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.

In one aspect, a method of monitoring a mobile railway asset is provided including detecting a strain of a component of a mobile railway asset and gathering data associated with a vibration of the mobile railway asset. The method includes comparing the strain of the component and the data associated with the vibration of the mobile railway asset. The method includes determining a load state of the mobile railway asset based at least in part on the comparison of the strain of the component and the data associated with the vibration of the mobile railway asset.

A railroad infrastructure communication network is presented. The network can include a plurality of infrastructure nodes distributed proximate a railroad track, such as near railroad equipment and/or assets. Infrastructure nodes can be configured to receive data from equipment sensor and/or assets and transmit such data via the network. Infrastructure nodes can further generate alert and/or alert packets based on such received data. Infrastructure nodes can self-define in a network infrastructure depending on configured connection types, and can for example, serve as repeater nodes (to promulgate a transmission to additional infrastructure nodes) and/or collector nodes (to collect data for a centralized server node). A server node can be configured to receive data and/or packet from infrastructure nodes and generate requests for additional systems, personnel, etc. to address such requests. The network can limit the data transmission size and leverage distributed processing capabilities to enable transmissions over long ranges, such as by reducing the bandwidth required to transmit packets.

The disclosed solution generally relates to a hyperloop vehicle detecting objects in a hyperloop system. Hyperloop vehicles operate at incredible velocities and require robust systems to detect objects that increase the risk to a hyperloop vehicle. Transponders typically provide long-range data about the activity of downstream hyperloop vehicles. However, nearby objects require detection at line-of-sight distances in order to ensure that objects and vehicles within a given transponder interval distance are detected. The disclosed system provides an elegant solution that combines the advantages of both transponder-based object detection and sensor-based object detection.

A system and method for automating railroad maintenance by a tie gang using electronic tie marking (ETM) configured to optimize railroad asset maintenance. The system enables collision avoidance between members of the tie gang performing maintenance on railway assets (e.g., Rails, Ties, Ballasts, Turnouts, Crossings, etc.). The system can generate production numbers for the railway assets and evaluate an asset queue for the tie gang to perform maintenance. The system can utilize real-time updates from the tie gang to optimize work output. The system can provide a customizable user interface to identify, track, and process information related to maintenance of the railroad asset. The system also provides for a heads-up-display (HUD) to notify an operator of relevant information, such as maintenance information, travel indicators, and updated asset queue. The system can identify a next location and calculate an optimum path based on sensor input incorporating machine-specific and environmental characteristics.

An imaging apparatus is mounted on a moving object and configured to capture an image while moving along a moving direction of the moving object. The imaging apparatus includes a sensor unit including a sensor substrate on which an image sensor is mounted, and a main unit including a main substrate on which an electronic component configured to process an output signal from the sensor substrate is mounted. The imaging apparatus further includes a heat dissipation fin configured to dissipate heat generated in at least one of the sensor unit and the main unit. The heat dissipation fin is provided in a direction substantially parallel to the moving direction.

Various embodiments of an autonomous rail vehicle that can travel ahead of a locomotive at a distance proportional to the locomotive's stopping capability are disclosed. The rail vehicle may scan its surroundings, gauges track conditions, and communicates with locomotive operators of the scanned results in real-time to timely enable activation of the locomotive's emergency brakes in case of detection of off-normal track conditions. The rail vehicle may paired with the locomotive and provides eyes to locomotive operators so that they can have information on tracks viability well ahead of the locomotive.

A method for analyzing one or more conditions of a transportation pathway includes obtaining, using an imaging device of an inspection system, image data reproducible as a plurality of images of the transportation pathway, each of the plurality of images being reproducible as an image of a portion of the transportation pathway, each portion of the transportation pathway having an associated location along a length of the transportation pathway, analyzing, using one or more processors of the inspection system, the image data to determine a first plurality of metrics indicative of a condition of the transportation pathway at each of the associated locations, and generating a first graph, using the determined first plurality of metrics, that is indicative of the condition of the transportation pathway at each of the associated locations.

An on-board thermal track misalignment detection system method therefor is presented. The system can use on-board locomotive sensors attached to an end-of-train device to detect (on the edge), signs and symptoms of thermal misalignments of the track. Once detected an alert can be transmitted to prevent potential derailments. The system can also include a forward-facing and rearward-facing imaging sensors (e.g., camera, LiDAR sensor, etc). The system can wirelessly communicate (e.g., via radio) with a leading locomotive to ensure proper air pressure and location. The system can be powered by an on-board battery and/or air pressure device. Advantageously, the system can calculate whether any rail deviation is significant (e.g., via one or more threshold values). The system can also leverage image processing functionality, executed by one or more processors) to find the centerline and the distance between the tracks.

A system for navigating within a track network includes, as system components, a system central, a track maintenance machine and a communication device. The system central is set up for administering network data representing a model of the track network. The track maintenance machine is suited for treatment of track sections of the track network. The track maintenance machine includes a navigation device for processing navigation data derived from the network data. The communication device is provided for data exchange between the system central and the navigation device. The system includes at least one movable or stationary carrier platform with sensors for collecting raw data representing characteristic information of the track network. A big data framework is set up in the system central to evaluate the raw data and synchronize them with the network data. Automated updating of the network data can be carried out with the system.