Methods of assessing wear of an electrical insulator and rail pad of an assembled rail fastening system utilize data from a 3D scan of the system to derive measurements of the system from which wear of the side post of the electrical insulator, or wear of the rail pad beneath the rail, may be assessed.

A system for modeling risk of rail buckling in railroad infrastructure is presented. The system can receive a myriad of data related to railroad tracks and/or railroad operations, and weight the data using specially-designed weighting factors that can be unique to each data type. The weighted data can be transformed via specialized algorithms to generate location scores reflective of a risk isolated to a particular area. The system can further utilize additional specialized algorithms to elucidate how such isolated risk can be extrapolated from one location to another. The system can implement a multilayer approach, formulating one or more layers of risk models and aggregating such models into an overarching risk model that can more-accurately forecast risk of rail buckling in a railroad track.

A system and method for inspecting a railway track using sensors oriented at an oblique angle relative to a rail vehicle on which the system is traveling. The orientation of the sensors allows for different data to be gathered regarding a particular rail including rail design specifications (gathered based on manufacturer markings detected and analyzed by the system), rail seat abrasion values based on direct measurement of rails from the oblique angle, and other analysis of rail features including joint bars, rail welds, bond wires, rail holes, and broken rails. The use of an air blower, ducts, and one or more air distribution lids over the sensors helps remove debris from blocking the sensors and structured light generators.

The present disclosure generally relates to automated detection of railroad track features. Images of a railroad track are captured and analyzed to identify track features such as anchors, spikes, rail ties, tie plates, and joints. Various image processing techniques are utilized to accurately distinguish between track features and other objects in the captured images. Track features identified in the images are assigned identifiers and locations and stored in a database so that a status and/or condition of the track features may be monitored for maintenance purposes.

A system for analyzing a railroad track comprises a transport device, a camera coupled to the transport device, an electronic display device, a memory device, and one or more processors. The camera is disposed adjacent to a rail of the railroad track and generates image data reproducible as one or more images of at least a portion of a surface of the rail. The processors can produce an image of the rail surface, which includes a plurality of elongated portions. The image is analyzed to identify any defects that exist within each elongated portion of the rail surface. The processors determine a value of a metric for each elongated portion of the rail surface. The metric is associated with the identified defects. The electronic display device displays a graph indicative of the metric for each elongated portion, the image of the rail surface, or both.

A system for modeling risk of rail buckling in railroad infrastructure is presented. The system can receive a myriad of data related to railroad tracks and/or railroad operations, and weight the data using specially-designed weighting factors that can be unique to each data type. The weighted data can be transformed via specialized algorithms to generate location scores reflective of a risk isolated to a particular area. The system can further utilize additional specialized algorithms to elucidate how such isolated risk can be extrapolated from one location to another. The system can implement a multilayer approach, formulating one or more layers of risk models and aggregating such models into an overarching risk model that can more-accurately forecast risk of rail buckling in a railroad track.

A system for railroad directive management is presented. The system can receive a myriad of data related to a directive, track segments, and/or vehicle events on the track and/or track segments. Vehicle- and/or event-specific data can be compared with one or more thresholds, including force thresholds, temporal thresholds, environmental thresholds, and/or event thresholds to determine whether and what kind of directive modification should be instantiated. Specialized algorithms can be implemented to trace vehicle paths along the track to determine whether directive-related segments are traversed, and specialized clustering algorithms can be utilized to cluster data unique to a particular segment on a per-segment basis. The system can be integrated with existing track infrastructure and can further generate alerts to notify coupled systems and/or personnel of directives and/or modification thereof.

The present invention relates to a method and system using multiple data sources for unsupervised and/or semi supervised algorithms to derive features such as speed of the train, length of the train, type of wagons, etc. Thus, classifying train categories. The invention provides a method and a system configured for analysing railway related vibration data. The invention is configured for collecting at least a first dataset from a sensor applied to the railway infrastructure. Further, it is configured for collecting at least a second dataset from a scheduling component. The at least one subset of the first dataset is curated with the second dataset to obtain first training database. The invention further discloses a method comprising the step of predicting at least a likelihood of one train belonging to at least one train-type.

According to one embodiment, a damaged region determination system of the embodiment includes a plurality of sensors, a position locator, and a determiner. The plurality of sensors detects elastic waves generated in a target object related to a railway which is a determination target of a damaged region. The position locator locates positions of sources of a plurality of elastic waves based on the plurality of elastic waves detected by each of the plurality of sensors. The determiner determines the damaged region in the target object based on the positions of the sources of the plurality of elastic waves.

A rail-guided permanent way machine is operated by means of a control device in such a way that at least one state variable (Z) of the permanent way machine is determined in dependence on an operating state, and the at least one state variable is compared to at least one pre-defined limit value (G.sub.W, G.sub.S) for monitoring a derailment safety of the permanent way machine. Thus, the derailment safety of the permanent way machine is determined in accordance with the current operating state and monitored. As a result, the permanent way machine has an expanded operating range and increased performance and thus increased efficiency.