1140 results about "Transmission tower" patented technology

A system for breakage early warning of high-voltage transmission lines based on acoustic prints, including a data acquisition unit, an edge processing unit, a cloud server, a warning execution unit, and a communication unit. The data acquisition unit is configured to collect environmental information of a high-voltage transmission tower in real time through a multimodal sensing device. The edge processing unit includes an adaptive filtering module configured to eliminate wind noise interference in the environmental information and compensate for frequency response deviation. The cloud server can generate a warning instruction based on the environmental information. The warning execution unit can perform warning and alarming actions based on the warning instruction. The communication unit is configured to enable data and information transmission among the units. A method implemented by such system is also provided.

A transmission tower deformation monitoring device based on a phased array radar technology relates to the field of irregular contour metering, and comprises a map construction module used for constructing a regional digital map; the boundary determination module is used for near-field region boundaries; the signal acquisition module is used for acquiring a near-field echo signal of a near-field region through a narrow beam and acquiring a far-field echo signal of a far-field region through a wide beam; the calibration table construction module is used for constructing a signal intensity comparison table; the data processing module is used for determining effective monitoring data; the error calculation module is used for performing error calculation on the effective monitoring data to obtain a phase error and an amplitude error; and the parameter determination module is used for determining iron tower deformation parameters. According to the invention, the accuracy of transmission tower deformation monitoring can be improved.

The invention relates to the technical field of pole and tower inclination monitoring, and provides a pole and tower inclination monitoring method and system based on point cloud rapid reconstruction, and the method comprises the following steps: obtaining original point cloud data of a pole and tower through a hierarchical scanning and adaptive sampling density method; performing down-sampling, noise filtering and preliminary classification on the original point cloud data to obtain tower structure point cloud data; extracting tower geometric features based on the tower structure point cloud data, and constructing a tower skeleton three-dimensional model through the tower geometric features; calculating the inclination angle of each part of the tower based on the central axis of the tower skeleton three-dimensional model; and carrying out deformation analysis and deformation prediction on the tower based on the inclination angle of each part of the tower, and generating a tower inclination monitoring report. According to the method, the whole-process deformation monitoring from data acquisition, processing, modeling to analysis and prediction is realized, and the tower inclination monitoring efficiency is improved.

The invention discloses a bird-related fault identification and early warning method based on a transmission tower gap model, and relates to the technical field of power system safety monitoring. The method comprises the following steps: firstly, constructing a three-dimensional transmission tower gap model containing a local insulated armor, and obtaining an electric field distortion feature library under various working conditions through finite element simulation; further simulating interference behaviors of the bird body, the bird nest and the excrement in the safety gap, calculating the discharge probability, and synthesizing and labeling a bird image for training a risk decision model. And in combination with a target detection algorithm integrating an attention mechanism and an SPPCSPC module, space coordinates of bird targets are extracted in real time and mapped to a high-risk area, and a discharge risk score and a breakdown trend index are output by using an LSTM network. And when the risk index exceeds a dynamically adjusted early warning threshold, generating an early warning signal and a fault coordinate. According to the invention, the precision and foresight of bird-related fault identification are improved, and the method has good engineering adaptability.

The invention discloses a power transmission tower edge multi-device linkage method based on an ad hoc network and two-dimensional and three-dimensional fusion, and relates to the technical field of intelligent power transmission networks, and the method comprises the steps: deploying multiple devices, embedding a passive sensor, and employing an unmanned plane to carry a laser radar to generate a tower three-dimensional space reference model; an unmanned aerial vehicle autonomous inspection route is planned based on the iron tower three-dimensional space reference model, laser point cloud, infrared thermal imaging and backscattering data are synchronously collected, passive sensor deformation parameters are extracted by analyzing channel state information, and a multi-dimensional data set is constructed; fusing the multi-dimensional data set, generating a dynamic risk thermodynamic diagram and labeling risk levels; and when a high risk level is detected, triggering an equipment deployment strategy and recording operation data. According to the invention, by constructing a mechanical-thermal-geometric multi-field coupled power transmission tower dynamic monitoring system, a monitoring normal form with high-precision positioning, real-time response and extremely simple operation and maintenance is provided for an intelligent power grid, and intelligent and unmanned evolution of power transmission facility management is promoted.

The invention discloses a transmission tower foundation differential settlement monitoring method and system based on LSTM, and belongs to the technical field of transmission tower monitoring. The system comprises a monitoring unit, a data processing unit, an operation unit, a judgment unit and an early warning unit. The method comprises the steps that monitoring data of differential settlement of the transmission tower and monitoring data of the surrounding environment of the transmission tower are collected through a monitoring unit; a data processing unit is used for preprocessing the monitoring data to form model data; an LSTM long short-term memory network algorithm is applied through an arithmetic unit, and a prediction model for differential settlement of the transmission tower foundation is constructed through model data training; the displacement data of the transmission tower in the future time are predicted according to the prediction model, the predicted displacement data are compared with standard displacement data through the judgment unit, and early warning is conducted through the early warning unit according to the displacement offset. According to the invention, manual monitoring cost is reduced by means of artificial intelligence, huge monitoring data can be processed, and monitoring timeliness and accuracy are improved.

The invention discloses a power grid transmission line tower inclination detection method based on remote sensing image semantic segmentation, and relates to the field of electric power safety and artificial intelligence. Comprising the following steps: step 1), preprocessing a remote sensing image, including shadow detection and image denoising; 2) performing semantic segmentation on the remote sensing image through an improved U-Net neural network, and extracting a tower body area and a tower top area of the power grid transmission tower; and step 3), according to semantic segmentation results of the tower body and the tower top of the transmission tower, calculating center point coordinates of the two areas, and according to the two center point coordinates, calculating the inclination of the tower. According to the invention, by using the remote sensing image and semantic segmentation technology, the rapid detection of the inclination condition of the pole tower in a large-range area can be realized.

The invention belongs to the technical field of transmission tower accessory machining, and discloses a machining stamping device and method for transmission tower angle steel. The machining and punching device for the angle steel of the power transmission tower comprises a punching machine, a steel walking frame is arranged on one side of the punching machine, a lifting compression roller assembly and a lower driving roller assembly which are arranged in parallel up and down are installed on the steel walking frame, a concentric-square-shaped frame is fixedly installed on the side, away from the punching machine, of the steel walking frame, and a plurality of carrier rollers are rotationally installed at the top end of the concentric-square-shaped frame; elastic stress application type swing arm assemblies are installed on the front edge and the rear edge of the top end of the frame shaped like the Chinese character'hui ', and abrasive belt grinding assemblies are installed on the sides, close to the vertical center datum plane of the frame shaped like the Chinese character'hui', of the elastic stress application type swing arm assemblies. The L-shaped angle steel obtained after stamping is completed is conveyed to the multiple carrier rollers through cooperation of the lifting pressing roller assembly and the lower driving roller assembly, and the outer wall face of the L-shaped angle steel is subjected to deburring and grinding operation through the abrasive belt grinding assembly.

The invention provides a power transmission and distribution line suspended foreign matter detection method and system based on image processing and deep learning. Wherein a historical point cloud set on the surface of the power transmission tower is acquired, a deformation gradient map is generated through dynamic registration of curvature differences of adjacent point clouds, a super-threshold region is marked as a deformation correlation region, and foreign matter contour parameters are extracted; performing time-frequency decomposition on the node strain signal, retaining a steady-state component, and mapping the steady-state component to an association region to form a strain map; calculating the displacement offset of the deformation association interval to construct a deformation propagation network, and extracting load over-threshold nodes to construct a stress diffusion network; and superposing the network, fusing the displacement and the load value in the superposition area to generate a risk index, and outputting early warning in combination with the foreign matter coordinates and the risk index. According to the technical scheme provided by the invention, the cross-modal dynamic analysis of deformation propagation and stress diffusion paths is fused, and the early warning efficiency of foreign matter attachment and structure abnormity risks of the power transmission tower is improved.

The invention discloses a power transmission tower state monitoring method and device in an emergency scene, and the method comprises the steps: obtaining the real-time state data of a power transmission tower through data obtaining modules disposed at the upper part and the middle part of the power transmission tower and a communication module disposed at the bottom of the power transmission tower; screening the real-time state data according to the correlation between the real-time state data and the state of the transmission tower; and sequentially inputting different types of screened real-time state data into input layers in different network layers of the transmission tower state monitoring model, and outputting a transmission tower state monitoring result. According to the invention, the state of the power transmission tower in the emergency scene can be monitored, the state of the power transmission tower can be efficiently and accurately monitored and evaluated in real time, the safety of the power transmission tower is guaranteed, the emergency response capability is effectively improved, and the state monitoring cost of the power transmission tower in the emergency scene is reduced.

The invention relates to the field of transmission towers, and discloses a tension type transmission tower buffer connecting device which comprises a supporting frame, a plurality of isolation assemblies are symmetrically arranged on the upper surface of the supporting frame, sliding seats are slidably connected into the isolation assemblies, and connecting rods are fixedly connected to the outer surfaces of the sliding seats. A belleville spring set is arranged between the outer surface of the sliding base and the inner wall of the isolation assembly, the belleville spring set is arranged on the outer surface of the connecting rod in a sleeving mode, and a telescopic rod and a first spring are fixedly connected between the outer surface of the sliding base and the inner wall of the isolation assembly. A primary buffer layer is formed by the belleville spring set and the first spring, axial impact force can be absorbed without sliding of the sliding seat during daily wind vibration and wire slight galloping, meanwhile, vibration can be restrained through the huge static friction torque of the fan-shaped friction face and the friction ball in the omnidirectional damping assembly, the circuit is kept stable, and slight load impact is effectively dealt with.

The invention discloses a tower crane installation path planning method and system, a terminal and a medium, and the method comprises the following steps: collecting and preprocessing three-dimensional point cloud data and visual information in a tower crane installation area, fusing the point cloud data with image data, and generating a fused three-dimensional point cloud image which comprises distance and color information; a deep learning model is adopted to carry out obstacle detection on the fused three-dimensional point cloud image; an RRT algorithm is adopted, and a safety path is planned according to the obstacle detection result and the requirement of the hoisting task; and controlling the movement of the hoisting equipment according to the obtained safe path, and executing ascending, descending, horizontal moving and rotating actions of a lifting hook according to a path planning result. The method has the advantages that the safety and the efficiency in the hoisting operation of the power transmission tower are improved, and the quality and the reliability of power transmission line construction are improved.

The invention discloses a power transmission tower wind damage vulnerability analysis method based on long-term marine atmospheric corrosion. The method comprises the following steps: step 1, establishing a wind load numerical simulation model; 2, establishing a corrosion depth prediction model of the steel structure in the marine atmospheric environment; 3, establishing a finite element model of the corroded power transmission tower line system; 4, establishing a wind damage vulnerability model of the power transmission line structure; 5, performing push hover analysis on the power transmission tower structures with different service lives considered; and 6, analyzing the wind damage vulnerability of the power transmission tower structure. According to the power transmission tower wind disaster vulnerability analysis method based on long-term marine atmospheric corrosion, by establishing the wind disaster vulnerability curves under different corrosion degrees, the damage probability of the power transmission tower under the wind load effect can be predicted more accurately, a scientific basis is provided for design, maintenance and operation of the power transmission tower, and the method is suitable for popularization and application. And the stability and the safety of the system in a complex marine atmospheric environment are ensured.

The invention relates to the technical field of unmanned aerial vehicle flight control, in particular to an unmanned aerial vehicle flight control and monitoring integrated system for power transmission tower inspection, and the system comprises a flight monitoring module which is used for obtaining the wind speed in the environment where an unmanned aerial vehicle is located, the rotating speed of each rotor wing of the unmanned aerial vehicle, and the inclination angle of the unmanned aerial vehicle body; the flight control module is used for acquiring the disturbance value of each rotary wing in each preset time period and the inclination fluctuation degree of the unmanned aerial vehicle body; disturbance factors of the positions of all the rotary wings at the current moment are obtained, and the power of brushless motors in all the rotary wings at the current moment is adjusted; the flight obstacle avoidance module is used for planning a flight path for avoiding obstacles; the tower monitoring module is used for monitoring damage information of the transmission tower; and the wireless communication module is used for transmitting the damage information to a ground station. By correcting the flight attitude of the unmanned aerial vehicle, the stability of the fuselage during flight of the unmanned aerial vehicle is improved, and then the inspection efficiency and quality of the transmission tower are improved.

The invention discloses a transmission tower vulnerability analysis method and system based on seismic simulation, and belongs to the technical field of electric power facility disaster prevention, and the method comprises the steps: correcting bedrock seismic oscillation parameters based on equivalent shear wave velocity, and generating a high-precision earth surface PGA distribution diagram; automatically positioning a key node layer through eigenvalue decomposition, reducing the order of the three-dimensional model of the power transmission tower into a two-dimensional series multi-degree-of-freedom model, and outputting a layer mass vector, a condensation stiffness matrix and rod piece bending stiffness; performing time-history analysis by using the corrected PGA-driven reduced-order model to generate an earthquake damage probability; the multi-source remote sensing data and the PGA are fused, the landslide space probability is output through a deep learning model, and the impact strength and the landslide kinetic energy are calculated to judge the landslide damage probability; and based on the dual-threshold condition triggering probability union set, calculating a comprehensive damage probability, and generating a three-dimensional vulnerable curved surface. According to the method, the problems of high missing report rate and low calculation efficiency of single disaster assessment are solved, and minute-level accurate early warning of the composite disaster risk of the power transmission tower is realized.

The invention discloses a power transmission tower deformation monitoring method and device and a computer program product, and the method comprises the steps: obtaining a multi-angle collection image of a random speckle pattern on the surface of a power transmission tower; constructing an image sequence based on the multi-angle acquired images, reconstructing a three-dimensional displacement field on the surface of the power transmission tower by using a stereoscopic vision reconstruction algorithm, and exporting a strain tensor field; performing time sequence processing on the strain tensor field under a plurality of time nodes through a strain evolution analysis model of a continuous time sequence, and extracting a strain change trend of each preset structure part; carrying out space consistency mapping and weighted interpolation processing according to the strain change trends of the plurality of preset structure parts, and calculating to obtain the overall structural dependent variable of the power transmission tower; and S5, in combination with historical strain data and the current overall structural dependent variable, identifying an abnormal deformation area of the power transmission tower by comparing the spatio-temporal evolution mode of the strain tensor field. The method has the effect of improving the accuracy of deformation monitoring of the power transmission tower.

The invention relates to the technical field of power transmission line safety monitoring, and particularly discloses a self-adaptive calibration method for an ultrasonic wind speed sensor, which comprises the following steps of: arranging an orthogonal ultrasonic probe array at the top of a tower, and compensating probe offset caused by swinging of a tower body in real time through GNSS / IMU (Global Navigation Satellite System / Inertial Measurement Unit) fusion positioning; integrating a temperature, humidity and pressure sensor and vibration spectrum analysis to construct an environmental parameter compensation model; double-frequency ultrasonic waves are adopted to detect the ice accumulation thickness of the protective cover and correct the sound path distance; deploying a lightweight LSTM model at an edge computing unit to realize minute-level dynamic parameter adjustment; electromagnetic interference is suppressed by combining linear frequency modulation spread spectrum and beam forming technologies; and establishing a three-height-layer wind speed gradient model to generate a galloping early warning. The problem of measurement distortion caused by tower deformation, icing and parameter solidification of a traditional sensor is solved, all-working-condition operation from-40 DEG C to 60 DEG C is supported, and the monitoring reliability in a strong electromagnetic environment is remarkably improved.

The invention provides a power transmission tower settlement monitoring method and system based on a laser scanning measurement technology, and the method comprises the following steps: scanning key points of a power transmission tower structure according to a preset time interval, the key points including a tower foot, a middle tower and a tower top of a power transmission tower; acquiring scanning data in real time; performing data processing on the received scanning data to obtain processed scanning data; and receiving the processed scanning data, carrying out real-time monitoring, giving an alarm when an abnormal condition is found, carrying out prediction and evaluation on historical data, and obtaining the settlement trend of the iron tower. According to the invention, through automatic laser scanning and real-time data acquisition at a preset time interval, unattended continuous monitoring is realized, and efficiency and data timeliness are significantly improved; through a real-time monitoring and threshold alarm mechanism, an abnormal alarm is triggered instantly; the settlement trend is predicted in combination with historical data, potential risks are found in advance, and the preventive maintenance capability is enhanced.

The invention discloses a safety sag calculation method and system for a power transmission tower wire, and the method comprises the steps: constructing a wire stress change relation according to the elastic deformation of the wire under each control condition and the original wire length of the wire; wherein each control condition is set according to a preset environment parameter; based on the wire stress change relation and a preset nonlinear stress change relation, determining the wire tension characteristic under the actual working condition; and obtaining a safety sag meeting a preset lead safety requirement according to the tension characteristic of the lead, and adjusting the sag of the lead under an actual working condition according to the safety sag. According to the method, the nonlinear characteristic of the wire is considered when the tension characteristics of the wire of the power transmission tower in different environments are calculated, so that the calculated wire sag is more accurate and meets the safety requirement of an overhead power transmission line, and sufficient data support is provided for effectively evaluating and ensuring the safety of the power transmission line.

The invention relates to the technical field of line crane warning, in particular to an overhead line trend intelligent crane sentry warning method and system based on Beidou positioning. The method comprises the steps that base station data information including power transmission tower pole and line trend data is acquired based on Beidou positioning, and construction crane position information is monitored in real time; respectively constructing a power transmission line corridor model and a warning tape model based on the acquired data; carrying out model integration and optimization on the constructed power transmission line corridor model and the warning tape model; generating early warning information based on the integrated and optimized model; and carrying out sentry alarm on the construction crane based on the generated early warning information. Real-time monitoring of numerous power transmission tower and power transmission line corridor areas, including power grid power transmission line channel display, crane equipment map point location display, crane early warning track display and the like, can be realized.

The invention discloses a risk category assessment method and device for a power transmission tower, terminal equipment and a storage medium, and relates to the technical field of tower assessment, and the method comprises the steps: obtaining real-time data of a target power transmission tower, the real-time data comprising time sequence data and image data; inputting the real-time data into a hybrid model composed of an attention mechanism and a residual network, extracting a time sequence feature vector of the time sequence data through the attention mechanism, and extracting an image feature vector in the image data through the residual network; and fusing the time sequence feature vector and the image feature vector, inputting the fused time sequence feature vector and image feature vector into a classifier, outputting the probability of each risk category, and selecting the category with the highest probability as a risk category label. According to the method, the time sequence feature vector in the time sequence data and the image feature vector in the image data are extracted, and the two different feature vectors are combined for evaluation, so that the accuracy of risk category evaluation of the power transmission tower can be effectively improved.

An agricultural unmanned aerial vehicle wireless energy transmission and information relay method oriented to low-altitude remote sensing data acquisition comprises the following steps: design of an agricultural unmanned aerial vehicle quick charging system, a relay strategy of an agricultural unmanned aerial vehicle, an agricultural unmanned aerial vehicle-infinite sensor network path planning algorithm based on the relay strategy, and a wireless energy transmission and information relay method based on the relay strategy. As an important supplement of aerial remote sensing, unmanned aerial vehicle remote sensing has high feasibility in a low-altitude remote sensing scheme in the agricultural field, (1) an unmanned aerial vehicle intelligent quick charging platform on a high-voltage transmission tower intelligently and quickly charges an unmanned aerial vehicle in the air by using a wireless energy transfer technology, and the problems of short endurance time and frequent battery replacement of the unmanned aerial vehicle are solved; (2) in the sparse wireless sensor network, the unmanned aerial vehicle can replace a wireless sensor network node to monitor some unperceived areas, and can also play a role of a relay node to transmit information, so that energy consumption generated by routing is reduced, the survival time of the whole network system is prolonged, and the system reliability is improved. The problem that the communication range of the unmanned aerial vehicle is limited in the agricultural data acquisition process is solved.

The invention relates to the technical field of power transmission tower detection, in particular to a target detection method for power transmission tower detection in a remote sensing image, and the method comprises the steps: improving a Faster RCNN network model, and obtaining a power transmission tower detection model; acquiring a remote sensing image data set of the power transmission tower, and performing image processing on the remote sensing image data set of the power transmission tower to obtain a sample data set for training a power transmission tower detection model; testing and training the power transmission tower detection model by using the sample data set to obtain a trained power transmission tower detection model; and inputting a remote sensing image of a to-be-detected power transmission tower into the trained power transmission tower detection model to obtain a power transmission tower image center coordinate. According to the method, the defect that the omission ratio of the power transmission tower is high due to the fact that feature information of different scales is ignored and only the feature layer of the minimum scale is detected is overcome, and the method can be used for automatically obtaining the geographic coordinates of the power transmission tower in the target area.

The invention discloses a power transmission tower structure safety evaluation method based on computer vision, and relates to the field of power transmission tower structure safety evaluation, and the method comprises the following steps: obtaining a structure static curvature parameter; the dynamic curvature modal area difference square ratio of the rod piece structure is calculated; combining the structure static curvature parameter and the dynamic curvature modal area difference ratio corresponding to each basic evaluation unit into a dynamic and static fusion feature data set; calculating the structure damage posterior probability of each basic evaluation unit through Bayesian reasoning; and according to the structure damage posterior probability distribution results of all the basic evaluation units, carrying out comprehensive safety grade evaluation on the power transmission tower structure. The non-contact monitoring method based on computer vision is adopted, the deformation and displacement information of the nodes is obtained through the image processing technology, the equipment arrangement and maintenance work is greatly simplified, and the overall monitoring cost is reduced.

The invention discloses a power transmission tower corrosion damage assessment operation and maintenance method and system combining digital twinning and AI, and relates to the technical field of power transmission and transformation project operation and maintenance safety assessment. Based on a parameterized digital twinning base model, a mechanical response and an environmental corrosion rate are obtained by combining environmental parameters, and then a training data set is constructed; training a multi-task machine learning model based on the training data set to obtain a trained multi-task machine learning model; performing feature extraction on the image data to obtain visual features, performing feature extraction on the point cloud data to obtain geometric features, and fusing the visual features and the geometric features by adopting a double-flow feature fusion network based on an attention mechanism to obtain fused features; and inputting the fusion features into a multi-task machine learning model for prediction to obtain a predicted mechanical response and an environment corrosion rate, and then evaluating the corrosion state and predicting the service life so as to realize rapid, accurate and intelligent evaluation and operation and maintenance decision support of the corrosion state of the power transmission tower.

The invention discloses a power transmission tower modal parameter automatic identification method, device and system, and relates to the field of power transmission tower structure monitoring. According to the specific implementation scheme, a plurality of measurement points are arranged on a power transmission tower body in the height direction, and response data a are obtained; based on the response data a, a random subspace method is used for solving and drawing a first stability graph, through first modal data between each first stability point and a nearest point of an adjacent order, fuzzy C-means clustering (Fuzzy C-Means Clustering, abbreviated as FCM) is used for clustering the first modal data, false points are deleted, and a second stability graph is obtained; secondly, extracting stable points, meeting conditions, of each order by adopting two-time hierarchical clustering, and averaging to obtain the frequency, damping and vibration mode of each order; according to the method, the modal parameters of the power transmission tower are indirectly solved by using the data collected by the sensors arranged at the multiple measuring points, and the problems that the modal parameter identification efficiency of the power transmission tower is low and the reliability is poor are solved.

A power transmission tower grounding resistance intelligent measurement method based on ground potential field distributed sensing comprises the steps that a ground potential sensing network is arranged around a power transmission tower grounding device, and a ground potential field distributed measurement system with an iron tower as the center is established; a broadband characteristic coding current signal is injected into the grounding system through a weak current injection module; acquiring potential response data of each node of the ground potential sensing network excited by the feature coding current signal by adopting a distributed synchronous acquisition technology, and reconstructing complete ground potential field spatial distribution from sparse node observation data based on a compressed sensing theory through a signal reconstruction algorithm; and inputting the reconstructed complete ground potential field spatial distribution map into a pre-trained map neural network model, and outputting an intelligent identification result and an anomaly diagnosis conclusion of the ground resistance. According to the invention, non-contact, distributed and high-precision grounding resistance measurement under the condition that a grounding lead does not need to be disconnected is realized, and the measurement precision and reliability under a complex working condition are remarkably improved.

The invention discloses a three-dimensional reconstruction method, system and device for an extra-high voltage power transmission and transformation line, and belongs to the technical field of point cloud reconstruction. The three-dimensional reconstruction method comprises the following steps: placing a laser radar along the extra-high voltage power transmission and transformation line to obtain point cloud data of the extra-high voltage power transmission and transformation line; rTK positioning software is placed at the laser radar and the selected reference point to obtain longitude, latitude and height coordinate data; correcting and filtering the obtained point cloud data and longitude and latitude coordinate data of the extra-high voltage power transmission and transformation line; splicing the filtered extra-high voltage power transmission and transformation line point cloud data, and constructing a preliminary reconstruction model; performing point cloud segmentation on the preliminary reconstruction model by using a region growing algorithm, and extracting incomplete power transmission tower point clouds in the preliminary reconstruction model; acquiring three-dimensional models of different types of required power transmission towers, and constructing a standard model library; and matching the incomplete point cloud of the power transmission tower with the constructed standard model library, and placing a matched three-dimensional model in a scene to realize complete point cloud reconstruction.

The invention discloses a power transmission tower attitude monitoring and vibration intrusion identification method based on multi-source data fusion, and the method comprises the steps: carrying out the deep fusion of GPS displacement data and accelerometer inclination angle data, employing a dynamic weight fusion mechanism: adjusting a fusion coefficient alpha in real time according to the GPS signal quality, guaranteeing the accuracy and stability of data fusion, and at the same time, carrying out the real-time adjustment of the fusion coefficient alpha, and carrying out the recognition of the vibration intrusion of a power transmission tower. And continuously optimizing the error propagation model by taking the final inclination angle theta final of the power transmission tower as a state variable, updating the attitude estimation of the power transmission tower, and realizing + / -0.01-degree high-precision attitude monitoring. According to the invention, the system can output a high-precision three-dimensional attitude angle in real time by combining the rapid dynamic response of the accelerometer and the long-term stability of the GPS. Besides, an LCD-MPE (feature extraction technology) is introduced, lightweight neural network classification is combined, vibration signal sampling, noise reduction and abnormal signal segment identification, analysis and extraction are carried out on the transmission tower through an MEMS accelerometer, and second-level detection and behavior type discrimination of invasion behaviors around the transmission tower are realized. The core technical barrier from'inability perception 'to'accurate identification' is overcome, and subversive upgrading of power facility safety protection from'passive disposal 'to'active defense' is promoted.

The invention discloses an automatic tower foundation pit dividing device and method based on laser point cloud, relates to the technical field of tower foundation pit dividing of power transmission line mechanical construction, and solves the problems that existing power transmission line tower foundation pit dividing is low in automation degree, low in operation efficiency, low in manual operation precision and prone to generating pit dividing errors. Comprising a tripod and an equipment holder installed at the top of the tripod, a box body is arranged above the equipment holder, the box body is in butt joint with the equipment holder through a holder connecting piece, a laser radar is arranged on the inner side of the box body, and a top cover is installed at the top of the box body; the device further comprises a pit separating mechanism used for enabling the laser radar to automatically and efficiently separate pits, and the pit separating mechanism is installed on the inner side of the box body. Through the pit separation mechanism, automatic pit separation, design guidance, foundation acceptance and foundation bolt verification of the transmission tower foundation can be achieved, and therefore the effect of automatic and efficient pit separation is achieved.