Defect detection method based on transmission line, electronic equipment and storage medium

Abstract

The present invention belongs to the technical field of defect detection of power transmission lines, and specifically discloses a defect detection method, electronic device and storage medium based on power transmission lines, including: by simulating and predicting the dancing tendency information of power transmission cables under actual wind conditions, comparing it with the actually detected dancing tendency information, identifying the corresponding difference characteristics of the dancing tendency of the power transmission cables, and evaluating the dancing risk level of the power transmission cables under wind conditions; by analyzing the evaluation coefficients of each defect condition, locating the defect conditions included in the dancing of the transmission cable, and combining the changes in the wind conditions, constructing the correlation function between the dancing of the transmission cable and the defect conditions and the wind conditions, and calculating the relationship factors between the wind conditions and each defect condition; by substituting the evaluation coefficients of each defect condition obtained in real time into the relationship function, the key defect conditions currently affecting the dancing of the transmission cable are immediately determined.

Description

Technical Field

[0001] The present invention belongs to the technical field of defect detection of power transmission lines, and relates to a defect detection method based on power transmission lines, electronic equipment and a storage medium. Background Art

[0002] With the sustained and rapid development of my country's economy, helicopter inspection has gradually become popular. Drones can be equipped with high-definition cameras to capture images of power transmission lines from multiple angles, greatly improving the efficiency and scope of power transmission line inspections. However, a large number of images taken by drones require manual defect identification and classification, which is a cumbersome and error-prone process, resulting in frequent false detections and missed detections. In order to solve the above problems, image detection technology based on deep learning has been introduced into the defect detection of power transmission lines.

[0003] There are some related solutions related to transmission line defect detection in the prior art. For example, the patent with Chinese patent publication number CN115239646A discloses a transmission line defect detection method, device, electronic device and storage medium, which obtains a transmission line inspection image, and inputs the transmission line inspection image into a pre-trained basic base area algorithm model to obtain a basic base area frame in the transmission line inspection image; determines a basic base area detection frame based on the basic base area frame, and determines a basic base area image in the transmission line inspection image based on the basic base area detection frame; inputs the basic base area image into a pre-trained transmission line defect algorithm model to obtain the transmission line defect type corresponding to the transmission line inspection image, thereby effectively improving the accuracy of the detection result of the transmission line defect type.

[0004] Although the above scheme proposes some solutions for detecting defects in transmission lines through images, there are still the following limitations. Specifically, the existing technology is more inclined to analyze static images of transmission lines, lacks exploration of the dancing posture of transmission lines, and lacks understanding of wind conditions during analysis. The dancing posture includes the real-time response of the transmission line under the action of wind, such as amplitude, frequency, dancing trajectory and other key information. This information is crucial for evaluating the stability and safety of transmission lines, but static image analysis cannot provide these data, making it difficult to accurately predict the risk of dancing failure of transmission lines under specific wind conditions.

[0005] In addition, when identifying the types of transmission line defects, the existing technology mainly conducts comprehensive defect assessment based on preset impact weights, and does not make relationship judgments based on the actual dancing state of the transmission line under wind conditions, resulting in defect assessment results that are not comprehensive and accurate. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a defect detection method based on a power transmission line, an electronic device and a storage medium are now proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides a defect detection method based on a transmission line, which includes the following steps: Step 1, obtain the scanning contour of the transmission cable structure, locate the defect areas of the transmission cable, and then evaluate the defect level α of the transmission cable itself.

[0008] Step 2: predict the dancing tendency information of the defects of the transmission cable itself under various wind conditions, and identify the tension coefficient L of the corresponding insulator of the transmission line.

[0009] Step 3: Detect defects in insulators and hardware, and determine the fluctuation compensation coefficient β of the defects in insulators and hardware to the galloping tendency information of the transmission cable.

[0010] Step 4: Obtain the corresponding wind conditions at the installation location of the transmission cable, and detect the risk level of the transmission cable dancing under the wind conditions.

[0011] Step 5: Analyze the correlation between the transmission cable dancing and defect conditions and wind conditions, locate the key defect conditions, and provide defect feedback.

[0012] The second aspect of the present invention provides an electronic device, comprising: a processor, a memory and a communication bus; the memory stores a computer-readable program that can be executed by the processor; the communication bus realizes the connection and communication between the processor and the memory; when the processor executes the computer-readable program, it implements the power transmission line defect detection method described in the present invention.

[0013] A third aspect of the present invention provides a storage medium storing one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the power transmission line defect detection method described in the present invention.

[0014] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention simulates and predicts the dancing tendency information of the transmission cable under actual wind conditions, and then compares it with the actually detected dancing tendency information to identify the corresponding different characteristics of the dancing tendency of the transmission cable, thereby evaluating the dancing risk level of the transmission cable under wind conditions and timely discovering potential dancing risks.

[0015] (2) The present invention locates the defect conditions included in the galloping of transmission cables by analyzing the evaluation coefficients of various defect conditions, and constructs a correlation function between the galloping of transmission cables and the defect conditions and wind conditions in combination with the changes in wind conditions. Based on this, the relationship factors between wind conditions and various defect conditions are calculated, providing a quantitative means to evaluate the degree of mutual influence between different factors, which is helpful to formulate more accurate and detailed maintenance strategies for different defect conditions and wind conditions.

[0016] (3) The present invention can instantly determine the key defect conditions that currently affect the galloping of transmission cables by substituting the evaluation coefficients of each defect condition obtained in real time into the relationship function. This instant response mechanism enables power operation and maintenance personnel to quickly locate the problem and take corresponding treatment measures, thereby effectively reducing the expansion of transmission line galloping faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] See also Figure 1 As shown, the first aspect of the present invention provides a defect detection method based on a transmission line, which includes the following steps: Step 1, obtain the scanning contour of the transmission cable structure, locate the defect areas of the transmission cable, and then evaluate the defect level α of the transmission cable itself.

[0021] In a preferred embodiment, the positioning of each defect area of ​​the transmission cable includes: collecting the surface structure image of the transmission cable through drone inspection, obtaining the transmission cable structure scanning contour therefrom, comparing the transmission cable structure scanning contour with the preset standard structure contour of the transmission cable, obtaining the preset texture features corresponding to each defect type, and then identifying each physical defect area, each environmental defect area and each shape defect area on the transmission cable structure scanning contour according to texture detection technology, and obtaining the defect information within the area, such as defect type, defect degree, and morphological contour.

[0022] The defect types include physical type, environmental type and shape type.

[0023] The physical defect areas include corrosion areas, broken strand areas, and wear areas.

[0024] The load-bearing defective areas include ice-covered areas, water-covered areas, and dirty areas.

[0025] The shape defect area is, for example, a diameter mismatch area, a twisted area, a local protrusion or a depression.

[0026] According to the defect information of each defect area on the scanning contour of the transmission cable structure, the defect level of the transmission cable itself is evaluated. The specific acquisition method is: extract the defect degree from the defect information of each defect area on the scanning contour of the transmission cable structure, compare it with the preset reference defect degree, take the sum of their ratios, and record it as the defect level of the transmission cable itself.

[0027] The defect degree is determined by the texture area and color value depth of the defect area. Specifically, the texture area and color value depth of the defect area are compared with the preset reference area and reference color value, and the product of their ratios is taken and marked as the defect degree.

[0028] Step 2: predict the dancing tendency information of the defects of the transmission cable itself under various wind conditions, and identify the tension coefficient L of the corresponding insulator of the transmission line.

[0029] In a preferred embodiment, the prediction of the dancing tendency information of the defects of the transmission cable itself under various wind conditions includes: using three-dimensional reconstruction technology to map the defect information of each defect area to a three-dimensional model to construct a defect structure model of the transmission cable.

[0030] The simulation software is used to simulate the dancing tendency information of the defective structure model of the transmission cable under various wind conditions, such as dancing frequency, dancing span, and dancing direction.

[0031] The dancing frequency refers to the number of vibrations per unit time caused by the transmission cable under the influence of wind conditions.

[0032] The dancing span refers to the path distance between the static position of the transmission cable and the position farthest from the static position for each vibration in the number of vibrations per unit time.

[0033] The dancing direction refers to the path to which the majority of vibrations are selected from the path distances between the static position of the transmission cable and the position farthest from the static position.

[0034] In a further preferred embodiment, the identification of the tension coefficient of the corresponding insulator of the transmission line includes: obtaining the shape parameters, material parameters, design parameters and installation parameters of the transmission cable, shape parameters such as diameter, span, length, sag, etc., material parameters such as cross-sectional area, elastic modulus, density, etc., design parameters such as design tension, safety factor, etc., installation parameters such as suspension height, tower spacing, suspension method, etc.

[0035] The shape parameters are acquired through image detection, and the material parameters, design parameters and erection parameters are structural parameters pre-arranged for the transmission line.

[0036] The parabolic model is used to calculate the geometric shape of the transmission cable according to the shape parameters of the cable, such as length, span, sag, etc., and then combined with the material parameters and installation parameters of the transmission cable, the expected tension distribution of the transmission cable at different positions is calculated using the principles of mechanics, from which the expected tension F′ at the insulator end is extracted.

[0037] Obtain the preset mechanical performance characteristics X of the insulator and the connection mode between the insulator and the transmission cable, match the connection mode between the insulator and the transmission cable with the preset connection strength corresponding to each connection mode, obtain the connection strength D between the insulator and the transmission cable, and extract the safety factor P from the design parameters to estimate the tensile force on the insulator end. Where X0 and D0 represent the preset reference mechanical performance characteristics and reference connection strength respectively, and e is a natural constant.

[0038] Obtain the design tension F in the transmission cable design parameters design , evaluate the tension coefficient of the corresponding insulator of the transmission line

[0039] Step 3: Detect defects in insulators and hardware, and determine the fluctuation compensation coefficient β of the defects in insulators and hardware to the galloping tendency information of the transmission cable.

[0040] The insulator is an important component of an electric power system, and its main function is to keep the conductors insulated from each other and from the ground, and to support and suspend the conductors and fix them on the cross arms of the tower.

[0041] The hardware includes but is not limited to various wire clamps for installing conductors, various hanging rings for forming insulator strings, various crimping tubes and repair tubes for connecting conductors, spacer rods on split conductors, etc.

[0042] The insulator and hardware defects include erosion and roughening of the insulator shed, grooves and marks of erosion of the outer covering, flashover of the insulation shed, cracking of the shed or outer covering, crushing of the outer covering, exposure of the core rod, etc.

[0043] In a preferred embodiment, the method for identifying defects in insulators and fittings is as follows: performing image acquisition on insulators and fittings, obtaining preset image textures corresponding to various defect features of insulators and fittings, comparing them with preset standard images corresponding to insulators and fittings according to texture recognition technology, obtaining texture areas corresponding to defects in insulators and fittings, extracting the corresponding defect degrees of each texture area, summing the corresponding defect degrees of each texture area, and obtaining the fluctuation compensation coefficient of insulator and fitting defects for the dancing tendency information of transmission cables.

[0044] The method for obtaining the corresponding defect degree of each texture area is the same as the above-mentioned method for obtaining the defect degree.

[0045] Step 4: Obtain the corresponding wind conditions at the installation location of the transmission cable, the wind conditions including wind direction and wind speed, and detect the risk level of the transmission cable dancing under the wind conditions.

[0046] In a preferred embodiment, the detection of the dancing risk level of the transmission cable under wind conditions includes: extracting the dancing tendency information of the transmission cable under the corresponding wind conditions at the installation location from the simulation software, collecting the actual dancing video of the transmission cable, identifying the actual dancing tendency information of the transmission cable under the wind conditions, comparing the dancing tendency information with the actual dancing tendency information, and obtaining the corresponding difference characteristics ρ of the dancing tendency of the transmission cable k , such as frequency difference, span difference, wind angle, k is the number of the difference feature, k = 1, 2,…, n.

[0047] The wind deflection angle refers to the difference between the actual swing direction of the transmission cable under the influence of wind conditions and the swing direction simulated by the simulation software.

[0048] Detect other environmental conditions corresponding to the installation location of the transmission cable, such as rain and snow intensity and sunlight intensity, and compare them with the preset benchmark environmental conditions to obtain the ratio, which is recorded as the airflow blockage characteristic ε corresponding to other environmental conditions.

[0049] The galloping risk level of the transmission cable under wind conditions is evaluated by combining the defect level α of the transmission cable itself, the tension coefficient L of the insulators at both ends of the transmission cable, and the fluctuation compensation coefficient β of the insulator and hardware defects on the galloping tendency information of the transmission cable. Where ρ′ k The k-th difference feature representing the dancing tendency of the transmission cable corresponds to a preset reference value.

[0050] The present invention can more comprehensively consider various factors that may affect the dancing behavior, such as wind speed, wind direction, cable material, etc., by simulating the dancing tendency information of the defective structural model of the transmission cable under various wind conditions. This comprehensive analysis method can more truly reflect the dancing characteristics of the transmission cable in the actual environment, predict the dancing tendency information of the transmission cable under the actual wind conditions, and then compare it with the actual detected dancing tendency information, identify the corresponding difference characteristics of the dancing tendency of the transmission cable, and evaluate the dancing risk level of the transmission cable under wind conditions accordingly, so as to timely discover potential dancing risks. When the predicted result is significantly different from the actual result, it indicates that there may be unknown defects or influencing factors, which need further inspection and processing. This early warning mechanism helps to take timely measures to prevent the occurrence of dancing failures and ensure the safe and stable operation of the power grid.

[0051] Step 5: Analyze the correlation between the transmission cable dancing and defect conditions and wind conditions, locate the key defect conditions, and provide defect feedback.

[0052] In a preferred embodiment, the analysis of the correlation between the galloping of the transmission cable and the defect conditions and the wind conditions includes: locating the defect conditions included in the galloping of the transmission cable, which include inherent defects, tension conditions, insulator and hardware defects, and installation conditions. The specific positioning method is: comparing the defect level of the transmission cable itself with the preset benchmark inherent risk level. When the inherent defect level of the transmission cable exceeds the preset benchmark inherent defect level, it indicates that the galloping defect condition of the transmission cable includes inherent defects; comparing the tension coefficient of the corresponding insulator of the transmission line with the preset tension coefficient threshold. When the corresponding insulator of the transmission line is When the tension coefficient is lower than the preset tension coefficient threshold, it means that the transmission cable galloping defect condition includes the tension condition; the fluctuation compensation coefficient of the insulator and fitting defects on the transmission cable galloping tendency information is compared with the preset benchmark fluctuation compensation coefficient. When the fluctuation compensation coefficient of the insulator and fitting defects on the transmission cable galloping tendency information exceeds the preset benchmark fluctuation compensation coefficient, it means that the transmission cable galloping defect condition includes the insulator and fitting defects; the transmission cable galloping risk level is compared with the preset benchmark galloping risk level. When the transmission cable galloping risk level exceeds the preset benchmark galloping risk level, it means that the transmission cable galloping defect condition includes the installation condition.

[0053] Extract historical monitoring data within a specified period, including the corresponding wind conditions at each time point and the defect level of the transmission cable itself α j , the tension coefficient L of the transmission cable insulator j, the fluctuation compensation coefficient β of insulator and fitting defects on the galloping tendency information of transmission cables j , the dancing risk level of transmission cables under wind conditions δj, where j is the number of the time point, j=1,2,…,τ,τ>5.

[0054] Set the indication mark of each wind direction, compare it with the wind direction in the corresponding wind force conditions at each time point, and obtain the corresponding wind direction indication mark g at each time point j , and obtain the corresponding wind speed υ at each time point j .

[0055] Constructing a linear system of equations In the formula, c0, c1, c2, c3, and c4 are all unknowns, among which c0 represents the compensation factor of the corresponding relationship between wind conditions and the defect conditions of the dancing of transmission cables, c1 represents the relationship factor between wind conditions and the defect level of the transmission cable itself, c2 represents the relationship factor between wind conditions and the tension coefficient, c3 represents the relationship factor between wind conditions and the fluctuation compensation coefficient, and c4 represents the relationship factor between wind conditions and the dancing risk level.

[0056] Use linear algebra methods (such as Gaussian elimination, LU decomposition, matrix inversion, etc.) to solve the linear equations and find the values ​​of the unknowns c0, c1, c2, c3, and c4.

[0057] The present invention locates the defect conditions included in the galloping of the transmission cable by analyzing the defect level of the transmission cable itself, the tension coefficient of the corresponding insulator of the transmission line, the fluctuation compensation coefficient of the defects of insulators and hardware on the galloping tendency information of the transmission cable, and the corresponding airflow blocking characteristics of other environmental conditions, and constructs the correlation function between the galloping of the transmission cable and the defect conditions and wind environmental conditions in combination with the changes in wind environmental conditions. Based on this, the relationship factors between the wind environmental conditions and each defect condition are calculated, providing a quantitative means to evaluate the degree of mutual influence between different factors, which is helpful to formulate more accurate and detailed maintenance strategies for different defect conditions and wind environmental conditions.

[0058] In a further preferred embodiment, the positioning of key defect conditions and performing defect feedback include: comparing the unknowns c1, c2, c3, and c4 with each other, screening out the unknowns belonging to the maximum value, extracting their corresponding defect conditions as key defect conditions, and performing defect feedback.

[0059] The linear equation group is used as the correlation function between the dancing of the transmission cable and the defect conditions and wind conditions, and the evaluation coefficient of each defect condition is obtained in real time. It is imported into the correlation function, the key defect conditions are determined in real time, and defect feedback is performed.

[0060] The evaluation coefficients corresponding to the defect conditions are specifically: the defect level of the transmission cable itself belonging to the defect itself, the tension coefficient of the insulator of the transmission cable belonging to the tension condition, the fluctuation compensation coefficient of the insulator and fittings defects on the dancing tendency information of the transmission cable belonging to the insulator and fittings defects, and the dancing risk level of the transmission cable under wind conditions belonging to the installation condition.

[0061] Specifically, the defect feedback content is: 1) when c1 is the maximum value, each physical defect area, each environmental defect area, each shape defect area on the scanning contour of the transmission cable structure and the defect information within the area are fed back.

[0062] 2) When c2 is the maximum value, the difference between the tension coefficient of the corresponding insulator of the transmission line and the preset tension coefficient threshold is obtained to adjust the insulator tension Where F0 represents the preset adjustment tension to which the unit difference of the insulator tension coefficient belongs.

[0063] 3) When c3 is at its maximum value, c3 is compared with the preset reference relationship factor c3′ of insulator and fitting defects. When c3>c3′, the defect positions of the insulator and fittings of the transmission line are fed back.

[0064] 4) When c4 is at its maximum value, c4 is compared with a preset reference relationship factor c4′ of the installation condition, and when c4>c4′, feedback is provided on the position of the transmission line.

[0065] The present invention can instantly determine the key defect conditions that currently affect the galloping of transmission cables by substituting the evaluation coefficients of each defect condition obtained in real time into the relationship function. This instant response mechanism enables power operation and maintenance personnel to quickly locate the problem and take corresponding treatment measures, thereby effectively reducing the expansion of transmission line galloping failures.

[0066] The second aspect of the present invention provides an electronic device, comprising: a processor, a memory and a communication bus; the memory stores a computer-readable program that can be executed by the processor; the communication bus realizes the connection and communication between the processor and the memory; when the processor executes the computer-readable program, it implements the power transmission line defect detection method described in the present invention.

[0067] A third aspect of the present invention provides a storage medium storing one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the power transmission line defect detection method described in the present invention.

[0068] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A defect detection method based on a transmission line, characterized in that: The method comprises the following steps: Step 1: Obtain the transmission cable structure scanning profile, locate the defect areas of the transmission cable, and then evaluate the defect level of the transmission cable itself ; Step 2: Predict the dancing tendency information of the defects of the transmission cable itself under various wind conditions, and identify the tension coefficient of the corresponding insulator of the transmission line ; Step 3: Detect insulator and hardware defects, and determine the fluctuation compensation coefficient of insulator and hardware defects on the galloping tendency information of the transmission cable ; Step 4: Obtain the wind conditions corresponding to the installation location of the transmission cable, and detect the risk level of the transmission cable dancing under the wind conditions; Step 5: Analyze the correlation between the transmission cable galloping and defect conditions and wind conditions, locate the key defect conditions, and provide defect feedback; The analysis of the correlation between the galloping of transmission cables and defect conditions and wind conditions includes: Locate the defect conditions of transmission cable galloping, including intrinsic defects, tension conditions, insulator and hardware defects, and installation conditions; Extract historical monitoring data within a specified period, including wind conditions at each time point and the level of defects in the transmission cables themselves , Tensile coefficient of transmission cable insulator , insulator and fitting defects to the fluctuation compensation coefficient of the transmission cable galloping tendency information , the risk level of transmission cable dancing in wind conditions , is the number of the time point, ; Set the indication mark of each wind direction, compare it with the wind direction in the corresponding wind force conditions at each time point, and obtain the corresponding wind direction indication mark at each time point , and obtain the corresponding wind speed at each time point ; Constructing a linear system of equations , where are all unknown, among which The compensation factor representing the corresponding relationship between wind conditions and the defective conditions of the transmission cable galloping, The factor that represents the relationship between wind conditions and the defect level of the transmission cable itself, The factor that represents the relationship between wind conditions and tension coefficient, The factor that represents the relationship between wind conditions and fluctuation compensation coefficient, Factor indicating the relationship between wind conditions and galloping risk level; Use linear algebra to solve linear equations and find unknown numbers The value of .

2. The method for defect detection based on a power transmission line according to claim 1, characterized in that: The positioning of each defective area of ​​the transmission cable includes: comparing the transmission cable structure scan profile with the preset standard structure profile of the transmission cable, identifying each physical defect area, each environmental defect area and each shape defect area on the transmission cable structure scan profile, and obtaining defect information in the area; According to the defect information of each defect area on the scanning contour of the transmission cable structure, the defect level of the transmission cable itself is evaluated.

3. The method for defect detection based on a power transmission line according to claim 1, characterized in that: The prediction of the dancing tendency information of the defects of the transmission cable itself under various wind conditions includes: using three-dimensional reconstruction technology to map the defect information of each defect area to a three-dimensional model to construct a defect structure model of the transmission cable; The simulation software is used to simulate the dancing tendency information of the defective structure model of the transmission cable under various wind conditions, including the dancing frequency, dancing span, and dancing direction; The dancing frequency is the number of vibrations per unit time caused by the transmission cable under the influence of wind conditions; The dancing span is the path distance between the static position of the transmission cable and the position farthest from the static position for each vibration in the number of vibrations per unit time; The dancing direction is a path to which the majority of vibrations are selected from the path distances between the static position of the transmission cable and the position farthest from the static position.

4. The method for defect detection based on a power transmission line according to claim 1, characterized in that: The identification of the tension coefficient of the corresponding insulator of the transmission line includes: Obtaining shape parameters, material parameters, design parameters and installation parameters of transmission cables; The parabola model is used to calculate the geometric shape of the transmission cable according to the shape parameters. Then, combined with the material parameters and installation parameters of the transmission cable, the expected tension distribution of the transmission cable at different positions is calculated using the principles of mechanics, from which the expected tension at the insulator end is extracted. ; Obtain preset mechanical performance characteristics of insulators and the connection mode between the insulator and the transmission cable, matching the connection mode between the insulator and the transmission cable with the preset connection strength corresponding to each connection mode, and obtaining the connection strength between the insulator and the transmission cable , and extract the safety factor from the design parameters , estimate the tensile force on the insulator end , where They represent the preset reference mechanical performance characteristics and reference connection strength respectively, and e is a natural constant; Obtain the design tension in the transmission cable design parameters , evaluate the tension coefficient of the corresponding insulator of the transmission line .

5. The method for defect detection based on a power transmission line according to claim 1, characterized in that: The method for detecting defects of insulators and hardware fittings comprises: performing image acquisition on insulators and hardware fittings, obtaining preset image textures corresponding to various defect features of insulators and hardware fittings, comparing them with preset standard images corresponding to insulators and hardware fittings according to texture recognition technology, obtaining texture areas corresponding to defects of insulators and hardware fittings, extracting the corresponding defect degree of each texture area, summing the corresponding defect degrees of each texture area, and obtaining the fluctuation compensation coefficient of insulator and hardware fitting defects for the dancing tendency information of transmission cables.

6. The method for defect detection based on a power transmission line according to claim 3, characterized in that: The detection of the risk level of the transmission cable dancing under wind conditions includes: Extract the dancing tendency information of the transmission cable under the corresponding wind conditions at the installation location from the simulation software, and collect the actual dancing video of the transmission cable to identify the actual dancing tendency information of the transmission cable under wind conditions, and compare and obtain the corresponding difference characteristics of the dancing tendency of the transmission cable , including frequency difference, span difference, wind angle, is the number of the difference feature, ; Detect other environmental conditions corresponding to the installation location of the transmission cable and analyze the airflow obstruction characteristics corresponding to other environmental conditions ; Assessing the risk level of transmission cable galloping in wind conditions , where Indicates the dancing tendency of the transmission cable The difference features correspond to preset reference values.

7. The method for defect detection based on a power transmission line according to claim 1, characterized in that: The key defect conditions are located and defect feedback is provided, including: The unknown Compare with each other, filter out the unknown number to which the maximum value belongs, extract its corresponding defect condition as the key defect condition, and provide defect feedback; The linear equation group is used as the correlation function between the dancing of the transmission cable and the defect conditions and wind conditions, and the evaluation coefficient of each defect condition is obtained in real time. It is imported into the correlation function, the key defect conditions are determined in real time, and defect feedback is performed.

8. An electronic device, characterized in that: include: Processor, memory and communication bus; The memory stores a computer-readable program that can be executed by the processor; the communication bus realizes the connection and communication between the processor and the memory; When the processor executes the computer-readable program, the power transmission line-based defect detection method as described in any one of claims 1 to 7 is implemented.

9. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the power transmission line-based defect detection method as described in any one of claims 1-7.

Images