6209 results about "Trackway" patented technology

The invention discloses a high-precision defect detection system for a track inspection robot, which relates to the technical field of track inspection and comprises a multi-mode visual acquisition module, a time sequence synchronization module, a data fusion processing module and a defect identification output module, by adopting a multi-modal visual fusion detection technology, various modal visual technologies of visible light vision, infrared vision and ultraviolet vision are combined, fusion processing is carried out on all modal image data, visual defects such as cracks and abrasion on the surface of a track can be clearly recognized through visible light vision, and the visual performance of the track is improved. The infrared vision can detect temperature abnormity of a track component to find out potential poor contact and other problems, the ultraviolet vision can be used for detecting corona discharge and other phenomena, track information is comprehensively obtained, the accuracy and reliability of defect recognition are effectively improved, defects which are difficult to find in a single mode can be detected, and the detection efficiency is improved. And powerful support is provided for safe operation and maintenance of the track.

The invention discloses a circulating type gravity energy storage transportation system which comprises a master controller, an annular rail, a high-position storage yard and a low-position storage yard, a transportation train is composed of a plurality of carriages which are flexibly connected and arranged on the annular rail, a low-position running rail is arranged on the annular rail, the high-position running rail is provided with a linear loading and unloading section, and the low-position running rail is provided with a linear loading and unloading section. A plurality of grabbing parts are arranged on the high-position storage yard and the low-position storage yard and move back and forth between the loading and unloading section and the stacking area, and the hoisting device is electrically connected with the master controller. By means of the double-circulation design of train circulation operation and heavy block rapid loading and unloading, the core pain points that an existing gravity energy storage system is not coherent in operation and low in efficiency are effectively solved, and the energy storage efficiency is improved. And a reliable system solution is provided for realizing large-scale, high-efficiency and fast-response gravity energy storage commercialized application.

An intelligent fault-in-rail analysis method based on multimodal fusion learning. Ultrasonic analysis data of the rail and high-definition rail surface images taken by line scan cameras are exploited in combination to detect and display internal and surface faults of the rail through different renditions using multimodal data. Rail DEtection TRansformer (R-DETR) technology or a You Only Look Once (YOLO) inspection machine-learning algorithm are employed in a deep convolutional neural network to analyze B-scan and rail surface image data to recognize rail line faults. After obtaining expressive data through data enhancement by computer processing, faults are recognized and pinpointed using the deep convolutional neural network learning algorithm. Analysis results are corrected with expert systems. The disclosed automatic ultrasonic fault-in-rail inspection solves the problem of slow detection and difficulties in tracking faults in everyday routine maintenance while also protecting the safety of rail operation and maintenance personnel.

The invention provides a railway track periodical intelligent monitoring method based on the Internet of Things. The railway track periodical intelligent monitoring method comprises the steps that track geometric deformation data and track temperature distribution data are collected through sensing nodes deployed beside a track and on the track; extracting abnormal sections in the track geometric deformation data based on time window segmentation, and mapping the abnormal sections to a space grid of the track temperature distribution data to generate a deformation-temperature incidence matrix; calculating a track stress change gradient by combining the matrix and historical track temperature distribution data, and generating a track health degree evaluation index; and when the track health degree evaluation index meets a preset degradation condition, inputting the time sequence multi-source fusion data into a deep learning track state prediction module, and outputting a track failure risk level. According to the invention, the efficiency, accuracy and intelligent level of railway track monitoring can be improved, and the safety and reliability of railway transportation are guaranteed.

The invention relates to a railway bridge post-earthquake traffic safety probability evaluation method and device, which are applied to the technical field of traffic safety, and the method comprises the steps: obtaining an earthquake-induced damage value set of each component through a probability distribution function of different material parameters of a railway track-bridge system; the method comprises the following steps: acquiring a mapping relation between the earthquake-induced damage of a key component and track irregularity through a balance differential equation of a bridge and railway track structural mechanical model, and acquiring earthquake-induced track random irregularity samples of different components based on an earthquake-induced damage value set of each component and the mapping relation between the earthquake-induced damage of the key component and track irregularity; constructing a power spectrum of the track irregularity caused by vibration of different components; establishing a rapid prediction model of the driving performance indexes on the axle after the earthquake through the earthquake-induced track irregularity sample and the coupling dynamic response result; through a Monte Carlo method, based on the earthquake-induced track irregularity power spectrum and the rapid prediction model, the overrun probability and the confidence interval of the driving safety on the axle after the earthquake are rapidly and accurately obtained.

The embodiment of the invention provides a multi-unmanned aerial vehicle cooperative surveying and mapping method and system for areas along a railway, and belongs to the technical field of railway surveying and mapping. The method comprises the steps that the unmanned aerial vehicle collects monitoring data in the flight process; the relative position and posture between the aircrafts are dynamically adjusted, and an observation configuration with variable baseline parameters is constructed; laser ranging modules carried by the unmanned aerial vehicles are controlled to execute synchronous ranging operation, and multiple sets of laser point cloud data covering the railway structure area are generated; performing coordinate registration and fusion on the collected laser point cloud data, and combining position information and attitude information of each unmanned aerial vehicle; and extracting geometric dimension parameters of the railway structure from the compensated three-dimensional model, and outputting the geometric dimension parameters as measurement results. According to the scheme, high-precision non-contact measurement of geometric dimension parameters such as the track gauge, the height difference and the roll angle of a railway track structure is achieved.

The invention provides a rail turnout foreign matter detection and type analysis method and system, and the method comprises the steps: arranging a first camera group at the front end of a train, recognizing the position of a turnout through a preset target detection model, and calibrating foreign matters in the turnout through a preset foreign matter detection model; shooting an image calibrated to the foreign matter in the turnout through a second camera group as a to-be-analyzed image; extracting a second boundary region rolled by a wheel on the foreign matter from the to-be-analyzed image through a preset wheel rolling track detection model, performing coarse classification on the foreign matter in the to-be-analyzed image to obtain a coarse classification result, and selecting a boundary detection strategy to identify the first boundary region according to the coarse classification result in the foreign matter image; and respectively extracting corresponding texture features in the first boundary region and the second boundary region through a deep learning network, performing one-to-one mapping on the extracted texture features to obtain a mapping relation group, performing analysis through the mapping relation group to obtain a feature change rate, and performing analysis through a multi-feature analysis strategy to obtain a specific foreign matter type.

The invention discloses a rapid measurement method and system for geometric irregularity of a track in a turnout zone. The method comprises the steps that complete three-dimensional point cloud data of the surface of a railway turnout steel rail are obtained in real time through a multi-angle line structure laser scanner on a special detection vehicle body; accurate attitude and position data of the detected vehicle body in the measurement process are obtained in real time through an inertial navigation measurement unit and an odometer; obtaining a high-precision pose of a detected vehicle body through a robust dead reckoning method of an IMU (Inertial Measurement Unit) assisted by a speedometer dynamic lever arm value based on a variable wheel-rail contact point; constructing a turnout area three-dimensional point cloud model; extracting geometric irregularity key points of turnout steel rail point cloud from the turnout area three-dimensional point cloud model; calculating parameters of track gauge, horizontal and rail direction irregularity and unevenness; the special detection vehicle body can quickly and stably pass through a turnout area to complete continuous and accurate measurement of geometric irregularity of a track.

The invention relates to the field of rail transit equipment, and discloses a rail transit equipment multi-source sensing data real-time fault-tolerant decision-making system, which comprises a multi-source sensing module used for collecting rail environment and locomotive state data through a 3D laser radar, a binocular camera and a Beidou positioning terminal, including obstacle, turnout, signal lamp and locomotive position information; the data fusion processing module is used for carrying out preprocessing, redundancy check and feature extraction on the multi-source sensing data to generate a fusion sensing result; and the fault-tolerant decision module is used for judging the safety state of the track based on the fusion sensing result, triggering an alarm / braking instruction and executing self-checking logic when the sensor is abnormal. Through the combination of double groups of redundant sensors and a three-level progressive fault-tolerant strategy, closed-loop control from data acquisition to safety decision is formed, the system robustness under complex working conditions is remarkably improved, and an omnibearing safety protection barrier is constructed for rail transit equipment.

The invention discloses a rail transit fastener model identification system and method, and relates to the technical field of fastener overhaul, an initial image of a rail is acquired through an image acquisition module, and an image preprocessing module is used for preprocessing to obtain a reference image; the image analysis module inputs the reference image into a preset model for processing, completes segmentation of the fastener assembly and the steel rail assembly, and obtains segmented images; the positioning module is used for screening the images of part of fastener assemblies and the images of the rail bottom of the steel rail and restoring the images to the reference images; the feature acquisition module is used for acquiring a reference adjustment line based on the segmented image of the rail bottom, acquiring feature parameters of the partial components based on the segmented images of the partial components, and correcting by using the reference adjustment line to obtain reference feature parameters; and the model identification module is used for matching the reference characteristic parameters of the screening component with the data in the constructed database and outputting a corresponding fastener model. According to the invention, efficient identification of the models of the fasteners can be realized, and the identification accuracy is also guaranteed.

The invention provides a track board drilling parameter intelligent optimization method and system based on deep learning, and relates to the technical field of deep learning, and the method comprises the steps: recognizing a feature region in three-dimensional scanning data through a deep learning semantic segmentation network, building a local coordinate system, calculating hole site deviation, constructing a pose correction field, and achieving the intelligent correction of drilling process parameters. And an optimal drilling track is generated by using a state space search algorithm. The method can adapt to actual geometric errors of the track plate, the drilling precision and efficiency are improved, the drilling failure rate is reduced, and the manufacturing quality of the track plate is improved.

The invention relates to the technical field of positioning, in particular to a rail-mounted robot high-precision fusion positioning method and system. According to the method, the error compensation model of each track segment is constructed, dynamic correction is carried out in combination with real-time environment interference data, dynamic compensation can be carried out on pulse data generated by an incremental encoder in real time, accumulation of position errors is remarkably reduced, it is ensured that the position of the robot is more accurate, and the accuracy of the robot is improved. By fusing satellite positioning data, motion state data and pulse data after error compensation, the positioning precision of the orbital robot in each orbital segment is remarkably improved, and by monitoring the position deviation in real time and comparing the position deviation with a preset threshold value, the unqualified orbital segments can be repeatedly corrected according to needs, so that the accuracy of the orbital robot is improved. And the accuracy of the positioning result is ensured, so that the robot can adaptively optimize the positioning precision under different working scenes and environment changes, and the continuity of high-precision positioning is ensured.

Described herein is a lightweight, power-efficient edge computing system, called the Autonomous Power-efficient Track Inspection System (APTIS), designed specifically for railroad track component inspection, and methods for making same, using an edge-computing device equipped with a custom computer vision model for meticulous track inspection that employs advanced deep learning and AI technologies, enabling automated detection and evaluation of the condition of various track components in concert with built-in cameras for surveillance.

A system for guiding the movement of one or more load handling devices in operation includes: a) a first set of parallel tracks and a second set of parallel tracks, the first and second sets of parallel tracks sharing a common track, each track of the first and second set of parallel tracks providing a track surface; and b) a first load handling device and a second load handling device, each having a wheel assembly engaging with the track surface and with the track surface of the common track; wherein each track of the first and second sets of parallel tracks include only two guide surfaces extending from the track surface for guiding the first and second load handing devices along their respective first and second sets of parallel tracks.

An umbrella includes a vertical support having a track carried on an outer surface of the vertical support, the track extending longitudinally, and a canopy configured to switch between an open state and a closed state. The umbrella also includes a sliding collar coupled to the vertical support and configured to slidingly engage the vertical support to control an angle of the canopy with respect to the vertical support, a first arm coupled between the sliding collar and the canopy, and a second arm coupled between the vertical support and the first arm. The sliding collar has a housing defining a recess, an activation button slidingly received by the recess of the housing and switching between an extended state and a retracted state, and a locking device carried by the housing. The locking device is configured to pivot about the housing to selectively engage the track in the extended state.

The invention discloses a high-speed rail seamless track displacement real-time detection system based on Beidou navigation, and relates to the technical field of traffic engineering, a target locking module is used for receiving Beidou observation data by using a Beidou GNSS receiver, locking GNSS lock losing signals at various monitoring moments based on the Beidou observation data, and transmitting the locked GNSS lock losing signals to the target locking module; the GNSS lock losing signal comprises a GNSS interruption starting point, a signal lock losing time period and a corresponding track space position; the interruption compensation module is used for initializing a mapping vector according to a track state before a signal lock losing time period to form a track estimation sequence, and judging whether IMU drift tends to systematic deviation or not after modal residual verification; the reconstruction module is used for performing error compensation on track position points at all moments in a signal lock losing time period if the deviation tends to systematic deviation; and the identification module is used for carrying out feature extraction in a signal lock losing time period based on the reconstruction module, and delimiting a dominant source of the current displacement in a form of a spatial domain angle.

The utility model relates to the technical field of rail travelling cranes, and discloses travelling crane rail cleaning equipment which comprises a rail body and a support arranged on a travelling crane, a scraper bucket used for cleaning the rail body is arranged on the support, the scraper bucket is in contact with the rail body, and the travelling crane rail cleaning equipment further comprises a shell arranged on the scraper bucket and used for cleaning the rail body. A mounting area is arranged on the surface of one side close to the track body; the rack is arranged in the mounting area on the shell; the rotary driving assemblies are arranged on the rack, and the two rotary driving assemblies are arranged side by side; the vibrating mechanism is arranged on the rack and connected with the rotation driving assembly; and the driving assembly is arranged in the mounting area on the shell and is connected with the rotation driving assembly. According to the travelling crane rail cleaning equipment, the cleaning efficiency and quality are improved, the abrasion and energy consumption of the equipment are reduced, and a powerful guarantee is provided for safe and efficient running of travelling cranes.

The invention discloses a portable insulating single-mast moving lifting platform, and relates to the technical field of lifting platforms, the portable insulating single-mast moving lifting platform comprises a controller platform, insulating rubber crawler belts are symmetrically mounted on the end faces of the two sides of the controller platform, a sliding groove is formed in the inner side of the controller platform, and a supporting groove plate is slidably mounted on the inner side of the sliding groove; the controller platform is scientific and reasonable in structure and convenient to use, through multi-directional supporting, the controller platform can stably move to guarantee safety when an operator is carried on the top, it can also be guaranteed that the controller platform can stably move on the uneven terrain, the use safety is improved, and the practicability is high. The application range of the high-altitude operation device is expanded, the use convenience is further improved, the mast does not need to be lifted for multiple times to adjust balance through local movement, the comfort of operators is further improved, and meanwhile the high-altitude operation efficiency is improved.

The invention provides an arrangement method of a steel fishway structure capable of automatically pulling and stretching along with water level changes. The arrangement method comprises the steps that the water level difference of an inlet and an outlet of a fishway is monitored in real time; the buoyancy driving assembly is triggered according to the water level difference to drive the steel fishway subsections to move along the rails; calculating the telescopic length based on the water level difference and the fishway base length to ensure that the gradient is within the design range; the track motor is controlled to adjust the cable-stayed angles and gaps of the fishway sections; the gradient error is corrected in real time through the tilt angle sensor; the distribution density and the opening-closing angle of the guide plates are dynamically adjusted according to the flow speed and the water depth, and vortex is inhibited; the water temperature change is monitored, the thermal deformation compensation amount is calculated, and deformation is absorbed through the elastic sealing assembly. The fish passing rate can be increased, the adaptability and stability of the structure are enhanced, and the device is suitable for complex hydrological environments.

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 a ballast track resistance measuring system and method, and relates to the technical field of track resistance detection, an image acquisition module is used for acquiring a grey-scale map and a depth map of a track bed, an image preprocessing module is used for preprocessing the grey-scale map, and a sleeper detection module is used for detecting the resistance of a ballast track by extracting sleeper characteristics in the grey-scale map. The real-time position and form of the sleeper in the ballast bed are obtained; the railway ballast height is measured through a railway ballast measuring module, the processing logic of the railway ballast measuring module is that a steel rail area, a sleeper area and a railway ballast area are determined firstly, and the actual value of the railway ballast height on the two sides of a ballast bed and the actual value of the railway ballast height in the center of the ballast bed are calculated through the steel rail area, the sleeper area, the railway ballast area and a depth map, namely, the railway ballast height; and the resistance measurement module is used for comparing the real-time position and form of the sleeper with the standard position and form to obtain the displacement and the pollution value of the sleeper, and finally integrating the information to complete the measurement of the ballast bed resistance. According to the invention, the ballast bed resistance can be measured simply and efficiently.

The invention discloses a track digital twinning real-time online deduction method and system, and belongs to the technical field of traffic simulation based on machine learning. The problem that in the prior art, a traditional traffic simulation and rail passenger flow dynamic allocation method is low in solving efficiency, and consequently the large-scale rail traffic network dynamic passenger flow allocation requirement is difficult to meet is solved. The method comprises the following steps: constructing a track road network model; generating road network passenger flow data and line shift data; further, simulation individuals of the train and the passengers are generated, path track matching based on time and space is carried out, and passenger-train dynamic traffic distribution and passenger-train interactive operation deduction are completed; according to the real-time detection data and the simulation result, dynamic line shift and passenger flow adjustment is carried out until a preset convergence condition is reached, and dynamic traffic checking is completed; and simulation is carried out to realize reduction and prediction of the passenger flow / flow direction of the whole line network. The method effectively improves the rail passenger flow dynamic distribution efficiency, and can be applied to large-scale traffic network simulation.

The invention relates to the technical field of track bridge engineering, in particular to a high-speed railway track-bridge system earthquake-caused residual irregularity prediction method, which comprises the following steps of: determining a target object, and constructing an earthquake-caused irregularity database based on historical earthquake oscillation data of the target object; based on the earthquake-induced irregularity damage database, constructing an earthquake-induced peak irregularity deep learning prediction model fused with the vibration mode superposition method, and performing prediction by adopting the earthquake-induced peak irregularity deep learning prediction model to obtain an earthquake-induced peak irregularity prediction value; calculating an earthquake-caused residual irregularity equivalent coefficient based on earthquake-caused peak irregularity and earthquake-caused residual irregularity in the earthquake-caused irregularity damage database; and earthquake-caused residual irregularity is predicted based on the predicted earthquake-caused peak irregularity predicted value and the earthquake-caused residual irregularity equivalent coefficient. According to the method, the engineering safety and reliability of the result are ensured based on the mapping relation of the probability assurance rate, and the method has high efficiency and safety and is suitable for practical engineering application.

The invention belongs to the technical field of data measurement, and discloses a high-speed railway ballastless track construction measurement method, which comprises the following steps of: carrying out internal reference and external reference calibration on a binocular camera of a track detection trolley; obtaining related data containing a binocular image, and carrying out space-time alignment processing on the related data so as to construct a prediction state vector; carrying out stereo matching on the binocular image to generate a prediction disparity map, and carrying out three-dimensional reconstruction on the prediction disparity map to obtain a track point cloud map; and extracting a track inner side point coordinate sequence and a track height program sequence from the track point cloud picture, and generating a corresponding track gauge table and a corresponding smoothness table. According to the invention, vision, three-dimensional reconstruction and inertial navigation technologies are integrated, and integrated detection of gauge, elevation and smoothness parameters is realized.

The invention relates to a self-adaptive control method for a rain and snow mode of rail transit, electronic equipment and a medium, and the method comprises the steps: comprehensively studying and judging a rain condition based on multi-sensor data and numerical weather forecast data, and calculating a weather grade in the rain and snow mode, the multi-sensor data including video detection data, laser radar data and rainfall data; whether a rain and snow mode is set or not is judged according to the weather level, if yes, the current track slip degree is evaluated according to the multi-sensor data, and the GEBR value is adaptively updated based on the slip degree; the CC calculates the running safety braking envelope of the train by using the updated GEBR value, and feeds back a slip detection result and a dynamic parameter adjustment result in real time; and the ATS dynamically adjusts the operation plan of the train according to the slip detection result reported by the CC, and optimizes the operation scheduling of the whole train. Compared with the prior art, the method has the advantages that self-adaptive management of the rain and snow mode is achieved based on the dynamically-adjusted GEBR, and the running safety and reliability of the train in the rain and snow weather are effectively improved.

The invention discloses an elbow connector forward and reverse intelligent deviation rectification virtual assembly blanking method, which comprises the following steps: carrying out 3d scanning on a new elbow and two old pipes, carrying out space matching on two axes of the new elbow and the axes of the two old pipes, searching an optimal assembly position, calculating boundary data of an annular track and extracting track deviation rectification characteristics; the track deviation correction characteristics are added into the preliminary cutting control data so as to compensate the track installation deviation when the cutting robot cuts; and generating final cutting control data. The device has the beneficial effects that a new bent pipe and an old pipe are scanned in a handheld 3d mode, point cloud data are recognized, a cutting route is simulated, final cutting control data, the walking route for controlling the cutting robot and control data for controlling the cutting torch to move on the sliding rail are obtained, automatic cutting is achieved in cooperation with the cutting robot, and the cutting efficiency is improved. Therefore, data support is provided for efficiently completing pipeline first-aid repair.

The invention relates to the field of intelligent traffic control, discloses an intelligent control method and system for a bidirectional driving wheel type sightseeing train, and aims to solve the problems of low efficiency, poor safety, weak adaptability and the like caused by dependence on a fixed track, path solidification and control lag of a traditional sightseeing train. According to the method, a dynamic environment map is constructed by deploying a front-back symmetric multi-mode sensor array and fusing laser radar, vision, millimeter wave radar and inertial data; an improved mixed A star algorithm is adopted to plan a global collision-free trajectory, high-precision tracking is realized in combination with model prediction control, bidirectional autonomous operation, multi-vehicle intelligent cooperation and full-scene adaptive control under a trackless condition are realized, and the traffic efficiency, safety and intelligent level of a scenic spot are remarkably improved.

The invention belongs to the technical field of track planning, and particularly relates to a track planning method for a track and non-track mixed region, and the method comprises the steps: dynamically distributing a path point sequence for an automatic guided vehicle, and switching a control mode according to the type of a region where a current target point is located: generating a first control instruction for path tracking in a track region; in the non-orbital area, the pose and curvature of the exit of the previous orbital area are used as initial reference quantities to plan a smooth trajectory, and a second control instruction is generated; constraint shaping is carried out on the first control instruction, the second control instruction is adjusted, it is ensured that the end point state of path tracking and the starting point state of trajectory planning meet the continuity rules of the position, the course and the curvature at the joint point of the two areas, and finally the instructions are sent to corresponding control loops to be executed. According to the invention, smooth and coherent navigation control of the automatic guided vehicle between the fixed track and the free driving area is realized.

The embodiment of the utility model belongs to the technical field of track locking mechanisms, and relates to a track locking mechanism and a conveying device, and the track locking mechanism comprises a base, a track supporting seat and a fastening assembly. The base comprises a bottom plate and at least two side plates, the two side plates are oppositely arranged at the two ends of the bottom plate, and a mounting groove is defined by the two side plates and the bottom plate; the track supporting seat is located in the mounting groove and provided with an inclined plane, and an included angle A is formed between the inclined plane and the bottom of the mounting groove; the fastening assembly is arranged on the base in a penetrating mode, and the fastening assembly and the side plates of the installation groove can jointly achieve transverse clamping and longitudinal clamping on the inclined face so as to fix the rail supporting base. When the fastening assembly abuts against the inclined face, force exerted on the inclined face by the fastening assembly is converted into longitudinal force and transverse force. The rail supporting seat is longitudinally clamped by the fastening assembly and the bottom plate and transversely clamped by the fastening assembly and the side plate at the same time, transverse and longitudinal vibration can be resisted, the stability of the rail locking mechanism is maintained, meanwhile, the rail supporting seat does not need to be fixed through a complex device, and the production cost is reduced.

The invention discloses a track robot inspection path planning method for a space steel structure, and the method comprises the following steps: S1, calculating the clear height of the space steel structure of each grid of a three-dimensional space, obtaining a passable three-dimensional space region, converting the three-dimensional space into a two-dimensional plane grid, and carrying out the calculation to obtain a key point coordinate set; s2, performing grouping solution according to the key point coordinate set to obtain an optimal path and a total path length; and S3, inputting the key point coordinates corresponding to the optimal path into a three-dimensional space, and verifying the rationality of the planned path. The problem of railway station steel structure complex three-dimensional space track path arrangement is solved, the optimal path is achieved through an algorithm, the optimal target combination with the shortest track length, the minimum robot number and the maximum inspection coverage rate is achieved, meanwhile, cruising power of the robots is saved, the walking time is prolonged, and the service life of the robots is prolonged. The space steel structure is widely applied to the industrial fields of railway stations, airports, rail transit, stadiums and the like.