Engineering quantity metering method based on electric power construction supervision project

Abstract

The invention provides an electric power construction supervision project-based project quantity metering method, which comprises the following steps of: acquiring geographic coordinate data of an extra-high voltage tower footing position, and extracting topographic and geomorphic diversity characteristics and soil type difference information from the geographic coordinate data through satellite remote sensing image processing, carrying out overlay analysis through a geographic information system to obtain an extra-high voltage tower footing resistance geographic rule distribution diagram; high-voltage electric field interference intensity data generated by an extra-high voltage transmission line around the tower footing is collected, the influence degree of high-voltage electric field interference on tower footing grounding resistance fluctuation is analyzed in combination with the extra-high voltage tower footing resistance geographical rule distribution diagram, and the adjusted tower footing resistance change rate and fluctuation frequency are obtained; and obtaining a tower footing position analysis result from the differentiated reinforcement cage binding amount metering strategy, and optimizing the distribution proportion of the reinforcement cage binding amount in combination with the resistance geographical rule subset to obtain a binding amount meter with optimized resource allocation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information technology, and in particular to a method for measuring engineering quantity based on power construction supervision engineering. BACKGROUND

[0002] As the backbone of modern power systems, ultra-high voltage transmission projects bear the heavy responsibility of long-distance and large-capacity power transmission, and their construction quality directly affects the safety and economic benefits of the power grid. In the construction of tower foundation, the measurement of steel reinforcement cage binding quantity and the stability of grounding resistance are key links to ensure the quality of the project and the safety of operation.

[0003] However, the existing methods have obvious shortcomings in dealing with complex environmental factors, and it is difficult to meet the needs of fine management. Therefore, technical breakthroughs are needed to optimize resource allocation and improve engineering efficiency. Currently, the measurement of steel reinforcement cage binding quantity in tower foundation construction relies mainly on manual experience or simple models, which cannot adapt to the diversity of terrain and soil types along the ultra-high voltage transmission line. This method often fails to accurately reflect the fluctuation characteristics of tower foundation grounding resistance in complex geological conditions, resulting in large deviations in measurement results. For example, in special terrains such as mountainous areas or wetlands, the soil resistivity varies significantly, and the existing methods cannot dynamically adjust the measurement strategy, thereby affecting the rational allocation of engineering resources. The high-voltage electric field generated during the operation of ultra-high voltage transmission lines further exacerbates the technical problems. Electric field interference can significantly affect the measurement accuracy of tower foundation grounding resistance, and the fluctuation of grounding resistance is closely related to the terrain and soil type of the tower foundation location. The geographical environment of different tower foundations varies, resulting in spatial heterogeneity in resistance fluctuation. In some areas, the resistance fluctuates dramatically, while in other areas, it is relatively stable. This spatial heterogeneity makes it difficult for a unified measurement method to be applicable, increasing the complexity of engineering quantity estimation. For example, in areas close to the center of the line with high electric field intensity, the grounding resistance may fluctuate frequently due to electric field interference, thereby affecting the accurate calculation of the steel reinforcement cage binding quantity.

[0004] Therefore, how to accurately analyze the geographical distribution of grounding resistance according to the terrain, soil characteristics and electric field interference level of different tower foundation locations, and develop differentiated measurement strategies for steel reinforcement cage binding quantity, has become a key problem for fine management of engineering quantity and optimization of resource allocation. SUMMARY

[0005] The present application provides a method for measuring engineering quantity based on power construction supervision engineering, which mainly includes: Obtain the geographical coordinate data of the ultra-high voltage tower foundation location, locate the corresponding image area through satellite remote sensing image processing combined with the geographical coordinate data of the ultra-high voltage tower foundation location, extract the terrain and soil type information in the geographical coordinate data from the satellite remote sensing image data, and generate an ultra-high voltage tower foundation resistance geographical regularity distribution map through geographical information system overlay analysis; Collect the high-voltage electric field interference intensity data generated by the ultra-high voltage transmission line around the tower base, combine the ultra-high voltage tower base resistance geographical regularity distribution map, analyze the influence of the high-voltage electric field interference on the fluctuation of the tower base grounding resistance, and generate the adjusted tower base resistance change rate and fluctuation frequency; According to the adjusted tower base resistance change rate and fluctuation frequency, analyze the resistance change deviation between the tower bases, screen the tower base positions with resistance changes higher than the average level, divide the tower base area groups with similar resistance fluctuations, and generate the resistance geographical regularity subset of the tower base area group; Through the resistance geographical regularity subset, analyze the grounding resistance fluctuation of the tower base positions in the tower base area group, generate the average fluctuation level, and develop a resistance fluctuation characteristic compensation scheme according to the average fluctuation level, and generate an optimized grounding resistance fluctuation adjustment strategy; According to the optimized grounding resistance fluctuation adjustment strategy, combine the topographic and geomorphic features and soil type information to evaluate the reinforcement cage binding amount demand of the tower base position, preferentially adjust the tower base with resistance change higher than the average level, and generate a differentiated reinforcement cage binding amount measurement strategy; Extract the tower base position analysis result from the differentiated reinforcement cage binding amount measurement strategy, combine the resistance geographical regularity subset to optimize the reinforcement cage binding amount distribution proportion, and generate a resource allocation optimized binding amount measurement table.

[0006] Further, the geographical coordinate data of the ultra-high voltage tower base position is obtained, the corresponding image area is located through satellite remote sensing image processing combined with the geographical coordinate data of the ultra-high voltage tower base position, the topographic and geomorphic features and soil type information in the geographical coordinate data are extracted from the satellite remote sensing image data, and an ultra-high voltage tower base resistance geographical regularity distribution map is generated through geographic information system overlay analysis, including: Obtain the latitude and longitude coordinate data of the tower base along the ultra-high voltage transmission line, collect the three-dimensional spatial information of the tower base through the satellite positioning system, and establish a coordinate index database; For the tower base points in the coordinate index database, obtain high-resolution satellite remote sensing image data around the tower base, process the satellite remote sensing image data in an image fusion manner, and generate clear ground image data; Based on the clear ground image data, calculate the terrain slope and fluctuation degree, extract the image texture parameters as the ground roughness coefficient, and generate a tower base topographic feature parameter library; Identify the soil type distribution through multispectral remote sensing image, extract the soil water content and particle structure information combined with the thermal infrared band and radar remote sensing data, and generate a tower base soil attribute data set; Input the tower base topographic feature parameter library and the tower base soil attribute data set into the geographic information system, perform spatial overlay analysis, and generate an ultra-high voltage tower base resistance geographical regularity distribution map.

[0007] Further, the collection of the tower base periphery ultra-high voltage transmission line generated high voltage electric field interference intensity data, combined with the ultra-high voltage tower base resistance geographical regular distribution map, analyzes the influence of the high voltage electric field interference on the tower base grounding resistance fluctuation, generates the adjusted tower base resistance change rate and fluctuation frequency, including: Laying out electric field strength measurement sensor network, recording the horizontal and vertical electric field components of the tower base periphery, generating electric field strength numerical value; Extracting the fundamental frequency and harmonic components of the electric field strength numerical value through Fourier transform, generating a spatio-temporal distribution data set; Based on the spatio-temporal distribution data set and the ultra-high voltage tower base resistance geographical regular distribution map, calculating the correlation coefficient of electric field strength and grounding resistance measurement value, generating electric field interference influence coefficient matrix; Through the electric field interference influence coefficient matrix, extracting the grounding resistance measurement value sequence of the tower base position, calculating the resistance change slope, identifying the resistance fluctuation frequency component, generating the adjusted tower base resistance change rate and fluctuation frequency.

[0008] Further, according to the adjusted tower base resistance change rate and fluctuation frequency, analyzing the resistance change deviation between towers, screening the tower base positions with resistance change higher than the average level, dividing the tower base area groups with similar resistance fluctuation, generating the resistance geographical regular subset of the tower base area group, including: According to the adjusted tower base resistance change rate and fluctuation frequency, calculating the mean and standard deviation of the resistance change rate, generating the standardized deviation value, screening the high change tower base position; Based on the high change tower base position, using clustering algorithm to divide the tower base area groups with similar resistance fluctuation; Extracting the geographical coordinates and resistance characteristic data of the tower base area group, constructing the resistance distribution continuous surface, generating the resistance geographical regular subset containing the geographical coordinates of the tower base area group, grounding resistance change rate, fluctuation frequency, terrain feature parameters and soil property data, and constructing the resistance distribution continuous surface of the area through Kriging interpolation.

[0009] Further, through the resistance geographical regular subset, analyzing the grounding resistance fluctuation of the tower base position in the tower base area group, generating the average fluctuation level, formulating the resistance fluctuation characteristic compensation scheme according to the average fluctuation level, generating the optimized grounding resistance fluctuation adjustment strategy, including: Extracting the tower base grounding resistance time series data through the resistance geographical regular subset, calculating the moving average and fluctuation amplitude, generating the average fluctuation level of the grounding resistance of the area group; Based on the average fluctuation level, generating the resistance adjustment coefficient and compensation frequency, determining the grounding material type, formulating the resistance fluctuation characteristic compensation scheme; According to the resistance fluctuation characteristic compensation scheme, the reinforcement cage binding density and spacing are adjusted, the connection mode is determined, and adjusted reinforcement cage binding amount configuration parameters are generated. In the high fluctuation area, a grounding electrode array is added, the application amount of the chemical resistance reduction material is adjusted, and an optimized grounding resistance fluctuation adjustment strategy is generated.

[0010] Further, according to the optimized grounding resistance fluctuation adjustment strategy, the reinforcement cage binding amount demand of the tower foundation position is evaluated in combination with the topographic and geomorphic features and the soil type information, the tower foundation with a resistance change higher than the average level is preferentially adjusted, a differentiated reinforcement cage binding amount measurement strategy is generated, and the differentiated reinforcement cage binding amount measurement strategy includes: According to the optimized grounding resistance fluctuation adjustment strategy, reinforcement configuration parameters are extracted, the proportion of transverse reinforcement is adjusted in combination with the terrain slope, and preliminary demand amount of the reinforcement cage is generated. The soil type information is used to calculate a grounding resistance contribution coefficient, a terrain relief degree is used to generate a tower foundation stability influence weight, high change tower foundations are screened to form a preferential adjustment sequence. According to the preferential adjustment sequence, the reinforcement cage binding density and spacing are adjusted, the number of binding point distributions is determined, and a binding parameter configuration set is generated. Based on the binding parameter configuration set, the resistance fluctuation characteristics of the tower foundation area are integrated, and a differentiated reinforcement cage binding amount measurement strategy is generated.

[0011] Further, the tower foundation position analysis result is extracted from the differentiated reinforcement cage binding amount measurement strategy, the reinforcement cage binding amount distribution proportion is optimized in combination with the resistance geographical law subset, and a resource configuration optimized binding amount measurement table is generated, and the resource configuration optimized binding amount measurement table includes: The binding parameters are extracted from the differentiated reinforcement cage binding amount measurement strategy, the resource demand weight is calculated in combination with the resistance geographical law subset, and a regionally weighted reinforcement configuration scheme is generated. According to the reinforcement configuration scheme, the total material demand amount is calculated, the configuration standard is adjusted, if the total reinforcement demand amount of a certain regional group exceeds the total amount of the preset reinforcement constraint, the reinforcement configuration standard of the corresponding tower foundation is sequentially reduced in priority from low to high according to the tower foundation resistance change rate, and a total amount balanced distribution result is generated. Based on the distribution result, the amount of reinforcement is optimized, a data record containing the tower foundation number and the binding parameters is established, and a resource configuration optimized binding amount measurement table is generated.

[0012] The technical scheme provided by the embodiment of the application can include the following beneficial effects: The application discloses an engineering quantity measurement method based on power construction supervision engineering, and solves the tower foundation grounding resistance fluctuation problem caused by differences in topography, soil types and high-voltage electric field interference in an extra-high voltage power transmission system. The geographic coordinates, topographic features and soil parameters of the tower foundation position are extracted through satellite remote sensing image processing, and a resistance geographic regularity distribution map is generated in combination with a geographic information system to analyze the influence of high-voltage electric field interference on resistance fluctuation and quantify the change rate and fluctuation frequency. Based on this, the application screens tower foundations with abnormal resistance changes, divides regional groups and formulates a differentiated grounding resistance fluctuation compensation scheme to optimize the steel cage binding amount, grounding material selection and auxiliary grounding device configuration. The application integrates the comprehensive influence of topography and soil types on the stability of the tower foundation and resistance, dynamically adjusts the steel cage binding density and distribution ratio, and generates a resource-optimized measurement table. The application significantly improves the stability and safety of the extra-high voltage tower foundation grounding system, reduces the influence of resistance fluctuation on power transmission efficiency, and provides efficient technical support for extra-high voltage projects in complex environments. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 A flowchart of an engineering quantity measurement method based on power construction supervision engineering of the application. DETAILED DESCRIPTION

[0014] In order to further understand the content of the application, the application will be described in detail in combination with the drawings and examples. It can be understood that the specific examples described herein are only used to explain the related application, and not to limit the application. In addition, it should be noted that, for the convenience of description, only the parts related to the application are shown in the drawings.

[0015] As Figure 1 , the engineering quantity measurement method based on power construction supervision engineering of the embodiment specifically can include: S101, geographic coordinate data of an extra-high voltage tower foundation position is acquired, corresponding image areas are positioned from satellite remote sensing image data in combination with the geographic coordinate data of the extra-high voltage tower foundation position through satellite remote sensing image processing, topographic features and soil type information in the geographic coordinate data are extracted from the satellite remote sensing image data, and an extra-high voltage tower foundation resistance geographic regularity distribution map is generated through geographic information system superposition analysis.

[0016] The latitude and longitude coordinate data of all tower foundations along the UHV transmission line are acquired, three-dimensional space information of each tower foundation point is collected through the Beidou satellite positioning system, a coordinate index database is established according to the tower foundation number, high-resolution satellite remote sensing image data within a radius of 500 meters of each tower foundation point is acquired, a multi-temporal remote sensing image fusion method is used to eliminate the influence of cloud and fog shielding, and clear ground image data of each tower foundation position is obtained. Based on the clear ground image data of each tower foundation position, the terrain slope value of each tower foundation position is calculated through a digital elevation model, the terrain undulation degree is determined according to the adjacent elevation point difference value, the contrast and correlation parameters of the image texture are extracted by using a gray level co-occurrence matrix as a ground roughness coefficient, and if the slope exceeds a preset threshold value, the complex terrain region is marked, and a tower foundation terrain feature parameter library containing the slope, undulation degree and roughness coefficient is formed. The coordinate position information in the tower foundation terrain feature parameter library is used to identify the soil type distribution through the band combination of multi-spectral remote sensing images, the soil water content distribution is inverted according to the brightness temperature value of the thermal infrared band, the particle structure composition is judged by using the correlation between the radar remote sensing backscattering coefficient and the soil particle size, the resistivity value range of each type of soil is determined in combination with the geological exploration data, and a tower foundation soil attribute data set is generated. The tower foundation soil attribute data set and the tower foundation terrain feature parameter library are input into a geographic information system, the resistivity value, terrain slope, undulation degree and soil water content distribution are rasterized through spatial overlay analysis, each tower foundation position is marked as high, medium and low according to the resistivity value range, the spatial correlation matrix between the parameters is established, and a UHV tower foundation resistance geographic law distribution map is output.

[0017] Specifically, in an embodiment, when acquiring the accurate position information of the tower foundation along the UHV transmission line, the carrier phase difference technology of the Beidou satellite positioning system is used to achieve centimeter-level positioning accuracy.

[0018] A Beidou receiver is deployed at each tower foundation construction point to receive navigation signals from at least 4 visible satellites, pseudo-range observation values and carrier phase observation values are solved, and three-dimensional coordinates of the tower foundation center point in the WGS-84 coordinate system are obtained. The coordinate index database establishes a two-level index structure according to the line direction and tower foundation number, which is convenient for quick retrieval and spatial query.

[0019] For remote sensing image acquisition of each tower foundation point, high-resolution satellite data with a spatial resolution better than 2 meters is selected.

[0020] The multi-temporal remote sensing image fusion method collects images of the same area at different time nodes, uses a weighted average method or a principal component analysis method to fuse multiple images. When a certain phase image is shielded by cloud and fog, corresponding pixel values are extracted from clear areas of other phases to replace them, the color consistency of the replaced area is adjusted through histogram matching, and finally complete and clear ground image data is generated.

[0021] In one implementation, the digital elevation model is constructed based on stereo image pairs or LiDAR point cloud data, and a continuous elevation surface is generated by triangulated irregular network interpolation. The terrain slope value is derived by calculating the elevation difference between the target point and its 8-neighborhood points, and the relief degree is determined according to the combination of the extreme value difference and the standard deviation of the elevation within the analysis window.

[0022] As the core technology of texture analysis, the gray level co-occurrence matrix quantifies the texture features by calculating the joint distribution probability of the gray level values of two pixels with a specific distance and direction. In the specific processing process, the gray level of the remote sensing image is first compressed to 16 levels, and then the co-occurrence matrix in four directions of 0 degrees, 45 degrees, 90 degrees and 135 degrees is calculated respectively. The contrast parameter is extracted from the co-occurrence matrix in each direction, which reflects the clarity and groove depth of the texture. The calculation formula involves the product sum of the matrix elements and the square of the difference between their row and column indexes. The correlation parameter measures the similarity of the texture in a specific direction, which is obtained by normalized covariance calculation. The contrast and correlation parameters in the four directions are averaged to obtain the isotropic surface roughness coefficient. The larger the roughness coefficient, the more intense the surface relief change, and the more significant the impact on the tower foundation construction and grounding resistance.

[0023] For example, in the soil type identification process, the reflectivity difference between the red light band and the near-infrared band of the multispectral remote sensing image can effectively distinguish different soil types. Clay has lower reflectivity in the red light band, while sandy soil has higher reflectivity. Classification and identification are performed by setting a threshold range.

[0024] In one embodiment, the principle of thermal infrared remote sensing for soil moisture content inversion is based on the positive correlation between soil thermal inertia and moisture content.

[0025] Obtain the surface temperature data at two time phases of day and night, calculate the diurnal temperature difference value, and the smaller the temperature difference, the larger the soil thermal inertia, and the higher the corresponding moisture content. The backscattering coefficient of radar remote sensing is mainly affected by the soil dielectric constant and surface roughness, and the dielectric constant is closely related to the soil particle size. The backscattering coefficient of coarse-grained soil is usually larger than that of fine-grained soil. By establishing an empirical relationship model between the scattering coefficient and the particle composition, the relative content of sand, silt and clay can be inverted. Combined with the measured data of soil resistivity obtained by geological exploration, a corresponding relationship table of different soil types and resistivity values is established. The resistivity of sandy soil is generally in the range of 1000 to 5000 ohm-m, and the resistivity of clay is in the range of 10 to 100 ohm-m.

[0026] The spatial overlay analysis function of the geographic information system realizes information synthesis by spatial operation of multiple thematic layers. First, the resistivity value, terrain slope, relief degree, and soil moisture distribution are converted into a unified grid data format, and each grid cell corresponds to an actual range of 10 m x 10 m on the ground.

[0027] It should be noted that the three-level labeling of the resistivity value adopts the natural breakpoint classification method, and the classification threshold is determined according to the inherent characteristics of the data distribution. The high-resistance area usually corresponds to dry sandy soil or bedrock exposure area, the medium-resistance area is the conventional soil coverage area, and the low-resistance area is mostly high-moisture clay or marsh area.

[0028] The establishment of the spatial correlation matrix is realized by calculating the Moran index of each parameter in the spatial neighborhood, which reflects the spatial aggregation degree of the parameter value. When the resistivity and the terrain slope show a positive correlation, it indicates that the soil resistivity in the steep slope area is generally high. This correlation rule has important guiding significance for the subsequent differentiation of the steel cage binding amount. Through comprehensive analysis of the spatial distribution characteristics and mutual relationship of each parameter, the generated ultra-high voltage tower foundation resistivity geographic regularity distribution map can intuitively show the advantages and disadvantages of the grounding conditions of each tower foundation position.

[0029] S102, collect the high-voltage electric field interference intensity data generated by the ultra-high voltage transmission line around the tower foundation, combine the ultra-high voltage tower foundation resistivity geographic regularity distribution map, analyze the influence of the high-voltage electric field interference on the fluctuation of the tower foundation grounding resistance, and generate the adjusted tower foundation resistance change rate and fluctuation frequency.

[0030] The electric field strength measurement sensor network is arranged around the tower base, a three-dimensional electric field measuring instrument is used to record the horizontal and vertical electric field components, the measurement points are determined according to the relative position relationship between the tower base and the power transmission line, the electric field strength values of different height layers are obtained, the fundamental frequency and harmonic components of the electric field are extracted through Fourier transform, and the space-time distribution data set of the high-voltage electric field around the tower base is obtained. Based on the electric field strength values in the space-time distribution data set, combined with the electric resistance reference values in the geographic regular distribution map of the ultra-high voltage tower base, the linear correlation degree between the electric field strength and the measured value of the grounding resistance is determined by calculating the Pearson correlation coefficient, and if the electric field strength exceeds the preset threshold, it is marked as a strong interference area, and the electric field interference influence coefficient matrix is constructed according to the correlation coefficient value. Using the electric field interference influence coefficient matrix, the grounding resistance measurement value sequence of each tower base position at different time periods is extracted, the change slope of the resistance value is calculated by setting a fixed length sliding window moving along the time axis, the dominant frequency component of the resistance fluctuation is identified by using fast Fourier transform, and the original change rate is divided by the interference influence coefficient of the corresponding position to obtain the real resistance change rate after eliminating the electric field interference. For the real resistance change rate sequence, the number of times that the resistance value exceeds the preset percentage of the reference value in a unit time is counted as the initial value of the fluctuation frequency, the peak position is identified by calculating the autocorrelation function value under different time delays to identify the fluctuation period, the fluctuation frequency is corrected combined with the daily variation law of the electric field strength, and the adjusted tower base resistance change rate and fluctuation frequency are output.

[0031] Specifically, in an embodiment, the arrangement of the electric field strength measurement sensor network needs to consider the spatial relationship between the tower base and the power transmission line.

[0032] The measurement points are arranged on concentric circles at a distance of 5 meters, 10 meters and 15 meters from the center of the tower base, and 8 measurement points are uniformly arranged on each circle. The three-dimensional electric field measuring instrument adopts a spherical electrode structure, and measures the electric field components in X, Y and Z directions through three mutually perpendicular electrode pairs. The measurement frequency is set to 50 samples per second.

[0033] When processing the electric field measurement data by Fourier transform, the collected time domain signal is first processed by windowing, and Hamming window is used to reduce spectrum leakage. The time domain signal is converted to frequency domain by discrete Fourier transform, and the fundamental frequency component of 50Hz and the harmonic components of 100Hz and 150Hz are extracted. These frequency components reflect the electric field characteristics of ultra-high voltage alternating current transmission.

[0034] It should be noted that the calculation process of Pearson correlation coefficient involves the standardization of two key variables. First, extract the electric field intensity sequence and the ground resistance measurement sequence in the same time period, and calculate the mean and standard deviation of the two sequences respectively. Standardize each data point, that is, subtract the mean from the original value and divide by the standard deviation. Multiply the two normalized sequences point by point and sum them up, and then divide by the sequence length minus 1 to get the correlation coefficient value. The closer the absolute value of the correlation coefficient is to 1, the stronger the influence of the electric field on the ground resistance. According to the size of the correlation coefficient value, assign an interference influence coefficient between 0.1 and 1.0 to each tower foundation position. When the absolute value of the correlation coefficient is greater than 0.8, the interference influence coefficient is close to 1.0; when the absolute value of the correlation coefficient is less than 0.3, the interference influence coefficient is close to 0.1. This quantification method can accurately reflect the difference in electric field interference at different positions.

[0035] In one implementation, the setting of the sliding window needs to consider both the time resolution and the calculation stability. The window length is set to 30 minutes, and the sliding step is 5 minutes, so each window contains 1500 ground resistance measurement data points.

[0036] The correction process of resistance change rate adopts a step-by-step processing method. The slope of the linear regression equation obtained by least squares fitting of the resistance value sequence in the window is taken as the original change rate. The dominant frequency component identified by the fast Fourier transform is used to judge the type of interference. If the dominant frequency is 50Hz or its multiple, it is confirmed as fluctuation caused by electric field interference. When correcting, the original change rate is divided by the interference influence coefficient of the corresponding position to get the true change rate after eliminating the electric field interference. For example, the original resistance change rate of a certain tower foundation position is 20 ohms per hour increase, and the interference influence coefficient of this position is 0.8, then the corrected true resistance change rate is 25 ohms per hour increase. This correction method can restore the true change trend of the ground resistance caused by natural factors such as soil humidity and temperature, and exclude the false fluctuation caused by electric field interference.

[0037] For example, when calculating the fluctuation frequency, the number of times the ground resistance value exceeds the reference value by 10% within one hour is counted as the initial estimate of the fluctuation frequency.

[0038] The calculation of the autocorrelation function adopts a normalization processing method. For the true resistance change rate sequence, calculate the autocorrelation value under different time delays τ, the delay range is from 0 to 24 hours, and the step is 1 hour. When the autocorrelation function has a clear peak at a certain delay value, the delay value is the fluctuation period.

[0039] In an embodiment, the daily variation of the electric field intensity presents a clear double-peak feature, reaching a peak at 10 am and 8 pm and dropping to a valley at 3 am. According to this law, the fluctuation frequency is corrected by time period weighting, with the weight coefficient of the peak period set to 1.2 and the weight coefficient of the valley period set to 0.8.

[0040] It can be understood that the final output adjusted tower base resistance change rate is in ohms per hour, and the fluctuation frequency is in cycles per hour. These two parameters together constitute the dynamic characteristic description of the tower base grounding resistance, and provide a quantitative basis for the subsequent optimization configuration of the reinforcement cage binding amount.

[0041] S103, according to the adjusted tower base resistance change rate and the fluctuation frequency, analyze the tower base resistance change deviation, filter the tower base positions with resistance change higher than the average level, divide the tower base area groups with similar resistance fluctuation, and generate the resistance geographical law subset of the tower base area group.

[0042] According to the adjusted tower base resistance change rate and the fluctuation frequency, the mean and standard deviation of the resistance change rate of all tower base positions are calculated. The standardized deviation value is obtained by dividing the difference between the resistance change rate of each tower base and the mean by the standard deviation. If the standardized deviation value is greater than 1.5, it is marked as a high change tower base, and a high change tower base position set is obtained. For the high change tower base position set, the K-means clustering algorithm is used to cluster according to the two dimensions of resistance change rate and fluctuation frequency. The attribution relationship is determined by calculating the Euclidean distance between each tower base and the cluster center. If adjacent tower bases are assigned to different cluster groups but the difference in resistance characteristics is less than a preset threshold, they are adjusted to the same cluster group, and a tower base area group with similar resistance fluctuation is obtained. Based on the tower base area group, the geographic coordinates, resistance change rate, fluctuation frequency and terrain soil attribute data of all tower bases in each area group are extracted, and the resistance distribution continuous surface in the area is constructed by Kriging interpolation method. The change rate of the surface in each direction is calculated to identify the spatial trend of resistance increase or decrease, and the resistance geographical law subset containing spatial distribution characteristics and change law is formed.

[0043] Specifically, in an embodiment, the calculation of the standardized deviation value quantitatively evaluates the tower base resistance change characteristics by statistical methods.

[0044] First, the resistance change rate data of all tower base positions are summarized, the arithmetic mean is calculated as a reference value, and the sum of squares of the difference between each data point and the average value is calculated, and the standard deviation is obtained by dividing the total number of tower bases.

[0045] For a certain UHV transmission line, if the average resistance change rate of 100 tower foundations is 15 ohms per hour, the standard deviation is 5 ohms per hour, and the resistance change rate of a certain tower foundation reaches 22.5 ohms per hour, the standardized deviation value is calculated as 1.5, which exceeds the preset threshold and is marked as a high change tower foundation.

[0046] It should be noted that the K-means clustering algorithm needs to consider both electrical characteristics and geographical location when processing tower foundation grouping. The initial clustering center is determined by randomly selecting K high change tower foundation positions. In each iteration, the Euclidean distance of each tower foundation to the clustering center is calculated, and the distance calculation considers both resistance change rate and fluctuation frequency. The adjustment mechanism of geographical adjacency constraint is realized by checking the clustering attribution of adjacent tower foundations. When two geographically adjacent tower foundations are assigned to different clustering groups, but the difference in resistance change rate is less than 3 ohms per hour and the difference in fluctuation frequency is less than 2 times per hour, the two tower foundations are adjusted to the same clustering group. This adjustment ensures the continuity of regional groups in geographical space.

[0047] The Kriging interpolation method is based on the principle of geostatistics, which constructs a variogram model by analyzing the spatial autocorrelation of tower foundation resistance data.

[0048] In an implementation manner, the interpolation process first calculates the experimental variogram, calculates the semi-variance value through tower foundations at different distance intervals, and then fits a spherical model or a Gaussian model to determine the three key parameters of range, sill value and nugget value.

[0049] The resistance geographical law subset includes the spatial distribution characteristic matrix, resistance gradient vector and change trend identification of each regional group. These information provides quantitative basis for subsequent differentiated configuration of steel cage binding.

[0050] S104, analyze the grounding resistance fluctuation of the tower foundation position in the tower foundation regional group through the resistance geographical law subset, generate an average fluctuation level, formulate a resistance fluctuation characteristic compensation scheme according to the average fluctuation level, and generate an optimized grounding resistance fluctuation adjustment strategy.

[0051] The grounding resistance time series data of each tower foundation in each regional group is extracted by resistance geographical regularity subset extraction, the arithmetic mean of data points in a fixed time window is used to calculate the moving average, the fluctuation amplitude is determined according to the difference between the resistance value of adjacent time points and the moving average, the mean value of the fluctuation amplitude of all tower foundations in the regional group is calculated, and the average fluctuation level of the regional group is obtained. Based on the average fluctuation level, the resistance adjustment coefficient is obtained by multiplying the fluctuation level value by a preset proportion factor, the main fluctuation period is determined based on the spectrum analysis of the fluctuation data, the reciprocal of the period length is taken as the compensation frequency, the grounding material type corresponding to the electrical conductivity performance is selected according to the soil resistivity range, and the resistance fluctuation characteristic compensation scheme containing the adjustment coefficient and the compensation frequency is formulated. According to the adjustment coefficient in the resistance fluctuation characteristic compensation scheme, the additional binding density requirement is obtained by multiplying the adjustment coefficient and the reference binding amount, the spacing adjustment amount of the longitudinal and transverse reinforcement of the reinforcement cage is determined by the product of the compensation frequency and the preset conversion factor, the welding or bolt connection mode is selected according to the resistivity of the grounding material, and the adjusted reinforcement cage binding amount configuration parameter is obtained. For the reinforcement cage binding amount configuration parameter, the grounding electrode array is added in the high fluctuation area, the grounding effect is strengthened by the burial depth and distribution density of the electrode, the application amount of the chemical resistance reduction material is determined according to the soil moisture content, and the grounding resistance fluctuation adjustment strategy containing the adjustment of the reinforcement cage binding amount, the optimization of the grounding material selection and the increase of the auxiliary grounding device is formed.

[0052] Specifically, in an embodiment, the extraction of the grounding resistance time series data is based on the historical measurement values recorded in the resistance geographical regularity subset.

[0053] Each tower foundation position is equipped with an automatic monitoring device, and the grounding resistance value is collected once an hour to form a continuous time series data. The moving average method adopts a fixed time window of 5 hours, and the arithmetic mean of 5 data points in the window is taken as the smoothing value at this time.

[0054] The calculation of the fluctuation amplitude is determined by the absolute value of the difference between the resistance measured value of the adjacent time point and the corresponding moving average value. When the resistance value of a certain tower foundation at a certain time is 50 ohms, and the moving average value at this time is 45 ohms, the fluctuation amplitude is 5 ohms. The arithmetic mean of all fluctuation amplitude values in an observation period is calculated as the fluctuation characteristic value of the tower foundation.

[0055] It should be noted that the determination of the resistance adjustment coefficient adopts a hierarchical mapping method. According to the numerical range of the average fluctuation level, different proportion factors are set. When the fluctuation level is in the range of 0 to 10 ohms, the proportion factor is 0.1; when the fluctuation level is in the range of 10 to 20 ohms, the proportion factor is 0.15; and when the fluctuation level exceeds 20 ohms, the proportion factor is 0.2.

[0056] The spectrum analysis process realizes the identification of fluctuation period through fast Fourier transform. The time series data of grounding resistance is subjected to discrete Fourier transform to convert the time domain signal into frequency domain representation. The frequency component with the largest amplitude in the spectrum diagram corresponds to the main fluctuation frequency. The main fluctuation period is equal to the inverse of the frequency. For example, when the dominant frequency is 0.05 Hz, the corresponding fluctuation period is 20 hours. The determination of the compensation frequency needs to consider the operability of the actual construction. Usually, the theoretical compensation frequency is rounded down to the nearest integer hour. In the actual application of the ultra-high voltage tower foundation, due to the daily periodicity of the power grid load, the grounding resistance often presents a 24-hour main fluctuation period. Therefore, the compensation frequency is usually set to 1 or 2 times per day. This spectrum analysis method can accurately identify the periodic fluctuation mode caused by electric field interference, providing a scientific basis for formulating a targeted compensation scheme.

[0057] In one implementation, the selection of grounding material is classified and configured according to the soil resistivity range. When the soil resistivity is less than 100 ohm·m, ordinary steel is selected as the grounding material; when the resistivity is in the range of 100 to 500 ohm·m, galvanized steel is used; and when the resistivity exceeds 500 ohm·m, copper-clad steel material is used.

[0058] The calculation of the configuration parameters of the reinforcement cage binding amount involves multiple conversion steps. The product of the adjustment coefficient and the reference binding amount determines the additional binding requirement, and the reference binding amount is pre-set according to the tower foundation bearing capacity requirement, usually 150 to 200 kg of steel per cubic meter of concrete. When the adjustment coefficient is 0.15, the additional binding amount is 15% of the reference value, i.e. an increase of 22.5 to 30 kg of steel per cubic meter. The spacing adjustment of longitudinal and transverse reinforcement is associated with the compensation frequency through a conversion coefficient, which is valued at 10 mm·day / time according to engineering experience. If the compensation frequency is 2 times per day, the spacing is reduced by 20 mm. This quantitative parameter conversion method ensures accurate mapping from electrical characteristic analysis to structural design parameters, making the configuration of the reinforcement cage meet both grounding performance requirements and structural strength standards.

[0059] For example, welded connections are suitable for grounding materials with resistivity less than 200 ohm·m, while bolted connections are used for higher resistivity material combinations.

[0060] In one embodiment, the design of the grounding electrode array adopts a ring arrangement, with 8 to 12 vertical grounding electrodes buried around the tower foundation according to the equidistant principle. The electrode length is determined according to the soil structure, usually 2.5 to 4 meters. The horizontal grounding grid uses flat steel material, and the grid spacing is adjusted according to the fluctuation intensity of the resistance. The grid spacing in high fluctuation areas is reduced to 0.5 meters.

[0061] It can be understood that the application amount of the chemical resistance reduction material is inversely proportional to the soil water content. When the soil water content is less than 15%, 8 to 10 kg of resistance reduction agent is applied per cubic meter of soil; when the soil water content is between 15% and 25%, the application amount is reduced to 5 to 7 kg; and when the soil water content exceeds 25%, the application amount is further reduced to 3 to 4 kg. The resistance reduction agent reduces the relative amplitude of resistance fluctuation by improving the electrical conductivity of the soil and reducing the baseline value of the grounding resistance.

[0062] S105, according to the optimized grounding resistance fluctuation adjustment strategy, combining the topographic features and soil type information, evaluate the steel reinforcement cage binding amount requirement of the tower foundation position, preferentially adjust the tower foundation with resistance change higher than the average level, and generate a differentiated steel reinforcement cage binding amount measurement strategy.

[0063] According to the optimized grounding resistance fluctuation adjustment strategy, extract the steel reinforcement configuration parameters of each tower foundation, calculate the foundation steel reinforcement cage binding amount combining the tower foundation bearing capacity requirement, compare the slope value in the topographic feature diversity characteristics with the preset slope threshold value, if the slope exceeds the threshold value, increase the configuration proportion of the transverse reinforcing bar by a preset percentage, and obtain the preliminary requirement amount of the steel reinforcement cage combined with the topographic factors. Based on the preliminary requirement amount of the steel reinforcement cage, divide the soil resistivity value by the baseline resistivity to obtain the grounding resistance contribution coefficient, multiply the contribution coefficient by the terrain relief value to determine the tower foundation stability influence weight, compare the resistance change rate of each tower foundation with the average change rate of all tower foundations, and select the tower foundations higher than the average level, arrange the influence weight from high to low to form a preferential adjustment sequence. For each tower foundation in the preferential adjustment sequence, determine the steel reinforcement cage binding density increment according to the proportion relationship between the resistance fluctuation amplitude and the preset baseline value, multiply the adjustment factor obtained by converting the fluctuation frequency by the baseline spacing to calculate the longitudinal and transverse bar spacing adjustment value, determine the number of binding points distributed in different depth layers by depth layering, and obtain the binding parameter configuration set of each tower foundation. Based on the binding parameter configuration set, combining the spatial distribution characteristics and resistance fluctuation similarity of the tower foundations in the regional group, using linear interpolation to supplement the parameter transition value between adjacent tower foundations, integrating the binding density value, longitudinal and transverse bar spacing value and the number of binding points in each layer of each tower foundation, a differentiated steel reinforcement cage binding amount measurement strategy is formed, which conforms to the regional resistance fluctuation characteristics of each tower foundation.

[0064] Specifically, in an embodiment, the extraction of the steel reinforcement configuration parameters is based on the adjustment coefficients and compensation frequency data recorded in the optimized grounding resistance fluctuation adjustment strategy.

[0065] The foundation steel reinforcement cage binding amount of each tower foundation is determined according to the tower foundation design bearing capacity, which is calculated by combining factors such as tower height, conductor tension and wind load, and a baseline value of 150 to 200 kg of steel reinforcement per cubic meter of concrete foundation is usually configured.

[0066] The terrain slope threshold is set to 15 degrees, and when the measured slope of a certain tower foundation position reaches 20 degrees, the configuration proportion of the transverse reinforcing bar is increased by 30% on the original basis. This increase is determined according to a linear relationship according to the degree of slope exceeding the threshold, and an increase of 2% of the configuration amount is added for every 1 degree of excess.

[0067] It should be noted that the calculation of the grounding resistance contribution coefficient is determined by the relative ratio method. The reference resistivity is set to 100 ohm·m, representing the standard value under normal soil conditions. When the measured soil resistivity of a certain tower foundation position is 250 ohm·m, the contribution coefficient is calculated as 2.5. The terrain relief is determined by analyzing the elevation change within a 100-meter range around the tower foundation, and the relief value is equal to the maximum elevation difference divided by 10. The stability influence weight is equal to the product of the contribution coefficient and the relief value, and this weight value reflects the comprehensive influence of terrain and soil on the stability of the tower foundation. In actual engineering, the relief of mountainous tower foundations may reach 5 to 8, combined with higher soil resistivity, the stability influence weight can reach 15 to 20, and such tower foundations need to be prioritized for reinforcing cage configuration adjustment. By sorting all tower foundations according to the influence weight, a clear construction priority sequence is formed, ensuring that resources are prioritized for tower foundation positions with higher stability risks.

[0068] The comparison reference of resistance change rate is obtained by calculating the arithmetic mean of the change rates of all tower foundations. If the average change rate of 100 tower foundations of a certain transmission line is 12 ohm per hour, then the tower foundation with a change rate exceeding 15 ohm is marked as a high-change tower foundation.

[0069] In an implementation manner, the determination of the reinforcing cage binding density increment is based on the proportional relationship between the resistance fluctuation amplitude and a preset reference value. The preset reference value is usually 10 ohm, and when the fluctuation amplitude is 15 ohm, the density increment is 50% of the reference density. The process of converting the fluctuation frequency into an adjustment factor uses logarithmic transformation, and the frequency value is taken as the natural logarithm and multiplied by 0.1 to obtain the adjustment factor. The reference spacing is usually 200 mm, and when the adjustment factor is 0.2, the longitudinal and transverse bar spacing is adjusted to 240 mm. The depth layering method divides the tower foundation base into three layers of upper, middle and lower according to depth, with a thickness of about 1 meter. The upper layer is close to the ground surface and is greatly affected by the environment, so the number of binding points is set to 16 per square meter; the middle layer is the main bearing area, and the number of binding points is 12 per square meter; the lower layer penetrates into the stable soil layer, and the number of binding points can be reduced to 8 per square meter. This layered configuration method not only ensures the structural strength, but also realizes the economic use of materials.

[0070] For example, the fluctuation amplitude of a certain high-change tower foundation reaches 18 ohm, and the calculated density increment is 80%, which means that the steel reinforcement amount needs to be increased by 80% based on the reference value.

[0071] Linear interpolation method is used to supplement the parameter transition value between adjacent piers. When the binding density of two adjacent piers is 120 kg / m3 and 180 kg / m3 respectively, and the distance between them is 500 meters, the interpolation density of the intermediate position is 150 kg / m3.

[0072] In one embodiment, the spatial distribution characteristics are represented by the Euclidean distance matrix between piers, and the resistance fluctuation similarity is quantified by the correlation coefficient matrix. The similarity threshold is set to 0.7, and the piers with correlation coefficients exceeding this value are classified into the same similar group.

[0073] It can be understood that the final formation of the differentiated reinforcement cage binding amount measurement strategy needs to integrate the configuration information of three dimensions: the binding density in kg / m3, the longitudinal and transverse reinforcement spacing in mm, and the number of binding points in each layer in pieces / m2. This multi-dimensional quantitative expression provides clear technical parameter guidance for construction and realizes accurate mapping from electrical performance requirements to structural design parameters.

[0074] S106, extracting the pier location analysis result from the differentiated reinforcement cage binding amount measurement strategy, combining the resistance geographical law subset to optimize the reinforcement cage binding amount distribution ratio, and generating a resource configuration optimized binding amount measurement table.

[0075] From the differentiated reinforcement cage binding amount measurement strategy, the binding density, spacing and binding point number parameters of each pier are extracted, the product of the number of piers in each regional group and the resistance fluctuation intensity is calculated as the resource demand weight according to the spatial distribution characteristics in the resistance geographical law subset, the weight value is multiplied by the benchmark distribution ratio to obtain the adjusted distribution ratio, and the regional weighted reinforcement configuration scheme is formed. Based on the reinforcement configuration scheme, the total demand amount of reinforcement material for each pier is calculated, the priority of pier configuration is determined according to the resistance change rate, and if the total demand amount of a regional group exceeds the preset resource upper limit, the configuration standard of the pier is lowered in turn from low to high according to the priority until the constraint condition is met, and the total amount balanced distribution result is obtained. According to the final configuration parameters of each pier in the distribution result, the reinforcement amount is optimized in combination with the material sharing coefficient between adjacent piers, the binding density, spacing and binding point number data of each pier are summarized to establish a data record containing pier number, position coordinates and various binding parameters, and a resource configuration optimized binding amount measurement table is formed.

[0076] Specifically, in one embodiment, the parameters extracted from the differentiated reinforcement cage binding amount measurement strategy include the binding density, longitudinal and transverse reinforcement spacing, and the number of binding points in each layer of each pier. These parameters have been subjected to previous resistance fluctuation analysis and terrain soil evaluation, reflecting the actual demand characteristics of each pier.

[0077] The calculation of resource demand weight is based on two key factors: the number of piers in the regional group and the resistance fluctuation intensity.

[0078] A certain area group contains 10 tower bases, and the average resistance fluctuation intensity is 15 ohms. The resource demand weight value of the area is 150. The benchmark allocation ratio is determined by the average allocation of the total project, and the initial ratio of each area group is the same. The adjusted allocation ratio is equal to the product of the weight value and the benchmark ratio, and then normalized to ensure that the sum of the allocation ratios of all areas is 1.

[0079] It should be noted that the determination of the tower base configuration priority directly uses the resistance change rate as the basis for sorting. The higher the resistance change rate of the tower base, the greater the fluctuation of the grounding performance, and more reinforcement needs to be configured to ensure stability, so it obtains a higher priority. When the total demand of an area exceeds the upper limit of resources, start with the tower base with the lowest priority, reduce its configuration standard by 10%, and adjust upwards in turn until the total amount meets the constraint condition.

[0080] Preferably, the material sharing coefficient between adjacent tower bases is determined according to the distance between the tower bases. The sharing coefficient is set to 0.9 for adjacent tower bases with a distance of less than 500 meters, indicating that part of the material reserve can be shared; the sharing coefficient is 0.95 for a distance between 500 and 1000 meters; and material sharing is not considered for a distance exceeding 1000 meters.

[0081] In an implementation manner, the binding amount metering table adopts a structured data format and includes fields such as tower base number, latitude and longitude coordinates, binding density, longitudinal reinforcement spacing, transverse reinforcement spacing, number of binding points in the upper, middle and lower three layers, and total amount of reinforcement. Each record corresponds to a tower base and is arranged in order according to the line direction.

[0082] Through this resource configuration optimization method, reasonable allocation of reinforcement materials can be realized under the premise of meeting the total project constraint, and the configuration needs of high-risk tower bases can be focused on.

[0083] The above description is only the preferred embodiment of the present application and the explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the concept of the present application. For example, the above features are replaced with the technical features disclosed in the present application (but not limited to) with similar functions to form a technical solution.

Claims

1. A method for measuring the quantity of work in power construction supervision projects, characterized in that, The method includes: Geographic coordinate data of the location of the UHV tower base is obtained. The corresponding image area is located by combining the geographic coordinate data of the UHV tower base location with satellite remote sensing image processing. The topographic features and soil type information in the geographic coordinate data are extracted from the satellite remote sensing image data. The geographic distribution map of the resistance of the UHV tower base is generated by overlay analysis through a geographic information system. Data on the intensity of high-voltage electric field interference generated by the ultra-high voltage transmission lines around the tower base are collected. Combined with the geographical distribution map of the ultra-high voltage tower base resistance, the influence of the high-voltage electric field interference on the fluctuation of the tower base grounding resistance is analyzed, and the adjusted tower base resistance change rate and fluctuation frequency are generated. Based on the adjusted tower base resistance change rate and fluctuation frequency, analyze the resistance change deviation between tower bases, screen tower base locations with resistance changes higher than the average level, divide tower base area groups with similar resistance fluctuations, and generate a subset of the resistance geographical patterns of the tower base area groups. By analyzing the grounding resistance fluctuations at the tower base locations within the tower base area group using the subset of resistance geographical patterns, an average fluctuation level is generated. Based on the average fluctuation level, a resistance fluctuation characteristic compensation scheme is formulated, and an optimized grounding resistance fluctuation adjustment strategy is generated. Based on the optimized grounding resistance fluctuation adjustment strategy, combined with the topographic features and soil type information, the required amount of rebar cage binding at the tower base location is assessed, and tower bases with resistance changes higher than the average level are prioritized for adjustment, thereby generating a differentiated rebar cage binding amount measurement strategy. Extract the tower foundation location analysis results from the differentiated rebar cage binding quantity measurement strategy, and combine the optimized rebar cage binding quantity allocation ratio with the resistivity geographical law subset to generate a binding quantity measurement table with optimized resource allocation.

2. The method for measuring engineering quantities based on power construction supervision projects according to claim 1, characterized in that, The process involves acquiring the geographic coordinate data of the UHV tower base locations, locating corresponding image areas using satellite remote sensing image processing and the geographic coordinate data, extracting topographic features and soil type information from the geographic coordinate data, and generating a geographic distribution map of the UHV tower base resistance through overlay analysis using a geographic information system. This includes: Acquire the latitude and longitude coordinates of the tower foundations along the ultra-high voltage transmission line, collect the three-dimensional spatial information of the tower foundations through a satellite positioning system, and establish a coordinate index database; For the tower base locations in the coordinate index database, high-resolution satellite remote sensing image data of the surrounding area is acquired, and the satellite remote sensing image data is processed by image fusion to generate clear surface image data; Based on the clear surface image data, the terrain slope and undulation are calculated, the image texture parameters are extracted as the surface roughness coefficient, and a base base terrain feature parameter library is generated. Soil type distribution is identified by multispectral remote sensing images, and soil moisture content and particle structure information are extracted by combining thermal infrared band and radar remote sensing data to generate a data set of soil properties for the tower base. The database of topographic feature parameters of the tower base and the dataset of soil properties of the tower base are input into the geographic information system for spatial overlay analysis to generate a geographic distribution map of the resistance of the UHV tower base.

3. The method for measuring engineering quantities based on power construction supervision projects according to claim 1, characterized in that, The process involves collecting high-voltage electric field interference intensity data generated by ultra-high-voltage transmission lines around the tower base, combining this data with a geographical distribution map of the ultra-high-voltage tower base resistance, analyzing the impact of this high-voltage electric field interference on the fluctuation of the tower base grounding resistance, and generating adjusted tower base resistance change rate and fluctuation frequency, including: A network of electric field strength measurement sensors is deployed to record the horizontal and vertical electric field components around the tower base and generate electric field strength values. The fundamental frequency and harmonic components of the electric field intensity values ​​are extracted by Fourier transform to generate a spatiotemporal distribution dataset. Based on the spatiotemporal distribution dataset and the geographical distribution map of the UHV tower base resistance, the correlation coefficient between the electric field strength and the measured grounding resistance is calculated, and an electric field interference influence coefficient matrix is ​​generated. Using the electric field interference influence coefficient matrix, the grounding resistance measurement sequence at the tower base location is extracted, the resistance change slope is calculated, the resistance fluctuation frequency component is identified, and the adjusted tower base resistance change rate and fluctuation frequency are generated.

4. The method for measuring engineering quantities based on power construction supervision projects according to claim 1, characterized in that, The process involves analyzing the resistance variation deviation between tower bases based on the adjusted tower base resistance change rate and fluctuation frequency, screening tower base locations with resistance changes higher than the average level, dividing tower base regions with similar resistance fluctuations into groups, and generating a subset of the geographical patterns of resistance within these tower base regions, including: Based on the adjusted tower base resistance change rate and fluctuation frequency, calculate the mean and standard deviation of the resistance change rate, generate a standardized deviation value, and screen for tower base locations with high change rates. Based on the highly variable tower base locations, a clustering algorithm is used to divide the tower base regions with similar resistance fluctuations into groups. The geographic coordinates and resistance characteristic data of the tower base area group are extracted, a continuous surface of resistance distribution is constructed, and data including geographic coordinates of the tower base area group, grounding resistance change rate, fluctuation frequency, terrain feature parameters and soil properties are generated. Furthermore, a subset of the geographic resistance law of the continuous surface of resistance distribution within the region is constructed by Kriging interpolation.

5. The method for measuring engineering quantities based on power construction supervision projects according to claim 1, characterized in that, The process involves analyzing the grounding resistance fluctuations at tower base locations within the tower base area group using the subset of geographical resistance patterns, generating an average fluctuation level, and formulating a resistance fluctuation characteristic compensation scheme based on the average fluctuation level to generate an optimized grounding resistance fluctuation adjustment strategy, including: The time series data of tower base grounding resistance is extracted by the subset of the resistance geographical patterns, the moving average and fluctuation amplitude are calculated, and the average fluctuation level of grounding resistance of the regional group is generated. Based on the average fluctuation level, a resistance adjustment coefficient and a compensation frequency are generated, the grounding material type is determined, and a resistance fluctuation characteristic compensation scheme is formulated. Based on the resistance fluctuation characteristic compensation scheme, adjust the reinforcement cage binding density and spacing, determine the connection method, and generate the adjusted reinforcement cage binding quantity configuration parameters. By adding a grounding electrode array in the high-fluctuation region and adjusting the amount of chemical resistance-reducing material applied, an optimized grounding resistance fluctuation adjustment strategy is generated.

6. The method for measuring engineering quantities based on power construction supervision projects according to claim 1, characterized in that, The optimized grounding resistance fluctuation adjustment strategy, combined with the topographic features and soil type information, assesses the required amount of rebar cage binding at the tower foundation location, prioritizing adjustments for tower foundations with resistance variations higher than the average level, and generating a differentiated rebar cage binding quantity measurement strategy, including: Based on the optimized grounding resistance fluctuation adjustment strategy, the steel reinforcement configuration parameters are extracted, and the proportion of transverse reinforcement bars is adjusted in combination with the terrain slope to generate the initial steel cage requirement. The grounding resistance contribution coefficient is calculated using the soil type information, and the influence weight of tower base stability is generated by combining the topographic relief. Tower bases with high variation are screened to form a priority adjustment sequence. Based on the priority adjustment sequence, adjust the reinforcement cage binding density and spacing, determine the number of binding points, and generate a binding parameter configuration set. Based on the binding parameter configuration set, the resistance fluctuation characteristics of the tower base area are integrated to generate a differentiated steel cage binding quantity measurement strategy.

7. The method for measuring engineering quantities based on power construction supervision projects according to claim 1, characterized in that, The step of extracting tower foundation location analysis results from the differentiated rebar cage binding quantity measurement strategy, optimizing the rebar cage binding quantity allocation ratio based on the resistivity geographical pattern subset, and generating a binding quantity measurement table with optimized resource allocation includes: The binding parameters are extracted from the differentiated rebar cage binding quantity measurement strategy, and the resource demand weights are calculated by combining the resistivity geographical law subset to generate a regionally weighted rebar configuration scheme. The total material demand is calculated based on the steel reinforcement configuration scheme. The configuration standard is adjusted. If the total steel reinforcement demand of a certain area group exceeds the project's preset total steel reinforcement limit, the steel reinforcement configuration standard of the corresponding tower base is reduced in order of priority from low to high according to the tower base resistance change rate, and a total balance distribution result is generated. Based on the allocation results, optimize the amount of steel reinforcement used, establish data records including tower base numbers and binding parameters, and generate a binding quantity measurement table for resource allocation optimization.

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