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 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.

A new over lay technology for the Positive Train Control and Energy Management systems used by the railroad industry today which allows for automated train handling responses to potential on-track hazards. Various sensors, including image-capture devices, radar, and drones, are placed on or proximate to a train. These sensors are used to interface with or override the Positive Train Control and Energy Management systems where those systems activate specific actions such as slowing or stopping a train but hazardous conditions on the track may dictate an alternative response.

A system for detecting and pre-warning railway roadbed deformation includes: a control box and an optical fiber-pressure sensor group. The optical fiber-pressure sensor group is formed by disposing a plurality of optical fiber-pressure sensors into a cuboid shape, and is buried in the railway roadbed for detecting magnitude of roadbed deformation in each direction. The direction of the deformation can be acknowledged easily, allowing the staff to eliminate potential risks purposefully. A time series prediction algorithm is performed to forecast a trend of the roadbed deformation in each direction, such that the staff may purposefully overhaul and correct the tracks where the roadbed is deformed excessively. At the same time, the staff may overhaul the track before the magnitude of the roadbed deformation reaches a predetermined value. Potential safety hazards may be eliminated in advance, ensuring the safety for the operation of the railroad.

A method for optically examining a route such as a track includes obtaining one or more images of a segment of a track from a camera mounted to a rail vehicle while the rail vehicle is moving along the track and selecting a benchmark visual profile of the segment of the track. The benchmark visual profile represents a designated layout of the track. The method also can include comparing the one or more images of the segment of the track with the benchmark visual profile of the track and identifying one or more differences between the one or more images and the benchmark visual profile as a misaligned segment of the track.

In one embodiment, a method includes capturing, by a machine vision device, an image of an object in a railway environment. The machine vision device is attached to a first train car that is moving in a first direction along a first railroad track of the railway environment. The method also includes analyzing, by the machine vision device, the image of the object using one or more machine vision algorithms to determine a value associated with the object. The method further includes determining, by the machine vision device, that the value associated with the object indicates a potential deficiency of the object and communicating, by the machine vision device, an alert to a component external to the first train car. The alert comprises an indication of the potential deficiency of the object.

A method includes obtaining one or more images of a segment of a route from a camera while a vehicle is moving along the route. The segment of the route includes one or more guide lanes. The method also includes comparing, with one or more computer processors, the one or more images of the segment of the route with a benchmark visual profile of the route based at least in part on an overlay of the one or more images onto the benchmark visual profile or an overlay of the benchmark visual profile onto the one or more images. The one or more processors identify a misaligned segment of the route based on one or more differences between the one or more images and the benchmark visual profile and respond to the identification of the misaligned segment of the route by modifying an operating parameter of the vehicle.

A system and method for monitoring a track and/or rail employs one or more distance measuring imagers mounted to a railcar and directed to image the track and/or rails wherein the images are geo-tagged with location data. Geo-tagged distance measurements are processed to determine at least track gauge and/or at least rail fastener integrity. The system and method may also determine other track and/or rail integrity issues including, e.g., rail profile, rail alignment, center point dip, cross level, rail cant, wheel wear, wheel integrity, rail wear, rail defects, and/or rail temperature. The system and method may also determine when inspection and/or maintenance of the track is indicated, and provide selected records of where and/or when such inspection and/or maintenance is indicated.

A system and method for detecting buckled rail and for predicting a risk for rail buckling is disclosed. The method may comprise receiving data from a camera mounted on locomotive traveling on the railroad track. The data may include images of the buckled rail and dimensions of the buckled rail when the camera detects the buckled rail. The data may further include images of the ballast and condition of the ballast. The method may further comprise receiving data from a thermal camera mounted to the locomotive indicating the temperature of the rails. The method may further comprise transmitting an alarm signal to a display interface of a remote unit if the dimensions of the buckled rail meet a predetermined threshold, and predicting a risk for rail buckling based at least on the temperature of the rails and the condition of the ballast.

A system and method for monitoring a track and/or rail employs one or more imagers mounted to a railcar and directed to image the track and/or rails wherein the images are geo-tagged with location data. Geo-tagged images are processed to determine at least track gauge and/or at least rail fastener integrity. The system and method may also determine other track and/or rail integrity issues including, e.g., rail fastener integrity, rail profile, rail alignment, center point dip, cross level, rail cant, wheel wear, wheel integrity, rail wear, rail defects, and/or rail temperature. The system and method may also determine when inspection and/or maintenance of the track is indicated, and provide selected records of where and/or when such inspection and/or maintenance is indicated.

Examples relate to digital context aware (DCA) data collection. In some examples, a DCA start location component is positioned at a first location along a travel route, and a DCA end location component is positioned at a second location along the travel route. In response to using a wireless interface to detect the DCA start location component, data collection of measurements by a sensor are initiated. In response to using the wireless interface to detect the DCA end location component, the data collection by the sensor is halted.