Line windage yaw galloping early warning system combining multi-parallel-line laser and monocular vision

Abstract

The invention provides a line windage yaw galloping early warning system combining multi-parallel-line laser and monocular vision, and relates to the technical field of windage yaw galloping early warning, and the system comprises a monitoring configuration optimization module which is used for adjusting a galloping monitoring configuration result; the galloping capture module is used for carrying out galloping capture on the power transmission line according to the multi-parallel-line laser assembly and the monocular vision assembly; the galloping parameter analysis module is used for calculating multi-dimensional windage yaw galloping parameters; the galloping risk assessment module is used for carrying out galloping risk assessment on the power transmission line; and the line galloping early warning module is used for generating a windage yaw galloping early warning signal according to the line galloping risk coefficient. According to the application, the technical problem in the prior art that the accuracy of windage yaw galloping early warning is affected due to poor adaptability of a windage yaw galloping early warning system to a complex environment can be solved, accurate monitoring and risk assessment of power transmission line galloping are realized by combining the multi-parallel-line laser and monocular vision technologies, and the accuracy of the power transmission line galloping early warning is improved. And the accuracy of windage yaw galloping early warning is improved.

Description

Technical Field

[0001] The present application relates to the technical field of wind deviation and sway warning technology, and in particular to a line wind deviation and sway warning system combining multi-parallel line lasers and monocular vision. Background Art

[0002] Transmission lines will vibrate or flutter in strong winds or when the wind speed changes. In severe cases, this may lead to line damage, tower tilting or line breakage, and other faults, affecting the safety of power transmission. The transmission line wind deviation flutter warning system is a system used to monitor and prevent the flutter of transmission lines due to wind force. It mainly monitors parameters such as wind speed, wind direction, line tension, vibration frequency, etc., timely identifies and warns of fluttering phenomena, and takes preventive measures to reduce the risk of line failure. However, the existing wind deviation flutter warning system is easily disturbed under extreme meteorological conditions (such as storms, heavy rains, ice and snow, etc.) and complex terrain (such as mountains, plains and rivers, etc.), resulting in instability or failure of monitoring data, limiting the accuracy and timeliness of the warning system, especially when rapid response is required. Due to the complex and changeable natural environment, the warning system may be insufficiently robust, and it is easy to have excessive warnings (false alarms) or missed alarms. False alarms lead to increased maintenance costs and burdens, and missed alarms may lead to failures that fail to warn in time, affecting the actual prevention and control effect.

[0003] In summary, there are technical problems in the prior art due to the poor effect of the wind yaw and sway warning system of the transmission line in complex environments, resulting in false alarms and missed alarms, which further affects the accuracy of the wind yaw and sway warning. Summary of the invention

[0004] The purpose of this application is to provide a line wind deviation and sway warning system that combines multi-parallel line lasers with monocular vision, so as to solve the technical problem in the prior art that the power transmission line wind deviation and sway warning system is not effective in complex environments, resulting in false alarms and missed alarms, further affecting the accuracy of the wind deviation and sway warning.

[0005] In view of the above problems, the present application provides a line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision, wherein the line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision includes: a monitoring configuration optimization module, the monitoring configuration optimization module is used to adjust the dancing monitoring configuration result of the transmission line according to the predetermined future time zone, and generate a dancing monitoring configuration optimization result; a dancing capture module, the dancing capture module is used to capture the dancing of the transmission line according to the multi-parallel line laser component and the monocular vision component based on the predetermined future time zone and the dancing monitoring configuration optimization result, and obtain A dancing parameter analysis module is provided, which is used to perform multi-dimensional windage dancing parameter calculation according to the line dancing capture result to obtain the dancing parameter calculation result; a dancing risk assessment module is used to perform dancing risk assessment on the transmission line according to the windage dancing risk factor and the dancing parameter calculation result to determine the line dancing risk coefficient; a line dancing warning module is used to generate a windage dancing warning signal based on the line dancing risk coefficient, according to the line dancing risk threshold and the dancing risk classification warning device.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: Through the monitoring configuration optimization module, the monitoring configuration optimization module is used to adjust the dancing monitoring configuration result of the transmission line according to the predetermined future time zone, and generate the dancing monitoring configuration optimization result; the dancing capture module, the dancing capture module is used to capture the dancing of the transmission line according to the multi-parallel line laser component and the monocular vision component based on the predetermined future time zone and the dancing monitoring configuration optimization result, and obtain the line dancing capture result; the dancing parameter analysis module, the dancing parameter analysis module is used to perform multi-dimensional wind deviation dancing parameter calculation according to the line dancing capture result, and obtain the dancing parameter calculation result; the dancing risk assessment module, the dancing risk assessment module is used to perform dancing risk assessment on the transmission line according to the wind deviation dancing risk factor and the dancing parameter calculation result, and determine the line dancing risk coefficient; the line dancing warning module, the line dancing warning module is used to generate a wind deviation dancing warning signal based on the line dancing risk coefficient, according to the line dancing risk threshold and the dancing risk grading warning device. In other words, through the combination of multi-parallel line lasers and monocular vision, high-precision monitoring data can be provided under various complex conditions, risk assessments can be conducted on transmission lines, wind deviation and fluctuation warning signals can be generated, the accuracy of wind deviation and fluctuation warnings can be improved, and missed reports and false alarms can be reduced.

[0007] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0009] Figure 1 This is a schematic diagram of the structure of the line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision in this application; Figure 2 This is a schematic diagram of the process of determining the line dancing risk coefficient in the line wind deviation dancing warning system combining multi-parallel line lasers and monocular vision in this application.

[0010] Explanation of the reference numerals: monitoring configuration optimization module 11 , dancing capture module 12 , dancing parameter analysis module 13 , dancing risk assessment module 14 , line dancing warning module 15 . DETAILED DESCRIPTION

[0011] This application solves the technical problem in the prior art that the wind yaw warning system for power transmission lines is not effective in complex environments, resulting in false alarms and missed alarms, which further affects the accuracy of wind yaw warnings, by providing a wind yaw warning system that combines multi-parallel lasers with monocular vision. Through the combination of multi-parallel lasers and monocular vision, high-precision monitoring data is provided under various complex conditions, risk assessment of power transmission lines is performed, and wind yaw warning signals are generated, thereby improving the accuracy of wind yaw warnings and reducing missed alarms and false alarms.

[0012] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0013] For examples, please see the attached Figure 1 The present application provides a line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision, wherein the line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision comprises: The monitoring configuration optimization module 11 is used to adjust the dancing monitoring configuration result of the transmission line according to the predetermined future time zone to generate the dancing monitoring configuration optimization result.

[0014] Specifically, according to the prediction of environmental conditions in the future time zone, the existing monitoring configuration is adjusted to optimize the monitoring effect. The scheduled future time zone means predicting environmental conditions such as wind speed, temperature, humidity, etc. in the future period of time based on weather forecasts, historical data or other relevant information. The dancing monitoring configuration results include monitoring parameters of multi-parallel line laser components and monocular vision components, such as the power and emission angle of the laser transmitter, the position and focal length of the camera, etc. According to the predicted environmental conditions, the multi-parallel line laser components and monocular vision components of the existing monitoring configuration are adjusted accordingly, and the optimization results are integrated to obtain the optimized results of the dancing monitoring configuration. For example, the original laser monitoring configuration is a laser emission angle of 45 degrees and a line spacing of 1.0 meters. Due to the high wind speed of the transmission line in the scheduled future time zone, it will cause more violent dancing. The laser emission angle is adjusted to 40 degrees and the line spacing is reduced to 0.8 meters to improve the resolution; the original visual monitoring configuration is a camera focal length of 75mm and a frame rate of 25fps. In order to capture faster dancing speeds, the camera focal length is adjusted to 50mm and the frame rate is increased to 30fps. By adjusting the configuration, the monitoring system can more accurately capture the dancing of the transmission lines, better adapt to different environmental conditions, and improve the overall performance of the monitoring system.

[0015] The dancing capture module 12 is used to capture the dancing of the power transmission line based on the predetermined future time zone and the dancing monitoring configuration optimization result according to the multi-parallel line laser component and the monocular vision component to obtain the line dancing capture result.

[0016] Specifically, based on future meteorological conditions (such as wind speed, wind direction, temperature, etc.) and historical dancing data of the transmission line, the optimization results of the dancing monitoring configuration are generated, including the emission parameters of the laser component (such as laser intensity, emission angle) and the monitoring parameters of the visual component (such as exposure time, resolution). According to the optimization results, the parameters of the multi-parallel line laser component are adjusted to ensure that the laser can effectively cover the transmission line and form a stable laser grid. At the same time, the monocular vision component is started to monitor the transmission line in real time according to the optimized configuration parameters (such as frame rate, focal length) to capture the image of the line under laser irradiation. K reference points are identified in the laser grid to track the dancing of the line; the line monitoring image captured by the monocular vision component is processed using the gamma enhancement function to improve the contrast and clarity of the image; based on the laser grid and the identified reference points, the enhanced image is feature tracked and the position change of each reference point is recorded; the motion trajectory of each reference point tracked is fused and analyzed to obtain the dancing of the transmission line. For example, suppose that in the next 6 hours, the weather forecast predicts that there will be strong winds with a speed of 15m / s in the area where the transmission line is located. According to the forecast, the emission frequency of the multi-parallel line laser component and the sampling rate of the monocular vision component are adjusted to adapt to the upcoming strong wind conditions. During the monitoring process, the laser component captures the vibration of the line under the action of strong wind, while the visual component records the actual movement trajectory of the line. By analyzing these data, the dancing of the line during this period is obtained, including the amplitude, frequency and pattern of the dancing. Through the collaborative work of the multi-parallel line laser component and the monocular vision component, the dancing of the line is captured in real time, which improves the adaptability and monitoring efficiency of the system, especially in complex weather conditions and night environments.

[0017] The dancing parameter analysis module 13 is used to calculate the multi-dimensional wind deviation dancing parameters according to the line dancing capture result to obtain the dancing parameter calculation result.

[0018] Specifically, the line dancing capture results obtained by the multi-parallel line laser component and the monocular vision component are analyzed and calculated from multiple angles and multiple parameters to obtain detailed information on the line dancing. The calculation of multi-dimensional wind deviation dancing parameters includes wind deflection angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and elliptical inclination angle. Among them, the wind deflection angle refers to the lateral deflection angle of the line under the action of wind, which is usually used to describe the degree of deviation of the line relative to the vertical line; the dancing amplitude refers to the maximum displacement of the line during the dancing process, which can be a vertical or horizontal displacement; the vertical dancing amplitude refers to the maximum displacement of the line in the vertical direction; the horizontal dancing amplitude refers to the maximum displacement of the line in the horizontal direction; the elliptical inclination angle refers to the inclination angle of the ellipse formed by the line dancing trajectory relative to the horizontal plane. The captured transmission line dancing images or laser point cloud data are preprocessed, including denoising, filtering and image enhancement, to improve data quality. The key feature points of the transmission line are extracted from the processed data to track the dancing trajectory of the line and calculate the wind deflection angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and ellipse inclination angle. By calculating the position change of the feature point, the angle of the line deviation from the original position is determined to obtain the wind deflection angle; by analyzing the maximum displacement of the feature point, the overall dancing amplitude of the line is obtained; the maximum displacement of the feature point in the vertical direction is analyzed separately to obtain the vertical dancing amplitude; the maximum displacement of the feature point in the horizontal direction is analyzed separately to obtain the horizontal dancing amplitude; by fitting the dancing trajectory of the feature point, the inclination angle of the trajectory ellipse is calculated to obtain the ellipse inclination angle. For example, the maximum wind deflection angle of the line is 15 degrees, the maximum displacement of the line is 50 cm, the maximum displacement of the line in the vertical direction is 30 cm, the maximum displacement of the line in the horizontal direction is 40 cm, and the inclination angle of the ellipse formed by the dancing trajectory of the line relative to the horizontal plane is 10 degrees. Through multi-dimensional calculation, quantitative analysis of line dancing is achieved, which helps to diagnose whether the line has excessive dancing or other abnormal behaviors, so as to take corresponding maintenance or reinforcement measures.

[0019] The galloping risk assessment module 14 is used to perform a galloping risk assessment on the transmission line according to the wind deviation galloping risk factor and the galloping parameter calculation result to determine the line galloping risk coefficient.

[0020] Specifically, the risk factors of wind yaw dancing include instantaneous dancing risk, waiting dancing risk and maintenance dancing risk. Among them, the instantaneous dancing risk refers to the situation where the amplitude or frequency of the dancing of the transmission line is too high at a certain moment, resulting in an increase in instantaneous risk; the waiting dancing risk refers to the possibility that the dancing phenomenon may accumulate over a period of time, increasing the possibility of subsequent dancing risks, reflecting the potential dancing risk of the line under long-term exposure to wind force; the maintenance dancing risk refers to the risk of damage to the transmission line or its ancillary equipment caused by dancing, and maintenance costs and resource requirements are also one of the considerations. Risk assessment is performed on the calculation results of the dancing parameters (such as wind yaw angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude, and elliptical inclination angle data) to quantify the impact of each parameter on instantaneous risk, waiting risk and maintenance risk. The weight of each wind yaw dancing risk factor is initialized according to the actual situation, that is, the initial weight is assigned according to the relative importance of the risk factor, and the initial weight is assigned to each risk factor (instantaneous risk, waiting risk, maintenance risk) to obtain the first weight condition for the dancing risk assessment.

[0021] According to the relative importance of each risk factor in the overall risk assessment in the risk assessment results, weights are assigned to obtain the second weight condition for the galloping risk assessment. The first weight condition and the second weight condition are calculated with a centralized value, the weights of each risk factor are balanced, and the final comprehensive weight of the current galloping risk is calculated, which reflects the overall risk level of the current galloping phenomenon and comprehensively considers the influence of the galloping parameter calculation results, instantaneous, waiting and maintenance risks. According to the galloping parameter calculation results and the final weight setting, the galloping parameter calculation results, instantaneous risk, waiting risk and maintenance risk are weighted together to determine the line galloping risk coefficient. Through the comprehensive evaluation of various risk factors such as galloping instantaneous risk, waiting risk, maintenance risk, etc., combined with weight setting and weighted calculation, the line galloping risk coefficient is finally generated, which accurately evaluates the galloping risk of transmission lines and adapts to complex environments and multi-dimensional risk scenarios.

[0022] The line galloping warning module 15 is used to generate a windage galloping warning signal based on the line galloping risk coefficient, according to the line galloping risk threshold and the galloping risk classification warning device.

[0023] Specifically, according to the design standards, environmental conditions and safety requirements of the line, a line galloping risk threshold is pre-set, which represents the maximum allowable galloping risk level. It can be a fixed value or dynamically adjusted according to real-time conditions. It is judged whether the line galloping risk coefficient is greater than or equal to the line galloping risk threshold. If it is greater than or equal to the line galloping risk threshold, it means that the current galloping risk has reached a dangerous or critical level, which may threaten the safe operation of the transmission line, triggering the galloping risk classification warning device to generate a wind deviation galloping warning signal. Multiple thresholds are set according to different galloping risk levels, such as first-level warning, second-level warning, and third-level warning. The warning signal usually includes the warning level, warning content, warning time, warning range, warning measures, etc. Once the warning signal is generated, it is notified to the relevant operation and maintenance personnel and management personnel through appropriate communication channels (such as SMS, e-mail, on-site sound and light alarm, etc.). The operation and maintenance personnel take corresponding preventive or emergency measures according to the warning signal, such as strengthening line monitoring, adjusting the line operation status, preparing maintenance resources, etc. If it is less than the line galloping risk threshold, it means that the line is within the safe range, no alarm is required, and it will continue to monitor without taking any additional emergency measures. By judging whether the line galloping risk coefficient is greater than or equal to the line galloping risk threshold, high-risk status is automatically identified and an early warning mechanism is triggered, which helps power grid operation and maintenance personnel to take necessary preventive measures in a timely manner to reduce the risk of line galloping, thereby ensuring the safe operation of the power grid.

[0024] Furthermore, the monitoring configuration optimization module 11 in the line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision is also used for: The dancing monitoring configuration result includes the laser monitoring configuration result of the multi-parallel line laser component and the visual monitoring configuration result of the monocular vision component; based on the predetermined future time zone, the environment of the transmission line is predicted to obtain the line environment prediction result; based on the line environment prediction result, the wind deviation dancing characteristics of the transmission line are predicted to obtain the line dancing prediction result; based on the line dancing prediction result, the laser monitoring configuration result is rewarded and punished to generate a laser monitoring configuration optimization result; according to the line dancing prediction result, the visual monitoring configuration result is rewarded and punished to generate a visual monitoring configuration optimization result; the laser monitoring configuration optimization result and the visual monitoring configuration optimization result are added to the dancing monitoring configuration optimization result.

[0025] Specifically, multi-parallel line laser assemblies are installed at key points of the transmission line or areas prone to dancing, such as transmission towers, to ensure that the line of sight of the multi-parallel line laser assembly is not blocked by the tower structure or other obstacles. The multi-parallel line laser assembly is a multi-parallel line laser device in the prior art, which is used to emit multiple parallel laser lines, which form laser stripes on the surface of the transmission line. The multi-parallel line laser assembly is set and adjusted to achieve accurate monitoring of the transmission line, including the position, emission angle, power and other parameters of the multi-parallel line laser assembly, and the laser monitoring configuration results are determined. At the same time, a monocular camera (i.e., a monocular vision component) is installed near the multi-parallel line laser assembly to capture images of the scene and laser lines, determine the position, focal length, resolution, sensitivity and other parameters of the camera, and obtain the visual monitoring configuration results. Based on weather forecasts or other relevant factors, a monitoring time period is pre-set, that is, a future time zone is scheduled, and weather forecast data for the scheduled future time zone is obtained, including information such as wind speed, wind direction, temperature, humidity, etc. The environmental conditions of the transmission line in the future are predicted to obtain line environment prediction results, including key environmental parameters such as expected wind speed, wind direction, temperature, humidity, and precipitation probability in the future time zone.

[0026] Analyze historical dancing data, combine current and predicted environmental conditions, predict the dancing characteristics of the transmission line, such as dancing amplitude, frequency, etc., and obtain the line dancing prediction results. For example, if the forecast shows strong winds in the next few hours, it is predicted that the transmission line will have a large dancing amplitude and frequency. Reward and punishment correction is a method of adjusting the monitoring configuration according to the prediction results. If the prediction results are consistent with the actual monitoring results, the corresponding monitoring configuration is rewarded, that is, these configurations are maintained or enhanced; if the prediction results are inconsistent with the actual monitoring results, the corresponding monitoring configuration is punished, that is, these configurations are adjusted or weakened. According to the line dancing prediction results, the laser monitoring configuration results and the visual monitoring configuration results are adjusted, such as adjusting the power and emission frequency of the laser transmitter, or adjusting the position, focal length, image acquisition speed, etc. of the camera. Integrate the adjusted laser monitoring configuration optimization results and visual monitoring configuration optimization results to obtain the dancing monitoring configuration optimization results. For example, suppose that after the reward and punishment correction, the laser monitoring configuration optimization results show that the power of the laser transmitter needs to be increased from 100 watts to 150 watts, and the visual monitoring configuration optimization results show that the camera's image acquisition speed needs to be increased from 10 frames per second to 20 frames per second. The optimization results are added to the dancing monitoring configuration optimization results to update the overall monitoring strategy of the system. By adjusting the laser emission angle and spacing, as well as the camera focal length and frame rate, the monitoring system can more accurately capture the dancing of the transmission line. According to the reward and punishment correction algorithm, the monitoring system automatically adjusts the configuration according to different environmental conditions, improving the system's adaptability and operating efficiency.

[0027] Furthermore, the dancing capture module 12 in the line wind deviation dancing warning system combining multi-parallel line lasers and monocular vision is also used for: Based on the predetermined future time zone and the laser monitoring configuration optimization result, the multi-parallel line laser component is controlled to perform laser emission on the transmission line to establish a line laser grid; according to the transmission line, the reference point of the line laser grid is identified to obtain K identification reference points, wherein K is a positive integer greater than 1; based on the predetermined future time zone and the visual monitoring configuration optimization result, the monocular vision component is synchronously controlled to perform real-time monitoring of the transmission line to obtain a line monitoring image; the line monitoring image is enhanced according to the gamma enhancement function to obtain a line enhanced image; based on the line laser grid, the line enhanced image is feature tracked according to the K identification reference points to obtain a K-point feature tracking result; trajectory fusion is performed based on the K-point feature tracking result to generate the line dancing capture result.

[0028] Specifically, the environmental conditions of the predetermined future time zone, such as weather forecast, wind speed, temperature, etc., are analyzed to predict the environmental changes that the transmission line may face in the future. Using the optimized configuration results, the multi-parallel line laser assembly is controlled according to environmental changes, and the parameters of the laser transmitter are adjusted so that it can perform laser emission according to the predicted environmental conditions, emit multiple parallel laser lines, intersect on the surface of the transmission line, and form a laser grid to achieve monitoring of the transmission line. Laser emission controls the multi-parallel line laser assembly to emit multiple parallel laser lines in the transmission line area, which can capture any tiny movement on the line, thereby achieving accurate monitoring of the line dance. K reference points are identified in the established laser grid, usually based on specific feature points in the laser grid, such as the intersection of laser lines, fixed points on the line, etc., which can be used as reference points for subsequent image processing.

[0029] According to the optimized configuration results, the monocular vision component is synchronously controlled to monitor the transmission line in real time. The monocular vision component will continuously capture the image of the line according to the optimized parameter settings to obtain a series of line monitoring images to capture the real-time status of the line. The line monitoring image is enhanced using the gamma enhancement function to improve the contrast and clarity of the image. Gamma enhancement is a commonly used image enhancement technology that changes the contrast and brightness of the image by adjusting the gamma value of the image. For each pixel, the difference between its grayscale value and the average grayscale value is calculated, and then the difference is multiplied by the gamma coefficient and rounded. The rounded result is added to the original grayscale value to obtain the enhanced grayscale value. The pixel values ​​that have been processed by gamma enhancement are combined to generate a line enhanced image.

[0030] Using the K reference points in the line laser grid, the enhanced image is feature tracked to obtain the position changes of the K reference points in the enhanced image, which reflects the line galloping, such as swing amplitude, frequency, etc. Feature tracking is an image processing technology used to track the changes of specific features in consecutive image frames over time. The tracking results of the K reference points are fused to obtain the overall galloping capture result of the transmission line. Trajectory fusion is a data fusion technology used to combine information from multiple data sources to obtain more accurate and comprehensive results. For example, suppose a 1000-meter-long transmission line is monitored, and a reference point is identified every 50 meters, for a total of 20 reference points (K=20). The monitoring image is processed using an enhancement function with a gamma value of 1.5, and each reference point is tracked in 10 consecutive frames of images. The tracking results of the 20 reference points are fused to generate a comprehensive capture result of the line galloping. By establishing a line laser grid to monitor the transmission lines, identifying reference points improves the accuracy of capturing line dance characteristics, gamma enhancement processing improves image quality, feature tracking technology can capture the real-time dynamics of the line, and trajectory fusion technology integrates the information of multiple reference points to generate comprehensive line dance capture results, providing a basis for risk assessment and early warning.

[0031] Furthermore, the dancing capture module 12 in the line wind deviation dancing warning system combining multi-parallel line lasers and monocular vision is also used for: The gamma enhancement function is: ; in, Represents the grayscale value at the (x, y) position in the line enhanced image, and round represents the rounding process. It represents the gray value at the position (x, y) in the line monitoring image, mean represents the average gray value of the line monitoring image, and γ represents the image enhancement gamma coefficient.

[0032] Specifically, the gamma enhancement function is used to enhance the monitoring image of the transmission line, and the expression is: ; Subtract the average gray value from the gray value of each pixel in the original image, and perform gray normalization to make the gray value distribution of the image more uniform, thereby enhancing the contrast of the image. Multiply the result by the gamma coefficient and perform rounding to convert the calculated gray value into an integer. Add the rounded result to the original gray value to obtain the enhanced gray value, in order to retain some details of the original image while enhancing the contrast. Among them, Represents the gray value at the position (x, y) in the line enhanced image; round represents the rounding process, that is, the calculation result is rounded off; Represents the gray value at the (x, y) position in the line monitoring image; mean represents the average gray value of the line monitoring image; γ represents the image enhancement gamma coefficient, which is used to control the degree of image enhancement. When the gamma value is greater than 1, the highlight part of the image will be enhanced and the contrast will be improved, while when the gamma value is less than 1, the dark details of the image will be enhanced and the contrast will be reduced. By adjusting the gray value of each pixel, the overall contrast of the image is enhanced, while retaining a certain amount of original image information, which is effective in improving the quality of transmission line monitoring images, especially in low light or insufficient contrast conditions.

[0033] Further, as attached Figure 2 As shown, the dancing risk assessment module 14 in the line wind deviation dancing warning system combining multi-parallel line lasers and monocular vision is also used for: The wind deviation dancing risk factor includes instantaneous dancing risk, dancing waiting risk and dancing maintenance risk; based on the wind deviation dancing risk factor, the dancing parameter calculation result is subjected to risk assessment to obtain a dancing risk assessment result; based on the wind deviation dancing risk factor, the weight is initialized to set the first weight condition for dancing risk assessment; according to the dancing risk assessment result, a proportion is calculated to generate a second weight condition for dancing risk assessment; based on the first weight condition for dancing risk assessment and the second weight condition for dancing risk assessment, a concentration value is calculated to generate a third weight condition for dancing risk assessment; according to the third weight condition for dancing risk assessment, the dancing risk assessment result is weightedly calculated to generate the line dancing risk coefficient.

[0034] Furthermore, the dancing risk assessment module 14 in the line wind deviation dancing warning system combining multi-parallel line lasers and monocular vision is also used for: Based on the windage dancing risk factor, back-tracing learning is performed to build a dancing risk analysis multi-channel, wherein the dancing risk analysis multi-channel includes a dancing instantaneous risk analysis channel, a dancing waiting risk analysis channel and a dancing maintenance risk analysis channel; the dancing parameter calculation result is input into the dancing instantaneous risk analysis channel to obtain the dancing instantaneous risk coefficient; based on the dancing parameter calculation result, according to the dancing waiting risk analysis channel, the dancing waiting risk coefficient is obtained; based on the dancing parameter calculation result, according to the dancing maintenance risk analysis channel, the dancing maintenance risk coefficient is obtained; the dancing instantaneous risk coefficient, the dancing waiting risk coefficient and the dancing maintenance risk coefficient are output as the dancing risk assessment result.

[0035] Specifically, the wind deviation and galloping risk factor is an indicator used to evaluate the safety risks of the line under wind deviation and galloping conditions, including the instantaneous risk of galloping, the waiting risk of galloping and the maintenance risk of galloping. Among them, the instantaneous risk of galloping refers to the immediate risk of the transmission line when wind deviation and galloping occur, which may be related to the galloping amplitude, speed and other factors; the waiting risk of galloping refers to the accumulation or aggravation of risks that may be caused in the future after the transmission line gallops; the galloping maintenance risk refers to the risks that may be faced when maintaining or repairing galloping faults, such as operational safety risks and power outage risks.

[0036] The wind deviation dancing risk factor is used to conduct risk assessment on the calculation results of dancing parameters (such as wind deviation angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and elliptical inclination angle, etc.). Retrospective learning is a machine learning method that analyzes historical data to discover potential risk patterns and associations, thereby improving the ability to predict future risks. According to risk factors such as dancing instantaneous risk, dancing waiting risk and dancing maintenance risk, the risk type that needs to be analyzed is determined, and an independent channel is established for each risk factor to analyze the safety risks of the line at the current moment, in the future, and in long-term operation. In each channel, the dancing risk coefficient of the line is calculated based on the calculation results of the dancing parameters and the corresponding risk factors, reflecting the safety risk level of the line at different time scales. The dancing instantaneous risk analysis channel specifically processes data related to dancing instantaneous risk. The dancing parameter calculation results (such as wind deviation angle, dancing amplitude, etc.) are input into the channel, and the relationship between historical dancing events and dancing parameters is analyzed to calculate the dancing instantaneous risk coefficient. The Dancing Waiting Risk Analysis Channel focuses on the cumulative risks that may result from not promptly handling dancing after it occurs. It also uses the dancing parameter calculation results and analyzes historical data to determine the dancing waiting risk coefficient, reflecting the risk level that may be faced in the future. The Dancing Maintenance Risk Analysis Channel assesses the risks that may be encountered during maintenance or repair, analyzes historical maintenance records and dancing events, and calculates the dancing maintenance risk coefficient. The risk coefficients output by the three channels (dancing instantaneous risk coefficient, dancing waiting risk coefficient, and dancing maintenance risk coefficient) are combined to form the final dancing risk assessment result, which can be a comprehensive score or grade, or three independent risk coefficients to indicate the severity of different types of risks.

[0037] According to the relative importance of risk factors, initial weights are assigned, and corresponding weights are assigned to different risk factors to determine the first weight condition of the dancing risk assessment, which reflects the relative importance of different risk factors to line safety risks. For example, if instantaneous risk is considered to be the most important, then a higher weight is assigned. According to the results of the dancing risk assessment, the contribution ratio of each risk factor in the overall risk assessment is calculated. According to the results of the dancing risk assessment, the proportion calculation is performed to generate the second weight condition of the dancing risk assessment, specifically, each risk factor is divided by the sum of all risk factors through expert scoring, historical data analysis or machine learning algorithm to obtain the importance of each risk factor in the overall risk assessment. For example, the instantaneous risk coefficient of dancing is 0.8, the waiting risk coefficient of dancing is 0.6, and the maintenance risk coefficient of dancing is 0.4. Calculate the proportion of each coefficient and determine the importance of each risk coefficient in the overall risk assessment. The instantaneous risk proportion: 0.8 / (0.8+0.6+0.4) is approximately equal to 0.4, the waiting risk proportion: 0.6 / (0.8+0.6+0.4) is approximately equal to 0.3, and the maintenance risk proportion: 0.4 / (0.8+0.6+0.4) is approximately equal to 0.2.

[0038] On the basis of the first weight condition and the second weight condition, the third weight condition is calculated by statistical methods (such as mean value, median, etc.), and the weights of different risk factors are considered more comprehensively and balanced, not only the relative importance of risk factors (first weight condition) but also the contribution ratio in the overall risk assessment (second weight condition) are considered. According to the third weight condition, each risk factor in the galloping risk assessment result is weighted, and the assessment result of each risk factor is multiplied by its corresponding third weight condition, and then the product is added to obtain a total risk coefficient, that is, the line galloping risk coefficient is obtained, which is used to indicate the current risk level of the transmission line. The higher the line galloping risk coefficient, the greater the risk of line galloping, and corresponding early warning measures need to be taken. A comprehensive line galloping risk coefficient is obtained through weight setting and weighted calculation, which fully reflects the safety status of the line.

[0039] Furthermore, the dancing risk assessment module 14 in the line wind deviation dancing warning system combining multi-parallel line lasers and monocular vision is also used for: According to the wind deviation dancing risk factor, the dancing risk assessment records of the transmission line are traced back to obtain the dancing parameter calculation sample set, the dancing instantaneous risk sample set, the dancing waiting risk sample set and the dancing maintenance risk sample set; with the dancing parameter calculation sample set as input data and the dancing instantaneous risk sample set as output data, deep learning is performed on the residual neural network to build the dancing instantaneous risk analysis channel; based on the dancing parameter calculation sample set and the dancing waiting risk sample set, deep learning is performed to establish the dancing waiting risk analysis channel; based on the dancing parameter calculation sample set and the dancing maintenance risk sample set, deep learning is performed to generate the dancing maintenance risk analysis channel; the dancing instantaneous risk analysis channel, the dancing waiting risk analysis channel and the dancing maintenance risk analysis channel are connected as parallel nodes to generate the dancing risk analysis multi-channel.

[0040] Specifically, the dancing risk assessment records of the transmission lines in the past period of time are reviewed and analyzed, including the calculation results of the dancing parameters, the risk assessment results, and the relevant environmental parameters (such as wind speed, wind direction, etc.). Through retrospective analysis, four different sample sets are generated: the dancing parameter calculation sample set contains the calculation results of the historical dancing parameters; the dancing instantaneous risk sample set contains the results of the historical instantaneous risk assessment; the dancing waiting risk sample set contains the results of the historical waiting risk assessment; and the dancing maintenance risk sample set contains the results of the historical maintenance risk assessment.

[0041] The dancing parameter calculation sample set is used as input data, including wind angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude, and elliptical tilt angle data, and the dancing instantaneous risk sample set is used as output data. The residual neural network is trained for deep learning to establish a prediction model for dancing instantaneous risk. Deep learning is a machine learning method that uses a multi-layer neural network model to learn high-level features and complex patterns in data. The residual neural network (ResNet) is a deep learning architecture that can effectively reduce the gradient vanishing problem in deep networks and is particularly suitable for processing complex data relationships. In the dancing monitoring system, ResNet is used to learn the complex mapping relationship between the input dancing parameters (such as wind speed, wind direction, line vibration amplitude, etc.) and the output instantaneous risk. By training the residual neural network, a special channel is established to parse and predict the instantaneous risk of the line, which can process the input dancing parameters and output the corresponding instantaneous risk prediction results.

[0042] Similarly, a dancing waiting risk analysis channel is established through deep learning technology to process the input dancing parameters and output the corresponding waiting risk prediction results; a dancing maintenance risk analysis channel is generated through deep learning technology to process the input dancing parameters, but the output is the prediction results of maintenance risks. Each risk analysis channel is an independent node, running in parallel, and each processing a specific risk type. The instantaneous risk analysis channel focuses on predicting risks in a short period of time, the waiting risk analysis channel focuses on risks in a slightly longer period of time, and the maintenance risk analysis channel focuses on assessing the risks when performing maintenance activities, including the difficulty and cost of maintenance operations and the risks that may occur during maintenance. Each channel can independently process the risk type associated with it, and the trained channels are connected in a parallel manner to ensure that the channels can simultaneously receive input data and generate outputs. The output results of each channel are comprehensively analyzed to obtain a comprehensive risk assessment. Through deep learning, complex risk patterns are learned from historical data to improve the accuracy of risk assessment. Through parallel channels, different types of risks are considered at the same time to obtain more comprehensive risk assessment results, and multiple channels of dancing risk analysis are generated to provide a comprehensive risk assessment view to help power grid operation and maintenance personnel better understand the risks of lines at different time scales.

[0043] Furthermore, the line dancing warning module 15 in the line wind deviation dancing warning system combining multi-parallel line lasers and monocular vision is also used for: Determine whether the line dancing risk coefficient is greater than / equal to the line dancing risk threshold; if the line dancing risk coefficient is greater than / equal to the line dancing risk threshold, activate the dancing risk classification warning device; input the line dancing risk coefficient into the dancing risk classification warning device to obtain the wind deviation dancing warning signal.

[0044] Specifically, according to the design standards, environmental conditions and safety requirements of the line, the line galloping risk threshold is set in advance, and the calculated line galloping risk coefficient is compared with the set line galloping risk threshold. If the line galloping risk coefficient is greater than or equal to the line galloping risk threshold, it is considered that the line is in a high-risk state, and early warning measures need to be taken to activate the galloping risk classification early warning device, which can be done automatically through software instructions or manually after manual confirmation. The line galloping risk coefficient is input into the activated galloping risk classification early warning device to generate a corresponding wind deviation galloping early warning signal. For example, if the galloping risk coefficient is close to but does not exceed the threshold, the operation and maintenance personnel are reminded to pay close attention to the galloping situation; if the galloping risk coefficient is greater than or equal to the first threshold but lower than the highest threshold, it is recommended to take some countermeasures, such as increasing the line monitoring frequency or adjusting equipment parameters; if the galloping risk coefficient is greater than or equal to the highest threshold, it is recommended to take emergency measures immediately, such as stopping the line operation or performing emergency maintenance.

[0045] Early warning signals usually include warning levels (such as level 1 warning, level 2 warning, level 3 warning, etc.), warning content (such as possible line galloping, recommended measures, etc.), warning time (specific time when the warning signal is issued), and warning scope (affected line sections). Relevant operation and maintenance personnel and management personnel are notified through appropriate communication channels (such as text messages, emails, on-site sound and light alarms, etc.) to remind them to pay attention to possible dangerous situations, or trigger automated protection measures, such as adjusting line tension, starting vibration dampers, and even stopping line operation in extreme cases. After the early warning is issued, it enters the continuous monitoring mode and dynamically adjusts the risk assessment results through further calculation of galloping parameters and real-time data analysis. If the galloping risk factor continues to rise, the alarm level can be increased or more severe measures can be taken; if the galloping risk factor decreases, the alarm can be canceled and normal operation can be resumed. By detecting that the line galloping risk exceeds the safety threshold, an early warning signal is automatically issued to remind power grid operation and maintenance personnel to take necessary preventive measures, which helps to respond to potential safety risks in a timely manner, thereby ensuring the safe operation of the power grid.

[0046] In summary, the line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision provided by the present application has the following technical effects: Through the monitoring configuration optimization module, the monitoring configuration optimization module is used to adjust the dancing monitoring configuration result of the transmission line according to the predetermined future time zone, and generate the dancing monitoring configuration optimization result; the dancing capture module, the dancing capture module is used to capture the dancing of the transmission line according to the multi-parallel line laser component and the monocular vision component based on the predetermined future time zone and the dancing monitoring configuration optimization result, and obtain the line dancing capture result; the dancing parameter analysis module, the dancing parameter analysis module is used to perform multi-dimensional wind deviation dancing parameter calculation according to the line dancing capture result, and obtain the dancing parameter calculation result; the dancing risk assessment module, the dancing risk assessment module is used to perform dancing risk assessment on the transmission line according to the wind deviation dancing risk factor and the dancing parameter calculation result, and determine the line dancing risk coefficient; the line dancing warning module, the line dancing warning module is used to generate a wind deviation dancing warning signal based on the line dancing risk coefficient, according to the line dancing risk threshold and the dancing risk grading warning device. In other words, through the combination of multi-parallel line lasers and monocular vision, high-precision monitoring data can be provided under various complex conditions, risk assessments can be conducted on transmission lines, wind deviation and fluctuation warning signals can be generated, the accuracy of wind deviation and fluctuation warnings can be improved, and missed reports and false alarms can be reduced.

[0047] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0048] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A line wind deviation warning system combining multi-parallel line lasers and monocular vision, characterized by: include: A monitoring configuration optimization module, the monitoring configuration optimization module is used to adjust the dancing monitoring configuration result of the transmission line according to the predetermined future time zone to generate a dancing monitoring configuration optimization result; A dancing capture module, the dancing capture module is used to capture the dancing of the transmission line according to the multi-parallel line laser component and the monocular vision component based on the predetermined future time zone and the dancing monitoring configuration optimization result, so as to obtain a line dancing capture result; A dancing parameter analysis module, the dancing parameter analysis module is used to calculate multi-dimensional wind deviation dancing parameters according to the line dancing capture result to obtain a dancing parameter calculation result; A galloping risk assessment module, the galloping risk assessment module is used to perform a galloping risk assessment on the transmission line according to the wind deviation galloping risk factor and the galloping parameter calculation result, and determine the line galloping risk coefficient; A line galloping warning module is used to generate a windage galloping warning signal based on the line galloping risk coefficient, according to the line galloping risk threshold and the galloping risk classification warning device.

2. The line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision according to claim 1 is characterized in that: The monitoring configuration optimization module is used to adjust the dancing monitoring configuration result of the transmission line according to the predetermined future time zone to generate the dancing monitoring configuration optimization result, including: The dancing monitoring configuration result includes the laser monitoring configuration result of the multi-parallel line laser assembly and the visual monitoring configuration result of the monocular vision assembly; Performing environmental prediction on the power transmission line based on the predetermined future time zone to obtain a line environment prediction result; Based on the line environment prediction result, the windage yaw characteristic of the transmission line is predicted to obtain a line yaw prediction result; Performing reward and punishment correction on the laser monitoring configuration result based on the line galloping prediction result to generate a laser monitoring configuration optimization result; Performing reward and punishment correction on the visual monitoring configuration result according to the line dancing prediction result to generate a visual monitoring configuration optimization result; The laser monitoring configuration optimization result and the visual monitoring configuration optimization result are added to the dancing monitoring configuration optimization result.

3. The line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision as claimed in claim 1 is characterized in that: The dancing capture module is used to capture the dancing of the power transmission line based on the predetermined future time zone and the dancing monitoring configuration optimization result according to the multi-parallel line laser component and the monocular vision component to obtain the line dancing capture result, including: Based on the predetermined future time zone and the laser monitoring configuration optimization result, controlling the multi-parallel line laser assembly to perform laser emission on the transmission line and establish a line laser grid; According to the transmission line, the line laser grid is subjected to reference point identification to obtain K identification reference points, wherein K is a positive integer greater than 1; Based on the predetermined future time zone and the visual monitoring configuration optimization result, synchronously controlling the monocular vision component to monitor the transmission line in real time to obtain a line monitoring image; Performing enhancement processing on the line monitoring image according to a gamma enhancement function to obtain a line enhanced image; Based on the line laser grid, feature tracking is performed on the line enhanced image according to the K identification reference points to obtain K-point feature tracking results; Trajectory fusion is performed based on the K-point feature tracking result to generate the line dance capture result.

4. The line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision as claimed in claim 3 is characterized in that: The gamma enhancement function is: ； in, Represents the grayscale value at the (x, y) position in the line enhanced image, and round represents the rounding process. It represents the gray value at the position (x, y) in the line monitoring image, mean represents the average gray value of the line monitoring image, and γ represents the image enhancement gamma coefficient.

5. The line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision as claimed in claim 1 is characterized in that: The galloping risk assessment module is used to perform a galloping risk assessment on the transmission line according to the wind deviation galloping risk factor and the galloping parameter calculation result to determine the line galloping risk coefficient, including: The wind deviation dancing risk factors include dancing instantaneous risk, dancing waiting risk and dancing maintenance risk; Based on the wind deviation dancing risk factor, risk assessment is performed on the dancing parameter calculation result to obtain a dancing risk assessment result; Initialize weight setting based on the wind deviation dancing risk factor to determine the first weight condition for dancing risk assessment; Calculate the proportion according to the dancing risk assessment result to generate a second weight condition for dancing risk assessment; Performing a concentrated value calculation based on the first weight condition for dancing risk assessment and the second weight condition for dancing risk assessment to generate a third weight condition for dancing risk assessment; The dancing risk assessment result is weighted according to the third weight condition of the dancing risk assessment to generate the line dancing risk coefficient.

6. The line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision as claimed in claim 5 is characterized in that: Based on the wind deviation dancing risk factor, risk assessment is performed on the dancing parameter calculation result to obtain a dancing risk assessment result, including: Based on the wind deviation dancing risk factor, backtracking learning is performed to build a dancing risk analysis multi-channel, wherein the dancing risk analysis multi-channel includes a dancing instantaneous risk analysis channel, a dancing waiting risk analysis channel and a dancing maintenance risk analysis channel; Inputting the dancing parameter calculation result into the dancing instantaneous risk analysis channel to obtain the dancing instantaneous risk coefficient; Based on the dancing parameter calculation result, and according to the dancing waiting risk analysis channel, a dancing waiting risk coefficient is obtained; Based on the dancing parameter calculation result and according to the dancing maintenance risk analysis channel, a dancing maintenance risk coefficient is obtained; The dancing instantaneous risk coefficient, the dancing waiting risk coefficient and the dancing maintenance risk coefficient are output as the dancing risk assessment result.

7. The line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision as claimed in claim 6 is characterized in that: Based on the wind deviation dancing risk factor, backtracking learning is performed to build a dancing risk analysis multi-channel, wherein the dancing risk analysis multi-channel includes a dancing instantaneous risk analysis channel, a dancing waiting risk analysis channel and a dancing maintenance risk analysis channel, including: According to the wind deviation galloping risk factor, the galloping risk assessment record of the transmission line is traced back to obtain a galloping parameter calculation sample set, a galloping instantaneous risk sample set, a galloping waiting risk sample set and a galloping maintenance risk sample set; Using the dancing parameter calculation sample set as input data and the dancing instantaneous risk sample set as output data, deep learning is performed on the residual neural network to build the dancing instantaneous risk analysis channel; Perform deep learning based on the dancing parameter calculation sample set and the dancing waiting risk sample set to establish the dancing waiting risk analysis channel; Perform deep learning based on the dancing parameter calculation sample set and the dancing maintenance risk sample set to generate the dancing maintenance risk analysis channel; The dancing instantaneous risk analysis channel, the dancing waiting risk analysis channel and the dancing maintenance risk analysis channel are connected as parallel nodes to generate the dancing risk analysis multi-channel.

8. The line wind deviation and dancing warning system combining multi-parallel line lasers and monocular vision as claimed in claim 1 is characterized in that: The line galloping warning module is used to generate a wind deviation galloping warning signal based on the line galloping risk coefficient, according to the line galloping risk threshold and the galloping risk classification warning device, including: Determining whether the line galloping risk coefficient is greater than / equal to the line galloping risk threshold; If the line dancing risk coefficient is greater than / equal to the line dancing risk threshold, activating the dancing risk classification warning device; The line dancing risk coefficient is input into the dancing risk classification warning device to obtain the wind deviation dancing warning signal.

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