Method and system for determining moisture distribution in oil-paper insulation under different temperature fields

Abstract

The present application relates to the technical field of detection and optimization of oil paper insulation material, and provides a method and system for determining moisture distribution in oil paper insulation under different temperature fields, which comprises the following steps: an oil paper insulation state evaluation step: a physical model of the oil paper insulation is established, and insulation performance indexes of the oil paper insulation are calculated based on historical operation data and the physical model; a moisture distribution determination step: the distribution of moisture in the oil paper insulation is analyzed based on the insulation performance indexes, and if the deviation of the moisture distribution from an expected distribution is greater than a first threshold value, a detection or treatment strategy is adjusted so that the deviation of the moisture distribution in the oil paper insulation from the expected distribution is less than or equal to the first threshold value; an insulation performance optimization step: if the insulation performance of all the oil paper insulation meets a predetermined standard, the detection ends; otherwise, the insulation performance of a region to be optimized is optimized, and the moisture distribution determination step is returned; the present application can effectively guarantee the reliability of the oil paper insulation and prolong the service life thereof.

Description

Technical Field

[0001] This invention relates to the field of detection and optimization technology of oil-paper insulation materials in power equipment, and more specifically, to a method and system for determining the moisture distribution in oil-paper insulation under different temperature fields. Background Technology

[0002] In the operation and maintenance of power equipment, oil-paper insulation materials are widely used due to their excellent insulation properties. However, during long-term operation, oil-paper insulation materials are affected by various factors such as temperature and humidity, causing changes in the distribution of moisture within the insulation material, which in turn affects its insulation performance. Current technologies for moisture detection and distribution analysis of oil-paper insulation materials largely rely on empirical judgment and simple measurement methods, lacking systematicity and precision. Furthermore, existing methods often ignore the dynamic characteristics of moisture distribution under different temperature conditions, making it difficult to achieve real-time assessment and optimization of the oil-paper insulation condition.

[0003] In the process of implementing the embodiments of the present invention, the inventors discovered that the prior art has at least the following problems or defects: First, the existing detection methods cannot accurately reflect the moisture distribution of oil-paper insulation under different temperature conditions, resulting in the inability to adjust the detection or treatment strategy in a timely manner; second, the prior art fails to effectively integrate key performance indicators such as permittivity, dielectric loss, and resistivity of oil-paper insulation, and lacks the ability to comprehensively evaluate insulation performance; finally, when optimizing the performance of oil-paper insulation, the prior art fails to make precise adjustments to areas where the insulation performance does not meet the standards, affecting the optimization effect and efficiency. Summary of the Invention

[0004] This invention provides a method and system for determining the moisture distribution in oil-paper insulation under different temperature fields.

[0005] In a first aspect of the present invention, a method for determining the moisture distribution in oil-paper insulation under different temperature fields is provided, comprising:

[0006] Includes the following steps:

[0007] S1. Establish a physical model of oil-paper insulation to assess the condition of oil-paper insulation materials and obtain the insulation performance indicators of oil-paper insulation.

[0008] S2. Moisture distribution is determined based on the insulation performance indicators;

[0009] S3. Optimize insulation performance based on the insulation performance indicators.

[0010] Furthermore, the oil-paper insulation condition assessment step includes establishing a physical model of the oil-paper insulation, and calculating the insulation performance index of the oil-paper insulation based on historical operating data and the physical model.

[0011] Furthermore, the moisture distribution determination step includes analyzing the moisture distribution in the oil-paper insulation based on the insulation performance index. If the deviation between the moisture distribution and the expected distribution is greater than a first threshold, the detection or processing strategy is adjusted so that the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold.

[0012] Furthermore, the insulation performance optimization step includes the following steps: if the insulation performance indicators of all oil-paper insulation meet the predetermined standards, the test ends; otherwise, after the initial moisture distribution measurement step, the insulation performance of the areas where the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold is optimized, and the test returns to the moisture distribution measurement step.

[0013] Furthermore, the historical operating data includes: the permittivity, dielectric loss, and resistivity of the oil-paper insulation under two different temperature conditions, as well as the moisture content, temperature, and aging degree of the oil-paper insulation.

[0014] Furthermore, based on historical operating data and the physical model, the insulation performance indicators of the oil-paper insulation are calculated, including:

[0015] The permeability change of the oil-paper insulation was calculated based on the historical operating data.

[0016] The dielectric loss of the oil-paper insulation is calculated based on the historical operating data.

[0017] The resistivity of the oil-paper insulation was calculated based on the historical operating data.

[0018] Furthermore, the physical model of oil-paper insulation is decomposed into multiple sub-models, namely, a permittivity sub-model, a dielectric loss sub-model, and a resistivity sub-model for oil-paper insulation. Based on these sub-models, the insulation performance indicators of the oil-paper insulation are calculated.

[0019] In a second aspect of the invention, a system for determining the moisture distribution in oil-paper insulation under different temperature fields is provided, comprising:

[0020] The oil-paper insulation status assessment module is used to establish a physical model of the oil-paper insulation and calculate the insulation performance index of the oil-paper insulation based on historical operating data and the physical model.

[0021] The moisture distribution measurement module is used to analyze the distribution of moisture in the oil-paper insulation. If the deviation between the moisture distribution and the expected distribution is greater than the first threshold, the detection or processing strategy will be adjusted.

[0022] The insulation performance optimization module is used to end the test when the insulation performance of all oil-paper insulations reaches the predetermined standard. Otherwise, after the initial moisture distribution measurement step, if the insulation performance of the area where the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold is not optimized, the test returns to the moisture distribution measurement step.

[0023] The embodiments of the present invention have at least the following beneficial effects: By establishing a physical model of oil-paper insulation and combining it with historical operating data, the present invention can accurately calculate insulation performance indicators, thereby comprehensively evaluating the state of oil-paper insulation. This method not only improves the accuracy of moisture distribution measurement, but also, by analyzing the deviation between the moisture distribution and the expected distribution, can adjust detection or treatment strategies in a timely manner, effectively controlling moisture distribution and ensuring that the insulation performance of the oil-paper insulation material meets predetermined standards. Furthermore, the present invention also has the ability to dynamically optimize insulation performance. When insulation performance is detected to be substandard, the system automatically optimizes the insulation performance of the area to be optimized by adjusting the moisture content, so that the insulation performance indicators reach or exceed predetermined standards. This optimization not only improves the reliability and service life of oil-paper insulation, but also reduces maintenance costs by reducing unnecessary maintenance and replacement. In summary, the method and system of the present invention can provide strong technical support for the safe operation and efficient maintenance of power equipment, and have significant economic and social benefits. Attached Figure Description

[0024] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of the invention are illustrated in the drawings by way of example and not limitation, wherein:

[0025] Figure 1 This is a flowchart illustrating a method for determining the moisture distribution in oil-paper insulation under different temperature fields, as provided in an embodiment of the present invention.

[0026] Figure 2 This is a schematic diagram of a system for determining the moisture distribution in oil-paper insulation under different temperature fields, provided in an embodiment of the present invention. Detailed Implementation

[0027] The principles and spirit of the invention will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are provided merely to enable those skilled in the art to better understand and implement the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided to make the invention more thorough and complete, and to fully convey the scope of the invention to those skilled in the art.

[0028] Those skilled in the art will recognize that embodiments of the present invention can be implemented as a system, apparatus, device, method, or computer program product. Therefore, the present invention can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0029] It should be noted that the number of any elements in the accompanying drawings is for illustrative purposes only and not as a limitation, and any naming is for distinction only and has no limiting meaning.

[0030] The following is for reference. Figure 1 , Figure 1 This is a flowchart illustrating a method for determining moisture distribution in oil-paper insulation under different temperature fields, as provided in an embodiment of the present invention. Figure 1 As shown, a method 100 for determining the moisture distribution in oil-paper insulation under different temperature fields includes:

[0031] The steps for assessing the condition of oil-paper insulation are as follows: 1. Establish a physical model of the oil-paper insulation. 2. Calculate the insulation performance indicators of the oil-paper insulation based on historical operating data and the physical model.

[0032] Moisture distribution determination steps: Based on the insulation performance index, analyze the moisture distribution in the oil-paper insulation. If the deviation between the moisture distribution and the expected distribution is greater than the first threshold, adjust the detection or processing strategy so that the deviation between the moisture distribution and the expected distribution in the oil-paper insulation is less than or equal to the first threshold.

[0033] Insulation performance optimization step: If the insulation performance of all oil-paper insulation meets the predetermined standard, the test ends; otherwise, optimize the insulation performance of the areas where the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold after the initial moisture distribution measurement step, and return to the moisture distribution measurement step.

[0034] When the moisture distribution in oil-paper insulation deviates from the expected distribution, the detection or treatment strategy should be adjusted, which may include the following:

[0035] 1. Increase detection frequency: Monitor moisture distribution more frequently in order to detect deviations and make adjustments more quickly.

[0036] 2. Improve detection technology: Use more precise or higher resolution detection technology to more accurately assess moisture distribution.

[0037] 3. Adjust operating conditions: Based on the physical characteristics of the paper insulation and environmental conditions, adjust operating parameters such as temperature and humidity to affect the migration and distribution of moisture.

[0038] 4. Optimize insulation structure: Redesign or adjust the physical structure of the paper insulation, such as the number of layers, thickness, or material combination, to improve moisture distribution.

[0039] 5. Apply dehumidification technology: Use methods such as vacuum drying, heating dehumidification, or chemical dehumidification to reduce the moisture content in oil paper insulation.

[0040] 6. Improve the quality of insulating oil: By purifying or replacing the insulating oil, the moisture and contaminants in the oil are reduced, thereby affecting the distribution of moisture in the paper insulation.

[0041] 7. Use of additives: Add specific chemicals to insulating oil to change its physical properties, such as increasing the oil's viscosity and reducing the solubility and diffusion of water.

[0042] 8. Localized treatment: Special treatment is applied to specific areas with large deviations in moisture distribution, such as localized heating, localized dehumidification, or the use of shielding materials.

[0043] 9. Data Analysis and Predictive Models: Utilize historical data and predictive models to analyze trends in water distribution, predict potential deviations, and take preventative measures.

[0044] 10. Maintenance and Replacement: For aged or damaged oil-paper insulation, perform maintenance or replacement to restore its moisture retention capacity and insulation performance.

[0045] It should be noted that the expected distribution refers to the moisture distribution state predicted under ideal or standard conditions, based on the physical and chemical properties of the oil-paper insulation material and historical best operating data, through theoretical calculations, simulation analysis, and other methods. This distribution reflects the optimal or average distribution pattern of moisture in oil-paper insulation under a specific temperature field and serves as a reference benchmark for assessing the actual moisture distribution. For example, inside an oil-immersed transformer, driven by multiple physical field gradients such as electric and temperature fields, moisture is constantly in a dynamic migration process. The expected distribution represents the ideal state of moisture distribution under these conditions, which helps to achieve effective early warning of transformer faults.

[0046] Predetermined standards refer to the performance indicators and safety requirements set based on industry specifications, historical experience, and risk assessments to ensure the performance and reliability of oil-paper insulation in practical applications. These standards include, but are not limited to, insulation performance indicators such as permittivity, dielectric loss, and resistivity, as well as environmental conditions such as temperature and humidity, taking into account environmental adaptability. Predetermined standards are the minimum requirements that oil-paper insulation must meet in design and operation to ensure the safe operation and expected lifespan of the equipment. For example, dielectric impedance and loss factor, which can be measured using techniques such as frequency domain dielectric spectroscopy (FDS), can be used to assess the aging state of oil-paper insulation and thus determine whether it meets the predetermined insulation performance standards.

[0047] It should be noted that the method for determining the moisture distribution in oil-paper insulation under different temperature fields includes the following steps: The core of this step is to establish a physical model of the oil-paper insulation and use historical operating data to calculate insulation performance indicators. This involves not only measuring the permittivity, dielectric loss, and resistivity of the oil-paper insulation material, but also considering the influence of factors such as moisture content, temperature, and degree of aging.

[0048] Specifically, the condition assessment of oil-paper insulation involves setting the following key parameters: First, it is necessary to collect data on the permittivity, dielectric loss, and resistivity of the oil-paper insulation under different temperature conditions; second, the moisture content, temperature, and aging degree of the oil-paper insulation are measured. These data will serve as input parameters for the physical model, which can then be used to predict the insulation performance of the oil-paper insulation under different conditions. For example, the change in permittivity can be calculated using the formula... In progress, among which Let be the permittivity of the i-th region. The permittivity is the value when there is no moisture. The influence coefficient of moisture content, This refers to the moisture content.

[0049] Preferably, the moisture distribution measurement step can be further refined into the following steps: First, calculate the initial state of moisture distribution based on the design parameters of the oil-paper insulation; then, use the formula... The permeability variation deviation for each region is calculated, and the moisture distribution is updated by combining this with changes in dielectric loss and resistivity. More specifically, the update of the moisture distribution can be achieved by considering a function of permeability variation, dielectric loss, resistivity, current moisture content, and temperature; the formula can be expressed as follows: ,in It is a composite function. and These represent the changes in dielectric loss and resistivity, respectively. This represents the current moisture content. For temperature.

[0050] In the insulation performance optimization step, if the insulation performance of all oil-paper insulations meets the predetermined standard, the test ends; otherwise, after the initial moisture distribution measurement step, the insulation performance of areas where the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold is not optimized, and the process returns to the moisture distribution measurement step. Specific optimization strategies may include adjusting the moisture content, using formulas... To correct the moisture content of the area to be optimized, among which This is used to adjust the coefficients. More specifically, the area to be optimized can be determined based on whether the sum of the insulation performance index and the moisture distribution deviation value is greater than or equal to a first threshold, thereby achieving more precise optimization.

[0051] In some embodiments, the historical operating data includes: the permittivity, dielectric loss, and resistivity of the oil-paper insulation under two sets of different temperature conditions, as well as the moisture content, temperature, and aging degree of the oil-paper insulation.

[0052] It should be noted that the historical operating data includes: the permittivity, dielectric loss, and resistivity of the oil-paper insulation under two different temperature conditions, as well as the moisture content, temperature, and aging degree of the oil-paper insulation. This means that in practical applications, we need to collect electrical performance data and physical state data of the oil-paper insulation under at least two different temperature environments. This data is the basis for evaluating the condition of the oil-paper insulation and provides crucial information for subsequent moisture distribution determination and insulation performance optimization.

[0053] Specifically, the collection of historical operating data involves the following aspects: First, the measurements of permittivity, dielectric loss, and resistivity should be conducted under different temperature conditions to ensure data diversity and representativeness; second, moisture content can be measured using methods such as gravimetric or capacitance methods; third, temperature measurements should use high-precision temperature sensors to ensure data accuracy; and finally, the degree of aging can be assessed using indicators such as the service life, color change, and mechanical property changes of the oil-paper insulation. The settings of these parameters should be determined based on the specific application scenario and equipment requirements.

[0054] Preferably, to improve the accuracy and reliability of the data, the following measures can be taken: First, the measurements of permittivity, dielectric loss, and resistivity should be performed under controlled laboratory conditions to reduce interference from environmental factors; second, moisture content measurements can be performed using an online monitoring system to achieve real-time data collection; third, temperature measurements can be performed using a distributed temperature monitoring system to obtain the temperature distribution in different areas of the oil-paper insulation; finally, the assessment of aging can be combined with the results of chemical analysis and physical performance tests of the oil-paper insulation. Furthermore, to improve the efficiency of data processing, dedicated data analysis software can be developed to automatically process and analyze the collected data, thereby providing a more accurate basis for the condition assessment of the oil-paper insulation.

[0055] In some embodiments, based on historical operating data and the physical model, the insulation performance indicators of the oil-paper insulation are calculated, including:

[0056] The permeability change of the oil-paper insulation was calculated based on the historical operating data.

[0057] The dielectric loss of the oil-paper insulation is calculated based on the historical operating data.

[0058] The resistivity of the oil-paper insulation was calculated based on the historical operating data.

[0059] The physical model of oil-paper insulation is decomposed into multiple sub-models, namely, the permittivity sub-model, the dielectric loss sub-model, and the resistivity sub-model of oil-paper insulation. Based on the multiple sub-models, the insulation performance index of the oil-paper insulation is calculated.

[0060] It should be noted that the insulation performance indicators of the oil-paper insulation are calculated based on historical operating data and the physical model, including: calculating the permittivity change of the oil-paper insulation based on the historical operating data; calculating the dielectric loss of the oil-paper insulation based on the historical operating data; calculating the resistivity of the oil-paper insulation based on the historical operating data; and decomposing the physical model of the oil-paper insulation into multiple sub-models, represented as the permittivity sub-model, dielectric loss sub-model, and resistivity sub-model, respectively. Based on these sub-models, the insulation performance indicators of the oil-paper insulation are calculated. This step is the core of the entire method, involving the quantitative analysis of the properties of the oil-paper insulation material, providing a scientific basis for subsequent moisture distribution determination and insulation performance optimization.

[0061] Specifically, the process of calculating insulation performance indicators can be broken down into the following steps: First, based on historical operating data, using formulas... Calculate the permittivity change for each region, where These are actual measured values. The first is the theoretical value predicted based on the physical model; the second is through the formula. Calculate dielectric loss, where Dielectric loss rate, Moisture content, The current temperature. The reference temperature is used; furthermore, resistivity can be calculated using the conductivity function. To achieve this, in which Moisture content, For temperature. The establishment of these sub-models requires a basis on the physical and chemical properties of the paper insulation material, and their relationship with electrical properties.

[0062] Preferably, to improve the accuracy and efficiency of the calculations, the following measures can be taken: First, the calculation of permittivity changes can employ numerical analysis methods, such as finite element analysis, to account for the non-uniformity of the oil-paper insulation material; second, the calculation of dielectric loss can incorporate a temperature correction factor to reflect the changes in material properties at different temperatures; third, the calculation of resistivity can employ nonlinear regression analysis to more accurately describe the relationship between the conductivity function and moisture content and temperature. Furthermore, to improve the adaptability and generalization ability of the model, machine learning algorithms can be used to analyze historical operating data, thereby optimizing the parameter settings of the sub-models. These measures help improve the accuracy of oil-paper insulation condition assessment, providing support for the precise determination of moisture distribution and the effective optimization of insulation performance.

[0063] In some embodiments, the change in permittivity of the oil-paper insulation is calculated using the following formula:

[0064]

[0065] in, Let be the permittivity of the i-th region. Let be the permittivity of the i-th region in the absence of moisture. This is the coefficient representing the effect of moisture content on permittivity. Let be the moisture content of the oil-paper insulation in the i-th region.

[0066] It should be noted that in the formula for calculating the change in permittivity of oil-paper insulation... This represents the capacitance at a specific moisture content. It is the permittivity when there is no moisture. It is the coefficient representing the effect of moisture content on permittivity. This represents the moisture content of the oil-paper insulation in the i-th region. This formula allows us to predict changes in permittivity based on changes in moisture content, thereby assessing the insulation performance of the oil-paper insulation.

[0067] Specifically, calculating the change in permittivity involves setting several key parameters. First, This can be obtained through laboratory testing or from data provided by the manufacturer. Secondly, It is an empirical coefficient, which can be determined experimentally, and reflects the degree to which changes in moisture content affect permittivity. Furthermore, Measurements can be taken in various ways, such as using a humidity sensor or by measuring the weight difference. The settings for these parameters need to take into account the specific characteristics of the paper insulation material and the application environment.

[0068] Preferably, to improve the accuracy of permittivity change calculation, the following measures can be taken: First, Measurements should be conducted under standardized conditions to minimize the impact of environmental factors. Secondly, The capacitance value can be determined by testing the capacitance of oil-paper insulation materials with different moisture contents, and then obtaining it through data fitting. Furthermore, The measurement can be performed using high-precision sensors to improve accuracy. More specifically, the calculation of permittivity change can be combined with the aging degree of the oil-paper insulation material and historical operating data, and a more complex mathematical model can be established to consider the combined effects of these factors. For example, an aging coefficient can be introduced to adjust... The value, or a nonlinear model, can be used to describe it more accurately. and The relationship between these alternatives can further improve the accuracy and reliability of oil-paper insulation condition assessment.

[0069] In some embodiments, the dielectric loss of the oil-paper insulation is calculated using the following formula:

[0070]

[0071] in, Let be the dielectric loss of the i-th region. Dielectric loss rate, The moisture content of the oil-paper insulation in the i-th region. Let be the temperature of the i-th region. This is a reference temperature.

[0072] It should be noted that in the formula for calculating the dielectric loss of oil-paper insulation... This represents the dielectric loss of the i-th region. It is the dielectric loss rate. It refers to the moisture content of the oil-paper insulation. It is the temperature of the current area, and This is the reference temperature. This formula allows us to assess the dielectric loss of oil-paper insulation under different moisture contents and temperature conditions, thereby further analyzing its insulation performance.

[0073] Specifically, the calculation of dielectric loss involves setting several key parameters. First, It is a constant related to the material's inherent properties and can be determined through laboratory testing. Secondly, Measurements can be obtained through gravimetric methods, capacitance methods, or other suitable methods. Again, It can be measured in real time using a temperature sensor, and A standard temperature, such as 25°C, is typically chosen as a reference for comparison. Accurate setting of these parameters is crucial for accurate calculation of dielectric loss.

[0074] Preferably, to improve the accuracy and applicability of dielectric loss calculation, the following measures can be taken: First, The determination can be achieved by conducting extensive testing on different types of oil-paper insulation materials and using statistical methods to determine their average value and range of variation. Secondly, moisture content... Measurements can be taken using automated online monitoring systems to achieve continuous monitoring and real-time data collection. Furthermore, The measurement can employ a multi-point temperature monitoring system to obtain the temperature distribution in different areas of the oil-paper insulation. More specifically, the calculation of dielectric loss can be combined with the aging degree of the oil-paper insulation and environmental factors. By introducing an aging coefficient and an environmental correction factor, the formula can be adjusted to more accurately reflect the dielectric loss in practical applications. These alternatives can further improve the accuracy and reliability of dielectric loss calculation.

[0075] In some embodiments, the resistivity of the oil-paper insulation is calculated using the following formula:

[0076]

[0077] in, Let be the resistivity of the i-th region. The conductivity function is determined by the water content. and temperature Calculated.

[0078] It should be noted that this formula allows us to predict the resistivity of paper insulation based on its moisture content and temperature changes, thereby assessing its insulation performance.

[0079] Specifically, the calculation of resistivity involves the conductivity function. Determining the conductivity function is a crucial step. Parameters can be defined based on the physical and chemical properties of the paper insulation material and their relationship with moisture content and temperature. Temperature can be obtained through laboratory testing or on-site measurement. Temperature can be monitored in real time using a temperature sensor installed near the paper insulation. Calculating resistivity requires accurate measurements of these parameters and a suitable mathematical model to describe the relationship between conductivity and moisture content and temperature.

[0080] Preferably, to improve the accuracy and robustness of resistivity calculation, the following measures can be taken: First, the conductivity function It can be obtained through fitting experimental data to ensure that it accurately reflects the electrical conductivity behavior of oil-paper insulation material under different moisture contents and temperatures. Secondly, moisture content... High-precision sensors can be used for measurement to reduce measurement errors. In addition, temperature... Monitoring can employ a distributed temperature monitoring system to obtain more comprehensive temperature distribution data for oil-paper insulation. More specifically, resistivity calculations can incorporate the aging state of the oil-paper insulation and other environmental factors. By introducing aging correction factors and environmental impact parameters to adjust the conductivity function, the resistivity variation in practical applications can be more accurately reflected. These alternatives can further improve the accuracy and reliability of resistivity calculations.

[0081] In some embodiments, analyzing the distribution of moisture in oil-paper insulation includes:

[0082] The initial state of moisture distribution is calculated based on the design parameters of the oil-paper insulation.

[0083] Update the moisture distribution status according to the following formula:

[0084]

[0085] in, It is a function that comprehensively considers changes in permittivity, dielectric loss, resistivity, current moisture content, and temperature, specifically:

[0086]

[0087] a, b, c, d, e are weighting coefficients. ,、 , , , These are average permittivity, average dielectric loss, average resistivity, average moisture content, and average temperature, respectively.

[0088] It should be noted that, in some embodiments, analyzing the moisture distribution in the oil-paper insulation includes: calculating the initial state of the moisture distribution based on the design parameters of the oil-paper insulation; and updating the moisture distribution state according to the following formula. This sentence describes how to analyze and update the moisture distribution using the design parameters and performance indicators of oil-paper insulation. Here, It is the updated moisture content, and It is a function that comprehensively considers changes in permittivity, dielectric loss, resistivity, current moisture content, and temperature.

[0089] Specifically, the analysis and updating process of moisture distribution involves the following key steps: First, based on the design parameters of the oil-paper insulation, such as thickness and initial moisture content, the initial state of moisture distribution is calculated; second, the formula is used... To update the water distribution status, among which , and These represent changes in permittivity, dielectric loss, and resistivity, respectively, which can be calculated based on historical operating data and physical models. This refers to the current moisture content of the area. This is the temperature of the current area. The specific form of the function can be determined based on the characteristics of the oil-paper insulation material and environmental conditions.

[0090] Preferably, to improve the accuracy and practicality of moisture distribution analysis, the following measures can be taken: First, the calculation of the initial moisture distribution state can be combined with the production process and historical data of the oil-paper insulation material to ensure that it reflects the actual initial conditions; second, The function design can employ machine learning algorithms, automatically learning and optimizing its form by analyzing large amounts of historical data. Furthermore, the process of updating the water distribution state can utilize an iterative method, gradually approximating the actual water distribution state through multiple iterations. More specifically, The function can contain multiple sub-functions, each corresponding to the effects of permittivity, dielectric loss, and resistivity on moisture distribution. Each sub-function can be designed and optimized based on its corresponding physical process. Furthermore, environmental and aging factors can be incorporated, and adjustments can be made... Weighting coefficients in the function are used to account for the impact of these factors on moisture distribution. These alternatives can further improve the accuracy and adaptability of moisture distribution analysis.

[0091] In some embodiments, the insulation performance index of oil-paper insulation is calculated using the following formula:

[0092]

[0093] in, Let be the permeability variation deviation value of the i-th region. This represents the average value of the permittivity variation across all regions.

[0094] It should be noted that, This represents the deviation value of the permittivity change in the i-th region. It is the permittivity obtained from actual measurement, while It is the average value of the permittivity variation across all regions. This formula provides a method for quantifying insulation performance deviations, helping to identify areas where insulation performance fails to meet standards.

[0095] Specifically, the calculation of insulation performance indicators involves setting the following key parameters: First, Measurements need to be conducted under specific environmental conditions to ensure the accuracy and comparability of the data; secondly, The calculation requires collecting permittivity measurements from all areas and averaging them. This average value reflects the overall insulation performance level of the entire oil-paper insulation system. The settings for these parameters need to be determined based on the characteristics of the oil-paper insulation material and the test conditions.

[0096] Preferably, to improve the accuracy and applicability of insulation performance index calculations, the following measures can be taken: First, The measurement can be performed using high-precision permittivity measuring equipment at multiple time points to reduce the impact of random errors; secondly, The calculation can employ a weighted average method, where the weights can be determined based on the importance or representativeness of each region to more accurately reflect the overall insulation performance. Furthermore, the calculation of insulation performance indicators can incorporate the aging degree of the paper insulation and other environmental factors, adjusting for these factors by introducing an aging coefficient and an environmental correction factor. or The value of is obtained to more accurately reflect the insulation performance in practical applications. More specifically, statistical methods can be used for analysis. By analyzing the distribution of data, areas with significant insulation performance deviations can be identified and optimized accordingly. These alternative solutions can further improve the accuracy and effectiveness of insulation performance assessment.

[0097] In some embodiments, the moisture content of the area to be optimized is corrected using the following formula:

[0098]

[0099] in, The corrected moisture content for the i-th region. To adjust the coefficient, Let be the permeability variation deviation value of the i-th region.

[0100] It should be noted that the process of correcting the moisture content involves setting several key parameters. First, Measurements can be obtained through laboratory testing or on-site monitoring. Secondly, The calculation requires measured and average permittivity values ​​of the paper insulation. Again, The value of this parameter needs to be determined based on the characteristics of the paper insulation material and the required degree of insulation performance improvement. It is an empirical coefficient that can be optimized through experiments or data analysis. Accurate setting of these parameters is crucial for the proper correction of moisture content.

[0101] Preferably, to improve the accuracy and effectiveness of moisture content correction, the following measures can be taken: First, The measurement can employ high-precision sensors and be calibrated in conjunction with environmental conditions to ensure the accuracy of the measurement results. Secondly, The calculations can be combined with long-term performance data of oil-paper insulation to more comprehensively reflect the changing trends of insulation performance. Furthermore, The value can be determined experimentally or automatically adjusted using machine learning algorithms based on historical data. More specifically, the correction of moisture content can be an iterative process, achieved by continuously monitoring and adjusting insulation performance indicators. The moisture content is gradually optimized until the predetermined insulation performance standard is achieved. Furthermore, a safety factor or threshold can be introduced to limit the correction range for moisture content, avoiding other potential problems caused by over-correction. These alternatives can further improve the accuracy and reliability of moisture content correction.

[0102] like Figure 2 As shown in some embodiments, a system 200 for determining the moisture distribution in oil-paper insulation under different temperature fields is provided. The system 200 includes:

[0103] The oil-paper insulation status assessment module 201 is used to establish a physical model of the oil-paper insulation and calculate the insulation performance index of the oil-paper insulation based on historical operating data and the physical model.

[0104] The moisture distribution measurement module 202 is used to analyze the distribution of moisture in the oil paper insulation. If the deviation between the moisture distribution and the expected distribution is greater than the first threshold, the detection or processing strategy is adjusted.

[0105] The insulation performance optimization module 203 is used to end the test when the insulation performance of all oil-paper insulations reaches the predetermined standard; otherwise, it optimizes the insulation performance of areas where the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold after the initial moisture distribution measurement step, and returns to the moisture distribution measurement step.

[0106] It is understandable that the modules described in the system 200 for determining the moisture distribution in oil-paper insulation under different temperature fields are similar to those in the reference system. Figure 1 The steps described in the method for determining the moisture distribution in oil-paper insulation under different temperature fields correspond to those steps. Therefore, the operations, features, and beneficial effects described above for the method for determining the moisture distribution in oil-paper insulation under different temperature fields are also applicable to the system 200 for determining the moisture distribution in oil-paper insulation under different temperature fields and the modules contained therein, and will not be repeated here.

[0107] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept.

Claims

1. A method for determining the moisture distribution in oil-paper insulation under different temperature fields, characterized in that, Includes the following steps: S1. Establish a physical model of oil-paper insulation to assess the state of oil-paper insulation and obtain the insulation performance indicators of oil-paper insulation. S2. Based on the insulation performance indicators, the moisture distribution is measured. The moisture distribution measurement steps are as follows: First, calculate the initial state of moisture distribution according to the design parameters of the oil-paper insulation; then, use the formula... The permeability variation deviation for each region is calculated, and the moisture distribution is updated by combining the changes in dielectric loss and resistivity. Let be the permittivity of the i-th region; the update of the moisture distribution state is performed by comprehensively considering the changes in permittivity, dielectric loss, resistivity, current moisture content, and temperature, as shown in the formula: ,in It is a composite function. and These represent the changes in dielectric loss and resistivity, respectively. This represents the current moisture content. For temperature; S3. Optimize insulation performance based on the aforementioned insulation performance indicators, including adjusting moisture content using the formula. Correct the moisture content of the area to be optimized, among which To adjust the coefficient, the region to be optimized is determined based on whether the sum of the insulation performance index and the moisture distribution deviation value is greater than or equal to the first threshold.

2. The method according to claim 1, characterized in that, The oil-paper insulation condition assessment steps include establishing a physical model of the oil-paper insulation, and calculating the insulation performance index of the oil-paper insulation based on historical operating data and the physical model.

3. The method according to claim 2, characterized in that, The moisture distribution determination step includes analyzing the moisture distribution in the oil-paper insulation based on the insulation performance index. If the deviation between the moisture distribution and the expected distribution is greater than a first threshold, the detection or processing strategy is adjusted so that the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold.

4. The method according to claim 3, characterized in that, The insulation performance optimization step includes the following steps: if the insulation performance indicators of all oil-paper insulation meet the predetermined standards, the test ends; otherwise, after the initial moisture distribution measurement step, the insulation performance of the areas where the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold is optimized, and the test returns to the moisture distribution measurement step.

5. The method according to claim 4, characterized in that, The historical operating data includes: the permittivity, dielectric loss, and resistivity of the oil-paper insulation under two different temperature conditions, as well as the moisture content, temperature, and aging degree of the oil-paper insulation.

6. The method according to claim 5, characterized in that, Based on historical operating data and the physical model, the insulation performance indicators of the oil-paper insulation are calculated, including: The permeability change of the oil-paper insulation was calculated based on the historical operating data. The dielectric loss of the oil-paper insulation is calculated based on the historical operating data. The resistivity of the oil-paper insulation was calculated based on the historical operating data.

7. The method according to claim 6, characterized in that, The physical model of oil-paper insulation is decomposed into multiple sub-models, namely, the permittivity sub-model, the dielectric loss sub-model, and the resistivity sub-model of oil-paper insulation. Based on the multiple sub-models, the insulation performance index of the oil-paper insulation is calculated.

8. A system for determining the moisture distribution in oil-paper insulation under different temperature fields, the system implementing the method as described in any one of claims 1-7, characterized in that, include: The oil-paper insulation status assessment module is used to establish a physical model of the oil-paper insulation and calculate the insulation performance index of the oil-paper insulation based on historical operating data and the physical model. The moisture distribution measurement module is used to analyze the distribution of moisture in the oil-paper insulation. If the deviation between the moisture distribution and the expected distribution is greater than the first threshold, the detection or processing strategy will be adjusted. The insulation performance optimization module is used to end the test when the insulation performance of all oil-paper insulations reaches the predetermined standard. Otherwise, after the initial moisture distribution measurement step, if the insulation performance of the area where the deviation between the moisture distribution and the expected distribution is less than or equal to the first threshold is not optimized, the test returns to the moisture distribution measurement step.

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