Abstract: A system and method for calibrating a machine vision system on the undercarriage of a rail vehicle while the rail vehicle is in the field is presented. The system enables operators to calibrate the machine vision system without having to remove the machine vision system from the undercarriage of the rail vehicle. The system can capture, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum can be attached to a fixture and the target can be attached to the drum. The system can also determine a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate can be programmed into a drum encoder.

Abstract: A system and method for monitoring a roadway by comparing captured images to image inconsistencies caused by lost or unnecessary motion and for minimizing lost or unnecessary motion of an axle of a vehicle and filtering erroneous pulses of an electrical signal to generate a trigger signal to capture images is presented. The system enables the minimization of image artifacts causing distortion in an image. The system can take images of a target, compute an object pixel size of the image to ensure calibration of longitudinal measurements, and calibrate the rotary encoder with the camera of the machine vision system. The system can enable calibration of the locomotive components in the field to compensate for the misalignment of the machine vision system and provide safe travels.

Abstract: A system and method for monitoring a roadway by comparing captured images to image inconsistencies caused by lost or unnecessary motion and for minimizing lost or unnecessary motion of an axle of a vehicle and filtering erroneous pulses of an electrical signal to generate a trigger signal to capture images is presented. The system enables the minimization of image artifacts causing distortion in an image. The system can take images of a target, compute an object pixel size of the image to ensure calibration of longitudinal measurements, and calibrate the rotary encoder with the camera of the machine vision system. The system can enable calibration of the locomotive components in the field to compensate for the misalignment of the machine vision system and provide safe travels.

Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: A system and method for calibrating a machine vision system on the undercarriage of a rail vehicle while the rail vehicle is in the field is presented. The system enables operators to calibrate the machine vision system without having to remove the machine vision system from the undercarriage of the rail vehicle. The system can capture, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum can be attached to a fixture and the target can be attached to the drum. The system can also determine a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate can be programmed into a drum encoder.

Abstract: A system and method for monitoring a roadway by comparing captured images to image inconsistencies caused by lost or unnecessary motion and for minimizing lost or unnecessary motion of an axle of a vehicle and filtering erroneous pulses of an electrical signal to generate a trigger signal to capture images is presented. The system enables the minimization of image artifacts causing distortion in an image. The system can take images of a target, compute an object pixel size of the image to ensure calibration of longitudinal measurements, and calibrate the rotary encoder with the camera of the machine vision system. The system can enable calibration of the locomotive components in the field to compensate for the misalignment of the machine vision system and provide safe travels.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Abstract: A system and method for calibrating a machine vision system on the undercarriage of a rail vehicle while the rail vehicle is in the field is presented. The system enables operators to calibrate the machine vision system without having to remove the machine vision system from the undercarriage of the rail vehicle. The system can capture, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum can be attached to a fixture and the target can be attached to the drum. The system can also determine a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate can be programmed into a drum encoder.

Abstract: A system and method for calibrating a machine vision system on the undercarriage of a rail vehicle while the rail vehicle is in the field is presented. The system enables operators to calibrate the machine vision system without having to remove the machine vision system from the undercarriage of the rail vehicle. The system can capture, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum can be attached to a fixture and the target can be attached to the drum. The system can also determine a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate can be programmed into a drum encoder.

Abstract: A system and method for monitoring a roadway by comparing captured images to image inconsistencies caused by lost or unnecessary motion and for minimizing lost or unnecessary motion of an axle of a vehicle and filtering erroneous pulses of an electrical signal to generate a trigger signal to capture images is presented. The system enables the minimization of image artifacts causing distortion in an image. The system can take images of a target, compute an object pixel size of the image to ensure calibration of longitudinal measurements, and calibrate the rotary encoder with the camera of the machine vision system. The system can enable calibration of the locomotive components in the field to compensate for the misalignment of the machine vision system and provide safe travels.

Abstract: A system and method for monitoring a roadway by comparing captured images to image inconsistencies caused by lost or unnecessary motion and for minimizing lost or unnecessary motion of an axle of a vehicle and filtering erroneous pulses of an electrical signal to generate a trigger signal to capture images is presented. The system enables the minimization of image artifacts causing distortion in an image. The system can take images of a target, compute an object pixel size of the image to ensure calibration of longitudinal measurements, and calibrate the rotary encoder with the camera of the machine vision system. The system can enable calibration of the locomotive components in the field to compensate for the misalignment of the machine vision system and provide safe travels.

Abstract: A system and method for monitoring a roadway by comparing captured images to image inconsistencies caused by lost or unnecessary motion and for minimizing lost or unnecessary motion of an axel of a vehicle and filtering erroneous pulses of an electrical signal to generate a trigger signal to capture images is presented. The system enables the minimization of image artifacts causing distortion in an image. The system can take images of a target, compute an object pixel size of the image to ensure calibration of longitudinal measurements, and calibrate the rotary encoder with the camera of the machine vision system. The system can enable calibration of the locomotive components in the field to compensate for the misalignment of the machine vision system and provide safe travels.

Abstract: A system and method for calibrating a machine vision system on the undercarriage of a rail vehicle while the rail vehicle is in the field is presented. The system enables operators to calibrate the machine vision system without having to remove the machine vision system from the undercarriage of the rail vehicle. The system can capture, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum can be attached to a fixture and the target can be attached to the drum. The system can also determine a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate can be programmed into a drum encoder.

Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: In one embodiment, a sample confinement tool includes a first end and a second end. The first end of the sample confinement tool is coupled to a driving tool. The driving tool is coupled to a heavy-duty vehicle. The sample confinement tool is operable to insert a predetermined depth below a ballast surface and collect a ballast sample within the second end of the sample confinement tool. The sample confinement tool is also operable to confine the ballast sample within the second end of the sample confinement tool by mechanically compressing the ballast sample. The sample confinement tool is further operable to release the ballast sample into a sample receptacle by mechanically decompressing the ballast sample.

Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: The disclosure describes a sample confinement tool that includes a first end and a second end. The first end of the sample confinement tool is coupled to a driving tool. The driving tool is coupled to a heavy-duty vehicle. The sample confinement tool is operable to insert a predetermined depth below a ballast surface and collect a ballast sample within the second end of the sample confinement tool. The sample confinement tool is also operable to confine the ballast sample within the second end of the sample confinement tool by mechanically compressing the ballast sample. The sample confinement tool is further operable to release the ballast sample into a sample receptacle by mechanically decompressing the ballast sample.

Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.