UHV (extra-high voltage) fitting size parameter optimization method based on altitude correction

Abstract

The invention discloses an extra-high voltage fitting size parameter optimization method based on altitude correction, and relates to the technical field of high-altitude electrical design, and the method comprises the steps: collecting microclimate dynamic data, carrying out the preprocessing, obtaining a key climate parameter set, and analyzing a glacier reduction rate through a Landsat satellite multi-temporal remote sensing image; calculating an equivalent altitude attenuation amount according to the glacier shrinkage rate, combining the equivalent altitude attenuation amount with the microclimate correction size, and obtaining a final optimization size through an altitude-size mapping relation; according to the final optimization size, processing and manufacturing a voltage-sharing ball sample, performing two-stage test to generate a test data set, and performing deviation analysis on the test data set to generate a quantitative analysis data set; and based on the quantitative analysis data set, dynamically correcting the microclimate weight coefficient and the glacier shrinkage compensation coefficient, obtaining an updated dynamic optimization coefficient library, optimizing the size parameters according to the updated dynamic optimization coefficient library, and generating a size parameter optimization report.

Description

Technical Field

[0001] This invention relates to electrical digital data processing, and more specifically to the field of high-altitude electrical design technology, specifically to a method for optimizing the size parameters of ultra-high voltage fittings based on altitude correction. Background Technology

[0002] In ultra-high voltage direct current (UHVDC) transmission projects, fittings serve as critical supporting components and also involve electrical digital data processing. Their dimensional design must comprehensively consider electric field distribution, mechanical strength, and environmental adaptability. In areas with altitudes above 2000 meters, reduced air density leads to a decrease in the corona induction field strength. Traditional design methods linearly correct the minimum curvature radius of fittings based on the altitude correction coefficient of national standards. This new method determines benchmark parameters through static mapping relationships combined with empirical engineering formulas and verifies design reliability through full-scale testing. The existing technological system has formed a comprehensive altitude-graded correction framework, providing a fundamental design basis for UHVDC projects in high-altitude areas.

[0003] However, there are still two limitations in complex microclimate regions: First, the differential impact of regional climate factors (UV intensity, temperature and humidity fluctuations) on corona characteristics is not quantified, resulting in large fluctuations in the redundancy of fitting dimensions in different climate zones at the same altitude; Second, the dynamic parameters of glacier retreat are not integrated, which cannot reflect the equivalent altitude decay during the operation cycle, affecting the long-term operational reliability. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an altitude-corrected optimization method for the size parameters of ultra-high voltage fittings to address the problem of insufficient adaptability to the multi-parameter coupling effect of microclimate and the influence of long-term geological activities.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, this invention provides a method for optimizing the size parameters of ultra-high voltage fittings based on altitude correction. The method includes: collecting and preprocessing dynamic microclimate data to obtain a set of key climate parameters; analyzing glacier retreat rates using multi-temporal remote sensing images from the Landsat satellite; performing microclimate correction calculations based on the key climate parameter set using a pre-defined microclimate weight coefficient library to obtain microclimate-corrected dimensions; calculating the equivalent altitude attenuation based on the glacier retreat rate and combining the equivalent altitude attenuation with the microclimate-corrected dimensions to obtain the final optimized dimensions through an altitude-size mapping relationship; fabricating and manufacturing uniform pressure sphere specimens based on the final optimized dimensions, conducting two-stage tests to generate a test dataset, and simultaneously performing deviation analysis on the test dataset to generate a quantitative analysis dataset; dynamically correcting the microclimate weight coefficient library and the glacier retreat compensation coefficient based on the quantitative analysis dataset to obtain an updated coefficient library, optimizing the size parameters based on the updated coefficient library, and generating a size parameter optimization report.

[0007] As a preferred embodiment of the ultra-high voltage fitting size parameter optimization method based on altitude correction described in this invention, the microclimate dynamic data includes the measured altitude of the installation location, the annual temperature range, the relative humidity fluctuation range, and the peak ultraviolet intensity. The preprocessing includes data cleaning, outlier removal, and standardization.

[0008] As a preferred embodiment of the altitude-corrected optimization method for UHV fitting dimensions described in this invention, the steps of analyzing glacier retreat rates using multi-temporal remote sensing images from the Landsat satellite are as follows: Acquire multi-temporal remote sensing images from the Landsat satellite; Multispectral band threshold segmentation was performed on Landsat satellite multi-temporal remote sensing images, and the glacier boundary was identified by combining the normalized snow cover index algorithm. Based on the glacier boundary, the change in glacier area between adjacent years is calculated to obtain the glacier retreat rate.

[0009] As a preferred embodiment of the altitude-corrected optimization method for UHV fitting dimensions described in this invention, the steps for obtaining the microclimate-corrected dimensions are as follows: The key climate parameter set is normalized to generate a normalized climate parameter vector, and the microclimate weight coefficient triplet in the preset microclimate weight coefficient library is extracted simultaneously. The weighted linear combination method is used to perform dot product calculation on the normalized climate parameter vector and the triplet of microclimate weight coefficients to output the comprehensive correction coefficient. The current elevation reference size and comprehensive correction coefficient are corrected and calculated using a linear weighted correction method, and the microclimate corrected size is output.

[0010] As a preferred embodiment of the altitude-corrected optimization method for UHV fitting dimensions described in this invention, the steps for obtaining the final optimized dimensions through the altitude-dimensional mapping relationship are as follows: Based on the set operating life of the ultra-high voltage project and combined with the glacier retreat rate, the equivalent altitude attenuation is calculated through the altitude-size mapping relationship; Based on the microclimate-corrected size and the equivalent altitude attenuation, the final optimized size is obtained through the altitude-size mapping relationship.

[0011] As a preferred embodiment of the altitude-corrected optimization method for UHV fitting dimensions described in this invention, the steps for processing and manufacturing the equalizing ball specimen and conducting two-stage tests to generate a test dataset are as follows. Based on the final optimized dimensions, the pressure equalization ball specimen was processed using a five-axis CNC machine tool; The equalizing ball specimen was subjected to microclimate extreme working condition test, and the corona voltage was observed in real time to generate a microclimate extreme working condition test dataset. The equalizing ball specimens were subjected to accelerated aging tests, and the maximum surface electric field was monitored in real time to generate an accelerated aging test performance dataset. Integrate the microclimate extreme condition test dataset and the aging accelerated test performance dataset to generate a test dataset.

[0012] As a preferred embodiment of the method for optimizing the size parameters of UHV fittings based on altitude correction described in this invention, the step of performing deviation analysis on the test dataset to generate a quantitative analysis dataset refers to calculating the corona voltage deviation and the maximum field strength deviation based on the test dataset, and comparing them with the engineering safety margin threshold to generate a quantitative analysis dataset.

[0013] As a preferred embodiment of the altitude-corrected optimization method for UHV fitting dimensions described in this invention, the steps for generating the dimensions optimization report are as follows: Based on the quantitative analysis dataset, the microclimate weight coefficient and glacier retreat compensation coefficient are dynamically adjusted according to the deviation ratio to obtain an updated dynamic optimization coefficient library. The updated dynamic optimization coefficient library and normalized climate parameter vector are combined, and the comprehensive correction coefficient is recalculated through a weighted combination algorithm. The optimized size parameters are obtained based on the altitude-size mapping relationship. The optimized dimensional parameters, the quantitative analysis dataset, and the updated dynamic optimization coefficient library are fused together to generate a dimensional parameter optimization report.

[0014] In a second aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the method for optimizing the size parameters of ultra-high voltage fittings based on altitude correction as described in the first aspect of the present invention.

[0015] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the method for optimizing the size parameters of ultra-high voltage fittings based on altitude correction as described in the first aspect of the present invention.

[0016] The beneficial effects of this invention are as follows: By adjusting the parameters of the coefficient library in real time based on the deviation analysis results of the experimental dataset, the adaptive matching between microclimate influencing factors and long-term geological activities is achieved, solving the dynamic adaptation problem under complex environments and ensuring that the size correction model continuously closely matches the actual working conditions; by integrating the retreat rate analyzed by satellite and the engineering operation years, and combining the glacier compensation coefficient to generate the equivalent altitude attenuation, the problem of implicit altitude changes caused by glacier retreat is solved, ensuring the electric field stability of the fittings throughout their entire life cycle. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a method for optimizing the size parameters of UHV fittings based on altitude correction.

[0019] Figure 2 A flowchart for analyzing glacier retreat rates.

[0020] Figure 3 A flowchart for obtaining microclimate correction dimensions.

[0021] Figure 4 This is a flowchart of the manufacturing and testing of equalizing pressure ball samples. Detailed Implementation

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0025] Reference Figures 1-4 The high-voltage engineering and mechanical design of this invention falls under the category of electrical digital data processing. As one embodiment of this invention, this embodiment provides a method for optimizing the dimensional parameters of ultra-high voltage fittings based on altitude correction, comprising the following steps: S1. Collect and preprocess dynamic microclimate data to obtain a set of key climate parameters, and analyze the glacier retreat rate using multi-temporal remote sensing images from the Landsat satellite. Microclimate dynamic data include measured elevation of the installation location, annual temperature range, relative humidity fluctuation range, and peak UV intensity. It should be noted that the measured altitude of the installation location was obtained by measuring the converter station coordinates on-site with a GNSS positioning instrument and combining it with the elevation data published by the State Bureau of Surveying and Mapping; the annual temperature range was extracted from the difference between the highest and lowest temperatures based on continuous monitoring data from the on-site meteorological station throughout the year; the relative humidity fluctuation range was extracted from the difference between the maximum and minimum humidity based on data collected throughout the year by a capacitive humidity sensor; and the peak ultraviolet intensity was the maximum value obtained by converting the measured ultraviolet A-band and B-band radiation intensities into the standard ultraviolet index using a professional ultraviolet radiation measuring instrument in accordance with the World Health Organization standards. Preprocessing includes data cleaning, outlier removal, and standardization. It should be noted that data cleaning refers to standardizing the format of microclimate dynamic data, filling in missing values, and correcting obvious errors to ensure that the data is complete and usable; outlier removal refers to identifying and deleting extreme data that exceed a reasonable range through statistical methods (such as the 3σ principle); standardization refers to converting microclimate dynamic data of different dimensions into dimensionless values ​​to eliminate the impact of differences in magnitude on calculations. Multitemporal remote sensing images from the Landsat satellite were acquired using a multispectral scanner. Furthermore, the Landsat satellite's multispectral scanner scans the target area (a specific geographical area along the UHV project where glacier changes need to be monitored) according to a preset orbital cycle, simultaneously recording visible light, near-infrared, and thermal infrared data to generate raw digital images. The ground receiving station performs radiometric calibration and atmospheric correction on the raw digital images to eliminate sensor noise and atmospheric scattering effects, outputting pre-processed standardized images. Specialized remote sensing software is used to perform geometric precision correction on the pre-processed standardized images to ensure accurate matching of pixel spatial positions at different time phases, generating Landsat satellite multi-temporal remote sensing images with a unified coordinate system. It should be noted that the preset orbit period is calculated based on the sun-synchronous orbit altitude of the Landsat satellite and the Earth's rotation period in order to ensure repeated observations with global coverage; professional remote sensing software refers to tools with multispectral image processing capabilities (such as ENVI software, i.e., environmental and natural resource analysis software), which can directly perform geometric correction on remote sensing images through ground control points to eliminate projection distortion and terrain displacement errors; Multispectral band threshold segmentation was performed on Landsat satellite multi-temporal remote sensing images, and the glacier boundary was identified by combining the normalized snow cover index algorithm. Furthermore, firstly, visible light (blue, green, and red bands) and shortwave infrared bands are extracted from Landsat satellite multi-temporal remote sensing images, and reflectance values ​​are determined pixel by pixel to generate a multispectral band reflectance dataset. Secondly, based on the multispectral band reflectance dataset, preliminary coarse segmentation of snow and ice cover areas is performed by setting reflectance thresholds: if the reflectance value of a pixel in the shortwave infrared band is >0.3, it is marked as a candidate area for snow and ice cover; otherwise, it is marked as a non-snow and ice cover area, and a two-dimensional label matrix is ​​output. Then, the two-dimensional label matrix is ​​directly written into a GeoTIFF (geotag image file format) file, and the geographic coordinate information of the original digital image is inherited to generate a binary raster map with spatial reference, in which pixels in the snow and ice cover candidate area are assigned a value of 1, and pixels in the non-snow and ice cover area are assigned a value of 0, generating a preliminary snow and ice cover binary map. Then, pixels with an area less than 10 pixels in the preliminary snow and ice cover binary map (based on Landsat) are removed. Isolated noise points (defined as the smallest glacier unit of 300 square meters at 30-meter resolution) are identified, and an optimized binary map of snow and ice cover is output. The optimized binary map of snow and ice cover and the multispectral reflectance dataset are then substituted into the normalized snow cover index standard formula to calculate the normalized snow cover index. Pixels with a normalized snow cover index value > 0.4 in the glacier probability distribution map (because measured data shows that glaciers have the highest distinguishability from other land features at this index) are selected as glacier candidate areas. At the same time, digital elevation data is used to remove interference from low-altitude seasonal snow cover. Finally, a 3×3 pixel circular structural element is used to first expand the glacier probability distribution map to extend the boundary, and then an erosion operation is performed to restore the original state. Through the superposition effect of expansion and erosion, holes with an area of ​​less than 10 pixels are eliminated, generating a continuous glacier boundary. It should be noted that the reflectivity threshold is set based on the typical reflectivity characteristics of ice and snow in the shortwave infrared band, with an exemplary value range of (0.3~0.5). Pixels in ice and snow candidate areas are assigned a value of 1, while pixels in non-ice and snow areas are assigned a value of 0. This is a binary encoding of the spatially referenced binary raster map. Setting the pixel value of ice and snow areas to 1 enables seamless compatibility with GIS (Geographic Information System), while setting the pixel value of non-ice and snow areas to 0 facilitates subsequent morphological operations. Digital elevation data is surface elevation information obtained through airborne lidar scanning. Based on the glacier boundary, calculate the change in glacier area between adjacent years to obtain the glacier retreat rate; Furthermore, firstly, GIS is used to filter the continuous glacier boundaries over time to extract glacier boundary vector layers for adjacent years (e.g., 2022 and 2023). The coordinate system of the glacier boundary vectors for adjacent years is standardized to WGS84, outputting a spatially aligned boundary dataset. Secondly, symmetric difference is achieved through GIS spatial overlay analysis. Further, an XOR operation is performed on the spatially aligned boundary dataset, followed by multispectral image-assisted verification and automatic error correction using topological rules to eliminate geometric inconsistencies (such as holes, overlaps, or gaps) in the glacier change polygons generated by the XOR operation, ensuring boundary closure and attribute consistency. This generates polygon layers representing the glacier change areas of the two periods. Spatial area calculation and difference analysis are then performed on these polygon layers. The process involves several steps: First, an area change polygon is output. Based on this polygon, the area difference between two glacier change periods is calculated using the polygon area algebraic difference method to obtain the area change. Then, the area and perimeter attributes of the original glacier boundary are extracted using a combination of manual digitization and analytical geometry. These are then substituted into the equivalent front width formula to calculate the average width of the glacier front, outputting the average front width parameter. Next, the area change and the average front width parameter are converted into a line retreat rate using the area-line retreat conversion method. Finally, digital elevation data is used to perform terrain filtering on the line retreat rate, removing interference signals from areas with slopes greater than a fixed angle (e.g., slopes > 30°, where glacier mobility is extremely low and prone to ice avalanches or surface erosion, leading to distorted retreat rate data), outputting an effective glacier retreat rate. It should be noted that topological rules are defined based on the geometric and logical relationships of spatial data and include the following core constraints: closure, non-overlap, connectivity, and inclusion.

[0026] S2. Based on the key climate parameter set, call the preset microclimate weight coefficient library to perform microclimate correction calculation and obtain the microclimate correction size; The key climate parameter set is normalized to generate a normalized climate parameter vector, and the microclimate weight coefficient triplet in the preset microclimate weight coefficient library is extracted simultaneously. Furthermore, each parameter in the key climate parameter set (temperature range, humidity fluctuation, and UV peak) is standardized and converted to its corresponding benchmark value (30℃, 50%, and level 8) to eliminate dimensional differences and generate a normalized climate parameter vector. Based on the measured elevation of the engineering point (e.g., 4300 meters), the corresponding elevation range (4000-4500 meters) in the preset microclimate weight coefficient library is matched. Then, the three sets of weight coefficients (e.g., [0.41, 0.19, 0.40]) of temperature range, humidity fluctuation, and UV intensity, calibrated by multiple regression analysis, are extracted within this range and output as a microclimate weight coefficient triplet. It should be noted that the benchmark values ​​for each parameter are obtained by querying the fixed values ​​specified in the national standards: the benchmark value for temperature range is 30℃, the benchmark value for humidity fluctuation is 50%, and the benchmark value for ultraviolet peak is level 8; the measured elevation of the engineering point is an accurate elevation value obtained by combining GNSS-RTK differential positioning technology (Global Navigation Satellite System real-time dynamic differential positioning technology) with the national elevation benchmark network; the preset microclimate weight coefficient library is a database established based on historical engineering measured data and climate parameter regression analysis, containing three sets of weight coefficients for temperature range, humidity fluctuation, and ultraviolet intensity (e.g., temperature coefficient 0.38, humidity coefficient 0.25, ultraviolet coefficient 0.37). The weighted linear combination method is used to perform dot product calculation on the normalized climate parameter vector and the triplet of microclimate weight coefficients to output the comprehensive correction coefficient. Furthermore, the normalized climate parameter vector and the microclimate weight coefficient triplet are first strictly paired according to parameter type to generate parameter-coefficient pairs, which are then input into the weighted linear formula. Multiplication is performed on each parameter-coefficient pair to obtain the product of temperature, humidity, and ultraviolet radiation, and the three-term product is output. Then, the three-term product results are algebraically summed to obtain the uncorrected comprehensive value. Finally, the uncorrected comprehensive value is constrained in the interval [0,1]. If the result is less than 0, the comprehensive correction coefficient is output as 0; if it is greater than 1, the comprehensive correction coefficient is output as 1, ensuring that the final comprehensive correction coefficient conforms to the physical meaning. The current elevation reference size and comprehensive correction coefficient are corrected and calculated using a linear weighted correction method, and the microclimate corrected size is output. Furthermore, based on the measured elevation of the engineering points, the elevation interval search function (e.g., 4300m belongs to the 4000-4500m interval) is used to query the benchmark dimensions corresponding to the measured elevation of the engineering points; then, the current elevation benchmark dimensions and the comprehensive correction coefficient are input into the linear weighted formula to perform dimension compensation calculation and generate preliminary microclimate correction dimensions; finally, the preliminary microclimate correction dimensions are checked for engineering compliance. If they meet the design requirements, the final result is output; otherwise, an alarm is triggered and the calculation is returned to recalculate, and the final verified microclimate correction dimensions are output. It should be noted that the current altitude reference dimensions are empirical values ​​derived from long-term engineering practice and accumulated data on the operation of UHV equipment in high-altitude areas. Specifically, they are the corresponding reference radius of curvature matched to the measured altitude of the installation location (e.g., 4300 meters) (e.g., for ±800kV projects, the reference value is 500mm in the altitude range of 4000-4500 meters). The design requirements are defined according to the UHV fitting design specifications, including minimum size thresholds (exemplary range: (450-600mm), to balance material cost and structural reliability), surface radius of curvature tolerances, and material strength verification indicators.

[0027] S3. Calculate the equivalent elevation reduction based on the glacier retreat rate, and combine the equivalent elevation reduction with the microclimate correction size to obtain the final optimized size through the elevation-size mapping relationship. Based on the set operating life of the ultra-high voltage project and combined with the glacier retreat rate, the equivalent altitude attenuation is calculated through the altitude-size mapping relationship; The expression for calculating the equivalent altitude reduction is: ; in, It is the equivalent altitude reduction; This refers to the corrected glacier retreat compensation coefficient. Indicates "new" (after correction), used to distinguish the glacier retreat compensation coefficient before and after correction; It is the rate of glacier retreat; It refers to the operational lifespan of the project; Furthermore, firstly, the planned service life (e.g., 30 years for ±800kV projects) is extracted from the UHV project design data, and the specific service life value is output; secondly, the annual glacier retreat distance data verified by field experience is extracted (e.g., 1.5 meters retreat per year in a certain region), and the annual retreat amount is output; thirdly, the fixed proportional coefficient of 0.002 for the altitude-size mapping relationship is extracted, and the fixed proportion of 0.002 km altitude reduction corresponding to each meter of glacier retreat is determined, and the conversion proportion is output; then, the service life, annual retreat amount, and conversion proportion are multiplied together to output the equivalent altitude reduction; finally, it is checked whether the equivalent altitude reduction is within the allowable range of the project. If it meets the requirements, the final altitude reduction is output for subsequent design; if it exceeds the allowable range of the project, a warning is issued and the input data is rechecked, and the verified equivalent altitude reduction is output. It should be noted that the set service life of UHV projects is determined according to the design life standard of power equipment, usually 30 years; the altitude-size mapping relationship is set based on the influence of gas density change on the corona initiation field strength, including the reference size, altitude correction, and fixed proportional coefficient 0.002 (i.e., each meter of glacier retreat is equivalent to a decrease in altitude of 0.002 kilometers, or 2 meters); the allowable range of the project is set as ±50 meters of equivalent altitude attenuation, which is derived from 20 years of operation data of UHV projects. This is to ensure that after the hardware size is corrected, the design safety margin requirements of corona initiation voltage ≥ 1.1 times the rated voltage (e.g., ≥ 880kV for ±800kV projects) and surface field strength ≤ 25kV / cm are still met. Based on the microclimate-corrected size and the equivalent altitude attenuation, the final optimized size is obtained through the altitude-size mapping relationship; Furthermore, the validated microclimate correction size and equivalent altitude attenuation are first invoked, and the scaling factor of the altitude-size mapping relationship is extracted. The scaling factor of 0.002 is determined for every 1 kilometer change in altitude. Then, the validated microclimate correction size, equivalent altitude attenuation, and scaling factor of 0.002 are input into the calculation formula to perform preliminary compensation calculation and output the original optimized size. Finally, the original optimized size is verified to see if it meets the engineering design threshold. If the original optimized size is less than the minimum allowable value of the engineering design threshold, the deviation between the original optimized size and the engineering design threshold is compared, and the process returns to the microclimate correction or altitude attenuation calculation stage for re-verification. If it is within the engineering design threshold, the final optimized size is output. It should be noted that the engineering design threshold is defined based on the surface field strength control requirements and material strength standards of UHV fittings, with an exemplary range of 450-600 mm.

[0028] S4. Based on the final optimized dimensions, process and manufacture equalizing ball test specimens, conduct two-stage tests, generate test datasets, and perform deviation analysis on the test datasets to generate quantitative analysis datasets. Based on the final optimized dimensions, the pressure equalization ball specimen was processed using a five-axis CNC machine tool; Furthermore, the final optimized dimensions are first input into the engineering drawings, and the radius of curvature and tolerance dimensions are marked. Then, according to the engineering drawings, the machining parameters are manually set using the machine tool operation panel. Next, through the programming interface of the modern five-axis CNC machine tool, code instructions are written line by line according to the point coordinates to generate a five-axis linkage machining path. After conversion by the post-processor, a CNC machining program that can be executed by the five-axis CNC machine tool is generated, which includes X / Y / Z / A / B five-axis coordinates. 6061-T6 aluminum alloy blanks are selected and fixed on the worktable with special fixtures to output the positioned blanks. The positioned blanks and CNC machining programs are input into the machine tool, and roughing and finishing are performed in sequence to output semi-finished equalizing balls. Finally, a laser scanner is used to detect the dimensions of the semi-finished equalizing balls. The semi-finished equalizing balls that meet the size requirements are sandblasted to output equalizing ball test samples. The equalizing ball specimen was subjected to microclimate extreme working condition test, and the corona voltage was observed in real time to generate a microclimate extreme working condition test dataset. Furthermore, the equalizing sphere test specimen was first installed on the artificial climate chamber test rack. After cleaning with anhydrous ethanol and resting for 24 hours (based on actual measurements, the shortest time required for the residual charge on the surface of the ±800kV fitting test specimen to decay after cleaning with anhydrous ethanol is 22 hours, and 24 hours is taken as the standard resting period) to eliminate assembly stress, the output test specimen was stabilized. Then, based on the historical extreme meteorological data of the project location (obtained through long-term monitoring by the National Meteorological Administration's ground observation station and the fusion of satellite remote sensing data, specifically including parameters such as maximum temperature, minimum humidity, and UV index), environmental parameters (such as maximum temperature 45℃, minimum humidity 10%, and UV index 14) were set, and precisely adjusted to the set values ​​using a temperature and humidity controller and a UV radiometer. Next, the negative terminal of the ±800kV DC power supply was connected to the high-voltage end of the equalizing sphere test specimen, and the positive terminal was grounded. The voltage was gradually increased from 0kV at a rate of 2kV / s, while a UV imager was used. The field strength probe monitors the surface discharge and electric field strength of the test specimen in real time, ultimately forming a standardized test environment that includes extreme climatic conditions, a high-voltage electric field (880kV), and real-time monitoring equipment. The test is then conducted: starting from 0kV, the voltage is increased, and the number of photons on the test specimen surface is monitored in real time using an ultraviolet imager. When the number of photons on the test specimen surface suddenly increases by ≥50% (the sudden change in photon count must significantly exceed the background noise), it is recorded as the corona initiation voltage, and a voltage-photon count curve dataset is output. The test environment is maintained stably for 30 minutes at 1.1 times the rated voltage (i.e., 880kV, which is the upper limit of long-term operating voltage to ensure insulation margin) (to verify the short-term stability of the equipment under extreme conditions). The maximum surface field strength is recorded every minute using a field strength sensor array, and field strength-time series data is output. Finally, the voltage-photon count curve dataset, field strength-time series data, and environmental parameters are merged to generate a structured microclimate extreme condition test dataset. It should be noted that extreme microclimate conditions refer to the extreme test conditions set based on historical extreme meteorological data of the location of the UHV project (such as a maximum temperature of 40°C, humidity of 95%, and UV index of 12). The equalizing ball specimens were subjected to accelerated aging tests, and the maximum surface electric field was monitored in real time to generate an accelerated aging test performance dataset. Furthermore, firstly, the uniform pressure ball specimens that have completed the microclimate extreme condition test are placed in a constant temperature and humidity chamber to eliminate residual charge, and the neutralized uniform pressure ball specimens are output. Then, the glacier retreat rate and acceleration factor are input into the salt spray concentration calculation formula to obtain the salt spray concentration, and the glacier retreat rate and temperature cycle coefficient are input into the temperature parameter calculation formula to obtain the temperature cycle parameters. Next, the salt spray concentration and temperature cycle parameters are aligned along the time axis to generate a time-series task table. The salt spray spray cycle is dynamically adjusted according to the glacier retreat rate (e.g., a retreat rate of 1.5 meters / year corresponds to 3 sprays per day), and the total number of cycles is set according to the engineering operation years (e.g., 30-year equivalent aging = 30 days × 20 times acceleration). Then, it is integrated into a test instruction set containing three elements: concentration gradient, temperature change rate, and number of cycles. Finally, the instruction set is loaded through the aging test chamber control software to generate a standardized aging test plan. The neutralized uniform pressure ball specimens are then placed... The test chamber is equipped with environmental parameters configured according to a standardized aging test protocol and connected to an electric field monitoring probe. The test environment is then continuously run for 30 days (simulating 30 years of natural aging effect, with an acceleration factor of 20 times × 30 days ≈ 25 years of equivalent aging). The maximum surface electric field and salt spray deposition are collected in real time using the electric field monitoring probe to obtain environmental parameters and output an electric field-time series dataset. The aging process is interrupted daily, and a rated voltage (e.g., ±800kV) is applied to the neutralized, pressure-equalizing ball sample. The RIV (radio interference voltage) in the effective frequency band (e.g., 1MHz to 10MHz) is measured in real time, and an RIV-aging days relationship dataset is output. Finally, the electric field-time series dataset, the RIV-aging days relationship dataset, and the environmental parameters are used to calculate the electric field attenuation rate and RIV change using the weighted least squares method to generate an accelerated aging test performance dataset. It should be noted that the acceleration factor is set based on the engineering equivalent aging principle. The exemplary value range is (5 to 20 times). 1 times corresponds to the natural aging rate, that is, no acceleration. 5 to 20 times is achieved by strengthening stress (such as increasing salt spray concentration and intensifying temperature cycling) to compress the 1-year aging effect in the laboratory to be completed within 2.4 to 0.3 months. Integrate the microclimate extreme condition test dataset and the aging accelerated test performance dataset to generate a test dataset; Furthermore, firstly, the corona initiation voltage in the microclimate extreme condition test dataset and the RIV in the aging accelerated test performance dataset are uniformly converted to volt units and timestamped to generate a standardized preprocessed subset of the test data. Then, the corona initiation voltage and maximum field strength are extracted from the standardized preprocessed subset of the test data, outputting corona characteristic parameters. Simultaneously, the field strength decay rate and RIV change are extracted from the aging accelerated test performance dataset, outputting aging performance parameters. The corona characteristic parameters and aging performance parameters are then integrated into a structured feature parameter table. Next, the temperature, humidity, and UV lamp intensity recorded in the microclimate extreme condition test are merged with the salt spray concentration and temperature cycling parameters obtained from the aging accelerated test to generate a complete environmental parameter matrix. Then, the structured feature parameter table and the complete environmental parameter matrix are spatiotemporally correlated and aligned to generate a spatiotemporally correlated dataset with topological tags. Finally, the spatiotemporally correlated dataset is validated according to logical rules. If the validation fails, it is marked as abnormal data, and the original records are manually checked and corrected before re-analysis. If the validation passes, the validated data is packaged into a test dataset according to ISO standards. It should be noted that the logical rules refer to a field strength attenuation rate ≤10% (based on 10 years of operation data of ±800kV project; when the field strength attenuation exceeds 10%, the insulation failure rate increases by 5 times), and an RIV change ≤100μV (to prevent radio interference voltage from exceeding the allowable limit of power equipment; actual measurements show that when the RIV exceeds 100μV, the signal-to-noise ratio of nearby communication equipment decreases); the original records refer to the unprocessed data directly collected during the two-stage test (such as the number of photons on the surface of the test specimen recorded in real time by the ultraviolet imager in the microclimate extreme working condition test, and the daily measurement of salt spray deposition during the accelerated aging test). Based on the experimental dataset, the corona voltage deviation and maximum field strength deviation are calculated and compared with the engineering safety margin threshold to generate a quantitative analysis dataset. The expression for calculating the corona voltage deviation is: ; in, It is the relative deviation of the corona voltage; It is the measured corona initiation voltage; It is the theoretical corona voltage; The expression for calculating the maximum field strength deviation is: ; in, It is the maximum field strength deviation; It is the theoretical limit of the field strength; It is the measured maximum electric field strength; Furthermore, the corona initiation voltage and maximum field strength values ​​are first extracted from the verified test dataset. Then, based on the current engineering voltage level and altitude classification, the corresponding theoretical corona voltage (1.1 times the rated voltage at the end of the microclimate extreme condition test, e.g., 880kV for ±800kV projects) and maximum field strength limit are queried. Next, the corona initiation voltage and theoretical corona voltage are substituted into the deviation calculation formula to calculate the corona voltage deviation. Simultaneously, the maximum field strength value and maximum field strength limit are substituted into the deviation calculation formula to calculate the maximum field strength deviation. Then, the calculated corona voltage deviation and maximum field strength deviation are compared with the engineering safety margin threshold. If they are within the engineering safety margin threshold, they are marked as "qualified"; if they exceed the engineering safety margin threshold, they are marked as "exceeding the standard," and the exceeding standard marking result is output. The exceeding standard marking result, corona voltage deviation, and maximum field strength deviation are integrated according to ISO 10303-28 standard to generate a quantitative analysis dataset. It should be noted that the engineering safety margin threshold is set by the state according to the requirements for safe operation of high-voltage equipment. In order to ensure that the corona does not exceed the standard and the materials do not deteriorate, it includes the relative deviation threshold of corona voltage (exemplary value range: ≤3%, which is to ensure the reliability of corona extinction) and the absolute deviation threshold of field strength (exemplary value range: ≤0.5kV / cm, which is to control the field strength safety margin).

[0029] S5. Based on the quantitative analysis dataset, dynamically correct the microclimate weight coefficient and glacier retreat compensation coefficient, obtain the updated dynamic optimization coefficient library, optimize the size parameters according to the updated dynamic optimization coefficient library, and generate a size parameter optimization report. Based on the quantitative analysis dataset, the microclimate weight coefficient and glacier retreat compensation coefficient are dynamically adjusted according to the deviation ratio to obtain an updated dynamic optimization coefficient library. Furthermore, firstly, corona voltage deviation and maximum field strength deviation are extracted from the quantitative analysis dataset. The corona voltage deviation proportionality coefficient is obtained by comparing the ratio of the corona voltage deviation to the relative corona voltage deviation threshold. Simultaneously, the maximum field strength deviation proportionality coefficient is obtained by comparing the ratio of the maximum field strength deviation to the absolute field strength deviation threshold. Next, rule matching is performed based on the corona voltage deviation proportionality coefficient and the maximum field strength deviation proportionality coefficient. If the corona voltage deviation proportionality coefficient > 0.8 (when the corona voltage deviation exceeds 3% of the theoretical corona voltage value (i.e., proportionality coefficient = 0.03 / 0.038 ≈ 0.8), the humidity influence needs to be corrected), the humidity in the climate chamber is adjusted downwards using a logarithmic correction formula to obtain the corrected microclimate humidity weighting coefficient. If the maximum field strength deviation proportionality coefficient > 1 (when the field strength deviation exceeds the limit of 0.5 kV / cm (i.e., proportionality coefficient...), the humidity is adjusted downwards using a logarithmic correction formula. When the coefficient is 0.5 / 0.5=1, it is determined that the glacier retreat compensation is insufficient and the coefficient needs to be adjusted upward. Then, the original glacier compensation coefficient is adjusted upward according to the linear compensation formula, and the corrected glacier retreat compensation coefficient is output. The corrected microclimate humidity weight coefficient and the corrected glacier retreat compensation coefficient are weighted and superimposed according to the engineering voltage level (±800kV) and altitude (4300m) to generate a joint correction coefficient. Finally, the joint correction coefficient is compared with the original parameters in the historical version coefficient library. If the change of the joint correction coefficient exceeds 5% (based on the statistical data of the ±800kV project, a 5% change in the joint correction coefficient corresponds to a hardware size correction of ±2.5mm, which is the critical value allowed by the design tolerance), a new version coefficient library is automatically generated, and the correction time, triggering conditions and related test data numbers are recorded synchronously to form an updated dynamic optimization coefficient library. It should be noted that the original glacier compensation coefficient is an empirical value derived from fitting the measured relationship between glacier retreat rate and altitude attenuation in historical engineering data. For new projects, the industry typical value of 0.002 (determined through statistical analysis of long-term observation data from the Qinghai-Tibet Plateau) is adopted. The updated dynamic optimization coefficient library and normalized climate parameter vector are combined, and the comprehensive correction coefficient is recalculated through a weighted combination algorithm. The optimized size parameters are obtained based on the altitude-size mapping relationship. Furthermore, firstly, microclimate weight coefficients (including temperature coefficient, corrected humidity coefficient, and ultraviolet coefficient) are extracted from the updated dynamic optimization coefficient library, and a coefficient set is output. Simultaneously, a normalized climate parameter vector is loaded. Next, the coefficient set and the normalized climate parameter vector are strictly paired according to parameter type to generate parameter-coefficient pairs. Then, a weighted combination algorithm is used to re-perform the dot product calculation to obtain the comprehensive correction coefficient. Next, the obtained glacier retreat compensation coefficient, glacier retreat rate, and operating years are input into the linear attenuation formula, and the equivalent altitude attenuation is multiplied again to obtain the equivalent altitude attenuation. Finally, the comprehensive correction coefficient and equivalent altitude attenuation are re-performed according to the altitude-size mapping relationship to output the optimized size parameters. The optimized size parameters are then checked again to ensure they meet the minimum size threshold in the design requirements. If the check fails, the system returns to the updated dynamic optimization coefficient library for correction and recalculation. If the check passes, the final verified optimized size parameters are output. The optimized dimensional parameters, the quantitative analysis dataset, and the updated dynamic optimization coefficient library are fused together to generate a dimensional parameter optimization report. Furthermore, the final verified optimized size parameters, quantitative analysis dataset, and updated dynamic optimization coefficient library are aligned and matched according to the test timestamp and project number to ensure that the time sequence of the data and the project affiliation are consistent. The data is then organized in a standard format to generate a size parameter optimization report containing the original size, optimized size, deviation correction effect, and coefficient adjustment records.

[0030] This embodiment also provides a computer device applicable to the method for optimizing the size parameters of UHV fittings based on altitude correction, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the method for optimizing the size parameters of UHV fittings based on altitude correction as proposed in the above embodiment.

[0031] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0032] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the method for optimizing the size parameters of ultra-high voltage fittings based on altitude correction as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0033] In summary, this invention achieves adaptive matching between microclimate influencing factors and long-term geological activities by adjusting coefficient library parameters in real time based on deviation analysis results of experimental datasets, thus solving the dynamic adaptation problem in complex environments and ensuring that the size correction model continuously closely matches actual working conditions. By fusing the retreat rate obtained from satellite analysis with the engineering operation period and combining it with the glacier compensation coefficient to generate an equivalent altitude reduction, this invention solves the problem of implicit altitude changes caused by glacier retreat and ensures the electric field stability of the fittings throughout their entire life cycle.

[0034] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing the dimensional parameters of ultra-high voltage fittings based on altitude correction, characterized in that: include, Collect and preprocess dynamic microclimate data to obtain a set of key climate parameters, and analyze the glacier retreat rate using multi-temporal remote sensing images from the Landsat satellite. Based on the key climate parameter set, the microclimate correction calculation is performed by calling the preset microclimate weight coefficient library to obtain the microclimate correction size; Based on the glacier retreat rate, the equivalent elevation reduction is calculated, and the equivalent elevation reduction is combined with the microclimate correction size. The final optimized size is obtained through the elevation-size mapping relationship. Based on the final optimized dimensions, pressure equalization ball specimens are manufactured and subjected to two-stage tests to generate test datasets. Simultaneously, deviation analysis is performed on the test datasets to generate quantitative analysis datasets. Based on the quantitative analysis dataset, the microclimate weight coefficient and glacier retreat compensation coefficient are dynamically adjusted to obtain an updated dynamic optimization coefficient library. The size parameters are then optimized according to the updated dynamic optimization coefficient library, and a size parameter optimization report is generated.

2. The method for optimizing the dimensional parameters of UHV fittings based on altitude correction as described in claim 1, characterized in that: The microclimate dynamic data includes the measured elevation of the installation location, the annual temperature range, the relative humidity fluctuation range, and the peak ultraviolet intensity. The preprocessing includes data cleaning, outlier removal, and standardization.

3. The method for optimizing the dimensional parameters of UHV fittings based on altitude correction as described in claim 1, characterized in that: The steps for analyzing glacier retreat rates using multi-temporal remote sensing images from the Landsat satellite are as follows: Acquire multi-temporal remote sensing images from the Landsat satellite; Multispectral band threshold segmentation was performed on Landsat satellite multi-temporal remote sensing images, and the glacier boundary was identified by combining the normalized snow cover index algorithm. Based on the glacier boundary, the change in glacier area between adjacent years is calculated to obtain the glacier retreat rate.

4. The method for optimizing the dimensional parameters of UHV fittings based on altitude correction as described in claim 1, characterized in that: The steps for obtaining the microclimate correction dimensions are as follows: The key climate parameter set is normalized to generate a normalized climate parameter vector, and the microclimate weight coefficient triplet in the preset microclimate weight coefficient library is extracted simultaneously. The weighted linear combination method is used to perform dot product calculation on the normalized climate parameter vector and the triplet of microclimate weight coefficients to output the comprehensive correction coefficient. The current elevation reference size and comprehensive correction coefficient are corrected and calculated using a linear weighted correction method, and the microclimate corrected size is output.

5. The method for optimizing the dimensional parameters of UHV fittings based on altitude correction as described in claim 1, characterized in that: The steps for obtaining the final optimized size through the altitude-size mapping relationship are as follows: Based on the set operating life of the ultra-high voltage project and combined with the glacier retreat rate, the equivalent altitude attenuation is calculated through the altitude-size mapping relationship; Based on the microclimate-corrected size and the equivalent altitude attenuation, the final optimized size is obtained through the altitude-size mapping relationship.

6. The method for optimizing the dimensional parameters of UHV fittings based on altitude correction as described in claim 1, characterized in that: The process of manufacturing equalizing ball test specimens and conducting two-stage tests to generate test datasets is as follows. Based on the final optimized dimensions, the pressure equalization ball specimen was processed using a five-axis CNC machine tool; The equalizing ball specimen was subjected to microclimate extreme working condition test, and the corona voltage was observed in real time to generate a microclimate extreme working condition test dataset. The equalizing ball specimens were subjected to accelerated aging tests, and the maximum surface electric field was monitored in real time to generate an accelerated aging test performance dataset. Integrate the microclimate extreme condition test dataset and the aging accelerated test performance dataset to generate a test dataset.

7. The method for optimizing the dimensional parameters of UHV fittings based on altitude correction as described in claim 1, characterized in that: The aforementioned deviation analysis of the test dataset to generate a quantitative analysis dataset refers to calculating the corona voltage deviation and the maximum field strength deviation based on the test dataset, and comparing them with the engineering safety margin threshold to generate a quantitative analysis dataset.

8. The method for optimizing the dimensional parameters of UHV fittings based on altitude correction as described in claim 1, characterized in that: The steps for generating the size parameter optimization report are as follows: Based on the quantitative analysis dataset, the microclimate weight coefficient and glacier retreat compensation coefficient are dynamically adjusted according to the deviation ratio to obtain an updated dynamic optimization coefficient library. The updated dynamic optimization coefficient library and normalized climate parameter vector are combined, and the comprehensive correction coefficient is recalculated through a weighted combination algorithm. The optimized size parameters are obtained based on the altitude-size mapping relationship. The optimized dimensional parameters, the quantitative analysis dataset, and the updated dynamic optimization coefficient library are fused together to generate a dimensional parameter optimization report.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the method for optimizing the size parameters of ultra-high voltage fittings based on altitude correction as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for optimizing the size parameters of ultra-high voltage fittings based on altitude correction as described in any one of claims 1 to 8.

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