156 results about "Track geometry" patented technology

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 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.

According to some embodiments, a method includes accessing track geometry data for a railroad track. The track geometry data includes historical measurements for a plurality of types of surface conditions of the railroad track over a period of time. The method further includes determining, by analyzing the track geometry data for a particular type of surface condition, a plurality of measurements that exceed a predetermined value. The method further includes identifying, by clustering the plurality of measurements that exceed the predetermined value, a particular track location on the railroad track as a progressive defect location. The method further includes determining, using a remaining useful life model and the track geometry data for the particular type of surface condition at the progressive defect location, a future time when the particular type of surface condition at the progressive defect location will exceed a predetermined limit.

The invention belongs to the technical field of rail transit, particularly relates to a line feature region identification method and system for rail geometric detection and electronic equipment, and aims to solve the problem of insufficient reliability of a monitoring result of line feature information of the rail geometric detection. The method comprises the following steps: determining a to-be-identified track line feature image; inputting a track line feature image to be recognized into the line feature region recognition model to obtain a line feature region recognition result output by the line feature region recognition model; wherein the line feature region identification model is obtained based on sample data of a line feature image and region image annotation training of the sample data; the line feature region recognition model is used for performing multi-feature judgment on fusion data after space-time synchronization of the to-be-recognized track line feature image and the track geometric detection waveform data to obtain a line feature region recognition result. According to the invention, high reliability of monitoring results can be realized.

The invention discloses a method and a device for positioning a steel rail telescopic regulator based on dynamic and static data fusion. The method comprises the following steps of: acquiring track geometric data, a railway track curve and machine account information of which the distance from the steel rail telescopic regulator is within a preset distance range; according to a railway track curve and ledger information, carrying out initial correction on the track geometric data; performing modal decomposition on the track geometric data after the initial correction by using an adaptive chirp signal modal decomposition algorithm; performing Wigner time-frequency analysis on the track geometric data after modal decomposition to generate a mileage frequency diagram; converting the mileage frequency diagram into a mileage energy diagram by utilizing a preset moving window edge spectrum analysis algorithm; according to the mileage energy diagram and the ledger information, the position of the steel rail telescopic adjuster is determined, the efficiency and accuracy of positioning the steel rail telescopic adjuster can be improved, the positioning time and labor cost are reduced, and then the stability and safety of high-speed railway driving performance are improved.

The invention discloses a thunder-vision fusion multi-sensor collaborative sensing system along a railway and an installation and calibration method, and belongs to the technical field of intelligent traffic and environment sensing. Aiming at the problems of low target detection precision, poor multi-source data fusion timeliness, dependence on manpower on sensor installation and calibration and the like in a complex scene along a railway, the system provides an innovative architecture of'layered sensing-dynamic fusion-autonomous calibration '. The multi-modal sensor array of a laser radar, a millimeter-wave radar, a visible light camera and a thermal infrared imager is deployed; autonomous optimization of sensor pose parameters is realized by using track geometric constraint and a deep learning model; an edge computing node and a cloud collaboration platform are integrated, and real-time target tracking, intrusion early warning and equipment state diagnosis are supported. Experiments show that the target detection accuracy rate of the system is greater than or equal to 98.5%, the false alarm rate is less than or equal to 0.3% and the self-calibration error of sensor installation parameters is less than 0.05 degree in the scenes of rain and fog, night, high-speed movement and the like, which are improved by more than 40% compared with the traditional scheme.

The invention discloses a multifunctional modularized track comprehensive detection system, which relates to the technical field of track detection, takes a lightweight moving trolley as a carrier, and integrates a system body, a positioning module, six multifunctional detection modules and a data processing module, and the system body is used for providing a walking platform, power supply and operation control. Control and synchronization of different function detection modules are realized through differential pulse signals; the positioning module is used for realizing position alignment of module data in the system; the multifunctional detection module covers visual inspection, track geometric parameter detection, steel rail profile detection, steel rail crawling displacement detection, turnout area detection and high-precision fastener detection; and the data processing module is used for processing the multi-source detection data and outputting a detection result and a maintenance suggestion. The problems that traditional equipment is single in function, low in detection efficiency and accuracy, high in manpower dependence and poor in data collaboration are solved, and scientificity and efficiency of track maintenance are improved.

The invention provides a vehicle-mounted track detection system, which comprises a vehicle bottom detection beam, an in-vehicle detection host and a remote control terminal, and is characterized in that the vehicle bottom detection beam is arranged at the compartment bottom of a target train and is used for acquiring train track data including image data and non-image data; the system comprises a sensor unit, a pre-processing unit, a data exchange unit and a power conversion module. The in-train detection host is arranged in a carriage of the target train and comprises a rail detection host, a switch and a fusion algorithm host; and the remote control terminal comprises human-computer interface software. The train bottom detection beam is arranged at the bottom of the train compartment, the collected train track data is processed by the in-train detection host, the accuracy of track detection is improved through image data, and the accuracy of track geometric parameter calculation under the variable speed condition is guaranteed.

The embodiment of the invention provides an inspection robot and a track inspection system, the inspection robot comprises a driving platform, the bottom of the driving platform is provided with a plurality of walking wheel sets oppositely arranged in the transverse direction, and the walking wheel sets are used for walking on a steel rail; the image detection module is located on the driving platform and used for collecting surface damage image information of the steel rail and damage image information of the interior of the steel rail and a track line; one end of the main control module is connected with the image detection module, the other end of the main control module is connected with an upper computer, and the main control module is used for uploading the image information collected by the image detection module to the upper computer. Track fastener system inspection, steel rail surface defect detection, steel rail ultrasonic base metal detection, steel rail electromagnetic detection (near surface), track geometric dimension, tunnel inspection and track plate foreign matter detection are realized through an image recognition technology, an electromagnetic detection module and a limit detection and ultrasonic detection module; the problems that manual inspection efficiency is low, and traditional public work inspection is single in detection item and low in detection precision are solved.

The invention relates to the technical field of rail transit, and provides a multifunctional rail detection system, which comprises a multi-source data acquisition unit, an optical fiber inertial navigation sensor, a laser array module, a dual-mode camera group, a radar speed measurement module and a temperature and humidity sensor, the data acquisition module is used for synchronously acquiring track geometric parameters, three-dimensional surface topography, inertial navigation data, real-time vehicle speed and environmental parameters; the dynamic processing unit is arranged in the compartment and comprises a data fusion controller, a self-adaptive Kalman filtering module, an anomaly diagnosis engine and an edge computing host, and the data fusion controller integrates multi-source data through a multi-thread parallel processing technology. On the basis of self-adaptive Kalman filtering and vehicle speed-parameter dynamic mapping, the track gauge detection error under the variable speed working condition is reduced to + / -0.3 mm from + / -3 mm, and the curvature radius calculation error lt is obtained; and the predictive maintenance model prolongs the overhaul period of the track by 40%, and reduces the operation and maintenance cost by 35%.

The invention discloses an electric passenger car track detection method, which comprises the following steps of: starting initialization after a track detection host is electrified, entering a waiting state after completion, reading a tag ID, judging the tag ID, starting detection if the tag ID is started, and continuing to detect the tag ID if the tag ID is not started. The track detection host obtains the transverse / vertical acceleration of a vehicle through the triaxial accelerometer, obtains a line radio frequency tag signal through the radio frequency tag reader, and obtains and calculates track information through the inertial navigation device. And the synchronous controller outputs mileage information to the rail detection host after acquiring a signal of the speed sensor, and triggers the laser triangulation assembly to acquire steel rail profile data. The rail inspection host obtains the transverse / vertical acceleration, the track, the mileage and the steel rail profile information of the vehicle, and solves the geometric parameter data of the rail. The technical problems that an existing rail detection operation mode is low in operation efficiency, real-time online detection cannot be achieved, and detection line data cannot truly reflect line dynamic parameters in the running state of the electric passenger car can be solved.

The invention provides a train positioning method and device, electronic equipment, a storage medium and a product. The method comprises the following steps: constructing a multi-objective optimization model; the multi-objective optimization model comprises a first objective function taking GNSS positioning error minimization as a target, a second objective function taking INS accumulative error minimization as a target, a third objective function taking INS attitude error minimization as a target and constraint conditions; the constraint conditions comprise a GNSS error boundary constraint condition, an INS error boundary constraint condition and a track geometric polynomial constraint condition, and the track geometric polynomial constraint condition is used for constraining that the position deviation of the train position obtained through current optimization is smaller than or equal to a preset deviation value; and performing optimization solution on the multi-objective optimization model by adopting a differential evolution algorithm to obtain optimal train position and attitude information. According to the invention, the positioning precision and reliability of the train in a complex environment can be improved, and the real-time requirement of train positioning is met.

The utility model relates to the technical field of track detection, and aims to provide a comprehensive inspection trolley for track state detection, which has the characteristics of convenience in use and high working efficiency. According to the technical scheme, the comprehensive inspection trolley for track state detection is characterized in that the comprehensive inspection trolley comprises a walking unit, a track flaw detection unit and a track geometric state detection unit, and the track flaw detection unit comprises a flaw detection host and an ultrasonic flaw detection wheel and an ultrasonic coupling mechanism which are arranged on the two sides of the walking unit; the track geometric state detection unit comprises a levelness measuring mechanism and track gauge measuring mechanisms arranged on the two sides of the walking unit.

The invention discloses a railway track online movement detection system and method, and relates to the technical field of rail detection, and the technical scheme is that the railway track online movement detection system comprises a detection management platform module, a signal processing module is arranged at the connection end of the detection management platform module, and a data processing module is arranged at the connection end of the signal processing module; the signal processing module comprises a track geometric parameter detection management module, a track fastener detection module and a foreign matter detection module, and the track geometric parameter detection management module comprises a track height detection module, a track gauge detection module, a track direction detection module, a horizontal detection module and a triangular pit detection module. The rail geometric parameter detection and management module comprises an image monitoring module, a laser photoelectric monitoring module and an ultrasonic monitoring module. The rail geometric parameter detection and management system has the beneficial effects that the working efficiency of an inspection mode is high, problems on a railway transportation line are found in time, a scientific and reasonable method is applied in time to maintain and repair the line, and good operation of the line and transportation safety are ensured.

Described herein are techniques for determining motion characteristics of trains traveling along a train track. In some embodiments, a processor may determine an estimated position of a train using an observed position obtained using one or more UWB antennas and an observed position obtained using one or more GNSS receivers. In some embodiments, a processor may access information specifying a geometry of a train track and determining the position of a train along the train track using an observed position determined using one or more UWB antennas and / or GNSS receiver(s) and the information specifying the geometry of the train track. In some embodiments, a processor may determine estimated positions of a train using the geometry of the train track and at least one observation of the train obtained using one or more positioning devices and select the position of the train from among the estimated positions.

The invention relates to the technical field of track settlement deformation measurement, and discloses a railway track settlement deformation measurement device and method, and the railway track settlement deformation measurement device comprises a detection vehicle, a detection sleeve and a settlement detection mechanism. According to the detection vehicle, multiple types of steel rails can be installed and detected through the arranged detection sleeve, the application range of the detection vehicle is widened, through linkage of the arranged settlement detection mechanism and the arranged detection sleeve, multi-angle and multi-azimuth deformation of the geometrical shape of the rail can be accurately detected, the accuracy of the detection value can be ensured, and the detection vehicle is convenient to use. The operation difficulty of workers is reduced, time and labor are saved, the structures supplement each other, and the combined use of various structures can more accurately detect the settlement of the rail and detect the state of the two steel rails when the rail is settled at the same time.

The invention discloses a railway construction simulation model generation method based on full-line design parameters, and relates to the technical field of model simulation. Line track geometric parameters, geological exploration data, bridge and tunnel structure parameters, construction mechanical performance indexes and environment constraint conditions are collected, a multi-source heterogeneous database is constructed, and a simulation model is generated; the method comprises the following steps: constructing full-line design parameters after space coordinate unification and data cleaning, establishing a space-time dependency relationship of construction elements based on a railway line segmentation topological structure, generating an initial construction logic network, and optimizing the construction logic network according to construction efficiency, a resource scheduling rule and a dynamic constraint condition, so as to obtain a construction result; parallel construction events in the railway construction process are defined, full-line design parameters and a construction logic network are mapped into a three-dimensional visual simulation model of railway construction through a parametric modeling engine, real-time railway construction data are introduced, the construction delay probability of railway construction is predicted, and the construction delay probability of railway construction is calculated. And determining whether to carry out construction process adjustment and construction resource redistribution.

The invention discloses a geometric irregularity state deterioration characterization method for a longitudinally-connected ballastless track on a high-speed railway bridge under a transverse earthquake, and the method comprises the steps: building a refined finite element model of a longitudinally-connected ballastless track-bridge system, and analyzing the damage characteristics and distribution rules of key components of the earthquake-caused track-bridge system; the characteristic of damage state degradation of key components of the earthquake-induced track-bridge system and a mapping mechanism are disclosed; then, based on the second theorem of Castlliano and the superposition principle, a geometric irregularity state deterioration characterization model of the longitudinally-connected ballastless track on the high-speed railway bridge under the action of the transverse earthquake is constructed, the geometric irregularity state of the longitudinally-connected ballastless track on the simply-supported / continuous beam bridge is mapped based on the deterioration characterization model, deformation data of the steel rail under the action of the earthquake are accurately quantified, and the accuracy of the deformation of the steel rail under the action of the transverse earthquake is improved. The method provides a theoretical basis for quickly judging the post-earthquake traffic capacity and maintenance engineering of a track-bridge system, ensures the operation safety of a high-speed railway, provides a theoretical basis for the design of a high-speed railway track-bridge, is beneficial to post-earthquake track repair and train operation recovery, and has a good practical value and a good popularization prospect.

The invention discloses a train positioning method based on vehicle-mounted IMU and track geometric feature data fusion, and belongs to the technical field of train positioning. The method comprises the following steps: preprocessing measurement data acquired by a single vehicle-mounted IMU, and dividing a line according to intervals to obtain vehicle-mounted IMU measurement data of each interval; vehicle-mounted IMU autonomous navigation calculation is carried out, and the initial running speed and the running mileage of the train in the interval are calculated through a vehicle-mounted IMU autonomous navigation calculation model; according to curvature information of track geometry, map matching is carried out based on autonomous navigation calculation information of a vehicle-mounted IMU (Inertial Measurement Unit); fusing the measurement information of the vehicle-mounted IMU with the geometric gradient and curvature information of the track; and calibrating the running speed of the train, and updating the position of the train. According to the method, output information of a single vehicle-mounted IMU is fused with geometric gradient and curvature information of a track, so that the running speed of the train is calibrated, and the train is further accurately positioned.

Systems and techniques for generating track geometry data (TGD) for railroad track analysis. In embodiments, rail profile data for each of the rails of a track may be obtained at regular intervals as a vehicle carrying the system traverses the track. The rail profile data may be validated, and reference points on the profiles of each of the rails corresponding to specific geometric features of the rails may be identified. The rail profile data may be filtered and processed to generate track geometry data. The track geometry data may include data for a plurality of data channels. The track geometry data may be transmitted to a backend system receives for further processing to determine rail defects, and to generate notifications and alerts based on the determined defects. The system utilizes machine learning algorithms and models for defect detection and validation.

A track monitoring system (and a method thereof) for mounting to a vehicle on a track comprising at least one rail is provided. The track monitoring system comprises a position and attitude measurement unit configured to determine a geographical position and attitude of the system during at least one pass of the vehicle on the track, a storage medium for storing track geometry data, a laser imaging and / or scanning unit configured to determine a position of the at least one rail relative to the track monitoring system, and a position of the at least one rail and surroundings relative to the track monitoring system during the at least one pass, a processor configured to determine, in the at least one pass, a first geographically referenced rail position based on the geographical position and attitude of the rail monitoring system and the position of the at least one rail relative to the system, determine, in the at least one pass, a second geographically referenced rail position based on the geographical position and attitude of the rail monitoring system and the position of the at least one rail and surroundings relative to the rail monitoring system, determine a third geographically referenced rail position based on the first and the second geographically referenced rail positions, and corresponding geographically referenced track geometry data, acquire, in a further pass, track geometry data associated with each position of the rail relative to the rail monitoring system, and the output of the position and attitude measurement unit, update, based on the third geographically referenced position of the rail, the track geometry data acquired in the further pass, and store updated track geometry data to the storage medium.

The invention discloses a railway roadbed dynamic safety assessment method combined with train-rail coupling analysis, and relates to the technical field of safety assessment, and the method comprises the steps: carrying out retrieval to obtain K unit train marshalling models of K passing trains and K train correlation parameter information; performing track state detection to obtain a track geometric flatness spectrum; obtaining roadbed mechanical parameter information of the local roadbed; establishing a roadbed-rail coupling model; integrating the K unit train marshalling models into the roadbed-rail coupling model to obtain a train-rail coupling dynamic model; and adopting the target construction task to drive the vehicle-rail coupling kinetic model, performing roadbed external disturbance simulation, and outputting a critical working condition space as a railway roadbed safety assessment result. According to the method, the technical problem that the railway roadbed dynamic safety assessment is not accurate enough in the prior art is solved, and the technical effect of improving the railway roadbed dynamic safety assessment precision is achieved by establishing the vehicle-rail coupling dynamic model and performing external disturbance simulation.

Systems and techniques for railway track monitoring and defect detection. In embodiments, a system captures and processes rail profile data for detecting defects on a railroad track. An on-board rail profile capture system, mounted to a railroad vehicle, captures rail profile data at regular intervals as the vehicle traverses the track. The system includes profile capture sensors and an inertial measurement unit to capture rates and angles of the vehicle's orientation. A main computer receives the rail profile data and generates track geometry data. A backend rail profile processing system receives the track geometry data, processes it to determine rail defects, and generates notifications and alerts based on the determined defects. The system utilizes machine learning algorithms and models for defect detection and validation.

The invention relates to the technical field of train aided driving control, and discloses a train aided driving control method and system based on four-eye vision. The method comprises the steps that a forward four-eye camera array is used for synchronously collecting a front track image sequence, multi-scale feature synchronous extraction is carried out, and a unified sensing data block containing track geometry, identification semantics and an obstacle contour form is directly generated. On the basis, a space-time probability distribution diagram of collision threats is generated by constructing a virtual track reference surface and analyzing the spatial relationship between the dynamic target and the virtual track reference surface, so that the upgrading from discrete alarm to continuous risk prediction is realized. A preliminary control instruction is generated by combining speed limiting constraint and system deduction, then the instruction is cooperatively adjusted by combining the real-time traction braking state and a load signal of a train, and finally an executable closed-loop control instruction set is output. According to the method, the efficiency of environment perception and the perspectiveness and accuracy of decision control are improved.

A method of aligning rail parameter measurements comprises receiving measurement data indicating variations in a parameter of the rail along the length of the rail derived from measurement runs performed at different points in time, each item of measurement data comprising a value for the parameter and an estimate of the location at which the parameter was measured. A signal is formed corresponding to each measurement run. Pairwise relative offsets are found between spatially overlapping segments in the signals corresponding to consecutive windows within the signals. For each signal and window the average relative offset to other signals is computed. Errors in the location estimates are determined based on the computed average relative offsets. The determined errors are used to refine the location estimates in the signal data.

The application provides a geometric position real-time correction method and system for railway ballastless track construction, and relates to the technical field of track construction. The method comprises: analyzing the design coordinates of the railway ballastless track, and dividing the construction line; extracting the geometric position gradient period of the pouring construction; anchoring the target monitoring feature space-time distribution of each time sequence stage; connecting the monitoring equipment for corresponding pouring state monitoring by taking the space-time monitoring feature chain as the regulation and control activation demand of the time sequence period; analyzing the geometric position correction parameters based on the monitoring state data to generate correction regulation and control information, and performing real-time correction control on the geometric position. The application solves the technical problem that the existing technology lacks recognition of the dynamic evolution of the track geometric position in the concrete pouring process, resulting in a mismatch between the correction opportunity and the material physical state, and further affecting the construction efficiency of the railway ballastless track. The correction is changed from post-correction to process adaptive regulation and control, and the forming quality and construction efficiency are improved.

The invention provides a magnetic levitation traffic rail irregularity monitoring and adjustable complete assembly. The magnetic levitation traffic rail irregularity monitoring and adjustable complete assembly comprises an adjusting mechanism and a rail irregularity monitoring device. The adjusting mechanism is arranged in the large pedestal below the track plate and is used for dynamically adjusting the height of the track in a hydraulic driving manner; the monitoring device is composed of wireless vision displacement sensing equipment and a receiving target, is installed on large pedestals on the two sides of a track plate, and captures track geometric deformation signals in real time. In the working process, the sensing device recognizes the displacement change of the receiving target, the data processing unit is combined to generate a track smoothness curve and calculate deviation parameters, and when irregularity is detected, the adjusting mechanism is automatically triggered to conduct accurate compensation. According to the assembly, high-smoothness intelligent maintenance of the whole period of rail installation and operation is achieved, the manual maintenance requirement is remarkably reduced, and the train operation safety and operation continuity are effectively improved.

The present invention discloses a method for evaluating the dynamic safety of railway subgrades in combination with vehicle-track coupling analysis, which relates to the technical field of safety evaluation and includes: retrieving to obtain K unit train formation models of K passing trains and K train-related parameter information; detecting the track state to obtain the track geometric flatness spectrum; obtaining the subgrade mechanical parameter information of the local subgrade; establishing a subgrade-rail coupling model; integrating the K unit train formation models into the subgrade-rail coupling model to obtain a vehicle-track coupling dynamics model; using the target construction task to drive the vehicle-track coupling dynamics model to simulate the external disturbance of the subgrade, and outputting the critical condition space as the evaluation result of the railway subgrade safety. The present invention solves the technical problem that the existing technology is not accurate enough in evaluating the dynamic safety of railway subgrades, and achieves the technical effect of improving the accuracy of the dynamic safety evaluation of railway subgrades by establishing a vehicle-track coupling dynamics model and simulating external disturbances.

1. The name of the design product: track detector. 2. The use of the design product: for track geometry detection. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view 1.

According to some embodiments, a method includes accessing track geometry data for a railroad track. The track geometry data includes historical measurements for a plurality of types of surface conditions of the railroad track over a period of time. The method further includes determining, by analyzing the track geometry data for a particular type of surface condition, a plurality of measurements that exceed a predetermined value. The method further includes identifying, by clustering the plurality of measurements that exceed the predetermined value, a particular track location on the railroad track as a progressive defect location. The method further includes determining, using a remaining useful life model and the track geometry data for the particular type of surface condition at the progressive defect location, a future time when the particular type of surface condition at the progressive defect location will exceed a predetermined limit.