Geo-defect repair modeling is provided. A method includes logically dividing a railroad network according to spatial and temporal dimensions with respect to historical data collected. The spatial dimensions include line segments of a specified length and the temporal dimensions include inspection run data for inspections performed for each of the line segments over a period of time. The method also includes creating a track deterioration model from the historical data, identifying geo-defects occurring at each inspection run from the track deterioration model, calculating a track deterioration condition from the track deterioration model by analyzing quantified changes in the geo-defects measured at each inspection run, and calculating a derailment risk based on track conditions determined from the inspection run data and the track deterioration condition. The method further includes determining a repair decision for each of the geo-defects based on the derailment risk and costs associated with previous comparable repairs.

Geo-defect repair modeling is provided. A method includes logically dividing a railroad network according to spatial and temporal dimensions with respect to historical data collected. The spatial dimensions include line segments of a specified length and the temporal dimensions include inspection run data for inspections performed for each of the line segments over a period of time. The method also includes creating a track deterioration model from the historical data, identifying geo-defects occurring at each inspection run from the track deterioration model, calculating a track deterioration condition from the track deterioration model by analyzing quantified changes in the geo-defects measured at each inspection run, and calculating a derailment risk based on track conditions determined from the inspection run data and the track deterioration condition. The method further includes determining a repair decision for each of the geo-defects based on the derailment risk and costs associated with previous comparable repairs.

A sensing system includes a leading sensor, a trailing sensor, and a route examining unit. The leading sensor is onboard a first vehicle of a vehicle system that is traveling along a route. The leading sensor measures first characteristics of the route as the vehicle system moves along the route. The trailing sensor is disposed onboard a second vehicle of the vehicle system. The trailing sensor measures second characteristics of the route as the vehicle system moves along the route. The route examining unit is disposed onboard the vehicle system and receives the first characteristics of the route and the second characteristics of the route to compare the first characteristics with the second characteristics. The route examining unit also identifies a segment of the route as being damaged based on a comparison of the first characteristics with the second characteristics.

A method to obtain data concerning the upper profile of an element of a railway track or switch by means of an electronic measuring module mounted on a cart and provided with at least one laser profilometer to acquire a sequence of images while the cart moves forward along the railway track so that each image comprises a point cloud indicative of the upper profile in correspondence with a respective plane transverse to the forward moving direction of the cart. The method provides that, for each point cloud, a respective piecewise polynomial function, preferably a spline function, that approximates the point cloud, is generated, so as to transform original data consisting of said point cloud into compressed data consisting of parameters of the piecewise polynomial function.

A route examination system includes a thermographic camera configured to be logically or mechanically coupled with a vehicle that travels along a route. The thermographic camera is also configured to sense infrared radiation emitted or reflected from the route and to generate a sensed thermal signature representative of the infrared radiation that is sensed. The system also includes a computer readable memory device configured to store a designated thermal signature representative of infrared radiation emitted from a segment of the route that is not damaged. The system also includes an analysis processor configured to determine a condition of a first portion of the route relative to other portions of the route at least in part by comparing the sensed thermal signature and the designated thermal signature.

Systems, methods and devices for a computer vision-based pixel-level rail components detection system using an improved one-stage instance segmentation model and prior knowledge, aiming to inspect railway components in a rapid, accurate, and convenient fashion.

A sensing system includes a leading sensor, a trailing sensor, and a route examining unit. The leading sensor is onboard a first vehicle of a vehicle system that is traveling along a route. The leading sensor measures first characteristics of the route as the vehicle system moves along the route. The trailing sensor is disposed onboard a second vehicle of the vehicle system. The trailing sensor measures second characteristics of the route as the vehicle system moves along the route. The route examining unit is disposed onboard the vehicle system and receives the first characteristics of the route and the second characteristics of the route to compare the first characteristics with the second characteristics. The route examining unit also identifies a segment of the route as being damaged based on a comparison of the first characteristics with the second characteristics.

The present application involves a railroad track inspection system comprising a plurality of track scanning sensors, a data store, and a scan data processor. The data store is used for storing track scan data recorded by the track scanning sensors. The scan data processor is used for automatic analysis of the track scan data upon receipt thereof to detect one or more track components within the scan data from a predetermined list of component types according to one or more features identified in said scan data. The system comprises a common support structure to which the track scanning sensors, the data store and scan data processor are attached, the common support structure having a mounting for attachment of the system to a railway vehicle in use.

An ultrasonic probe for non-destructive testing of a rail, said probe comprising a housing; an insert comprising an ultrasonic transducer and a polycarbonate shoe having a face for contacting a rail; and a compressed spring for exerting a downward force on said insert; the system further comprising a plate with a restraining flange around an aperture to prevent the polycarbonate shoe from extending more than a preset fixed amount through the aperture.

The present application involves a railroad track asset surveying system comprising an image capture sensor, a location determining system, and an image processor. The image capture sensor is mounted to a railroad vehicle. The location determining system holds images captured by the image capture sensor. The image processor includes an asset classifier and an asset status analyser. The asset classifier detects an asset in one or more captured images and classifies the detected asset by assigning an asset type to the detected asset from a predetermined list of asset types according to one or more features in the captured image. The asset status analyser identifies an asset status characteristic and compares the identified status characteristic to a predetermined asset characteristic so as to evaluate a deviation therefrom.