Oil leakage analysis method, system, medium and product for oil-filled cable terminal

Abstract

A method, system, medium and product for analyzing oil leakage at an oil-filled cable terminal relate to the field of electrical digital data processing. In implementing this application, the detection system collects the temperature values ​​of each sensor based on the sensor array arranged longitudinally on the inner side of the closed structure of the oil-filled cable terminal, calculates the temperature difference sequence, and extracts the characteristic parameters of the temperature field in the closed structure. The detection system corrects the finite element simulation results in combination with the current ambient temperature and the current load current, and obtains the corresponding relationship between the oil leakage temperature under actual working conditions, thereby accurately reflecting the oil leakage situation under actual working conditions. This oil leakage analysis method based on the corresponding relationship between the temperature field characteristic parameters and the oil leakage temperature under actual working conditions avoids the limitations of traditional detection methods that rely solely on oil level gauges and float switches for detection, improves the perception ability of slow leakage and the accuracy of quantitative analysis, can timely and accurately discover oil leakage hazards, prevent accidents, and improve the accuracy and reliability of oil leakage detection.

Description

Technical Field

[0001] The present application relates to the field of electronic digital data processing, and in particular to a method, system, medium and product for analyzing oil leakage at an oil-filled cable terminal. Background Art

[0002] Oil-filled cable terminals are crucial connection devices in power systems, and their operational reliability is directly linked to the stable power supply of the entire system. The insulating oil within these terminals is crucial for their proper function. An oil leak can severely impact their insulation performance and potentially even cause a power system failure.

[0003] At present, the oil leakage monitoring method of oil-filled cable terminals mainly obtains internal pressure changes through pressure monitoring devices, thereby indirectly judging whether there is an oil leakage fault. When the internal pressure value is lower than the preset pressure threshold, an alarm signal is issued.

[0004] This traditional detection method suffers from low accuracy. Since oil leaks from oil-filled cable terminals are often slow, oil level changes are very small. Oil level gauges and float switches struggle to detect these subtle changes, making it difficult for oil level gauges and float switches to detect them in a timely manner. Consequently, the accuracy and timeliness of leak detection results cannot be guaranteed. Summary of the Invention

[0005] The present application provides an oil leakage analysis method, system, medium and product for oil-filled cable terminals, which are used to improve the accuracy of oil leakage detection for oil-filled cable terminals.

[0006] In the first aspect, the present application provides an oil leakage analysis method for an oil-filled cable terminal, which is applied to a detection system. The method includes: collecting the temperature value of each sensor through a sensor array arranged longitudinally on the inner side of the closed structure of the oil-filled cable terminal, and calculating the temperature difference between adjacent sensors to obtain a temperature difference sequence, the sensor array includes a first sensor to an Nth sensor arranged in sequence from top to bottom; determining the temperature field characteristic parameters according to the temperature difference sequence, the temperature field characteristic parameters including the maximum temperature difference value, the maximum temperature difference position, the temperature difference average value, the rate of change of adjacent temperature differences and the temperature difference standard deviation in the temperature difference sequence; calculating the ambient temperature correction coefficient and the load current correction coefficient according to the current ambient temperature, the current load current, the preset reference ambient temperature and the preset reference load current to correct the finite element simulation results to obtain the actual working condition oil leakage temperature correspondence, the finite element simulation results refer to different temperature field distributions corresponding to different oil leakage degrees determined by the finite element simulation method under the preset reference ambient temperature and the preset reference load current; determining the current oil leakage degree of the oil-filled cable terminal based on the temperature field characteristic parameters and the actual working condition oil leakage temperature correspondence.

[0007] By adopting the above technical solution, the detection system collects the temperature values ​​of each sensor based on the sensor array arranged longitudinally on the inner side of the closed structure of the oil-filled cable terminal, calculates the temperature difference sequence, and extracts the characteristic parameters of the temperature field in the closed structure. The detection system corrects the finite element simulation results based on the current ambient temperature and the current load current, and obtains the corresponding relationship between the oil leakage temperature under actual working conditions, thereby accurately reflecting the oil leakage situation under actual working conditions. This oil leakage analysis method based on the corresponding relationship between the temperature field characteristic parameters and the oil leakage temperature under actual working conditions avoids the limitations of traditional detection methods that rely solely on oil level gauges and float switches for detection, improves the perception ability of slow leakage and the accuracy of quantitative analysis, can promptly and accurately detect oil leakage hazards, prevent accidents, and improve the accuracy and reliability of oil leakage detection.

[0008] In combination with some embodiments of the first aspect, in some embodiments, before calculating the ambient temperature correction coefficient and the load current correction coefficient based on the current ambient temperature, the current load current, the preset reference ambient temperature, and the preset reference load current to correct the finite element simulation results to obtain the corresponding relationship of the oil leakage temperature under actual working conditions, the method further includes: establishing a three-dimensional model of the oil-filled cable terminal, the three-dimensional model of the oil-filled cable terminal including a conductor and a sealed structure, the sealed structure including an insulating oil chamber and an air domain located above the insulating oil chamber, and a sensor array being longitudinally arranged on the inner side of the sealed structure; setting a heat source boundary condition on the surface of the conductor, setting a convection heat transfer boundary condition on the outer surface of the sealed structure, and setting a radiation heat transfer boundary condition on the outer surface of the sealed structure to obtain the oil-filled cable terminal model, the heat source boundary condition being determined by the preset reference load current, and the convection heat transfer boundary condition and the radiation heat transfer boundary condition being determined by the preset reference ambient temperature; performing finite element simulation on the oil-filled cable terminal at different air domain heights to obtain different temperature field distributions corresponding to different oil leakage degrees under the preset reference ambient temperature and the preset reference load current, the air domain height being used to characterize the oil leakage degree, and the higher the air domain height, the more severe the oil leakage degree.

[0009] By employing the above technical solution, the detection system established a three-dimensional model of the oil-filled cable terminal, including the conductor and the enclosed structure. Heat source boundary conditions, convection heat transfer boundary conditions, and radiation heat transfer boundary conditions were set within the 3D model to more realistically simulate the temperature field distribution of the oil-filled cable terminal. The detection system used air domain height to characterize the extent of oil leakage. Finite element simulations were used to obtain different temperature field distributions for different oil leakage levels, establishing a corresponding relationship between oil leakage level and temperature field characteristics. This physical model-based simulation and analysis method provides a reliable theoretical basis for oil leak detection and improves the scientific nature of leak level determination.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the heat source boundary condition is: ; Among them, Q is the heat source of the oil-filled cable terminal, P is the heating power of the conductor, is the lateral area of ​​the conductor, I is the preset reference load current flowing through the conductor, is the cross-sectional area of ​​the conductor, ρ is the resistivity of the conductor, and l is the length of the conductor. The convection heat transfer boundary condition is: ; where λ is the thermal conductivity of the insulating material in the closed structure, is the temperature gradient, is the surface area of ​​the oil-filled cable terminal, h is the heat transfer coefficient of the outer surface of the oil-filled cable terminal in contact with the air, is the surface temperature of the oil-filled cable terminal, is the preset reference ambient temperature; the radiation heat transfer boundary conditions are: Where, is the Stefan-Boltzmann constant, is the surface emissivity.

[0011] By employing this technical solution, the detection system specifies detailed mathematical expressions for heat source boundary conditions, convection heat transfer boundary conditions, and radiation heat transfer boundary conditions. These conditions account for multiple physical parameters, including the heat generation power of the conductor, the thermal conductivity of the insulating material within the enclosed structure, and the heat transfer coefficient of the outer surface of the oil-filled cable terminal where it contacts the air. The precise description of these boundary conditions allows finite element simulations to more closely resemble actual operating conditions, improving the accuracy of temperature field distribution calculations.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the ambient temperature correction coefficient and the load current correction coefficient are calculated based on the current ambient temperature, the current load current, the preset reference ambient temperature and the preset reference load current to correct the finite element simulation results and obtain the actual working condition oil leakage temperature correspondence, specifically including: determining the ratio of the current ambient temperature to the preset reference ambient temperature as the ambient temperature correction coefficient, and determining the square ratio of the current load current to the preset reference load current as the load current correction coefficient; multiplying the temperature field distribution in the finite element simulation results by the product of the ambient temperature correction coefficient and the load current correction coefficient to obtain the corrected temperature field distribution; establishing a correspondence between different oil leakage degrees and different corrected temperature field distributions to obtain the actual working condition oil leakage temperature correspondence.

[0013] By adopting the above technical solution, the detection system corrects the finite element simulation results according to the ambient temperature correction coefficient and the load current correction coefficient, taking into account the influence of ambient temperature and load current on the temperature field distribution. It can convert the simulation results under standard working conditions into the temperature distribution characteristics under actual working conditions, thereby establishing a correspondence between different oil leakage degrees and different corrected temperature field distributions, so as to accurately evaluate the oil leakage status under actual operating conditions and improve the adaptability and accuracy of oil leakage detection.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of determining the current oil leakage degree of the oil-filled cable terminal based on the correspondence between the temperature field characteristic parameters and the actual operating oil leakage temperature, the method also includes: periodically obtaining multiple sets of temperature field characteristic parameters within a preset time period, and determining the ambient temperature, load current and oil leakage degree corresponding to each of the multiple sets of temperature field characteristic parameters to draw an oil leakage development trend curve; determining the slope of the oil leakage development trend curve as the oil leakage rate to judge the stability of the oil leakage development trend; when the oil leakage development trend is unstable, analyzing the correlation between the temperature field characteristic parameters and the ambient temperature and load current; if the correlation exceeds the preset correlation threshold, adjusting the ambient temperature and load current to the preset standard range; if the correlation is less than or equal to the preset correlation threshold, triggering an emergency alarm.

[0015] By employing this technical solution, the detection system plots an oil leakage trend curve and determines the stability of the leak trend based on the leak rate. If the leak trend is unstable, the detection system analyzes the correlation between the temperature field characteristic parameters and the ambient temperature and load current to effectively identify anomalies. When the correlation exceeds a preset correlation threshold, the detection system adjusts the ambient temperature and load current to within a preset standard range to eliminate the influence of external factors. When the correlation is less than or equal to the preset correlation threshold, it indicates an internal anomaly at the oil-filled cable terminal, triggering a timely emergency alarm. This multi-level analysis and processing mechanism prevents false alarms while promptly identifying real oil leak risks.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of determining the slope of the oil leakage development trend curve as the oil leakage rate to judge the stability of the oil leakage development trend, the method also includes: when the oil leakage development trend is stable, calculating the remaining time to reach the preset oil leakage level threshold based on the current oil leakage level and the oil leakage rate; if the remaining time is less than the preset time threshold, generating a maintenance instruction, and the maintenance instruction includes a recommended maintenance time window.

[0017] By employing this technical solution, if the oil leak trend remains stable, the detection system calculates the remaining time until the leak reaches the preset threshold based on the current leak level and rate. Based on this remaining time, it generates a maintenance instruction with a recommended maintenance window. This predictive maintenance solution helps operators plan maintenance schedules, avoiding safety hazards caused by operating faulty equipment and preventing resource waste caused by excessive maintenance.

[0018] In combination with some embodiments of the first aspect, in some embodiments, when the oil leakage development trend is unstable, the correlation between the temperature field characteristic parameters and the ambient temperature and load current is analyzed, specifically including: arranging the temperature field characteristic parameters, ambient temperature and load current in chronological order to obtain a temperature field characteristic parameter sequence, an ambient temperature sequence and a load current sequence; calculating the Pearson correlation coefficient of the temperature field characteristic parameter sequence and the ambient temperature sequence to obtain the ambient temperature correlation; calculating the Pearson correlation coefficient of the temperature field characteristic parameter sequence and the load current sequence to obtain the load current correlation; and determining the correlation between the temperature field characteristic parameters and the ambient temperature and load current based on the ambient temperature correlation and the load current correlation.

[0019] By employing this technical solution, the detection system uses the Pearson correlation coefficient to analyze the correlation between temperature field characteristic parameters and ambient temperature and load current, providing an objective and quantitative assessment method. Calculating the correlation between temperature field characteristic parameters, ambient temperature, and load current accurately identifies whether temperature field changes are caused by external environmental factors or actual oil leaks. This improves the reliability of leak detection, reduces the rate of false positives, and provides a scientific basis for subsequent appropriate treatment measures.

[0020] In a second aspect, an embodiment of the present application provides a detection system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the detection system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when the computer program product is run on a detection system, enables the detection system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on a detection system, the detection system executes the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the detection system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can be referenced to the beneficial effects of the corresponding methods and will not be repeated here.

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

[0025] 1. By adopting the above-mentioned technical solution, the detection system collects the temperature values ​​of each sensor based on the sensor array arranged longitudinally on the inner side of the closed structure of the oil-filled cable terminal, calculates the temperature difference sequence, and extracts the characteristic parameters of the temperature field in the closed structure. The detection system corrects the finite element simulation results based on the current ambient temperature and the current load current to obtain the corresponding relationship between the oil leakage temperature under actual working conditions, thereby accurately reflecting the oil leakage situation under actual working conditions. This oil leakage analysis method based on the corresponding relationship between the characteristic parameters of the temperature field and the oil leakage temperature under actual working conditions avoids the limitations of traditional detection methods that rely solely on oil level gauges and float switches for detection, improves the perception ability of slow leakage and the accuracy of quantitative analysis, can promptly and accurately detect oil leakage hazards, prevent accidents, and improve the accuracy and reliability of oil leakage detection.

[0026] 2. By employing the above technical solution, the detection system established a three-dimensional model of the oil-filled cable terminal, including the conductor and the enclosed structure. Heat source boundary conditions, convection heat transfer boundary conditions, and radiation heat transfer boundary conditions were set within the 3D model to more realistically simulate the temperature field distribution of the oil-filled cable terminal. The detection system used air domain height to characterize the extent of oil leakage. Finite element simulations were used to obtain different temperature field distributions for different oil leakage levels, establishing a corresponding relationship between oil leakage level and temperature field characteristics. This physical model-based simulation and analysis method provides a reliable theoretical basis for oil leak detection and improves the scientific nature of leak level determination.

[0027] 3. By adopting the above technical solution, the detection system corrects the finite element simulation results according to the ambient temperature correction coefficient and the load current correction coefficient, taking into account the influence of ambient temperature and load current on the temperature field distribution. It can convert the simulation results under standard working conditions into the temperature distribution characteristics under actual working conditions, thereby establishing a correspondence between different oil leakage degrees and different corrected temperature field distributions, so as to accurately evaluate the oil leakage status under actual operating conditions and improve the adaptability and accuracy of oil leakage detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of the oil leakage analysis method for oil-filled cable terminals according to an embodiment of the present application;

[0029] Figure 2 This is another flow chart of the oil leakage analysis method for oil-filled cable terminals according to an embodiment of the present application;

[0030] Figure 3 It is a schematic diagram of the structure of a physical device of the detection system in the embodiment of the present application. DETAILED DESCRIPTION

[0031] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular expressions "a", "an", "above", "the", and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations of one or more of the listed items.

[0032] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0033] The following is a description of the process of the method provided by this implementation. Figure 1 , is a flow chart of the oil leakage analysis method for oil-filled cable terminals in an embodiment of the present application.

[0034] S101, using a sensor array longitudinally disposed inside a sealed structure of an oil-filled cable terminal, collecting temperature values ​​from each sensor and calculating temperature differences between adjacent sensors to obtain a temperature difference sequence, wherein the sensor array includes a first sensor to an Nth sensor disposed sequentially from top to bottom;

[0035] Among them, the oil-filled cable terminal refers to the device used to connect and terminate the oil-filled cable; the enclosed structure refers to the outer shell used to seal and protect the internal components of the oil-filled cable; the sensor array refers to a collection of multiple temperature sensors arranged in the longitudinal direction; the temperature value refers to the real-time temperature data detected by each sensor; the temperature difference represents the temperature change between adjacent sensors; the temperature difference sequence refers to a set of temperature difference data arranged in order of sensor position; the first sensor to the Nth sensor represent N temperature sensors arranged in sequence from top to bottom, where N is a positive integer greater than 1.

[0036] Specifically, the detection system collects real-time temperature data from a sensor array pre-installed inside the sealed structure of the oil-filled cable terminal. The sensors in the sensor array are numbered and evenly distributed from top to bottom, ensuring that each sensor accurately captures the temperature at its location. After acquiring the temperature values ​​of all sensors, the detection system calculates the temperature difference between each pair of adjacent sensors, following the spatial order of the sensors. For example, the temperature difference between the second sensor and the first, the temperature difference between the third sensor and the second, and so on, up to the temperature difference between the Nth sensor and the N-1th sensor, thus forming a complete temperature difference sequence.

[0037] Assume that five temperature sensors (N=5) are evenly installed longitudinally inside the sealed structure of an oil-filled cable terminal. They are numbered 1 to 5 from top to bottom. At a certain moment, the temperature values ​​collected by these five sensors are as follows:

[0038] Sensor No. 1 (top): 45°C;

[0039] Sensor No. 2: 47°C;

[0040] Sensor No. 3: 46°C;

[0041] Sensor No. 4: 48°C;

[0042] Sensor No. 5 (bottom): 47°C;

[0043] Then the calculated temperature difference is:

[0044] The difference between No. 2 and No. 1: 47℃-45℃=+2℃;

[0045] The difference between No. 3 and No. 2: 46℃-47℃=-1℃;

[0046] The difference between No. 4 and No. 3: 48℃-46℃=+2℃;

[0047] The difference between No. 5 and No. 4: 47℃-48℃=-1℃;

[0048] This results in a temperature difference sequence: [+2, -1, +2, -1].

[0049] S102, determining temperature field characteristic parameters according to the temperature difference sequence, the temperature field characteristic parameters including the maximum temperature difference value, the maximum temperature difference position, the average temperature difference value, the rate of change of adjacent temperature differences, and the standard deviation of the temperature difference in the temperature difference sequence;

[0050] Among them, temperature field characteristic parameters refer to a set of key indicators used to describe the distribution characteristics of the temperature field; the maximum temperature difference refers to the maximum value in the temperature difference sequence; the maximum temperature difference position refers to the position where the maximum temperature difference occurs; the average temperature difference refers to the arithmetic mean of the temperature difference sequence; the rate of change of adjacent temperature differences refers to the rate of change between adjacent values ​​in the temperature difference sequence; the standard deviation of temperature difference refers to a statistic used to characterize the degree of dispersion of the temperature difference sequence.

[0051] Specifically, the detection system performs a multi-dimensional analysis of the temperature difference sequence, extracting five key characteristic parameters: first, identifying the maximum value in the temperature difference sequence and its corresponding sensor location; then calculating the arithmetic mean of the temperature difference sequence; then calculating the rate of change between each pair of adjacent temperature differences, i.e., the second-order difference of the temperature difference; and finally, calculating the standard deviation of the temperature difference sequence to characterize the uniformity of the temperature distribution. Together, these characteristic parameters form a comprehensive temperature field characteristic parameter that reflects the distribution characteristics of the temperature field and provides basic data support for subsequent oil leak analysis.

[0052] Following the temperature difference sequence [+2, -1, +2, -1] in step S101, these characteristic parameters are calculated:

[0053] (1) Maximum temperature difference: +2°C;

[0054] (2) Maximum temperature difference position (+2°C occurs at two locations):

[0055] Between sensors No. 2 and No. 1 (1st position);

[0056] Between sensors 4 and 3 (3rd position);

[0057] (3) Average temperature difference: (+2 + (-1) + 2 + (-1)) ÷ 4 = 0.5°C;

[0058] (4) Rate of change of adjacent temperature differences (second-order difference):

[0059] Group 1: (-1)-(+2)=-3;

[0060] Group 2: (+2)-(-1)=+3;

[0061] Group 3: (-1)-(+2)=-3;

[0062] Get the change rate sequence: [-3, +3, -3];

[0063] (5) Standard deviation of temperature difference: √[(2-0.5)²+(-1-0.5)²+(2-0.5)²+(-1-0.5)²] / 4√(9 / 4)≈1.5℃;

[0064] Temperature field characteristic parameters:

[0065] Maximum temperature difference: 2°C;

[0066] Maximum temperature difference position: 1st position and 3rd position;

[0067] Average temperature difference: 0.5℃;

[0068] The rate of change sequence of adjacent temperature differences: [-3, +3, -3];

[0069] Standard deviation of temperature difference: 1.5℃.

[0070] S103. Calculating an ambient temperature correction factor and a load current correction factor based on the current ambient temperature, the current load current, a preset reference ambient temperature, and a preset reference load current to correct the finite element simulation results to obtain a corresponding relationship between the oil leakage temperature under actual operating conditions. The finite element simulation results refer to different temperature field distributions corresponding to different oil leakage levels determined using the finite element simulation method under the preset reference ambient temperature and the preset reference load current.

[0071] Among them, the current ambient temperature refers to the real-time temperature of the environment in which the oil-filled cable terminal is located; the current load current refers to the actual current currently carried by the oil-filled cable terminal; the preset reference ambient temperature refers to the standard ambient temperature set during finite element simulation; the preset reference load current refers to the standard load current set during finite element simulation; the ambient temperature correction coefficient refers to the coefficient used to correct the influence of ambient temperature; the load current correction coefficient refers to the coefficient used to correct the influence of load current; the finite element simulation result refers to the temperature field distribution data obtained by finite element simulation; the temperature field distribution refers to the distribution of temperature at each point in space; the actual operating condition oil leakage temperature correspondence refers to the mapping relationship between the degree of oil leakage and the temperature field distribution under actual operating conditions.

[0072] Specifically, the detection system obtains the current ambient temperature and current load current and compares them with a preset baseline ambient temperature and preset baseline load current. When calculating the ambient temperature correction coefficient, the current ambient temperature is divided by the preset baseline ambient temperature; when calculating the load current correction coefficient, the square of the current load current is divided by the square of the preset baseline load current. The detection system then multiplies the product of these two correction coefficients with the data previously obtained using the finite element method to determine the correspondence between the degree of oil leakage and the temperature field distribution under standard operating conditions. This yields data reflecting the correspondence between the degree of oil leakage and the temperature field distribution under actual operating conditions, namely, the actual operating condition oil leakage temperature correspondence.

[0073] Optionally, under normal circumstances, the ambient temperature correction coefficient and the load current correction coefficient are calculated based on the current ambient temperature, the current load current, the preset reference ambient temperature and the preset reference load current to correct the finite element simulation results. The actual operating oil leakage temperature correspondence can be obtained in the following way, which is not limited here: the ratio of the current ambient temperature to the preset reference ambient temperature is determined as the ambient temperature correction coefficient, and the square ratio of the current load current to the preset reference load current is determined as the load current correction coefficient; the temperature field distribution in the finite element simulation results is multiplied by the product of the ambient temperature correction coefficient and the load current correction coefficient to obtain the corrected temperature field distribution; the correspondence between different oil leakage degrees and different corrected temperature field distributions is established to obtain the actual operating oil leakage temperature correspondence.

[0074] Assume the following initial conditions:

[0075] Current ambient temperature: 25°C;

[0076] Preset reference ambient temperature: 20°C;

[0077] Current load current: 800A;

[0078] Preset reference load current: 500A;

[0079] Calculate the correction factor:

[0080] Ambient temperature correction factor = 25°C ÷ 20°C = 1.25;

[0081] Load current correction factor = (800A)² ÷ (500A)² = 2.56;

[0082] Assume that the corresponding relationship between the oil leakage degree and the temperature field distribution under standard working conditions in finite element simulation is as follows:

[0083] Temperature distribution when there is no oil leakage: [40℃, 42℃, 41℃, 43℃, 42℃];

[0084] Temperature distribution during minor oil leakage: [42°C, 45°C, 43°C, 46°C, 44°C];

[0085] Temperature distribution during severe oil leakage: [45°C, 49°C, 46°C, 50°C, 47°C];

[0086] Calculate the corrected temperature field distribution under actual working conditions:

[0087] Total product of correction factors = 1.25 × 2.56 = 3.2;

[0088] Corrected temperature distribution when there is no oil leakage: [40×3.2, 42×3.2, 41×3.2, 43×3.2, 42×3.2] = [128℃, 134.4℃, 131.2℃, 137.6℃, 134.4℃];

[0089] Corrected temperature distribution for a slight oil leak: [42×3.2, 45×3.2, 43×3.2, 46×3.2, 44×3.2] = [134.4°C, 144°C, 137.6°C, 147.2°C, 140.8°C];

[0090] Corrected temperature distribution during severe oil leakage: [45×3.2, 49×3.2, 46×3.2, 50×3.2, 47×3.2] = [144°C, 156.8°C, 147.2°C, 160°C, 150.4°C];

[0091] In this way, the corresponding relationship data between the oil leakage degree and the temperature field distribution under actual working conditions is obtained:

[0092] No oil leakage: [128℃, 134.4℃, 131.2℃, 137.6℃, 134.4℃];

[0093] Minor oil leakage: [134.4℃, 144℃, 137.6℃, 147.2℃, 140.8℃];

[0094] Severe oil leakage: [144℃, 156.8℃, 147.2℃, 160℃, 150.4℃].

[0095] S104: Determine the current oil leakage degree of the oil-filled cable terminal based on the corresponding relationship between the temperature field characteristic parameters and the actual oil leakage temperature under working conditions.

[0096] Among them, the actual operating condition oil leakage temperature correspondence refers to the mapping relationship between the oil leakage degree and the temperature field characteristics after correction by ambient temperature and load current; the current oil leakage degree indicates the current oil leakage status of the oil-filled cable terminal, which can be divided into multiple levels such as no oil leakage, slight oil leakage, moderate oil leakage and severe oil leakage.

[0097] Specifically, the detection system matches the currently collected temperature field characteristic parameters with the actual operating oil leakage temperature correspondence table. First, the degree of match between the temperature field characteristic parameters and the characteristic parameters at each leakage level in the actual operating oil leakage temperature correspondence table is calculated, using Euclidean distance or other similarity metrics. Then, based on the principle of maximum match, the current leakage level is determined. If the match falls below a preset match threshold, the detection system marks the leakage level as "pending" for further verification.

[0098] By adopting the above technical solution, the detection system collects the temperature values ​​of each sensor based on the sensor array arranged longitudinally on the inner side of the closed structure of the oil-filled cable terminal, calculates the temperature difference sequence, and extracts the characteristic parameters of the temperature field in the closed structure. The detection system corrects the finite element simulation results based on the current ambient temperature and the current load current, and obtains the corresponding relationship between the oil leakage temperature under actual working conditions, thereby accurately reflecting the oil leakage situation under actual working conditions. This oil leakage analysis method based on the corresponding relationship between the temperature field characteristic parameters and the oil leakage temperature under actual working conditions avoids the limitations of traditional detection methods that rely solely on oil level gauges and float switches for detection, improves the perception ability of slow leakage and the accuracy of quantitative analysis, can promptly and accurately detect oil leakage hazards, prevent accidents, and improve the accuracy and reliability of oil leakage detection.

[0099] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the oil leakage analysis method for oil-filled cable terminals in an embodiment of the present application.

[0100] S201. Collect the temperature value of each sensor through a sensor array longitudinally arranged inside the sealed structure of the oil-filled cable terminal, and calculate the temperature difference between adjacent sensors to obtain a temperature difference sequence. The sensor array includes the first sensor to the Nth sensor arranged in sequence from top to bottom.

[0101] For details, please refer to step S101, which will not be described in detail here.

[0102] S202 , determining temperature field characteristic parameters according to the temperature difference sequence, the temperature field characteristic parameters including the maximum temperature difference value, the maximum temperature difference position, the average temperature difference value, the rate of change of adjacent temperature differences, and the standard deviation of the temperature difference in the temperature difference sequence.

[0103] For details, please refer to step S102, which will not be described again here.

[0104] S203. Establish a three-dimensional model of an oil-filled cable terminal. The three-dimensional model of the oil-filled cable terminal includes a conductor and a closed structure. The closed structure includes an insulating oil chamber and an air space above the insulating oil chamber. A sensor array is longitudinally arranged inside the closed structure.

[0105] Among them, the three-dimensional model of the oil-filled cable terminal refers to the three-dimensional digital representation used for finite element analysis; the conductor refers to the metal conductor used to transmit current; the enclosed structure refers to the shell system used to protect and seal internal components; the insulating oil chamber refers to the sealed space used to contain insulating oil; and the air domain refers to the gas space above the insulating oil chamber.

[0106] Specifically, the detection system uses computer-aided design (CAD) software to construct a three-dimensional model of the conductor, insulating oil chamber, and air domain based on the actual structural dimensions and material parameters of the oil-filled cable terminal. Multiple temperature sensor nodes are evenly spaced longitudinally inside the insulating oil chamber and air domain. The location and number of these temperature sensor nodes match the actual installed sensor array. The modeling process pays special attention to the interface between the insulating oil chamber and the air domain to ensure that the position of the oil-air interface changes accurately under different oil leakage levels.

[0107] S204. Set heat source boundary conditions on the conductor surface, set convection heat transfer boundary conditions on the outer surface of the sealing structure, and set radiation heat transfer boundary conditions on the outer surface of the sealing structure to obtain an oil-filled cable terminal model. The heat source boundary conditions are determined by a preset reference load current, and the convection heat transfer boundary conditions and the radiation heat transfer boundary conditions are determined by a preset reference ambient temperature.

[0108] Among them, the heat source boundary condition refers to the mathematical expression that describes the heat generation characteristics of the conductor; the convection heat transfer boundary condition refers to the heat exchange characteristics between the surface of the closed structure and the surrounding air; and the radiation heat transfer boundary condition refers to the thermal radiation characteristics of the surface of the closed structure.

[0109] Specifically, after completing the 3D model, the detection system needs to set boundary conditions for thermal field analysis. First, a heat source boundary condition is applied to the conductor surface. The heat source magnitude is determined by the product of the square of the preset baseline load current and the conductor resistance. Then, convection and radiation heat transfer boundary conditions are simultaneously set on the outer surface of the enclosed structure. The parameters of these two heat transfer modes depend on the preset baseline ambient temperature. The convection heat transfer coefficient is determined based on the specific conditions of natural convection and forced convection, while radiation heat transfer requires consideration of the material's emissivity. By setting these boundary conditions, a complete thermal field analysis model for the oil-filled cable terminal is formed.

[0110] Optional, in general, the heat source boundary condition is: ; Among them, Q is the heat source of the oil-filled cable terminal, P is the heating power of the conductor, is the lateral area of ​​the conductor, I is the preset reference load current flowing through the conductor, is the cross-sectional area of ​​the conductor, ρ is the resistivity of the conductor, and l is the length of the conductor. The convection heat transfer boundary condition is: ; where λ is the thermal conductivity of the insulating material in the closed structure, is the temperature gradient, is the surface area of ​​the oil-filled cable terminal, h is the heat transfer coefficient of the outer surface of the oil-filled cable terminal in contact with the air, is the surface temperature of the oil-filled cable terminal, is the preset reference ambient temperature; the radiation heat transfer boundary conditions are: Where, is the Stefan-Boltzmann constant, is the surface emissivity.

[0111] The heat source of an oil-filled cable terminal is primarily generated by the cable core. During operation, the temperature of the cable core can reach over 70°C. Heat dissipation occurs through multiple channels, including heat conduction, convection, and radiation. These three factors cannot be ignored in the temperature field simulation of an oil-filled cable terminal, and their heat intensity must be accurately quantified to simulate the actual temperature rise.

[0112] Regarding the heat source boundary conditions, the oil-filled cable terminal heat source is set as a generalized source. Its size is determined by the size of the cable core and the size of the preset reference load current. The cross-sectional area of ​​the cable core in the oil-filled cable terminal model is 800mm. 2 , under the condition of preset reference load current of 800A, the heat source of oil-filled cable terminal is 16800W / m 3 .

[0113] Regarding the convection heat transfer boundary conditions, select the convection heat flux in the heat flux to set. Under natural convection conditions, the heat transfer coefficient of the outer surface of the oil-filled cable terminal in contact with the air is 5.8W / (m 2 ·K), the preset reference ambient temperature is set to 20℃.

[0114] Regarding the radiation heat transfer boundary conditions, the surface is selected to set the ambient radiation, where the surface emissivity of the silicone rubber is 0.8, the surface emissivity of the aluminum alloy is 0.1, and the preset reference ambient temperature is set to 20°C.

[0115] S205. Perform finite element simulation on the oil-filled cable terminal at different air domain heights to obtain different temperature field distributions corresponding to different oil leakage degrees under a preset reference ambient temperature and a preset reference load current. The air domain height is used to characterize the oil leakage degree. The higher the air domain height, the more severe the oil leakage degree.

[0116] Among them, finite element simulation refers to the method of discretizing a continuous physical field into a finite number of grid cells for numerical calculation; the air domain height represents the vertical distance of the gas space above the insulating oil chamber; the oil leakage degree refers to the severity of the insulating oil loss; and the temperature field distribution represents the temperature state in the closed structure.

[0117] Specifically, the detection system first divides the three-dimensional model of the oil-filled cable terminal into tetrahedral mesh elements, with the mesh size appropriately increased in areas with large temperature gradients. The detection system then sets different airspace heights, for example, increasing the airspace height by 5mm from the initial value until it reaches a preset maximum height. For each airspace height, under a preset reference ambient temperature (e.g., 20°C) and a preset reference load current (e.g., 500A), the detection system sets the aforementioned heat source boundary conditions, convection heat transfer boundary conditions, and radiation heat transfer boundary conditions in COMSOL finite element simulation software. The system then uses a solver to determine the overall temperature field distribution of the oil-filled cable terminal. The detection system establishes a mapping between the airspace height (i.e., the degree of oil leakage) and the temperature field distribution, generating finite element simulation results.

[0118] S206. Calculate an ambient temperature correction coefficient and a load current correction coefficient based on the current ambient temperature, the current load current, the preset reference ambient temperature, and the preset reference load current to correct the finite element simulation results and obtain the corresponding relationship between the oil leakage temperature under the actual working conditions. The finite element simulation results refer to different temperature field distributions corresponding to different oil leakage degrees determined by the finite element simulation method under the preset reference ambient temperature and the preset reference load current.

[0119] For details, please refer to step S103, which will not be described again here.

[0120] S207: Determine the current oil leakage degree of the oil-filled cable terminal based on the corresponding relationship between the temperature field characteristic parameters and the actual oil leakage temperature under working conditions.

[0121] For details, please refer to step S104, which will not be described again here.

[0122] S208. Periodically obtain multiple sets of temperature field characteristic parameters within a preset time period, and determine the ambient temperature, load current, and oil leakage degree corresponding to each of the multiple sets of temperature field characteristic parameters to draw an oil leakage development trend curve.

[0123] Among them, the preset time length refers to the pre-set data collection period; the oil leakage development trend curve refers to the graphical representation of the change of the oil leakage status over time.

[0124] Specifically, the detection system periodically collects data at preset sampling intervals (e.g., every 30 minutes). Each data collection includes temperature field characteristic parameters, the corresponding ambient temperature, and the load current. For each set of collected temperature field characteristic parameters, the detection system calculates the corresponding oil leakage extent. The detection system arranges the data in chronological order to form a multidimensional time series. Using data visualization technology, the changes in oil leakage extent over time are plotted as a leakage development trend curve, visually displaying the development of the oil leakage status.

[0125] S209: Determine the slope of the oil leakage development trend curve as the oil leakage rate to determine the stability of the oil leakage development trend.

[0126] Among them, the slope refers to the rate of change of the oil leakage development trend curve at each time point; the oil leakage rate indicates how fast the oil leakage degree changes over time; and the stability of the oil leakage development trend refers to the degree of fluctuation in the oil leakage development process.

[0127] Specifically, the detection system uses numerical differentiation to calculate the slope of the oil leak trend curve at each time point, using the central difference formula: current slope = (leakage level at the next moment - leakage level at the previous moment) / (2 × preset sampling interval). The detection system then calculates the average slope over a period of time and uses it as a quantitative indicator of the oil leak rate. The detection system compares the leak rate with a preset rate threshold and analyzes fluctuations in the slope to determine whether the leak trend is stable.

[0128] S210. When the oil leakage development trend is unstable, analyze the correlation between the temperature field characteristic parameters and the ambient temperature and load current.

[0129] The correlation refers to the degree of linear correlation between two variables, and its value range is between -1 and 1.

[0130] Specifically, when the detection system detects an unstable oil leakage trend, it needs to analyze whether this instability is caused by external factors (ambient temperature and load current) or a fault within the equipment. The detection system collects historical data on temperature field characteristic parameters, ambient temperature, and load current over a period of time (typically 24 hours to 7 days). This data is then preprocessed to remove outliers caused by measurement errors and signal interference, and the data of different dimensions is normalized using the z-score or min-max method. The detection system then calculates the Pearson correlation coefficient (or correlation) between the normalized temperature field characteristic parameters and the ambient temperature and load current. This calculation first determines the mean and standard deviation of each variable, then calculates the covariance between the variables, and finally determines the correlation. Based on the correlation, the detection system can determine whether the temperature field changes are caused by ambient temperature and load current (a large correlation, such as greater than 0.8) or by an oil leakage fault (a small correlation, such as less than 0.5).

[0131] Optionally, under normal circumstances, when the development trend of oil leakage is unstable, the analysis of the correlation between the temperature field characteristic parameters and the ambient temperature and load current can be achieved in the following way, which is not limited here: arrange the temperature field characteristic parameters, ambient temperature and load current in chronological order to obtain a temperature field characteristic parameter sequence, an ambient temperature sequence and a load current sequence; calculate the Pearson correlation coefficient of the temperature field characteristic parameter sequence and the ambient temperature sequence to obtain the ambient temperature correlation; calculate the Pearson correlation coefficient of the temperature field characteristic parameter sequence and the load current sequence to obtain the load current correlation; determine the correlation between the temperature field characteristic parameters and the ambient temperature and load current based on the ambient temperature correlation and the load current correlation.

[0132] Among them, the temperature field characteristic parameter sequence refers to the temperature field characteristic parameters arranged in chronological order; the ambient temperature sequence refers to the ambient temperatures arranged in chronological order; and the load current sequence refers to the load currents arranged in chronological order.

[0133] Specifically, first, the detection system performs data preprocessing on the collected temperature field characteristic parameter sequence and ambient temperature sequence, including removing outliers, supplementing missing values ​​and data standardization. Then, the detection system calculates the mean of the two sequences and subtracts each mean to obtain the deviation value. Next, the detection system calculates the product of the deviation values ​​of the two sequences and divides it by the product of the standard deviation of the two sequences and the product of the number of samples minus one, and finally obtains the Pearson correlation coefficient. The detection system uses the Pearson correlation coefficient as a quantitative indicator of the correlation with the ambient temperature, and is used to subsequently determine whether the temperature field change is mainly affected by the ambient temperature. For example, if the calculated Pearson correlation coefficient is 0.85, it means that the temperature field characteristic parameter has a strong positive correlation with the ambient temperature, indicating that the ambient temperature change may be one of the main reasons for the temperature field change. The processing method of the temperature field characteristic parameter sequence and the load current sequence is similar and will not be repeated here.

[0134] S211 : If the correlation exceeds a preset correlation threshold, adjust the ambient temperature and the load current to a preset standard range.

[0135] Among them, the preset correlation threshold refers to the critical value used to judge the significance of the correlation; the preset standard range refers to the normal working range of ambient temperature and load current; ambient temperature adjustment refers to changing the ambient temperature through environmental control equipment; load current adjustment refers to changing the current size through load transfer or power control.

[0136] Specifically, when the detection system finds that the correlation between characteristic temperature field parameters and external factors exceeds a preset correlation threshold, it indicates that the temperature field anomaly is primarily caused by external factors. The detection system generates operating condition adjustment instructions to determine whether the ambient temperature and load current are within the preset standard range (e.g., ambient temperature 15-35°C, load current 300-700A). If the ambient temperature and load current exceed the preset standard range, the detection system will activate environmental control equipment (such as air conditioning and ventilation systems) to adjust the ambient temperature. Simultaneously, the power distribution automation system will adjust the load distribution to bring the load current back within the preset standard range.

[0137] S212: If the correlation is less than or equal to the preset correlation threshold, trigger an emergency alarm.

[0138] Specifically, when the correlation between characteristic temperature field parameters and external factors is lower than or equal to a preset correlation threshold, the abnormal temperature field may be caused by a device fault. The detection system immediately triggers an emergency alarm: first, an alarm message containing the device number, fault type, and severity is sent to the monitoring center; a text message or app notification is also sent to relevant maintenance personnel; and the detection system automatically generates a detailed report containing historical data analysis, fault diagnosis results, and recommended actions.

[0139] S213. When the oil leakage development trend is stable, calculate the remaining time to reach the preset oil leakage threshold based on the current oil leakage level and leakage rate; if the remaining time is less than the preset time threshold, generate a maintenance instruction, which includes a recommended maintenance time window.

[0140] Among them, the remaining time refers to the estimated time required to reach the preset oil leakage threshold; the preset oil leakage threshold refers to the critical oil leakage level that requires maintenance; the preset time threshold refers to the time threshold that triggers the maintenance recommendation; the maintenance instruction refers to the maintenance command issued by the detection system; the recommended maintenance time window indicates the recommended maintenance execution period.

[0141] Specifically, the detection system uses a linear extrapolation method to calculate the remaining time required to reach a preset leakage threshold (such as 40%) based on the current leakage level (such as 20%) and the leakage rate (such as an increase of 0.5% per day). If the calculated remaining time is less than the preset time threshold (such as 7 days), the detection system will generate a maintenance instruction. This maintenance instruction includes: basic equipment information, current leakage status data, predicted remaining time, recommended maintenance time window (selecting a low-peak period considering the load curve), a list of required maintenance materials, etc. For example, if the current leakage level of an oil-filled cable terminal is 35%, the leakage rate is 0.8% per day, and the preset leakage threshold is 40%, then the remaining time is approximately 6.25 days, and the detection system will recommend completing the maintenance within 5 days.

[0142] The following describes the detection system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , is a schematic diagram of the physical device structure of the detection system in an embodiment of the present application.

[0143] It should be noted that Figure 3 The structure of the detection system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0144] like Figure 3 As shown, the detection system includes a CPU 301, which can perform various appropriate actions and processes according to programs stored in a read-only memory ROM 302 or programs loaded from a storage unit 308 into a random access memory RAM 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0145] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, push button switches, and the like; an output section 307 including a liquid crystal display (LCD), an audio output device, indicator lights, and the like; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 310 as needed, so that computer programs read from the removable media can be installed in the storage section 308 as needed.

[0146] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 309 and / or installed from the removable medium 311. When the computer program is executed by the CPU 301, the various functions defined in the present invention are performed.

[0147] It should be noted that specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0148] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings.

[0149] Specifically, the detection system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the oil leakage analysis method for the oil-filled cable terminal provided by the above embodiment is implemented.

[0150] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the detection system described in the above embodiments, or may exist independently and not incorporated into the detection system. The storage medium carries one or more computer programs, which, when executed by a processor of the detection system, enable the detection system to implement the oil leakage analysis method for oil-filled cable terminals provided in the above embodiments.

[0151] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0152] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for analyzing oil leakage at an oil-filled cable terminal, characterized in that: Applied to a detection system, the method comprises: A sensor array is provided longitudinally inside the sealed structure of the oil-filled cable terminal to collect temperature values ​​of the sensors and calculate temperature differences between adjacent sensors to obtain a temperature difference sequence, wherein the sensor array includes a first sensor to an Nth sensor provided sequentially from top to bottom; Determining temperature field characteristic parameters according to the temperature difference sequence, wherein the temperature field characteristic parameters include a maximum temperature difference value, a maximum temperature difference position, an average temperature difference value, a rate of change of adjacent temperature differences, and a temperature difference standard deviation in the temperature difference sequence; According to the current ambient temperature, the current load current, the preset reference ambient temperature and the preset reference load current, the ambient temperature correction coefficient and the load current correction coefficient are calculated to correct the finite element simulation results to obtain the corresponding relationship of the oil leakage temperature under the actual working condition. The finite element simulation results refer to different temperature field distributions corresponding to different oil leakage degrees determined by the finite element simulation method under the preset reference ambient temperature and the preset reference load current; before the step of calculating the ambient temperature correction coefficient and the load current correction coefficient according to the current ambient temperature, the current load current, the preset reference ambient temperature and the preset reference load current to correct the finite element simulation results to obtain the corresponding relationship of the oil leakage temperature under the actual working condition, the method also includes: establishing a three-dimensional model of the oil-filled cable terminal, and the three-dimensional model of the oil-filled cable terminal includes conductors and dense A closed structure, the closed structure comprising an insulating oil chamber and an air domain above the insulating oil chamber, a sensor array being longitudinally arranged on the inner side of the closed structure; a heat source boundary condition being set on the surface of the conductor, a convection heat transfer boundary condition being set on the outer surface of the sealed structure, and a radiation heat transfer boundary condition being set on the outer surface of the sealed structure, to obtain an oil-filled cable terminal model, the heat source boundary condition being determined by the preset reference load current, and the convection heat transfer boundary condition and the radiation heat transfer boundary condition being determined by the preset reference ambient temperature; finite element simulation is performed on the oil-filled cable terminal at different air domain heights to obtain different temperature field distributions corresponding to different oil leakage degrees at the preset reference ambient temperature and the preset reference load current, the air domain height being used to characterize the oil leakage degree, and the higher the air domain height, the more severe the oil leakage degree; Based on the correspondence between the temperature field characteristic parameters and the actual operating oil leakage temperature, the current oil leakage degree of the oil-filled cable terminal is determined; after the step of determining the current oil leakage degree of the oil-filled cable terminal based on the correspondence between the temperature field characteristic parameters and the actual operating oil leakage temperature, the method also includes: periodically obtaining multiple groups of temperature field characteristic parameters within a preset time period, and determining the ambient temperature, load current and oil leakage degree corresponding to each of the multiple groups of temperature field characteristic parameters to draw an oil leakage development trend curve; determining the slope of the oil leakage development trend curve as the oil leakage rate to judge the stability of the oil leakage development trend; when the oil leakage development trend is unstable, analyzing the correlation between the temperature field characteristic parameters and the ambient temperature and load current; if the correlation exceeds the preset correlation threshold, adjusting the ambient temperature and load current to a preset standard range; if the correlation is less than or equal to the preset correlation threshold, triggering an emergency alarm.

2. The method according to claim 1, characterized in that The heat source boundary conditions are: ; Wherein, Q is the heat source at the oil-filled cable terminal, P is the heating power of the conductor, is the lateral area of ​​the conductor, I is the preset reference load current flowing through the conductor, is the cross-sectional area of ​​the conductor, ρ is the resistivity of the conductor, and l is the length of the conductor; The convective heat transfer boundary conditions are: ; Wherein, λ is the thermal conductivity of the insulating material in the closed structure, is the temperature gradient, is the surface area of ​​the oil-filled cable terminal, h is the heat transfer coefficient of the outer surface of the oil-filled cable terminal in contact with air, is the surface temperature of the oil-filled cable terminal, is the preset reference ambient temperature; The radiation heat transfer boundary conditions are: ; Where, is the Stefan-Boltzmann constant, is the surface emissivity.

3. The method according to claim 1, characterized in that The calculation of the ambient temperature correction coefficient and the load current correction coefficient based on the current ambient temperature, the current load current, the preset reference ambient temperature, and the preset reference load current to correct the finite element simulation results and obtain the corresponding relationship of the oil leakage temperature under actual working conditions specifically includes: Determining the ratio of the current ambient temperature to the preset reference ambient temperature as the ambient temperature correction coefficient, and determining the square ratio of the current load current to the preset reference load current as the load current correction coefficient; Multiplying the temperature field distribution in the finite element simulation result by the product of the ambient temperature correction coefficient and the load current correction coefficient to obtain a corrected temperature field distribution; The corresponding relationship between different oil leakage degrees and different corrected temperature field distributions is established to obtain the corresponding relationship between the oil leakage temperature in the actual working condition.

4. The method according to claim 1, wherein After the step of determining the slope of the oil leakage development trend curve as the oil leakage rate to judge the stability of the oil leakage development trend, the method further includes: When the oil leakage development trend stabilizes, the remaining time until reaching a preset oil leakage threshold is calculated based on the current oil leakage extent and the oil leakage rate; If the remaining time is less than a preset time threshold, a maintenance instruction is generated, and the maintenance instruction includes a recommended maintenance time window.

5. The method according to claim 1, wherein When the oil leakage development trend is unstable, the correlation between the temperature field characteristic parameters and the ambient temperature and load current is analyzed, specifically including: Arrange the temperature field characteristic parameters, ambient temperature and load current in chronological order to obtain a temperature field characteristic parameter sequence, an ambient temperature sequence and a load current sequence; Calculating the Pearson correlation coefficient between the temperature field characteristic parameter sequence and the ambient temperature sequence to obtain the ambient temperature correlation; Calculating the Pearson correlation coefficient between the temperature field characteristic parameter sequence and the load current sequence to obtain the load current correlation; The correlations of the temperature field characteristic parameters with the ambient temperature and the load current are determined according to the ambient temperature correlation and the load current correlation.

6. A detection system, characterized in that: The detection system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the detection system to perform the method described in any one of claims 1 to 5.

7. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a detection system, the detection system is caused to execute the method according to any one of claims 1 to 5.

8. A computer program product, characterized in that When the computer program product is run on a detection system, the detection system is caused to perform the method according to any one of claims 1 to 5.

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