35 results about "Rail infrastructure" patented technology

The invention provides an online rail fault diagnosis method and system based on knowledge transfer learning, and belongs to the technical field of crossing of intelligent monitoring and artificial intelligence of railway infrastructures. The method comprises the steps that S1, a server trains a model framework through a source domain data set to obtain a teacher diagnosis model; based on the target domain data set, training the teacher diagnosis model by adopting a mixed training strategy to obtain a student diagnosis model; s2, acquiring real-time multi-modal monitoring data from a target domain line by the edge computing equipment, compensating to obtain corrected data, and dynamically selecting the most important feature subset from the corrected data to form a simplified feature set; and S3, inputting the simplified feature set into a student diagnosis model to obtain a student fault diagnosis result and confidence thereof, and introducing a D-S evidence theory to generate a student fault diagnosis report. The method has the advantages that the accuracy, the real-time performance, the cross-domain adaptability and the overall system safety of railway track fault diagnosis are greatly improved.

The invention relates to the technical field of railway infrastructure disease identification, and discloses a railway infrastructure crack segmentation method, a readable storage medium and computer equipment, and the segmentation method comprises the steps: obtaining a data set of a railway infrastructure crack image; marking images in the data set, and dividing the data set according to a proportion to obtain a training set and a test set; a multi-head self-attention module and a triple attention module are embedded in a YOLO11 cross-scale trunk in parallel, a data enhancement strategy is combined, a decoupling Anchor-Free instance segmentation head is designed at a detection head, and an improved YOLO11 model is obtained; training the improved YOLO11 detection model based on the training set to obtain a railway infrastructure crack segmentation model; and inputting the test set into the railway infrastructure crack segmentation model to obtain a test result and a railway infrastructure crack segmentation result. According to the invention, the accuracy of detection and segmentation can be effectively improved, and the practicability of detection and the engineering application value are remarkably improved.

The present invention provides a monitoring system (104) comprising at least two interconnected sensors (102a, b, c) for monitoring events or situations in a traffic infrastructure (100) by detecting vibration at multiple sensor locations, wherein each sensor (102a, b, c) is integrated in a housing of an electrical connector directly connected to a traffic infrastructure equipment for deriving vibration patterns (109a, b, c) from the detected vibration, a method for monitoring events or situations in a traffic infrastructure (100) using a monitoring system (104) and a traffic infrastructure (100), in particular railway infrastructure, provided with such monitoring system (104).

Energy system (1) for supplying a railway infrastructure with electrical energy, wherein the energy system (1) comprises: - a plurality of wind energy installations (2) arranged along a railway section of the railway infrastructure and in the immediate vicinity of a track of the railway section and designed to generate electrical energy by means of the wind generated by a passing rail vehicle (3), and - a plurality of energy transmission installations (4) coupled to the plurality of wind energy installations (2) and designed to supply the generated electrical energy directly to the railway infrastructure.

A portable rail clamp mount assembly configured to be installed on a railway without requiring any modification to the existing rail infrastructure is described herein. In various embodiments, the rail clamp mount assembly may comprise a set of one or more horizontal base components removably attachable to and positioned beneath a set of tracks of a railway and at least one vertical component attached to the set of one or more horizontal base components and configured to support railway equipment positioned proximate to the railway. For example, the railway equipment may include one or more devices for operating a railroad or railyard. Each of the set of one or more horizontal base components may include at least one tie configured to engage an outside edge of the set of tracks when attached to the set of tracks.

Visibility of a railway infrastructure asset (e.g. trackside railway signal 104) to a driver 107 of a train 103 on a railway track 102 is determined using a computer model modelling (e.g. in three dim

1. The name of the design product: double track flaw detector single probe wheel alignment structure. 2. The use of the design product: for ultrasonic flaw detection of steel rails in railway infrastructure. 3. The design features of the design product: in the frame structure. 4. The picture or photo that best indicates the design features: perspective view.

The invention discloses a high-speed railway roadbed hidden danger intelligent identification system based on infrared image analysis, and belongs to the technical field of railway infrastructure detection. The system comprises an infrared image acquisition module, a visible light image acquisition module, an environment parameter acquisition module, an image fusion module, an environment correction module, a thermal anomaly detection module, a hidden danger classification module and a space positioning module. The system fuses infrared and visible light images based on an attention mechanism, eliminates the influence of environmental factors based on environmental parameter adaptive correction, extracts spatio-temporal features from an image sequence to detect temperature anomaly, and intelligently classifies hidden danger types and severity based on form and temperature features. And mapping the abnormal region to an actual spatial position and generating a visual distribution map. According to the invention, high-precision, high-efficiency and high-reliability intelligent identification of the hidden danger of the high-speed rail roadbed is realized, the detection rate reaches more than 95%, and technical guarantee is provided for safe operation of the high-speed rail.

The application provides a high-speed railway infrastructure detection data processing method and device, and belongs to the high-speed railway data processing field. The high-speed railway infrastructure detection data processing method comprises the following steps: acquiring detection data, wherein the detection data comprises structured data and unstructured data; performing mile calibration on the structured data by using a dynamic functionalization feature modeling alignment method; performing data cleaning on the detection data; constructing an intermediate data model for mixed storage of the structured data and the unstructured data, and performing mile correction on the unstructured data; constructing a data quality scoring model for scoring the detection data; and storing the detection data through the intermediate data model when the score of the detection data meets the requirements. The method optimizes the mile correction method of the detection data, and improves the mile correction accuracy of the detection data. Meanwhile, the intermediate data model is constructed for storing the detection data, and the problem of multi-source data fusion difficulty can be overcome.

The invention discloses a railway special line intelligent inspection robot system and a multi-mode sensing method thereof, and the system comprises a crawler-type mobile platform which is used for autonomously moving on a railway track and under complex road conditions along the line; the multi-mode sensing module is installed on the crawler-type mobile platform and used for collecting multi-source heterogeneous data of the railway infrastructure and the environment, therefore, the multi-mode sensing module is adopted, full-dimension recognition is achieved, the missing detection rate and the false detection rate are greatly reduced, the crawler-type mobile platform is adopted, the crawler-type structure is high in road holding force, the anti-interference capacity is outstanding, and the reliability of the system is improved. The robot can flexibly adapt to scene seamless switching of a track, a soil road along the line and a ramp, can complete operations such as close-range review and slight disposal of hidden dangers through the mechanical arm, makes up for the defect that existing equipment has no execution capability, does not need manual intervention into a closed loop, and greatly improves the inspection and disposal efficiency.

The application discloses a kind of frozen soil area railway subgrade and underlying stratum multi-physical field on-line detection evaluation method, through periodic excitation, observation direct current electric field and seismic wave field, network upload data, fast processing direct current electric field and seismic wave field observation data, realize the real-time detection of railway subgrade structure density and the upper and lower limit of underground frozen soil layer, short interval, nondestructive, fast, accurately grasp the change situation of road basic body structure and underground frozen soil layer, provide safety early warning for railway infrastructure, and provide early warning reference standard.Observation system cost is low, installation is convenient, once installation benefits for life, detection method has the advantages such as large detection depth, real-time, few people, intelligent detection, can meet the engineering operation detection demand of plateau railway, highway and the like, provide safety early warning method and equipment for railway, highway and the like subgrade engineering.

The application provides a high-speed railway rail irregularity polishing strategy making method for sound and vibration comfort, and belongs to the technical field of intelligent operation and maintenance of high-speed railway infrastructure, and the method comprises the following steps: (1) establishing a vehicle-track coupling dynamics model; (2) collecting field synchronous test data; (3) model verification; (4) sound comfort index calculation; (5) vibration comfort index calculation; (6) comprehensive comfort index fusion; (7) determining a target rail irregularity spectrum; and (8) polishing strategy generation. The application takes human sound and vibration comprehensive comfort as an optimization target, and realizes a more scientific, accurate and economic rail polishing strategy making method.

The invention discloses an unsupervised polygonal structural member profile fitting method, which belongs to the technical field of railway infrastructure intelligent monitoring and computer vision, and comprises the following steps: acquiring a profile contour point set of a structural member in an image, and describing a straight line where the edge of the structural member is located by a slope parameter and a translation parameter corresponding to the slope parameter; constructing an objective function based on the distance between the contour point and the straight line, optimizing a slope parameter and a translation parameter, minimizing the objective function to train a neural network model, generating a slope parameter and a translation parameter corresponding to the predicted optimal straight line, and obtaining a contour point set corresponding to the contour image of the to-be-detected structural member. And generating an optimal slope parameter and an optimal translation parameter through the trained neural network model, generating an optimal straight line, and obtaining the appearance of the polygonal structural member through the intersection points between the straight lines. According to the invention, accurate fitting and state detection can be carried out on the appearance of the polygonal structural member, so that accurate and efficient real-time monitoring of railway infrastructures is realized.

The invention discloses a roadbed freezing damage diagnosis method based on satellite remote sensing data enhancement and SCNN-BN. The method comprises the following steps: firstly, acquiring PS-InSAR settlement time sequence data of a railway roadbed, and preprocessing the data to eliminate noise and improve data quality; then, performing time sequence alignment and enhancement on the original data by adopting an FDTW algorithm, and generating a training data set with higher representativeness and balance; then, a convolutional neural network model based on a sequence structure is designed, and the convergence speed, stability and diagnosis precision of the model are remarkably improved in combination with a batch normalization technology; and finally, through experimental verification, the performance of the proposed method is comprehensively evaluated. Experimental results show that the method has a high accuracy rate of 96.76% in railway roadbed freeze injury diagnosis, has excellent performance in a noise environment, and is significantly superior to that of a traditional model. The method provides an efficient and reliable solution for intelligent monitoring of the railway infrastructure.

An electric rail infrastructure for a work machine (100) is disclosed. The electric rail infrastructure comprises: a plurality of powered rails (104); a plurality of energy interfaces positioned throughout the plurality of powered rails (104); a power module (108) connected to the plurality of energy interfaces for providing electrical power to the plurality of powered rails (104); a plurality of electric clamps (200) positioned on each end of the powered rails (104), each electric clamp (200) having at least one resistor (204).

The present application relates to the technical field of data processing, in particular to a kind of integrated platform construction method for railway infrastructure operation and maintenance, comprising: the configuration information and communication log of infrastructure are automatically scanned by data probe, and the preliminary integrated basic node of information control unit is set;Based on the actual data delay of communication link, the association between basic nodes is established, and the virtual space node of railway operation and maintenance is aggregated to form;When the data of virtual space node is updated, based on the update event corresponding to virtual space node, the degree of mutual constraint between infrastructure is quantified, and update path diagram is formed;According to the data preference of update path diagram, the target equipment group under service mapping is determined according to the topology structure of data preference degree and update path diagram;Distributed resource planning is carried out to target equipment group, and the authority boundary of each update is determined, and integrated architecture after authority mapping is formed.The processing efficiency of data integration and the operation and maintenance efficiency of railway infrastructure are improved.

A computer (e.g. monitoring system Fig.1,103) predicts an effect of weather on railway infrastructure including track 104. A spatial region 301 is determined which encompasses the railway track and t

The invention discloses an on-line detection and evaluation method for multiple physical fields of a railway roadbed and an underlying stratum in a frozen earth region, which comprises the following steps of: periodically exciting, observing a direct-current electric field and a seismic wave field, uploading data in a networked manner, and quickly processing observation data of the direct-current electric field and the seismic wave field; real-time detection of the compactness of the railway subgrade structure and the upper and lower limits of the underground frozen soil layer is achieved, the change conditions of the subgrade body structure and the underground frozen soil layer are mastered in a short-interval, lossless, rapid and accurate mode, safety early warning is provided for railway infrastructures, and an early warning reference standard is provided. The observation system is low in manufacturing cost and convenient to install, life-long benefits are achieved through one-time installation, the detection method is large in detection depth and real-time, has the advantages of few people, intelligent detection and the like, can meet the operation detection requirements of projects such as plateau railways and highways, and provides a safety early warning method and equipment for roadbed projects such as railways and highways.

The invention provides a high-speed railway multi-professional data unified registration method and device based on visual features, and relates to the technical field of railway infrastructure operation, maintenance and detection, and the method comprises the steps: obtaining multi-source data; respectively extracting facility feature points from the geometric one-dimensional data of the track and the one-dimensional data of the overhead line system, and outputting the category and mileage position of the facility through identification processing; image facility feature points are detected from line-scan digital camera image data, facility categories and image pixel coordinates are output through detection, and a unified coordinate system is constructed based on the image pixel coordinates; grouping according to facility types, and matching the track inspection facility feature points with the image facility points and matching the network inspection facility points with the image facility points to obtain matching results; and piecewise linear spreading is carried out between adjacent matching pairs, a monotonous mileage-to-image pixel mapping function is generated according to a mileage-to-image pixel mapping relation, multi-source data is mapped to a unified coordinate system, and a registration result is obtained.

A portable rail clamp mount assembly configured to be installed on a railway without requiring any modification to the existing rail infrastructure is described herein. In various embodiments, the rail clamp mount assembly may comprise a set of one or more horizontal base components removably attachable to and positioned beneath a set of tracks of a railway and at least one vertical component attached to the set of one or more horizontal base components and configured to support railway equipment positioned proximate to the railway. For example, the railway equipment may include one or more devices for operating a railroad or railyard. Each of the set of one or more horizontal base components may include at least one tie configured to engage an outside edge of the set of tracks when attached to the set of tracks.

The invention belongs to the technical field of railway infrastructure detection and positioning, and particularly relates to a railway sleeper level positioning method based on multi-cascade self-adaptive fusion, which comprises the following steps: S1, fusing data of a high-frequency inertial measurement unit and a speedometer through a primary fusion layer, and carrying out motion constraint optimization in combination with track geometric parameters detected in real time, so as to obtain a final fusion layer; generating a relative track with high continuity; s2, dynamically comparing the track geometric feature sequence detected in real time with a pre-stored line design database through an intermediate fusion layer, identifying matched feature segments, and performing local deviation correction on the relative track; and S3, automatically identifying the geometric reference point associated with the CP III control point in the real-time track geometric data through the advanced fusion layer. According to the invention, continuous, stable and high-precision sleeper-level absolute positioning under full-road-section and GNSS-free conditions can be realized, and the robustness of the system under sensor abnormity or environmental disturbance is improved through an adaptive mechanism.

The application discloses a railway construction optimization method and system based on an improved grey wolf algorithm, and the method comprises the following steps: constructing a railway construction model according to the time required by each process, the cost required by each process, the quality coefficient of each process and the safety coefficient of each process, wherein the model parameters in the railway construction model comprise the time required by a project, the cost required by the project, the quality coefficient of the project and the safety coefficient of the project; and the railway construction model is solved according to the improved grey wolf algorithm, so that the project process duration is obtained. The railway infrastructure construction model can be simplified, the railway infrastructure project construction management efficiency is improved, and the decision maker can better formulate a construction scheme.

Events or situations in a traffic (e.g. railway) infrastructure 100 are monitored by a system 104 comprising multiple interconnected sensors 102a,b,c which detect vibration at respective locations. E

Described are a system and method for assessing seismic resilience of deteriorated railway infrastructure that can assess seismic resilience of railway infrastructure by quantifying resilience according to disaster safety by reflecting a resilience concept of an urban network type and extending to a damage index-based seismic performance assessment based on the quantified resilience, in railway infrastructure such as deteriorated concrete bridges, tunnel structures, and concrete slab tracks, define a correlation between a seismic performance value of deteriorated railway infrastructure and resilience of an urban network by calculating a reliable damage index, quantify and calculate resilience of detailed facilities of the urban network, and link the quantified and calculated resilience with the seismic performance value of the railway infrastructure to calculate a final seismic resilience of the urban network, and furthermore, easily assess resilience of the entire urban network as well as seismic performance / resilience of aged railway infrastructure.

The application discloses a kind of based on unsupervised polygon structural member shape fitting method, belong to railway infrastructure intelligent monitoring and computer vision technical field, by obtaining the contour point set of structural member in image, with slope parameter and its corresponding translation parameter describe the straight line where structure piece edge is, based on the distance between contour point and straight line, construct target function, by optimizing slope parameter and translation parameter, minimize target function to train neural network model, generate the slope parameter and translation parameter corresponding to predicted optimal straight line, obtain the contour point set corresponding to the image of structure to be measured, by trained neural network model, generate optimal slope parameter and translation parameter, have generated optimal straight line, by the intersection point between straight line and straight line, obtain the shape of polygon structural member.The application can accurately fit and state detection to the shape of polygon structural member, to realize the real-time monitoring of railway infrastructure accurately, efficiently.

An Urban Intermodal Freight System is capable of transporting large volumes and tonnage of freight by containerized or other means on a mass transit rail system. It captures excess capacity in the existing mass transit rail infrastructure to move packages, parcels, and freight by using miniaturized intermodal cargo containers that are designed to integrate seamlessly with the existing transit infrastructure, while displacing delivery trucks from increasingly crowded city streets. By enabling inbound trucks to transfer their cargo to the Urban Intermodal Freight System at a city's outskirts, freight is delivered without trucks entering congested downtown areas, greatly alleviating traffic congestion, delays, greenhouse gas emissions and other negative environmental impacts. The Linear Loading Dock and Conveyor System may have other useful applications, for example to access a facility, building or vehicle, or in other circumstances where off street truck parking or loading docks are not available.

The invention provides a sound and vibration comfort-oriented high-speed railway steel rail irregularity grinding strategy making method, and belongs to the technical field of intelligent operation and maintenance of high-speed railway infrastructures, and the method comprises the following steps: (1) establishing a vehicle-rail coupling dynamic model; (2) collecting field synchronous test data; (3) verifying the model; (4) sound comfort index calculation; (5) calculating a vibration comfort index; (6) integration of comprehensive comfort indexes; (7) determining a target steel rail irregularity spectrum; and (8) a polishing strategy is generated. According to the method, the comprehensive comfort of sound and vibration of the human body serves as an optimization target, and the more scientific, accurate and economical steel rail grinding strategy making method is achieved.

The invention relates to the technical field of railway infrastructure intelligent detection, in particular to a steel rail surface damage full-automatic identification and grading method based on a multi-modal large model, which comprises the following steps: synchronously acquiring three kinds of modal original data in the same time window in the steel rail operation process; performing feature extraction on the original data of the three modes, and outputting multi-mode features; carrying out element-by-element fusion on the multi-modal features based on a formula and generating the multi-modal features; performing self-attention-based large model reasoning on the input and outputting category confidence and severity scores; calculating an evolution rate based on historical data, calculating a risk score according to a formula, and outputting a maintenance suggestion; and sending the detection result, the risk assessment and the maintenance suggestion to an operation and maintenance system or a display terminal.

This invention discloses a method for monitoring and assessing the safety level of railway infrastructure based on cross-business data fusion of engineering and power supply. It constructs a two-layer quantitative indicator system covering both objective conditions and external environmental risks; employs a bidirectional cross-attention mechanism to achieve deep semantic feature fusion of engineering, power supply, and environmental data; collaboratively identifies the status of key components and outputs indicator values ​​based on a shared backbone network and multiple semantic detection heads; utilizes a combination of the analytic hierarchy process (AHP) and entropy weighting method for weighting, and dynamically adjusts the weights using a context-aware mechanism to calculate a comprehensive safety evaluation value, thereby classifying safety levels and triggering early warnings; ultimately achieving hierarchical processing from millisecond-level instinctive reflexes to long-cycle knowledge evolution. This invention realizes deep semantic fusion and coupled feature extraction of cross-business data, establishes a dynamically adaptive safety assessment model, and completes hierarchical intelligent early warning and response, improving the intelligent level of railway infrastructure operation and maintenance and enhancing traffic safety assurance capabilities.