A method, system, device, and medium for evaluating wire icing non-uniformity

Abstract

The present application relates to the technical field of power transmission line anti-icing and disaster mitigation, and discloses a conductor icing unevenness evaluation method, system, device and medium, comprising: setting multiple monitoring points along the conductor and collecting icing data; calculating the equivalent icing thickness of each point according to the icing thickness, density and shape; calculating three evaluation indexes of the variation coefficient, the range ratio and the skewness coefficient based on the equivalent thickness; calculating the comprehensive evaluation value of the icing unevenness by using a weighted comprehensive evaluation model; and dividing the unevenness level according to the comprehensive evaluation value. The present application eliminates the influence of the icing density and shape difference by constructing a multi-dimensional evaluation index system, realizes the quantitative evaluation and level division of the icing spatial distribution unevenness, and provides a scientific basis for the differentiated operation and maintenance and precise anti-icing decision of the power transmission line.

Description

Technical Field

[0001] This invention relates to the field of transmission line anti-icing and disaster reduction technology, and in particular to a method, system, equipment and medium for assessing the unevenness of conductor icing. Background Technology

[0002] Icing on transmission lines is a significant factor affecting the safe operation of power grids. Due to the vast areas traversed by transmission lines and the significant differences in terrain, altitude, and microclimate conditions along the routes, icing on conductors within the same span or tension section often exhibits an uneven distribution. This uneven icing can lead to unbalanced stress on adjacent towers, increasing the risk of tower overturning; localized stress concentration on conductors, accelerating hardware wear and fatigue damage; uneven icing can cause jumping phenomena, triggering phase-to-phase flashovers or ground discharges; and inaccurate calculation methods for conventional equivalent icing thickness can affect the assessment of line safety margins.

[0003] Current technologies for monitoring and assessing conductor icing primarily focus on the absolute or equivalent value of ice thickness, lacking a systematic quantitative assessment method for the spatial unevenness of ice distribution. Therefore, there is an urgent need to establish a scientific and comprehensive method for assessing conductor icing unevenness, providing technical support for differentiated operation and maintenance and precise anti-icing measures for transmission lines. Summary of the Invention

[0004] In view of the above-mentioned existing problems, the present invention provides a method, system, device and medium for evaluating the unevenness of conductor icing.

[0005] Therefore, the technical problem solved by this invention is to achieve quantitative assessment and classification of the degree of unevenness in the spatial distribution of ice accretion on conductors by establishing a multi-dimensional evaluation index system and comprehensive evaluation model for ice accretion unevenness.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a method for assessing conductor icing unevenness, comprising: setting icing monitoring points along the line direction on the conductor of the transmission line to be monitored, and collecting icing data at each monitoring point at the same time; calculating the equivalent icing thickness at each monitoring point based on the icing data; calculating a conductor icing unevenness assessment index based on the equivalent icing thickness at each monitoring point; calculating a comprehensive evaluation value for icing unevenness using a comprehensive evaluation model based on the icing unevenness assessment index; and determining the conductor icing unevenness level based on the comprehensive evaluation value for icing unevenness.

[0007] As a preferred embodiment of the method for evaluating the non-uniformity of conductor icing described in this invention, the equivalent icing thickness of each monitoring point is obtained by comprehensively calculating the measured icing thickness at each monitoring point, the ratio of its icing density to the standard ice density, and the shape correction coefficient determined based on the icing shape.

[0008] As a preferred embodiment of the method for evaluating the non-uniformity of conductor icing according to the present invention, the value of the shape correction coefficient is determined by judging the icing shape category, wherein the icing shape category includes circular or near-circular, elliptical, crescent or wing-shaped, and irregular shapes, and each category corresponds to a different range of coefficient values.

[0009] As a preferred embodiment of the method for evaluating the non-uniformity of conductor icing described in this invention, the coefficient of variation of icing thickness is obtained by calculating the average value and standard deviation of the equivalent icing thickness at each monitoring point. The ice thickness range ratio is obtained by calculating the ratio of the difference between the maximum and minimum equivalent ice thickness to the average value. The skewness coefficient of the icing distribution is obtained by calculating the ratio of the third central moment of the equivalent icing thickness distribution to the cube of the standard deviation.

[0010] In a preferred embodiment of the conductor icing unevenness assessment method described in this invention, the comprehensive evaluation model is a weighted comprehensive evaluation model, and the formula for calculating the comprehensive evaluation value U of icing unevenness is as follows: in, , , These are the normalized values ​​of the coefficient of variation of icing thickness, the range ratio of icing thickness, and the skewness coefficient of icing distribution, respectively. , , These are the weighting coefficients for the corresponding indicators, and .

[0011] As a preferred embodiment of the conductor icing unevenness assessment method of the present invention, the determination of the conductor icing unevenness level includes comparing the comprehensive evaluation value with a predefined threshold, which corresponds to four unevenness levels: uniform icing distribution, slight unevenness, moderate unevenness, and severe unevenness.

[0012] As a preferred embodiment of the method for evaluating the unevenness of conductor icing according to the present invention, the method for setting up icing monitoring points includes: Within the tension section of the transmission line, monitoring points are set at equal intervals along the direction of the conductor; In areas with dramatic topographic changes, significant micro-topographic effects, or frequent historical icing accidents, monitoring points should be densely deployed. The methods for collecting icing data include: Install icing sensors at monitoring points and measure the icing load and calculate the icing thickness using the tensile weighing method or the torsion angle method. Image acquisition devices are installed at monitoring points, and image recognition algorithms are used to analyze ice morphology parameters. Drones equipped with lidar or visible light cameras are used to inspect the power lines and obtain three-dimensional morphological data of the ice accretion. The ice thickness is calculated by inverting the vibration frequency of the conductor after it is covered with ice using the vibration method.

[0013] This invention provides a system for evaluating the unevenness of icing on conductors.

[0014] As a preferred embodiment of the conductor icing non-uniformity assessment system of the present invention, it includes: The data acquisition module is used to collect icing data from N monitoring points arranged along the conductor direction. The icing data includes icing thickness, icing shape parameters, and icing density. The equivalent icing calculation module is used to calculate the equivalent icing thickness of each monitoring point based on the icing data of each monitoring point. The non-uniformity index calculation module is used to calculate the coefficient of variation of ice thickness, the range ratio of ice thickness, and the skewness coefficient of ice distribution based on the equivalent ice thickness at each monitoring point. The comprehensive evaluation module is used to calculate the comprehensive evaluation value of icing unevenness based on the icing unevenness assessment index using a comprehensive evaluation model. The rating module is used to determine the rating of uneven icing on the conductor based on the comprehensive evaluation value of uneven icing and to output the evaluation results.

[0015] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a method for evaluating the non-uniformity of wire icing.

[0016] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for evaluating the non-uniformity of wire icing.

[0017] The beneficial effects of this invention are as follows: A multi-dimensional evaluation index system for icing unevenness is established, comprehensively characterizing the spatial distribution characteristics of icing from three perspectives: dispersion, extreme differences, and distribution skewness; the use of equivalent icing thickness eliminates the influence of differences in icing density and shape, making icing data from different monitoring points comparable; the comprehensive evaluation model integrates multiple index information, making the evaluation results more reliable and providing a scientific basis for differentiated operation and maintenance and precise anti-icing of transmission lines; the clear classification of levels facilitates maintenance personnel to quickly determine the line status and take corresponding measures. Attached Figure Description

[0018] 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.

[0019] Figure 1 This is a schematic flowchart of a method for evaluating the unevenness of icing on a conductor, provided in one embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of the icing monitoring point layout for a method for assessing uneven icing of conductors according to an embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of different icing shapes provided in an embodiment of the present invention for evaluating the unevenness of conductor icing.

[0022] Figure 4 The equivalent ice thickness distribution at each monitoring point is provided in an embodiment of the present invention for a method for evaluating the non-uniformity of conductor icing.

[0023] Figure 5 A radar chart showing the icing unevenness assessment results of a method for assessing the icing unevenness of a conductor, provided in an embodiment of the present invention. Detailed Implementation

[0024] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0025] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a method for evaluating the unevenness of conductor icing, comprising: S1: Set up icing monitoring points along the line direction on the conductor of the transmission line to be monitored, and collect icing data at each monitoring point at the same time.

[0026] S2: Calculate the equivalent icing thickness at each monitoring point based on the icing data at each monitoring point.

[0027] S3: Calculate the evaluation index of uneven icing on the conductor based on the equivalent icing thickness at each monitoring point.

[0028] S4: Based on the aforementioned icing unevenness assessment index, calculate the comprehensive evaluation value of icing unevenness using a comprehensive evaluation model.

[0029] S5: Determine the level of uneven icing on the conductor based on the comprehensive evaluation value of the uneven icing.

[0030] It should be noted that, in response to the problem that existing conductor icing monitoring technologies only focus on the absolute or equivalent value of thickness and lack a systematic quantitative assessment of the unevenness of spatial distribution of icing, a multi-dimensional assessment index system was established. The equivalent icing thickness calculation was introduced to eliminate the influence of density and shape differences. Furthermore, a comprehensive evaluation model and grading method were adopted to achieve a quantitative assessment of the degree of unevenness in the spatial distribution of icing. This provides a direct technical basis for differentiated operation and maintenance and precise icing prevention of transmission lines.

[0031] Example 2, refer to Figure 2 - Figure 5 As an embodiment of the present invention, based on the above embodiment, a method for evaluating the unevenness of conductor icing is provided.

[0032] Furthermore, in this embodiment of the application, step S1 involves setting up icing monitoring points along the line direction on the conductor of the transmission line to be monitored, and collecting icing data at each monitoring point at the same time. The specific steps include: N icing monitoring points are set up along the line direction on the conductor of the transmission line to be monitored, N≥3; icing data of each monitoring point at the same time are collected, including icing thickness, icing shape parameters and icing density.

[0033] Furthermore, in this embodiment of the application, step S2 calculates the equivalent icing thickness at each monitoring point based on the icing data at each monitoring point. The specific steps include: Based on the icing data from each monitoring point, the equivalent icing thickness at each monitoring point is calculated. Since there are differences in icing density and icing shape among different monitoring points, directly comparing the measured icing thickness cannot accurately reflect the differences in icing load. Therefore, it is necessary to convert the measured icing thickness into the equivalent icing thickness under standard conditions.

[0034] The formula for calculating the equivalent ice thickness at the i-th monitoring point is: In the formula: The equivalent icing thickness at the i-th monitoring point is expressed in mm. The measured ice thickness at the i-th monitoring point is in mm. The ice density at the i-th monitoring point is expressed in g / cm³. The standard ice density is 0.9 g / cm³. Let be the icing shape correction coefficient for the i-th monitoring point, which is dimensionless.

[0035] Ice shape correction factor The rules for determining the value are as follows: (1) Circular or nearly circular ice cover: =1.0, at which point the ice is evenly distributed around the conductor, and the cross-section is close to a circle; (2) Elliptical ice cover: =0.85~0.95, at this point the ice is thicker on the windward side and thinner on the leeward side, and the cross-section is elliptical; (3) Crescent-shaped or wing-shaped icing: =0.70~0.85, at which point the ice mainly deposits on the windward side, forming an asymmetrical structure; (4) Irregularly shaped ice covering: =0.60~0.70, at which point the ice is affected by complex airflow and has an irregular shape.

[0036] For elliptical icing, the shape correction factor can be accurately calculated using the following formula: In the formula: a is the major axis radius of the ice-covered cross section, in mm; b is the minor axis radius of the ice-covered cross section, in mm.

[0037] In an optional embodiment, determining the shape correction coefficient can also merge and simplify the categories of icing shapes, distinguishing them into only three categories: "symmetrical icing" (corresponding to the original circular / approximate circular shape), "unilaterally thicker icing" (merging the original elliptical, crescent-shaped, and wing-shaped shapes), and "irregular icing". A fixed shape correction coefficient value or a wider range of values ​​can be directly set for each category, thereby reducing the complexity of shape recognition and classification.

[0038] In another alternative embodiment, the shape correction coefficient can also be determined by directly calculating a quantitative parameter that reflects the symmetry of the ice distribution through image analysis, and establishing a linear or piecewise functional correspondence between the parameter and the shape correction coefficient, and directly determining the Ki value by looking up a table or by calculation.

[0039] Furthermore, in this embodiment of the application, step S3 calculates the evaluation index of conductor icing non-uniformity based on the equivalent icing thickness at each monitoring point. The specific steps include: Based on the equivalent ice thickness at each monitoring point, three indicators for evaluating ice non-uniformity are calculated: the coefficient of variation of ice thickness, the range ratio of ice thickness, and the skewness coefficient of ice distribution.

[0040] (1) Basic statistics of equivalent icing thickness First, calculate the basic statistics of the equivalent ice thickness at each monitoring point: average value: in, The average value is given by N, which represents the total number of monitoring points. Standard deviation: in, Indicates standard deviation; Maximum and minimum values: (2) Coefficient of variation of ice thickness The coefficient of variation reflects the dispersion of ice thickness relative to the average value and is a core indicator for measuring the overall uniformity of ice cover. A higher coefficient of variation indicates a greater dispersion in ice thickness and a more uneven ice distribution. Generally speaking, When the value is less than 0.1, the ice distribution is considered uniform; when the value is less than or equal to 0.1, the ice distribution is considered uniform. A value <0.3 indicates slight unevenness. A value ≥0.3 indicates significant inhomogeneity.

[0041] In an alternative embodiment, the coefficient of variation for icing thickness can be calculated using the ratio of the mean absolute deviation to the mean. The absolute deviation of the equivalent icing thickness at each point from the mean is calculated, then the average of these absolute deviations is calculated, and finally, this average is divided by the average thickness.

[0042] In another alternative embodiment, the coefficient of variation for icing thickness can also be calculated using the ratio of the interquartile range to the median to assess the degree of dispersion. The equivalent icing thickness data for all monitoring points are sorted by size, the difference between the upper and lower quartiles is calculated to obtain the interquartile range, and this interquartile range is then divided by the median of all thicknesses.

[0043] (3) Ice thickness range ratio The range ratio reflects the relative difference between the maximum and minimum ice thickness and is an important indicator for measuring the extreme unevenness of ice accumulation. A larger range ratio indicates a more pronounced extreme difference in icing thickness. The range ratio is sensitive to localized anomalous icing and can capture extreme cases where the coefficient of variation might be negligible.

[0044] (4) Skewness coefficient of ice distribution The skewness coefficient reflects the symmetry and skewness direction of the ice thickness distribution: when When = 0, the ice thickness is symmetrically distributed; when When the value is >0, the distribution is skewed to the right, meaning that a few monitoring points have particularly severe icing; when When the skewness coefficient is less than 0, the distribution is skewed to the left, meaning that a few monitoring points have very slight icing. The larger the absolute value of the skewness coefficient, the more severe the skewness of the icing distribution.

[0045] In an optional embodiment, the Pearson skewness coefficient can also be used to assess the distribution pattern when calculating the icing distribution skewness coefficient. The difference between the mean and median of the equivalent icing thickness is calculated, and then this difference is divided by the standard deviation.

[0046] In another optional embodiment, the skewness coefficient of the icing distribution can also be calculated by qualitatively determining the direction of skewness by comparing the relative positions of different quartiles with the median. The difference between the upper quartile and the median, and the difference between the median and the lower quartile are calculated. By comparing the magnitude of these two differences, it can be determined whether the distribution is skewed upward (right) or downward (left). The degree of skewness can be roughly measured by the ratio of the two differences.

[0047] (5) Spatial correlation index I s To further analyze the spatial distribution characteristics of icing, a spatial autocorrelation index based on Moran's I can be introduced: In the formula: For the elements of the spatial weight matrix, when monitoring points i and j are adjacent... =1, otherwise =0; W is the sum of the elements of the spatial weight matrix.

[0048] I s The value range of I is [-1, 1]. s A value close to 1 indicates that the icing is spatially clustered and that adjacent areas have similar icing patterns; I s A value close to -1 indicates that the icing is spatially discrete, with significant differences in icing between adjacent areas; I s A value close to 0 indicates that the icing is randomly distributed with no obvious spatial correlation.

[0049] Furthermore, in this embodiment of the application, step S4 calculates the comprehensive evaluation value of icing unevenness using a comprehensive evaluation model based on the aforementioned icing unevenness evaluation index. The specific steps include: Based on the evaluation index of icing unevenness, a weighted comprehensive evaluation model is used to calculate the comprehensive evaluation value of icing unevenness.

[0050] (1) Indicator normalization processing Because the dimensions and value ranges of the various evaluation indicators are different, normalization is required. The min-max normalization method is used: The reference range values ​​for each indicator are shown in the table below:

[0051] (2) Determination of weighting coefficients The weighting coefficients can be determined using the Analytic Hierarchy Process (AHP) or the entropy weighting method. This invention recommends using a combination of subjective and objective weighting methods, comprehensively considering expert experience and the amount of data information.

[0052] The steps for determining subjective weights using the analytic hierarchy process are as follows: Construct judgment matrix A: in The importance of index i relative to index j is indicated by the 1-9 scale.

[0053] Calculate the weight vector: Consistency check: Where CR is the consistency ratio, CI is the consistency index, RI is the random consistency index, and n is the order of the judgment matrix. When CR < 0.1, the judgment matrix has satisfactory consistency.

[0054] The steps for determining objective weights using the entropy weight method are as follows: Calculate the entropy value of the j-th index: in p ij Let represent the weight of the j-th indicator in the i-th sample.

[0055] Calculate objective weights: Combined weights: Where α is the subjective weight adjustment coefficient, and a value of 0.5 is recommended. Let be the subjective weight of the j-th indicator. Based on engineering experience, the recommended weight range is: , , These are the weighting coefficients for the corresponding indicators, and .

[0056] In an optional embodiment, the weight coefficients of each evaluation index can also be determined based on generally recognized engineering experience or historical evaluation practices in the field. A fixed weight value is assigned to each of the three indexes of the coefficient of variation, the range ratio, and the absolute value of the skewness coefficient, and it is ensured that the sum of the three weights is 1.

[0057] In another optional embodiment, the weight coefficients of each evaluation index can also be qualitatively ranked for the importance of the three evaluation indexes by experts or based on the results of historical data analysis. According to the preset weight distribution rules corresponding to the ranking, the weight coefficients of each index are directly calculated.

[0058] (3) Comprehensive evaluation value calculation The calculation formula for the comprehensive evaluation value U of ice accretion non-uniformity is: The value range of the comprehensive evaluation value U is [0, 1]. The larger the U value, the more serious the degree of ice accretion non-uniformity.

[0059] Furthermore, in the implementation manner of the present application, step S5 determines the grade of conductor ice accretion non-uniformity according to the comprehensive evaluation value of ice accretion non-uniformity. The specific steps include: According to the comprehensive evaluation value U of ice accretion non-uniformity, the conductor ice accretion non-uniformity is divided into four grades; When U ≤ 0.2, it is determined as grade I, indicating that the ice accretion distribution is uniform and routine monitoring is carried out; When 0.2 < U ≤ 0.4, it is determined as grade II, indicating that the ice accretion distribution is slightly non-uniform, enhanced monitoring is carried out, and the development trend is concerned; When 0.4 < U ≤ 0.6, it is determined as grade III, indicating that the ice accretion distribution is moderately non-uniform, early warning is given, and ice melting measures are prepared; When U > 0.6, it is determined as grade IV, indicating that the ice accretion distribution is severely non-uniform, ice melting is immediately started, and key inspections are carried out.

[0060] Embodiment 3 is the third embodiment of the present invention. The difference from the previous two embodiments is: This embodiment also provides a system for evaluating conductor ice accretion non-uniformity, including: A data acquisition module for acquiring ice accretion data of N monitoring points arranged along the conductor direction. The ice accretion data includes ice accretion thickness, ice accretion shape parameters, and ice accretion density; An equivalent ice accretion calculation module for calculating the equivalent ice accretion thickness of each monitoring point according to the ice accretion data of each monitoring point; A non-uniformity index calculation module for calculating the coefficient of variation of ice accretion thickness, the range ratio of ice accretion thickness, and the skewness coefficient of ice accretion distribution based on the equivalent ice accretion thickness of each monitoring point; The comprehensive evaluation module is used to calculate the comprehensive evaluation value of icing unevenness based on the icing unevenness assessment index using a comprehensive evaluation model. The rating module is used to determine the rating of uneven icing on the conductor based on the comprehensive evaluation value of uneven icing and to output the evaluation results.

[0061] This embodiment also provides an electronic device, including: 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 wire icing non-uniformity evaluation method proposed in the above embodiment.

[0062] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a method for evaluating the unevenness of wire icing as proposed in the above embodiments.

[0063] The storage medium proposed in this embodiment and the method for evaluating the non-uniformity of wire icing proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0064] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0065] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not 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.

[0066] Example 4 is an embodiment of the present invention, used to verify a method for evaluating the unevenness of conductor icing.

[0067] Taking a tension section of a 220kV transmission line as an example, the specific application process of the method of the present invention is explained. The tension section is about 500 meters long and passes through mountainous terrain and mountain passes. Historically, there have been accidents caused by increased sag due to icing.

[0068] Eight icing monitoring points (N=8) were set up within the tension section, numbered 1# to 8#, with a spacing of approximately 150 meters. The icing data collected from each monitoring point during a particular icing event are shown in the table below:

[0069] Taking monitoring point #1 as an example, the calculation process for the equivalent icing thickness is as follows: =12.5×(0.85 / 0.9)×0.90=10.63mm Similarly, the equivalent ice thickness at other monitoring points was calculated, and the results are shown in the last column of the table above.

[0070] Step 3: Calculation of evaluation index for uneven icing (1) Calculation of basic statistics average value: μ=(10.63+13.67+19.01+25.30+23.21+19.24+12.04+12.15) / 8=16.91mm Standard deviation: σ= =5.31mm Maximum and minimum values: =25.30mm =10.63mm (2) Coefficient of variation of ice thickness =5.31 / 16.91=0.314 (3) Ice thickness range ratio =(25.30-10.63) / 16.91=0.867 (4) Skewness coefficient of ice distribution Calculate the cubic deviation for each monitoring point: = (-6.28)³ + (-3.24)³ + (2.10)³ + (8.39)³ + (6.30)³ + (2.33)³ + (-4.87)³ + (-4.76)³ = -247.67 - 34.01 + 9.26 + 590.59 + 250.05 + 12.65 - 115.50 - 107.85 = 357.52 = (357.52 / 8) / 5.31³ = 44.69 / 149.72 = 0.298 Comprehensive evaluation of ice accretion non-uniformity (1)Index normalization = (0.314 - 0) / (1.0 - 0) = 0.314 = (0.867 - 0) / (2.0 - 0) = 0.434 = (|0.298| - 0) / (3.0 - 0) = 0.099 (2)Weight coefficient This embodiment adopts the recommended weights: w1 = 0.40, w2 = 0.35, w3 = 0.25 (3)Calculation of comprehensive evaluation value U = 0.40 × 0.314 + 0.35 × 0.434 + 0.25 × 0.099 = 0.126 + 0.152 + 0.025 = 0.303 Judgment of ice accretion non-uniformity level The comprehensive evaluation value U = 0.303, which meets the condition of 0.2 < U ≤ 0.4. Therefore, the ice accretion non-uniformity of the conductors in this strain section is judged as level II (slightly non-uniform).

[0071] Suggested measures: Strengthen the monitoring frequency of this line section, closely monitor the development trend of ice accretion, especially the pass area where the monitoring points 4# and 5# are located, and arrange ice melting preparation in advance if necessary.

[0072] Summary of evaluation results:

Claims

1. A method for evaluating the unevenness of icing on conductors, characterized in that: include, Ice accretion monitoring points are set up along the direction of the transmission line to be monitored on the conductor, and ice accretion data of each monitoring point are collected at the same time. Calculate the equivalent icing thickness at each monitoring point based on the icing data at each monitoring point; Based on the equivalent icing thickness at each monitoring point, the evaluation index for uneven icing of the conductor is calculated. Based on the aforementioned icing unevenness assessment index, a comprehensive evaluation model is used to calculate the comprehensive evaluation value of icing unevenness. The level of uneven icing on the conductor is determined based on the comprehensive evaluation value of the uneven icing.

2. The method for evaluating the unevenness of conductor icing as described in claim 1, characterized in that, The equivalent ice thickness at each monitoring point is obtained by comprehensively calculating the measured ice thickness at each monitoring point, the ratio of its ice density to the standard ice density, and the shape correction coefficient determined based on the ice shape.

3. The method for evaluating the unevenness of conductor icing as described in claim 2, characterized in that: The value of the shape correction coefficient is determined by judging the ice shape category, which includes circular or near-circular, elliptical, crescent or wing-shaped, and irregular shapes. Each category corresponds to a different range of coefficient values.

4. The method for evaluating the unevenness of conductor icing as described in claim 3, characterized in that: The coefficient of variation of ice thickness is obtained by calculating the average value and standard deviation of the equivalent ice thickness at each monitoring point; The ice thickness range ratio is obtained by calculating the ratio of the difference between the maximum and minimum equivalent ice thickness to the average value. The skewness coefficient of the icing distribution is obtained by calculating the ratio of the third central moment of the equivalent icing thickness distribution to the cube of the standard deviation.

5. The method for evaluating the unevenness of conductor icing as described in claim 4, characterized in that: The comprehensive evaluation model is a weighted comprehensive evaluation model, and the formula for calculating the comprehensive evaluation value U of icing unevenness is as follows: in, , , These are the normalized values ​​of the coefficient of variation of icing thickness, the range ratio of icing thickness, and the skewness coefficient of icing distribution, respectively. , , These are the weighting coefficients for the corresponding indicators, and .

6. The method for evaluating the unevenness of conductor icing as described in claim 5, characterized in that: The determination of the unevenness level of conductor icing includes comparing the comprehensive evaluation value with a predefined threshold, which corresponds to four unevenness levels: uniform icing distribution, slight unevenness, moderate unevenness, and severe unevenness.

7. The method for evaluating the unevenness of conductor icing as described in claim 6, characterized in that, The methods for setting up icing monitoring points include: Within the tension section of the transmission line, monitoring points are set at equal intervals along the direction of the conductor; In areas with dramatic topographic changes, significant micro-topographic effects, or frequent historical icing accidents, monitoring points should be densely deployed. The methods for collecting icing data include: Install icing sensors at monitoring points and measure the icing load and calculate the icing thickness using the tensile weighing method or the torsion angle method. Image acquisition devices are installed at monitoring points, and image recognition algorithms are used to analyze ice morphology parameters. Drones equipped with lidar or visible light cameras are used to inspect the power lines and obtain three-dimensional morphological data of the ice accretion. The ice thickness is calculated by inverting the vibration frequency of the conductor after it is covered with ice using the vibration method.

8. A system for assessing the unevenness of conductor icing, employing the method for assessing the unevenness of conductor icing as described in any one of claims 1 to 7, characterized in that, include: The data acquisition module is used to collect icing data from N monitoring points arranged along the conductor direction. The icing data includes icing thickness, icing shape parameters, and icing density. The equivalent icing calculation module is used to calculate the equivalent icing thickness of each monitoring point based on the icing data of each monitoring point. The non-uniformity index calculation module is used to calculate the coefficient of variation of ice thickness, the range ratio of ice thickness, and the skewness coefficient of ice distribution based on the equivalent ice thickness at each monitoring point. The comprehensive evaluation module is used to calculate the comprehensive evaluation value of icing unevenness based on the icing unevenness assessment index using a comprehensive evaluation model. The rating module is used to determine the rating of conductor icing unevenness based on the comprehensive evaluation value of icing unevenness and output the evaluation results.

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 evaluating the unevenness of conductor icing as described in any one of claims 1 to 7.

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 evaluating the non-uniformity of conductor icing as described in any one of claims 1 to 7.

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