High-temperature superconducting cable cooling pipe aging prediction method based on multi-factor coupling

Abstract

The invention relates to the field of cable cooling pipe aging prediction, in particular to a high-temperature superconducting cable cooling pipe aging prediction method based on multi-factor coupling. The method comprises the following steps: firstly, acquiring current data and temperature data of different moments in the high-temperature superconducting cable every day, segmenting the current data every day to obtain a current stable time period and a current transition time period every day, and calculating the current transition time period according to the overall level and fluctuation of the current data of each current stable time period; obtaining the loss degree of each current stabilization time period, analyzing the change of the current data of the current stabilization time periods on the two adjacent sides of the current transition time period, obtaining the influence degree of each current transition time period, and obtaining the loss degree of each current transition time period according to the change and influence degree of the temperature data of each current transition time period every day. And obtaining an influence gain coefficient of the high-temperature superconducting cable cooling pipe, and performing aging prediction on the cooling pipe based on the influence gain coefficient. According to the invention, the accuracy of aging prediction of the cooling pipe of the high-temperature superconducting cable can be improved.

Description

Technical Field

[0001] This invention relates to the field of aging prediction for cable cooling pipes, and specifically to a method for predicting the aging of high-temperature superconducting cable cooling pipes based on multi-factor coupling. Background Technology

[0002] High-temperature superconducting cables are a core technology for next-generation power transmission. They utilize liquid nitrogen (at 77K) to cool superconducting materials, achieving zero-resistance power transmission with an efficiency 5-10 times higher than traditional cables. The cooling tube, acting as a vacuum-insulated conduit encasing the superconducting material, maintains the cable's temperature below the critical temperature of the superconducting material through circulating coolant (liquid nitrogen), ensuring the superconducting cable maintains its zero-resistance characteristics and enables efficient power transmission. During operation, the cooling tube experiences continuous fluctuations in coolant temperature, especially under significant load changes. The liquid temperature inside the cooling tube undergoes drastic changes, causing thermal expansion and contraction of the tube wall, resulting in thermal stress and fatigue aging. Failure of the cooling tube can lead to insulation failure, liquid nitrogen leakage, and superconducting instability in the high-temperature superconducting cable, ultimately causing system failure.

[0003] In related technologies, the stress inside the cooling tube is usually estimated under a fixed scenario and combined with environmental parameters and the physical properties of the cooling tube (such as size) to predict the aging condition of the cooling tube. However, in actual use scenarios, the stability of high-temperature superconducting cables is very sensitive to changes in current. Fluctuations in current may also cause significant changes in the environment inside the cable, causing the cable and cooling tube to be impacted, thus accelerating aging. Therefore, existing methods reduce the accuracy of predicting the aging of cooling tubes of high-temperature superconducting cables without considering the fluctuations in the current inside the cable. Summary of the Invention

[0004] To address the technical problem that existing methods reduce the accuracy of aging prediction for cooling tubes in high-temperature superconducting cables when they do not consider fluctuations in the internal current of the cable, the present invention aims to provide a method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling. The specific technical solution adopted is as follows: This invention proposes a method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling. The method includes: Acquire current and temperature data inside a high-temperature superconducting cable at different times of the day within a preset time period; Based on the distribution of daily current data, the daily current data is segmented to obtain daily current stable periods and current transition periods. Based on the overall level and fluctuation of current data in each current stable period, the degree of loss in each current stable period is obtained. The two current stable periods adjacent to each current transition period are used as reference current stable periods for each current transition period. Based on the difference in current data between reference current stable periods, the degree of loss in the reference current stable periods, and the length of each current transition period and the reference current stable period, the degree of influence of each current transition period is obtained. Based on the temperature data changes and the degree of influence during each current transition period of the day, the influence gain coefficient of the high-temperature superconducting cable cooling tube is obtained. Based on the influence gain coefficient of the high-temperature superconducting cable cooling tube, aging prediction of the cooling tube is performed.

[0005] Furthermore, obtaining the daily current stabilization period and current transition period includes: Take any day as the target day, and based on the difference in current data between different times on the target day, cluster all times on the target day to obtain multiple clusters. The time period consisting of consecutive times in the same cluster is taken as the approximate current time period of the target day. Take any approximate current period of the target day as the approximate current period. Based on the distribution of current data at each moment of the approximate current period, divide the approximate current period into a current stability period and a current transition period.

[0006] Furthermore, the division of the approximate target current time period into a current stabilization period and a current transition period includes: The maximum and minimum values ​​are extracted from the current data at all times during the approximate period of the target current. The average of all the maximum values ​​during the approximate period of the target current is taken as the upper limit of the normal current during the approximate period of the target current. The average of all the minimum values ​​during the approximate period of the target current is taken as the lower limit of the normal current during the approximate period of the target current. The lower limit of the normal current and the upper limit of the normal current are used to form the normal current fluctuation range during the approximate period of the target current. Within the target current approximation period, the time period consisting of consecutive moments when the current data does not fall within the normal current fluctuation range is designated as the current transition period of the target current approximation period, and all other time periods excluding the current transition period are designated as the current stabilization period of the target current approximation period.

[0007] Furthermore, obtaining the degree of loss for each current stabilization period includes: The average value of the current data at all times during each current stabilization period is taken as the overall current level value for each current stabilization period. Extreme values ​​are extracted from the current data at all times during each current stabilization period. Based on the differences in current data between adjacent times during each current stabilization period and the number of extreme values ​​during each current stabilization period, the degree of current fluctuation during each current stabilization period is obtained. The overall current level and the degree of current fluctuation for each current stable period are combined and normalized to obtain the loss level for each current stable period.

[0008] Furthermore, obtaining the degree of current fluctuation for each current stabilization period includes: In each current stabilization period, the difference between the current data at each time point and the next adjacent time point is taken as the current change at each time point, and the average of the absolute values ​​of the differences between the current changes at all two adjacent time points is taken as the fluctuation coefficient for each current stabilization period. The degree of current fluctuation in each stable current period is obtained by combining the fluctuation coefficient of each stable current period and the number of extreme values ​​in each stable current period.

[0009] Furthermore, the degree of influence of obtaining each current transition period includes: The average of the loss levels of the two reference current stabilization periods for each current transition period is taken as the overall loss level of the reference current stabilization period for each current transition period. The current stabilization period located to the right of each current transition period is designated as the right current stabilization period of each current transition period, and the current stabilization period located to the left of each current transition period is designated as the left current stabilization period of each current transition period. The numerator is the difference between the overall current level value of the right current stabilization period and the overall current level value of the left current stabilization period in each current transition period, and the denominator is the average length of the two reference current stabilization periods in each current transition period. The ratio is used as the current upward trend value of the reference current stabilization period in each current transition period. After combining the overall loss level and the current rise trend value and normalizing them, the impact level of the reference current stable period during each current transition period is obtained. The impact of each current transition period is determined by the difference in the overall current level between the two reference current stable periods for each current transition period, the length of each current transition period, and the degree of impact of the change.

[0010] Furthermore, obtaining the degree of influence of each current transition period based on the difference in the overall current level between the two reference current stabilization periods of each current transition period, the length of each current transition period, and the degree of change impact includes: The absolute value of the difference between the overall current level values ​​between the two reference current stable periods for each current transition period is used as the numerator, the length of each current transition period is used as the denominator, and the ratio is used as the rate of change assessment value for each current transition period. The impact degree of each current transition period is obtained by combining the rate of change assessment value of each current transition period and the impact degree of the change in the reference current stable period of each current transition period and then normalizing them.

[0011] Furthermore, the gain coefficient of the obtained high-temperature superconducting cable cooling tube includes: The difference between the maximum value of the temperature data at all times in the current steady period adjacent to the right of each current transition period and the temperature data at the first time of each current transition period is taken as the temperature rise of each current transition period. The two-dimensional data points, consisting of the temperature rise and the degree of influence during each current transition period of each day, are mapped onto a coordinate system. A straight line is fitted to all the two-dimensional data points for each day, and the slope of the fitted straight line is used as the correlation trend value for each day. The horizontal axis of the coordinate system represents the temperature rise, and the vertical axis represents the degree of influence. The ReLU function is used to map the difference between the correlation trend value of each day within a preset time period and the correlation trend value of the previous day to obtain the degree of correlation increase each day. The cumulative value of the impact of all current transition periods each day is taken as the cumulative impact of current each day. The product of the daily increase in correlation and the cumulative effect of current is taken as the daily change in current effect, and the sum of the daily cumulative effect of current and the change in current effect is taken as the daily degradation coefficient. The influence gain coefficient of the high-temperature superconducting cable cooling pipe is obtained based on the difference in the degradation coefficient between adjacent days within a preset time period.

[0012] Furthermore, obtaining the influence gain coefficient of the high-temperature superconducting cable cooling pipe based on the difference in the degradation coefficient between adjacent days within a preset time period includes: The difference between the degradation coefficient of each day within the preset time period and the degradation coefficient of the previous day is taken as the daily degradation coefficient change. The average value of the degradation coefficient change over all days within a preset time period is normalized to obtain the influence gain coefficient of the high-temperature superconducting cable cooling pipe.

[0013] Furthermore, the aging prediction of the cooling pipe includes: If the gain coefficient is greater than the preset threshold, it indicates that the cooling tube of the high-temperature superconducting cable is aging.

[0014] The present invention has the following beneficial effects: This invention addresses the issue that neglecting current fluctuations would reduce the accuracy of predicting the aging of cooling tubes in high-temperature superconducting cables. Therefore, it first acquires current and temperature data from the inside of the cable at different times each day. The daily current data is then segmented to identify relatively stable current periods and fluctuating current transition periods. Since losses also occur in the cooling tubes during relatively stable current periods, and the higher the current level and the more pronounced the fluctuations, the greater the impact of the current conditions during stable current periods on cooling tube losses. Therefore, the acquired loss level can reflect the extent of current damage to the cooling tubes during stable current periods. Considering that the current transition period is the time between two stable current periods, and the current... The current changes drastically during the transition period, causing corresponding changes in the cooling demand of the cooling tube. Different current states also have different requirements for the temperature and flow rate of the coolant inside the cooling tube. Therefore, the greater the difference in current conditions between the current stable periods on both sides of the current transition period, the greater the impact on the stability of the cooling tube. Thus, the degree of impact can be obtained to reflect the extent to which the current changes on both sides of the current transition period affect the cooling tube of the high-temperature superconducting cable. Considering that the change in current can cause changes in the internal temperature of the cable, the gain coefficient of the impact can be obtained to reflect the growth of the impact of the internal current on cable aging. Based on the gain coefficient of the impact of the high-temperature superconducting cable cooling tube, the aging of the cooling tube can be predicted, thereby improving the accuracy of the aging prediction of the high-temperature superconducting cable cooling tube. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 The flowchart illustrates a method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling, as provided in one embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a high-temperature superconducting cable cooling tube aging prediction method based on multi-factor coupling proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the high-temperature superconducting cable cooling tube aging prediction method provided by the present invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of an aging prediction method for high-temperature superconducting cable cooling tubes based on multi-factor coupling, according to an embodiment of the present invention. The method includes: Step S1: Obtain the current and temperature data inside the high-temperature superconducting cable at different times of the day within a preset time period.

[0021] The purpose of this invention is to analyze the aging of the cable cooling pipe by combining the changes in the working state of the high-temperature superconducting cable. Therefore, firstly, a current sensor is used to collect the current data inside the high-temperature superconducting cable at different times of the day within a preset time period, and a temperature sensor is used to collect the temperature data inside the high-temperature superconducting cable at different times of the day within the preset time period. The preset time period is usually in the range of 30 to 60 days. In one embodiment of this invention, the preset time period is set to 30 days, and the data collection frequency of the current data and temperature data is the same, which is set to collect data once every 10 milliseconds. The specific value of the preset time period and the data collection frequency can also be set by the implementer according to the specific implementation scenario, and are not limited here.

[0022] It should be noted that different types of data have different dimensions. Therefore, the embodiments of the present invention also need to standardize the collected different types of data to eliminate the influence of dimensions. Data standardization is a technical means well known to those skilled in the art and will not be elaborated here.

[0023] Step S2: Based on the distribution of daily current data, segment the daily current data to obtain daily current stable periods and current transition periods; based on the overall level and fluctuation of current data in each current stable period, obtain the degree of loss in each current stable period; take the two current stable periods adjacent to each current transition period as reference current stable periods for each current transition period, and based on the difference in current data between reference current stable periods, the degree of loss in the reference current stable periods, and the length of each current transition period and the reference current stable periods, obtain the degree of influence of each current transition period.

[0024] When the operating current inside a cable changes, it causes changes in the magnetic field, temperature, and other states within the cable, which in turn impacts the cable conduit. The current inside a high-temperature superconducting cable varies at different times of the day. There are periods of relatively stable current change and periods of large fluctuations in the current. Therefore, this embodiment of the invention first segments the daily current data based on its distribution to obtain the relatively stable current periods and the fluctuating current transition periods. Subsequently, the stable current periods and the current transition periods can be analyzed separately to accurately determine the impact of the current on the aging of the cooling tube of the high-temperature superconducting cable.

[0025] Preferably, in one embodiment of the present invention, the method for obtaining the daily current stabilization period and current transition period specifically includes: First, any day is taken as the target day. Based on the difference in current data between different times on the target day, all times on the target day are clustered to obtain multiple clusters. The time period consisting of consecutive times in the same cluster is taken as the approximate current time period of the target day. Among them, the current data of each time in the same approximate current time period are relatively similar. In one embodiment of the present invention, the existing AP clustering algorithm can be used to implement the clustering operation, which is not limited or described in detail here.

[0026] Within each approximate current period, there are periods with relatively large current fluctuations and periods with relatively stable current. Therefore, any approximate current period of the target day can be taken as the target current approximate period. Based on the distribution of current data at each moment of the target current approximate period, the target current approximate period can be divided into a current stable period and a current transition period.

[0027] Preferably, in one embodiment of the present invention, the method for obtaining the daily current stabilization period and current transition period further includes: The maximum and minimum values ​​are extracted from the current data at all times during the approximate period of the target current. The extraction method for the maximum and minimum values ​​can be the existing Newton's method, which will not be limited or elaborated here. The average value of all the maximum values ​​during the approximate period of the target current is taken as the upper limit of the normal current during the approximate period of the target current, and the average value of all the minimum values ​​during the approximate period of the target current is taken as the lower limit of the normal current during the approximate period of the target current. The lower limit and upper limit of the normal current are used to construct the normal current fluctuation range during the approximate period of the target current.

[0028] If the current data at a certain moment in the approximate target current period is outside the normal current fluctuation range, it indicates that the current data fluctuation at that moment is relatively obvious. Conversely, it indicates that the current data at that moment is relatively stable. Therefore, in the approximate target current period, the time period consisting of consecutive moments when the current data is outside the normal current fluctuation range is taken as the current transition period of the approximate target current period, and all other time periods except the current transition period are taken as the current stabilization period of the approximate target current period. In other words, the time period consisting of consecutive moments when the current data is within the normal current fluctuation range is taken as the current stabilization period of the approximate target current period.

[0029] Using the same method described above, the approximate current period of each target day can be divided, thus obtaining multiple current stable periods and current transition periods for the target day. Similarly, each day can be divided using the same method to obtain multiple current stable periods and current transition periods for each day. It should be noted that for the same day, there may be two temporally adjacent current stable periods or current transition periods. In such cases, the two temporally adjacent current stable periods can be combined into a longer current stable period, or the two temporally adjacent current transition periods can be combined into a longer current transition period.

[0030] Although the resistance loss in high-temperature superconducting cables is extremely small, it is not completely zero. When the current is large, the resistance loss will also cause heat to be generated inside the cable, which will require the system to handle more heat and increase the cooling burden on the cooling tube. Therefore, the high current state itself will cause a large loss to the cooling system, and the loss to the cooling system will be even greater when there are large fluctuations in the current load. At the same time, the cooling tube will also be damaged during the relatively stable current period. Therefore, the embodiments of the present invention first analyze the overall level and fluctuation of the current data for each stable current period of the day, and the degree of loss obtained reflects the degree of damage to the cooling tube caused by the current state during the stable current period.

[0031] Preferably, in one embodiment of the present invention, the method for obtaining the degree of loss during each current stabilization period specifically includes: The average value of the current data at all times during each current stabilization period is taken as the overall current level value for each current stabilization period. The larger the overall current level value, the higher the current level during the current stabilization period.

[0032] Extreme values ​​are extracted from the current data at all times during each current stabilization period. These extreme values ​​include maximum and minimum values. Based on the differences in current data between adjacent times during each current stabilization period and the number of extreme values ​​in each current stabilization period, the degree of current fluctuation in each current stabilization period is obtained. The greater the degree of current fluctuation, the more obvious the current fluctuation within the current stabilization period.

[0033] Preferably, in one embodiment of the present invention, the method for obtaining the degree of current fluctuation in each current stabilization period specifically includes: In each current stabilization period, the difference between the current data at each moment and the next adjacent moment is taken as the current change at each moment, and the average of the absolute values ​​of the differences between the current changes at all two adjacent moments is taken as the fluctuation coefficient for each current stabilization period. The larger the fluctuation coefficient, the stronger the current fluctuation during the current stabilization period.

[0034] It should be noted that there is no adjacent next moment in the last moment of each current stabilization period. For the convenience of subsequent calculations, the average of the current changes at all moments before the last moment of each current stabilization period can be used as the current change at the last moment.

[0035] Meanwhile, the more extreme values ​​there are in a stable current period, the more frequent the current fluctuations are in that period. Therefore, the fluctuation coefficient and the number of extreme values ​​in each stable current period can be combined to obtain the degree of current fluctuation in each stable current period.

[0036] In embodiments of the present invention, the sum or product of the fluctuation coefficient of each current stable period and the number of extreme values ​​in each current stable period can be used as the degree of current fluctuation in each current stable period, thereby achieving a comprehensive analysis of the two. This is not limited here, and the same method can also be used to achieve the comprehensive processing of two or more data in subsequent steps.

[0037] As an example, in one embodiment of the present invention, the expression for the degree of current fluctuation during each current stabilization period can be specifically as follows:

[0038] in, Indicates the first of each day The degree of current fluctuation during a period of stable current; Indicates the first The number of extreme values ​​in a current steady-state period; Indicates the first The first current stabilization period The change in current at each moment; Indicates the first The first current stabilization period The change in current at time n, where the nth time n is the change in current at ... The moment and the These two moments are two consecutive moments. Indicates the first The number of all moments contained in a current steady-state period, then Indicates the first The number of two adjacent moments in a current-stable period; Indicates the first The fluctuation coefficient during a period of stable current.

[0039] Then, the overall current level and current fluctuation degree during each current stabilization period are combined and normalized to limit the calculation results to within a certain range. Within a certain range, the degree of loss during each stable current period can be obtained.

[0040] In one embodiment of the present invention, the normalization process can be specifically, for example, maximum and minimum value normalization. Furthermore, the normalization in subsequent steps can all adopt maximum and minimum value normalization. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of values, or activation functions and hyperbolic tangent functions can be used to implement the normalization process. These will not be elaborated or limited further.

[0041] As an example, in one embodiment of the present invention, the expression for the degree of loss during each current stabilization period can be specifically as follows:

[0042] in, Indicates the first of each day The degree of loss during each period of stable current; Indicates the first The average value of the current data at all times during the current steady-state period, i.e., the... The overall current level during a period of stable current; Indicates the first The degree of current fluctuation during a period of stable current; This represents the normalization function, used for normalization processing.

[0043] Since the current transition period is the time between two current stable periods, and the current changes on both sides of the current transition period are relatively drastic, the cooling demand of the cooling tube will change accordingly. This leads to different requirements for the temperature and flow rate of the coolant in the cooling tube under different current conditions. The greater the current difference between the current stable periods on both sides of the current transition period, and the more rapid the current change, the more serious the impact on the stability of the cooling tube will be. Therefore, in this embodiment of the invention, the two current stable periods adjacent to each current transition period are first used as reference current stable periods for each current transition period. Based on the difference in current data between the reference current stable periods, the degree of loss in the reference current stable periods, and the length of each current transition period and the reference current stable period, the degree of influence of each current transition period is obtained. The degree of influence reflects the extent to which the current changes on both sides of the current transition period affect the cooling tube of the high-temperature superconducting cable.

[0044] Preferably, in one embodiment of the present invention, the method for obtaining the degree of influence of each current transition period specifically includes: The average of the loss levels of the two reference current stable periods during each current transition period is taken as the overall loss level of the reference current stable period during each current transition period. The greater the overall loss level, the greater the degree of loss caused to the cooling pipe by the current state during the reference current stable periods on both sides of the current transition period, and the greater the influence of the current state on the cooling pipe.

[0045] The current stabilization period to the right of each current transition period is taken as the right current stabilization period of each current transition period, and the current stabilization period to the left of each current transition period is taken as the left current stabilization period of each current transition period. The difference between the overall current level value of the right current stabilization period and the overall current level value of the left current stabilization period of each current transition period is used as the numerator, and the average length of the two reference current stabilization periods of each current transition period is used as the denominator. The ratio is used as the current upward trend value of the reference current stabilization period of each current transition period. When the current upward trend value is positive and larger, it indicates that the current data from the left current stabilization period to the right current stabilization period is on an upward trend in time sequence, and the current change on both sides of the current transition section has a greater impact on the cooling pipe.

[0046] Then, the overall loss level and current upward trend values ​​are combined and normalized to limit the calculation results to a range of values. Within the range, the impact degree of the reference current stability period during each current transition period is obtained. The greater the impact degree, the stronger the impact of the current change on the stability of the cooling pipe system.

[0047] As an example, in one embodiment of the present invention, the expression for the impact degree of the reference current stabilization period change during each current transition period can be specifically as follows:

[0048] in, Indicates the first of each day The impact of changes in the reference current during the current transition period and the steady period of the current; Indicates the first The overall loss level of the reference current during the current transition period; Indicates the first The overall current level during the right current stabilization period of each current transition period; Indicates the first The overall current level during the left current stabilization period of each current transition period; Indicates the first The average length of the two reference current steady-state periods for each current transition period, wherein the length of the reference current steady-state period can be expressed by the number of moments it contains; Indicates the first The current rising trend value during the reference current stable period of each current transition period; This represents the normalization function, used for normalization processing.

[0049] Meanwhile, the greater the difference in current level between the two reference current stable periods in the current transition section and the shorter the length of the current transition period, the more rapid the change in current in the current transition section and on both sides, and the stronger the impact on the stability of the cooling pipe system. Therefore, the degree of influence of each current transition period can be obtained based on the difference in the overall current level between the two reference current stable periods in each current transition period, the length of each current transition period, and the degree of change impact.

[0050] Preferably, in one embodiment of the present invention, the method for obtaining the degree of influence of each current transition period further includes: The absolute value of the difference between the overall current level between the two reference current stable periods in each current transition period is used as the numerator, and the length of each current transition period is used as the denominator. The ratio is used as the rate of change assessment value for each current transition period. The larger the rate of change assessment value, the more rapidly the current changes when transitioning from the current stable period on the left to the current stable period on the right, and the greater the impact on the stability of the cooling pipe system.

[0051] Therefore, the rate of change assessment for each current transition period and the impact of the reference current steady-state period for each current transition period can be combined and normalized to limit the calculation results to within a certain range. Within the range, the degree of influence of each current transition period can be obtained.

[0052] As an example, in one embodiment of the present invention, the expression for the degree of influence of each current transition period can be specifically as follows:

[0053] in, Indicates the first of each day The degree of influence of each current transition period; Indicates the first The overall current level during the right current stabilization period of each current transition period; Indicates the first The overall current level during the left current stabilization period of each current transition period; Indicates the first The length of a current transition period can be represented by the number of moments contained within the current transition period; Indicates the first The impact of changes in the reference current during the current transition period and the steady period of the current; This represents the normalization function, used for normalization processing.

[0054] Step S3: Based on the changes and impact of temperature data during each current transition period each day, obtain the influence gain coefficient of the high-temperature superconducting cable cooling pipe.

[0055] When the current inside the cable changes, it often causes changes in the internal temperature, which in turn causes changes in the cooling demand of the cooling system, resulting in changes in the working state of the cooling pipe. Frequent current changes will exacerbate the wear and tear on the cooling pipe. As the cooling system is subjected to multiple temperature change shocks, the aging wear and tear on the cooling system will continue to accumulate, and the cooling system's ability to withstand shocks will also change. This step evaluates the cable's temperature resistance after being subjected to multiple current change shocks by analyzing the correlation between the degree of impact and temperature. The worse the temperature resistance, the higher the cooling demand on the cooling pipe, and the greater the wear and tear. Therefore, this embodiment of the invention uses the influence gain coefficient to reflect the growth of the continuous impact of the internal current on cable aging by analyzing the temperature changes and the degree of impact during each current transition period of the day. The larger the influence gain coefficient, the greater the aging degree of the high-temperature superconducting cable cooling pipe. Subsequently, the aging condition of the high-temperature superconducting cable cooling pipe can be accurately predicted by combining the influence gain coefficient.

[0056] Preferably, in one embodiment of the present invention, the method for obtaining the gain coefficient of the high-temperature superconducting cable cooling tube specifically includes: The difference between the maximum temperature data at all times in the adjacent current stabilization period to the right of each current transition period and the temperature data at the first time of each current transition period is taken as the temperature rise for each current transition period.

[0057] The two-dimensional data points, consisting of the temperature rise and the degree of influence during each current transition period of each day, are mapped onto a coordinate system. A straight line is fitted to all the two-dimensional data points for each day, and the slope of the fitted straight line is taken as the correlation trend value for each day. The horizontal axis of the coordinate system is the temperature rise, and the vertical axis is the degree of influence. In one embodiment of the present invention, the existing least squares method can be used to achieve the straight line fitting, which is not limited or described in detail here.

[0058] If the correlation trend values ​​of adjacent days are different, it indicates that the correlation between the temperature rise and the degree of impact has changed. Therefore, the ReLU function is used to map the difference between the correlation trend value of each day and the correlation trend value of the previous day within the preset time period to obtain the degree of correlation increase each day. It should be noted that there is no adjacent previous day for the first day of the preset time period. Therefore, for the convenience of subsequent calculations, the degree of correlation increase on the first day is set to a value of 0.

[0059] The cumulative value of the impact of all current transition periods each day is taken as the cumulative impact of the current each day.

[0060] The product of the daily increase in correlation and the cumulative effect of current is used as the daily change in current effect. The sum of the daily cumulative effect of current and the change in current effect is used as the daily degradation coefficient. The degradation coefficient reflects the degree of deterioration in the cable cooling pipe's ability to withstand current changes each day, that is, it reflects the degree of wear and tear exhibited by the cooling pipe system each day.

[0061] As an example, in one embodiment of the present invention, the expression for the daily degradation coefficient can be specifically as follows:

[0062] in, Indicates the number of times within the preset time period The degradation coefficient of the day; Indicates the first The current of the day affects the degree of accumulation; Indicates the first The correlation trend value of the day; Indicates the first The correlation trend value of the previous day; Represents the ReLU function, whose function expression is: That is, output the maximum value between the input value and the value 0; Indicates the first The degree of increase in the correlation between the day and the day; Indicates the first The change in the current over time affects the amount of change.

[0063] Then, based on the difference in degradation coefficient between adjacent days within a preset time period, the influence gain coefficient of the high-temperature superconducting cable cooling pipe is obtained.

[0064] Preferably, in one embodiment of the present invention, the method for obtaining the gain coefficient of the high-temperature superconducting cable cooling tube further includes: The difference between the daily degradation coefficient and the previous day's degradation coefficient within a preset time period is taken as the daily degradation coefficient variation. A positive and larger degradation coefficient variation indicates that the aging of the high-temperature superconducting cable cooling pipe is increasing, thus indicating a greater degree of aging. Therefore, the average degradation coefficient variation for all days within the preset time period is normalized, limiting the calculation results to... Within the range, the influence gain coefficient of the high-temperature superconducting cable cooling pipe is obtained.

[0065] It should also be noted that there is no adjacent day before the first day of the preset time period. Therefore, for the convenience of subsequent calculations, the change in the degradation coefficient on the first day is set to a value of 0.

[0066] As an example, in one embodiment of the present invention, the expression for the gain coefficient of the high-temperature superconducting cable cooling tube can be specifically as follows:

[0067] in, This indicates the gain coefficient representing the effect of the cooling pipe on the high-temperature superconducting cable. Within the preset time period The change in the degradation coefficient over the day; Indicates the number of days within a preset time period; This represents the hyperbolic tangent function, used for normalization.

[0068] Step S4: Based on the influence gain coefficient of the cooling tube of the high-temperature superconducting cable, predict the aging of the cooling tube.

[0069] The above steps analyze the daily current and temperature data of the high-temperature superconducting cable to obtain the influence gain coefficient of the cooling tube. The larger the influence gain coefficient, the greater the degree of aging of the cooling tube caused by the change in the internal current state of the cable. Therefore, the aging of the cooling tube can be predicted based on the influence gain coefficient of the high-temperature superconducting cable cooling tube, thereby improving the accuracy of the aging prediction of the high-temperature superconducting cable.

[0070] Preferably, in one embodiment of the present invention, if the gain coefficient is greater than a preset threshold, the high-temperature superconducting cable cooling tube is considered to have aging. The preset threshold value ranges from [value missing]. In one embodiment of the present invention, the preset threshold is set to 0.6. The specific value of the preset threshold can also be set by the implementer according to the specific implementation scenario, and is not limited here.

[0071] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling, characterized in that, The method includes: acquiring current and temperature data of the high-temperature superconducting cable at different times of the day within a preset time period; segmenting the daily current data according to the distribution of the daily current data to obtain daily current stable periods and current transition periods; obtaining the loss degree of each current stable period based on the overall level and fluctuation of the current data in each current stable period; using two current stable periods adjacent to each current transition period as reference current stable periods for each current transition period; obtaining the influence degree of each current transition period based on the difference in current data between the reference current stable periods, the loss degree of the reference current stable periods, and the length of each current transition period and the reference current stable periods; obtaining the influence gain coefficient of the high-temperature superconducting cable cooling tube based on the temperature data changes and the influence degree of each current transition period of the day; and predicting the aging of the cooling tube based on the influence gain coefficient of the high-temperature superconducting cable cooling tube.

2. The method for predicting the aging of high-temperature superconducting cable cooling tubes based on multi-factor coupling according to claim 1, characterized in that, The daily current stabilization period and current transition period include: Take any day as the target day, and based on the difference in current data between different times on the target day, cluster all times on the target day to obtain multiple clusters. The time period consisting of consecutive times in the same cluster is taken as the approximate current time period of the target day. Take any approximate current period of the target day as the approximate current period. Based on the distribution of current data at each moment of the approximate current period, divide the approximate current period into a current stability period and a current transition period.

3. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling according to claim 2, characterized in that, The division of the approximate target current time period into a current stabilization period and a current transition period includes: The maximum and minimum values ​​are extracted from the current data at all times during the approximate period of the target current. The average of all the maximum values ​​during the approximate period of the target current is taken as the upper limit of the normal current during the approximate period of the target current. The average of all the minimum values ​​during the approximate period of the target current is taken as the lower limit of the normal current during the approximate period of the target current. The lower limit of the normal current and the upper limit of the normal current are used to form the normal current fluctuation range during the approximate period of the target current. Within the target current approximation period, the time period consisting of consecutive moments when the current data does not fall within the normal current fluctuation range is designated as the current transition period of the target current approximation period, and all other time periods excluding the current transition period are designated as the current stabilization period of the target current approximation period.

4. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling as described in claim 1, characterized in that, The degree of loss obtained during each current stabilization period includes: The average value of the current data at all times during each current stabilization period is taken as the overall current level value for each current stabilization period. Extreme values ​​are extracted from the current data at all times during each current stabilization period. Based on the differences in current data between adjacent times during each current stabilization period and the number of extreme values ​​during each current stabilization period, the degree of current fluctuation during each current stabilization period is obtained. The overall current level and the degree of current fluctuation for each current stable period are combined and normalized to obtain the loss level for each current stable period.

5. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling according to claim 4, characterized in that, The degree of current fluctuation obtained during each current stabilization period includes: In each current stabilization period, the difference between the current data at each time point and the next adjacent time point is taken as the current change at each time point, and the average of the absolute values ​​of the differences between the current changes at all two adjacent time points is taken as the fluctuation coefficient for each current stabilization period. The degree of current fluctuation in each stable current period is obtained by combining the fluctuation coefficient of each stable current period and the number of extreme values ​​in each stable current period.

6. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling according to claim 4, characterized in that, The degree of influence obtained for each current transition period includes: The average of the loss levels of the two reference current stabilization periods for each current transition period is taken as the overall loss level of the reference current stabilization period for each current transition period. The current stabilization period located to the right of each current transition period is designated as the right current stabilization period of each current transition period, and the current stabilization period located to the left of each current transition period is designated as the left current stabilization period of each current transition period. The numerator is the difference between the overall current level value of the right current stabilization period and the overall current level value of the left current stabilization period in each current transition period, and the denominator is the average length of the two reference current stabilization periods in each current transition period. The ratio is used as the current upward trend value of the reference current stabilization period in each current transition period. After combining the overall loss level and the current rise trend value and normalizing them, the impact level of the reference current stable period during each current transition period is obtained. The impact of each current transition period is determined by the difference in the overall current level between the two reference current stable periods for each current transition period, the length of each current transition period, and the degree of impact of the change.

7. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling according to claim 6, characterized in that, The determination of the impact degree of each current transition period based on the difference in the overall current level between two reference current stable periods for each current transition period, the length of each current transition period, and the degree of change impact includes: The absolute value of the difference between the overall current level values ​​between the two reference current stable periods for each current transition period is used as the numerator, the length of each current transition period is used as the denominator, and the ratio is used as the rate of change assessment value for each current transition period. The impact degree of each current transition period is obtained by combining the rate of change assessment value of each current transition period and the impact degree of the change in the reference current stable period of each current transition period and then normalizing them.

8. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling according to claim 1, characterized in that, The gain coefficient of the obtained high-temperature superconducting cable cooling pipe includes: The difference between the maximum value of the temperature data at all times in the current steady period adjacent to the right of each current transition period and the temperature data at the first time of each current transition period is taken as the temperature rise of each current transition period. The two-dimensional data points, consisting of the temperature rise and the degree of influence during each current transition period of each day, are mapped onto a coordinate system. A straight line is fitted to all the two-dimensional data points for each day, and the slope of the fitted straight line is used as the correlation trend value for each day. The horizontal axis of the coordinate system represents the temperature rise, and the vertical axis represents the degree of influence. The ReLU function is used to map the difference between the correlation trend value of each day within a preset time period and the correlation trend value of the previous day to obtain the degree of correlation increase each day. The cumulative value of the impact of all current transition periods each day is taken as the cumulative impact of current each day. The product of the daily increase in correlation and the cumulative effect of current is taken as the daily change in current effect, and the sum of the daily cumulative effect of current and the change in current effect is taken as the daily degradation coefficient. The influence gain coefficient of the high-temperature superconducting cable cooling pipe is obtained based on the difference in the degradation coefficient between adjacent days within a preset time period.

9. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling according to claim 8, characterized in that, The gain coefficient for obtaining the influence of the high-temperature superconducting cable cooling pipe based on the difference in the degradation coefficient between adjacent days within a preset time period includes: The difference between the degradation coefficient of each day within the preset time period and the degradation coefficient of the previous day is taken as the daily degradation coefficient change. The average value of the degradation coefficient change over all days within a preset time period is normalized to obtain the influence gain coefficient of the high-temperature superconducting cable cooling pipe.

10. The method for predicting the aging of cooling tubes in high-temperature superconducting cables based on multi-factor coupling according to claim 1, characterized in that, The aging prediction of the cooling pipes includes: If the gain coefficient is greater than the preset threshold, it indicates that the cooling tube of the high-temperature superconducting cable is aging.

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