866 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.

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 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 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 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 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.

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 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.

The invention provides an unmanned aerial vehicle inspection identification method and device for a power transmission tower, and relates to the technical field of electric power facility health monitoring. Polar coordinates of stay wire endpoints are obtained through unmanned aerial vehicle laser ranging, the length of the stay wire is calculated, and the deformation abnormity degree is evaluated; on the basis of a five-channel hyperspectral imaging system, orthogonal route scanning imaging is utilized, an insulator is positioned in real time in combination with a CNN algorithm, and the state of the insulator is analyzed through a UV wave band radiation value, a discharge gradient and a temperature difference; extracting reflectivity data of a wave band of 550-700nm, and calculating a corrosion area proportion by adopting a wave band ratio method; and evaluating the health state of the iron tower by combining the stay wire deformation, the insulator abnormal state and the corrosion degree. According to the method, multi-source data and an intelligent algorithm are fused, high-precision detection of stay wire deformation, insulator defects and corrosion area is realized, the problems of low efficiency and single parameter of traditional inspection are solved, and automation and reliability of state evaluation of the power transmission tower are remarkably improved.

The invention belongs to the technical field of cable mounting tools, and particularly relates to an anti-falling aerial cable clamping and mounting structure which comprises a bottom clamp and a top clamp, and the top clamp is arranged above the bottom clamp. And a tension spring is arranged between the top clamp and the bottom clamp, so that the top clamp downwards clamps the cable under the action of the tension spring. Arc-shaped clamping grooves are formed in the opposite faces of the bottom clamp and the top clamp, and mounting planes are arranged at the left ends and the right ends of the opposite faces of the bottom clamp and the top clamp. The bottom clamp comprises a bearing clamp on the upper portion and a fixing base on the lower portion, the bearing clamp is connected to the upper portion of the fixing base in a sleeved mode, and the bearing clamp can move up and down on the fixing base in a limited mode. Through the integrated design of elastic pre-tightening, double limiting and buffering energy absorption, stable clamping, dynamic adaptation and damage protection of the cable are achieved, and the cable clamp is suitable for various installation scenes such as a power transmission tower and a telegraph pole cross arm and can tolerate cable installation in severe environments such as high and low temperature, strong wind and salt mist.

The invention relates to the technical field of inclination monitoring, and discloses a miniature power transmission tower inclination monitoring device, which comprises a shell, the top of the shell is connected with a top plate, and the top plate is provided with a protection cover; an alarm assembly is arranged in the shell and comprises a hammer rod, four trigger rods and an alarm, and when the hammer rod swings, the alarm can be triggered through one of the trigger rods; the alarm assembly further comprises a display part. The display part comprises four pointer blocks and four scale plates. A leveling part is arranged at the bottom of the shell and used for adjusting the shell to be in a horizontal state. Through the arrangement of the alarm assembly, the device can drive the hammer rod to swing through gravity to trigger mechanical extrusion alarm, the technical effects of being simple in structure, low in cost and timely in alarm are achieved, and the technical problems that an existing temporary transmission tower alarm device is complex, expensive and inconvenient to operate and maintain are solved.

The invention discloses a transmission tower foundation extrusion monitoring method and a soil pressure monitoring pile, and the method comprises the steps: setting a maximum displacement allowable value of a tower foundation pile, carrying out the initial layout of the positions of a soil displacement detection pile and a soil pressure detection pile according to the stacking non-uniformity, and calculating a pressure attenuation coefficient and a displacement attenuation coefficient; performing layout optimization according to the pressure attenuation coefficient and the displacement attenuation coefficient, calculating an absolute value index, a change rate index, a correlation index and a direction difference index of soil pressure and displacement, and setting grading early warning judgment conditions of each index by combining a pole tower foundation pile maximum displacement allowable value and a pile side maximum soil pressure allowable value; according to the invention, the early warning response time for local and sudden loading is shortened, and the false alarm rate is reduced.

The invention discloses a high-voltage transmission line breakage prevention early warning system and method based on voiceprint recognition, and the system comprises a data collection unit which can collect the environment information around a high-voltage transmission tower in real time; the edge processing unit is used for eliminating wind noise interference generated when the multi-mode sensing device collects environment information, compensating frequency response deviation and extracting voiceprint MFCC features and low frequency spectrum energy entropy of vibration signals; the cloud server is used for generating an early warning instruction according to the environment information processed by the edge processing unit; and the early warning execution unit is used for carrying out early warning and expelling according to the early warning instruction. According to the invention, the environment information around the high-voltage tower is acquired in real time through the data acquisition unit, and the edge processing unit and the cloud server are arranged to carry out rapid collaborative analysis and judgment on the acquired voiceprint signals, so that real-time monitoring on the periphery of the high-voltage tower is ensured, and timely early warning and expelling on surrounding vehicles are realized.

The utility model discloses a special welding fixture for angle steel tower feet of a power transmission tower, and relates to the technical field of special welding fixtures for angle steel tower feet, the special welding fixture comprises an operation table, the top of the operation table is provided with a first positioning assembly, the first positioning assembly comprises two first positioning plates, and the two first positioning plates are arranged on the operation table. The first positioning plate is fixedly connected to the operation table, a second positioning assembly used for welding two steel plates is arranged on the operation table, a third positioning assembly used for welding three steel plates is arranged on the operation table, and a fourth positioning assembly used for welding four steel plates is arranged on the operation table. According to the special welding clamp for the angle steel tower foot of the power transmission tower, by arranging the first positioning assembly, the second positioning assembly, the third positioning assembly and other structures, different numbers of steel plates can be conveniently positioned, operation is easy and convenient, and the applicability of the special welding clamp for the angle steel tower foot of the power transmission tower is improved.

The present invention discloses a method, device, equipment and storage medium for anti-icing risk assessment of transmission towers, which are used to solve the technical problems of low accuracy and poor effect in the anti-icing capacity assessment of existing transmission tower assessment methods. The present invention includes: obtaining a numerical simulation model of a transmission tower; calculating the ice-covered load of the transmission tower under a preset ice thickness according to the numerical simulation model; calculating a stress response result according to the ice-covered load; calculating a stress ratio of each member according to the stress response result; determining a target member according to the stress ratio; obtaining the actual stress and strain of the target member in real time; and judging the anti-icing risk of the target member according to the actual stress and strain.

The invention discloses an overhead transmission tower lightning current monitoring system and method, and the method comprises the following steps: installing a multi-mode sensor module on a tower, and collecting a lightning current signal and structure response data; utilizing a local sparse dynamic window optimization algorithm to process the data segment by segment, extracting dynamic features and generating a multi-scale feature map; modeling a lightning stroke propagation rule through a space-time generative adversarial network, and generating a space-time characteristic matrix; constructing a spatial correlation map by combining a hypergeometric map embedding algorithm, and identifying a lightning stroke influence range and a diffusion path; dynamically adjusting a communication path and frequency distribution by adopting a Bayesian game optimization model; analyzing the potential influence of lightning stroke on the structure based on a multi-task self-supervised learning model, and predicting a time evolution trend; and comprehensively evaluating real-time and historical data through the remote monitoring terminal, and generating a risk prediction report and a protection reinforcement strategy. According to the invention, the problems of real-time performance, accuracy and environmental adaptability of lightning current monitoring are solved.

The invention belongs to the technical field of damage identification, and particularly relates to a multi-index curvature modal damage identification method based on test simulation dual-data driving, which comprises the following steps: establishing a finite element model of a power transmission tower; performing finite element analysis on the finite element model in combination with actual working conditions to obtain a vulnerable position; arranging a measuring point at a vulnerable position of the finite element model, and arranging a sensor in the power transmission tower according to the measuring point; constructing a curvature modal damage sample library at the measuring points of the finite element model; constructing a neural network model, and training the neural network model by using the curvature modal damage sample library to obtain a trained neural network model; acquiring actual data of the power transmission tower by using a sensor, calculating a curvature modal damage identification index according to the actual data, and inputting the curvature modal damage identification index into the trained neural network model to obtain a structural damage identification result; according to the method, the neural network is trained by combining the curvature modal difference value, the superposition curvature modal difference value and the curvature modal difference value change rate, so that the accuracy of damage identification is improved.

The invention provides a tower assembling robot control method and system, a tower assembling robot and a tower assembling system, and relates to the technical field of electric power construction, and the tower assembling robot control method comprises the following steps: respectively obtaining images collected under a first focal length and a second focal length; fusing the images collected under the first focal length and the second focal length to obtain a fused image, extracting geometric features of the bolt based on the fused image, and estimating an initial pose of the bolt based on the extracted geometric features of the bolt; optimizing the initial pose in combination with a pose optimization strategy to obtain an optimized bolt pose; and the tower assembling robot is controlled to conduct fastening operation on the to-be-fastened bolt by combining the optimized bolt pose and the self-adaptive impedance control bolt fastening scheme. The tower assembling efficiency of the high-voltage power transmission iron tower can be improved.

The invention discloses an automatic transfer device for transmission tower parts, and relates to the technical field of steel structure production equipment. The device comprises a bottom plate, a mounting structure is fixedly connected to the right side of the upper end face of the bottom plate, a rotating driving structure is arranged in an inner cavity of the mounting structure, a conveying driving structure is arranged on the left end face of the mounting structure, a reversing conveying structure is arranged in an inner cavity of the conveying driving structure, and a placing structure is fixedly connected to the middle of the lower end face of the inner cavity of the mounting structure; height adjusting structures are arranged on the end faces of the front side and the rear side of the conveying driving structure, height transmission structures are arranged on the left side of the upper end face of the bottom plate, and a height driving structure is fixedly connected to the position, located between the two height transmission structures, of the upper end face of the bottom plate; through cooperation of the telescopic inner rod and the positioning push rod, the angle iron is adjusted to be in an inverted V shape and is positioned above the conveying rollers, and the stability and accuracy of the angle iron in the conveying process are guaranteed through the positioning and overturning functions.