnet according to the real-time cooling operation parameters, providing a basis for real-time control and regulation;

[0046] The present invention analyzes the temperature change prediction data, divides it into several stages, and determines the temperature change characteristics of the high-temperature superconducting magnet in each stage, which helps to deeply understand the dynamic changes in the cooling process;

[0047] The cooling performance evaluation value of the present invention for cooling a high-temperature superconducting magnet can help evaluate the working efficiency, stability and energy efficiency of the cooling system, and provide a basis for system optimization and improvement;

[0048] The present invention determines the adjustment coefficient based on the cooling performance evaluation value, and applies it to the real-time cooling operation parameters for adjustment and control, thereby realizing real-time optimization and adjustment of the cooling system and improving the adaptability and stability of the system.

[0049] In summary, the present invention can help achieve an in-depth understanding, prediction and optimized control of the high-temperature superconducting magnet cooling system, thereby improving the working efficiency, stability and reliability of the cooling system, accelerating the cooling of the high-temperature superconducting magnet, and providing important support for the safe operation and performance improvement of the high-temperature superconducting magnet. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the flow structure of a control method for accelerating the cooling of a conductive high-temperature superconducting magnet in an embodiment of the present invention;

[0051] Figure 2 It is a schematic diagram of the composition of a control system for accelerating the cooling of a conductive high-temperature superconducting magnet in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0053] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0054] The terms "second" and "second" are used for descriptive purposes only and should not be understood as indicating or implying a relative degree of importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined with "second" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "multiple" means two or more.

[0055] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a cooling connection, or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technical personnel in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0056] like Figure 1 As shown, in an embodiment of the present application, a control method for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, comprising: S100: acquiring historical cooling operation data of a cooling system and temperature change data of a high-temperature superconducting magnet, analyzing the historical cooling operation data and the temperature change data, and determining cooling operation parameters in the historical cooling operation data that affect the temperature change of the high-temperature superconducting magnet; S200: constructing a temperature change prediction model based on the cooling operation parameters and the temperature change data, and acquiring real-time cooling operation parameters of the cooling system, and using the temperature change prediction model to predict the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters; S300: analyzing the temperature change prediction data of the high-temperature superconducting magnet, dividing the temperature change prediction data into several stages, and determining the temperature change characteristics of the high-temperature superconducting magnet in each stage; S400: obtaining a cooling performance evaluation value of the cooling system based on a comprehensive analysis and evaluation of the temperature change characteristics of the high-temperature superconducting magnet in each stage; S500: determining an adjustment coefficient according to the cooling performance evaluation value, and adjusting and controlling the real-time cooling operation parameters of the cooling system according to the adjustment coefficient.

[0057] Furthermore, the present invention determines the main cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet, providing an important basis for understanding the working mechanism of the cooling system; the present invention constructs a temperature change prediction model based on historical data and cooling operation parameters, which can predict the temperature change of the high-temperature superconducting magnet according to the real-time cooling operation parameters, providing a basis for real-time control and adjustment; the present invention analyzes the temperature change prediction data, divides it into several stages, and determines the temperature change characteristics of the high-temperature superconducting magnet in each stage, which helps to deeply understand the dynamic changes in the cooling process; the cooling performance evaluation value of the high-temperature superconducting magnet cooling of the present invention can help evaluate the working efficiency, stability and energy efficiency of the cooling system, and provide a basis for system optimization and improvement; the present invention determines the adjustment coefficient based on the cooling performance evaluation value, and applies it to the real-time cooling operation parameters for adjustment and control, thereby realizing real-time optimization and adjustment of the cooling system and improving the adaptability and stability of the system; in summary, the present invention can help to achieve an in-depth understanding, prediction and optimization control of the high-temperature superconducting magnet cooling system, thereby improving the working efficiency, stability and reliability of the cooling system, so as to accelerate the cooling of the high-temperature superconducting magnet, and provide important support for the safe operation and performance improvement of the high-temperature superconducting magnet.

[0058] In an embodiment of the present application, a control method for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, wherein historical cooling operation data of a cooling system and temperature change data of a high-temperature superconducting magnet are obtained, and the historical cooling operation data and the temperature change data are analyzed to determine the cooling operation parameters in the historical cooling operation data that affect the temperature change of the high-temperature superconducting magnet, including: dividing the historical cooling operation data into a plurality of cooling operation parameter data groups according to parameter type, and analyzing the correlation between each cooling operation parameter data group and the temperature change data; selecting the cooling operation parameter data group with a correlation greater than a preset value as a candidate cooling operation parameter in the historical cooling operation data that affects the temperature change of the high-temperature superconducting magnet; for each candidate cooling operation parameter, screening the temperature change data of the high-temperature superconducting magnet when other candidate cooling operation parameters are the same, and determining the change amount of the temperature change data of the high-temperature superconducting magnet; selecting the candidate cooling operation parameter with a change amount greater than the preset value as the cooling operation parameter in the historical cooling operation data that affects the temperature change of the high-temperature superconducting magnet.

[0059] Specifically, the historical cooling operation data are divided into several cooling operation parameter data groups according to parameter types, such as cooling medium flow rate, temperature gradient, cooling medium pressure, etc.; the correlation between each cooling operation parameter data group and the temperature change data is analyzed, and statistical methods such as correlation coefficient can be used to evaluate the degree of influence on temperature change; cooling operation parameter data groups with correlation greater than a preset value are selected as candidate cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet in the historical cooling operation data; for each candidate cooling operation parameter, the temperature change data of the high-temperature superconducting magnet when other candidate cooling operation parameters are the same are screened, and the change amount of the temperature change data of the high-temperature superconducting magnet is determined; candidate cooling operation parameters with a change amount greater than the preset value are selected and determined as cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet in the historical cooling operation data. The above steps determine the main cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet, providing an important basis for understanding the working mechanism of the cooling system.

[0060] In an embodiment of the present application, a control method for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, wherein a temperature change prediction model is constructed based on cooling operation parameters and temperature change data, and real-time cooling operation parameters of the cooling system are obtained, and the temperature change prediction model predicts the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters, including: obtaining the cooling operation parameters and the temperature change data of the high-temperature superconducting magnet, and preprocessing the cooling operation parameters and the temperature change data, wherein the preprocessing includes removing erroneous data points and duplicate data points, filling in missing data points, and standardizing the data; constructing a temperature change prediction model based on the preprocessed cooling operation parameters and the temperature change data of the high-temperature superconducting magnet; and The method comprises the following steps: obtaining a data set, inputting the data set into a preset neural network model, and constructing an initial model for predicting temperature changes of a high-temperature superconducting magnet; dividing the data set into a training set and a test set according to a preset ratio, and inputting the training set and the test set into the initial model for predicting temperature changes of a high-temperature superconducting magnet; training and testing the initial model for predicting temperature changes of a high-temperature superconducting magnet until the initial model for predicting temperature changes of a high-temperature superconducting magnet meets a preset convergence condition, and obtaining a temperature change prediction model for a high-temperature superconducting magnet; obtaining real-time cooling operation parameters of the high-temperature superconducting magnet, and inputting the real-time cooling operation parameters into the temperature change prediction model for the high-temperature superconducting magnet for prediction, and obtaining temperature change prediction data of the high-temperature superconducting magnet.

[0061] Specifically, the cooling operation parameters and the temperature change data of the high-temperature superconducting magnet are obtained, and preprocessed, including removing erroneous data points and duplicate data points, filling missing data points, and standardizing the data; a data set is constructed based on the preprocessed cooling operation parameters and the temperature change data of the high-temperature superconducting magnet; the data set is input into a preset neural network model to construct an initial model for predicting the temperature change of the high-temperature superconducting magnet; the data set is divided into a training set and a test set according to a preset ratio; the initial model for predicting the temperature change of the high-temperature superconducting magnet is trained and tested until the model meets the preset convergence conditions, and a temperature change prediction model for the high-temperature superconducting magnet is obtained; the real-time cooling operation parameters of the high-temperature superconducting magnet are obtained, and the real-time cooling operation parameters are input into the temperature change prediction model of the high-temperature superconducting magnet for prediction, and the temperature change prediction data of the high-temperature superconducting magnet are obtained. The above steps construct a temperature change prediction model based on historical data and cooling operation parameters, which can predict the temperature change of the high-temperature superconducting magnet according to the real-time cooling operation parameters, and provide a basis for real-time control and regulation.

[0062] In an embodiment of the present application, a control method for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, wherein the temperature change prediction data of the high-temperature superconducting magnet is analyzed, the temperature change prediction data is divided into several stages, and the temperature change characteristics of the high-temperature superconducting magnet in each stage are determined, including: obtaining the temperature change prediction data, and drawing a temperature change-time curve diagram according to the temperature change prediction data; determining the slope change of a curve segment from the temperature change-time curve diagram, and dividing the temperature change-time curve diagram into several stages according to a preset slope change amount; respectively calculating the slope value and the temperature change average value in each stage, and determining the slope value and the temperature change average value corresponding to each stage as the temperature change characteristics of the high-temperature superconducting magnet in each stage.

[0063] Specifically, obtain temperature change prediction data, which is the temperature change data of the high-temperature superconducting magnet predicted by the model over time; plot the temperature change prediction data into a temperature change-time curve to intuitively show the temperature change trend of the high-temperature superconducting magnet; determine the slope change of the curve segment from the temperature change-time curve, and divide the temperature change-time curve into several stages according to the preset slope change; calculate the slope value and the average temperature change value in each stage respectively, and determine the slope value and the average temperature change value corresponding to each stage as the temperature change characteristics of the high-temperature superconducting magnet in each stage. The above steps analyze the temperature change prediction data, divide it into several stages, and determine the temperature change characteristics of the high-temperature superconducting magnet in each stage, which helps to deeply understand the dynamic changes in the cooling process.

[0064] In an embodiment of the present application, a control method for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, wherein the method is based on a comprehensive analysis and evaluation of the temperature change characteristics of the high-temperature superconducting magnet in each stage to obtain a cooling performance evaluation value of the cooling system, including: obtaining the temperature change characteristics of the high-temperature superconducting magnet in each stage, and determining the slope value and the temperature change average value corresponding to each stage; calculating the average value of the slope values ​​of all stages, and calculating the ratio of the slope value corresponding to each stage to the average value, and using the ratio as the weight corresponding to each stage; evaluating and valuing the temperature change average value corresponding to each stage to obtain an evaluation value corresponding to each stage; and performing a comprehensive calculation based on the weight and evaluation value corresponding to each stage to obtain a cooling performance evaluation value of the cooling system.

[0065] Specifically, the temperature change characteristics of the high-temperature superconducting magnet in each stage include the slope value and the average value of the temperature change; the average value of the slope values ​​of all stages is calculated, and the ratio of the slope value corresponding to each stage to the average value is calculated, and the ratio is used as the weight corresponding to each stage; the average value of the temperature change corresponding to each stage is evaluated and valued according to the preset evaluation criteria; based on the weight and evaluation value corresponding to each stage, a comprehensive calculation is performed to obtain the cooling performance evaluation value of the cooling system. The cooling performance evaluation value of the high-temperature superconducting magnet cooled by the above steps can help evaluate the working efficiency, stability and energy efficiency of the cooling system, and provide a basis for system optimization and improvement.

[0066] In an embodiment of the present application, a control method for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, and the calculation formula of the cooling performance evaluation value of the cooling system is:

[0067] S= ,

[0068] Among them, S is the cooling performance evaluation value of the cooling system, ai is the weight corresponding to the i-th stage, and Pi is the evaluation value corresponding to the i-th stage.

[0069] In an embodiment of the present application, a control method for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, wherein the adjustment coefficient is determined according to the cooling performance evaluation value, and the real-time cooling operation parameters of the cooling system are adjusted and controlled according to the adjustment coefficient, including: presetting the adjustment coefficient-cooling performance evaluation value interval correspondence relationship, and the adjustment coefficient-cooling performance evaluation value interval correspondence relationship is associated with a corresponding adjustment coefficient for each cooling performance evaluation value interval; obtaining the cooling performance evaluation value, and selecting the adjustment coefficient corresponding to the cooling performance evaluation value interval based on the mapping relationship of the cooling performance evaluation value interval to which the cooling performance evaluation value belongs within the adjustment coefficient-cooling performance evaluation value interval correspondence relationship; multiplying each parameter in the real-time cooling operation parameter according to the adjustment coefficient to complete the adjustment control of the real-time cooling operation parameters of the cooling system. The above steps determine the adjustment coefficient based on the cooling performance evaluation value, and apply it to the real-time cooling operation parameters for adjustment and control, thereby realizing real-time optimization and adjustment of the cooling system and improving the adaptability and stability of the system.

[0070] Specifically, for each cooling performance evaluation value interval, a corresponding adjustment coefficient is set to form a correspondence between the adjustment coefficient and the cooling performance evaluation value interval; the real-time cooling performance evaluation value is obtained, and based on the mapping relationship between the cooling performance evaluation value interval to which the cooling performance evaluation value belongs within the correspondence between the adjustment coefficient and the cooling performance evaluation value interval, the adjustment coefficient corresponding to the cooling performance evaluation value interval is selected; according to the selected adjustment coefficient, each parameter in the real-time cooling operation parameters is multiplied to complete the adjustment control of the real-time cooling operation parameters of the cooling system.

[0071] like Figure 2 As shown, in an embodiment of the present application, a control system for accelerating the cooling of a conductive high-temperature superconducting magnet is provided, including: an acquisition module, which is used to acquire historical cooling operation data of a cooling system and temperature change data of a high-temperature superconducting magnet, and analyze the historical cooling operation data and the temperature change data to determine the cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet in the historical cooling operation data; a prediction module, which is used to construct a temperature change prediction model based on the cooling operation parameters and the temperature change data, and acquire the real-time cooling operation parameters of the cooling system, and the temperature change prediction model predicts the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters; a determination module, which is used to analyze the temperature change prediction data of the high-temperature superconducting magnet, divide the temperature change prediction data into several stages, and determine the temperature change characteristics of the high-temperature superconducting magnet in each stage; an evaluation module, which is used to obtain a cooling performance evaluation value of the cooling system based on a comprehensive analysis and evaluation of the temperature change characteristics of the high-temperature superconducting magnet in each stage; a control module, which is used to determine an adjustment coefficient according to the cooling performance evaluation value, and adjust and control the real-time cooling operation parameters of the cooling system according to the adjustment coefficient.

[0072] In summary, the embodiment of the present invention provides a control method and system for accelerating the cooling of a conductive high-temperature superconducting magnet, which includes: obtaining historical cooling operation data of the cooling system and temperature change data of the high-temperature superconducting magnet, and analyzing and determining the cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet in the historical cooling operation data; constructing a temperature change prediction model based on the cooling operation parameters and the temperature change data, and predicting the temperature change prediction data; analyzing the temperature change prediction data of the high-temperature superconducting magnet to divide the stages, and determining the temperature change characteristics of each stage; based on a comprehensive analysis and evaluation of the temperature change characteristics of each stage, obtaining a cooling performance evaluation value; determining an adjustment coefficient according to the cooling performance evaluation value, and adjusting and controlling the real-time cooling operation parameters according to the adjustment coefficient. The present invention can improve the cooling efficiency of the cooling system to accelerate the cooling of the high-temperature superconducting magnet, and provide important support for the safe operation of the high-temperature superconducting magnet.

[0073] Finally, it should be noted that: Obviously, a person skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technology, the present invention is also intended to include these modifications and variations.

[0074] The above is only an example of implementation of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be regarded as falling within the scope of protection of the present invention and being restricted. Technical personnel in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0075] The term "comprises" or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that includes a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0076] So far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings. However, it is easy for a person skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, a person skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0077] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A control method for accelerating the cooling of a conductive high-temperature superconducting magnet, characterized in that: include: Acquire historical cooling operation data of the cooling system and temperature change data of the high-temperature superconducting magnet, analyze the historical cooling operation data and the temperature change data, and determine the cooling operation parameters that affect the temperature change of the high-temperature superconducting magnet in the historical cooling operation data; A temperature change prediction model is constructed based on the cooling operation parameters and the temperature change data, and the real-time cooling operation parameters of the cooling system are obtained, and the temperature change prediction model predicts the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters; Analyze the temperature change prediction data of the high-temperature superconducting magnet, divide the temperature change prediction data into several stages, and determine the temperature change characteristics of the high-temperature superconducting magnet in each stage; Based on comprehensive analysis and evaluation of the temperature variation characteristics of the high-temperature superconducting magnet in each stage, the cooling performance evaluation value of the cooling system is obtained; The adjustment coefficient is determined according to the cooling performance evaluation value, and the real-time cooling operation parameters of the cooling system are adjusted and controlled according to the adjustment coefficient.

2. A control method for accelerating the cooling of a conductive high-temperature superconducting magnet according to claim 1, characterized in that: The acquiring of historical cooling operation data of the cooling system and temperature change data of the high-temperature superconducting magnet, and analyzing the historical cooling operation data and the temperature change data to determine cooling operation parameters in the historical cooling operation data that affect the temperature change of the high-temperature superconducting magnet include: Divide the historical cooling operation data into several cooling operation parameter data groups according to parameter types, and analyze the correlation between each cooling operation parameter data group and the temperature change data; Selecting a cooling operation parameter data group with a correlation greater than a preset value as a candidate cooling operation parameter affecting the temperature change of the high-temperature superconducting magnet in the historical cooling operation data; For each candidate cooling operation parameter, screening the temperature change data of the high temperature superconducting magnet when other candidate cooling operation parameters are the same, and determining the change amount of the temperature change data of the high temperature superconducting magnet; The candidate cooling operation parameters whose variation is greater than a preset value are selected and determined as the cooling operation parameters that affect the temperature variation of the high-temperature superconducting magnet in the historical cooling operation data.

3. A control method for accelerating the cooling of a conductive high-temperature superconducting magnet according to claim 2, characterized in that: The method comprises: building a temperature change prediction model based on the cooling operation parameters and the temperature change data, obtaining the real-time cooling operation parameters of the cooling system, and using the temperature change prediction model to predict the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters. Acquire cooling operation parameters and temperature change data of high-temperature superconducting magnets, and preprocess the cooling operation parameters and temperature change data, the preprocessing includes removing erroneous data points and duplicate data points, filling missing data points, and standardizing the data; Building a data set based on the preprocessed cooling operation parameters and the temperature change data of the high-temperature superconducting magnet, and inputting the data set into a preset neural network model to build an initial model for predicting the temperature change of the high-temperature superconducting magnet; The data set is divided into a training set and a test set according to a preset ratio, and the training set and the test set are input into an initial model for predicting temperature changes of high-temperature superconducting magnets; Training and testing the initial model for predicting the temperature change of the high-temperature superconducting magnet until the initial model for predicting the temperature change of the high-temperature superconducting magnet meets a preset convergence condition, thereby obtaining the temperature change prediction model of the high-temperature superconducting magnet; The real-time cooling operation parameters of the high-temperature superconducting magnet are obtained, and the real-time cooling operation parameters are input into the temperature change prediction model of the high-temperature superconducting magnet for prediction, so as to obtain the temperature change prediction data of the high-temperature superconducting magnet.

4. A control method for accelerating the cooling of a conductive high-temperature superconducting magnet according to claim 3, characterized in that: The temperature change prediction data of the high-temperature superconducting magnet is analyzed, the temperature change prediction data is divided into several stages, and the temperature change characteristics of the high-temperature superconducting magnet in each stage are determined, including: Acquire temperature change prediction data, and draw a temperature change-time curve graph based on the temperature change prediction data; Determining a slope change of a curve segment from a temperature change-time curve graph, and dividing the temperature change-time curve graph into a plurality of stages according to a preset slope change amount; The slope value and the average value of the temperature change in each stage are calculated respectively, and the slope value and the average value of the temperature change corresponding to each stage are determined as the temperature change characteristics of the high-temperature superconducting magnet in each stage.

5. A control method for accelerating cooling of a conductive high temperature superconducting magnet according to claim 4, characterized in that: The cooling performance evaluation value of the cooling system is obtained based on a comprehensive analysis and evaluation of the temperature variation characteristics of the high-temperature superconducting magnet in each stage, including: Obtain the temperature variation characteristics of the high temperature superconducting magnet in each stage, and determine the slope value and the average value of the temperature variation corresponding to each stage; Calculate the average of the slope values ​​of all stages, and calculate the ratio of the slope value corresponding to each stage to the average value, and use the ratio as the weight corresponding to each stage; The average value of the temperature change corresponding to each stage is evaluated and the evaluation value corresponding to each stage is obtained; A comprehensive calculation is performed based on the weights and evaluation values ​​corresponding to each stage to obtain the cooling performance evaluation value of the cooling system.

6. A control method for accelerating the cooling of a conductive high-temperature superconducting magnet according to claim 5, characterized in that: The calculation formula of the cooling performance evaluation value of the cooling system is: S= ， Among them, S is the cooling performance evaluation value of the cooling system, ai is the weight corresponding to the i-th stage, and Pi is the evaluation value corresponding to the i-th stage.

7. A control method for accelerating cooling of a conductive high temperature superconducting magnet according to claim 5, characterized in that: Determining the adjustment coefficient according to the cooling performance evaluation value, and adjusting and controlling the real-time cooling operation parameters of the cooling system according to the adjustment coefficient, includes: A correspondence relationship between the adjustment coefficient and the cooling performance evaluation value interval is preset, and the correspondence relationship between the adjustment coefficient and the cooling performance evaluation value interval is associated with a corresponding adjustment coefficient for each cooling performance evaluation value interval; Acquire a cooling performance evaluation value, and based on a mapping relationship between a cooling performance evaluation value interval to which the cooling performance evaluation value belongs and an adjustment coefficient corresponding to the cooling performance evaluation value interval, select an adjustment coefficient corresponding to the cooling performance evaluation value interval; Each parameter in the real-time cooling operation parameter is multiplied according to the adjustment coefficient to complete the adjustment control of the real-time cooling operation parameter of the cooling system.

8. A control system for accelerating the cooling of a conductive high-temperature superconducting magnet, characterized in that: include: An acquisition module is used to acquire historical cooling operation data of the cooling system and temperature change data of the high-temperature superconducting magnet, and analyze the historical cooling operation data and temperature change data to determine cooling operation parameters in the historical cooling operation data that affect the temperature change of the high-temperature superconducting magnet; A prediction module is used to build a temperature change prediction model based on cooling operation parameters and temperature change data, and obtain real-time cooling operation parameters of the cooling system, and the temperature change prediction model predicts the temperature change prediction data of the high-temperature superconducting magnet according to the real-time cooling operation parameters; A determination module is used to analyze the temperature change prediction data of the high-temperature superconducting magnet, divide the temperature change prediction data into several stages, and determine the temperature change characteristics of the high-temperature superconducting magnet in each stage; An evaluation module, used to obtain a cooling performance evaluation value of the cooling system based on a comprehensive analysis and evaluation of the temperature variation characteristics of the high-temperature superconducting magnet in each stage; The control module is used to determine the adjustment coefficient according to the cooling performance evaluation value, and adjust and control the real-time cooling operation parameters of the cooling system according to the adjustment coefficient.

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