Conductor sag curve construction method for heavy-load line

Abstract

The invention discloses a conductor sag curve construction method for a heavy-load line, and belongs to the technical field of conductor sag construction, and the method comprises the steps: carrying out the initial parameter setting of an unmanned aerial vehicle according to differentiated environmental conditions, collecting the conductor video of each survey sub-road section, carrying out the iterative optimization of the parameters of the unmanned aerial vehicle, and judging the number of image cutting, and generating a conductor sag analysis image set of each surveying sub-road section, analyzing a conductor sag deviation correction value, generating an ideal conductor sag curve, generating a corrected conductor sag curve, and outputting the ideal conductor sag curve and the corrected conductor sag curve. According to the method, the actual operation condition of the existing line in the target building area can be accurately considered, the ideal and corrected conductor sag curve is finally built, accurate data reference is provided for line design, building and operation maintenance, line faults caused by the conductor sag problem are reduced, unmanned aerial vehicle survey data transmission is dynamically adjusted, and the unmanned aerial vehicle survey data transmission efficiency is improved. And stable and accurate transmission of data is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of conductor sag construction, and in particular to a method for constructing a conductor sag curve for a heavy-load line. Background Art

[0002] As electricity demand continues to grow, high-load transmission lines are becoming increasingly important in power transmission. Their operational status directly impacts the stability and reliability of power supply. Conductor sag is a key factor affecting the safe and stable operation of high-load transmission lines. Constructing accurate conductor sag curves is crucial for ensuring normal operation.

[0003] For example, the invention patent publication number CN112577455B discloses a cable sag monitoring device based on the Beidou high-precision positioning system, which includes a measuring vehicle and a ground server. The measuring vehicle is equipped with a Beidou high-precision positioning system and a data transmission unit, and the ground server includes a data transceiver unit, a sag intelligent detection system, a display, an operation control unit, a data storage unit, a data processing unit, a data prediction unit, a sag judgment unit, and a cable database.

[0004] For example, the invention patent announcement with publication number: CN111272117B discloses an online monitoring system for sag of overhead transmission lines, comprising: a map acquisition unit for acquiring digital maps and topographic maps within the range to be monitored; a transmission line tower acquisition unit for acquiring design drawings of transmission line towers within the range to be monitored and obtaining size and contour information of the transmission line towers; a three-dimensional data acquisition unit for regularly acquiring data on trees and buildings along the transmission line that pose a potential threat to the transmission line; a three-dimensional modeling unit for establishing a three-dimensional model of the transmission line based on data collected by the map acquisition unit, the transmission line tower acquisition unit and the three-dimensional data acquisition unit; a sag detection unit for acquiring sag information of the transmission line in real time; and a central processing unit connected to the three-dimensional modeling unit and the sag detection unit, respectively.

[0005] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: During initial line design, conductor sag calculations often rely solely on fixed methods, failing to fully consider complex and variable field environmental factors. This is especially true for heavily loaded lines, where the significant thermal effects of current can lead to significant variations in conductor expansion and contraction. These variations exhibit nonlinear characteristics, causing significant deviations between fixed calculation results and actual conditions. Consequently, in actual operation, conductor sag is less compatible with design expectations, impacting safe and stable line operation, increasing maintenance costs, and posing potential risks. Summary of the Invention

[0006] The present invention provides a method for constructing a conductor sag curve for a heavy-load line, comprising the following steps: S1, through the multimodal sensors carried by the UAV, the differentiated environmental conditions of the target route are obtained, and the initial parameters of the UAV are set according to the differentiated environmental conditions.

[0007] S2: Divide the target survey line into survey sub-sections based on the transmission line racks, collect conductor videos of each survey sub-section, iteratively optimize the drone parameters, determine the number of image cuts, and generate a conductor sag analysis image set for each survey sub-section.

[0008] S3, analyzing the conductor sag deviation correction value based on the conductor sag analysis image set of each survey sub-section.

[0009] S4, obtaining the preset conductor sag of each constructed sub-section, generating an ideal conductor sag curve, and simultaneously combining the deviation correction result of the conductor sag to generate a corrected conductor sag curve and output it.

[0010] One or more technical solutions provided in the present invention have at least the following technical effects or advantages: 1. The present invention provides a method for constructing a conductor sag curve for a high-load line. The method can accurately consider the actual operating conditions of existing lines in the target construction area. During the data collection phase, a drone equipped with a multimodal sensor is used for flight surveys, and drone parameters are iteratively optimized. High-quality conductor videos and accurate conductor status data are collected in combination with complex environmental conditions, providing a more accurate data basis for subsequent analysis. Ultimately, an ideal and corrected conductor sag curve is constructed, providing an accurate data reference for line design, construction, and operation and maintenance. This reduces line failures caused by conductor sag problems, reduces maintenance costs and potential risks, and effectively ensures the reliability of power transmission on high-load lines. In addition, dynamic adjustment of drone survey data transmission further ensures stable and accurate data transmission, improving the reliability and stability of the entire line monitoring and analysis.

[0011] 2. By iteratively optimizing the drone parameters, the present invention can dynamically adjust the drone parameters for the next survey section based on the quality of the conductor video of each survey sub-section, so that the drone can always maintain the best shooting and data collection state under different environmental conditions and line conditions, and can continuously obtain high-quality conductor videos, providing clear and accurate data for subsequent precise analysis of conductor sag, improving the efficiency and accuracy of data collection, and reducing analysis errors caused by poor video quality.

[0012] 3. This invention optimizes the use of computing resources by determining the number of images used for conductor sag analysis based on the quality of the monitoring video of each survey sub-section and the complexity of the conductor status. Furthermore, when the video quality is poor or the conductor status is complex, the number of image cuts is increased to ensure that enough images are obtained to comprehensively and meticulously present the conductor status, thereby improving the integrity and accuracy of the conductor sag analysis data and providing a precise data basis for subsequent more accurate analysis of conductor sag values ​​and construction of accurate conductor sag curves.

[0013] 4. The present invention analyzes the conductor sag deviation correction value and compares the deviation between the actual conductor sag value and the ideal conductor sag value under normal and harsh environments to correct the theoretical calculation results. This helps to accurately construct the conductor sag curve, ensure that the conductor sag of heavy-load lines in actual operation is more in line with design expectations, reduce line failures caused by abnormal sag, reduce maintenance costs and potential risks, and ensure the stability and reliability of power supply.

[0014] 5. The present invention dynamically adjusts the transmission of UAV survey data based on the UAV flight survey environment, can adapt to the complex and changeable flight environment in real time, ensure the stability and accuracy of data transmission, increase the transmission frequency band when interference is serious, use multiple frequency bands to transmit data simultaneously, enhance anti-interference ability, effectively avoid data loss, delay or error caused by environmental interference, ensure the complete and reliable acquisition of data required for conductor sag analysis, and provide accurate data basis for accurately constructing the conductor sag curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a method for constructing a conductor sag curve for a heavy-load line provided in an embodiment of the present application; DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0017] Reference Figure 1 As shown, the present invention provides a method for constructing a conductor sag curve for a heavy-load line, comprising the following steps: S1, through the multimodal sensors carried by the UAV, the differentiated environmental conditions of the target route are obtained, and the initial parameters of the UAV are set according to the differentiated environmental conditions.

[0018] In a specific embodiment, a multimodal sensor is used to capture wire video and detect drone flight environment data.

[0019] In this embodiment, the differentiated environmental conditions of the target route are obtained, and the initial parameters of the drone are set according to the differentiated environmental conditions. The specific analysis method is as follows: The differentiated environmental conditions include normal environment and adverse environment.

[0020] Extract the initial parameters of the UAV corresponding to the differentiated environmental conditions in the database, and set the initial parameters of the UAV accordingly.

[0021] The initial parameters of the UAV include the speed of the UAV, the exposure time of the camera, the integration time of the spectrometer and the data compression rate.

[0022] It should be understood that the spectrometer integration time refers to the length of time that each pixel is continuously exposed to accumulate light signals when the sensor collects spectral data.

[0023] It should be noted that the rules for determining differentiated environmental adjustments are pre-set in the database. In one specific embodiment, a normal environment is determined when the ambient temperature is between -10°C and 40°C, the relative humidity is less than 85%, the wind speed is less than 10m / s, and there is no precipitation. The initial drone parameters are: 15m / s speed, 1 / 1000s camera exposure time, 50ms spectrometer integration time, and a data compression ratio of 3:1. A severe environment is determined when any of the following conditions occur: the temperature is outside the range of -10°C to 40°C, the relative humidity is greater than or equal to 85%, the wind speed is greater than or equal to 10m / s, and there is rain or snow. In this case, the drone parameters are: 8m / s speed for stability, 1 / 500s camera exposure time to compensate for motion blur, 30ms spectrometer integration time to reduce motion blur, and a 5:1 data compression ratio to optimize transmission efficiency.

[0024] It should also be noted that due to differences in drone models, the above-mentioned drone parameter settings are only parameter configuration examples. In actual applications, different parameters need to be initially set according to different differences. This application does not make any special restrictions on this.

[0025] S2: Divide the target survey line into survey sub-sections based on the transmission line racks, collect conductor videos of each survey sub-section, iteratively optimize the drone parameters, determine the number of image cuts, and generate a conductor sag analysis image set for each survey sub-section.

[0026] In this embodiment, the iterative optimization of the drone parameters is performed, and the specific analysis process is as follows: Collect the wire video of each survey sub-section and obtain the video quality parameters of each survey sub-section.

[0027] The video quality index of each survey sub-section is analyzed according to the video quality parameters of each survey sub-section.

[0028] In a specific embodiment, the video quality index of each survey sub-section is analyzed in the following manner: The video quality parameters of each survey sub-section include the effective frame rate, bit rate stability and motion blur degree of the video of each survey sub-section.

[0029] The effective frame rate refers to the ratio of the actual transmission frame rate to the target frame rate.

[0030] Bitrate stability refers to the degree of deviation between the actual bitrate and the target bitrate during video transmission.

[0031] The proportion of high-frequency components in the frequency domain is calculated by Fourier transform, and the proportion is used as the numerical result of the degree of motion blur. In a specific embodiment, the smaller the proportion of high-frequency components in the frequency domain, the higher the degree of motion blur.

[0032] It should be noted that the video quality parameters can be obtained by reading the video stream using OpenCV and analyzing it.

[0033] The reference video quality parameters stored in the database are extracted, including reference effective frame rate, reference bit rate stability, and reference motion blur level.

[0034] The video quality index of each survey sub-section is obtained by analyzing and processing the video quality parameters of each survey sub-section and the reference video quality parameters.

[0035] The video quality index of each survey sub-section is used to quantify the quality status of the video of each survey sub-section and its potential impact on the acquisition of conductor sag analysis data. The specific processing process includes: based on the video smoothness reflected by the effective frame rate, the video data transmission stability reflected by the bit rate stability, and the video image clarity represented by the degree of motion blur, the video quality index of each survey sub-section is finally obtained by comprehensively comparing the results of each parameter with the reference video quality parameter, quantifying the coupling influence of each parameter.

[0036] It's important to understand that the video quality indicators for each survey sub-section, derived through analysis and processing based on the video quality parameters of each survey sub-section, take into account the interdependence between these parameters. For example, the effective frame rate represents the ratio of the actual transmission frame rate to the target frame rate. A low effective frame rate can lead to video stuttering and frame drops, which can reduce the coherence of moving objects in the video and increase motion blur. Bitrate stability reflects the degree of deviation between the actual bitrate and the target bitrate during video transmission. When the bitrate is unstable, fluctuations in data transmission can affect the integrity of the video data, which in turn affects the stability of the frame rate and may also cause loss of image detail, indirectly affecting the degree of motion blur. Motion blur is also measured by calculating the proportion of high-frequency components in the frequency domain using Fourier transform. Greater motion blur means reduced clarity of object edges and motion trajectories in the video. This may require adjusting the frame rate or bitrate to improve the image quality. For example, increasing the frame rate appropriately to capture more detail or stabilizing the bitrate to ensure stable data transmission to reduce blur.

[0037] In a specific embodiment, the video quality index of each survey sub-section is specifically expressed as follows: , in, is the video quality index of the i-th survey sub-section, is the effective frame rate of the i-th survey sub-section, is the bit rate stability of the i-th survey sub-section, is the motion blur degree of the i-th survey sub-section, is the reference effective frame rate, For reference bit rate stability, is the reference motion blur level, is the effective frame rate weight, is the bit rate stability weight, is the weight of the motion blur degree, i is the number of the survey sub-section, , r is the number of survey sub-sections, and e is a natural constant.

[0038] It should be noted that the effective frame rate weight, bit rate stability weight and motion blur degree weight all have value ranges between 0 and 1. When used, the pre-set values ​​can be directly extracted from the database. The specific extraction method is, for example: constructing a mapping set with the effective frame rate, bit rate stability and motion blur degree and the corresponding effective frame rate weight, bit rate stability weight and motion blur degree weight respectively. When used, the effective frame rate, bit rate stability and motion blur degree obtained in real time are input into the corresponding mapping set respectively, so as to extract the effective frame rate weight, bit rate stability weight and motion blur degree weight.

[0039] Extract the preset video quality verification indicators in the database.

[0040] The video quality deviation index of each survey sub-section is obtained by subtracting the video quality verification index from the video quality index of each survey sub-section.

[0041] It should be noted that the video quality deviation indicator can be greater than zero, less than zero, or equal to zero.

[0042] Extract the drone parameter adjustment value corresponding to each video quality deviation index interval stored in the database, and map the drone parameter adjustment value corresponding to the interval of the video quality deviation index of the survey sub-section, and record it as the drone parameter adjustment value of the survey sub-section.

[0043] It's important to understand that the video quality index is a quantitative measure of the quality of drone survey videos. When the video quality deviation index is less than the lower limit of the preset video quality tolerance index range, it indicates that the current video quality is below expected standards. In this case, the corresponding extracted drone parameter adjustment values ​​should include a speed adjustment value less than zero, meaning the speed needs to be reduced to improve video quality. The camera exposure time adjustment value should be greater than zero, increasing the exposure time for clearer images. The spectrometer integration time adjustment value should be greater than zero, increasing the integration time to improve spectral data quality. The data compression rate adjustment value should be greater than zero, increasing the compression rate to optimize transmission efficiency. When the video quality deviation index exceeds the lower limit of the preset video quality tolerance index range, it indicates that the current video quality is above expected. To promote efficient resource utilization, the speed adjustment value should be greater than zero, appropriately increasing the speed. The camera exposure time adjustment value should be less than zero, shortening the exposure time. The spectrometer integration time adjustment value should be less than zero, reducing the integration time. The data compression rate adjustment value should be less than zero, reducing the compression rate. The larger the absolute value of the video quality deviation index, the larger the absolute values ​​of the corresponding extracted drone parameter adjustment values.

[0044] It should be noted that if the corresponding extracted drone parameter adjustment value exceeds the acceptable range of the drone's own adjustment, the drone parameter adjustment will be performed based on the maximum or minimum value that the drone can tolerate.

[0045] Get the drone parameters of the current survey sub-section.

[0046] The UAV parameters of the current survey sub-section and the UAV parameter adjustment values ​​of the survey sub-section are combined to iteratively optimize the UAV parameters.

[0047] In a specific embodiment, assume that the drone parameters for the current survey subsection are: speed 12 m / s, camera exposure time 1 / 800 s, spectrometer integration time 40 ms, and data compression ratio 4:1. After analyzing the video quality deviation index for this survey subsection, the drone parameter adjustment values ​​extracted from the database are mapped to: speed adjustment value -2 m / s, camera exposure time adjustment value 1 / 200 s, spectrometer integration time adjustment value 10 ms, and data compression ratio adjustment value 1:1. The iteratively optimized drone parameters are: speed adjusted to 10 m / s, camera exposure time to 1 / 160 s, spectrometer integration time to 50 ms, and data compression ratio to 5:1.

[0048] In this embodiment, a conductor sag analysis image set is generated for each survey sub-section. The specific analysis process is as follows: Collect the wire video of each survey sub-section and analyze the image acquisition demand indicators of each survey sub-section.

[0049] In a specific embodiment, the image acquisition requirement indicators of each survey sub-section are analyzed in the following specific steps: Collect the wire video of each survey sub-section and obtain the wire status data of each survey sub-section.

[0050] The conductor state characteristic parameters of each survey sub-section are analyzed based on the conductor state data of each survey sub-section.

[0051] In a specific embodiment, the conductor state characteristic parameters of each survey sub-section are analyzed in the following manner: Collect the wire video of the survey sub-section, identify and locate the wire of the survey sub-section, and select fixed marking points. Record the position change trajectory of the fixed marking points in each vibration cycle by looking down at continuous video frames. Thus, obtain the distance difference between the highest and lowest points of the marking points in the vertical direction in each vibration cycle, which is recorded as the maximum vertical distance in each vibration cycle. Statistically calculate the maximum vertical distances in all vibration cycles within the survey video period, perform average processing on the average maximum vertical distance, and record it as the vertical swing amplitude of the wire.

[0052] It should be noted that the wire video of the survey sub-section includes a bird's-eye view video segment and a side view video segment. In a specific embodiment, the drone shoots the bird's-eye view video segment with a preset first survey duration and then shoots the side view video segment with a preset second survey duration.

[0053] It should be understood that the vibration period is pre-set in the database.

[0054] The horizontal position coordinates of the fixed marker point are continuously recorded by side-viewing continuous video frames to generate a horizontal swing coordinate change waveform of the fixed marker point. The number of complete fluctuations during the survey video period is counted, and the number of complete fluctuations is divided by the survey video duration. The result is recorded as the swing frequency of the wire.

[0055] What needs to be understood is that the process from peak to trough and then back to peak in the waveform is regarded as a complete fluctuation.

[0056] Extract the static position of the conductor at the same angle in a windless state stored in the database and use it as the baseline. Analyze the horizontal distance of the fixed mark point deviating from the baseline when the conductor is affected by wind by side-viewing continuous video frames, record it as the horizontal offset distance, obtain the conductor hanging height stored in the database, obtain the inverse tangent value of the horizontal offset distance and the vertical height, record it as the conductor windage radian, obtain the maximum conductor windage radian during the survey video period, obtain the conductor initial radian stored in the database, and subtract the maximum conductor windage radian from the conductor initial radian to obtain the conductor windage angle.

[0057] A marking point symmetrically distributed with the fixed marking point is located on the same cross-section of the conductor and recorded as the symmetrical marking point. The rotational misalignment of the fixed marking point and the symmetrical marking point around the conductor axis is recorded by looking down at continuous video frames and recorded as the linear displacement difference. Based on the conductor circumference stored in the database, the linear displacement difference is converted into a rotation angle, and the maximum rotation angle within the survey video period is obtained, which is recorded as the torsion angle of the conductor.

[0058] In a specific embodiment, the linear displacement difference is divided by the circumference of the wire and then multiplied by 360 degrees to obtain a numerical result as the rotation angle.

[0059] The wire videos of each survey sub-section are traversed in sequence to obtain the vertical swing amplitude, swing frequency, wind deflection angle and torsion angle of the wire of each survey sub-section, and record them as the wire status data of each survey sub-section.

[0060] The reference conductor status data stored in the database is extracted, including the reference vertical swing amplitude, reference swing frequency, reference wind deflection angle and reference torsion angle of the conductor.

[0061] The vertical swing amplitude weight, swing frequency weight, windage angle weight and torsion angle weight preset in the database are extracted.

[0062] The conductor state characteristic parameters of each survey sub-section are obtained by analyzing and processing the conductor state data of each survey sub-section.

[0063] The conductor state characteristic parameters of each survey sub-section are used to characterize the difficulty of conducting conductor sag analysis based on the conductor state in the survey video. The specific processing process includes: based on the vertical swing amplitude of the conductor reflecting the intensity of the vertical vibration of the conductor, the swing frequency reflecting the frequency of the horizontal swing of the conductor, the wind angle reflecting the angle of wind deviation of the conductor, and the torsion angle reflecting the degree of torsion of the conductor itself, the conductor state characteristic parameters of each survey sub-section are finally obtained by comprehensively comparing the results of each parameter with the reference conductor state data, quantifying the coupling influence of each parameter.

[0064] It should be understood that the characteristic parameters of the conductor state for each survey sub-section are derived from the analysis and processing of the conductor state data for each survey sub-section, taking into account the interrelationships between these parameters. For example, when the conductor is affected by external factors, such as strong winds, multiple changes may occur simultaneously. A larger windage angle means that the conductor is subjected to a larger horizontal deviation due to the wind force. This deviation will cause the conductor's oscillation frequency to change. The larger the windage angle, the higher the oscillation frequency may be. The increase in oscillation frequency will increase the vertical swing amplitude of the conductor during the oscillation process. In other words, the more frequent the oscillation, the greater the vertical swing amplitude may be. In addition, during windage and oscillation, the internal force of the conductor is uneven, which will cause torsion. Changes in windage angle, oscillation frequency, and vertical swing amplitude may all affect the torsion angle. For example, violent oscillation and large windage may cause the conductor to torsion angle to increase.

[0065] In a specific embodiment, the conductor state characteristic parameters of each survey sub-section are specifically expressed as follows: , in, is the characteristic parameter of the conductor state of the i-th survey sub-section, is the vertical swing amplitude of the conductor in the i-th survey sub-section, is the oscillation frequency of the conductor in the i-th survey sub-section, is the wind deflection angle of the conductor of the i-th survey sub-section, is the torsion angle of the traverse of the i-th survey sub-section, is the reference vertical swing of the conductor, is the reference swing frequency of the conductor, is the reference wind deflection angle of the conductor, is the reference twist angle of the wire, is the vertical swing weight, is the swing frequency weight, is the wind angle weight, is the torsion angle weight, i is the number of the survey sub-section, , r is the number of survey sub-sections.

[0066] The image acquisition requirement indicators of each survey sub-section are analyzed based on the video quality indicators of each survey sub-section and the wire status characteristic parameters of each survey sub-section.

[0067] The image acquisition requirement index of each survey sub-section is used to quantify the monitoring video quality of each survey sub-section and the difficulty of conductor sag analysis due to the conductor state. The specific processing process includes: based on the video quality reflected by the video quality index of each survey sub-section and the complexity of the conductor state reflected by the conductor state characteristic parameters of each survey sub-section, the correlation influence results of each parameter are comprehensively considered to finally obtain the image acquisition requirement index of each survey sub-section.

[0068] In a specific embodiment, the image acquisition requirement index of each survey sub-section is specifically expressed as follows: , in, is the image acquisition requirement index of the i-th survey sub-section, is the video quality index of the i-th survey sub-section, is the characteristic parameter of the conductor state of the i-th survey sub-section, is the video quality index weight, is the weight of the characteristic parameter of the conductor state, i is the number of the survey sub-section, , r is the number of survey sub-sections.

[0069] It is important to understand that the softsign function is a built-in function in Python. .

[0070] It should be noted that the value range of the video quality index weight and the conductor state characteristic parameter weight are both 0-1, and the pre-set values ​​can be directly extracted from the database. The specific extraction method is, for example, to construct a mapping set between the video quality index and the video quality index weight, and to construct a mapping set between the conductor state characteristic parameter and the conductor state characteristic parameter weight. When used, the video quality index and conductor state characteristic parameter obtained in real time are respectively input into the corresponding mapping set, so as to extract the corresponding video quality index weight and conductor state characteristic parameter weight.

[0071] The number of images corresponding to each image acquisition requirement index interval stored in the database is extracted, and the number of images corresponding to the image acquisition requirement index of the survey sub-section is mapped and extracted, and recorded as the number of image cuts of the survey sub-section.

[0072] It should be noted that the image acquisition demand index reflects the urgency and complexity of obtaining high-quality conductor sag analysis data. The larger the image acquisition demand index, the more unstable the conductor status of the current survey sub-section and the greater the impact of video quality on accurate analysis. In order to more accurately analyze conductor sag and ensure data integrity and accuracy, the corresponding number of image cuts should be increased.

[0073] Each survey sub-section is traversed in turn, and the wire sag analysis image set of each survey sub-section is extracted and statistically obtained.

[0074] S3, analyzing the conductor sag deviation correction value based on the conductor sag analysis image set of each survey sub-section; In this embodiment, the conductor sag deviation correction value is analyzed based on the conductor sag analysis image set of each survey sub-section. The specific analysis process is as follows: The first ideal conductor sag value of each survey sub-section and the second ideal conductor sag value of each survey sub-section preset in the database are extracted.

[0075] A conductor sag analysis image set of each survey sub-section corresponding to a normal environment is obtained, and the conductor sag value of each survey sub-section is analyzed and recorded as the first conductor sag value of each survey sub-section.

[0076] A first conductor sag value of each survey sub-section is subjected to difference processing with a first ideal conductor sag value of each survey sub-section to obtain a first conductor sag deviation value of each survey sub-section.

[0077] A conductor sag analysis image set of each survey sub-section corresponding to the abnormal environment is obtained, and the conductor sag value of each survey sub-section is analyzed and recorded as the second conductor sag value of each survey sub-section.

[0078] The second conductor sag value of each survey sub-section is subjected to difference processing with the second ideal conductor sag value of each survey sub-section to obtain the second conductor sag deviation value of each survey sub-section.

[0079] The first deviation value of the conductor sag of each survey sub-section and the second deviation value of the conductor sag of each survey sub-section are averaged and summed and then weighted to obtain the conductor sag deviation value.

[0080] In a specific embodiment, the steps for obtaining the conductor sag deviation value are as follows: the first conductor sag deviation value of each survey sub-section and the second conductor sag deviation value of each survey sub-section are summed and averaged respectively to obtain the first average conductor sag deviation value and the second average conductor sag deviation value; based on the weight factors corresponding to the first average conductor sag deviation value and the weight factors corresponding to the second average conductor sag deviation value preset in the database, the first average conductor sag deviation value and the second average conductor sag deviation value are weightedly summed to obtain the conductor sag deviation value.

[0081] It should be noted that the weight factor corresponding to the first average deviation value of the conductor sag and the weight factor corresponding to the second average deviation value of the conductor sag can be directly extracted from the database when used. The extraction method is, for example: constructing a mapping set with the first average deviation value of the conductor sag and the second average deviation value of the conductor sag and the corresponding weight factors respectively. When used, the first average deviation value of the conductor sag and the second average deviation value of the conductor sag obtained in real time are input into the mapping set one by one to extract the corresponding weight factors.

[0082] The deviation correction value corresponding to each sag deviation value interval stored in the database is extracted, and the deviation correction value corresponding to the interval where the conductor sag deviation value is located is mapped and recorded as the conductor sag deviation correction value.

[0083] It should be noted that the larger the sag deviation value, the greater the difference between the actual conductor sag and the ideal state, the further the conductor's operating state deviates from the expected standard, and the greater the impact on the safe and stable operation of the line. To make the conductor sag as close to the ideal state as possible and ensure reliable operation of the line, the corresponding extracted conductor sag deviation correction value should be larger. A larger correction value can make more significant adjustments to the current undesirable sag state.

[0084] S4, obtaining the preset conductor sag of each constructed sub-section, generating an ideal conductor sag curve, and simultaneously combining the deviation correction result of the conductor sag to generate a corrected conductor sag curve and output it.

[0085] In a specific embodiment, the preset conductor sag of each construction sub-section is obtained to generate an ideal conductor sag curve. The specific analysis steps are as follows: A1. Obtain basic parameters and design parameters of the conductor for the sub-section. The basic parameters include conductor diameter, conductor mass per unit length, and rated tensile strength. The design parameters of the target line include the span, design wind speed, ice thickness, and a set safety factor of the target line.

[0086] It should be understood that the basic conductor parameters and design parameters are analysis parameters corresponding to the constructed sub-sections pre-stored in the database.

[0087] It should also be understood that the span refers to the distance between adjacent towers in the construction route, and the ice thickness refers to the maximum ice thickness of the construction sub-section.

[0088] A2: Analyze vertical loads based on the mass per unit length of conductor, ice thickness, and conductor diameter; analyze horizontal loads based on the design wind speed, conductor diameter, and ice thickness; and analyze total loads based on vertical and horizontal loads.

[0089] In a specific embodiment, the calculation methods of the vertical load, horizontal load, total load and conductor sag are all formulas known in the art. For ease of understanding, the specific expression methods are as follows: The vertical load is expressed as follows: ,in, is the acceleration due to gravity, is the vertical specific load, is the mass per unit length of the conductor, is the ice thickness, is the wire diameter, is the density of ice.

[0090] Horizontal load, the specific expression method is as follows: ,in, is the air density, is the horizontal load, is the design wind speed, is the ice thickness, is the wire diameter.

[0091] Total load, specifically expressed as follows: ,in, is the total load, is the vertical specific load, For horizontal load.

[0092] A3, the conductor sag is obtained based on the rated tensile strength, set safety factor, span and total load analysis.

[0093] In a specific embodiment, the conductor sag is specifically expressed as follows: ,in, is the conductor sag, is the total load, is the gear spacing, is the rated tensile strength, To set the safety factor.

[0094] It should be understood that the calculation of conductor sag discussed in this embodiment assumes that the two suspension points are on the same horizontal plane and the span is less than 1000 meters. The method for expressing conductor sag is obtained through static equilibrium analysis under the assumption of the parabola method.

[0095] A4, traverse each constructed sub-section in turn, and obtain the conductor sag of each constructed sub-section.

[0096] A5: Perform cubic spline interpolation on the conductor sag data of each constructed sub-section to generate a continuous sag curve, which is recorded as the ideal conductor sag curve.

[0097] In this embodiment, the deviation correction result of the conductor sag is synchronously combined to generate a corrected conductor sag curve. The specific analysis process is as follows: The conductor sag of each constructed sub-section is obtained, and combined with the conductor sag deviation correction value, the corrected conductor sag of each constructed sub-section is analyzed and obtained.

[0098] The modified conductor sag data of each constructed sub-section is subjected to cubic spline interpolation to generate a continuous sag curve, which is recorded as the modified conductor sag curve.

[0099] This embodiment provides a method for constructing a conductor sag curve for a heavy-load line, further comprising dynamically adjusting the transmission of drone survey data based on the drone flight survey environment. The specific analysis process is as follows: Collect UAV flight environment data for each survey sub-section, including wind speed, temperature, electromagnetic interference intensity, and electric field intensity.

[0100] Extract the reference UAV flight environment data stored in the database, including reference wind speed, ideal temperature, reference electromagnetic interference intensity, and reference electric field intensity.

[0101] Based on the UAV flight environment data of each survey sub-section, the UAV flight transmission interference index of each survey sub-section is analyzed.

[0102] The UAV flight transmission interference index of each survey sub-section is used to quantify the degree of external interference suffered by the UAVs of each survey sub-section during the survey data transmission process and its potential impact on the stability and accuracy of data transmission. The specific processing process includes: based on the air flow interference reflected by the wind speed of each survey sub-section, the environmental thermal interference reflected by the temperature, the electromagnetic environment interference represented by the electromagnetic interference intensity, and the electric field environment interference reflected by the electric field strength, the comparison results of each parameter with the reference UAV flight environment data are comprehensively compared to quantify the coupling influence of each parameter, and finally obtain the UAV flight transmission interference index of each survey sub-section.

[0103] In a specific embodiment, the UAV flight transmission interference index of each survey sub-section is specifically expressed as follows: , in, is the UAV flight transmission interference index of the i-th survey sub-section, is the wind speed of the i-th survey sub-section, is the temperature of the i-th survey sub-section, is the electromagnetic interference intensity of the i-th survey sub-section, is the electric field strength of the i-th survey sub-section, is the reference wind speed, For the ideal temperature, For reference electromagnetic interference intensity, is the reference electric field strength, is the wind speed weight, is the temperature weight, is the electromagnetic interference intensity weight, is the electric field strength weight, i is the number of the survey sub-section, , r is the number of survey sub-sections, and e is a natural constant.

[0104] It should be noted that the wind speed weight, temperature weight, electromagnetic interference intensity weight and electric field strength weight are pre-set values ​​in the database, and the value range is 0 to 1. They can be directly extracted when used. For example, the extraction method is to construct a one-to-one mapping set for the wind speed, temperature, electromagnetic interference intensity and electric field strength and the corresponding weights respectively. When used, the wind speed, temperature, electromagnetic interference intensity and electric field strength obtained in real time are input into the mapping set to extract the corresponding wind speed weight, temperature weight, electromagnetic interference intensity weight and electric field strength weight.

[0105] The transmission frequency band number corresponding to each transmission interference index stored in the database is extracted, and the transmission frequency band number corresponding to the interval in which the UAV flight transmission interference index is located is mapped and extracted, and recorded as the data transmission frequency band number.

[0106] It should be noted that the transmission interference index is a quantitative measure of the degree of external interference experienced by drones during survey data transmission. A higher transmission interference index indicates more severe interference during data transmission, which can affect the stability and accuracy of data transmission and potentially lead to data loss, delays, or errors. To ensure data transmission quality and efficiency and reduce the negative impact of interference, more transmission frequency bands are selected. By increasing the number of transmission frequency bands and utilizing multiple frequency bands for simultaneous data transmission, anti-interference capabilities are enhanced, ensuring stable and accurate transmission of survey data.

[0107] Dynamic adjustment of UAV survey data transmission based on the number of data transmission frequency bands.

[0108] In a specific embodiment, assume that analysis of drone flight environment data for a survey subsection reveals that the drone flight transmission interference index for that subsection indicates a corresponding number of data transmission frequency bands of 3. This number is then recorded as the data transmission frequency band number for that subsection. Based on this number of frequency bands, the drone survey data transmission is dynamically adjusted, with the drone configured to transmit data simultaneously using three different frequency bands. During transmission, if one frequency band experiences significant interference, the other two bands can continue to transmit data. This ensures data transmission stability, avoids data loss or errors due to interference, and ensures that survey data is transmitted completely and accurately to the receiving end.

[0109] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0110] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0113] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0114] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for constructing a conductor sag curve for a heavy-load line, characterized in that: The following steps are involved: S1, using multimodal sensors onboard the drone to obtain differentiated environmental conditions of the target route and set the initial parameters of the drone based on the differentiated environmental conditions; S2: Divide the target survey line into survey sub-sections based on the transmission line pylons, collect conductor videos of each survey sub-section, iteratively optimize the drone parameters, determine the number of image cuts, and generate a conductor sag analysis image set for each survey sub-section; S3, analyzing the conductor sag deviation correction value based on the conductor sag analysis image set of each survey sub-section; S4, obtaining the preset conductor sag of each constructed sub-section, generating an ideal conductor sag curve, and simultaneously combining the deviation correction result of the conductor sag to generate a corrected conductor sag curve and output it.

2. A method for constructing a conductor sag curve for a heavy-load line according to claim 1, characterized in that: The differentiated environmental conditions of the target route are obtained, and the initial parameters of the drone are set according to the differentiated environmental conditions. The specific analysis method is as follows: The differentiated environmental conditions include normal environment and adverse environment; Extract the initial parameters of the UAV corresponding to the differentiated environmental conditions in the database, and then set the initial parameters of the UAV; The initial parameters of the UAV include the speed of the UAV, the exposure time of the camera, the integration time of the spectrometer and the data compression rate.

3. The method for constructing a conductor sag curve for a heavy-load line according to claim 1, wherein: The iterative optimization of the UAV parameters is performed, and the specific analysis process is as follows: Collect the wire video of each survey sub-section and obtain the video quality parameters of each survey sub-section; Analyze the video quality index of each survey sub-section based on the video quality parameters of each survey sub-section; Extract the video quality verification indicators preset in the database; The video quality deviation index of each survey sub-section is obtained by subtracting the video quality verification index from the video quality index of each survey sub-section; Extract the drone parameter adjustment value corresponding to each video quality deviation index interval stored in the database, and map the extracted drone parameter adjustment value corresponding to the interval of the video quality deviation index of the survey sub-section, and record it as the drone parameter adjustment value of the survey sub-section; Get the drone parameters of the current survey sub-section; The UAV parameters of the current survey sub-section and the UAV parameter adjustment values ​​of the survey sub-section are combined to iteratively optimize the UAV parameters.

4. A method for constructing a conductor sag curve for a heavy-load line according to claim 3, characterized in that: The specific analysis process of the video quality indicators of each survey sub-section is as follows: The video quality parameters of each survey sub-section include the effective frame rate, bit rate stability and motion blur of the video of each survey sub-section; extracting reference video quality parameters stored in a database; Analyze and process the video quality parameters of each survey sub-section and the reference video quality parameters to obtain the video quality index of each survey sub-section; The video quality index of each survey sub-section is used to quantify the quality status of the video of each survey sub-section and its potential impact on the acquisition of conductor sag analysis data. The specific processing process includes: based on the video smoothness reflected by the effective frame rate, the video data transmission stability reflected by the bit rate stability, and the video image clarity represented by the degree of motion blur, the video quality index of each survey sub-section is finally obtained by comprehensively comparing the results of each parameter with the reference video quality parameter, quantifying the coupling influence of each parameter.

5. The method for constructing a conductor sag curve for a heavy-load line according to claim 1, wherein: The specific analysis process of generating the wire sag analysis image set of each survey sub-section is as follows: Collect the traverse video of each survey sub-section and analyze the image acquisition requirements of each survey sub-section; Extract the number of images corresponding to each image acquisition requirement index interval stored in the database, and map the number of images corresponding to the image acquisition requirement index of the survey sub-section to be extracted, and record it as the number of image cuts of the survey sub-section; Each survey sub-section is traversed in turn, and the wire sag analysis image set of each survey sub-section is extracted and statistically obtained.

6. A method for constructing a conductor sag curve for a heavy-load line according to claim 5, characterized in that: The specific analysis steps for the image acquisition requirement indicators of each survey sub-section are as follows: Collect the wire video of each survey sub-section and obtain the wire status data of each survey sub-section; Analyze the conductor state characteristic parameters of each survey sub-section based on the conductor state data of each survey sub-section; Analyze the image acquisition requirement indicators of each survey sub-section based on the video quality indicators of each survey sub-section and the wire state characteristic parameters of each survey sub-section; The image acquisition requirement index of each survey sub-section is used to quantify the monitoring video quality of each survey sub-section and the difficulty of conductor sag analysis due to the conductor state. The specific processing process includes: based on the video quality reflected by the video quality index of each survey sub-section and the complexity of the conductor state reflected by the conductor state characteristic parameters of each survey sub-section, the correlation influence results of each parameter are comprehensively considered to finally obtain the image acquisition requirement index of each survey sub-section.

7. A method for constructing a conductor sag curve for a heavy-load line according to claim 6, characterized in that: The specific analysis process of the conductor state characteristic parameters of each survey sub-section is as follows: Collect wire video of the survey subsection, identify and locate the wire in the survey subsection, and select fixed markers. Record the position change trajectory of the fixed markers during each vibration cycle by looking down at continuous video frames. Obtain the vertical distance difference between the highest and lowest points of the markers during each vibration cycle, which is recorded as the maximum vertical distance during each vibration cycle. Statistically calculate the maximum vertical distances during all vibration cycles within the survey video period, perform average processing, and obtain the average maximum vertical distance, which is recorded as the vertical swing amplitude of the wire. The horizontal coordinates of the fixed markers are continuously recorded by side-viewing continuous video frames to generate a waveform of the horizontal swing coordinate change of the fixed markers. The number of complete fluctuations during the survey video period is counted, and the number of complete fluctuations is divided by the survey video duration. The result is recorded as the swing frequency of the wire. Extract the static position of the conductor at the same angle in a windless state stored in the database and use it as the baseline. Analyze the horizontal distance that the fixed mark point deviates from the baseline when the conductor is affected by wind by side-viewing continuous video frames. Record it as the horizontal offset distance. Obtain the conductor hanging height stored in the database. Obtain the inverse tangent value of the horizontal offset distance and the vertical height. Record it as the conductor windage radian. Obtain the maximum conductor windage radian during the survey video period. Obtain the conductor initial radian stored in the database. Subtract the maximum conductor windage radian from the conductor initial radian to obtain the conductor windage angle. A marker point symmetrically distributed with the fixed marker point is located on the same cross section of the conductor. This is recorded as the symmetrical marker point. The rotational misalignment of the fixed marker point and the symmetrical marker point around the conductor axis is recorded by looking down at consecutive video frames and recorded as the linear displacement difference. Based on the conductor circumference stored in the database, the linear displacement difference is converted into a rotation angle. The maximum rotation angle within the survey video period is obtained and recorded as the torsion angle of the conductor. Traversing the wire videos of each survey sub-section in turn, thereby obtaining the vertical swing amplitude, swing frequency, wind deflection angle and torsion angle of the wire of each survey sub-section, and recording them as the wire status data of each survey sub-section; Analyzing and processing the conductor state data of each survey sub-section to obtain the conductor state characteristic parameters of each survey sub-section; The conductor state characteristic parameters of each survey sub-section are used to characterize the difficulty of conducting conductor sag analysis based on the conductor state in the survey video. The specific processing process includes: based on the vertical swing amplitude of the conductor reflecting the intensity of the vertical vibration of the conductor, the swing frequency reflecting the frequency of the horizontal swing of the conductor, the wind angle reflecting the angle of wind deviation of the conductor, and the torsion angle reflecting the degree of torsion of the conductor itself, the conductor state characteristic parameters of each survey sub-section are finally obtained by comprehensively comparing the results of each parameter with the reference conductor state data, quantifying the coupling influence of each parameter.

8. A method for constructing a conductor sag curve for a heavy-load line according to claim 1, characterized in that: The conductor sag analysis image set based on each survey sub-section is used to analyze the conductor sag deviation correction value. The specific analysis process is as follows: Extracting a first ideal conductor sag value of each survey sub-section and a second ideal conductor sag value of each survey sub-section preset in a database; Obtaining a conductor sag analysis image set of each survey sub-section corresponding to a normal environment, analyzing the conductor sag value of each survey sub-section, and recording the value as the first conductor sag value of each survey sub-section; Performing difference processing on the first conductor sag value of each survey sub-section and the first ideal conductor sag value of each survey sub-section to obtain a first conductor sag deviation value of each survey sub-section; Obtaining a conductor sag analysis image set of each survey sub-section corresponding to the abnormal environment, analyzing the conductor sag value of each survey sub-section, and recording it as the second conductor sag value of each survey sub-section; Performing difference processing on the second conductor sag value of each survey sub-section and the second ideal conductor sag value of each survey sub-section to obtain a second conductor sag deviation value of each survey sub-section; The first deviation value of the conductor sag of each survey sub-section and the second deviation value of the conductor sag of each survey sub-section are averaged and summed and then weighted to obtain the conductor sag deviation value; The deviation correction value corresponding to each sag deviation value interval stored in the database is extracted, and the deviation correction value corresponding to the interval where the conductor sag deviation value is located is mapped and recorded as the conductor sag deviation correction value.

9. A method for constructing a conductor sag curve for a heavy-load line according to claim 1, characterized in that: The deviation correction result of the conductor sag is synchronously combined to generate a corrected conductor sag curve. The specific analysis process is as follows: Obtain the conductor sag of each constructed sub-section, and analyze and obtain the corrected conductor sag of each constructed sub-section based on the conductor sag deviation correction value; The modified conductor sag data of each constructed sub-section is subjected to cubic spline interpolation to generate a continuous sag curve, which is recorded as the modified conductor sag curve.

10. A method for constructing a conductor sag curve for a heavy-load line, characterized by: It also includes dynamic adjustment of UAV survey data transmission based on the UAV flight survey environment. The specific analysis process is as follows: Collect UAV flight environment data for each survey sub-section, including wind speed, temperature, electromagnetic interference intensity, and electric field intensity; Analyze the UAV flight transmission interference index of each survey sub-section based on the UAV flight environment data of each survey sub-section; The UAV flight transmission interference index of each survey sub-section is used to quantify the degree of external interference to the UAV in each survey sub-section during the survey data transmission process and its potential impact on the stability and accuracy of data transmission. The specific processing process includes: based on the air flow interference reflected by the wind speed of each survey sub-section, the environmental thermal interference reflected by the temperature, the electromagnetic environment interference represented by the electromagnetic interference intensity, and the electric field environment interference reflected by the electric field intensity, the comprehensive comparison results of each parameter with the reference UAV flight environment data are used to quantify the coupling influence of each parameter, and finally obtain the UAV flight transmission interference index of each survey sub-section; Extract the transmission frequency band number corresponding to each transmission interference index stored in the database, and map the transmission frequency band number corresponding to the interval where the UAV flight transmission interference index is located, and record it as the data transmission frequency band number; Dynamic adjustment of UAV survey data transmission based on the number of data transmission frequency bands.

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