Thermal analysis method and system for conduction cooling type high-temperature superconducting magnet

Abstract

The invention relates to the technical field of thermal analysis of superconducting magnets, in particular to a thermal analysis method and system for a conduction cooling type high-temperature superconducting magnet, and the method comprises the steps: obtaining the thermal imaging information of a superconducting magnet to be analyzed; and determining the heat conduction speed of the superconducting magnet according to the thermal imaging information, and determining the cooling score of the superconducting magnet to be analyzed according to the heat conduction speed. And determining a two-dimensional temperature distribution diagram of the superconducting magnet according to the thermal imaging information, and correcting the cooling score of the superconducting magnet according to the two-dimensional temperature distribution diagram. And determining the quality grade of the superconducting magnet based on a relationship between the cooling score of the superconducting magnet and a preset first preset cooling score and a preset second preset cooling score. The cooling performance and the quality grade of the conduction cooling type high-temperature superconducting magnet can be effectively evaluated through the thermal imaging information and the two-dimensional temperature distribution diagram in combination with the heat conduction speed and the preset scoring standard.

Description

Technical Field

[0001] This invention relates to the field of thermal analysis technology for superconducting magnets, and more specifically, to a thermal analysis method and system for conductive-cooled high-temperature superconducting magnets. Background Technology

[0002] Thermal analysis is a crucial step in the research and application of superconducting magnets, especially in high-temperature superconducting magnets, where thermal management is paramount due to their high operating temperatures. Conductive cooling of high-temperature superconducting magnets achieves cooling through solid-state heat conduction. Compared to traditional methods such as liquid nitrogen cooling, conductive cooling offers advantages such as simple structure and high reliability. However, to fully leverage its advantages, a thorough understanding and analysis of its thermal characteristics is necessary.

[0003] Currently, thermal analysis of superconducting magnets mainly focuses on liquid nitrogen or liquid hydrogen cooling methods, with relatively little research on conductive cooling methods. Thermal analysis of conductively cooled high-temperature superconducting magnets not only relates to the magnet's performance stability and lifespan but also directly affects its reliability in various application scenarios.

[0004] Therefore, developing a thermal analysis method and system suitable for conductive cooling high-temperature superconducting magnets is of great significance for promoting the development of superconducting magnet technology, especially for optimizing the performance of high-temperature superconducting magnets in practical applications. Summary of the Invention

[0005] In view of this, the present invention proposes a thermal analysis method and system for conductive-cooled high-temperature superconducting magnets, aiming to provide a thermal analysis technology for conductive-cooled high-temperature superconducting magnets, and to fill the gap in the existing thermal analysis technology for conductive-cooled high-temperature superconducting magnets.

[0006] This invention proposes a thermal analysis method for conductive-cooled high-temperature superconducting magnets, comprising:

[0007] Acquire thermal imaging information of the superconducting magnet to be analyzed;

[0008] Based on the thermal imaging information, the thermal conduction velocity of the superconducting magnet is determined, and the cooling score of the superconducting magnet to be analyzed is determined based on the thermal conduction velocity.

[0009] Based on the thermal imaging information, a two-dimensional temperature distribution map of the superconducting magnet is determined, and the cooling score of the superconducting magnet is corrected based on the two-dimensional temperature analysis map.

[0010] Based on the relationship between the cooling score of the superconducting magnet and a pre-set first and second preset cooling score, the quality grade of the superconducting magnet is determined, wherein:

[0011] When the cooling score is lower than or equal to the first preset cooling score, the quality grade of the superconducting magnet is determined to be Grade 1.

[0012] When the cooling score is higher than the first preset cooling score and the cooling score is lower than or equal to the second preset cooling score, the quality grade of the superconducting magnet is determined to be level two.

[0013] When the cooling score is higher than the second preset cooling score, the quality level of the superconducting magnet is determined to be level three; and level one < level two < level three.

[0014] Furthermore, based on the thermal imaging information, the thermal conduction velocity of the superconducting magnet is determined, and a cooling score of the superconducting magnet to be analyzed is determined based on the thermal conduction velocity, including:

[0015] Acquire thermal imaging image information of the superconducting magnet to be analyzed during a preset time period, and determine the geometric dimensions, thermal curve, and thermal conduction velocity of the superconducting magnet based on the image information;

[0016] The cross-sectional area of ​​the superconducting magnet is determined based on its geometric dimensions.

[0017] Based on the geometry, thermal profile, and thermal conductivity of the superconducting magnet, a thermal conductivity score is determined using a formula. Then, based on the relationship between the thermal conductivity score and a pre-set thermal conductivity score, a cooling score is determined for the superconducting magnet.

[0018] Furthermore, when determining the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and a pre-set preset thermal conductivity score, the following steps are included:

[0019] Based on the geometric dimensions of the superconducting magnet, a first preset thermal conductivity score and a second preset thermal conductivity score are preset, wherein the first preset thermal conductivity score is less than the second preset thermal conductivity score.

[0020] The cooling score of the superconducting magnet is determined based on the relationship between the thermal conductivity score and each preset thermal conductivity score.

[0021] When the thermal conductivity score is less than or equal to the first preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M1.

[0022] When the thermal conductivity score is greater than the first preset thermal conductivity score and the thermal conductivity score is less than or equal to the second preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M2.

[0023] When the thermal conductivity score is greater than the second preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M3;

[0024] Furthermore, M1 < M2 < M3.

[0025] Furthermore, when determining the two-dimensional temperature distribution map of the superconducting magnet based on the thermal imaging information, and correcting the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map, the process includes:

[0026] Select any coordinate point on the two-dimensional temperature distribution map, and determine the temperature detection point and the area of ​​the detection point based on a preset radius;

[0027] The average temperature of the detection point is determined based on the temperature of each coordinate point within the area of ​​the detection point.

[0028] The average temperature between each detection point in the two-dimensional temperature distribution map is obtained. A comparison is made between the average temperature between each detection point and the average temperature of each detection point itself. Based on the comparison result, it is determined whether the average temperature of each detection point is an abnormal temperature.

[0029] When the average temperature of the detection point is consistent with the average temperature among all the detection points, it is determined that the average temperature of the detection point is not an abnormal temperature.

[0030] When the average temperature at the detection point is inconsistent with the average temperature among all the detection points, a preset temperature range is determined based on the average temperature among all the detection points. Furthermore, based on the relationship between the average temperature at the detection point and the preset temperature range, it is determined whether the average temperature at the detection point is an abnormal temperature.

[0031] A first preset temperature and a second preset temperature are predetermined within the preset temperature range, wherein the first preset temperature is less than the second preset temperature;

[0032] When the average temperature of the detection point is between the first preset temperature and the second preset temperature, it is determined that the average temperature of the detection point is not an abnormal temperature.

[0033] When the average temperature of the detection point is higher than the second preset temperature, or when the average temperature of the detection point is lower than the first preset temperature, the average temperature of the detection point is determined to be an abnormal temperature.

[0034] The number of detection points with abnormal temperatures is obtained, and the correction coefficient for correcting the cooling score of the superconducting magnet is determined based on the number of detection points with abnormal temperatures.

[0035] Furthermore, when determining the correction factor for correcting the cooling score of the superconducting magnet based on the number of detection points with abnormal temperatures, the following factors are included:

[0036] A first preset quantity and a second preset quantity are preset, wherein the first preset quantity is less than the second preset quantity;

[0037] Based on the relationship between the number of detection points for abnormal temperatures and each preset number, a correction coefficient is determined when correcting the cooling score of the superconducting magnet, where:

[0038] When the number of detection points for abnormal temperatures is less than or equal to the first preset number, the correction coefficient N3 is determined.

[0039] When the number of detection points for abnormal temperature is greater than the first preset number, and the number of detection points for abnormal temperature is less than or equal to the second preset number, then the correction coefficient N2 is determined.

[0040] When the number of detection points with abnormal temperatures is greater than the second preset number, the correction coefficient N1 is determined.

[0041] Furthermore, N1 < N2 < N3 < 1.

[0042] Compared with existing technologies, the advantages of this invention are as follows: By acquiring thermal imaging information of the superconducting magnet to be analyzed, a reliable data foundation is provided for subsequent thermal analysis. Thermal imaging technology can accurately capture the temperature distribution on the surface and inside of the superconducting magnet, thus providing detailed data support for subsequent calculation of heat conduction velocity and plotting of two-dimensional temperature distribution maps. Secondly, by analyzing the thermal imaging information to determine the heat conduction velocity and calculating the cooling score based on the heat conduction velocity, this process can accurately reflect the thermal conduction performance of the superconducting magnet. Heat conduction velocity is one of the important indicators of the thermal performance of superconducting magnets, and its accurate measurement can help us better understand the cooling efficiency and overall thermal management of superconducting magnets. In addition, plotting a two-dimensional temperature distribution map of the superconducting magnet and correcting the cooling score based on this map further improves the accuracy of the cooling score. The two-dimensional temperature distribution map can intuitively display the temperature differences in various regions of the superconducting magnet. By analyzing these differences, the cooling score can be more accurately corrected to make it closer to the actual situation. Finally, by comparing the cooling score with a preset cooling score standard, the quality grade of the superconducting magnet can be scientifically determined. This process not only considers the absolute value of the cooling score but also grades and evaluates superconducting magnets by setting different scoring thresholds. This allows for the grading of superconducting magnet quality based on actual conditions, providing a reliable basis for quality control and optimization.

[0043] On the other hand, this application also provides a thermal analysis system for high-temperature superconducting magnets with conductive cooling, comprising:

[0044] The thermal imaging detection module is used to acquire thermal imaging information of the superconducting magnet to be analyzed.

[0045] An evaluation module, electrically connected to the thermal imaging detection module, is used to determine the heat conduction velocity of the superconducting magnet based on the thermal imaging information, and to determine the cooling score of the superconducting magnet to be analyzed based on the heat conduction velocity; the evaluation module is also used to determine a two-dimensional temperature distribution map of the superconducting magnet based on the thermal imaging information, and to correct the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map;

[0046] A rating module, electrically connected to the evaluation module, determines the quality grade of the superconducting magnet based on the relationship between the cooling score of the superconducting magnet and a pre-set first and second preset cooling scores, wherein:

[0047] When the cooling score is lower than or equal to the first preset cooling score, the rating module determines the quality level of the superconducting magnet to be Level 1.

[0048] When the cooling score is higher than the first preset cooling score and the cooling score is lower than or equal to the second preset cooling score, the rating module determines that the quality level of the superconducting magnet is level two.

[0049] When the cooling score is higher than the second preset cooling score, the rating module determines the quality level of the superconducting magnet to be level three; and level one < level two < level three.

[0050] Furthermore, the evaluation module, when determining the thermal conduction velocity of the superconducting magnet based on the thermal imaging information and determining the cooling score of the superconducting magnet to be analyzed based on the thermal conduction velocity, includes:

[0051] The evaluation module is also used to acquire thermal imaging image information of the superconducting magnet to be analyzed during a preset time period, and to determine the geometric dimensions, thermal curve, and thermal conduction velocity of the superconducting magnet based on the image information.

[0052] The evaluation module is also used to determine the cross-sectional area of ​​the superconducting magnet based on its geometric dimensions.

[0053] The evaluation module is also used to determine the thermal conductivity score of the superconducting magnet based on a formula according to the geometry, thermal curve and thermal conduction velocity of the superconducting magnet, and to determine the cooling score of the superconducting magnet according to the relationship between the thermal conductivity score and a preset thermal conductivity score.

[0054] Furthermore, the evaluation module is also used to determine the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and a pre-set preset thermal conductivity score, including:

[0055] The evaluation module is also used to pre-configure a first preset thermal conductivity score and a second preset thermal conductivity score based on the geometric dimensions of the superconducting magnet, wherein the first preset thermal conductivity score is less than the second preset thermal conductivity score.

[0056] The evaluation module is also used to determine the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and each preset thermal conductivity score.

[0057] When the thermal conductivity score is less than or equal to the first preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet to be M1;

[0058] When the thermal conductivity score is greater than the first preset thermal conductivity score and the thermal conductivity score is less than or equal to the second preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet to be M2.

[0059] When the thermal conductivity score is greater than the second preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet to be M3;

[0060] Furthermore, M1 < M2 < M3.

[0061] Furthermore, the evaluation module is also used to determine a two-dimensional temperature distribution map of the superconducting magnet based on the thermal imaging information, and to correct the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map, including:

[0062] The evaluation module is also used to select any coordinate point of the two-dimensional temperature distribution map, and determine the temperature detection point and the area of ​​the detection point based on a preset radius;

[0063] The evaluation module is also used to determine the average temperature of the detection point based on the temperature of each coordinate point within the area of ​​the detection point;

[0064] The evaluation module is further configured to obtain the average temperature between each detection point in the two-dimensional temperature distribution map, compare the average temperature between each detection point with the average temperature of each detection point, and determine whether the average temperature of each detection point is an abnormal temperature based on the comparison result, wherein:

[0065] When the average temperature of the detection point is consistent with the average temperature among all the detection points, the evaluation module determines that the average temperature of the detection point is not an abnormal temperature.

[0066] When the average temperature of the detection point is inconsistent with the average temperature among all the detection points, the evaluation module determines a preset temperature range based on the average temperature among all the detection points, and determines whether the average temperature of the detection point is an abnormal temperature based on the relationship between the average temperature of the detection point and the preset temperature range, wherein:

[0067] The evaluation module is also used to pre-determine a first preset temperature and a second preset temperature within the preset temperature range, wherein the first preset temperature is less than the second preset temperature;

[0068] When the average temperature of the detection point is between the first preset temperature and the second preset temperature, the evaluation module determines that the average temperature of the detection point is not an abnormal temperature.

[0069] When the average temperature of the detection point is higher than the second preset temperature, or when the average temperature of the detection point is lower than the first preset temperature, the evaluation module determines that the average temperature of the detection point is an abnormal temperature.

[0070] The evaluation module is also used to obtain the number of detection points with abnormal temperatures among the detection points, and to determine the correction coefficient when correcting the cooling score of the superconducting magnet based on the number of detection points with abnormal temperatures.

[0071] Furthermore, the evaluation module is also used to determine the correction coefficient when correcting the cooling score of the superconducting magnet based on the number of detection points with abnormal temperatures, including:

[0072] The evaluation module is also configured with a first preset quantity and a second preset quantity, wherein the first preset quantity is less than the second preset quantity;

[0073] The evaluation module is also used to determine a correction coefficient for correcting the cooling score of the superconducting magnet based on the relationship between the number of detection points with abnormal temperatures and each preset number, wherein:

[0074] When the number of detection points for abnormal temperature is less than or equal to the first preset number, the evaluation module determines the correction coefficient N3.

[0075] When the number of detection points for abnormal temperature is greater than the first preset number, and the number of detection points for abnormal temperature is less than or equal to the second preset number, the evaluation module determines the correction coefficient N2.

[0076] When the number of detection points with abnormal temperatures is greater than the second preset number, the evaluation module determines the correction coefficient N1.

[0077] Furthermore, N1 < N2 < N3 < 1.

[0078] It is understood that the thermal analysis method and system for conductive cooling high-temperature superconducting magnets in various embodiments of the present invention have the same beneficial effects, and will not be described in detail here. Attached Figure Description

[0079] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0080] Figure 1 A flowchart illustrating a thermal analysis method for a conductive-cooled high-temperature superconducting magnet, provided in an embodiment of the present invention.

[0081] Figure 2 This is a functional block diagram of a thermal analysis system for high-temperature superconducting magnets with conductive cooling, provided as an embodiment of the present invention. Detailed Implementation

[0082] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0083] Thermal analysis is a crucial step in the research and application of superconducting magnets, especially in high-temperature superconducting magnets, where thermal management is paramount due to their high operating temperatures. Conductive cooling of high-temperature superconducting magnets achieves cooling through solid-state heat conduction. Compared to traditional methods such as liquid nitrogen cooling, conductive cooling offers advantages such as simple structure and high reliability. However, to fully leverage its advantages, a thorough understanding and analysis of its thermal characteristics is necessary.

[0084] Currently, thermal analysis of superconducting magnets mainly focuses on liquid nitrogen or liquid hydrogen cooling methods, with relatively little research on conductive cooling methods. Thermal analysis of conductively cooled high-temperature superconducting magnets not only relates to the magnet's performance stability and lifespan but also directly affects its reliability in various application scenarios.

[0085] In view of this, the present invention proposes a thermal analysis method and system for conductive-cooled high-temperature superconducting magnets, aiming to provide a thermal analysis technology for conductive-cooled high-temperature superconducting magnets, and to fill the gap in the existing thermal analysis technology for conductive-cooled high-temperature superconducting magnets.

[0086] like Figure 1 As shown, in some embodiments of this application, this embodiment provides a thermal analysis method for conductive-cooled high-temperature superconducting magnets, including:

[0087] Step S100: Obtain thermal imaging information of the superconducting magnet to be analyzed.

[0088] Step S200: Determine the thermal conduction velocity of the superconducting magnet based on the thermal imaging information, and determine the cooling score of the superconducting magnet to be analyzed based on the thermal conduction velocity.

[0089] Specifically, based on thermal imaging information, the thermal conduction velocity of the superconducting magnet is determined, and a cooling score for the superconducting magnet to be analyzed is determined based on the thermal conduction velocity. This includes: acquiring thermal imaging image information of the superconducting magnet to be analyzed during a preset time period, and determining the geometric dimensions, thermal profile, and thermal conduction velocity of the superconducting magnet based on the image information; determining the cross-sectional area of ​​the superconducting magnet based on its geometric dimensions, thermal profile, and thermal conduction velocity using a formula; and determining the cooling score of the superconducting magnet based on the relationship between the thermal conduction score and a pre-set preset thermal conduction score.

[0090] Understandably, by acquiring thermal imaging images of a superconducting magnet over a predetermined time period, the temperature distribution of the magnet at different points in time can be captured in detail. These thermal images not only provide temperature data but also reflect the heat conduction at different locations within the magnet, providing crucial foundational data for subsequent analysis. Next, based on the acquired image information, the geometric dimensions, thermal profile, and heat conduction velocity of the superconducting magnet are determined. Geometric dimensions include physical parameters such as the length, width, and thickness of the magnet, which are essential for calculating its cross-sectional area. The thermal profile reflects the temperature changes at different locations, while the heat conduction velocity is a key indicator of the magnet's heat conduction efficiency. Secondly, after determining the magnet's geometric dimensions, its cross-sectional area can be calculated. Cross-sectional area is a critical parameter in heat conduction calculations because the heat conduction rate largely depends on the material's cross-sectional area. Accurate measurement of the magnet's geometric dimensions ensures the accuracy of the cross-sectional area calculation. Then, combining the magnet's geometric dimensions, thermal profile, and heat conduction velocity, a heat conduction score is calculated using a specific heat conduction formula. This rating system systematically reflects the thermal conductivity of superconducting magnets, providing an intuitive and quantitative evaluation standard by integrating different parameters into a single rating system. Finally, the cooling rating of the superconducting magnet is determined by comparing the calculated thermal conductivity score with a pre-defined thermal conductivity rating standard. This pre-defined rating standard, derived from extensive experimental data and theoretical analysis, serves as a reference benchmark for superconducting magnet performance. Through comparison, the actual cooling effect of the superconducting magnet can be effectively evaluated, thereby enabling a scientific quality classification.

[0091] Specifically, the thickness and width of the superconducting magnet are determined based on image information, and then based on the thickness and width, a formula is used... The cross-sectional area A of the superconducting magnet is calculated, where w is the thickness of the superconducting magnet and t is the width of the superconducting magnet. Subsequently, based on the image information, the heat transfer path length of the superconducting magnet, the temperature difference in the thermal curves of each image, the thermal power, and the cross-sectional area A of the superconducting magnet are obtained, and then based on the formula... The heat conduction velocity k is obtained, where q is the heat power. This is the length of the heat transfer path. The temperature difference in the thermal curves of each image is calculated according to the formula. The thermal conductivity score Z of the superconducting magnet is obtained, where v1, v2 and v3 are weighting coefficients, and the sum of v1, v2 and v3 is 1.

[0092] Specifically, when determining the cooling score of a superconducting magnet based on the relationship between the thermal conductivity score and pre-set preset thermal conductivity scores, the process includes: pre-setting a first preset thermal conductivity score and a second preset thermal conductivity score based on the geometric dimensions of the superconducting magnet, wherein the first preset thermal conductivity score is less than the second preset thermal conductivity score. The cooling score of the superconducting magnet is then determined based on the relationship between the thermal conductivity score and each of the pre-set preset thermal conductivity scores. When the thermal conductivity score is less than or equal to the first preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M1. When the thermal conductivity score is greater than the first preset thermal conductivity score and less than or equal to the second preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M2. When the thermal conductivity score is greater than the second preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M3. Furthermore, M1 < M2 < M3.

[0093] Understandably, based on the geometry of the superconducting magnet, two preset thermal conductivity scores (a first preset thermal conductivity score and a second preset thermal conductivity score) are set, where the first preset thermal conductivity score is lower than the second preset thermal conductivity score. These preset score thresholds are derived from extensive experimental data and theoretical analysis, aiming to provide a scientific benchmark for evaluating the cooling performance of the superconducting magnet. Secondly, by comparing the actually measured thermal conductivity scores with these two preset values, the cooling performance of the superconducting magnet can be effectively classified. When the thermal conductivity score is less than or equal to the first preset thermal conductivity score, it indicates good cooling performance, and the cooling score is M1; when the thermal conductivity score is greater than the first preset thermal conductivity score but less than or equal to the second preset thermal conductivity score, the cooling performance is moderate, and the cooling score is M2; and when the thermal conductivity score is greater than the second preset thermal conductivity score, the cooling performance is poor, and the cooling score is M3. This classification method provides a clear understanding of the cooling performance of the superconducting magnet, enabling quality control and optimization. Furthermore, the basis for setting these two preset thermal conductivity scores mainly comes from experimental data and practical application requirements. By testing a large number of superconducting magnet samples, thermal conductivity data was obtained, and appropriate scoring thresholds were determined based on theoretical analysis. This method not only considers the accuracy of experimental data but also incorporates the needs of practical applications, ensuring the scientific rigor and practicality of the scoring system. Finally, this scoring system provides a quantitative evaluation standard for the cooling performance of superconducting magnets. This standard can not only help engineers and researchers quickly assess the cooling performance of superconducting magnets but also provide important references in the production and quality control processes of superconducting magnets. For example, during production, by measuring the thermal conductivity score, it is possible to quickly determine whether the product meets the expected cooling performance standards, thereby improving production efficiency and product quality.

[0094] Step S300: Based on the thermal imaging information, determine the two-dimensional temperature distribution map of the superconducting magnet, and correct the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map.

[0095] Specifically, when determining the two-dimensional temperature distribution map of the superconducting magnet based on thermal imaging information, and correcting the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map, the process includes: selecting any coordinate point on the two-dimensional temperature distribution map, and determining the temperature detection point and its area based on a preset radius; determining the average temperature of the detection point based on the temperature of each coordinate point within the detection point area; acquiring the average temperature between each detection point on the two-dimensional temperature distribution map, comparing the average temperature between each detection point with the average temperature of each detection point, and determining whether the average temperature of each detection point is an abnormal temperature based on the comparison result; wherein: when the average temperature of the detection point is consistent with the average temperature between each detection point, the average temperature of the detection point is determined not to be an abnormal temperature; when the average temperature of the detection point is inconsistent with the average temperature between each detection point, a preset temperature range is determined based on the average temperature between each detection point, and the relationship between the average temperature of the detection point and the preset temperature range is used to determine whether the average temperature of the detection point is an abnormal temperature; wherein: a first preset temperature and a second preset temperature are predetermined within the preset temperature range, and the first preset temperature is less than the second preset temperature. When the average temperature of the detection point is between the first preset temperature and the second preset temperature, the average temperature of the detection point is determined not to be an abnormal temperature. When the average temperature of the detection point is higher than the second preset temperature, or lower than the first preset temperature, the average temperature of the detection point is determined to be an abnormal temperature. The number of detection points with abnormal temperatures is obtained, and the correction factor is determined based on the number of detection points with abnormal temperatures when correcting the cooling score of the superconducting magnet.

[0096] Understandably, a two-dimensional temperature distribution map is generated by acquiring thermal imaging information of the superconducting magnet. This map visually displays the temperature distribution on the surface and inside of the magnet, helping to identify potential temperature anomalies. To further analyze the map, any coordinate point is selected, and a temperature detection point and its area are determined based on a preset radius. Setting these detection points not only facilitates accurate local temperature measurement but also allows for better capture of subtle changes in temperature distribution. Next, the average temperature of each detection point is calculated based on its temperature data within the detection area. This average temperature provides the overall temperature level of the detection point and is a crucial basis for judging temperature anomalies. By acquiring the average temperature of each detection point in the two-dimensional temperature distribution map, a comprehensive understanding of the temperature distribution of the entire superconducting magnet can be obtained. Furthermore, to identify temperature anomalies, the average temperatures of each detection point need to be compared. When the average temperature of a detection point matches the average temperature of surrounding detection points, it indicates that the temperature at that point is normal; conversely, when the average temperature differs from the average temperature of surrounding detection points, a temperature anomaly may exist. To further confirm temperature anomalies, a preset temperature range was established, including a first preset temperature and a second preset temperature, where the first preset temperature is lower than the second preset temperature. When the average temperature of the detection points falls within the preset temperature range, it is considered a normal temperature; if it is higher than the second preset temperature or lower than the first preset temperature, it is marked as an abnormal temperature. This method can effectively identify temperature anomaly regions in superconducting magnets. Finally, the number of abnormal temperature detection points is counted, and a correction coefficient is determined based on this number. The correction coefficient is used to adjust the cooling score of the superconducting magnet, making the score more accurately reflect the actual cooling performance of the superconducting magnet. This cooling score correction method based on a two-dimensional temperature distribution map, combining detailed analysis of temperature detection points and scientific setting of the preset temperature range, ensures the accuracy of temperature anomaly identification and the scientific nature of the cooling score correction. By analyzing the temperature distribution of the superconducting magnet in detail, its cooling performance can be better evaluated, thus providing reliable data support for the design optimization and performance improvement of superconducting magnets.

[0097] Specifically, when determining the correction coefficient for correcting the cooling score of the superconducting magnet based on the number of abnormal temperature detection points, the following steps are taken: A first preset number and a second preset number are pre-set, with the first preset number being less than the second preset number. The correction coefficient for correcting the cooling score of the superconducting magnet is determined based on the relationship between the number of abnormal temperature detection points and each preset number, wherein: when the number of abnormal temperature detection points is less than or equal to the first preset number, the correction coefficient N3 is determined. When the number of abnormal temperature detection points is greater than the first preset number and less than or equal to the second preset number, the correction coefficient N2 is determined. When the number of abnormal temperature detection points is greater than the second preset number, the correction coefficient N1 is determined. Furthermore, N1 < N2 < N3 < 1.

[0098] Step S400: Determine the quality grade of the superconducting magnet based on the relationship between the cooling score of the superconducting magnet and the preset first and second preset cooling scores.

[0099] Specifically, when determining the quality grade of a superconducting magnet based on its cooling score and the relationship between a pre-set first and second preset cooling score, the following steps are taken: if the cooling score is lower than or equal to the first preset cooling score, the superconducting magnet is classified as Grade 1. If the cooling score is higher than the first preset cooling score and lower than or equal to the second preset cooling score, the superconducting magnet is classified as Grade 2. If the cooling score is higher than the second preset cooling score, the superconducting magnet is classified as Grade 3. Furthermore, Grade 1 < Grade 2 < Grade 3.

[0100] In the above embodiments, acquiring thermal imaging information of the superconducting magnet to be analyzed provides a reliable data foundation for subsequent thermal analysis. Thermal imaging technology can accurately capture the temperature distribution on the surface and inside of the superconducting magnet, thus providing detailed data support for subsequent calculation of heat conduction velocity and plotting of two-dimensional temperature distribution maps. Secondly, determining the heat conduction velocity by analyzing the thermal imaging information and calculating the cooling score based on the heat conduction velocity accurately reflects the thermal conduction performance of the superconducting magnet. Heat conduction velocity is one of the important indicators of the thermal performance of a superconducting magnet, and its accurate measurement helps us better understand the cooling efficiency and overall thermal management of the superconducting magnet. Furthermore, plotting a two-dimensional temperature distribution map of the superconducting magnet and correcting the cooling score based on this map further improves the accuracy of the cooling score. The two-dimensional temperature distribution map can visually display the temperature differences in various regions of the superconducting magnet; by analyzing these differences, the cooling score can be more accurately corrected to better reflect actual conditions. Finally, by comparing the cooling score with a preset cooling score standard, the quality grade of the superconducting magnet can be scientifically determined. This process not only considers the absolute value of the cooling score but also grades and evaluates superconducting magnets by setting different scoring thresholds. This allows for the grading of superconducting magnet quality based on actual conditions, providing a reliable basis for quality control and optimization.

[0101] In another preferred embodiment based on the above embodiments, such as Figure 2 As shown, this embodiment provides a thermal analysis system for conductive-cooled high-temperature superconducting magnets, including: a thermal imaging detection module, an evaluation module, and a rating module. The thermal imaging detection module acquires thermal imaging information of the superconducting magnet to be analyzed. The evaluation module is electrically connected to the thermal imaging detection module and determines the heat conduction velocity of the superconducting magnet based on the thermal imaging information, and determines a cooling score for the superconducting magnet to be analyzed based on the heat conduction velocity. The evaluation module also determines a two-dimensional temperature distribution map of the superconducting magnet based on the thermal imaging information, and corrects the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map. The rating module is electrically connected to the evaluation module and determines the quality grade of the superconducting magnet based on the relationship between the cooling score of the superconducting magnet and a pre-set first preset cooling score and a second preset cooling score.

[0102] Specifically, the rating module determines the quality level of the superconducting magnet based on the relationship between its cooling score and a pre-set first and second preset cooling score. Specifically: when the cooling score is lower than or equal to the first preset cooling score, the rating module determines the superconducting magnet to be of quality level one. When the cooling score is higher than the first preset cooling score but lower than or equal to the second preset cooling score, the rating module determines the superconducting magnet to be of quality level two. When the cooling score is higher than the second preset cooling score, the rating module determines the superconducting magnet to be of quality level three. Furthermore, level one < level two < level three.

[0103] In some embodiments of this application, when the evaluation module determines the thermal conduction velocity of a superconducting magnet based on thermal imaging information and determines a cooling score of the superconducting magnet to be analyzed based on the thermal conduction velocity, the evaluation module further includes: acquiring thermal imaging image information of the superconducting magnet to be analyzed within a preset time period, and determining the geometric dimensions, thermal profile, and thermal conduction velocity of the superconducting magnet based on the image information. The evaluation module is also used to determine the cross-sectional area of ​​the superconducting magnet based on its geometric dimensions. Furthermore, the evaluation module is used to determine a thermal conduction score of the superconducting magnet based on a formula using its geometric dimensions, thermal profile, and thermal conduction velocity, and to determine a cooling score of the superconducting magnet based on the relationship between the thermal conduction score and a preset thermal conduction score.

[0104] In some embodiments of this application, the evaluation module is further configured to determine the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and the preset thermal conductivity scores, including: the evaluation module is further configured to pre-configure a first preset thermal conductivity score and a second preset thermal conductivity score based on the geometric dimensions of the superconducting magnet, wherein the first preset thermal conductivity score is less than the second preset thermal conductivity score. The evaluation module is further configured to determine the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and each preset thermal conductivity score. When the thermal conductivity score is less than or equal to the first preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet as M1. When the thermal conductivity score is greater than the first preset thermal conductivity score and less than or equal to the second preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet as M2. When the thermal conductivity score is greater than the second preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet as M3. And, M1 < M2 < M3.

[0105] In some embodiments of this application, the evaluation module is further configured to determine a two-dimensional temperature distribution map of the superconducting magnet based on thermal imaging information, and to correct the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map. This includes: the evaluation module further selecting any coordinate point on the two-dimensional temperature distribution map and determining a temperature detection point and its area based on a preset radius. The evaluation module further determines the average temperature of the detection point based on the temperature of each coordinate point within the detection point area. The evaluation module further obtains the average temperature between each detection point on the two-dimensional temperature distribution map, compares the average temperature between each detection point with the average temperature of each detection point, and determines whether the average temperature of each detection point is an abnormal temperature based on the comparison result. Specifically, when the average temperature of a detection point is consistent with the average temperature between each detection point, the evaluation module determines that the average temperature of the detection point is not an abnormal temperature. When the average temperature at a detection point is inconsistent with the average temperature across all detection points, the evaluation module determines a preset temperature range based on the average temperature across all detection points. It then determines whether the average temperature at a detection point is an abnormal temperature based on the relationship between the average temperature at the detection point and the preset temperature range. Specifically, the evaluation module further determines a first preset temperature and a second preset temperature within the preset temperature range, with the first preset temperature being lower than the second preset temperature. When the average temperature at a detection point is between the first and second preset temperatures, the evaluation module determines that the average temperature at the detection point is not abnormal. When the average temperature at a detection point is higher than the second preset temperature or lower than the first preset temperature, the evaluation module determines that the average temperature at the detection point is abnormal. The evaluation module also obtains the number of detection points with abnormal temperatures and determines a correction factor for correcting the cooling score of the superconducting magnet based on the number of detection points with abnormal temperatures.

[0106] In some embodiments of this application, the evaluation module is further configured to determine the correction coefficient when correcting the cooling score of the superconducting magnet based on the number of abnormal temperature detection points. This includes: the evaluation module is further configured with a first preset number and a second preset number, wherein the first preset number is less than the second preset number. The evaluation module is further configured to determine the correction coefficient when correcting the cooling score of the superconducting magnet based on the relationship between the number of abnormal temperature detection points and each preset number, wherein: when the number of abnormal temperature detection points is less than or equal to the first preset number, the evaluation module determines the correction coefficient N3. When the number of abnormal temperature detection points is greater than the first preset number and less than or equal to the second preset number, the evaluation module determines the correction coefficient N2. When the number of abnormal temperature detection points is greater than the second preset number, the evaluation module determines the correction coefficient N1. And, N1 < N2 < N3 < 1.

[0107] It is understood that the thermal analysis method and system for conductive cooling high-temperature superconducting magnets in various embodiments of the present invention have the same beneficial effects, and will not be described in detail here.

[0108] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0110] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0111] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A thermal analysis method for conductive-cooled high-temperature superconducting magnets, characterized in that, include: Acquire thermal imaging information of the superconducting magnet to be analyzed; Based on the thermal imaging information, the thermal conduction velocity of the superconducting magnet is determined, and the cooling score of the superconducting magnet to be analyzed is determined based on the thermal conduction velocity. Based on the thermal imaging information, a two-dimensional temperature distribution map of the superconducting magnet is determined, and the cooling score of the superconducting magnet is corrected based on the two-dimensional temperature analysis map. Based on the relationship between the cooling score of the superconducting magnet and a pre-set first and second preset cooling score, the quality grade of the superconducting magnet is determined, wherein: When the cooling score is lower than or equal to the first preset cooling score, the quality grade of the superconducting magnet is determined to be Grade 1. When the cooling score is higher than the first preset cooling score and the cooling score is lower than or equal to the second preset cooling score, the quality grade of the superconducting magnet is determined to be level two. When the cooling score is higher than the second preset cooling score, the quality level of the superconducting magnet is determined to be level three. Furthermore, Level 1 < Level 2 < Level 3.

2. The thermal analysis method for conductive-cooled high-temperature superconducting magnets as described in claim 1, characterized in that, Based on the thermal imaging information, the thermal conduction velocity of the superconducting magnet is determined, and a cooling score of the superconducting magnet to be analyzed is determined based on the thermal conduction velocity, including: Acquire thermal imaging image information of the superconducting magnet to be analyzed during a preset time period, and determine the geometric dimensions, thermal curve, and thermal conduction velocity of the superconducting magnet based on the image information; The cross-sectional area of ​​the superconducting magnet is determined based on its geometric dimensions. Based on the geometry, thermal profile, and thermal conductivity of the superconducting magnet, a thermal conductivity score is determined using a formula. Then, based on the relationship between the thermal conductivity score and a pre-set thermal conductivity score, a cooling score is determined for the superconducting magnet.

3. The thermal analysis method for conductive-cooled high-temperature superconducting magnets as described in claim 2, characterized in that, When determining the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and a pre-set preset thermal conductivity score, the following steps are included: Based on the geometric dimensions of the superconducting magnet, a first preset thermal conductivity score and a second preset thermal conductivity score are preset, wherein the first preset thermal conductivity score is less than the second preset thermal conductivity score. The cooling score of the superconducting magnet is determined based on the relationship between the thermal conductivity score and each preset thermal conductivity score. When the thermal conductivity score is less than or equal to the first preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M1. When the thermal conductivity score is greater than the first preset thermal conductivity score and the thermal conductivity score is less than or equal to the second preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M2. When the thermal conductivity score is greater than the second preset thermal conductivity score, the cooling score of the superconducting magnet is determined to be M3; Furthermore, M1 < M2 < M3.

4. The thermal analysis method for conductive cooling high-temperature superconducting magnets as described in claim 3, characterized in that, When determining a two-dimensional temperature distribution map of the superconducting magnet based on the thermal imaging information, and correcting the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map, the process includes: Select any coordinate point on the two-dimensional temperature distribution map, and determine the temperature detection point and the area of ​​the detection point based on a preset radius; The average temperature of the detection point is determined based on the temperature of each coordinate point within the area of ​​the detection point. The average temperature between each detection point in the two-dimensional temperature distribution map is obtained. A comparison is made between the average temperature between each detection point and the average temperature of each detection point itself. Based on the comparison result, it is determined whether the average temperature of each detection point is an abnormal temperature. When the average temperature of the detection point is consistent with the average temperature among all the detection points, it is determined that the average temperature of the detection point is not an abnormal temperature. When the average temperature at the detection point is inconsistent with the average temperature among all the detection points, a preset temperature range is determined based on the average temperature among all the detection points. Furthermore, based on the relationship between the average temperature at the detection point and the preset temperature range, it is determined whether the average temperature at the detection point is an abnormal temperature. A first preset temperature and a second preset temperature are predetermined within the preset temperature range, wherein the first preset temperature is less than the second preset temperature; When the average temperature of the detection point is between the first preset temperature and the second preset temperature, it is determined that the average temperature of the detection point is not an abnormal temperature. When the average temperature of the detection point is higher than the second preset temperature, or when the average temperature of the detection point is lower than the first preset temperature, the average temperature of the detection point is determined to be an abnormal temperature. The number of detection points with abnormal temperatures is obtained, and the correction coefficient for correcting the cooling score of the superconducting magnet is determined based on the number of detection points with abnormal temperatures.

5. The thermal analysis method for conductive-cooled high-temperature superconducting magnets as described in claim 4, characterized in that, When determining the correction factor for correcting the cooling score of the superconducting magnet based on the number of detection points with abnormal temperatures, the following factors are included: A first preset quantity and a second preset quantity are preset, wherein the first preset quantity is less than the second preset quantity; Based on the relationship between the number of detection points for abnormal temperatures and each preset number, a correction coefficient is determined when correcting the cooling score of the superconducting magnet, where: When the number of detection points for abnormal temperatures is less than or equal to the first preset number, the correction coefficient N3 is determined. When the number of detection points for abnormal temperature is greater than the first preset number, and the number of detection points for abnormal temperature is less than or equal to the second preset number, then the correction coefficient N2 is determined. When the number of detection points with abnormal temperatures is greater than the second preset number, the correction coefficient N1 is determined. Furthermore, N1 < N2 < N3 < 1.

6. A thermal analysis system for high-temperature superconducting magnets with conductive cooling, applicable to the thermal analysis method for high-temperature superconducting magnets with conductive cooling as described in any one of claims 1-5, characterized in that, include: The thermal imaging detection module is used to acquire thermal imaging information of the superconducting magnet to be analyzed. An evaluation module, electrically connected to the thermal imaging detection module, is used to determine the heat conduction velocity of the superconducting magnet based on the thermal imaging information, and to determine the cooling score of the superconducting magnet to be analyzed based on the heat conduction velocity; the evaluation module is also used to determine a two-dimensional temperature distribution map of the superconducting magnet based on the thermal imaging information, and to correct the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map; A rating module, electrically connected to the evaluation module, determines the quality grade of the superconducting magnet based on the relationship between the cooling score of the superconducting magnet and a pre-set first and second preset cooling scores, wherein: When the cooling score is lower than or equal to the first preset cooling score, the rating module determines the quality level of the superconducting magnet to be Level 1. When the cooling score is higher than the first preset cooling score and the cooling score is lower than or equal to the second preset cooling score, the rating module determines that the quality level of the superconducting magnet is level two. When the cooling score is higher than the second preset cooling score, the rating module determines that the quality level of the superconducting magnet is level three; Furthermore, Level 1 < Level 2 < Level 3.

7. The thermal analysis system for high-temperature superconducting magnets with conductive cooling as described in claim 6, characterized in that, The evaluation module is used to determine the thermal conduction velocity of the superconducting magnet based on the thermal imaging information, and to determine the cooling score of the superconducting magnet to be analyzed based on the thermal conduction velocity, including: The evaluation module is also used to acquire thermal imaging image information of the superconducting magnet to be analyzed during a preset time period, and to determine the geometric dimensions, thermal curve, and thermal conduction velocity of the superconducting magnet based on the image information. The evaluation module is also used to determine the cross-sectional area of ​​the superconducting magnet based on its geometric dimensions. The evaluation module is also used to determine the thermal conductivity score of the superconducting magnet based on a formula according to the geometry, thermal curve and thermal conduction velocity of the superconducting magnet, and to determine the cooling score of the superconducting magnet according to the relationship between the thermal conductivity score and a preset thermal conductivity score.

8. The thermal analysis system for high-temperature superconducting magnets with conductive cooling as described in claim 7, characterized in that, The evaluation module is further configured to determine the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and a pre-set preset thermal conductivity score, including: The evaluation module is also used to pre-configure a first preset thermal conductivity score and a second preset thermal conductivity score based on the geometric dimensions of the superconducting magnet, wherein the first preset thermal conductivity score is less than the second preset thermal conductivity score. The evaluation module is also used to determine the cooling score of the superconducting magnet based on the relationship between the thermal conductivity score and each preset thermal conductivity score. When the thermal conductivity score is less than or equal to the first preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet to be M1; When the thermal conductivity score is greater than the first preset thermal conductivity score and the thermal conductivity score is less than or equal to the second preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet to be M2. When the thermal conductivity score is greater than the second preset thermal conductivity score, the evaluation module determines the cooling score of the superconducting magnet to be M3; Furthermore, M1 < M2 < M3.

9. The thermal analysis system for high-temperature superconducting magnets with conductive cooling as described in claim 8, characterized in that, The evaluation module is further configured to determine a two-dimensional temperature distribution map of the superconducting magnet based on the thermal imaging information, and to correct the cooling score of the superconducting magnet based on the two-dimensional temperature analysis map, including: The evaluation module is also used to select any coordinate point of the two-dimensional temperature distribution map, and determine the temperature detection point and the area of ​​the detection point based on a preset radius; The evaluation module is also used to determine the average temperature of the detection point based on the temperature of each coordinate point within the area of ​​the detection point; The evaluation module is further configured to obtain the average temperature between each detection point in the two-dimensional temperature distribution map, compare the average temperature between each detection point with the average temperature of each detection point, and determine whether the average temperature of each detection point is an abnormal temperature based on the comparison result, wherein: When the average temperature of the detection point is consistent with the average temperature among all the detection points, the evaluation module determines that the average temperature of the detection point is not an abnormal temperature. When the average temperature of the detection point is inconsistent with the average temperature among all the detection points, the evaluation module determines a preset temperature range based on the average temperature among all the detection points, and determines whether the average temperature of the detection point is an abnormal temperature based on the relationship between the average temperature of the detection point and the preset temperature range, wherein: The evaluation module is also used to pre-determine a first preset temperature and a second preset temperature within the preset temperature range, wherein the first preset temperature is less than the second preset temperature; When the average temperature of the detection point is between the first preset temperature and the second preset temperature, the evaluation module determines that the average temperature of the detection point is not an abnormal temperature. When the average temperature of the detection point is higher than the second preset temperature, or when the average temperature of the detection point is lower than the first preset temperature, the evaluation module determines that the average temperature of the detection point is an abnormal temperature. The evaluation module is also used to obtain the number of detection points with abnormal temperatures among the detection points, and to determine the correction coefficient when correcting the cooling score of the superconducting magnet based on the number of detection points with abnormal temperatures.

10. The thermal analysis method for conductive-cooled high-temperature superconducting magnets as described in claim 9, characterized in that, The evaluation module is also used to determine the correction coefficient when correcting the cooling score of the superconducting magnet based on the number of detection points with abnormal temperatures, including: The evaluation module is also configured with a first preset quantity and a second preset quantity, wherein the first preset quantity is less than the second preset quantity; The evaluation module is also used to determine a correction coefficient for correcting the cooling score of the superconducting magnet based on the relationship between the number of detection points with abnormal temperatures and each preset number, wherein: When the number of detection points for abnormal temperature is less than or equal to the first preset number, the evaluation module determines the correction coefficient N3. When the number of detection points for abnormal temperature is greater than the first preset number, and the number of detection points for abnormal temperature is less than or equal to the second preset number, the evaluation module determines the correction coefficient N2. When the number of detection points with abnormal temperatures is greater than the second preset number, the evaluation module determines the correction coefficient N1. Furthermore, N1 < N2 < N3 < 1.

Images