Power transmission line wind deviation galloping monitoring and stereoscopic imaging system based on laser triangulation method

Abstract

The application provides a power transmission line wind deviation galloping monitoring and stereoscopic imaging system based on laser triangulation, and relates to the technical field of laser ranging. The system comprises: a wind deviation galloping mining component for wind deviation galloping partitioning and wind deviation galloping relationship mining; a wind deviation galloping monitoring module configuration component for configuring a wind deviation galloping monitoring module; a laser detection data determination component for determining laser detection data; a stereoscopic imaging module construction component for constructing a stereoscopic imaging module; a stereoscopic wind deviation galloping model determination component for determining a stereoscopic wind deviation galloping model; and a monitoring and early warning component for power transmission line monitoring feedback and wind deviation galloping early warning. The application can solve the technical problems of low power transmission line wind deviation galloping monitoring accuracy and the inability to accurately obtain power transmission line stereoscopic motion information, and achieve the technical effects of obtaining dynamic stereoscopic images of the power transmission line, improving the power transmission line wind deviation galloping monitoring accuracy, and ensuring the accuracy of the wind deviation galloping early warning.

Description

Technical Field

[0001] The present application relates to the field of laser ranging technology, and in particular to a transmission line wind yaw and sway monitoring and stereo imaging system based on laser triangulation. Background Art

[0002] During the operation of power transmission lines, environmental factors can cause them to experience wind-induced fluctuations, particularly under extreme weather conditions such as strong winds, ice, and snow. Wind-induced fluctuations not only pose a threat to the stable operation of transmission lines but can also cause mechanical damage. In severe cases, they can even lead to line disconnections and power outages. Therefore, accurately monitoring and providing early warnings for wind-induced fluctuations in transmission lines is crucial for ensuring the safe operation of power systems. Traditional methods for monitoring wind-induced fluctuations in transmission lines rely primarily on mechanical monitoring equipment or video surveillance equipment mounted on transmission towers. However, these methods have significant shortcomings. Mechanical monitoring equipment is prone to aging and damage after prolonged use, resulting in inaccurate or ineffective monitoring data. While video surveillance equipment can provide visual monitoring data, it is limited by weather conditions and nighttime light, resulting in poor monitoring effectiveness. Furthermore, these methods typically only capture two-dimensional motion information of the transmission line, making it difficult to fully and accurately capture the three-dimensional motion characteristics of the transmission line, limiting in-depth analysis of wind-induced fluctuations. Summary of the Invention

[0003] The purpose of this application is to provide a transmission line wind yaw and sway monitoring and stereo imaging system based on laser triangulation to solve the technical problems of low accuracy in transmission line wind yaw and sway monitoring and inability to accurately obtain three-dimensional motion information of transmission lines.

[0004] In view of the above problems, the present application provides a transmission line wind yaw and sway monitoring and stereo imaging system based on laser triangulation.

[0005] The present application provides a transmission line wind yaw dance monitoring and stereo imaging system based on laser triangulation, the system comprising: a wind yaw dance mining component for interacting with the historical wind yaw dance records of the target transmission line, performing wind yaw dance partitioning and wind yaw dance relationship mining, the wind yaw dance relationship comprising wind yaw dance characteristics - self-excited vibration elements, the self-excited vibration elements at least comprising eccentric icing, wind excitation, line structure and parameters; a wind yaw dance monitoring module configuration component for determining a baseline monitoring strategy and configuring a wind yaw dance monitoring module based on the wind yaw dance partitioning and the wind yaw dance relationship; a laser detection data determination component for controlling a laser transmitter to the target transmission line based on the wind yaw dance monitoring module. The transmission lines are laser detected and imaged with light spots based on photoelectric detectors to determine the laser detection data; a stereo imaging module construction component is used to perform data-driven training based on laser triangulation to construct a stereo imaging module, wherein the stereo imaging module includes a four-dimensional analysis unit and a stereo reconstruction unit; a stereo wind yaw and sway model determination component is used for the stereo imaging module to receive the laser detection data, perform wind yaw and sway analysis and wind yaw and sway modal reconstruction of the transmission line based on the change of light spot position, and determine a stereo wind yaw and sway model, wherein the stereo wind yaw and sway model is a dynamic model; a monitoring and early warning component is used to perform transmission line monitoring feedback and wind yaw and sway warning based on the stereo wind yaw and sway model.

[0006] The technical solution provided in this application has at least the following technical effects or advantages:

[0007] The aforementioned laser triangulation-based transmission line wind-induced yaw motion monitoring and stereoscopic imaging system first uses the yaw motion mining component to analyze historical transmission line wind-induced yaw motion records, delineate wind-induced yaw motion areas, and identify factors associated with wind-induced yaw motion, such as eccentric icing, wind excitation, and self-excited vibrations from the line structure. Based on these analysis results, the yaw motion monitoring module configuration component develops a monitoring strategy and configures the corresponding monitoring modules. During actual monitoring, the laser detection data determination component controls a laser transmitter to scan the target transmission line and uses a photodetector to capture the position of the reflected laser spot, acquiring accurate detection data. This data is then transmitted to the stereoscopic imaging module construction component for data processing and model training using laser triangulation to generate a three-dimensional image of the transmission line. Subsequently, the stereoscopic wind-induced yaw motion model determination component uses this three-dimensional data to analyze the transmission line's wind-induced yaw motion and reconstruct a dynamic wind-induced yaw motion model. Finally, the monitoring and early warning component provides real-time feedback on the transmission line's status based on the dynamic model and issues wind-induced yaw motion warnings to ensure safe operation of the power system.

[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, which can be implemented in accordance with the contents of the description, and 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 listed 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 this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without creative work.

[0010] Figure 1 This is a schematic diagram of the structure of the transmission line wind yaw and yaw monitoring and stereo imaging system based on laser triangulation in this application;

[0011] Figure 2 This is a schematic diagram of the process of dividing wind yaw zoning of the transmission line wind yaw zoning monitoring and stereo imaging system based on laser triangulation in this application.

[0012] Description of reference numerals:

[0013] Wind yaw and sway mining component 1, wind yaw and sway monitoring module configuration component 2, laser detection data determination component 3, stereo imaging module construction component 4, stereo wind yaw and sway model determination component 5, monitoring and early warning component 6. DETAILED DESCRIPTION

[0014] This application solves the technical problems of low accuracy in transmission line wind yaw and sway monitoring and inability to accurately obtain three-dimensional motion information of transmission lines by providing a transmission line wind yaw and sway monitoring and stereoscopic imaging system based on laser triangulation. It achieves the technical effect of improving the accuracy of transmission line wind yaw and sway monitoring and ensuring the accuracy of wind yaw and sway warning by obtaining dynamic three-dimensional images of transmission lines.

[0015] Below, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited to the example embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should also be noted that, for the convenience of description, only the parts related to this application, rather than all of them, are shown in the accompanying drawings.

[0016] For examples, please see the attached Figure 1 This application provides a transmission line wind yaw and yaw monitoring and stereoscopic imaging system based on laser triangulation, which specifically includes the following components:

[0017] The wind yaw dance mining component 1 is used to interact with the historical wind yaw dance records of the target transmission line, perform wind yaw dance zoning and wind yaw dance relationship mining. The wind yaw dance relationship includes wind yaw dance characteristics-self-excited vibration elements. The self-excited vibration elements at least include eccentric icing, wind excitation, line structure and parameters.

[0018] Specifically, in the wind yaw fluctuation mining component 1, the system terminal collects wind yaw fluctuation data of the target transmission line at different periods and under different environmental conditions from the historical database. These data include information such as the displacement, vibration frequency, and amplitude of the transmission line. The collected historical wind yaw fluctuation records are then preprocessed to remove noise and outliers to ensure the accuracy and reliability of the data. This step involves processes such as data cleaning and smoothing. Subsequently, based on the preprocessed historical wind yaw fluctuation records, the transmission line is divided into wind yaw fluctuation zones, that is, the transmission line is divided into multiple wind yaw fluctuation zones based on the similarity of wind yaw fluctuation characteristics through a clustering algorithm. Each zone represents an area with similar wind yaw fluctuation characteristics. Afterwards, based on the divided wind yaw fluctuation zones, the key factors affecting the wind yaw fluctuation are mined, that is, the wind yaw fluctuation characteristics within each zone are compared to understand the characteristic differences of each zone, and then the self-excited vibration elements of each zone are normalized using the maximum-minimum method, and the one with the largest normalized result is taken as the main self-excited vibration element of the zone. Then, the wind-induced yaw dance characteristics of the partitions belonging to the same self-excited vibration element are summarized to form a wind-induced yaw dance relationship. This wind-induced yaw dance relationship consists of wind-induced yaw dance characteristics and self-excited vibration elements. Yaw dance characteristics include yaw dance amplitude and frequency, while self-excited vibration elements encompass internal and external conditions that trigger wind-induced yaw dance, such as eccentric icing, wind excitation, line structure, and parameter determination. Eccentric icing refers to ice formation on the surface of a transmission line due to climatic conditions (such as rain and snow). This ice is not evenly distributed across the line, but rather concentrated on one side or in certain specific areas, resulting in uneven weight distribution on the transmission line. Wind excitation refers to the external forces exerted on the transmission line by wind. Factors such as wind speed, direction, and stability exert certain forces on the transmission line, which can cause the line to vibrate or oscillate. Line structure and parameters include the transmission line's geometry, material properties, installation method, and related physical parameters such as tension, bending stiffness, and suspension height. These structures and parameters determine the mechanical properties and response capabilities of the transmission line.

[0019] Further, if Figure 2As shown, the present application provides the wind deviation dancing zoning division, including:

[0020] Traverse the historical wind yaw dance records, perform clustering processing based on preset wind yaw dance differences, and determine multiple cluster clusters; traverse the multiple cluster clusters, perform position positioning and inter-cluster segmentation on the target transmission line, and determine a first wind yaw dance partition, wherein the first wind yaw dance partition has partition-similar wind yaw dance characteristics; traverse the first wind yaw dance partition, perform intra-partition clustering based on self-excited vibration elements, and determine a second wind yaw dance partition; merge the first wind yaw dance partition and the second wind yaw dance partition to determine the wind yaw dance partition.

[0021] In a preferred embodiment, the system terminal presets a windage fluctuation difference based on historical experience and expert advice. This difference is used to measure the similarity between different windage fluctuation records. Each data point in the historical windage fluctuation record is treated as a separate cluster, and the distance between two data points is calculated using Euclidean distance. A distance matrix is ​​then constructed based on the calculated distances and the corresponding data points, with each element in the matrix representing the distance between the two data points. Subsequently, the average distance between all pairs of points between the two clusters is calculated as the inter-cluster distance. Each time the distance between two clusters is calculated, the calculated inter-cluster distance is compared with the preset windage fluctuation difference. If the inter-cluster distance is less than the preset windage fluctuation difference, the two clusters are merged. This process is repeated until the distances between all clusters are greater than or equal to the preset windage fluctuation difference. Based on the clustering process, the system terminal draws a dendrogram, with each layer of the dendrogram representing an aggregation operation. By analyzing the structure of the dendrogram and selecting a cut point in the dendrogram based on the preset windage fluctuation difference, the data is divided into multiple clusters. Each cluster represents an area with similar wind yaw fluctuation patterns. The wind yaw fluctuation characteristics within these areas are similar, but influenced by different self-excited vibration factors. The wind yaw fluctuation records for each cluster are then spatially located to identify their specific locations within the transmission line. The clusters are then spatially divided to define the first wind yaw fluctuation zone. This zone encompasses areas with similar wind yaw fluctuation characteristics, but within these areas, the influence of different self-excited vibration factors varies. Within the first wind yaw fluctuation zone, the same clustering process is repeated based on the different self-excited vibration factors. This step further separates areas with similar wind yaw fluctuation characteristics but influenced by different factors, defining the second wind yaw fluctuation zone. Finally, the results from the first and second wind yaw fluctuation zones are combined to determine the final wind yaw fluctuation zone. These wind yaw fluctuation zones take into account both the similarity of wind yaw fluctuation characteristics and the differences in the influence of different self-excited vibration factors, providing strong support for subsequent monitoring and early warning work.

[0022] The windage and dancing monitoring module configuration component 2 is used to determine a benchmark monitoring strategy and configure a windage and dancing monitoring module based on the windage and dancing partitions and the windage and dancing relationship.

[0023] Specifically, in the wind yaw and dancing monitoring module configuration component 2, the system terminal traverses the wind yaw and dancing partitions. In each traversal, the most critical wind yaw and dancing influencing factors in each partition are identified based on the wind yaw and dancing relationship, and the partition wind yaw and dancing characteristics of the partition are obtained based on the determined wind yaw and dancing influencing factors. Subsequently, the initially configured automated benchmark monitoring strategy is determined based on the obtained partition wind yaw and dancing characteristics. Taking eccentric icing as an example, the wind yaw and dancing characteristics corresponding to eccentric icing, such as the conductor cross-section, ice thickness, etc., are compared with the corresponding thresholds to determine the current severity of the icing. When the wind speed, ice thickness, etc. are greater than the corresponding thresholds, a higher monitoring frequency can be set and more ice thickness monitoring equipment can be activated. Afterwards, the configured benchmark monitoring strategy is combined with the element monitoring branch to construct a wind yaw and dancing monitoring module to achieve effective monitoring and early warning of wind yaw and dancing of transmission lines.

[0024] Furthermore, the present application provides the windage and dance monitoring module, including:

[0025] Traverse the wind yaw and dance partitions, determine the wind yaw and dance characteristics of each partition, and configure the automated benchmark monitoring strategy; based on the benchmark monitoring strategy, configure the automatic monitoring trigger unit; intervene in the element monitoring branch, cooperate with the automatic monitoring trigger unit, and determine the wind yaw and dance monitoring module.

[0026] In a preferred embodiment, the system terminal traverses the acquired wind yaw fluctuation zones to obtain historical wind yaw fluctuation data for each zone, including time nodes (e.g., seasonality, diurnal variations), time periods (e.g., peak wind speed periods), topographic distribution (e.g., mountainous, plain, coastal), historical wind yaw fluctuation records, conductor cross-sections, and split conditions. The time nodes can be used to identify key times of the year for each zone, such as severe winter icing or high summer wind speeds. The time periods can be used to identify key times of the day for each zone, such as nighttime wind speeds or daytime sunlight exposure that causes conductor temperatures to rise. The topographic distribution can be used to identify topographic characteristics within the zone, e.g., mountainous areas may experience increased wind speeds, while plain areas may have relatively uniform wind speeds. Historical wind yaw fluctuation records can be used to identify the wind yaw fluctuation frequency and amplitude for each zone under specific conditions. For example, certain areas may experience more severe wind yaw fluctuations under certain wind directions. The conductor cross-section can be used to identify the wind yaw fluctuation characteristics of conductors of different cross-sections under wind force. The split conditions can be used to analyze the conductor split structure and determine the wind yaw fluctuation characteristics of the split conductors under specific wind speeds. Subsequently, based on the self-excited vibration elements corresponding to each wind yaw dance zone, the wind yaw dance characteristics of each zone are extracted to obtain the key wind yaw dance features associated with these self-excited vibration elements. The initial thresholds and monitoring frequencies for automated monitoring are then set for each key wind yaw dance feature in each zone, and an automated baseline monitoring strategy is configured based on these features. For example, in winter or at night, a lower trigger threshold is set for areas with severe icing or high wind speeds. During periods of high wind yaw dance or critical time points, a higher frequency of monitoring is configured. Next, an automatic monitoring trigger unit is configured for each zone based on the baseline monitoring strategy. For example, when the wind speed reaches a certain threshold or the temperature changes by a certain level, wind yaw dance monitoring is automatically triggered. The trigger unit's response time is then configured, tailored to the specific conditions of the zone, such as setting a shorter response time for areas with rapidly changing wind speeds. Finally, a factor monitoring branch is introduced to monitor the self-excited vibration elements. The system terminal integrates the element monitoring branch with the automatic monitoring trigger unit to define the wind speed fluctuation monitoring module, ensuring that the element monitoring branch and the automatic monitoring trigger unit work together. For example, if increasing ice thickness is detected, the frequency of wind speed monitoring will be automatically increased. This ensures the system's flexible response under different conditions to cope with complex wind speed fluctuations of the transmission line.

[0027] The laser detection data determination component 3 is used to control the laser transmitter to perform laser detection on the target transmission line and perform light spot imaging based on a photoelectric detector based on the windage and sway monitoring module to determine the laser detection data.

[0028] Specifically, in the laser detection data determination component 3, when the windage fluctuation monitoring module detects windage fluctuations in the target transmission line, the laser transmitter is activated and laser detection is automatically initiated. The laser transmitter then emits a laser beam that strikes the target transmission line at a specific angle. The laser beam reflects off the surface of the target transmission line, forming a reflected light beam. When the laser beam strikes the target transmission line, the reflected light forms a continuous light spot line on the photodetector. As the transmission line fluctuates, the position and shape of the light spot line change. The photodetector continuously monitors the position and shape changes of the reflected light spot line and collects real-time imaging data of the reflected light spot, including its position and shape change data. The light spot position and shape change data collected by the photodetector are then transmitted to the system terminal, generating laser detection data for the target transmission line. This laser detection data includes the light spot line position, windage fluctuation amplitude, and windage fluctuation frequency. This data provides a scientific basis for windage fluctuation monitoring and early warning of transmission line fluctuations.

[0029] Furthermore, the present application provides a method for controlling a laser transmitter to perform laser detection on the target transmission line based on the windage and vibration monitoring module, including:

[0030] Based on the self-excited vibration element, element monitoring data is determined; in combination with the wind yaw and dance relationship, wind yaw and dance monitoring judgment is performed on the element monitoring data to generate a first wind yaw and dance monitoring instruction, wherein the first wind yaw and dance monitoring instruction is marked with a monitoring partition; based on the automatic triggering of the monitoring node, monitoring verification is performed in combination with the element monitoring data to generate a second wind yaw and dance monitoring instruction.

[0031] In one optional embodiment, within each wind yaw and yaw zone, the system terminal continuously collects data related to self-excited vibration factors associated with wind yaw and yaw through sensors and monitoring equipment, generating factor monitoring data. This factor monitoring data includes data related to self-excited vibration factors such as wind speed, temperature, and ice thickness. The collected factor monitoring data is then analyzed in real time to determine whether these factors are in an abnormal state. For example, it analyzes whether the wind speed exceeds a set threshold or whether the ice thickness has increased significantly. The current factor monitoring data is then compared with the determined wind yaw and yaw relationship to determine whether the current environmental conditions may cause abnormal wind yaw and yaw of the transmission line. If the factor data analysis indicates a risk of wind yaw and yaw, the system terminal generates a first wind yaw and yaw monitoring instruction. This instruction contains detailed parameters for the monitoring task and clearly identifies the specific zone to be monitored. When the preset time node (i.e., the automatic monitoring node) is reached, the system terminal automatically triggers the monitoring task and determines whether monitoring is required based on the configured automated monitoring strategy. At this point, the system terminal performs a verification based on the currently collected factor data. For example, if the preset monitoring time has passed but the wind speed remains within the corresponding threshold and the ice thickness is normal, the system terminal will determine that the current risk is low and monitoring is not required. If the verification results indicate that monitoring is necessary, that is, if certain data exceeds the corresponding threshold, the system terminal will generate a second wind yaw and yaw monitoring command, which activates the laser transmitter to initiate the laser detection mission.

[0032] Furthermore, the present application provides a method for controlling a laser transmitter to perform laser detection on the target transmission line based on the windage and vibration monitoring module, including:

[0033] The target transmission line is traversed, and a detection distance is determined with a measuring point as a baseline; a linear constraint relationship is determined based on the detection distance, the spot size, and the resolution; and system detection parameters are adjusted based on the linear constraint relationship.

[0034] In a preferred embodiment, the system terminal first traverses the target transmission line and determines the locations of each monitoring point to be monitored. These monitoring points are located at key nodes or areas prone to wind yaw and sway. For each monitoring point, the straight-line distance from the laser emitter to the monitoring point is calculated and used as the detection distance. This distance is the distance the light spot travels from the laser emitter to the monitoring point and reflects back to the photodetector. The detection distance of each monitoring point is recorded to facilitate subsequent parameter adjustments. Subsequently, a linear constraint relationship between spot size and resolution is determined based on the detection distance. Spot size varies with detection distance. The larger the detection distance, the larger the spot size due to the divergence of the laser beam. The system terminal multiplies each detection distance by the divergence angle of the laser emitter to calculate the spot diameter at each monitoring point, which reflects the spot size at each monitoring point. To ensure monitoring accuracy, the system terminal sets the spot resolution at each monitoring point based on the spot size and the system's detection capabilities. Resolution determines whether subtle changes in wind yaw and sway can be detected. A higher detection distance requires a higher resolution to maintain monitoring accuracy. Afterwards, a linear constraint relationship is established between the spot size and resolution through a formula or function. This relationship is used to ensure that the spot size and resolution match at different detection distances, thereby ensuring the detection accuracy of the system. For example, it is necessary to ensure that the ratio of the spot diameter to the resolution remains within a certain range at a certain detection distance to prevent the spot from being too large and causing inaccurate detection. Then, the system terminal automatically adjusts the relevant parameters of the laser transmitter, such as the divergence angle, laser power, and emission frequency, based on the linear constraint relationship of each measuring point, to ensure that the spot size and resolution meet the monitoring requirements at each detection distance. For the photoelectric detector, its receiving parameters, such as photosensitivity and sampling rate, are also adjusted to ensure that the reflected spot information can be accurately captured.

[0035] The stereo imaging module construction component 4 is used to perform data-driven training based on the laser triangulation method to construct a stereo imaging module, wherein the stereo imaging module includes a four-dimensional analysis unit and a stereo reconstruction unit.

[0036] Specifically, in component 4 of the stereoscopic imaging module, the system terminal uses laser triangulation to form a triangle using a laser emitter, a target power line, and a photodetector. By measuring the angle and distance changes between the laser beam and the detector, the system terminal calculates the target power line's three-dimensional position, obtaining its precise spatial coordinates. To more conveniently restore the target power line in three dimensions, the system terminal collects wind-induced fluctuation data under various conditions (such as wind speed and temperature variations), generating a large amount of light spot position data and its corresponding timestamps. This data covers a wide range of possible wind-induced fluctuation scenarios, ensuring the module can handle a variety of complex situations. Key features are then extracted from this data, including light spot position, timestamp, and the relative position of the laser emitter and detector. These features are then preliminarily analyzed to construct training and validation data, laying the foundation for subsequent module training. Subsequently, a four-dimensional analysis unit is constructed, capable of analyzing the three spatial dimensions (X, Y, and Z) and the temporal dimension (T). This 4D analysis unit is trained using machine learning algorithms, such as LSTM networks, and can capture and predict the temporal wind-induced fluctuations of transmission lines. The training process is similar to existing training methods, including forward propagation, loss calculation, gradient calculation, and backpropagation. Through repeated training and cross-validation, the parameters of the 4D analysis unit are optimized to ensure that it accurately describes and predicts the dynamic wind-induced fluctuations of transmission lines and generates position predictions for transmission lines at future points in time. After constructing the 4D analysis unit, a stereo reconstruction unit is designed based on the data output by the 4D analysis unit. This unit reconstructs 2D spot data into 3D images, similar to the construction of the 4D analysis unit described above. During the stereo reconstruction process, the system terminal uses 3D geometric reconstruction techniques, such as multi-view geometry (MVG) and structure-from-motion (SfM), to convert spot position data at different time points into 3D point cloud data. By calculating the changes in the spot position at different viewpoints and time points, a preliminary 3D structure is generated. The point cloud data at different time points is then integrated to generate a preliminary 3D image of the transmission line. After forward propagation, loss calculation, gradient calculation, and backpropagation are performed, enabling the stereo reconstruction unit to reconstruct the windage fluctuation data at all time points into a complete 3D image, ensuring that the reconstructed 3D image reflects the actual windage fluctuation state. The 4D analysis unit is then integrated with the stereo reconstruction unit to form a complete stereo imaging module. The stereo imaging module receives input data from the laser triangulation system and, through 4D analysis and 3D reconstruction, generates real-time stereo images of the transmission line, enabling real-time stereo monitoring of windage fluctuation conditions.

[0037] The stereo wind yaw dance model determination component 5 is used for the stereo imaging module to receive the laser detection data, perform wind yaw dance analysis and wind yaw dance modal reconstruction of the transmission line based on the change of the light spot position, and determine the stereo wind yaw dance model, wherein the stereo wind yaw dance model is a dynamic model.

[0038] Specifically, in the stereoscopic wind-induced yaw motion model determination component 5, the stereoscopic imaging module receives real-time laser detection data of the target transmission line. This data includes the two-dimensional position coordinates of the light spot on the photodetector, as well as geometric information related to the laser emitter. These laser detection data are then analyzed by the internal four-dimensional analysis unit and stereoscopic reconstruction unit to generate a preliminary three-dimensional image of the transmission line. Subsequently, the wind-induced yaw motion modal elements of the target transmission line are extracted from the preliminary three-dimensional image, and the wind-induced yaw motion modal elements at the measuring point are determined based on these wind-induced yaw motion modal elements. The wind-induced yaw motion modal elements are then converted to the same spatial perspective and reconstructed through splicing to form a stereoscopic wind-induced yaw motion model. This model not only displays the three-dimensional shape of the transmission line, but also reflects the temporal evolution of the wind-induced yaw motion, helping to achieve real-time monitoring and risk warning of the target transmission line.

[0039] Furthermore, the present application provides the method for determining the three-dimensional wind yaw dance model, including:

[0040] Determine the wind yaw dance modal elements, where the wind yaw dance modal elements of each half-wave wind yaw dance mode include the average position limited by the neighborhood nodes, the wind yaw dance upper limit, and the wind yaw dance lower limit; determine the wind yaw dance mode of the measuring point based on the wind yaw dance modal elements; perform the same-space perspective conversion and splicing reconstruction on the wind yaw dance mode of the measuring point to determine the three-dimensional wind yaw dance model.

[0041] In a preferred embodiment, after obtaining a preliminary three-dimensional image, the system terminal analyzes the preliminary three-dimensional image to determine the neighborhood nodes for each half-wave wind yaw fluctuation and calculates the average position of these nodes. This average position represents the overall position offset of the transmission line within a half-wave. Neighborhood nodes refer to multiple adjacent and interconnected measurement points at the same time, where the wind yaw fluctuation amplitude and phase changes are similar. The upper and lower limits of the wind yaw fluctuation mode for each half-wave are then determined by detecting the extreme value positions at different time points in the preliminary three-dimensional image. The upper and lower limits of the wind yaw fluctuation represent the highest and lowest positions reached by the transmission line during the wind yaw fluctuation, respectively. These upper and lower limit data can help analyze the wind yaw fluctuation amplitude and wind yaw fluctuation stability of the transmission line. Subsequently, the data of each measurement point is compared with the wind yaw fluctuation modal elements of the neighborhood nodes to determine the wind yaw fluctuation mode of the measurement point. The wind yaw fluctuation mode of the measurement point includes the average position of the measurement point, the wind yaw fluctuation amplitude, and the upper and lower limits of the wind yaw fluctuation relative to the neighborhood nodes. The windage fluctuation mode at each measurement point is then calibrated to ensure it is consistent with the baseline spatial perspective of the laser emitter and photodetector. This calibration process involves converting the data at the measurement point into a unified coordinate system, enabling direct comparison and splicing with the modes of other measurement points. Next, the windage fluctuation modes at each measurement point undergo a spatial perspective conversion, using the laser and detection equipment as a reference. This conversion involves mapping the windage fluctuation data at each measurement point into the perspective coordinate system of the laser and detection equipment, ensuring that the windage fluctuation modes at all measurement points are correctly displayed from the same perspective. After completing the spatial perspective conversion, the windage fluctuation modes of all measurement points are spliced ​​and reconstructed. The splicing process involves spatially linking the windage fluctuation modes from different measurement points to form a complete transmission line windage fluctuation image. This is then combined with time to reconstruct a three-dimensional windage fluctuation model of the target transmission line throughout its entire windage fluctuation process. This three-dimensional windage fluctuation model displays the windage fluctuation behavior of the target transmission line in three dimensions and reflects the dynamic changes during the windage fluctuation process.

[0042] Furthermore, the present application provides a method for converting and reconstructing the windage vibration mode of the measurement point into the same spatial perspective, including:

[0043] Determine the windage dance mode of the measuring point, wherein the windage dance mode of the measuring point is located in the measuring point space; perform spatial perspective conversion on the windage dance mode of the measuring point based on the world coordinate system to determine the converted windage dance mode; traverse the converted windage dance mode, perform splicing and reconstruction based on the relative spatial position, and introduce a time axis to determine the three-dimensional windage dance model.

[0044] In an optional embodiment, the system terminal compares the data of each measuring point with the wind yaw dance modal elements of the neighboring nodes to determine the measuring point wind yaw dance mode of the measuring point. This measuring point wind yaw dance mode includes parameters such as the average position of the measuring point, the upper and lower limits of the wind yaw dance, etc., all of which are located in the measuring point space. The measuring point space refers to a local coordinate system based on each measuring point. In this coordinate system, the measuring point wind yaw dance mode represents the typical behavioral characteristics of the measuring point during the wind yaw dance of the transmission line. Subsequently, a world coordinate system is defined. The world coordinate system is a global, unified coordinate system used to represent the spatial position of the entire monitoring area. Here, the world coordinate system defines the absolute reference frame for monitoring the entire target transmission line. Afterwards, the wind yaw dance mode of each measuring point is converted from the measuring point space where it is located to the world coordinate system. This step is to unify the data in the local coordinate system into a global coordinate system for overall analysis and splicing reconstruction. Perspective conversion involves mapping the coordinates and windage motion modal parameters in the measurement point space to the world coordinate system through mathematical transformations such as rotation and translation, ensuring that the data from all measurement points are correctly aligned within the same reference system. After spatial perspective conversion, the windage motion modal data for each measurement point is converted to its relative position in the world coordinate system, forming a converted windage motion modal model. This converted windage motion modal model serves as the basis for subsequent splicing and reconstruction. The converted windage motion modal data for all measurement points is then iterated over, and their relative spatial positions in the world coordinate system are analyzed one by one. By calculating the relative position of each measurement point in the world coordinate system, the specific spatial distribution of these measurement points is determined, providing a basis for subsequent splicing and reconstruction. Based on the relative spatial positions of each measurement point, their windage motion modal data are then spliced ​​together to generate a complete transmission line windage motion image. During the splicing process, geometric interpolation is used to smoothly connect the windage motion modes between measurement points, ensuring that the generated windage motion model accurately reflects the overall windage motion behavior of the transmission line. During the reconstruction process, the time axis is introduced into the wind yaw dance model to form a dynamic model that changes over time. By superimposing the spliced ​​wind yaw dance modes at different time points, a time series is generated, showing the wind yaw dance changes of the target transmission line throughout the monitoring period. The introduction of the time axis enables the three-dimensional wind yaw dance model to not only display the wind yaw dance forms in three-dimensional space, but also reflect the evolution of these forms over time, thus forming a four-dimensional space-time model. After spatial perspective conversion and splicing reconstruction, combined with time axis information, the final three-dimensional wind yaw dance model can fully describe the dynamic wind yaw dance process of the transmission line in three-dimensional space, thereby providing strong support for the safe operation of the power system.

[0045] The monitoring and early warning component 6 is used to perform transmission line monitoring feedback and wind yaw and early warning based on the three-dimensional wind yaw and dancing model.

[0046] Specifically, in the monitoring and early warning component 6, the three-dimensional wind yaw dance model provides key support for the monitoring and early warning of transmission lines by accurately reflecting the dynamic wind yaw dance of the transmission line in three-dimensional space. Based on this three-dimensional wind yaw dance model, the system terminal can monitor the wind yaw dance status of the transmission line in real time and analyze whether the target transmission line is within a safe range based on changes in the wind yaw dance amplitude and frequency. If the three-dimensional wind yaw dance model detects that the wind yaw dance exceeds the safety threshold, it will promptly issue an early warning signal to remind relevant personnel to take measures to prevent damage or breakage of the transmission line caused by wind yaw dance. This real-time monitoring and early warning mechanism can effectively ensure the stable operation of the transmission line and avoid potential power accidents.

[0047] In summary, the laser triangulation-based transmission line windage yaw and yaw monitoring and stereoscopic imaging system provided in this application has the following technical effects:

[0048] This application realizes accurate monitoring and early warning of wind yaw dance of transmission lines through the collaborative work of multiple components. First, the historical wind yaw dance records of the target transmission line are analyzed through the wind yaw dance mining component 1, and the wind yaw dance is divided into zones, and the wind yaw dance relationship is mined, including wind yaw dance characteristics and self-excited vibration elements, such as eccentric icing, wind excitation, line structure and parameters, etc. Based on these zones and relationships, the wind yaw dance monitoring module configuration component 2 determines the baseline monitoring strategy and configures the corresponding wind yaw dance monitoring module. In the laser detection data determination component 3, according to the configuration of the wind yaw dance monitoring module, the laser transmitter is controlled to perform laser detection on the target transmission line, and the spot imaging data is collected by the photoelectric detector to determine the accurate laser detection data. The stereo imaging module is based on the laser triangulation method and constructs a stereo imaging module through data-driven training. It includes a four-dimensional analysis unit and a stereo reconstruction unit, which are used to receive laser detection data, perform wind yaw dance analysis and modal reconstruction of the transmission line, and finally determine a dynamic three-dimensional wind yaw dance model. The system also includes a monitoring and early warning component 6, which provides real-time transmission line monitoring feedback and early warning of wind yaw fluctuations based on a three-dimensional wind yaw fluctuation model. Wind yaw fluctuation zones are determined by traversing historical wind yaw fluctuation records and clustering them based on preset wind yaw fluctuation differences. Subsequently, an automated monitoring strategy is configured based on the zone characteristics, and element monitoring branches are introduced for collaborative monitoring. Before laser detection, element monitoring data is determined based on self-excited vibration elements, combined with wind yaw fluctuation relationships for judgment, and verified based on automatically triggered monitoring nodes to ensure accurate monitoring execution. Furthermore, after determining the detection distance and the linear constraint relationship based on the spot size and resolution, corresponding detection parameters are adjusted. Finally, a three-dimensional wind yaw fluctuation model is determined through same-space perspective conversion and splicing reconstruction, ensuring that the wind yaw fluctuation behavior of the transmission line is fully reflected. These technical effects collectively address the technical issues of low transmission line wind yaw fluctuation monitoring accuracy and the inability to accurately obtain three-dimensional transmission line motion information. By acquiring dynamic three-dimensional images of the transmission line, the accuracy of wind yaw fluctuation monitoring and wind yaw fluctuation early warnings are improved.

[0049] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one 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 is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

[0050] Obviously, those skilled in the art may 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 fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A transmission line wind-induced yaw and yaw monitoring and stereoscopic imaging system based on laser triangulation, characterized by: The system comprises: A wind yaw fluctuation mining component is used to interact with historical wind yaw fluctuation records of target transmission lines, perform wind yaw fluctuation zoning and wind yaw fluctuation relationship mining. The wind yaw fluctuation relationship includes wind yaw fluctuation characteristics and self-excited vibration elements. The self-excited vibration elements include at least eccentric icing, wind excitation, line structure and parameters. a windage dance monitoring module configuration component, configured to determine a baseline monitoring strategy and configure a windage dance monitoring module based on the windage dance partitions and the windage dance relationships; a laser detection data determination component for controlling a laser transmitter to perform laser detection on the target transmission line and light spot imaging based on a photoelectric detector based on the windage vibration monitoring module to determine laser detection data; A stereo imaging module construction component, configured to perform data-driven training based on laser triangulation to construct a stereo imaging module, wherein the stereo imaging module comprises a four-dimensional analysis unit and a stereo reconstruction unit; a three-dimensional wind yaw motion model determination component, configured for the three-dimensional imaging module to receive the laser detection data, perform wind yaw motion analysis and wind yaw motion modal reconstruction of the transmission line based on changes in the light spot position, and determine a three-dimensional wind yaw motion model, wherein the three-dimensional wind yaw motion model is a dynamic model; A monitoring and early warning component, for providing transmission line monitoring feedback and wind yaw early warning based on the three-dimensional wind yaw model; The windage and vibration monitoring module is configured, including: Traversing the wind yaw and dancing zones, determining the wind yaw and dancing characteristics of each zone, and configuring the automated benchmark monitoring strategy; Based on the baseline monitoring strategy, configuring an automatic monitoring trigger unit; The intervention factor monitoring branch cooperates with the automatic monitoring trigger unit to determine the wind deviation and dancing monitoring module; The windage zoning division includes: Traversing the historical wind yaw and dancing records, performing clustering processing based on preset wind yaw and dancing differences, and determining multiple clusters; Traversing the plurality of clusters, locating the target transmission line and performing inter-cluster segmentation to determine a first wind yaw and sway partition, wherein the first wind yaw and sway partition has a partition-similar wind yaw and sway feature; Traversing the first wind yaw and galloping partitions, performing intra-partition clustering based on self-excited vibration elements, and determining a second wind yaw and galloping partition; fusing the first windage dancing zone and the second windage dancing zone to determine the windage dancing zone; Determining the three-dimensional wind-induced swaying model includes: Determine the wind yaw dance modal elements, wherein the wind yaw dance modal elements of each half-wave wind yaw dance mode include an average position limited by a neighborhood node, a wind yaw dance upper limit, and a wind yaw dance lower limit; Determining the windage dancing mode of the measuring point based on the windage dancing mode elements; Performing same-space perspective conversion and splicing reconstruction on the windage yaw dance mode of the measuring point to determine the three-dimensional windage yaw dance model; The windage vibration mode of the measuring point is converted into the same spatial perspective and reconstructed by splicing, including: Determining the windage dancing mode of the measuring point, wherein the windage dancing mode of the measuring point is located in the measuring point space; Based on the world coordinate system, performing a spatial perspective conversion on the windage dancing mode of the measuring point to determine a converted windage dancing mode; The converted wind yaw motion modes are traversed, spliced ​​and reconstructed based on relative spatial positions, and a time axis is introduced to determine the three-dimensional wind yaw motion model.

2. The laser triangulation-based transmission line wind yaw and sway monitoring and stereoscopic imaging system according to claim 1, characterized in that: Based on the windage vibration monitoring module, before controlling the laser transmitter to perform laser detection on the target transmission line, the method includes: Determining element monitoring data based on the self-excited vibration element; In combination with the windage-swing relationship, a windage-swing monitoring determination is performed on the element monitoring data to generate a first windage-swing monitoring instruction, wherein the first windage-swing monitoring instruction is marked with a monitoring zone; Based on the automatic triggering of the monitoring node, monitoring verification is performed in combination with the element monitoring data to generate a second windage sway monitoring instruction.

3. The laser triangulation-based transmission line wind yaw and yaw monitoring and stereoscopic imaging system according to claim 1, wherein: Based on the windage vibration monitoring module, before controlling the laser transmitter to perform laser detection on the target transmission line, the method includes: Traversing the target transmission line, taking the measuring point as a baseline, and determining the detection distance; Based on the detection distance, a linear constraint relationship is determined with the spot size and resolution; Based on the linear constraint relationship, the system detection parameters are adjusted.

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