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US 12,367,570 B2Granted
System and method for railroad track geometry measurement
AssigneeBNSF Railway Company
InventorKanyon W. Loyd
Life of this patent
Estimating the term…
Abstract
Methods and systems for detecting and measuring physical conditions of a railroad track based on image-based distance measurements are provided. In embodiments, at least one object associated with a condition of a railroad track is detected in at least one image. A first point and a second point on the at least one object is detected. A pixel distance between the first point and the second point is measured, and a physical distance-based measurement of the condition of the railroad track is determined, using a conversion model, based on the pixel distance between the first point and the second point. An alert is generated when the physical distance-based measurement of the condition of the railroad track exceeds a predetermined threshold.
Claims14
A method of determining a condition of a railroad track, comprising:
- collecting image data related to at least a portion of a railroad track via one or more sensors disposed on a vehicle traveling along the railroad track;
- detecting at least one object in at least one image of at least a portion of the railroad track in the image data, the at least one object associated with at least one condition of the railroad track, wherein the at least one image includes a plurality of images each captured from a different angle;
- identifying a first point and a second point on the at least one object detected in each image of the plurality of images captured from a different angle;
- measuring a pixel distance between the first point and the second point in each image of the plurality of images captured from a different angle, wherein the pixel distance between the first point and the second point indicates a number of pixels in a line between the first point and the second point;
- determining, using a conversion model, a physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured in each image of the plurality of images captured from a different angle, wherein determining the physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured in each image of the plurality of images captured from a different angle includes one of:
- averaging the physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured in all images of the plurality of images captured from a different angle;
- and
- selecting a maximum physical distance-based measurement value from among the physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured for all images of the plurality of images captured from a different angle;
- and
- generating an alert when the physical size of the at least one condition of the railroad track exceeds a predetermined threshold.
7 more elements
A method of determining a condition of a railroad track, comprising:
- collecting image data related to at least a portion of a railroad track via one or more sensors disposed on a vehicle traveling along the railroad track;
- detecting a discontinuity in a rail joint section in at least one image of at least a portion of the railroad track in the image data, the discontinuity representing a rail gap between a first rail section and a second rail section, wherein the at least one image includes a plurality of images each captured from a different angle;
- detecting a first edge and a second edge of the discontinuity representing the rail gap;
- identifying a first point in the first edge of the discontinuity representing the rail gap and a second point in the second edge of the discontinuity representing the rail gap in each image of the plurality of images captured from a different angle;
- measuring a pixel distance between the first point and the second point in each image of the plurality of images captured from a different angle, wherein the pixel distance between the first point and the second point indicates a number of pixels in a line between the first point and the second point;
- determining, using a conversion model, a physical size of the rail gap based on the pixel distance between the first point and the second point measured in each image of the plurality of images captured from a different angle, wherein determining the physical size of the rail gap based on the pixel distance between the first point and the second point measured in each image of the plurality of images captured from a different angle includes one of:
- averaging the physical size of the rail gap based on the pixel distance between the first point and the second point measured in all images of the plurality of images captured from a different angle;
- or
- selecting a maximum physical distance-based measurement value from among the physical size of the rail gap based on the pixel distance between the first point and the second point measured for all images of the plurality of images captured from a different angle;
- and
- generating an alert when the physical size of the rail gap exceeds a predetermined threshold.
8 more elements
A system for determining a condition of a railroad track, the system comprising:
- at least one processor;
- and
- a memory operably coupled to the at least one processor and storing processor-readable code that, when executed by the at least one processor, is configured to perform operations including:
- one or more sensors disposed on a vehicle traveling along the railroad track configured to collect image data related to at least a portion of a railroad track;
- detecting at least one object in at least one image of at least a portion of the railroad track in the image data, the at least one object associated with at least one condition of the railroad track, wherein the at least one image includes a plurality of images each captured from a different angle;
- identifying a first point and a second point on the at least one object detected in each image of the plurality of images captured from a different angle;
- measuring a pixel distance between the first point and the second point in each image of the plurality of images captured from a different angle, wherein the pixel distance between the first point and the second point indicates a number of pixels in a line between the first point and the second point;
- determining, using a conversion model, a physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured in each image of the plurality of images captured from a different angle, wherein determining the physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured in each image of the plurality of images captured from a different angle includes one of:
- averaging the physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured in all images of the plurality of images captured from a different angle;
- and
- selecting a maximum physical distance-based measurement value from among the physical size of the at least one condition of the railroad track associated with the at least one object based on the pixel distance between the first point and the second point measured for all images of the plurality of images captured from a different angle;
- and
- generating an alert when the physical size of the at least one condition of the railroad track exceeds a predetermined threshold.
10 more elements
Dependencies are inferred from the claim text.