Power transmission line windage yaw galloping monitoring method based on cross curve laser and binocular vision

Abstract

The invention provides a power transmission line windage yaw galloping monitoring method based on cross curve laser and binocular vision, and relates to the technical field of windage yaw galloping monitoring, and the method comprises the steps: generating a preset cross laser beam propagation path; carrying out continuous dynamic monitoring on the laser contour based on binocular vision equipment, and generating a windage yaw galloping image set; performing windage yaw abnormal probability calculation to generate a first windage yaw abnormal probability; performing wind resistance analysis on the power transmission conductor, and compensating the first windage yaw abnormal probability; when the second windage yaw abnormal probability is greater than or equal to a preset abnormal probability, analyzing the windage yaw galloping image set; and performing early warning according to the windage yaw galloping data. According to the application, the technical problem that the accuracy of power transmission line windage yaw galloping monitoring is poor due to the fact that a physical sensor is complex to install and is easily influenced by the environment in the prior art can be solved, the technical target of accurately monitoring the power transmission line windage yaw galloping is achieved, and the technical effect of improving the monitoring accuracy is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of wind yaw and swing monitoring, and in particular to a method for monitoring wind yaw and swing of a power transmission line based on cross-line laser and binocular vision. Background Art

[0002] With the increasing demand for electricity in modern society, the stability and safety of transmission lines are particularly important. Wind yaw is one of the common external factors that affect the stable operation of transmission lines. Especially in areas with high wind speeds, transmission lines will vibrate violently under the action of wind, which will not only cause physical damage to the lines, but may also cause large-scale power outages.

[0003] At present, traditional wind yaw and flutter monitoring methods mainly rely on the deployment of physical sensors, such as strain gauges and accelerometers, which are directly installed on transmission towers or conductors to monitor line deformation and stress conditions. However, physical sensors are not only complex to install, but also easily damaged under harsh weather conditions, resulting in inaccurate or interrupted data collection, and relatively high maintenance costs. In addition, the monitoring range of physical sensors is limited, and it is impossible to achieve all-round real-time monitoring of long-distance transmission lines, and there is a large monitoring blind spot. Therefore, traditional monitoring methods have obvious deficiencies in coverage and real-time performance. In addition, although the method based on manual inspection can make up for the problem of insufficient coverage of physical sensors, it is inefficient, relies on manual operation, and is difficult to respond to emergencies such as wind yaw and flutter in a timely manner.

[0004] In summary, there are technical problems in the prior art due to the complex installation of physical sensors and their susceptibility to environmental influences, which leads to inaccurate or interrupted data collection, further affecting the real-time and accuracy of wind deviation and swing monitoring of transmission lines, as well as the timely response to emergencies. Summary of the invention

[0005] The purpose of this application is to provide a method for monitoring the wind yaw and sway of a power line based on cross-line laser and binocular vision, so as to solve the technical problems in the prior art that the installation of physical sensors is complex and susceptible to environmental influences, resulting in inaccurate or interrupted data collection, further affecting the real-time and accuracy of wind yaw and sway monitoring of power lines, as well as the timely response to emergencies.

[0006] In view of the above problems, the present application provides a method for monitoring the wind deviation and dancing of a power transmission line based on a cross-line laser and binocular vision, including: setting scanning parameters of a cross-line laser in a state where no wind deviation occurs for a transmission line in a preset area, and generating a preset cross laser beam propagation path; taking the preset cross laser beam propagation path as a target, controlling the cross-line laser to perform laser contour scanning on the transmission line, and simultaneously performing continuous dynamic monitoring of the laser contour based on a binocular vision device to generate a set of wind deviation and dancing images; calculating the probability of wind deviation abnormality based on the set of wind deviation and dancing images to generate a first wind deviation abnormality probability; performing a wind resistance analysis on the transmission line in the preset area, compensating the first wind deviation abnormality probability with the resistance analysis result, and generating a second wind deviation abnormality probability; when the second wind deviation abnormality probability is greater than or equal to the preset abnormality probability, performing a wind deviation and dancing analysis on the transmission line based on the cross-line laser and the binocular vision device to generate wind deviation and dancing data; and issuing an early warning based on the wind deviation and dancing data.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The preset cross laser beam propagation path is generated by setting scanning parameters of the cross laser for the transmission wire in the preset area when no wind deviation occurs; with the preset cross laser beam propagation path as the target, the cross laser is controlled to perform laser contour scanning on the transmission wire, and at the same time, continuous dynamic monitoring of the laser contour is performed based on the binocular vision device to generate a set of wind deviation dancing images; the wind deviation abnormality probability is calculated based on the wind deviation dancing image set to generate a first wind deviation abnormality probability; the wind resistance analysis is performed on the transmission wire in the preset area, and the first wind deviation abnormality probability is compensated with the resistance analysis result to generate a second wind deviation abnormality probability; when the second wind deviation abnormality probability is greater than or equal to the preset abnormality probability, the wind deviation dancing analysis is performed on the transmission wire based on the cross laser and the binocular vision device to generate wind deviation dancing data; an early warning is issued based on the wind deviation dancing data to achieve the technical goal of real-time and accurate monitoring of the wind deviation dancing of the transmission line, and to achieve the technical effect of improving the monitoring coverage, reducing maintenance costs, and enhancing the early warning response speed and accuracy.

[0008] 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

[0009] 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.

[0010] Figure 1 This is a flow chart of a method for monitoring windage swing of a power transmission line based on cross-line laser and binocular vision in this application; Figure 2 This is a flow chart of generating a first wind deviation abnormality probability in the wind deviation dancing monitoring method of a power transmission line based on cross-line laser and binocular vision in this application. DETAILED DESCRIPTION

[0011] This application provides a method for monitoring the wind swing of a power line based on cross-line laser and binocular vision, which solves the technical problem in the prior art that the physical sensor is complex to install and is susceptible to environmental influences, resulting in inaccurate or interrupted data collection, further affecting the real-time and accuracy of the wind swing monitoring of the power line, as well as the timely response to emergencies. The technical goal of achieving real-time and accurate monitoring of the wind swing of the transmission line is achieved, and the technical effects of increasing monitoring coverage, reducing maintenance costs, and enhancing the speed and accuracy of early warning response are achieved.

[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] Please see attached Figure 1 The present application provides a method for monitoring windage fluctuations of power transmission lines based on cross-line laser and binocular vision, which specifically includes the following steps: Step 1: For the transmission lines in the preset area, the scanning parameters of the cross-line laser are set in a state where no wind deflection occurs, and a preset cross laser beam propagation path is generated.

[0014] Specifically, the preset area refers to an area pre-set by the staff in this field. In the absence of wind deviation, the working parameters of the cross-line laser used to scan the transmission line in the preset area are determined to generate a preset cross laser beam propagation path. Among them, the cross-line laser refers to a type of laser that forms two horizontal and vertical laser lines crossing in space. The cross-line laser captures images through two cameras at the same time and uses triangulation to calculate the three-dimensional position of the object. In the absence of wind deviation of the transmission line, the center point of the cross laser beam emitted by the laser will completely coincide with the position of the transmission line. Through multiple scans, an accurate preset cross laser beam propagation path is generated as the reference path of the transmission line in a stationary state, that is, the marking network. The marking network is a reference coordinate system used to detect whether the transmission line has danced due to the action of wind. For example, if the line is found to deviate from the reference path by more than 1 mm during scanning, the dancing phenomenon is identified and an alarm is issued. The change of the line under the action of wind is effectively monitored by the marking network method.

[0015] Step 2: Taking the preset cross laser beam propagation path as the target, control the cross-line laser to perform laser contour scanning on the transmission line, and simultaneously perform continuous dynamic monitoring of the laser contour based on a binocular vision device to generate a set of wind deviation dancing images.

[0016] Specifically, based on the preset cross laser beam propagation path, the laser profile of the transmission line is scanned by controlling the cross laser. The laser beam emitted by the cross laser forms a contour line on the transmission line, and the binocular vision device captures the dynamic changes of the laser profile in real time and continuously monitors the position of the laser line. The binocular vision device measures the relative position of the laser profile and the transmission line, and generates a set of wind deviation dancing images for subsequent analysis.

[0017] Step three: Calculate the wind deviation abnormality probability based on the wind deviation dancing image set to generate a first wind deviation abnormality probability.

[0018] Specifically, the abnormal probability of wind deviation is calculated based on the set of wind deviation dancing images, and multiple sets of image data collected by binocular vision equipment are used to analyze the dancing of the transmission line, identify the position offset of the transmission line, and compare it with the preset reference position. Then, the first wind deviation abnormal probability is generated according to the degree of offset. The larger the offset, the higher the abnormal probability, and vice versa. For example, when the offset is 2 mm, the abnormal probability is 10%, and if the offset reaches 5 mm, the abnormal probability rises to 100%. By comparing the image data and the offset situation, the abnormal degree of wind deviation is quantified, and a clear probability value is generated for each dancing situation to help predict and warn of the wind deviation risk of the transmission line.

[0019] Step 4: Perform wind resistance analysis on the transmission lines in the preset area, compensate the first wind deviation abnormality probability with the resistance analysis result, and generate a second wind deviation abnormality probability.

[0020] Specifically, a wind resistance analysis is performed on the transmission lines in the preset area, and the degree of wind influence is evaluated by calculating the wind resistance of the lines under wind force. The first wind deviation abnormality probability is compensated using the resistance analysis results, and the wind deviation abnormality probability is adjusted according to the wind resistance of the line. For example, the first wind deviation abnormality probability is 20%, but if the wind resistance is weak, the abnormal probability is increased to generate a second wind deviation abnormality probability, which represents a more accurate wind deviation risk probability after considering the wind resistance. If the wind resistance is 80%, then after compensation, the second wind deviation abnormality probability may rise to 25%, which more truly reflects the risk of transmission lines in the wind.

[0021] Step 5: When the second wind deviation abnormal probability is greater than or equal to the preset abnormal probability, the wind deviation dancing analysis of the transmission line is performed based on the cross-line laser and the binocular vision device to generate wind deviation dancing data.

[0022] Specifically, when the second wind deviation abnormality probability is greater than or equal to the preset abnormality probability, a cross-line laser and binocular vision device are used to perform a detailed wind deviation dance analysis on the transmission line, thereby generating detailed wind deviation dance data. The cross-line laser can accurately project a cross-line to help locate the position of the wire; while the binocular vision device obtains the three-dimensional movement information of the wire by simulating human eye observation. The second wind deviation abnormality probability is a value obtained through preliminary calculations, indicating the possibility of wind deviation abnormalities in the line, and the preset abnormality probability is a threshold set in advance. For example, if the preset abnormality probability is 20%, when the second wind deviation abnormality probability reaches or exceeds this value, it is considered that the transmission line may be abnormal, and a more in-depth analysis is required.

[0023] Step six: issuing an early warning based on the wind deviation and dancing data.

[0024] Specifically, by analyzing the wind yaw and sway data of the line, it is determined whether an early warning is needed. The wind yaw and sway data contains various dynamic information of the transmission line under the action of wind, such as wind yaw angle, sway amplitude, vertical and horizontal displacement, etc. The safety status of the line is evaluated based on these data. For example, if the wind yaw angle reaches 5 degrees and the sway amplitude is 10 cm, this may indicate that the line is in an unstable state. By setting a safety threshold, when the sway data exceeds the threshold, an early warning will be triggered to remind maintenance personnel that the line is affected by wind and may fail, thereby promptly identifying potential risks and ensuring the safe operation of the transmission line.

[0025] The transmission line wind yaw and sway monitoring method based on cross-line laser and binocular vision can achieve the technical goal of real-time and accurate monitoring of the wind yaw and sway of the transmission line, and achieve the technical effects of increasing the monitoring coverage, reducing maintenance costs, and enhancing the early warning response speed and accuracy.

[0026] Furthermore, the present application also includes: The windage dancing data includes windage angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and elliptical tilt angle data.

[0027] Specifically, the wind deflection angle refers to the deviation angle of the transmission line under the action of wind, which is used to indicate the angle between the line and its original position. The dancing amplitude refers to the overall amplitude of the transmission line under the action of wind, indicating the maximum distance that the line deviates from the original position during the dancing process. The vertical dancing amplitude is the vertical displacement amplitude during the dancing process, which refers to the amplitude of the dancing of the transmission line in the vertical direction. The horizontal dancing amplitude indicates the dancing amplitude of the transmission line in the horizontal direction. The ellipse inclination angle data is used to describe the inclination degree of the dancing trajectory of the transmission line under the action of wind. When the dancing trajectory is elliptical, the inclination angle of the ellipse indicates the angle between the major axis of the ellipse and the horizontal line.

[0028] The wind deviation and dancing data integrates parameters of multiple dimensions, including the wind deviation angle of the line, the overall dancing amplitude, as well as the amplitudes in the vertical and horizontal directions and the inclination angle of the elliptical trajectory, to fully understand the dynamic behavior of the transmission line under the action of wind.

[0029] Furthermore, the present application also includes: Acquire multiple adjacent lines of the transmission line in the preset area; perform abnormal impact analysis based on the connection structure and distance between the multiple adjacent lines and the transmission line to generate multiple abnormal impact coefficients; establish an adjacent line topology based on the multiple abnormal impact coefficients with the transmission line in the preset area as the center; and perform linkage warning based on the adjacent line topology.

[0030] Specifically, multiple adjacent lines of the transmission line in the preset area are obtained, and other lines adjacent to the target transmission line are identified. The adjacent lines and the target line are physically close to each other or have a connection structure. For example, there are three other transmission lines near a certain transmission line, and the distance between them may be 50 meters, 80 meters, etc.

[0031] Next, an abnormal impact analysis is performed based on the connection structure and distance between multiple adjacent lines and the target transmission line to generate multiple abnormal impact coefficients. The connection structure refers to the physical or electrical connection relationship between the lines, and the distance refers to their relative position in space, which evaluates the potential impact of adjacent lines on the target line. For example, if the distance between two lines is close and there is a strong electrical coupling, the abnormal impact coefficient may be high. Assuming that the impact coefficient of a line is 0.8, the impact coefficient of a farther line may be only 0.2.

[0032] Then, with the transmission line in the preset area as the center, the neighboring line topology is established according to the abnormal influence coefficient. Topology is a diagram that describes the connection relationship between elements in the system. The influence network between the target line and the neighboring lines is constructed through the abnormal influence coefficient. For example, a line with a short distance and a high influence coefficient may have a larger node in the topology diagram, indicating that it is more important.

[0033] Finally, linkage warning is performed based on the topology of adjacent lines. Linkage warning means that when an abnormality occurs in an adjacent line, a warning is issued based on the topological relationship to predict the impact of the abnormality on the target line. For example, if a fault occurs in an adjacent line and the impact coefficient is 0.8, a timely warning is issued, indicating that the fault may have a significant impact on the target line.

[0034] By obtaining the adjacent lines of the target transmission line and performing abnormal impact analysis based on the connection structure and distance, multiple abnormal impact coefficients are generated, the topological structure of the adjacent lines is constructed, and linkage warning is performed through the topological relationship, thereby improving the safety monitoring capability of the transmission line.

[0035] Furthermore, the present application also includes: The wind yaw and sway data of the plurality of adjacent lines are estimated based on the wind yaw and sway data and the adjacent line topology; and a linkage warning is performed based on the estimated results of the wind yaw and sway data of the plurality of adjacent lines.

[0036] Specifically, the wind deviation swing data of multiple adjacent lines are estimated based on the wind deviation swing data and the adjacent line topology, and the wind deviation swing data of the target transmission line and the topological structure of the adjacent lines are used to estimate the swing of the adjacent lines. By analyzing the actual swing data of the target line, combined with the connection relationship and influence coefficient in the topology, the wind deviation of the adjacent lines under the same or similar environmental conditions is estimated. For example, if the wind deviation amplitude of the target line is 5 cm, and the adjacent lines are closely connected to it and have a high influence coefficient, then it may be estimated that the wind deviation amplitude of the adjacent line is 4 cm.

[0037] Then, a linkage warning is issued based on the inferred wind swing data of the adjacent lines. The linkage warning means that when the target line has wind swing, not only a warning is issued for the target line, but also an abnormal situation that may occur in these lines is warned based on the inferred results of the adjacent lines. For example, if the wind swing amplitude of a certain adjacent line is inferred to be 4 cm and exceeds the set safety threshold, a linkage warning is issued to indicate that the line also has a risk of swing.

[0038] By inferring the wind yaw fluctuation data of multiple adjacent lines based on the wind yaw fluctuation data of the target transmission line and the topological structure of the adjacent lines, a linkage warning is issued based on the inference results to prompt the risks that the adjacent lines may face, thereby improving the overall monitoring and early warning capabilities.

[0039] Further, if Figure 2 As shown, this application also includes: The wind deviation dancing image set includes multiple pairs of images, each pair of images includes a first image captured by a first camera and a second image captured by a second camera in the binocular vision device, and the first image and the second image are images of image acquisition areas with different viewing angles; two-dimensional image coordinates of the transmission line are identified based on the multiple pairs of images; based on the two-dimensional image coordinates of the transmission line, it is determined whether the two-dimensional image coordinates of the transmission line coincide with the center of the cross-line laser, and the coincidence comparison distance is obtained; an abnormal probability is assigned according to the coincidence comparison distance to generate the first wind deviation abnormality probability.

[0040] Specifically, the wind-biased dancing image set contains multiple pairs of images, each pair of images is collected by two cameras in the binocular vision device. Among them, the image collected by the first camera is the first image, and the image collected by the second camera is the second image. The first image and the second image have different viewing angles, but the collected areas are the same. The two cameras capture the same transmission line area from different angles. For example, the first camera is located on the left and the second camera is located on the right. Through dual-angle collection, more comprehensive stereo information can be obtained.

[0041] Next, the two-dimensional image coordinates of the transmission line are identified through multiple pairs of images. The two-dimensional image coordinates refer to the position of the transmission line on the image plane, for example, the X and Y coordinates of the transmission line, for subsequent analysis.

[0042] Then, based on the 2D image coordinates of the transmission line, determine whether the 2D image coordinates coincide with the center position of the cross-line laser. Coincidence means that the position of the transmission line is completely consistent with the preset laser center point. If not, the coincidence comparison distance will be calculated to indicate the degree of deviation between the line position and the laser center. If coincidence occurs, the distance is 0, and if deviation occurs, there is a corresponding value.

[0043] Based on the overlap comparison distance, the abnormal probability is assigned. If the deviation distance is large, a higher abnormal probability is assigned, while when the distance is small, the abnormal probability is low, which is then used to predict the degree of abnormality of wind deviation and dancing of transmission lines.

[0044] Multiple pairs of images are collected through binocular vision equipment, and the coordinates of the transmission line are identified in the image. They are then compared with the center of the cross-line laser, the overlap comparison distance is calculated, and finally the first abnormal probability of wind deviation dancing is generated based on the abnormal probability assigned by the distance, which can better monitor the wind deviation behavior of the transmission line.

[0045] Furthermore, the present application also includes: Establishing an extreme value assignment distance threshold constraint; assigning an abnormal probability to the overlap comparison distance according to the constraint that the overlap comparison distance is proportional to the first wind deviation abnormal probability and the extreme value assignment distance threshold constraint, and generating the first wind deviation abnormal probability.

[0046] Specifically, a limit assignment distance threshold constraint is established. The limit assignment distance threshold is the maximum allowable value of the overlap comparison distance. The distance exceeding the limit assignment distance threshold is considered abnormal, and its abnormal probability is directly set to 100%. For example, if the set limit assignment distance threshold is 5 mm, when the deviation of the transmission line exceeds 5 mm, the situation is directly assigned a 100% abnormal probability, indicating severe wind yaw.

[0047] Next, according to the constraint that the overlap comparison distance is proportional to the probability of the first wind deviation anomaly, the probability of anomaly is assigned to the overlap comparison distance. As the overlap comparison distance increases, the probability of wind deviation anomaly will also increase accordingly. For example, if the distance is 2 mm, the probability of anomaly is assigned to 10%; if the distance is 4 mm, the probability of anomaly increases to 80%.

[0048] Then, combined with the limit assignment distance threshold constraint, if the offset distance is greater than the set threshold (for example, 5 mm), the situation is directly assigned a 100% abnormal probability, ensuring that when the wind deviation and swaying of the transmission line reaches a serious level, an alarm is issued in time and intervention is carried out.

[0049] By establishing an extreme value assignment distance threshold, the value is assigned according to the proportional relationship between the size of the overlap comparison distance and the probability of wind deviation anomaly. Combined with the constraint of the threshold, it is ensured that abnormal situations exceeding the extreme distance are directly marked as 100% abnormal probability, effectively identifying the risks of transmission line dancing in different wind deviation conditions.

[0050] Furthermore, the present application also includes: Acquire line design information of the transmission line, wherein the line design information includes line structure and line material; acquire environmental data of a preset area, wherein the environmental data is environmental periodic variation data of the preset area; perform line deformation fitting based on the environmental periodic variation data, the line structure, the line material and the service life of the transmission line; perform wind resistance analysis based on the line deformation fitting result through a resistance fitting model, compensate the first wind deviation abnormality probability based on the resistance analysis result, and generate the second wind deviation abnormality probability.

[0051] Specifically, the line design information of the transmission line is obtained, and the design parameters related to the transmission line are collected, including the structure and material of the transmission line. The line structure refers to the shape, installation method and arrangement of the transmission line, and the line material refers to the material used to construct the transmission line, such as aluminum alloy or copper.

[0052] Next, the preset area is customized by the staff in this field according to the actual situation. The environmental data of the preset area is obtained, and the environmental data is the environmental periodic change data about the area where the line is located, such as the changes in the climate conditions, wind speed, humidity, etc. of the preset area over time.

[0053] Then, the environmental cycle change data is combined with the line structure, line material and service life of the transmission line to perform a fitting analysis of line deformation. Service life refers to the number of years the transmission line has been in service since its construction, such as the weight of the transmission line and the long-term wind force that causes the line sag to increase.

[0054] Subsequently, the line deformation fitting results are analyzed through the resistance fitting model to calculate the wind resistance of the line under wind force. Resistance analysis is to evaluate the wind resistance of transmission lines at different wind speeds. For example, if the wind resistance of a line with increased sag is reduced by 10%, the probability of wind deviation anomaly will also increase. The resistance analysis results are used to compensate for the first wind deviation anomaly probability. For example, if the wind resistance is reduced and the first wind deviation anomaly probability is 10%, after resistance analysis compensation, the second wind deviation anomaly probability may increase to 15%.

[0055] By collecting design information and environmental cycle change data of transmission lines, and combining the service life and material properties of the lines, a fitting analysis of line deformation is performed. The abnormal probability of wind deviation is compensated through the calculation of wind resistance, thus more accurately reflecting the wind deviation risk of the line.

[0056] Furthermore, the present application also includes: The resistance identification sample library is called through the resistance fitting model to screen the matching resistance identification sample with the greatest similarity to the line deformation fitting result; wherein the resistance identification sample library includes multiple groups of resistance identification samples, and any group of resistance identification samples includes a line deformation sample and identification information marked with wind resistance; the resistance analysis result is generated according to the matching resistance identification sample.

[0057] Specifically, the resistance fitting model is used to call the resistance identification sample library to screen out the resistance identification sample with the highest similarity to the line deformation fitting result. The resistance fitting model refers to comparing the calculation model with the pre-stored resistance identification samples according to the specific situation of the line deformation. For example, if the sag deformation amplitude of a line is 1.5 meters, the resistance identification sample with the closest similarity is found in the sample library.

[0058] Next, the resistance identification sample library contains multiple groups of samples, each of which consists of a line deformation sample and the corresponding wind resistance identification information. The line deformation sample describes the deformation of the transmission line under different conditions, and the identification information records the wind resistance of the line under these deformation samples. For example, a resistance identification sample includes a line with a sag increase of 1 meter, and its wind resistance is marked as 90%.

[0059] Then, the resistance analysis results are generated based on the selected matching resistance identification samples. The wind resistance of the current line is inferred by the similarity with the deformation sample. For example, if the matched resistance identification sample shows that the wind resistance is 85% when the sag increases by 1.5 meters, the corresponding resistance analysis results are generated.

[0060] By selecting the resistance identification sample that is closest to the line deformation fitting result from the resistance identification sample library, the resistance analysis result is generated according to the identification information of the sample, providing a more accurate basis for the subsequent windage analysis.

[0061] Furthermore, the present application also includes: The transmission line is scanned multiple times by the cross-line laser, and the binocular vision device is started to perform synchronous image acquisition to generate multiple pairs of scanned images; multiple scanning points are identified based on the multiple pairs of scanned images to generate a wire trajectory point set, wherein the wire trajectory point set has a time sequence identifier; based on the wire trajectory point set, wind deviation angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and elliptical inclination angle data are identified to generate the wind deviation dancing data.

[0062] Specifically, a cross-line laser is a device that projects a precise cross-shaped laser beam, which is used to mark the position of the wire in space. By using a cross-line laser to scan the transmission line multiple times, it is equivalent to drawing lines of light on the wire with a laser pen for subsequent analysis. For example, the laser may scan the wire 10 times in 1 second. At the same time, the binocular vision device is started for synchronous image acquisition. The binocular vision device can capture images from different angles to simulate the visual effect of three-dimensional space. Then, multiple pairs of scanned images can be generated, recording the position of the wire at different scanning times.

[0063] Next, multiple scanning points are identified based on multiple pairs of scanned images. These scanning points are the marks left by the laser on the wire. Through these points, a wire trajectory point set can be generated. The trajectory point set is a collection of the movement path of the wire over a period of time, and each point has its specific location information. These point sets also have a time sequence identifier, which means that each point is marked with the acquisition timestamp. For example, the timestamp of the first point is 0 seconds, the second point is 0.1 seconds, and so on.

[0064] Then, data recognition is performed based on the wire trajectory point set, including wind deflection angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and ellipse inclination angle. Wind deflection angle refers to the deviation angle of the wire relative to the vertical direction, dancing amplitude refers to the maximum swing distance of the wire in the wind, vertical and horizontal dancing amplitudes refer to the components of these swings in the vertical and horizontal directions respectively, and ellipse inclination angle describes the degree of inclination of the ellipse shape of the wire dancing trajectory relative to the horizontal plane. Through these data, wind deflection dancing data are finally generated, which can describe the dynamic behavior of the wire in the wind in detail.

[0065] The transmission line is scanned and imaged by a cross-line laser and binocular vision device to generate a point set of the line trajectory with a time stamp. Then, based on these point sets, the key parameters of the line such as wind deviation angle and dancing amplitude are calculated, and finally the wind deviation dancing data is obtained.

[0066] In summary, the method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision provided by the present application has the following technical effects: The preset cross laser beam propagation path is generated by setting scanning parameters of the cross laser for the transmission lines in the preset area without wind deviation; the preset cross laser beam propagation path is used as the target, the cross laser is controlled to perform laser contour scanning on the transmission lines, and the laser contour is continuously and dynamically monitored based on the binocular vision device to generate a set of wind deviation dancing images; the wind deviation abnormality probability is calculated based on the wind deviation dancing image set to generate a first wind deviation abnormality probability; the wind resistance analysis is performed on the transmission lines in the preset area, and the first wind deviation abnormality probability is compensated with the resistance analysis result to generate a second wind deviation abnormality probability; when the second wind deviation abnormality probability is greater than or equal to the preset abnormality probability, the multivariate comprehensive analysis model is activated to analyze the wind deviation dancing image set to generate wind deviation dancing data; an early warning is issued based on the wind deviation dancing data to achieve the technical goal of real-time and accurate monitoring of wind deviation dancing of transmission lines, and to achieve the technical effect of improving the monitoring coverage, reducing maintenance costs, and enhancing the early warning response speed and accuracy.

[0067] 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.

[0068] 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 method for monitoring windage fluctuations of power transmission lines based on cross-line laser and binocular vision, characterized in that: include: For the transmission lines in the preset area, the scanning parameters of the cross-line laser are set in a state where no wind deflection occurs, and a preset cross laser beam propagation path is generated; Taking the preset cross laser beam propagation path as the target, controlling the cross-line laser to perform laser contour scanning on the power transmission line, and simultaneously performing continuous dynamic monitoring of the laser contour based on a binocular vision device to generate a set of wind deflection dancing images; Calculate the wind deviation abnormality probability based on the wind deviation dancing image set to generate a first wind deviation abnormality probability; Performing a wind resistance analysis on the transmission lines in the preset area, compensating the first wind deviation abnormality probability with the resistance analysis result, and generating a second wind deviation abnormality probability; When the second wind deviation abnormal probability is greater than or equal to a preset abnormal probability, performing wind deviation dancing analysis on the transmission line based on the cross-line laser and the binocular vision device to generate wind deviation dancing data; An early warning is issued based on the wind deviation and dancing data.

2. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 1, characterized in that: The windage dancing data includes windage angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and elliptical tilt angle data.

3. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 1, characterized in that: Also includes: Acquire multiple adjacent lines of the power transmission line in the preset area; Performing an abnormal impact analysis based on the connection structures and distances between the plurality of adjacent lines and the transmission line to generate a plurality of abnormal impact coefficients; Taking the transmission line in the preset area as the center, establishing a neighboring line topology according to the multiple abnormal impact coefficients; A linkage warning is performed according to the adjacent line topology.

4. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 3 is characterized in that: Performing linkage warning according to the adjacent line topology includes: Inferring the wind yaw and galloping data of the plurality of adjacent lines based on the wind yaw and galloping data and the adjacent line topology; The wind deviation and fluctuation data of the plurality of adjacent lines are used to infer the results and make a joint warning.

5. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 1, characterized in that: Calculating the wind deviation abnormality probability based on the wind deviation dancing image set to generate a first wind deviation abnormality probability includes: The wind deviation dancing image set includes a plurality of pairs of images, each pair of images includes a first image captured by a first camera and a second image captured by a second camera in the binocular vision device, and the first image and the second image are images of different viewing angles but image capture areas; Performing two-dimensional image coordinate recognition of transmission line based on the multiple pairs of images; Determine whether the two-dimensional image coordinates of the power transmission line coincide with the center of the cross-line laser based on the two-dimensional image coordinates of the power transmission line, and obtain the coincidence comparison distance; An abnormal probability is assigned according to the overlap comparison distance to generate the first wind deviation abnormal probability.

6. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 5, characterized in that: Assigning an abnormal probability according to the overlap comparison distance to generate the first wind deviation abnormal probability includes: Establish limit assignment distance threshold constraints; According to the constraint that the overlap comparison distance is proportional to the first wind deviation abnormal probability and the limit assignment distance threshold constraint, the overlap comparison distance is assigned an abnormal probability to generate the first wind deviation abnormal probability.

7. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 1, characterized in that: Performing a wind resistance analysis on the transmission lines in the preset area, compensating the first wind deviation abnormality probability with the resistance analysis result, and generating a second wind deviation abnormality probability, including: Acquire line design information of the transmission line, wherein the line design information includes line structure and line material; Acquiring environmental data of a preset area, wherein the environmental data is environmental periodic change data of the preset area; Performing line deformation fitting based on the environmental periodic variation data, the line structure, the line material and the service life of the transmission line; A wind resistance analysis is performed according to the line deformation fitting result through a resistance fitting model, and the first wind deviation abnormality probability is compensated with the resistance analysis result to generate the second wind deviation abnormality probability.

8. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 7, characterized in that: The wind resistance analysis is performed based on the line deformation fitting results through the resistance fitting model, including: Calling a resistance identification sample library through a resistance fitting model to select a matching resistance identification sample with the greatest similarity to the line deformation fitting result; The resistance identification sample library includes multiple groups of resistance identification samples, and any group of resistance identification samples includes a line deformation sample and identification information marked with wind resistance; The resistance analysis result is generated according to the matching resistance identification sample.

9. The method for monitoring windage fluctuation of power transmission lines based on cross-line laser and binocular vision as claimed in claim 5, characterized in that: Performing windage analysis on the transmission line based on the cross-line laser and the binocular vision device to generate windage data includes: Scanning the transmission wire multiple times by the cross-line laser, and simultaneously starting the binocular vision device to perform synchronous image acquisition to generate multiple pairs of scanned images; Identifying a plurality of scanning points based on the plurality of pairs of scanning images to generate a wire trajectory point set, wherein the wire trajectory point set has a time sequence identifier; Based on the wire trajectory point set, the wind deviation angle, dancing amplitude, vertical dancing amplitude, horizontal dancing amplitude and elliptical tilt angle data are identified to generate the wind deviation dancing data.

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