A power connection line AI adaptive temperature closed-loop regulation system

Abstract

This invention discloses an AI-adaptive temperature closed-loop regulation system for power connection lines, relating to the field of power supply technology. The key technical points are: acquiring real-time load parameters of the current power connection line; establishing a thermal adaptation prediction model based on historical load parameters and historical thermal deformation repair and adjustment data; inputting the real-time load parameters into the thermal adaptation prediction model to obtain a basic temperature regulation value; performing heat conduction simulation based on the real-time load parameters to obtain simulated thermal deformation characteristic data; processing historical heat penetration area, historical line aging area, historical thermal deformation characteristic data, and simulated thermal deformation characteristic data to obtain the heat penetration area of ​​the coupled influence region; obtaining the actual temperature regulation value based on the basic temperature regulation value, the pre-processed temperature change rate, the heat penetration area, and the additional loss due to thermal deformation; and performing closed-loop temperature regulation of the power connection line based on the actual temperature regulation value and the heat penetration area, thereby improving the reliability and stability of the overall power supply system.

Description

Technical Field

[0001] This invention relates to the field of power supply technology, and more specifically, to an AI adaptive temperature closed-loop regulation system for power connection lines. Background Technology

[0002] In scenarios reliant on power cables, such as power transmission, data centers, and new energy vehicles, cable temperature control is always crucial for ensuring the safe and stable operation of the system. Traditional power cable temperature control solutions often employ passive cooling or active cooling based on fixed thresholds. These methods exhibit significant limitations when facing complex and dynamic load changes. Furthermore, traditional solutions generally ignore the coupled thermal effects of multiple adjacent cables. In data center cabinets or industrial power distribution scenarios, multiple power cables are typically densely arranged. When one cable generates heat due to high load, the heat diffuses to adjacent cables, creating a coupled effect area that causes multiple cables to rise in temperature simultaneously. Traditional temperature control systems only monitor and adjust the temperature of individual cables, failing to recognize this coupling effect. This can easily lead to insufficient localized heat dissipation or overcooling, reducing temperature control efficiency and wasting energy. In addition, traditional solutions lack quantitative analysis of the correlation between thermal deformation and heat loss, failing to predict the impact of additional losses caused by deformation on temperature changes, thus increasing maintenance costs and safety risks. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the present invention aims to provide an AI adaptive temperature closed-loop regulation system for power connection lines.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A power connection line AI adaptive temperature closed-loop regulation system includes:

[0006] First acquisition module: Acquires the real-time load parameters of the current power connection line;

[0007] The first processing module establishes a thermal adaptation prediction model based on historical load parameters and historical thermal deformation repair and adjustment data. It inputs real-time load parameters into the thermal adaptation prediction model to obtain the basic temperature adjustment value. It then performs heat conduction simulation based on the real-time load parameters to obtain simulated thermal deformation characteristic data.

[0008] Analysis module: Processes and analyzes historical data and simulated thermal deformation characteristic data to obtain the additional loss value of thermal deformation and the rate of change of preprocessed temperature;

[0009] The second acquisition module: acquires the coupling influence area formed by the adjacent layout of the main test connection line to which the main test thermal deformation characteristic data belongs and the auxiliary test connection line to which the auxiliary test thermal deformation characteristic data belongs;

[0010] The second processing module processes historical heat penetration area, historical line aging area, historical thermal deformation characteristic data, and pseudo-thermal deformation characteristic data to obtain the heat penetration area of ​​the coupled influence region.

[0011] The third processing module: derives the actual temperature adjustment value based on the base temperature adjustment value, the pretreatment temperature change rate, the heat penetration area, and the additional loss due to heat deformation.

[0012] Adjustment module: Performs closed-loop temperature adjustment of the power connection cable based on the actual temperature adjustment value and heat penetration area.

[0013] Preferably, the simulated thermal deformation characteristic data are obtained by performing heat conduction simulation based on real-time load parameters, specifically including the following steps:

[0014] The base number of heat generation during the transmission process of the line is extracted based on real-time load parameters. The initial boundary conditions for heat conduction simulation are determined based on the base number of heat generation, the thermal conductivity of the power connection line material itself, and the thermal barrier performance of the outer insulation structure. The base number of heat generation is the amount of heat generated per unit length and per unit time when the real-time load parameters are applied.

[0015] Based on the initial boundary conditions, a full-domain heat conduction path is constructed. Based on the full-domain heat conduction path, the heat conduction differences of each layer, such as the core, insulation layer, and protective sheath, are distinguished. After tracking the conduction rate and heat accumulation state of the heat generation base between each layer, hierarchical heat distribution data is formed.

[0016] The hierarchical heat distribution data is processed to obtain the target deformation region where deformation occurs;

[0017] The correlation between heat accumulation and linear deformation is quantified by combining the interaction of heat conduction between layers, and the deformation quantification results of the target deformation region are corrected after judging the constraint effect of deformation of adjacent layers.

[0018] Based on the deformation variation results of the target deformation region, the deformation location, deformation amplitude, deformation uniformity, and deformation variation law with heat conduction time are extracted to form simulated thermal deformation characteristic data.

[0019] Preferably, the hierarchical heat distribution data is processed to obtain the target deformation region where deformation occurs, specifically including the following steps:

[0020] The adaptation relationship between the thermal expansion coefficient of each level and the heat accumulation state is determined based on the hierarchical heat distribution data;

[0021] Based on the adaptation relationship, determine the trend of linear shape change corresponding to different heat accumulation areas;

[0022] The target deformation area that has undergone deformation is selected based on the trend of line shape change.

[0023] Preferably, the historical data and simulated thermal deformation characteristic data are processed and analyzed to obtain the additional loss value of thermal deformation and the rate of change of pre-processing temperature, specifically including the following steps:

[0024] The historical condition data includes historical thermal deformation characteristic data and historical heat loss increment values;

[0025] The additional heat deformation loss value is obtained by processing historical thermal deformation characteristic data, historical heat loss increment value and simulated thermal deformation characteristic data.

[0026] Based on the correlation trend between the historical temperature change rate of the current power connection line and the historical thermal deformation characteristic data, the preprocessed temperature change rate is obtained.

[0027] Preferably, the additional heat deformation loss value is obtained by processing historical thermal deformation characteristic data, historical heat loss increment values, and simulated thermal deformation characteristic data, specifically including the following steps:

[0028] The heat loss correlation coefficient is obtained based on the correlation trend characteristics between historical thermal deformation characteristic data and historical heat loss increment values.

[0029] The additional thermal deformation loss value of the current power connection line is obtained based on the thermal loss correlation coefficient and simulated thermal deformation characteristic data.

[0030] Preferably, the preprocessed temperature change rate is obtained based on the correlation trend characteristics between the historical temperature change rate of the current power connection line and the historical thermal deformation characteristic data, specifically including the following steps:

[0031] Extract the historical temperature change rate affected by historical thermal deformation characteristic data, and obtain the temperature change rate correlation coefficient based on the correlation trend characteristics between the historical temperature change rate and the historical thermal deformation characteristic data.

[0032] Select the main measured thermal deformation characteristic data and the auxiliary measured thermal deformation characteristic data from the simulated thermal deformation characteristic data;

[0033] The temperature change rate 1 of the main test connection line is obtained based on the thermal deformation characteristic data of the main test and the correlation coefficient of the temperature change rate; the temperature change rate 2 of the auxiliary test connection line is obtained based on the thermal deformation characteristic data of the auxiliary test and the correlation coefficient of the temperature change rate; the preprocessing temperature change rate is obtained based on the temperature change rate 1 and the temperature change rate 2.

[0034] Preferably, obtaining the coupling influence area formed by the adjacent arrangement of the main test connection line to which the main test thermal deformation characteristic data belongs and the auxiliary test connection line to which the auxiliary test thermal deformation characteristic data belongs specifically includes the following steps:

[0035] Acquire the thermal deformation characteristic data of the main test connection line and the auxiliary test connection line, and acquire the actual layout trajectory, line cross-sectional specifications and actual spacing data of the main test connection line and the auxiliary test connection line.

[0036] Based on the actual deployment trajectory, adjacent deployment segments are determined, and the line extension direction and relative positional relationship of adjacent deployment segments are extracted.

[0037] Based on the extension direction and relative position of adjacent deployment sections, the potential influence area is determined. Combined with the cross-sectional specifications of the line, the line radiation range corresponding to each potential influence area is determined. Based on the line radiation range, the overlapping area of ​​the radiation range of the main test connecting line and the radiation range of the auxiliary test connecting line is determined as the initial coupling area.

[0038] Extract the heat conduction path of the initial coupling region, and combine the main measured thermal deformation characteristic data and the auxiliary measured thermal deformation characteristic data to determine whether there is a bidirectional heat transfer effect in each heat conduction path. The coverage area of ​​the heat conduction path with bidirectional heat transfer effect is determined as the target influence area.

[0039] Based on the cross-sectional specifications of the line and the actual spacing data, the boundary range of the target influence area is corrected to form the coupling influence area caused by the adjacent layout of the main test connection line and the auxiliary test connection line.

[0040] Preferably, the heat penetration area of ​​the coupled influence region is obtained by processing historical heat penetration area, historical aging area of ​​the linear body, historical thermal deformation characteristic data, and pseudo-thermal deformation characteristic data, specifically including the following steps:

[0041] The area of ​​thermal stress distribution to be measured is obtained by statistically analyzing the coverage area of ​​the concentrated thermal stress region.

[0042] Based on the area of ​​thermal stress distribution to be measured, the area of ​​historical aging region of the line body and the historical heat penetration area of ​​the historical aging region of the line body affected by thermal deformation are extracted from historical monitoring data.

[0043] Based on the correlation and influence trend characteristics of historical heat penetration area, historical linear aging area and historical thermal deformation characteristics data, the area penetration influence factor is obtained.

[0044] The thermal penetration area of ​​the coupled influence region is obtained based on the measured thermal stress distribution area, the area penetration influence factor, and the simulated thermal deformation characteristic data.

[0045] Preferably, the actual temperature adjustment value is obtained based on the basic temperature adjustment value, the pretreatment temperature change rate, the heat penetration area, and the additional loss due to thermal deformation. This specifically includes the following steps:

[0046] Extract historical heat penetration-related loss values ​​from historical monitoring data, which show that the rate of temperature change is affected by the historical heat penetration area, resulting in a decrease in the heat dissipation efficiency of the production line.

[0047] The influence coefficient of heat penetration loss is obtained based on the correlation trend characteristics between historical temperature change rate, historical heat penetration area and historical heat penetration loss value.

[0048] The estimated value of heat penetration-related loss is obtained based on the heat penetration loss influence coefficient, the pretreatment temperature change rate, and the heat penetration area.

[0049] The actual temperature adjustment value is obtained based on the additional loss value of thermal deformation, the estimated value of heat penetration associated loss, and the basic temperature adjustment value.

[0050] Preferably, the power connection cable is subjected to closed-loop temperature regulation based on the actual temperature adjustment value and the heat penetration area, specifically including the following steps:

[0051] The additional heat deformation loss value is retrieved based on the actual temperature adjustment value. When the additional heat deformation loss value is greater than or equal to the standard range, the adjustment range of the adjustment parameter is increased in the cooling direction pointed to by the actual temperature adjustment value. When the additional heat deformation loss value is less than the standard range, the adjustment range of the adjustment parameter is decreased in the cooling direction pointed to by the actual temperature adjustment value, thus forming an initial adjustment trend of the adjustment parameter.

[0052] Based on the heat penetration area, the heat-sensitive section of the power connection line is defined, and the adjustment trend of the initial adjustment parameters is correspondingly allocated to the heat-sensitive section so that the adjustment response speed of the heat-sensitive section matches the temperature change rate, thus obtaining the prototype of the adjustment parameters.

[0053] Real-time thermal state data of the power connection line is collected after the initial adjustment parameter is applied. The real-time thermal state data is compared with the pre-processed temperature change rate to determine whether the initial adjustment parameter can suppress the temperature change rate from exceeding the reasonable range. If the temperature change rate deviates from the reasonable range, the initial adjustment parameter is corrected with the heat penetration area as the weight to form iterative adjustment parameters.

[0054] The adaptability of the iterative adjustment parameters is verified by combining the additional loss value of thermal deformation, and the adaptability adjustment parameters are obtained.

[0055] Temperature closed-loop regulation of the power connection cable is performed based on adaptability adjustment parameters.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] This invention accurately captures the thermal deformation characteristics of the power supply line through thermal conduction simulation, and quantifies the additional losses from thermal deformation and the heat penetration area using historical data, avoiding the lag of traditional temperature control that relies on threshold triggering. When a sudden surge in traffic from a server cluster causes a sharp increase in load, the air-cooling module enhances heat dissipation in heat-sensitive sections, effectively preventing the risk of insulation softening, core deformation, or even short circuits and fires due to overheating. By identifying and quantifying the heat penetration area, differentiated adjustments can be implemented for heat-sensitive sections, avoiding unnecessary energy waste. By suppressing the continuous accumulation of additional losses from thermal deformation, the aging rate of the power supply material is effectively slowed down. By monitoring the changing trend of the heat penetration area over a long period, aging areas of the power supply insulation layer can be identified in advance, improving the reliability and stability of the overall power supply system. Attached Figure Description

[0058] Figure 1 This is a schematic diagram of a power connection line AI adaptive temperature closed-loop regulation system provided in an embodiment of the present invention;

[0059] Figure 2 This is a schematic diagram illustrating the steps of obtaining the preprocessed temperature change rate in a power connection line AI adaptive temperature closed-loop regulation system according to an embodiment of the present invention. Detailed Implementation

[0060] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0061] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0062] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0063] Reference Figures 1-2 As shown.

[0064] The embodiments further illustrate the AI ​​adaptive temperature closed-loop regulation system for power connection lines proposed in this invention.

[0065] A power connection line AI adaptive temperature closed-loop regulation system includes:

[0066] First acquisition module: Acquires the real-time load parameters of the current power connection line;

[0067] The first processing module establishes a thermal adaptation prediction model based on historical load parameters and historical thermal deformation repair and adjustment data, and inputs real-time load parameters into the thermal adaptation prediction model to obtain the basic temperature adjustment value.

[0068] A thermal adaptation prediction model is constructed by deep learning of historical operating data to predict the temperature adjustment requirements of power connection lines. During actual operation, the thermal adaptation prediction model collects and integrates a large number of historical load parameters and corresponding historical thermal deformation repair and adjustment data. The historical load parameters include the current magnitude, voltage fluctuation and duration information of the power connection lines in different time periods. The historical thermal deformation repair and adjustment data records the temperature adjustment range and adjustment effect taken in the past to repair or alleviate the thermal deformation of the line.

[0069] Based on the above data, a thermal adaptation prediction model is established. This model uses algorithms to uncover the potential correlation between load changes and thermal deformation. For example, if the load current increases by 30% in a short period, the thermal deformation of the line increases by 12% within 15 minutes, requiring an effective temperature adjustment of 8% to suppress deformation. After the thermal adaptation prediction model is built, real-time load parameters are input into it. These parameters are combined with historical data to determine the required baseline temperature adjustment value for the current load condition.

[0070] The correspondence between parameters is clarified through calculation formulas. Let the base temperature adjustment value be J, the average fluctuation range of historical load parameters be K, the average effective range of historical thermal deformation repair adjustment data be L, and the rate of change of real-time load parameters relative to the historical average load be M. Then, the formula for calculating the base temperature adjustment value is J = L × (M × 1.2 + K × 0.8). For example, when the average effective range of historical thermal deformation repair adjustment data L is 5℃, the average fluctuation range of historical load parameters K is 10A, and the rate of change of real-time load parameters relative to the historical average load M is 1.3, substituting these values ​​into the formula yields J = 5 × (1.3 × 1.2 + 10 × 0.8) = 47.8℃. This value is the base temperature adjustment value required under the current real-time load.

[0071] Simulated thermal deformation characteristic data are obtained by performing heat conduction simulation based on real-time load parameters;

[0072] Analysis module: Processes and analyzes historical data and simulated thermal deformation characteristic data to obtain the additional loss value of thermal deformation and the rate of change of preprocessed temperature;

[0073] The second acquisition module: acquires the coupling influence area formed by the adjacent layout of the main test connection line to which the main test thermal deformation characteristic data belongs and the auxiliary test connection line to which the auxiliary test thermal deformation characteristic data belongs;

[0074] The second processing module processes historical heat penetration area, historical line aging area, historical thermal deformation characteristic data, and pseudo-thermal deformation characteristic data to obtain the heat penetration area of ​​the coupled influence region.

[0075] The third processing module: derives the actual temperature adjustment value based on the base temperature adjustment value, the pretreatment temperature change rate, the heat penetration area, and the additional loss due to heat deformation.

[0076] Adjustment module: Performs closed-loop temperature adjustment of the power connection cable based on the actual temperature adjustment value and heat penetration area.

[0077] The simulated thermal deformation characteristic data are obtained by performing heat conduction simulation based on real-time load parameters, specifically including the following steps:

[0078] The heat generation baseline of the line transmission process is extracted based on real-time load parameters. The initial boundary conditions for heat conduction simulation are determined based on the heat generation baseline, the thermal conductivity of the power connection line material, and the thermal barrier performance of the outer insulation structure. The heat generation baseline is the amount of heat generated per unit length and per unit time when the real-time load parameters are applied.

[0079] Based on the initial boundary conditions, a full-domain heat conduction path is constructed. Based on the full-domain heat conduction path, the heat conduction differences of each layer, such as the core, insulation layer, and protective sheath, are distinguished. After tracking the conduction rate and heat accumulation state of the heat generation base between each layer, hierarchical heat distribution data is formed.

[0080] The process of processing hierarchical heat distribution data to obtain the target deformation region where deformation occurs includes the following steps:

[0081] The adaptation relationship between the thermal expansion coefficient of each level and the heat accumulation state is determined based on the hierarchical heat distribution data;

[0082] Based on the adaptation relationship, determine the trend of linear shape change corresponding to different heat accumulation areas;

[0083] The target deformation area that has undergone deformation is selected based on the trend of line shape change;

[0084] The correlation between heat accumulation and linear deformation is quantified by combining the interaction of heat conduction between layers, and the deformation quantification results of the target deformation region are corrected after judging the constraint effect of deformation of adjacent layers.

[0085] Based on the deformation variation results of the target deformation region, the deformation location, deformation amplitude, deformation uniformity, and deformation variation law with heat conduction time are extracted to form simulated thermal deformation characteristic data.

[0086] First, the base heat generation during the transmission process of the wire is extracted based on real-time load parameters. The base heat generation represents the heat generated per unit length and per unit time of the wire under real-time load. When the real-time load current is 300A, the base heat generation of the copper wire core is significantly higher than that under a 200A load. Base heat generation = real-time load current² × resistance per unit length of wire core. Combining the thermal conductivity of the power connection wire material itself and the thermal barrier performance of the outer insulation structure, the initial boundary conditions for the heat conduction simulation can be determined.

[0087] A global heat conduction path is constructed based on initial boundary conditions. This path differentiates the heat conduction differences between the core, insulation layer, and protective sheath. The core, as the primary heat source, conducts heat to the insulation layer and then outwards to the protective sheath. The conduction rate and heat accumulation status of the heat generation base are tracked between each layer to form hierarchical heat distribution data. For example, in high-temperature environments, the thermal conductivity of the insulation layer decreases due to material softening, causing more heat to accumulate at the interface between the core and the insulation layer.

[0088] After obtaining the hierarchical heat distribution data, the target deformation region where deformation occurs is located. Based on the hierarchical heat distribution data, the compatibility between the thermal expansion coefficient of each level and the heat accumulation state is determined. Different materials have different thermal expansion coefficients; for example, the thermal expansion coefficient of copper wire core is... The coefficient of thermal expansion of PVC insulation is... When the heat in the wire core accumulates sufficiently, the expansion of the insulation layer is greater than that of the wire core. This fit is the basis for judging the deformation trend.

[0089] Based on the adaptation relationship, the trend of wire shape change corresponding to different heat accumulation areas is determined, and the target deformation area is screened out. For example, when the temperature exceeds 70°C due to local heat accumulation in the wire core, the corresponding insulation layer area shows obvious expansion and bulging, and this area is identified as the target deformation area.

[0090] By combining the interaction of heat conduction between layers, the correspondence between heat accumulation and the degree of wire deformation is quantified, and the deformation reduction result of the target deformation area is corrected after judging the deformation constraint effect of adjacent layers. Corrected deformation = initial deformation × (1 + adjacent layer constraint coefficient × difference in heat conduction rate). The adjacent layer constraint coefficient is determined by the deformation resistance of different materials. For example, the constraint coefficient of the insulation layer on the copper wire core is 0.3, while the constraint coefficient of the sheath on the insulation layer is 0.5. When the difference in heat conduction rate between the wire core and the insulation layer is 0.2, the corrected deformation of the area with an initial deformation of 1.2 mm is 1.2 × (1 + 0.3 × 0.2) = 1.272 mm.

[0091] Based on the deformation variation results of the target deformation area, the deformation location, deformation amplitude, deformation uniformity, and deformation variation patterns with heat conduction time are extracted to form complete simulated thermal deformation characteristic data. For example, in a 30-minute 250A load test, the system records that the deformation amplitude within a 15cm range in the middle section of the wire core increases from 0.5mm to 1.8mm, and the deformation uniformity gradually decreases over time. This characteristic data is directly used to optimize the temperature regulation strategy, enabling the temperature control system to operate in high-risk deformation areas, thereby improving the operational safety and service life of the power connection cable.

[0092] The historical data and simulated thermal deformation characteristic data are processed and analyzed to obtain the additional loss value of thermal deformation and the rate of change of preprocessing temperature. The specific steps include:

[0093] Historical data includes historical thermal deformation characteristics and historical heat loss increments;

[0094] The additional heat loss value is obtained by processing historical thermal deformation characteristic data, historical heat loss increment values, and simulated thermal deformation characteristic data. This process includes the following steps:

[0095] The heat loss correlation coefficient is obtained based on the correlation trend characteristics between historical thermal deformation characteristic data and historical heat loss increment values.

[0096] The additional thermal deformation loss value of the current power connection line is obtained based on the thermal loss correlation coefficient and simulated thermal deformation characteristic data.

[0097] Based on the correlation trend between the historical temperature change rate of the current power connection line and the historical thermal deformation characteristic data, the preprocessed temperature change rate is obtained, which specifically includes the following steps:

[0098] Extract the historical temperature change rate affected by historical thermal deformation characteristic data, and obtain the temperature change rate correlation coefficient based on the correlation trend characteristics between the historical temperature change rate and the historical thermal deformation characteristic data.

[0099] Select the main measured thermal deformation characteristic data and the auxiliary measured thermal deformation characteristic data from the simulated thermal deformation characteristic data;

[0100] The temperature change rate 1 of the main test connection line is obtained based on the thermal deformation characteristic data of the main test and the correlation coefficient of the temperature change rate; the temperature change rate 2 of the auxiliary test connection line is obtained based on the thermal deformation characteristic data of the auxiliary test and the correlation coefficient of the temperature change rate; the preprocessing temperature change rate is obtained based on the temperature change rate 1 and the temperature change rate 2.

[0101] Historical data includes historical thermal deformation characteristics and historical heat loss increments. Historical thermal deformation characteristics record the location, magnitude, and uniformity of deformation of the power connection lines under different loads in the past, while historical heat loss increments correspond to the additional power loss caused by these deformations. Based on the correlation trend between historical thermal deformation characteristics and historical heat loss increments, a quantitative correlation coefficient is obtained. When historical data shows that for every 1mm increase in the deformation amplitude of the line body, the average heat loss increases by 2.3W / m, the corresponding heat loss correlation coefficient is calculated through fitting.

[0102] The additional heat loss value is calculated as follows: heat loss correlation coefficient × weighted value of deformation amplitude in simulated heat deformation characteristic data. If the heat loss correlation coefficient is 2.3 and the current simulated heat deformation characteristic data shows that the average deformation amplitude within 10cm of the middle section of the line is 1.5mm, then substituting this value into the formula yields an additional heat loss value of 2.3 × 1.5 = 3.45W / m. This value directly reflects the additional heat loss caused by the current deformation.

[0103] After obtaining the additional loss value due to thermal deformation, the preprocessing temperature change rate is derived. First, the historical temperature change rate under the influence of historical thermal deformation characteristic data is extracted. The correlation trend between the historical temperature change rate and the historical thermal deformation characteristic data is determined, thus obtaining the temperature change rate correlation coefficient. For example, historical data shows that when the deformation uniformity decreases by 0.2, the average temperature change rate increases by 0.8℃ / min. The temperature change rate correlation coefficient = the increase in temperature change rate ÷ the decrease in deformation uniformity. Based on this pattern, the corresponding temperature change rate correlation coefficient can be calculated.

[0104] The simulated thermal deformation characteristic data is differentiated into primary and secondary thermal deformation characteristic data. The primary data comes from the core power supply line, while the secondary data comes from adjacent backup lines. The temperature change rate 1 of the primary test connection line is calculated based on the correlation coefficient between the primary test thermal deformation characteristic data and the temperature change rate. The temperature change rate 2 of the secondary test connection line is calculated based on the correlation coefficient between the secondary test thermal deformation characteristic data and the temperature change rate. Finally, the two are weighted and fused to obtain the preprocessed temperature change rate. Preprocessed temperature change rate = (Temperature change rate 1 × Primary test weight + Temperature change rate 2 × Secondary test weight) × Ambient temperature correction coefficient.

[0105] Assuming the primary measurement weight is 0.7, the secondary measurement weight is 0.3, and the ambient temperature correction coefficient is 1.1, when the first temperature change rate is 2.1℃ / min and the second temperature change rate is 1.5℃ / min, substituting these values ​​into the formula yields the pretreatment temperature change rate: (2.1 × 0.7 + 1.5 × 0.3) × 1.1 = 2.112℃ / min. This value provides a dynamic benchmark for subsequent temperature adjustment, allowing for the prediction of temperature change trends.

[0106] The coupling influence area formed by the adjacent layout of the main test connection line to which the main test thermal deformation characteristic data belongs and the auxiliary test connection line to which the auxiliary test thermal deformation characteristic data belongs includes the following steps:

[0107] Acquire the thermal deformation characteristic data of the main test connection line and the auxiliary test connection line, and acquire the actual layout trajectory, line cross-sectional specifications and actual spacing data of the main test connection line and the auxiliary test connection line.

[0108] Based on the actual deployment trajectory, adjacent deployment segments are determined, and the line extension direction and relative positional relationship of adjacent deployment segments are extracted.

[0109] Based on the extension direction and relative position of adjacent deployment sections, the potential influence area is determined. Combined with the cross-sectional specifications of the line, the line radiation range corresponding to each potential influence area is determined. Based on the line radiation range, the overlapping area of ​​the radiation range of the main test connecting line and the radiation range of the auxiliary test connecting line is determined as the initial coupling area.

[0110] Extract the heat conduction path of the initial coupling region, and combine the main measured thermal deformation characteristic data and the auxiliary measured thermal deformation characteristic data to determine whether there is a bidirectional heat transfer effect in each heat conduction path. The coverage area of ​​the heat conduction path with bidirectional heat transfer effect is determined as the target influence area.

[0111] Based on the cross-sectional specifications of the line and the actual spacing data, the boundary range of the target influence area is corrected to form the coupling influence area caused by the adjacent layout of the main test connection line and the auxiliary test connection line.

[0112] First, thermal deformation characteristic data of the main test connection cable and the auxiliary test connection cable are collected to obtain the actual layout trajectory, cable cross-sectional specifications, and actual spacing data of the main test connection cable and the auxiliary test connection cable. The main test connection cable is the main line carrying the power supply of the core server, and the auxiliary test connection cable is an adjacent backup line. The layout trajectory records the direction of the two cables in the rack. The cable cross-sectional specifications include the core diameter and insulation layer thickness, and the actual spacing is the minimum distance between the two cables.

[0113] Based on the actual deployment trajectory, the adjacent deployment segments of the two lines are determined, and the extension direction and relative positional relationship of the lines within the segment are extracted. For example, in the vertical cabling area of ​​the same cabinet, the main test and auxiliary test lines run parallel to each other and are adjacent to each other on the left and right. This direction and positional relationship directly determines the way heat-affected zones are transferred.

[0114] The potential impact zone is determined based on the extension direction and relative position of adjacent deployment segments. First, the extension direction of adjacent deployment segments is identified, including parallel, intersecting, and non-parallel directions. In the parallel direction scenario, the two lines extend continuously in the same direction, and heat is continuously transferred along the length of the lines; therefore, the potential impact zone covers the entire adjacent deployment segment of the two lines. In the intersecting direction, heat experiences brief local interaction near the intersection point, and the potential impact zone focuses on the local area around the intersection point. In the non-parallel direction, although the two lines are adjacent, they are not on the same plane, and heat transfer is affected by spatial angles; the potential impact zone is limited to the section where the projections of the two lines overlap. The boundaries of the potential impact zone are then refined based on the relative position of the lines.

[0115] When two lines are parallel and adjacent to each other, the width of the potential influence zone is based on the distance between the two lines and extends to both sides to cover the range of lateral heat diffusion. If they are parallel and adjacent vertically, the height of the potential influence zone is based on the vertical distance and extends upwards and downwards to match the longitudinal heat convection pattern. In the case of intersecting directions, the potential influence zone is determined as a circle or ellipse centered on the intersection point, according to the cross-sectional specifications of the lines, to ensure coverage of the heat diffusion range at the intersection point.

[0116] Taking the cabling inside a data center cabinet as an example, the main test and auxiliary test lines run vertically and parallel to each other inside the cabinet, with a left-right spacing of 25mm. The 2-meter vertical section of the two lines is defined as the potential impact zone, and the width of the zone is set at 25mm. In addition, there is a 10mm heat dissipation margin on each side, thus forming a rectangular potential impact zone with a width of 45mm and a length of 2 meters.

[0117] If two lines intersect at a 45-degree angle at the top of the cabinet, a circular potential impact zone with a diameter of 50mm is delineated with the intersection point as the center, covering only the local area of ​​the intersection point.

[0118] This method can transform abstract spatial orientation and positional relationships into specific potential influence zones.

[0119] The radiation range of the line body corresponding to each potential influence zone is calculated based on the line body cross-sectional specifications. The radiation range can be quantified using the formula: Radiation range = Line body cross-sectional radius × Ambient thermal conductivity × 1.2. Here, the ambient thermal conductivity is determined by the surrounding airflow. If the line body cross-sectional radius is 15mm and the ambient thermal conductivity is 0.8, substituting these values ​​into the formula yields a radiation range of 15 × 0.8 × 1.2 = 14.4mm. The radiation ranges of the main test connection line and the auxiliary test connection line are superimposed; the overlapping area is the initial coupling region. For example, when the distance between the main test and auxiliary test lines is 20mm, and their respective radiation ranges are 14.4mm, the width of their overlapping region is... This region is the initial coupling region.

[0120] Heat conduction paths within the initial coupling region are extracted, and the presence of bidirectional heat transfer effects is determined by combining the thermal deformation characteristic data of the main test line and the auxiliary test line. Bidirectional heat transfer effect refers to the phenomenon where heat is transferred from the main test line to the auxiliary test line, and heat is also transferred back to the main test line. When the thermal deformation amplitude of the main test line due to high load is 1.8 mm, and the thermal deformation amplitude of the auxiliary test line is 1.2 mm, the flow direction of heat in the overlapping area is determined. If the heat from the two lines permeates each other, the path is determined to have a bidirectional heat transfer effect, and the corresponding coverage area is the target influence area.

[0121] The boundary range of the target influence area is corrected based on the cross-sectional specifications of the line and the actual spacing data, thus forming the final coupled influence area. When the cross-sectional specifications of the line increase, the radiation range will expand accordingly, and the boundary of the target influence area will expand outward; when the actual spacing decreases, the overlapping area will increase, and the boundary will shrink inward. The corrected coupled influence area can reflect the actual thermal interaction range of two adjacent lines.

[0122] The heat penetration area of ​​the coupled influence region is obtained by processing historical heat penetration area, historical aging area of ​​the linear body, historical thermal deformation characteristic data, and pseudo-thermal deformation characteristic data. Specifically, this includes the following steps:

[0123] The area of ​​thermal stress distribution to be measured is obtained by statistically analyzing the coverage area of ​​the concentrated thermal stress region.

[0124] Based on the area of ​​thermal stress distribution to be measured, the area of ​​historical aging region of the line body and the historical heat penetration area of ​​the historical aging region of the line body affected by thermal deformation are extracted from historical monitoring data.

[0125] Based on the correlation and influence trend characteristics of historical heat penetration area, historical linear aging area and historical thermal deformation characteristics data, the area penetration influence factor is obtained.

[0126] The thermal penetration area of ​​the coupled influence region is obtained based on the measured thermal stress distribution area, the area penetration influence factor, and the simulated thermal deformation characteristic data.

[0127] First, the coverage area of ​​the thermal stress concentration region is calculated to obtain the thermal stress distribution area to be measured. The thermal stress concentration region refers to the area where heat accumulation in the power connection line under load causes a significant increase in local stress. When the main test connection line is running under continuous high load, a thermal stress concentration region with a length of 80cm and a width of 2cm appears at the interface between the wire core and the insulation layer. The area of ​​this region is the thermal stress distribution area to be measured, i.e., 80×2=160cm².

[0128] Based on the measured thermal stress distribution area, the corresponding historical aging area of ​​the production line and the historical heat penetration area affected by thermal deformation in the historical aging area are extracted from historical monitoring data. The historical aging area refers to the total area of ​​the production line where material aging occurred due to long-term thermal stress under similar load conditions in the past; the historical heat penetration area is the actual area in the aging area where heat penetrates the insulation layer and diffuses to the outside. For example, when the measured thermal stress distribution area is 160 cm², the corresponding historical aging area obtained from historical data is 200 cm², and the corresponding historical heat penetration area is 50 cm².

[0129] Based on the correlation trends between historical heat penetration area, historical aging area of ​​the linear body, and historical thermal deformation characteristics, an area penetration influence factor is derived. The area penetration influence factor quantifies the correlation strength between historical heat penetration area, historical aging area of ​​the linear body, and historical thermal deformation characteristics. Area penetration influence factor = Historical heat penetration area ÷ (Historical aging area of ​​the linear body × Weighted value of historical thermal deformation amplitude).

[0130] If the historical heat penetration area is 50 cm², the historical aging area is 200 cm², and the weighted value of historical thermal deformation amplitude is 0.4, then substituting these values ​​into the formula yields the area penetration influence factor = 50 ÷ (200 × 0.4) = 0.625. The area penetration influence factor reflects the relative intensity of heat penetration in historical data.

[0131] By combining the measured thermal stress distribution area, the area penetration influence factor, and the simulated thermal deformation characteristic data, the thermal penetration area of ​​the coupled influence region is obtained. The thermal penetration area of ​​the coupled influence region = measured thermal stress distribution area × area penetration influence factor × simulated thermal deformation amplitude weighting value. The measured thermal stress distribution area is 160 cm², the area penetration influence factor is 0.625, and the current simulated thermal deformation amplitude weighting value is 0.5. Substituting these values ​​into the formula, we get the thermal penetration area of ​​the coupled influence region = 160 × 0.625 × 0.5 = 50 cm². This value reflects the actual range of heat penetration through the insulation layer within the current coupled influence region.

[0132] The actual temperature adjustment value is obtained based on the baseline temperature adjustment value, the rate of change of pretreatment temperature, the heat penetration area, and the additional loss due to thermal deformation. This process includes the following steps:

[0133] Extract historical heat penetration-related loss values ​​from historical monitoring data, which show that the rate of temperature change is affected by the historical heat penetration area, resulting in a decrease in the heat dissipation efficiency of the production line.

[0134] The influence coefficient of heat penetration loss is obtained based on the correlation trend characteristics between historical temperature change rate, historical heat penetration area and historical heat penetration loss value.

[0135] The estimated value of heat penetration-related loss is obtained based on the heat penetration loss influence coefficient, the pretreatment temperature change rate, and the heat penetration area.

[0136] The actual temperature adjustment value is obtained based on the additional loss value of thermal deformation, the estimated value of heat penetration associated loss, and the basic temperature adjustment value.

[0137] The heat penetration loss influence coefficient = historical heat penetration associated loss value ÷ (historical temperature change rate × historical heat penetration area). The historical heat penetration associated loss value is 3.2 W / m, the historical temperature change rate is 1.8℃ / min, and the historical heat penetration area is 40 cm². Substituting these values ​​into the formula yields the heat penetration loss influence coefficient. The heat penetration loss influence coefficient reflects the intensity of the impact of heat penetration on loss in historical data.

[0138] The estimated heat penetration loss is calculated as follows: Heat penetration loss influence coefficient × Pretreatment temperature change rate × Heat penetration area. If the current pretreatment temperature change rate is 2.1℃ / min and the heat penetration area is 50cm², substituting the values, we get the estimated heat penetration loss as 0.044 × 2.1 × 50 ≈ 4.62 W / m. This quantifies the impact of current heat penetration on heat dissipation efficiency.

[0139] The actual temperature regulation value is obtained by integrating the additional heat deformation loss value, the estimated heat penetration loss value, and the base temperature regulation value. The actual temperature regulation value = base temperature regulation value × (1 + additional heat deformation loss value × 0.1 + estimated heat penetration loss value × 0.08). For example, when the base temperature regulation value is 12℃, the additional heat deformation loss value is 3.45W / m, and the estimated heat penetration loss value is 4.62W / m, substituting these values ​​into the formula yields the actual temperature regulation value = 12 × (1 + 3.45 × 0.1 + 4.62 × 0.08) ≈ 20.575℃. The actual temperature regulation value is the final regulation command after multi-dimensional loss correction, enabling the temperature control system to take temperature regulation measures based on the combined effects of current load, deformation, and heat penetration, thereby effectively ensuring the safe operation of the power connection cable.

[0140] The power connection cable undergoes closed-loop temperature regulation based on the actual temperature adjustment value and heat penetration area, specifically including the following steps:

[0141] The additional heat deformation loss value is retrieved based on the actual temperature adjustment value. When the additional heat deformation loss value is greater than or equal to the standard range, the adjustment range of the adjustment parameter is increased in the cooling direction pointed to by the actual temperature adjustment value. When the additional heat deformation loss value is less than the standard range, the adjustment range of the adjustment parameter is decreased in the cooling direction pointed to by the actual temperature adjustment value, thus forming an initial adjustment trend of the adjustment parameter.

[0142] Based on the heat penetration area, the heat-sensitive section of the power connection line is defined, and the adjustment trend of the initial adjustment parameters is correspondingly allocated to the heat-sensitive section so that the adjustment response speed of the heat-sensitive section matches the temperature change rate, thus obtaining the prototype of the adjustment parameters.

[0143] Real-time thermal state data of the power connection line is collected after the initial adjustment parameter is applied. The real-time thermal state data is compared with the pre-processed temperature change rate to determine whether the initial adjustment parameter can suppress the temperature change rate from exceeding the reasonable range. If the temperature change rate deviates from the reasonable range, the initial adjustment parameter is corrected with the heat penetration area as the weight to form iterative adjustment parameters.

[0144] The adaptability of the iterative adjustment parameters is verified by combining the additional loss value of thermal deformation, and the adaptability adjustment parameters are obtained.

[0145] Temperature closed-loop regulation of the power connection cable is performed based on adaptability adjustment parameters.

[0146] The corresponding additional heat deformation loss value is retrieved based on the actual temperature adjustment value, and an initial adjustment trend for the adjustment parameters is generated accordingly. When the additional heat deformation loss value is greater than or equal to the standard range, it indicates that the additional loss caused by the current deformation of the production line is at a high level, requiring stronger cooling intervention. The adjustment range of the adjustment parameters is increased along the cooling direction indicated by the actual temperature adjustment value. If the standard range for the additional heat deformation loss value is 1 to 3 W / m, and the current value is 4.2 W / m, exceeding the upper limit of the standard, the adjustment range of the adjustment parameters is increased from the basic 1.2 times to 1.5 times to accelerate the cooling rate. Conversely, if the additional heat deformation loss value is less than the standard range, for example, the current value is 0.8 W / m, it indicates that the deformation loss is at a low level. The adjustment range of the adjustment parameters is then reduced along the cooling direction, from 1.2 times to 0.9 times, to avoid over-adjustment leading to increased energy consumption.

[0147] The heat-sensitive section of the power connection cable is defined based on the heat penetration area. The heat-sensitive section refers to the area with strong heat penetration and a rapid temperature change rate. When the heat penetration area is 50 cm², the corresponding 100 cm section of the cable is designated as the heat-sensitive section. The initial adjustment parameters are then assigned to this heat-sensitive section to match the adjustment response speed with the temperature change rate, thus obtaining a preliminary adjustment parameter model. If the pre-processed temperature change rate is 2.1℃ / min, the adjustment response speed is set to 2.0℃ / min to ensure that the adjustment speed matches the temperature rise rate, avoiding lag or over-adjustment.

[0148] Real-time thermal status data of the power connection line under the action of the initial adjustment parameters are collected, including the temperature value and temperature change rate at various points on the line. This data is compared with the pre-processed temperature change rate to determine whether the initial adjustment parameters can suppress the temperature change rate from exceeding a reasonable range. If the real-time temperature change rate exceeds the preset reasonable range (e.g., the actual rate is 2.8℃ / min, while the reasonable range is 1.5 to 2.5℃ / min), the initial adjustment parameters are modified using the heat penetration area as a weight to form iterative adjustment parameters. Iterative adjustment parameter = initial adjustment parameter × (1 + (real-time temperature change rate - upper limit of reasonable range) × heat penetration area × 0.02). If the initial adjustment parameter is 1.5 and the heat penetration area is 50cm², substituting the values ​​yields the iterative adjustment parameter = 1.5 × (1 + (2.8 - 2.5) × 50 × 0.02) = 1.95. The iterative adjustment parameter enhances the cooling effect, adjusting the temperature change rate back to the reasonable range.

[0149] The adaptability of the iterative adjustment parameters was verified by combining the additional thermal deformation loss value. During verification, the changing trend of the additional thermal deformation loss value under the action of the iterative adjustment parameters was calculated. Before the iterative adjustment parameters were applied, the initial value of the additional thermal deformation loss of the current power connection line was recorded. The initial value of the additional thermal deformation loss was a quantitative result calculated based on real-time thermal deformation characteristic data and historical thermal loss correlation coefficients. For example, under a certain load scenario, the initial value of the additional thermal deformation loss was 4.2 W / m.

[0150] Real-time thermal state data of the production line is continuously collected within a preset period during which the iterative adjustment parameters take effect. This includes the temperature distribution, deformation amplitude, and uniformity of each level. The additional thermal deformation loss value sequence within this period is calculated in real time using the thermal loss correlation coefficient. For example, loss values ​​of 3.8 W / m, 3.5 W / m, and 3.3 W / m are obtained in the 1st, 2nd, and 3rd minutes, respectively.

[0151] Compare these real-time loss values ​​with the initial values ​​to calculate the rate of decrease in loss value. Loss change rate = (initial loss value - current loss value) ÷ adjustment duration. Taking an initial value of 4.2 W / m and a loss value of 3.3 W / m at the 3rd minute as an example, substitute these values ​​into the formula to obtain the loss change rate. The rate of change of loss reflects the efficiency of the iterative adjustment parameters in suppressing the additional loss caused by thermal deformation; a higher rate indicates better parameter suitability.

[0152] Compare the trend of the loss value with the preset target threshold. If the loss value continues to decrease and the rate of decrease is stable... The above demonstrates that iterative parameter adjustment can effectively reduce additional losses due to thermal deformation and exhibits good adaptability; however, if the rate of decrease in the loss value is lower than... If the loss value fluctuates upwards, it indicates that the adjustment of the current iteration parameters is insufficient or excessive, and further correction is needed. For example, when the loss value is monitored to be 3.9 W / m in the 3rd minute, the calculated loss change rate is... If the target threshold is not reached, the iterative parameter is deemed to be insufficiently adaptable. The adjustment parameter is then corrected again with the heat penetration area as the weight until the rate of change of loss meets the requirements.

[0153] By combining the temperature change rate and heat penetration area of ​​the production line, the rationality of the loss change trend is verified. When the temperature change rate returns to a reasonable range and the heat penetration area does not expand, if the additional loss value due to thermal deformation decreases simultaneously, it further confirms the suitability of the iterative adjustment parameters. This multi-dimensional trend calculation and verification ensures that the iterative adjustment parameters truly adapt to the current heat loss state, providing a reliable parameter basis for subsequent closed-loop adjustment.

[0154] If the loss value continues to decrease and approaches the standard range, it indicates that the parameter has good adaptability, and it can be directly used as the adaptability adjustment parameter; if the loss value does not decrease as expected, it is iterated and corrected again until the parameter meets the adaptability requirements.

[0155] Based on adaptive adjustment parameters, the power cable undergoes closed-loop temperature regulation, continuously monitoring the cable's thermal status data and dynamically adjusting the parameters according to real-time feedback to ensure the cable temperature remains within a safe and stable range. When server load fluctuations cause an increase in the cable's thermal deformation and additional losses, the adjustment range is rapidly increased. Air-cooling or liquid-cooling modules are used to enhance heat dissipation in heat-sensitive areas, preventing cable deformation or accelerated aging due to overheating, thereby effectively improving the power cable's operational safety and lifespan.

[0156] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0157] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0158] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A power connection line AI adaptive temperature closed-loop regulation system, characterized in that, include: First acquisition module: Acquires the real-time load parameters of the current power connection line; The first processing module establishes a thermal adaptation prediction model based on historical load parameters and historical thermal deformation repair and adjustment data. It inputs real-time load parameters into the thermal adaptation prediction model to obtain the basic temperature adjustment value. It then performs heat conduction simulation based on the real-time load parameters to obtain simulated thermal deformation characteristic data. Let the base temperature adjustment value be J, the average fluctuation range of historical load parameters be K, the average effective range of historical thermal deformation repair adjustment data be L, and the rate of change of real-time load parameters relative to historical average load be M. Then the formula for calculating the base temperature adjustment value is J = L × (M × 1.2 + K × 0.8). Analysis module: Processes and analyzes historical data and simulated thermal deformation characteristic data to obtain the additional loss value of thermal deformation and the rate of change of preprocessed temperature; The second acquisition module: acquires the coupling influence area formed by the adjacent layout of the main test connection line to which the main test thermal deformation characteristic data belongs and the auxiliary test connection line to which the auxiliary test thermal deformation characteristic data belongs; The second processing module processes historical heat penetration area, historical line aging area, historical thermal deformation characteristic data, and simulated thermal deformation characteristic data to obtain the heat penetration area of ​​the coupled influence region. The third processing module: Based on the base temperature adjustment value, the pretreatment temperature change rate, the heat penetration area, and the additional loss due to thermal deformation, the actual temperature adjustment value is obtained, specifically including the following steps: Extract historical heat penetration-related loss values ​​from historical monitoring data, which show that the rate of temperature change is affected by the historical heat penetration area, resulting in a decrease in the heat dissipation efficiency of the production line. The influence coefficient of heat penetration loss is obtained based on the correlation trend characteristics between historical temperature change rate, historical heat penetration area and historical heat penetration loss value. The estimated value of heat penetration-related loss is obtained based on the heat penetration loss influence coefficient, the pretreatment temperature change rate, and the heat penetration area. The actual temperature adjustment value is obtained based on the additional loss value of thermal deformation, the estimated value of heat penetration-related loss, and the basic temperature adjustment value. Adjustment module: Performs closed-loop temperature adjustment of the power connection cable based on the actual temperature adjustment value and heat penetration area.

2. The AI ​​adaptive temperature closed-loop regulation system for power connection lines according to claim 1, characterized in that, The simulated thermal deformation characteristic data are obtained by performing heat conduction simulation based on real-time load parameters, specifically including the following steps: The base number of heat generation during the transmission process of the line is extracted based on real-time load parameters. The initial boundary conditions for heat conduction simulation are determined based on the base number of heat generation, the thermal conductivity of the power connection line material itself, and the thermal barrier performance of the outer insulation structure. The base number of heat generation is the amount of heat generated per unit length and per unit time when the real-time load parameters are applied. Based on the initial boundary conditions, a full-domain heat conduction path is constructed. Based on the full-domain heat conduction path, the heat conduction differences of each layer, such as the core, insulation layer, and protective sheath, are distinguished. After tracking the conduction rate and heat accumulation state of the heat generation base between each layer, hierarchical heat distribution data is formed. The hierarchical heat distribution data is processed to obtain the target deformation region where deformation occurs; The correlation between heat accumulation and linear deformation is quantified by combining the interaction of heat conduction between layers, and the deformation quantification results of the target deformation region are corrected after judging the constraint effect of deformation of adjacent layers. Based on the deformation variation results of the target deformation region, the deformation location, deformation amplitude, deformation uniformity, and deformation variation law with heat conduction time are extracted to form simulated thermal deformation characteristic data.

3. The AI ​​adaptive temperature closed-loop regulation system for power connection lines according to claim 2, characterized in that, The process of processing hierarchical heat distribution data to obtain the target deformation region where deformation occurs includes the following steps: The adaptation relationship between the thermal expansion coefficient of each level and the heat accumulation state is determined based on the hierarchical heat distribution data; Based on the adaptation relationship, determine the trend of linear shape change corresponding to different heat accumulation areas; The target deformation area that has undergone deformation is selected based on the trend of line shape change.

4. The AI ​​adaptive temperature closed-loop regulation system for power connection lines according to claim 1, characterized in that, The historical data and simulated thermal deformation characteristic data are processed and analyzed to obtain the additional loss value of thermal deformation and the rate of change of preprocessing temperature. The specific steps include: The historical condition data includes historical thermal deformation characteristic data and historical heat loss increment values; The additional heat deformation loss value is obtained by processing historical thermal deformation characteristic data, historical heat loss increment value and simulated thermal deformation characteristic data. Based on the correlation trend between the historical temperature change rate of the current power connection line and the historical thermal deformation characteristic data, the preprocessed temperature change rate is obtained.

5. The AI ​​adaptive temperature closed-loop regulation system for power connection lines according to claim 4, characterized in that, The additional heat loss value is obtained by processing historical thermal deformation characteristic data, historical heat loss increment values, and simulated thermal deformation characteristic data. This process includes the following steps: The heat loss correlation coefficient is obtained based on the correlation trend characteristics between historical thermal deformation characteristic data and historical heat loss increment values. The additional thermal deformation loss value of the current power connection line is obtained based on the thermal loss correlation coefficient and simulated thermal deformation characteristic data.

6. The AI ​​adaptive temperature closed-loop regulation system for power connection lines according to claim 4, characterized in that, Based on the correlation trend between the historical temperature change rate of the current power connection line and the historical thermal deformation characteristic data, the preprocessed temperature change rate is obtained, which specifically includes the following steps: Extract the historical temperature change rate affected by historical thermal deformation characteristic data, and obtain the temperature change rate correlation coefficient based on the correlation trend characteristics between the historical temperature change rate and the historical thermal deformation characteristic data. Select the main measured thermal deformation characteristic data and the auxiliary measured thermal deformation characteristic data from the simulated thermal deformation characteristic data; The temperature change rate 1 of the main test connection line is obtained based on the thermal deformation characteristic data of the main test and the correlation coefficient of the temperature change rate; the temperature change rate 2 of the auxiliary test connection line is obtained based on the thermal deformation characteristic data of the auxiliary test and the correlation coefficient of the temperature change rate; the preprocessing temperature change rate is obtained based on the temperature change rate 1 and the temperature change rate 2.

7. The AI ​​adaptive temperature closed-loop regulation system for power connection lines according to claim 6, characterized in that, The coupling influence area formed by the adjacent layout of the main test connection line to which the main test thermal deformation characteristic data belongs and the auxiliary test connection line to which the auxiliary test thermal deformation characteristic data belongs includes the following steps: Acquire the thermal deformation characteristic data of the main test connection line and the auxiliary test connection line, and acquire the actual layout trajectory, line cross-sectional specifications and actual spacing data of the main test connection line and the auxiliary test connection line. Based on the actual deployment trajectory, adjacent deployment segments are determined, and the line extension direction and relative positional relationship of adjacent deployment segments are extracted. Based on the extension direction and relative position of adjacent deployment sections, the potential influence area is determined. Combined with the cross-sectional specifications of the line, the line radiation range corresponding to each potential influence area is determined. Based on the line radiation range, the overlapping area of ​​the radiation range of the main test connecting line and the radiation range of the auxiliary test connecting line is determined as the initial coupling area. Extract the heat conduction path of the initial coupling region, and combine the main measured thermal deformation characteristic data and the auxiliary measured thermal deformation characteristic data to determine whether there is a bidirectional heat transfer effect in each heat conduction path. The coverage area of ​​the heat conduction path with bidirectional heat transfer effect is determined as the target influence area. Based on the cross-sectional specifications of the line and the actual spacing data, the boundary range of the target influence area is corrected to form the coupling influence area caused by the adjacent layout of the main test connection line and the auxiliary test connection line.

8. The AI ​​adaptive temperature closed-loop regulation system for power connection lines according to claim 1, characterized in that, The heat penetration area of ​​the coupled influence region is obtained by processing historical heat penetration area, historical aging region area, historical thermal deformation characteristic data, and simulated thermal deformation characteristic data. This process includes the following steps: The area of ​​thermal stress distribution to be measured is obtained by statistically analyzing the coverage area of ​​the concentrated thermal stress region. Based on the area of ​​thermal stress distribution to be measured, the area of ​​historical aging region of the line body and the historical heat penetration area of ​​the historical aging region of the line body affected by thermal deformation are extracted from historical monitoring data. Based on the correlation and influence trend characteristics of historical heat penetration area, historical linear aging area and historical thermal deformation characteristics data, the area penetration influence factor is obtained. The thermal penetration area of ​​the coupled influence region is obtained based on the measured thermal stress distribution area, the area penetration influence factor, and the simulated thermal deformation characteristic data.

9. A power connection line AI adaptive temperature closed-loop regulation system according to claim 1, characterized in that, The power connection cable undergoes closed-loop temperature regulation based on the actual temperature adjustment value and heat penetration area, specifically including the following steps: The additional heat deformation loss value is retrieved based on the actual temperature adjustment value. When the additional heat deformation loss value is greater than or equal to the standard range, the adjustment range of the adjustment parameter is increased in the cooling direction pointed to by the actual temperature adjustment value. When the additional heat deformation loss value is less than the standard range, the adjustment range of the adjustment parameter is decreased in the cooling direction pointed to by the actual temperature adjustment value, thus forming an initial adjustment trend of the adjustment parameter. Based on the heat penetration area, the heat-sensitive section of the power connection line is defined, and the adjustment trend of the initial adjustment parameters is correspondingly allocated to the heat-sensitive section so that the adjustment response speed of the heat-sensitive section matches the temperature change rate, thus obtaining the prototype of the adjustment parameters. Real-time thermal state data of the power connection line is collected after the initial adjustment parameter is applied. The real-time thermal state data is compared with the pre-processed temperature change rate to determine whether the initial adjustment parameter can suppress the temperature change rate from exceeding the reasonable range. If the temperature change rate deviates from the reasonable range, the initial adjustment parameter is corrected with the heat penetration area as the weight to form iterative adjustment parameters. The adaptability of the iterative adjustment parameters is verified by combining the additional loss value of thermal deformation, and the adaptability adjustment parameters are obtained. Temperature closed-loop regulation of the power connection cable is performed based on adaptability adjustment parameters.

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