1050 results about "Overhead line" patented technology

The invention relates to the technical field of cable fault diagnosis and positioning, in particular to a cable fault positioning method and system based on multi-source data space-time correlation, and the method comprises the steps: obtaining partial discharge, traveling wave and temperature multi-source monitoring data from a high-voltage cable-overhead line hybrid power transmission network; on the basis of space-time correlation analysis of partial discharge and temperature data, heat-electricity associated defect points are calibrated; comparing traveling waves of the cable and the overhead line, and identifying and inhibiting cross-domain propagation interference; positioning the traveling wave data which are not identified to obtain temporary coordinates, judging fault characteristics by fusing information such as sheath ring current and the like, and comparing the temporary coordinates with defect points to generate matching identification; and inputting multi-dimensional information such as fault features, defect matching identification and temperature into the fusion model, calculating the confidence coefficient of a fault mode, and outputting a cross validation positioning result. According to the invention, high-reliability positioning of mixed line faults and active early warning of insulation defects are realized by carrying out space-time correlation and fusion decision on multi-source monitoring quantities such as traveling waves, partial discharge, circulation, temperature and the like.

The invention discloses a self-adaptive evaluation method and system for the running state of a contact network. The method comprises the following steps: constructing a contact network operation state evaluation index system, and obtaining time sequence detection data of each evaluation index; dynamically calculating the length of an adaptive window at the current evaluation moment, and extracting a nearest data subset matched with the length of the adaptive window from the time sequence detection data; using an improved CRITIC method to calculate and obtain a first objective weight vector; updating the gain coefficient vector, and calculating a second objective weight vector; combining the second objective weight vector with a subjective weight vector determined by an analytic hierarchy process by adopting a combined weight method to generate a final combined weight vector, and evaluating the running state of the overhead line system at the current evaluation moment until the evaluation task is finished; according to the method and the system, the accuracy and the timeliness of state evaluation of the overhead line system are effectively improved.

The invention relates to a rail contact network parameter high-precision measurement method and system based on a multi-dimensional coupling algorithm, and solves the problems that manual measurement precision is insufficient, continuous collection is difficult, operation is hindered in a severe environment, and safety risks exist in workers. Calculating an initial rail width, generating a rail width reference through temperature compensation, and synchronously combining inertial measurement data to establish a space reference coordinate system; re-calibrating the parameters, comparing with the attitude angle, updating the reference if the parameters exceed the threshold value, and otherwise, compensating and filtering the sensing data; then, a measured point of the contact network is tracked, a holder is adjusted for alignment, and finally, a three-dimensional coordinate, a guide height and a pull-out value are calculated and output by fusing multi-source data. The method has the advantages that high-precision and automatic measurement of the geometric parameters of the overhead line system is achieved, the safety risk and the efficiency bottleneck of manual measurement are remarkably reduced, and reliable data support is provided for intelligent operation and maintenance of railways.

The invention discloses an MEMS and TMR fused overhead line lightweight monitoring device, and the device comprises an annular shielding cover which sleeves a to-be-detected overhead conductor and is coaxial with the to-be-detected overhead conductor, and the side wall of the annular shielding cover is provided with a through hole; the sensing unit comprises at least two MEMS electric field sensors and at least two TMR magnetic field sensors and is used for detecting an electric field and a magnetic field generated by the overhead conductor to be detected; the analysis processing unit is used for receiving, processing and transmitting the signal generated by the sensing unit; and the power supply unit is arranged in the annular shielding cover and is electrically connected with the sensing unit and the analysis processing unit. The beneficial effect of the invention is that the coupling crosstalk phenomenon generated by an external electromagnetic field can be effectively suppressed. Moreover, the monitoring device is small in size, is convenient to install and deploy in a complex line environment, provides a stable hardware basis for precise inversion of voltage and current through structural cooperation, and provides reliable support for intelligent monitoring of an overhead line.

The invention discloses a method and a device for monitoring the running state of a railway overhead line system. The method comprises the following steps: receiving environmental data acquired by various sensors; the environment data comprises at least one of humidity data, wind speed data, temperature data, ultraviolet intensity data and electromagnetic induction intensity signals; predicting the environmental data through a pre-established risk prediction model to obtain a predicted contact network risk level; wherein the risk prediction model is established based on historical environment data; based on historical fault data, the environment data and an actual detection result, the contact network state is evaluated, and a contact network state evaluation grade is obtained; and generating early warning information according to the contact network risk level and the contact network state evaluation level. According to the invention, operation state monitoring, risk level discrimination and intelligent early warning linkage based on multi-source data can be realized, so that the safety and operation and maintenance efficiency of the contact network system are improved.

The invention provides an enhanced YOLOv10-based electrified railway overhead line system insulator defect detection method, system and equipment and a medium. The method comprises the following steps: acquiring an overhead line system insulator image of a target scene through a shooting device and automatic inspection equipment; marking contact network insulators and defects in the contact network insulator image by using a marking tool, and dividing the marked image into a training set and a verification set according to a preset proportion; performing model training on the basis of the training set and the verification set, and introducing a lightweight OfficientViT module, a Wise-IoU loss function and a knowledge distillation technology in the training process to obtain a contact network insulator defect detection model based on YOLOv10; and inputting the obtained image of the to-be-detected overhead line system insulator into the overhead line system insulator defect detection model to obtain a defect detection result. The method provided by the invention improves the accuracy and efficiency of insulator defect detection.

The invention belongs to the technical field of image processing, and particularly relates to a contact network defect identification method based on multiple modalities, which comprises the following steps of: 1, acquiring a visible light image sequence and an infrared thermal imaging image sequence of a target contact network, and carrying out time alignment and temperature calibration to obtain a unified reference frame sequence and a thermal vision consistency label set; 2, constructing a structure change graph and an overheat candidate graph in the obtained unified reference frame sequence, calling a cross-modal physical semantic autocatalysis recombination algorithm, and taking a generated thermal vision consistency label set as a constraint; and step 3, taking the output fusion evidence body as input, combining the thermal vision consistency label set and the reversible channel audit record to verify the candidate area, obtaining a defect target, and outputting a defect category and a defect position. According to the method, the precision and stability of defect detection are improved, the traceability of the result is also realized, and a reliable guarantee is provided for intelligent operation and maintenance of the electrified railway overhead line system.

The invention provides a fault positioning method and system for an overhead line of a power distribution network, and a storage medium. The method comprises the steps of obtaining a plurality of fault traveling wave magnetic field signals; performing the following steps on any signal: performing phase-mode transformation on the signal, extracting and decomposing a line mode component, determining a modulus maximum point, and determining the time corresponding to the point as a first fault traveling wave head arrival moment; carrying out clock synchronization on the moment, and obtaining a wave head arrival moment of a second fault traveling wave; obtaining a to-be-detected fault point and a line parameter; based on the wave head arrival moments of the plurality of second fault traveling waves, extracting a head end arrival moment and a tail end arrival moment; and performing fault positioning on the overhead line of the power distribution network based on the head end arrival time, the tail end arrival time and the fault line parameters. According to the fault positioning method for the overhead line of the power distribution network, interference to normal operation of the power distribution network can be avoided, and high-precision non-intrusive positioning of the overhead line of the power distribution network is realized through the tunneling magnetoresistive sensor.

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 control system and method for a steel wire traction type overhead rail inspection robot with a sliding contact line, and relates to the technical field of modern industry and infrastructure construction.The system comprises a steel wire traction control module and traction devices connected with the two ends of a rail through steel wires, the traction devices are provided with servo motors, and the servo motors are used for driving traction wheels to rotate; the movement control of the inspection robot along the track is realized; the sliding contact line power supply control module comprises a sliding contact line laid along the track and a power taking device carried by the inspection robot, and the sliding contact line is matched with the power taking device and used for providing continuous and stable power supply control for the inspection robot; the steel wire traction control module is further integrated with a steel wire tension real-time monitoring control unit, and the steel wire tension real-time monitoring control unit is electrically connected with the servo motor and used for dynamically adjusting the output power of the servo motor according to the tension data of the steel wire, so that the tension of the steel wire is kept within the preset optimal range. According to the invention, intelligent control of the inspection robot can be realized.

The invention relates to the technical field of power construction safety management and control, discloses a safety management and control detection method and system based on multi-modal data comprehensive analysis, and is suitable for safety monitoring and management of an overhead line construction scene. The system adopts a layered architecture and comprises a data access layer, a data analysis and processing layer and a service display layer, the data access layer collects data, and the data analysis and processing layer fuses and processes the data. The process comprises sensor calibration, time-space synchronous alignment, point cloud preprocessing, image feature enhancement, visual image and point cloud preliminary fusion, image defect identification and complementation, data fusion in BEV space, warning information generation and sending, timely reception and display of background warning information by a business display layer, and man-machine interaction display. According to the method, feature fusion of multi-modal heterogeneous data from different sensors can be realized, the safety problem of the construction process is efficiently identified, and the method has universality.

The invention discloses a live working robot on-line positioning accessory suitable for an overhead line, and relates to the technical field of overhead line maintenance. The structure of the live working robot on-line positioning accessory suitable for the overhead line in the prior art is optimized and improved; the three groups of wheel bodies are tightly attached to the cable to drive the hot-line work robot to move, and when the aging and damage areas of the cable need to be avoided, the shapes of the three groups of wheel bodies are timely adjusted to enable the three groups of wheel bodies to be timely separated from the cable one by one in sequence; the on-line positioning accessory for the hot-line work robot suitable for the overhead line has the technical effects that the on-line positioning accessory is convenient to use, the aging and damaged areas of the cable can be flexibly avoided as required during movement, and the trafficability and the applicability are relatively good.

The invention discloses a PINN and optical fiber sensing fusion-based line icing prediction method, and belongs to the technical field of overhead line icing monitoring, and the method comprises the steps: building a line state constraint between a reference working condition and a current working condition, and providing a physical constraint for PINN model training; measuring to obtain an overhead line vibration signal, performing selective weighting on a low frequency, extracting a main modal frequency, and constructing a low-frequency feature vector; using the temperature mean value as the temperature value of the overhead line, constructing a Brillouin spectrum data residual error, and inverting the temperature and strain; brillouin frequency shift features are extracted, and Brillouin frequency shift feature vectors are generated; inputting the low-frequency feature vector and the Brillouin frequency shift feature vector as conditions into a PINN model, and training the model; carrying out backtracking correction on prediction in a past time window by taking an on-site overhead line icing value as an anchor point; and predicting an icing thickness result of a future time domain output by the optimized PINN model. The overhead line icing thickness prediction precision can be improved, and the line operation and maintenance efficiency can be improved.

The invention discloses a 10kV overhead line adaptive evaluation method and system for non-power-cut operation, and the method comprises the following steps: obtaining the field data of a target line, and constructing the field data into a multi-dimensional evaluation feature vector according to a preset evaluation dimension system for non-power-cut operation; inputting the multi-dimensional evaluation feature vector into a non-power-cut operation adaptability evaluation model to obtain a comprehensive evaluation score and an optimization suggestion of the target line; outputting the comprehensive evaluation score and the optimization suggestion; wherein the non-power-cut operation adaptability evaluation model is constructed by the following steps: training to obtain an initial machine learning model; simulating a preset non-power-cut operation task flow in the digital twinborn body; and performing incremental training and parameter optimization on the initial machine learning model by using operation effect data fed back after actual operation of the simulation data vector. The problems of single evaluation dimension, model stiffness and the like in the prior art can be solved.

The invention discloses a power distribution overhead line icing measurement method, and belongs to the technical field of icing measurement, and the method comprises the steps: calculating the icing risk probability of a key position coordinate through an icing risk probability model, and constructing a high-precision sensor deployment multi-objective function through the combination of the icing risk probability, and carrying out the high-precision sensor deployment; constructing an asymmetric icing physical model to perform icing state analysis on the fused high-precision sensing data to obtain icing weight distribution and icing direction of the power distribution overhead line; and carrying out real-time early warning feedback on the icing weight distribution and the icing direction of the power distribution overhead line. According to the method, the ice layer weight distribution and the asymmetric direction of each key point of the power distribution overhead line are dynamically calculated by adopting a mode of combining a nonlinear fusion algorithm and a physical and mechanical model, and meanwhile, a risk probability model and a heuristic deployment optimization strategy are introduced, so that high-precision sensor precise layout and dynamic early warning feedback are realized; and the spatial resolution and response efficiency of icing monitoring are remarkably improved.

The invention provides a traveling wave signal feature extraction and fault identification method and system based on deep learning, and belongs to the technical field of power system fault diagnosis. The method comprises the following steps: deploying a monitoring terminal at a key node of a power distribution network, and collecting power frequency electric field, power frequency current and high-frequency traveling wave current data in real time; judging whether the power frequency electric field, the power frequency current and the high-frequency traveling wave current trigger wave recording or not, and reporting corresponding wave recording data after triggering; preprocessing the reported data; constructing and training a BP neural network model to obtain a traveling wave classification model; inputting the normalized discrete data into the trained traveling wave classification model, and outputting a fault category; if a fault occurs, judging a fault interval according to power frequency electric field change, power frequency current magnitude characteristics and high-frequency traveling wave current wave head polarity; and according to the judged fault interval, using a traveling wave fault distance measurement algorithm to obtain accurate positioning of a fault point of the overhead line. According to the invention, accurate identification and positioning of the power distribution network line fault are realized.

The invention relates to the technical field of state monitoring and fault diagnosis of power equipment, in particular to a distribution network overhead line and partial discharge live detection and positioning method of equipment along the line, which comprises the following steps of: 1, arranging a plurality of partial discharge signal detection points on the distribution network overhead line; 2, the central processing unit preprocesses the digital signals; step 3, the central processing unit carries out partial discharge identification on the preprocessed signal; 4, the central processing unit carries out positioning calculation on the partial discharge event; and step 5, the central processing unit outputs a partial discharge detection result and a positioning result, including the discharge source position coordinate, the discharge intensity and the risk level, and triggers an alarm mechanism if the risk level exceeds a preset risk threshold. Through efficient signal detection and accurate positioning calculation, not only can potential faults on the overhead line of the distribution network be found in time, but also an accurate reference basis can be provided for subsequent equipment maintenance, and the operation safety and stability of the distribution network are effectively improved.

A drive system for raising or lowering a sliding piece of a current collector for rail vehicles. The sliding piece is disposed on a positioning device of the current collector, and the sliding piece is configured to be brought into contact with an overhead line using contact pressure. The drive system includes a bellows drive which is actuated by compressed air to actuate the positioning device, and a pneumatic control unit having a control valve for supplying or withdrawing compressed air to / from the bellows drive. The drive system includes a detection line and a lowering valve for venting the bellows drive when pressure drops in the detection line, the lowering valve being a 3 / 2-way valve disposed in a pneumatic supply line between the control valve and the bellows drive.

The invention relates to the technical field of line fault monitoring, in particular to an overhead line health monitoring method based on a multi-dimensional monitoring sensor. According to the method, the change amplitude abnormal degree of operation data of different dimensions on a time sequence is analyzed on each monitoring unit of the overhead line, an abnormal time period is screened out, and a fault attention factor is determined according to the abnormal distribution continuous condition of multiple abnormal dimensions in the abnormal time period; and a more accurate fault assessment result is obtained by combining association among different monitoring units. According to the method, abnormal fluctuation and continuous stability analysis is carried out on the multi-dimensional data, and the spatial association condition of the overhead line is combined, so that the interference influence of fault assessment is reduced, and the accuracy and reliability of health monitoring are improved.

The invention discloses an overhead line foreign matter detection method and system based on a lightweight YOLO network, and relates to the technical field of power transmission lines. Multi-scene power transmission line images are collected through an unmanned aerial vehicle, a multi-scene power transmission line foreign matter data set is constructed, the images are amplified through a mixed data enhancement method, and a target image set is obtained; inputting the target image set into a preset target model to detect the foreign matter of the overhead line; if the foreign matter is detected, generating a foreign matter label; adding the foreign matter label into a preset 3D model diagram of the power transmission line; the foreign matter label comprises position coordinates and identification types of the foreign matters. The YOLOv5 model is improved to reduce the parameter quantity of the model, the performance improvement and real-time detection are realized, and the system can be carried on embedded equipment with limited storage space and calculation capability, such as a mobile terminal, so that the system can be deployed in an actual power transmission line inspection system to meet the actual application requirements.

The invention discloses a modeling method, device and equipment for a sling lifting net blocking system and a storage medium. The method comprises the following steps: acquiring working state parameters of a bearing cable under the overhead line crossing construction working condition, and determining an initial bearing cable curve based on a catenary formula, boundary conditions of suspension points on two sides of the bearing cable and the working state parameters of the bearing cable; constructing a finite element analysis model based on the initial bearing cable curve, and determining stress distribution data and deformation data of the bearing cable based on the finite element model; and under the condition that the stress distribution data and the deformation data meet preset engineering requirements, determining the finite element analysis model as a target mechanical analysis model. The technical effects of accurately simulating the stress and deformation of the bearing cable and guaranteeing the construction safety are achieved.

The invention discloses a fusion and modeling overhead line construction method, system and device and a medium, and the method comprises the steps: obtaining road detection data information, and constructing a construction simulation scene through the road detection data information; collecting construction condition information, and performing simulation construction in a construction simulation scene based on the construction condition information; in the simulation construction process, safety analysis is carried out, and construction hidden danger points are identified; and carrying out risk management and control on construction hidden danger points. Through a complete technical system of construction simulation scene construction, construction process simulation, safety analysis and risk management and control, the safety and efficiency of overhead line construction are remarkably improved. The virtual simulation technology and actual construction environment information are fused, scheme verification before construction and real-time risk prevention and control in construction are achieved, the mode that traditional overhead line construction depends on experience judgment is fundamentally changed, and a scientific basis is provided for construction decision making.

The invention relates to the technical field of line defect identification, and discloses an overhead line defect intelligent identification and positioning system, which comprises a span reference system construction module for constructing a span reference system; the catenary fitting module is used for fitting a catenary curve; the wire temperature inversion module is used for obtaining the real temperature of the surface of the wire through inversion; the temperature-induced sag expectation calculation module is used for carrying out iterative solution to obtain temperature-induced sag expectation; the candidate position scanning module is used for scanning to obtain a candidate position set; and the defect positioning module is used for generating a positioning coordinate in the span reference system when the transverse and vertical displacement ratio of the candidate position is greater than or equal to the lead defect threshold value. According to the method, the real temperature of the surface of the wire is inversed, the temperature-caused sag expectation is constructed, the influence of the temperature on the sag is corrected, the normal sag change caused by the temperature is prevented from being misjudged as a defect or missed detection of a real defect is avoided, a noise reference is established by a tower cross arm and other rigid structures, the defect is judged in combination with physical noise, and the defect recognition accuracy is improved.

The invention discloses a safe operation method for an aerial operation robot to quickly release an overhead line and a pressing walking device and an emergency quick release mechanism thereof, and has the advantages that the pressing walking device is integrated with the emergency quick release mechanism, a rotating seat of the emergency quick release mechanism is hinged with a fixed seat, and a torsion spring is sleeved on a hinge shaft; the two torsion springs are arranged on the two sides of the rotating base respectively, the two ends of each torsion spring abut against the fixed base and the rotating base respectively, the electromagnet is installed on the rotating base, and the pressing mechanism is installed below the rotating base. An iron core of the electromagnet extends out to be locked with the lock plate in a normal state, the pressing walking device can work normally, when an emergency occurs, the electromagnet can quickly act to enable the iron core of the electromagnet to retract to be unlocked from the lock plate, and at the moment, under the acting force of the torsion spring, the rotating seat immediately bounces and rotates to drive the pressing mechanism to quickly eject outwards to be opened so as to release the overhead line. The aerial operation robot can lift off and break away in time, so that damage is avoided.

The present application relates to the technical field of electrical safety, and more particularly to a low-voltage fire test system and method for forestry and animal husbandry areas, comprising a low-voltage power distribution cabinet, a power supply system, a wave recording system and a fault simulation area; the fault simulation area is used for simulating the fault of overhead lines with different diameters or insulation characteristics in various types of overhead line fault simulation tests according to pre-set test conditions; the power supply system is used for outputting alternating current with three-phase voltage when simulating different types of overhead line faults; the low-voltage power distribution cabinet is used for detecting the three-phase voltage of the bus and the three-phase current of the outgoing line under different overhead line fault types, so that the wave recording system detects whether there is arc breakdown and obtains corresponding fault simulation information. The present application can effectively analyze the short-circuit arc condition in the fault process by testing various fault types of overhead transmission lines and plant combustion, thereby reducing the probability of fire caused by power distribution network faults in forestry and animal husbandry areas.

The invention discloses an overhead line fault rapid positioning method and system, and belongs to the field of power system overhead line fault detection. According to the method, traveling wave acquisition assemblies are arranged at the head end and the tail end of an overhead line, and dual-mode redundant clock synchronization is used for guaranteeing time consistency of the two ends; obtaining a multi-feature fault signal, and carrying out preprocessing and weighted fusion to calculate the final time difference of the two ends of the fault traveling wave; correcting the wave velocity by combining the inherent electrical parameters of the line with the real-time environment and state parameters to obtain a dynamic propagation velocity; modeling is carried out according to the time difference, the dynamic wave velocity and the total length of the line, the distance from the head end to the fault point is solved, and a result is verified through signal attenuation characteristics. The method improves the positioning precision and reliability, avoids wrong positioning, shortens the troubleshooting period, and guarantees the stable power supply of a power system.

The invention belongs to the technical field of overhead line butt joint detection, and particularly discloses and provides a method for detecting overhead conductor steel strands after butt joint, and the method comprises the steps: building and correcting a digital twinborn model of a to-be-detected wire clamp based on a CAD drawing and three-dimensional scanning data of the to-be-detected wire clamp; extracting interface geometric parameters and identifying actual shapes of the interface geometric parameters; generating an initial gridding detection path based on a shape matching grid node distribution strategy; collecting a first ultrasonic data set according to the detection path and identifying an abnormal region; dynamically adjusting the grid density according to the abnormal index of the abnormal region, generating an updated detection path, and collecting a second ultrasonic data set; the first and second ultrasound data sets are combined to form a final detection data set. Through model correction and adaptive path planning, the defect of a fixed point distribution mode is overcome, the transformation from wide screening to accurate focusing is realized, and the defect identification accuracy and the evaluation reliability are remarkably improved.

The invention provides an unmanned aerial vehicle-based overhead line abnormal hidden danger identification method, device and equipment, and relates to the technical field of overhead line safety monitoring. The method comprises the following steps: dividing a target overhead line into a plurality of initial detection areas based on distribution parameters and design parameters of the target overhead line; and then, selecting a target detection area from the plurality of initial detection areas, and formulating a target inspection path for the target detection area by adopting a preset path design algorithm based on the parameter environment of the target detection area. And meanwhile, controlling the target unmanned aerial vehicle to inspect the target detection area according to the target inspection path. Furthermore, an inspection image shot by the target unmanned aerial vehicle in the inspection process is obtained, the inspection image is input to a pre-trained object detection model, and whether the target detection area has an abnormal hidden danger or not is identified according to a detection result output by the object detection model. According to the invention, the efficiency and accuracy of abnormal hidden danger identification of the overhead line can be improved.

The invention relates to the technical field of image segmentation, provides an image segmentation method and system for a cantilever system of a high-speed rail overhead line system supporting device, and solves the problems that defects in a metal part cannot be detected, and the defect recognition precision is low under high-frequency vibration noise interference. The method comprises the following steps: scanning a metal part of the cantilever system to generate a three-dimensional image, and collecting a stress wave signal of the surface of the metal part under the action of a dynamic load; based on the cyclic load parameter of the metal part, extracting the spectrum characteristic of the stress wave signal, and determining the energy distribution characteristic of the bolt joint by combining the geometric structure parameter of the bolt joint of the metal part; and fusing the three-dimensional image, the energy distribution characteristics, the temperature rise abnormal region and the electric field intensity distribution to generate a multi-source data set, and generating respective segmentation results of the fatigue crack and the insulation aging defect of the metal part in combination with the cyclic load parameters. According to the invention, high-precision collaborative segmentation of metal fatigue cracks and insulation aging defects of the cantilever system is realized.

The invention relates to the technical field of railway contact networks, in particular to an electrified railway anti-icing contact network and a control system.The device comprises a contact network wire and a brim flow guide structure arranged on the contact network wire in a sleeving mode; the upper part of the catenary wire is an arc-shaped surface, the middle part of the catenary wire is provided with a dovetail groove, and the lower part of the catenary wire is a conductive surface; the shape of the upper portion of the brim diversion structure is consistent with that of the upper portion of the contact network wire, the middle of the brim diversion structure extends towards the two sides to form brim-shaped diversion plates, and the brim-shaped diversion plates are used for guiding airflow to drive freezing rain water drops to slide towards the two sides so as to avoid a conductive surface; the brim-shaped flow guide plate is positioned below the dovetail groove; and after the cap-brim-shaped guide plate is sleeved on the overhead line system wire, the conductive surface can be in contact with the pantograph. Structural innovation and collaborative prevention and control logic are integrated, and the problems that an existing electrified railway anti-icing scheme is single, limited in function and insufficient in adaptability are solved.