674 results about "Rail traffic" patented technology

The invention relates to the technical field of rail traffic safety detection, in particular to a railway freight train key part online monitoring system based on an unmanned aerial vehicle, which comprises an unmanned aerial vehicle control module, a multi-modal data acquisition module, an edge calculation module, a central processing module and a feedback execution module. A dynamic three-dimensional grid flight path is generated by fusing a train Beidou positioning signal and a millimeter wave radar sensing result, a system is provided with an infrared thermal imager, a laser radar and a high-speed polarization camera, bearing temperature, train body point cloud and a train coupler image sequence are obtained, and temperature rise area identification, structural deformation extraction and coupling state modeling are completed on the edge side. The central processing module outputs a multi-dimensional safety assessment result, and the feedback module generates a compensation control instruction and a graded early warning signal based on the risk fusion index. The method has the advantages of being high in autonomy degree, high in recognition precision and high in response speed, and is suitable for full-time structural intelligent inspection and early warning of the freight train in a high-speed operation environment.

The invention discloses an obstacle detection method and an obstacle detection system for a track, relates to the technical field of track detection, and is used for solving the problem of insufficient safety of track traffic. Comprising a data acquisition module, a data storage module, a data processing and fusion module, an intelligent analysis and decision module and an execution module which are in signal connection. The data acquisition module dynamically adjusts the working range and frequency of the sensor according to environmental changes. The collected data is processed and fused through the data processing and fusion module to generate a consistent orbit environment model, and a high-precision obstacle model is generated in combination with multi-source data. The intelligent analysis and decision-making module carries out classification, tracking and risk assessment on obstacles and generates a reasonable coping strategy according to the risk level. And the execution module executes related operation according to the generated strategy instruction. According to the method, track obstacles can be accurately detected, self-adaptive adjustment can be carried out according to dynamic environment changes, and the safety and operation efficiency of track traffic are remarkably improved.

The invention relates to a low-altitude aircraft course operation longitudinal safety interval control method, which comprises the following steps of: identifying a position coordinate of a controlled aircraft, and calculating a safety position envelope corresponding to the controlled aircraft according to the position coordinate; acquiring information of a route where the controlled aircraft is located, and performing judgment according to the route information: if the route where the controlled aircraft is located is a low-density route, performing flight safety interval management by adopting a fixed blocking concept based on a safety position envelope corresponding to the controlled aircraft; if the course of the controlled aircraft is a high-density course, performing flight safety interval management by adopting a moving block concept based on the safety position envelope corresponding to the controlled aircraft; wherein the route information at least comprises a cruise operation time interval of two adjacent aircrafts. Compared with the prior art, the flight route density is judged according to the flight route information, interval management is carried out according to different flight route densities by adopting a rail transit fixed block or movable block concept, and the method has the advantages of being high in safety flight control reliability and the like.

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 the field of rail traffic intelligent control, and discloses a rail obstacle real-time detection and braking system based on multi-sensor redundancy, which comprises at least two groups of sensing modules arranged at the front end and the rear end of a train, and each group of sensing module comprises a laser radar used for collecting three-dimensional point cloud data of a forward or backward rail area of the train; the binocular camera is used for acquiring color image data and depth image data in corresponding directions; and the robot controller is in communication connection with the sensing module and is used for receiving sensing data acquired by the laser radar and the binocular camera and executing obstacle recognition, redundant information fusion and brake control logic. By constructing a multi-sensor redundancy sensing structure based on the laser radar and the binocular camera, high-robustness recognition of a dynamic or static obstacle target in a complex orbit environment is realized, and the effect of remarkably improving the obstacle detection accuracy and the false alarm suppression capability is achieved.

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 rail traffic safety monitoring, and discloses a railway foreign matter invasion real-time monitoring and alarm system based on an SAR radar, and the system comprises an SAR multi-dimensional information depth perception module which extracts polarization, coherence, texture and other multi-dimensional features from SAR data; the multi-scale space-time attention fusion module adaptively focuses the key space-time change through a space and time attention mechanism to generate space-time fusion features; and the railway foreign matter invasion evolution knowledge graph construction and reasoning module integrates the space-time fusion features and multi-source information such as railway infrastructure, environment and historical events to construct a dynamic knowledge graph, and performs risk reasoning and alarming by using a graph neural network. According to the invention, through deep fusion of multi-dimensional perception, intelligent attention and knowledge graph reasoning, the accuracy, robustness and intelligent level of foreign matter invasion monitoring are significantly improved, and deep understanding and adaptive early warning of risks are realized.

The invention belongs to the field of rail traffic control, and provides a heavy-load group train wheel-rail adhesion cooperative control method which comprises the following steps: respectively establishing a heavy-load double-compiled group train dynamic model, a rail surface recognition model, a wheel-rail adhesion control model and a group operation control model; inputting the equivalent braking force or traction force of the wheel and the normal force of the wheel rail into the rail surface recognition model, calculating an estimated value of an adhesion coefficient, and inputting the estimated value into the group operation control model; and inputting the estimated value of the adhesion coefficient, the speed, time and wheel pair angular velocity of the pilot train and the speed, time and wheel pair angular velocity of the following train into a wheel-rail adhesion control model, calculating motor torque of the pilot train and the following train and an output logic decision value of the following train, inputting the motor torque and the output logic decision value into a group operation control model, and performing adjustment control to obtain the wheel-rail adhesion coefficient. The motor torques of the pilot train and the following train after adjustment and control are obtained; and inputting the adjusted and controlled motor torques of the pilot train and the following train into the heavy-load double-compiled group train dynamical model.

The invention provides a strip-shaped long-distance unmanned aerial vehicle sensing countering system and method along a railway, and relates to the technical field of rail traffic safety. The system comprises an unmanned aerial vehicle detection device arranged at a key node along a railway and used for detecting an unmanned aerial vehicle; the unmanned aerial vehicle countering device transmits a controllable interference signal to interfere with the unmanned aerial vehicle; the signal receiving and directional transmitting equipment is used for receiving, amplifying and redirectionally transmitting the interference signal or the radio signal transmitted by the unmanned aerial vehicle; the rear-end intelligent management and control platform is used for receiving the signal information, analyzing the threat level in real time, selecting a countering strategy and implementing directional interference through equipment; the method comprises the steps of equipment deployment, detection and early warning, data analysis, instruction issuing, signal emission and interference, and response and dynamic adjustment. According to the invention, the problems of insufficient coverage, poor identification precision and single countering means in long-distance and strip-shaped scenes along the railway in the prior art can be solved, and real-time sensing and dynamic countering of the unmanned aerial vehicle are realized.

The invention discloses a single board detection system and method, and relates to the field of rail transit, and the system comprises an adapter plug-in box which is provided with at least one first slot and at least one second slot, the first slot is used for connecting a detected plug-in, and the second slot is used for connecting an accompanying test plug-in; and the main control assembly is connected with the adapter plug-in box and is configured to send test information corresponding to the tested plug-in to the accompanying test plug-in when the tested plug-in is a first type of plug-in, determine a test result of the tested plug-in based on test data, and output a preset test signal to the tested plug-in when the tested plug-in is a second type of plug-in, obtaining a test result of the tested plug-in; and the accompanying test plug-in is configured to load configuration parameters corresponding to the test information so as to disguise the accompanying test plug-in as a target interaction plug-in of the tested plug-in, then interact with the tested plug-in and collect test data in the interaction process. According to the invention, the cost of developing special detection equipment for different plug-in types can be reduced, and the universality of the detection system is improved.

The invention relates to the field of underground engineering and rail traffic engineering, in particular to a deformation control method for a double-line shield tunnel to underpass an existing railway soft soil roadbed, which comprises the following steps: S1, determining a grouting reinforcement range; s2, pile position and grouting hole position lofting is conducted in the reinforcing area, and a groove is excavated; s3, construction is conducted after the MJS pile main machine is in place, and drill bit trial spraying is conducted before a drill rod is placed; s4, after the drill rod reaches the specified depth, jet grouting is conducted till the designed elevation is reached, and the MJS pile main machine is moved to the next pile position sample placing point; s5, after the MJS pile reaches the designed strength, a drilling machine is arranged in place, and a formed hole is drilled to the designed depth; and S6, grouting is conducted, and then grouting and grout stopping section construction is conducted. The method has the advantages that corresponding reinforcement measures are taken in combination with the model, the shear strength of the soft soil is improved, the shear damage risk of the soft soil is reduced, deformation of the soft soil roadbed is controlled in time, and safety and stability in the shield underneath pass construction process are ensured.

The invention discloses an urban rail transit automatic fare collection virtual transfer method and system, and the method comprises the steps: judging whether the station is a virtual transfer station or not according to the information obtained from an entrance gate, if yes, judging whether the last departure station and the current entry station are the same operation day or not, if yes, continuing to judge whether the last departure station is an associated virtual transfer station or not, and if not, continuing to judge whether the last departure station is an associated virtual transfer station; if yes, judging whether the distance from last outbound is within a preset transfer duration, and if yes, retaining a newly added transaction field about transfer; judging whether a virtual transfer station is available according to the information acquired from the exit gate, if so, judging whether the exit of this time and the entrance of the last time are the same operation date, if so, continuing to judge whether a continuous transfer condition is met, and if so, charging according to a billing rule and emptying a newly added transaction field about transfer according to a preset rule; and if the continuous transfer condition is not met, normally charging and filling in a newly added transaction field according to a preset rule. According to the invention, the transfer efficiency of the urban rail transit can be improved and enhanced.

The invention relates to the technical field of rail traffic rack railways, in particular to a rack railway transition section tooth entering method, a control system and a medium, and the method comprises the following steps: S1, monitoring train driving information received by a train; the train running information comprises a wheel linear speed, a wheel driving speed and a rotation angle of a bogie gear; controlling a driving device according to the wheel linear speed, and adjusting the angular speed of a bogie gear to enable the linear speed of the bogie gear to be matched with the wheel linear speed; s2, after the linear speed of the bogie gear is matched with the linear speed of the wheel, real-time position information of train running is monitored; a meshing posture point is preset according to the real-time position information, the wheel linear speed and the rotation angle of the bogie gear; wherein the meshing posture point is a point position where the gear is in a meshing posture; and S3, distance information of the train running from the meshing posture point to the toothed rail section is obtained based on the meshing posture point, the gear is controlled to conduct posture adjustment according to the distance information, and gear entering is kept when the gear is driven into the toothed rail section.

The invention relates to the field of rail traffic intelligent driving, and discloses a rail car safety state real-time monitoring and early warning system based on deep learning, which comprises a multi-modal data acquisition module for deploying sensors on key components of a rail car and acquiring time sequence data including vibration, temperature, pressure and operation parameters; the cross-modal feature conversion module encodes the collected time sequence data into a three-channel color image; the safety state evaluation module is used for performing deep modeling and feature learning on the three-channel color image, predicting a current state classification result of the rail car in real time, and obtaining a safety state evaluation result of the rail car; and the early warning and intelligent decision-making module is used for carrying out anomaly detection and alarm prompt when potential risks exist in the rail car according to the safety state evaluation result. According to the invention, high-precision early fault identification and automatic early warning are realized.

The invention belongs to the technical field of rail traffic rail detection, and discloses a method for online detection of a rail corrugation fault based on a sliding time sequence window. The method is realized by adopting a sliding time sequence window analysis processing method, a wavelength range band-pass filtering method and a weighted calculation and normal value ratio method for vibration acceleration signals acquired by a plurality of measuring point sensors on the same side of the train, so that missed judgment caused by value errors can be avoided; and misjudgment caused by non-rail corrugation frequency signal interference, wheel abnormity and the like can be avoided. Meanwhile, sliding window value judgment is carried out according to the preset track resolution length, and refined judgment and positioning can be carried out on the rail corrugation fault in combination with a kilometer post. According to the rail corrugation fault detection method, the monitoring result is accurate and stable, the requirement for system performance is low, and the requirement for a real-time online monitoring system of low-cost embedded equipment is met.

The invention provides a door-shaped steel bar optimization method and system based on ballastless track interface damage analysis, and relates to the field of track traffic, the method comprises the following steps: determining track interlayer bonding parameters of a ballastless track based on interface comprehensive mechanical property test data of a concrete material composite test piece of the ballastless track, and establishing a finite element model of the ballastless track; a service temperature field of the ballastless track is calculated, and equivalent simulation of shrinkage of the self-compacting concrete layer is completed; on the basis of the multiple structure optimization variables, multiple door-shaped steel bar optimization schemes are determined, and the track interface damage area and distribution of the ballastless track under the combined action of shrinkage of the self-compacting concrete layer and the temperature load are calculated by utilizing a finite element analysis method based on a finite element model of the ballastless track corresponding to the door-shaped steel bar optimization schemes; the method has the advantages that the early-stage interface damage risk is reduced, and the durability and reliability of the track structure are improved.

The invention discloses a platform unmanned aerial vehicle charging control method and system based on cooperative communication and a medium. Relates to the technical field of unmanned aerial vehicle control. High-precision positioning and docking are realized through cooperative communication between the track platform and the unmanned aerial vehicle in combination with global path planning and local path planning; the environment of the track platform is detected in real time, the flight path of the unmanned aerial vehicle is corrected in real time, the flight path of the unmanned aerial vehicle is dynamically adjusted, sudden interference of moving obstacles is avoided, and accurate docking is ensured; through cooperative communication of the rail platform and the unmanned aerial vehicle, a multi-target optimization algorithm, cooperation of global and local path planning and intelligent charging management, the limitation of an existing unmanned aerial vehicle positioning and alignment method in complex environments such as the rail traffic platform is effectively solved.

The invention relates to the technical field of rail traffic engineering, and discloses a tunnel supporting system and a method for controlling tunnel floating, the tunnel supporting system comprises a subway tunnel, the outer side of the subway tunnel is provided with a reinforcing soil body which is not in contact with the subway tunnel, and the top end of the reinforcing soil body is a soil layer to be excavated; a plurality of supporting piles are arranged on the left side and the right side of the reinforced soil body, every two adjacent supporting piles on the left side and the right side are fixedly connected through a plurality of supporting pieces, and a dragging pipe with one end penetrating and extending to the gap between the two supporting piles on the left side is arranged in the gap between the two supporting piles on the right side. The dragging pipe penetrates through the reinforced soil body and is located on the outer side of the subway tunnel, a plurality of grouting holes are formed in the dragging pipe, and according to the tunnel supporting system, the integrality of the soil body above the tunnel can be enhanced through grouting of the dragging pipe and the grouting holes, downward pressure can be provided, upward floating deformation of the tunnel is limited, and the safety of the tunnel is improved.

The invention discloses a railway marshalling station intelligent scheduling control method and system based on hierarchical reinforcement learning, and belongs to the technical field of rail transit. In the hierarchical reinforcement learning framework, the upper layer achieves a global marshalling priority strategy by using a deep Q network trained in stages and by means of dynamic reward function design; and the lower layer optimizes a PPO algorithm by means of a near-end strategy of dynamic action space cutting, and regulates and controls the state of the debugging equipment in real time. A security policy distillation technology is adopted in a marshalling station scheduling control process, and a security policy passing verification is extracted as a rule tree to serve as an initial policy for reinforcement learning, so that a training convergence process is accelerated. A transfer learning method is further applied, so that the method can adapt to the dynamic flow distribution requirements of marshalling stations of different scales. By adopting the technical scheme of the invention, the physical limitation and the operation safety standard of the railway marshalling station can be met as far as possible.

The invention belongs to the technical field of rail traffic safety protection, and particularly relates to a mountain railway foreign matter invasion monitoring method and system. Comprising the steps that S1, structure sensing data of the passive protective net are collected, whether foreign matter invasion exists outside a boundary or not is judged according to the structure sensing data, and the structure sensing data comprise vibration and inclination angle data of stand columns of the passive protective net; s2, upper track sensing data of the track area are collected, whether foreign matter invasion exists in the boundary or not is judged according to the upper track sensing data, and the upper track sensing data comprise video image information in the boundary and detection information of a three-dimensional laser radar; and S3, processing the structure sensing data and the previous sensing data, and generating alarm information. The invention further provides a mountainous area railway foreign matter invasion monitoring system which comprises a structure sensing subsystem, an upper railway sensing subsystem, a data center and a monitoring terminal and is used for achieving comprehensive monitoring of foreign matter invasion outside and inside a boundary, and reliable guarantee is provided for safe operation of the mountainous area railway.

The present invention is based on the object of specifying a method for blocking and / or unblocking track sections in which human errors in the context of incorrect manipulations can be reliably excluded.This object is achieved according to the invention by a method for blocking and / or unblocking a track section in rail-bound traffic, which method comprises the following method steps: a) by means of an application executed on a mobile device, a blocking of a track and / or a switch is requested in a control system used to control rail-bound traffic; b) with this request, a secret key is generated, which is exchanged between the mobile device and the control system; c) every transaction that now takes place between a security chief and a train dispatcher operating the control system is always secured in the background by the mobile device and the control technology using cryptological methods based on the secret key, and is mutually controlled with regard to the desired blocking and / or unblocking.This ensures that only persons / authorities with the secret key can perform locking and / or unlocking actions that affect only the track section and / or switch identified by this key. This reliably prevents inadvertent access to the locked elements by third parties.

The utility model relates to the technical field of rail traffic, in particular to an eccentric support type anti-falling guard rail which comprises a guard rail support, a walking rail and a guard rail, the walking rail is vertically locked at the middle bottom of the guard rail support through a first locking mechanism, a guard rail eccentric support with the top sleeved with an elastic sleeve shoe is arranged at the top of one side of the guard rail support in a clamped mode, and the elastic sleeve shoe is arranged on the guard rail eccentric support. The guard rail and the guard rail eccentric support are horizontally locked at the top of one side of the guard rail support through the second locking mechanism, the guard rail eccentric support and the elastic sleeve shoe are adopted to solve the problem that original cushion blocks are large in model number and prone to falling off, the transverse load is increased, the guard rail strength of the guard rail is further guaranteed, and the service life of the guard rail is prolonged. The eccentric support type anti-falling guard rail is convenient to install and not prone to falling off, meanwhile, the installation height is kept constant, the transverse load is high, and the strength of the guard rail is high.

The invention provides a rail vehicle part cleaning production line and method, belongs to the technical field of rail traffic, and aims to solve the problems of high cost, low efficiency, low cleaning degree and high working intensity due to manual cleaning of a brake unit of an existing rail train. Comprising a cleaning room, and a soaking tank, a spraying tank, an ultrasonic cleaning tank, an ultrasonic rinsing tank, a water blowing tank and a drying tank are sequentially arranged in the cleaning room in the length direction of the cleaning room; one side of the soaking tank and one side of the drying tank are each provided with a first conveyor used for conveying a mesh basket, one end of each first conveyor is located in the cleaning room, and the other end of each first conveyor extends out of the cleaning room; second conveyors perpendicular to the two first conveyors are further arranged outside the cleaning room. A sliding rail is arranged at the top in the cleaning room, the sliding rail is arranged in the length direction of the cleaning room, a sliding seat is connected to the sliding rail in a sliding mode, the sliding seat is driven by a motor, and a lifting appliance matched with the mesh basket is arranged at the bottom of the sliding seat. A traditional manual cleaning mode is abandoned, and the cleaning efficiency is improved.

The invention discloses an induction power generation and frequency modulation vibration reduction integrated ballastless track vibration reduction structure, and belongs to the technical field of track traffic. A track plate and a base plate are longitudinally laid along a track line, and the track plate is located above the base plate; the adjusting layer is arranged between the track plate and the base plate; an elastic vibration reduction layer is arranged between the base plate and the piezoelectric device layer, and the elastic vibration reduction layer is filled in a limiting structure in the base plate; a silicon steel sheet iron core structure of an electromagnetic coil is arranged in the elastic vibration reduction layer in the limiting structure; the piezoelectric device layer is located between the adjusting layer and the base plate and connected with the electromagnetic coil through a wire. The piezoelectric material and the magneto-rheological elastomer material are adopted, integration of induction power generation and frequency modulation vibration reduction is achieved, when the pressure is not enough to enable the piezoelectric device to output current, the magneto-rheological elastomer material still has the mechanical property of a common rubber elastomer, the whole structure still can guarantee the vibration reduction function, and meanwhile power-off protection is achieved.

The invention provides a sensor layout method and device and a train, and can be applied to the technical field of rail transit. The sensor layout method comprises the following steps: determining a plurality of to-be-screened position points for installing sensors in a train; clustering the plurality of position points according to the strain energy density and the information entropy of each position point, and determining at least one to-be-screened region according to a clustering result; the multiple position points, the to-be-screened area and mechanical and load data, obtained through pre-testing, of all the position points are input into a pre-constructed target layout model, at least one initial layout scheme is output, and the initial layout scheme comprises the number of sensors and the installation positions of the sensors; and optimizing the at least one initial layout scheme by utilizing a multi-objective optimization algorithm and executing multiple iterative optimization operations to obtain a target layout scheme.

The invention discloses an urban multi-layer traffic network modeling and toughness analysis method under the influence of rainstorm, and relates to the technical field of traffic control, a rainstorm ponding model is built based on historical rainfall information, and a runoff depth and a ponding depth are simulated based on the rainstorm ponding model; building a multi-mode traffic model based on SUMO software; a rainstorm ponding model and a multi-mode traffic model are integrated to construct a coupling model, ponding information is matched to a corresponding road through a road ID, failure mechanisms of different traffic modes under rainstorm ponding are obtained, ponding influences are considered for road traffic and rail traffic respectively, and corresponding influence parameters are set. Adjusting the road speed limit in real time and updating the route in real time; the SUMO simulation output result is utilized, the toughness index change in different scenes is calculated, the comprehensive traffic network toughness in different rainstorm scenes is analyzed from the four dimensions of topology, convenience, service and safety, the comprehensive traffic network toughness is evaluated, the dynamic capture of traffic characteristics is realized, and the analysis depth and breadth are improved.

The invention relates to the technical field of rail traffic engineering, and particularly discloses a protection mechanism for a subway platform, which comprises a subway platform body, an adjusting cavity is formed in the upper portion of the outer wall of the subway platform body, two adjusting mechanisms are jointly installed between the top inner wall and the bottom inner wall of the adjusting cavity, a telescopic mechanism is installed in the adjusting cavity, and a buffering mechanism is installed on the outer wall of the telescopic mechanism. The adjusting mechanism comprises a spline shaft, an adjusting frame, an electric telescopic rod, a fixing frame and a telescopic gear. The telescopic gear can be driven to rotate through the adjusting frame, then the telescopic mechanism is driven to stretch out through power generated by door opening and closing, meanwhile, the telescopic mechanism can monitor the size of a gap between the telescopic mechanism and a train in real time, and after the stretching length is determined, the electric telescopic rod can push the adjusting frame to move upwards to cancel meshing; therefore, the extension length of the telescopic mechanism is automatically adjusted according to the actual gap size, and the application range and universality of the protection mechanism are expanded.

The invention provides a quality evaluation method and system for image correction and a rail transit detection device, and the method comprises the steps: carrying out the grading segmentation of a standard whole vehicle image with a single vehicle as a unit, and obtaining a standard key part region image; performing hierarchical segmentation on a target whole vehicle image to be evaluated by taking a single vehicle as a unit to obtain a target key component region image; performing feature extraction and feature segmentation on the standard key component region image to obtain a standard feature matrix; performing feature extraction and feature segmentation on the target key component region image to obtain a target feature matrix; and aligning the standard feature matrix with the target feature matrix, determining a feature change rate matrix, and evaluating the image correction quality based on the feature change rate matrix. According to the method, the whole vehicle image is segmented by taking a single vehicle as a unit, so that the computing power is saved, and the used memory is optimized. And the problem of quality evaluation after line scanning image correction is solved in a targeted manner.

The invention discloses a remote rail fault intelligent detection system based on big data driving, and relates to the technical field of rail traffic intelligent monitoring and state maintenance. The problems that a traditional detection method is high in manual dependence, slow in response and lack of prediction and self-repairing capacity are solved. According to the method, multi-source data are acquired through a fixed sensing network and a mobile inspection vehicle, a multi-scale digital twin is constructed and updated, and a probabilistic fault evolution graph is generated based on a random phase field model; collaborative judgment is carried out based on distributed edge computing nodes, and a maintenance scheme is generated by adopting a hybrid geometric distance retrieval immune memory bank; and finally, collaborative repair is executed through mixed reality and a micro-robot cluster, and continuous optimization of the system is realized based on federated learning and case-based reasoning. According to the system, integrated closed loop of track state sensing, fault prediction, intelligent decision making and self-repairing is achieved, and the detection foreseeability, the maintenance accuracy and the system self-adaptive capacity are improved.

The invention relates to a train positioning method based on a digital track map, which belongs to the technical field of satellite navigation and track traffic positioning, and is characterized in that a track is fitted by acquired track data to obtain a high-precision track curve model. Then, in the train positioning process, the train position calculated by the GNSS is matched with the fitted track curve, and a track constraint optimization method is adopted to correct the train position. A GNSS positioning result is projected to a nearest point of a fitting track curve, deviation correction is carried out in combination with track geometric information, positioning errors caused by environmental interference are eliminated, and therefore the relative positioning precision of a train is improved; according to the method, the train positioning precision is further improved by performing accurate fitting on the track line features and combining a global navigation satellite system (GNSS) positioning technology, the ambiguity fixing rate is effectively improved, and the problems of insufficient train positioning precision, low ambiguity fixing rate and the like in the prior art are solved.