RAILROAD TRACK SURVEY SYSTEM

• US 20170106885A1
• Filed: 12/29/2015
• Published: 04/20/2017
• Est. Priority Date: 09/03/2015
• Status: Active Grant

• Current Assignee: Sameer Singh
• Original Assignee: Sameer Singh
• Inventors: Singh, Sameer
• Granted Patent: US 10,040,463 B2
• Time in Patent Office: Days
• CPC Class Codes: B61K 9/08 Measuring installations for surveying permanent way applications of measuring apparatus or devices for track building purposes E01B35/00; measuring techniques G01
• CPC Class Codes: B61L 15/0072 On-board train data handling
• CPC Class Codes: B61L 15/0081 On-board diagnosis or maintenance
• CPC Class Codes: B61L 2205/04 Satellite based navigation systems, e.g. global positioning system [GPS]
• CPC Class Codes: B61L 23/04 for monitoring the mechanical state of the route
• CPC Class Codes: B61L 23/042 Track changes detection
• CPC Class Codes: B61L 23/044 Broken rails
• CPC Class Codes: B61L 23/045 Rail wear
• CPC Class Codes: B61L 23/047 Track or rail movements
• CPC Class Codes: B61L 23/048 Road bed changes, e.g. road bed erosion
• CPC Class Codes: B61L 25/021 Measuring and recording of train speed
• CPC Class Codes: B61L 25/023 Determination of driving direction of vehicle or train
• CPC Class Codes: B61L 25/025 Absolute localisation, e.g. providing geodetic coordinates
• CPC Class Codes: G01B 11/22 for measuring depth
• CPC Class Codes: G01N 21/8851 Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges G01N21/8806 and G01N21/93 - G01N21/95692 take precedence; optical measurement of dimensions G01B11/00; optical scanning G02B26/10; image transformation G06T3/00; computerised image enhancement G06T5/00; image processing per se for flaw detection G06T7/0002
• CPC Class Codes: G01N 2201/10 Scanning
• CPC Class Codes: G01N 2201/12 Circuits of general importance; Signal processing
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06F 18/2431 Multiple classes
• CPC Class Codes: G06V 20/52 : Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 2201/06 : Recognition of objects for industrial automation
• CPC Class Codes: H04N 23/90 : Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums

Abstract

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.

Claims

1-33. -33. (canceled)

34. A railroad track inspection system comprising:

a plurality of track scanning sensors;

a data store for storing track scan data recorded by the track scanning sensors; and

a scan data processor for automatic analysis of said 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;

wherein 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.

35. The system according to claim 34, wherein the common support structure comprises a rigid enclosure within which the track scanning sensors, the data store and scan data processor are housed as a single module or assembly.

36. The system according to claim 35, wherein the scan data processor and data store are provided in a housing as a removable processing unit, which is releasably mechanically and electrically coupled to the common support structure by one or more connector formation.

37. The system according to claim 36, wherein the module is arranged to operate selectively in both an attended mode in which a human operator provides control inputs for image data acquisition or control of the asset status analyser, wherein operator software tools are available for review and reporting of asset status information, and an unattended mode, wherein the system operates fully autonomously according to a preprogramed set of machine readable instructions embedded within it.

38. The system according to claim 37, wherein the unattended mode does not require human intervention for starting, stopping, data acquisition or analysis and is fully automated from data collection to transmission of data analysis to an operational control centre.

39. The system according to claim 35, wherein the rigid enclosure comprises a wall structure shaped so as to define a first portion arranged to be located above a rail of the railroad track in use and at least one further portion adjacent the first portion, the first portion facing the rail in use and being recessed with respect to the further portion.

40. The system according to claim 39, wherein the scan data processor and data store are provided in a housing as a removable processing unit, which is releasably mechanically and electrically coupled to the common support structure by one or more connector formation.

41. The system according to claim 40, wherein the track scanning sensors are mounted to the common support structure separately from the removable processing unit.

42. The system according to claim 40, wherein the module is arranged to operate selectively in both an attended mode in which a human operator provides control inputs for image data acquisition or control of the asset status analyser, wherein operator software tools are available for review and reporting of asset status information, and an unattended mode, wherein the system operates fully autonomously according to a preprogramed set of machine readable instructions embedded within it.

43. The system according to claim 42, wherein the unattended mode does not require human intervention for starting, stopping, data acquisition or analysis and is fully automated from data collection to transmission of data analysis to an operational control centre.

44. The system according to claim 40, wherein the removable processing unit comprises a sealed unit, an internal space of which is isolated from an interior of the rigid enclosure when connected thereto.

45. The system according to claim 44, wherein the track scanning sensors are mounted to the common support structure separately from the removable processing unit.

46. The system according to claim 35, wherein the enclosure comprises a plurality of window portions, each portion being arranged in the field of view of one or more of said track scanning sensors, wherein at least one window portion is arranged at a different angular orientation to at least one further window portion.

47. The system according to claim 34, wherein the common support structure and/or housing comprises a common power supply device and/or data connection device for connecting the system to the railway vehicle.

48. The system according to claim 34, further comprising:

a battery arranged to power at least the scan data processor and/or sensors such that storage and/or analysis of the track scan data can be performed by the system for a period of absence of external power.

49. The system according to claim 34, wherein the track scanning sensors are adjustably mounted on the common support relative to the mounting, and the system comprises an actuator and a controller for dynamically adjusting a field of view of the image capture sensors whilst the vehicle is in motion.

50. The system according to claim 49, wherein the actuator is a common actuator arranged for translation of the track scanning sensors in unison relative to the support structure mounting.

51. The system according to claim 50, comprising one or more light sources attached to the common support structure and arranged to illuminate a region of the railroad track corresponding to the field of view of the track scanning sensors.

52. The system according to claim 51, wherein the illumination from the light source is substantially uniform over a lateral section or width dimension of the track.

53. The system according to claim 34, wherein the controller is arranged to adjust the field of view of the sensors automatically based on the location or absence of one or more identified feature or track component in the scan data relative to the field of view.

54. The system according to claim 53, wherein the actuator is a common actuator arranged for translation of the track scanning sensors in unison relative to the support structure mounting.

55. The system according to claim 54, wherein the actuator comprises a linear actuator and/or the support structure comprises one or more runner arranged to constrain motion of the track scanning sensors in unison to a single degree of freedom.

56. The system according to claim 34, wherein the track scanning sensors comprise at least two track scanning sensors mounted at spaced positions relative to the common support structure and opposingly oriented so as to scan a common railroad track component from opposing sides in use.

57. The system according to claim 34, wherein the track scanning sensors comprise at least one digital image capture sensor and at least one depth detection sensor, wherein the depth detection sensor captures three-dimensional surface data of the one or more track components and the scan data processor automatically identifies features corresponding to the same one or more track components in both the three-dimensional surface data and the images from the digital image capture sensor.

58. The system according to claim 57, wherein the depth detection sensor captures three-dimensional surface data of the one or more track components and the scan data processor automatically identifies features corresponding to the same one or more track components in both the three-dimensional surface data and the images from the digital image capture sensor.

59. The system according to claim 57, comprising one or more light sources attached to the common support structure and arranged to illuminate a region of the railroad track corresponding to the field of view of the track scanning sensors.

60. The system according to claim 59, wherein the illumination form the light source is substantially uniform over a lateral section or width dimension of the track.

61. The system according to claim 34, further comprising a location determination system, the scan data processor arranged to index scan data with a location determination record corresponding to the location at which the scan data was obtained.

62. The system according to claim 61, wherein the location determination system comprises a vehicle travel distance sensor for determining the location of said sensor relative to a fixed datum point on the railroad track.

63. The system according to claim 62, wherein the vehicle travel distance sensor output is correlated with a location reading from a geographic coordinate determining system.

64. The system according to claim 34, wherein the scan data processor is arranged automatically to construct an image of a length of the railroad track from a plurality of consecutive scans from one or more of the track scanning sensors.

65. The system according to claim 34, wherein the scan data comprises one or more matrix of pixel intensity and/or color values and the scan data processor is arranged to identify features in said scan data by clustering pixels according to said intensity and/or color values.

66. The system according to claim 34, comprising one or more light sources attached to the common support structure and arranged to illuminate a region of the railroad track corresponding to the field of view of the track scanning sensors.

67. The system according to claim 66, wherein the illumination form the light source is substantially uniform over a lateral section or width dimension of the track.

68. The system according to claim 34, comprising:

a railroad vehicle travel sensor for sensing the speed, direction and/or travel distance of the railroad vehicle; and

a controller arranged to trigger a scan by the track scanning sensors according to an output of said vehicle travel sensor.

69. The system according to claim 68, wherein the vehicle travel sensor provides a pulsed output, the frequency of which corresponds to vehicle speed and a scan by the track scanning sensors is triggered by each pulse or a predetermined number of pulses.

70. The system according to claim 34, wherein the scan data processor comprises a plurality of processors, wherein at least one processor being arranged to log scan data captured by the plurality of track scanning sensors and associated location data in real time in the data store automatically upon receipt thereof.

71. The system according to claim 70, wherein at least one further processor is arranged to process the captured scan data automatically upon receipt thereof so as to identify track components in real-time or near-real-time.

72. The system according to claim 71, wherein at least one processor is arranged to perform analytical analysis of the scan data in order to identify a status or defect of the identified track components in real-time or near-real-time.

73. The system according to claim 34, wherein the data store comprises a non-volatile data store and a buffer for the scan data processor, the non-volatile data store comprising a database comprising raw scan data obtained from the sensors and a further database comprising track component classification and/or status data logged with a location record corresponding thereto.

74. The system according to claim 34, wherein the scan data processor determines a confidence score for a track component determination according to a degree of a match between a plurality of geometric and/or surface property features of a track component identified in the track scan data and one or more predetermined component features.

75. The system according to claim 34, comprising an alert module arranged to receive the output of the scan data processor and automatically determine whether one or more alert condition is met based on the one or more feature identified in said scan data.

76. The system according to claim 34, further comprising:

a data compression module.

77. The system according to claim 34 adapted for mounting to a passenger or freight revenue generating railway vehicle or locomotives in use.

78. The system according to claim 34, wherein the scan data processor or a further processor in communication therewith is arranged to output track component condition information derived from said track scan data, said track component condition information being provided as a track inspection report for use in planning track maintenance actions including track repair and/or renewal.

79. The system according to claim 78, wherein the asset and condition information, including defect data with location information, is transmitted wirelessly from the vehicle to a central control or data centre from where end-users can retrieve it for further analysis and maintenance planning.

80. The system according to claim 34, further comprising:

a thermal imaging sensor used for component condition analysis.

81. The system according to claim 34, further comprising:

a laser and an imaging capture sensor; and

a motion sensor and position sensor working in combination with the laser and imaging sensors with analytics to measure rail parameters including position, orientation, profile wear, track gauge under both loaded and unloaded conditions, geometry parameters such as twist, super-elevation, curvature, and rail-wheel interface measurements such as the amount of hunting of wheel on the track.

82. The system according to claim 81, further comprising:

an image capture sensor comprising a light sensor for sensing brightness and/or colour within a visible wavelength band.

83. The system according to claim 82, wherein the image capture sensor is any combination of an area scan imaging sensor, a linescan imaging sensor, a three-dimensional surface profile sensor and an asset distance sensor.

84. The system according to claim 83, further comprising:

a three-dimensional surface profile sensor and/or the asset distance sensor comprises a laser sensor device.

85. The system according to claim 82, wherein the image capture sensor is used with an asset/defect classifier and/or an asset/defect status analyser correlates an asset/defect feature in an image captured by one sensor with a corresponding image captured by one or more further sensor.

86. The system according to claim 85, wherein the asset feature comprises an edge profile and/or dimension of the asset and geometric feature or template matching is used to determine a degree of similarity between the feature of the detected asset and a predetermined geometric feature or template.

87. The system according to claim 85, wherein the asset feature comprises a surface property profile of the asset and surface property feature or template matching is used to determine a degree of similarity between the feature of the detected asset and a predetermined surface property feature or template.

88. The system according to claim 82, comprising a plurality of asset classifiers and an asset status analyser comprising two or more of a rule-based classifier, a template-based classifier and a statistical feature matching tool.

89. The system according to claim 34, wherein the scan data processor identifies one or more pixel clusters within an image according to one or more pixel brightness or colour property, each pixel clusters being used by the asset classifier and/or asset status analyser used to determine an edge, colour, texture or shape feature of an asset which is used to determine its condition and position of defects.

90. The system according to claim 89, wherein the predetermined asset status comprises a previously determined asset status characteristic, and the asset status analyser determines a change in asset orientation, shape, edge and/or color relative to the previously determined asset status characteristic.

91. The system according to claim 85, wherein the operation of the image processor comprising the asset classifier and/or asset status analyser is automated upon receipt of captured image data and/or location determination data.

92. The system according to claim 85, wherein the asset classifier and asset status analyser perform automated image analytics by use of software modules for processing image data to generate one or more output comprising the identity, properties and condition of each identified asset.

93. The system according to claim 34, further comprising:

a transmitter arranged to transmit a visual output signal to an operator console, the visual output signal comprising any or any combination of 2D or 3D maps indicating identified assets, asset risk reports, defects, and/or asset data graphs suitable for maintenance purposes.

94. The system according to claim 34, further comprising:

a local data store, wherein captured images from an image capture sensor and location data from a location determining system are indexed by the processor within one or more database in the local data store.

95. The system according to claim 34, further comprising:

a linescan x-ray imaging sensor coupled with an x-ray source and used to image the inside of components such as rails, whereas such images are further processed with analytics software to diagnose internal flaws.

96. A railroad track inspection method comprising:

operating an image capture sensor mounted on a railroad vehicle during motion of the railroad vehicle along a track;

determining and logging a location of the image capture sensor for each image captured by the sensor; and

automatically processing the captured images upon receipt using one or more computer processor by detecting an asset in one or more captured image and classifying the detected asset by assigning an asset type to the detected asset from a predetermined list of asset types according to one or more feature identified in the captured image, and identifying an asset status characteristic including the recognition and measurement of defects and comparing the identified status characteristic to a predetermined asset characteristic so as to evaluate a deviation therefrom.

97. A data carrier comprising machine readable code of the operation of railroad track asset survey image processor configured to:

receive images captured by an image capture sensor mounted on a railroad vehicle during motion of the railroad vehicle along a track;

log a geographic location for each image captured by the sensor;

process the captured images by detecting an asset in one or more captured image and classifying the detected asset by assigning an asset type to the detected asset from a predetermined list of asset types according to one or more feature identified in the captured image; and

identify an asset status characteristic and comparing the identified status characteristic to a predetermined asset characteristic so as to evaluate a deviation therefrom, and output an asset status indication based upon said deviation.

98. The data carrier according to claim 97, comprising individual modules responsible for:

real-time data acquisition of said images and geographic locations;

high speed data analysis comprising said classifying the detected asset identifying asset status characteristic, defect recognition and, transfer of asset status indications to one or more external interfaces, wherein the high speed data analysis module is selectively usable and/or reprogrammable.

99. The data carrier according to claim 97, wherein the image capture sensor comprises one or more of linescan, area scan, x-ray and thermal imaging sensors mounted with a view of the rail track and the machine readable instructions for classifying the asset and/or outputting the asset status indication including recognition and measurement of defects comprise a plurality of image analysis operators for any combination or all of edge detection, edge analysis, texture analysis, shape analysis, statistical analysis of pixel distribution data, color analysis, image enhancement, image segmentation, template matching using statistical and neural network methods, feature based object recognition, rail track environment semantic knowledge analysis.

100. The data carrier according to claim 97 comprising instructions to store in a database an image location for the assets and their defects including an asset/defect boundary, minimum and maximum image coordinates in horizontal and vertical directions, a centroid for the asset/defect and one or more visual feature of the asset/defect such as a colour or topology features.