833 results about "Contact network" patented technology

The invention relates to the technical field of railways, and discloses a railway passenger train operation state monitoring system based on artificial intelligence, which comprises a multi-modal sensor array, an edge AI judgment platform and a cloud intelligent decision center. According to the railway passenger train operation state monitoring method and system based on artificial intelligence, 28 parameters of a contact network, a running gear and the like are collected in real time through a multi-modal sensor array, an edge AI judgment platform utilizes a cross-modal fusion algorithm to deeply mine multi-source data potential association, the fault diagnosis accuracy is improved, and the fault diagnosis efficiency is improved. The cloud intelligent decision center dynamically aggregates gradient parameters of the edge end model based on federated learning, filters abnormal nodes and updates the abnormal nodes in an hour-level period, and constructs a digital twinborn model in combination with a Spark framework to realize dynamic parameter optimization; the fire-fighting early warning fusion model is linked with the air conditioner pressure and the compartment sealing state correction threshold value through a three-stage mechanism of parameter initial judgment, visual verification and environment verification, it is ensured that the early warning response time is shorter than 200 ms, and cooperation with the overall state of the train is achieved.

The invention discloses a railway catenary reliability evaluation method based on a Markov chain and a dynamic Bayesian network, and the method achieves the systematic monitoring and fault early warning of the operation state of catenary equipment through the construction of a catenary monitoring data collection system, and the utilization of multi-source data integration, multi-node multivariable modeling and hierarchical time scale monitoring. According to the scheme, comprehensive acquisition and analysis of key parameters of a contact network system are ensured by integrating various factors such as meteorology, load and equipment state. Through combined application of the dynamic Bayesian network and the Markov chain, multi-node and multi-variable modeling is carried out, and the dynamic influence of factors such as equipment aging, load fluctuation and external environment change on the system reliability can be accurately captured. In addition, by refining the time scale, performing high-frequency sampling on short-term variables such as weather and load fluctuation, and performing low-frequency monitoring on long-term factors such as equipment aging and corrosion, the state of the contact network is finely evaluated on different time scales.

The invention relates to the technical field of railway contact networks, and provides a railway contact network icing thickness prediction method and system. The method comprises the following steps: inputting meteorological environment parameters into a machine learning model, and carrying out dynamic calibration on icing medium parameters based on the meteorological environment parameters by utilizing the machine learning model to obtain calibrated icing medium parameters; obtaining an icing growth coefficient based on the meteorological environment parameters, the conductor physical characteristic parameters and the calibrated icing medium parameters; and inputting the calibrated icing medium parameters and the icing growth coefficient into a Makkonen model to obtain an icing thickness prediction value. According to the technical scheme provided by the invention, the key icing parameters are dynamically calibrated through machine learning, and the computational logic of the Makkonen model is optimized, so that the icing thickness prediction precision under complex meteorological conditions is improved, and the problem of prediction failure caused by insufficient environmental adaptability of a traditional static model is solved.

The invention relates to the technical field of high-speed railway operation and maintenance, and provides a 4C detection-based high-speed railway overhead line system completion acceptance method and system, and the method comprises the steps: collecting overhead line system image data, obtaining pose data and spatial positioning data of an inspection vehicle, carrying out the synchronous calibration processing, building a mapping relation, and obtaining a calibrated overhead line system image; inputting the calibrated overhead line system image into a multi-scale target detection model, outputting a detection result, performing pose correction on the detection result, and generating a three-dimensional positioning coordinate in combination with the mapping relation; constructing a time sequence feature vector, inputting the time sequence feature vector into the prediction model, outputting a defect evolution trend and a risk probability of the part, and grading the risk probability; and according to the risk level and the spatial positioning data, combining a knowledge graph driven rule engine, generating an intelligent work order, mapping the intelligent work order to field equipment, and collecting and feeding back a maintenance result. According to the method, the recognition and spatial positioning precision of the parts of the overhead line system is improved, and the safety and reliability of completion acceptance of the overhead line system of the high-speed rail are improved.

The invention provides a rail transit power supply digital twin system and a construction method, and relates to the technical field of data processing, and the method comprises the steps: constructing an urban rail transit power supply system digital twin model, achieving the digital virtualization associated with a physical entity, completing the model rendering, and displaying the state of the entity through a virtual model; according to the entity state, operating parameters of a substation and key equipment of a contact network are collected through a sensor and a hardware device; the operation parameters are cached by the station-level monitoring device body through the double-ring network architecture and then scheduled to a cloud platform communication ring network node, a data transmission path is optimized based on a load balancing strategy, and the data are uploaded to a cloud platform in real time. The management level can be improved, the operation and maintenance cost can be reduced, and a foundation is laid for intelligent operation and maintenance of a rail transit power supply system.

The invention discloses a method and a system for measuring the distance between cross positions of carrier cables of a rail contact network based on machine vision, and relates to the technical field of measurement of the distance between the cross positions of the carrier cables of the rail contact network. A laser radar and an infrared sensor are used for collecting depth information and temperature distribution data, and a multi-view image and depth temperature data are obtained; collecting the multi-view image and the depth temperature data to a central processing unit through a high-speed data transmission channel to obtain an initial data set; preprocessing the initial data set to obtain a high-quality data set; based on a deep learning algorithm and the high-quality data set, constructing a prediction model of the carrier cable and the intersection point, inputting sample data in the high-quality data set, and outputting prediction results of the carrier cable and the intersection point; and based on prediction results of the carrier cables and the intersection points, three-dimensional model reconstruction is carried out on the intersection positions of the carrier cables in combination with stereoscopic vision and structured light technologies.

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 discloses an energy storage rapid compensation method and system based on track overhead line system voltage fluctuation feature recognition, and relates to the technical field of track traffic traction power supply. The method comprises the following steps: synchronously acquiring voltage and current signals of the overhead line system, and extracting a composite feature vector containing disturbance root attributes and transient change rate; on the basis of the vector, a transient energy vacancy sequence covering the ultra-short-term future is output in real time through a prediction model fusing dynamic phasor analysis and a feedforward neural network; according to the sequence, a cooperative control strategy fusing overshoot and active damping is generated in combination with a proximity compensation principle and a voltage recovery state so as to drive an along-line energy storage unit; the strategy is executed in advance, compensation energy is injected, and finally double closed-loop correction is conducted based on the voltage residual error. According to the method, the problems of response lag, unclear disturbance identification, poor collaboration and lack of adaptive ability in the prior art are solved, and advanced, accurate, collaborative and self-optimized rapid suppression of the voltage fluctuation of the overhead line system is realized.

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 belongs to the technical field of droppers, and particularly relates to an intelligent pre-assembling platform and a pre-assembling method for an integral dropper of a contact network, and the intelligent pre-assembling platform comprises an automatic feeding system, an automatic laser etching system, a mechanical arm flexible assembling system, a tension / length detection system, a crimping process detection system, a bundling and labeling system, a rack, an auxiliary device and a quick-changing device, the dropper wire feeding system comprises a wire feeding wheel, a wire winding device, a straightening device, a fusing device and a servo length control device; the mechanical arm flexible assembly system comprises a six-axis mechanical arm and a crimping quick-change device; the auxiliary device comprises a secondary positioning mechanism, a heart-shaped ring / crimping pipe spacing control mechanism and a transfer printing device; the quick-change device is composed of a hydraulic cylinder, a crimping die and a quick-change transition block. According to the invention, the pre-assembling time of a single dropper is shortened, the dropper assembling process is shortened, the dropper pre-assembling device is suitable for dropper pre-assembling with different specification requirements, a crimping die is convenient to replace, meanwhile, personnel distinguishing is convenient, and finished products are not damaged in the bundling process.

The invention discloses a modulus-driven high-speed rail overhead line system full life cycle management method, and relates to the technical field of railway overhead line systems, and the method comprises the steps: analyzing the full life cycle of an overhead line system, and constructing a life stage block; collecting life stage data, and storing the life stage data into the corresponding life stage blocks; respectively constructing a representation model library, a data lake and a mechanism model library for the collected data according to a subject domain; establishing a collaborative periodic relationship based on the axial data relationship; building a digital-analog period integrated atlas relation; and performing operation processing to generate stage management information. The technical problems of unreasonable resource allocation, slow fault response and low management efficiency caused by the fact that information is difficult to share in real time and the intelligent level of full-life-cycle management is not high due to neglecting of contact and mutual influence of all stages of the full-life-cycle of the overhead line system in the prior art are solved. Concentrated storage and efficient management of data in all stages are achieved, and the technical effect of improving operation and maintenance management efficiency and power supply stability is achieved.

The invention discloses an overhead line system operation digital detection method and an evaluation system, and belongs to the field of rail transit overhead line system intelligent operation and maintenance. The method comprises the steps of collecting multi-source heterogeneous data, identifying data types and performing type-specific intelligent processing and feature extraction; evaluating a future state or risk in combination with the prediction model; applying an adaptive evaluation engine to fuse multi-source information and dynamically adjusting a strategy generation result; and finally feeding back and updating the model and logic. The invention also discloses a system comprising the sensor network, a processing unit, a prediction module, an adaptive evaluation engine and an updating unit. According to the method, through data classification processing, prediction, adaptive evaluation and closed-loop learning, the intelligence, accuracy, foresight and adaptive ability of detection and evaluation are remarkably improved, and an advanced quality control and ability evaluation means is provided for contact network automation / robot operation.

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 discloses a direct-current ice melting system of a subway overhead line system, which comprises an overhead line system and a running rail, and further comprises a subway rectification module and a direct-current ice melting module, the subway rectification module and the direct current ice melting module are connected with the contact network. The invention further discloses a direct-current ice melting method of the subway overhead line system. The direct-current ice melting device can stably output direct-current ice melting current in a large range to meet the ice melting requirements under different scenes, meanwhile, different wiring modes are adopted according to the ice melting requirements to melt ice on a plurality of contact nets or walking rails at the same time, and the operation time is saved.

The present application discloses a contact network device, a smart car, a smart network system and a transportation system. The contact network device is installed on the car. The smart network system includes a network information system and a network power supply system. The network power supply system includes a contact network connected to the contact network device. The contact network provides electricity and basic sensor information for the car. The network information system interconnects the contact network device, the smart car and the contact network information to form a vehicle network. The smart car equipped with the contact network device and the smart network system constitute a new transportation system. When the car is traveling on a road with smart network system facilities, the smart network system provides electricity and sensor information, and the car is driven by a person or automatically drives forward. When the car is traveling on a road without smart network system facilities, it is powered by a battery or an internal combustion engine, and can be driven by a person or a simple remote control driving system provides information to enable the car to move forward, solving the problems of electric vehicle charging, endurance and automatic driving application.

The invention discloses a self-adaptive grinding control method and system for a rigid contact network, and belongs to the technical field of maintenance of rail transit power supply equipment. The method comprises the following steps: acquiring pantograph-catenary action historical data of each position of the contact network along a busbar direction, and constructing a contact line damage index distribution curve; identifying a high damage interval based on the damage index, extracting roughness, ripple amplitude and oxidation thickness parameters, constructing a damage intensity vector, and calculating a damage grade score of each position by adopting a fuzzy comprehensive evaluation method; a preset polishing strategy library is matched according to the scoring result, a corresponding polishing wheel combination, the rotating speed and the contact pressure are determined, and a control parameter set is generated; the grinding device dynamically adjusts the working state according to the control parameters in the advancing process. The method achieves full-process self-adaptive closed-loop control of state recognition, strategy decision, execution control and quality feedback of contact line grinding operation.

The invention relates to a railway contact network contact line deicing method and device, the railway contact network contact line deicing device comprises an ice knocking unit installed on a first lifting unit, and the ice knocking unit is driven by an ice knocking driving unit to periodically knock the side face of a contact line; the device further comprises a first scraping plate, a blowing unit and a second scraping plate which are installed on the second lifting unit, the first scraping plate and the second scraping plate can abut against and support the bottom face contact face of the contact line, the blowing unit comprises a generating device and a blowing opening, and the blowing opening acts on the whole contact line. According to the deicing method and device provided by the invention, thick ice layers and thin ice residues can be sequentially removed step by step and layer by layer, residual ice is melted and blown, and residual ice residues or water stains are blown away. Ice covering the contact line, especially the bottom working face, can be thoroughly removed, the contact line and accessory equipment components cannot be damaged in the deicing process, and compared with manual deicing, the safety is high, and the working efficiency is high.

The invention relates to the technical field of industrial clusters, and discloses an industrial cluster industrial chain construction method and device, equipment and a medium, and the method comprises the steps: obtaining supply associated data and property right associated data of an enterprise of an industry category to which a target industrial cluster belongs; constructing a directed contact network based on the supply association data; constructing an undirected contact network based on the property right associated data; calculating property right connection degrees among the nodes in the undirected connection network, and accumulating the property right connection degrees to paths with corresponding node relations in the directed connection network according to a preset weight to generate a multi-source data enhanced network; and traversing all node paths in the multi-source data enhanced network, calculating the accumulated connection strength of each node path, and determining the path with the highest accumulated connection strength as the industrial cluster core industrial chain. According to the method, the universality, professional interpretability and objective accuracy of the constructed industrial chain are improved.

The invention provides a catenary deicing machine capable of automatically crossing a dropper, which can cross a dropper main body on a catenary main body and comprises a rack, a walking mechanism capable of walking on the catenary main body is arranged on the rack, and a cleaning mechanism and two groups of mounting frames arranged at intervals are further arranged on the rack. A gap for a contact network body to penetrate through is formed between the two sets of installation frames, multiple sets of installation bases are fixedly arranged in the two sets of installation frames and are arranged in a staggered mode, multiple sets of movable bases installed in a sliding mode are arranged in the installation frames, first elastic pieces are arranged between the movable bases and the installation bases, and hanging wheels are arranged on the movable bases. And the change gear shields a gap between the two groups of mounting frames. According to the deicing machine, the droppers can be automatically avoided when the overhead line system main body is deiced, so that continuous deicing operation is realized, the deicing machine does not need to be disassembled and assembled again when the overhead line system main body passes through the droppers, and the practicability and the deicing efficiency of the deicing machine are effectively improved.

The invention discloses a bolt attitude estimation method based on deep learning and template matching. The bolt attitude estimation method comprises the following steps: S1, collecting an image of a cantilever bolt of a contact network and making a data set; s2, marking a bounding box of the bolt image and hexagonal shape area information of the bolt; s3, identifying six angular points of the bolt through a deep learning method; and S4, obtaining 6D pose information of the bolt. According to the method, the angular points and the 6D poses of the bolts can be accurately recognized by combining deep learning and template matching, the precision of bolt pose estimation is greatly improved, meanwhile, the positioning and pose conditions of a plurality of bolts in one area can be detected in real time, efficient detection and segmentation of the bolts are achieved, and the processing speed and efficiency are improved.

The invention discloses a contact network state evaluation method and system based on adaptive empowerment optimization. The method comprises the following steps: collecting dynamic and static parameters of a contact network, calculating subjective and objective weights of each parameter by adopting an analytic hierarchy process and an entropy weight method, and calculating a static composite weight by adopting a combined weight method; historical degradation data of dynamic and static parameters of the overhead line system are collected, and the expected degradation rate of each parameter is obtained by adopting a time sequence neural network; calculating a parameter real-time degradation rate, and dynamically optimizing the static composite weight by adopting an adaptive method based on the real-time degradation rate and an expected degradation rate to obtain a dynamic composite weight optimization result; optimizing and updating the gain in the adaptive method; based on a dynamic composite weight optimization result, performing state evaluation on the contact network; the method and the system provided by the invention are not only suitable for contact network state evaluation, but also can be popularized and applied to other state evaluation fields, and have wide application prospects.

The utility model discloses a rapid grounding device for a rigid contact network, which comprises a main frame, a contact block and a locking assembly, a clamping part is constructed at the upper end of the main frame, and an extension part opposite to the clamping part is arranged at the lower end of the main frame; the contact block is movably arranged on the extension part, a clamping space is defined by the contact block and the clamping part, and the extension part is provided with a first spring which pushes the contact block to a contact net at the bottom end of the busbar and keeps a compressed state; the locking assembly comprises a locking piece and an unlocking piece which are in linkage, the unlocking piece is movably arranged on the clamping part, the lower end of the unlocking piece stretches into the clamping space, and the clamping part is provided with a second spring which pushes the unlocking piece to reset so as to drive the locking piece to reset to the locking position. The scheme has the effects that the busbar can be quickly clamped through the clamping part, and then the locking piece can be unlocked and the contact block can be released only by pulling the insulating telescopic rod to press the unlocking piece, so that the electric connection of the contact network is completed. And at the end, the contact block can be locked and the contact net can be released only by pushing the insulating telescopic rod.

The invention belongs to the technical field of intelligent detection and identification, and particularly relates to a contact network suspension state defect intelligent identification system, which comprises an abnormal index calculation unit, a defect category probability analysis unit, a data enhancement unit and a spatial proximity probability field inference unit, the abnormal index calculation unit is used for obtaining a normalized value and obtaining a composite abnormal index based on the normalized value and in combination with the position parameter; the defect category probability analysis unit is used for forming defect category probability distribution through logarithm likelihood function mapping; the data enhancement unit is used for obtaining a defect triple consisting of a defect category, a defect barycentric coordinate and a defect severity quantized value; and the spatial proximity probability field inference unit is used for automatically giving an alarm when the probability of any grid node exceeds an alarm threshold value. According to the invention, the defect detection rate, the positioning precision and the intelligent maintenance efficiency are obviously improved.

The invention discloses an overhead line system state evaluation method and system based on response type multivariable weighting optimization. The method comprises the steps of collecting dynamic and static parameters of a contact network, calculating subjective and objective weights of the parameters by adopting an analytic hierarchy process and an entropy weight method, and calculating a static composite weight by adopting a combined weight method; designing a dynamic response mechanism, if a response condition is met, dynamically optimizing the static composite weight to obtain a dynamic composite weight optimization result, and optimizing and updating the adaptive gain matrix; if the response condition is not met, keeping the dynamic composite weight optimization result and the adaptive gain matrix at the previous response moment; performing state evaluation based on a dynamic composite weight optimization result; the method and the system are not only suitable for contact network state evaluation, but also can be popularized and applied to other state evaluation fields with parameter coupling relations.

The invention discloses a machine account data correction method and device. The method comprises the following steps: obtaining pull-out value data of a railway overhead line system; inputting the pull-out value data into a pre-trained anchor section identification model, and outputting mileage data of the anchor section joint and the type of the anchor section joint; the anchor section recognition model is obtained by training a machine learning model according to historical pull-out value data of the railway overhead line system, mileage data of anchor section joints corresponding to the historical pull-out value data and types of the anchor section joints corresponding to the historical pull-out value data; according to the output type of the anchor section joint and the mileage data of the anchor section joint, determining the mileage data of the central column; correcting the machine account data according to the mileage data of the central column; the standing book data comprises the contact network line information, the strong association between the contact network waveform and the standing book data can be realized, the standing book data is corrected, and the standing book data accuracy is improved.

The invention discloses a power supply mode control method and control device for a dual-source locomotive, and the power supply mode control method comprises the steps: controlling the locomotive to enter an automatic power supply mode, and then obtaining a front networking signal and an upper networking signal sent by an automatic driving system of the locomotive in real time; wherein the front network signal is used for describing whether a contact network exists at a first preset distance in front of the running of the locomotive, and the upper network signal is used for describing whether the contact network exists above the current position of the locomotive; if the front network signal is the high-level signal and the upper network signal is the high-level signal, controlling the locomotive to enter an automatic pantograph-catenary mode; if the front network signal is the low-level signal or the upper network signal is the low-level signal, the locomotive is controlled to enter an automatic battery mode. According to the invention, automatic switching between the pantograph-catenary mode and the battery mode is realized, the operation steps of workers are reduced, the probability of machine damage accidents during manual switching of the modes is effectively reduced, and meanwhile, the energy utilization rate is improved.

The invention discloses a contact network insulator damage detection method and device based on few-sample transfer learning. The method comprises the following steps: inputting a to-be-detected contact network insulator image into a two-stage comparison suggestion coding network; the encoder performs feature encoding and feature extraction on the insulator image, and extracts feature representation of the image; the adaptive feature fusion module obtains an optimal fusion weight through adaptive weight learning; a hierarchical feature extraction module receives output of the adaptive feature fusion module, and extracts local position information of small objects in a shallow network of the encoder, global information of large objects in a deep network and local and global intermediate semantic information in an intermediate network layer; the inter-class and intra-class comparison suggestion coding module receives the output of the hierarchical feature extraction module, calculates the semantic similarity between different classes, and achieves the damage detection of the contact network insulator in a complex environment and a high-speed motion scene. According to the invention, the accuracy and efficiency of contact network insulator damage detection are improved.

The invention discloses a mobile contact network direct-current ice melting method, which comprises the following steps that: a monitoring vehicle and an ice melting vehicle are marshaled and run to a designated place, the two vehicles are de-marshaled, the ice melting vehicle is parked to the designated place, and the monitoring vehicle continues to run towards an ice melting section. The ice melting vehicle starts to electrically connect the wire clamp for construction after the contact network is subjected to electricity testing and grounding, and at the moment, the monitoring vehicle collects environment working conditions and icing state information in the ice melting section. And after construction of the electric connecting wire clamp and acquisition of monitoring information are completed, the monitoring vehicle sends an optimal ice melting current value to the ice melting vehicle, and the ice melting vehicle outputs an actual ice melting current after judging that the ice melting vehicle works normally. In the ice melting process, the monitoring vehicle reciprocates in the ice melting section, the icing degree of the contact network is monitored, and when it is monitored that icing disappears, an ice melting stopping instruction is sent to the ice melting vehicle. After ice melting is finished, the contact network is subjected to electricity testing and grounding at the ice melting vehicle, then the electric connecting wire clamp is removed, and the monitoring vehicle runs towards the ice melting vehicle. The technical problems that an existing overhead line system electric heating ice melting device is poor in mobility and low in utilization rate can be solved.