Conveyor belt monitoring system and method

• US 10,043,258 B2
• Filed: 03/22/2016
• Issued: 08/07/2018
• Est. Priority Date: 04/27/2015
• Status: Active Grant

• Current Assignee: The Thermoteknix Systems Limited
• Original Assignee: The Thermoteknix Systems Limited
• Inventors: Salisbury, Richard, Mitchell, Andrew
• Primary Examiner(s): Elahi, Shan E
• Application Number:
  US15/076,898
• Publication Number:
  US 20160314573A1
• Time in Patent Office: 868 Days
• Field of Search: 348164
• CPC Class Codes: B65G 43/02 detecting dangerous physical condition of load carriers, e.g. for interrupting the drive in the event of overheating
• CPC Class Codes: G01J 2005/0029 Sheet
• CPC Class Codes: G01J 2005/0077 Imaging
• CPC Class Codes: G01J 5/0022 for sensing the radiation of moving bodies
• CPC Class Codes: G01J 5/0066 for hot spots detection
• CPC Class Codes: G01J 5/026 Control of working procedures of a pyrometer, other than calibration; Bandwidth calculation; Gain control
• CPC Class Codes: G01J 5/07 Arrangements for adjusting the solid angle of collected radiation, e.g. adjusting or orienting field of view, tracking position or encoding angular position optical collimating elements G01J5/0806
• CPC Class Codes: G01J 5/10 using electric radiation detectors
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06T 2207/10048 Infrared image
• CPC Class Codes: G06T 2207/20024 Filtering details
• CPC Class Codes: G06T 2207/30164 Workpiece; Machine component
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: H04N 23/23 from thermal infrared radiation
• CPC Class Codes: H04N 25/701 Line sensors
• CPC Class Codes: H04N 5/33 Transforming infrared radiation cameras or camera modules for generating image signals from infrared radiation H04N23/20; circuitry of SSIS for transforming infrared radiation into image signals H04N25/20

Abstract

A conveyor belt temperature anomaly detection system, comprising: an infrared line scanner having one or more infrared detectors and arranged to scan the surface of a conveyor belt in a direction perpendicular to the direction of travel of the conveyor belt and to generate thermal image data in dependence on infrared radiation detected by the infrared detector; and a processing unit configured to process the thermal image data to identify temperature anomalies in the material travelling on the surface of the conveyor belt.

Claims

1. A conveyor belt temperature anomaly detection system, comprising:

an infrared line scanner having one or more infrared detectors and arranged to scan the surface of a conveyor belt in a direction perpendicular to the direction of travel of the conveyor belt and to generate thermal image data in dependence on infrared radiation detected by the infrared detector; and

a processing unit configured to perform processing operations to process the thermal image data to identify temperature anomalies in the material travelling on the surface of the conveyor belt, the processing operations including;

receiving a plurality of scan lines from the infrared line scanner, the scan lines comprising a plurality of pixels each having a pixel value corresponding to a temperature of the material detected at that pixel;

assembling a thermal image of the conveyor belt from the plurality of scan lines, the thermal image made up of the plurality of pixels;

filtering the image to remove high frequency spatial information from the image to remove small temperature anomalies from the thermal image; and

identifying, in the thermal image, groups of pixels having anomalous pixel values corresponding to temperature anomalies in the material.

2. The conveyor belt temperature anomaly detection system of claim 1, wherein the filtering comprises:

scanning a filter window over the thermal image; and

at each scan position of the filter window, calculating a filtered pixel value for the pixel centred in the filter window, the filtered pixel value equal to one of;

a) the value of a mean of the pixels within the filter window; and

b) the value of a weighted average of the pixels within the filter window.

3. The conveyor belt temperature anomaly detection system of claim 2, wherein the dimensions of the filter window correspond to the minimum dimensions of anomalies to be detected by the belt.

4. The conveyor belt temperature anomaly detection system of claim 2, wherein the weighting of the weighted average is such that pixels closer to the centre of the filter window contribute more to the filtered pixel value than pixels further away from the centre of the filter window.

5. The conveyor belt temperature anomaly detection system of claim 1, wherein the identifying comprises:

selecting first pixels in the thermal image having a pixel value exceeding a first predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected first pixels together.

6. The conveyor belt temperature anomaly detection system of claim 5, wherein the identifying further comprises:

selecting second pixels in the thermal image having a pixel value exceeding a second predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected second pixels together.

7. The conveyor belt temperature anomaly detection system of claim 6, wherein the identifying further comprises determining whether each group of first pixels has size greater than a first predetermined threshold size and/or determining whether each group of second pixels has a size greater than a second predetermined threshold size.

8. The conveyor belt temperature anomaly detection system of claim 1, further comprising an input for receiving an indication of conveyor belt speed from the conveyor belt, wherein the thermal image is assembled in dependence on the received conveyor belt speed indication.

9. The conveyor belt temperature anomaly detection system of claim 1, further comprising a display operable to display the thermal image data and one or more indications of the identified temperature anomalies in the thermal image.

10. The conveyor belt temperature anomaly detection system of claim 9, wherein the one or more indications comprise lines drawn around the anomalies in the thermal image.

11. The conveyor belt temperature anomaly detection system of claim 1, further comprising an input device for receiving threshold criteria for identifying the temperature anomalies.

12. The conveyor belt temperature anomaly detection system of claim 1, wherein the line scanner comprises a linear array of infrared detectors arranged to electronically scan the width of the conveyor belt.

13. A conveyor belt temperature anomaly detection system, comprising:

a two dimensional array of infrared detectors arranged to receive infrared radiation from the surface of a conveyor belt and to generate thermal image data in dependence on the received infrared radiation; and

a processing unit configured to perform processing operations to process the thermal image data to identify temperature anomalies in the material travelling on the surface of the conveyor belt, the processing operations including;

receiving the thermal image data from the array of infrared detectors, the thermal image data comprising a plurality of pixels each having a pixel value corresponding to a temperature value of the material detected by that pixel;

assembling a thermal image of the conveyer belt from the plurality of pixels;

filtering the image to remove high frequency spatial information from the image to remove small temperature anomalies from the thermal image; and

identifying, in the thermal image, groups of pixels having anomalous pixel values corresponding to temperature anomalies in the material.

14. The conveyor belt temperature anomaly detection system of claim 13, wherein the filtering comprises:

scanning a filter window over the thermal image; and

at each scan position of the filter window, calculating a filtered pixel value for the pixel centred in the filter window, the filtered pixel value equal to one of;

a) the value of a mean of the pixels within the filter window; and

b) the value of a weighted average of the pixels within the filter window.

15. The conveyor belt temperature anomaly detection system of claim 14, wherein the dimensions of the filter window correspond to the minimum dimensions of anomalies to be detected by the belt.

16. The conveyor belt temperature anomaly detection system of claim 14, wherein the weighting of the weighted average is such that pixels closer to the centre of the filter window contribute more to the filtered pixel value than pixels further away from the centre of the filter window.

17. The conveyor belt temperature anomaly detection system of claim 13, wherein the identifying comprises:

selecting first pixels in the thermal image having a pixel value exceeding a first predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected first pixels together.

18. The conveyor belt temperature anomaly detection system of claim 17, wherein the identifying further comprises:

selecting second pixels in the thermal image having a pixel value exceeding a second predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected second pixels together.

19. The conveyor belt temperature anomaly detection system of claim 17, wherein the identifying further comprises determining whether each group of first pixels has size greater than a first predetermined threshold size and/or determining whether each group of second pixels has a size greater than a second predetermined threshold size.

20. The conveyor belt temperature anomaly detection system of claim 13, further comprising an input for receiving an indication of conveyor belt speed from the conveyor belt, wherein the thermal image is assembled in dependence on the received conveyor belt speed indication.

21. The conveyor belt temperature anomaly detection system of claim 13, further comprising a display operable to display the thermal image data and one or more indications of the identified temperature anomalies in the thermal image.

22. The conveyor belt temperature anomaly detection system of claim 21, wherein the one or more indications comprise lines drawn around the anomalies in the thermal image.

23. The conveyor belt temperature anomaly detection system of claim 13, further comprising an input device for receiving threshold criteria for identifying the temperature anomalies.

24. The conveyor belt temperature anomaly detection system of claim 13, wherein the line scanner comprises a linear array of infrared detectors arranged to electronically scan the width of the conveyor belt.

25. A method for detecting temperature anomalies in material transported on a conveyor belt, the method comprising:

scanning an infrared line scanner across the surface of the conveyor belt in a direction perpendicular to the direction of travel of the conveyor belt;

generating thermal image data based on infrared radiation received by the infrared line scanner from the material travelling on the conveyor belt; and

processing the thermal image data to identify temperature anomalies in material travelling on the surface of the conveyor belt, wherein the processing comprises;

receiving a plurality of scan lines in the generated thermal image data, the scan lines comprising a plurality of pixels having pixel values;

assembling a thermal image of the conveyor belt from the plurality of scan lines, the thermal image made up of the plurality of pixels;

filtering the thermal image to remove high frequency spatial information to remove small temperature anomalies from the thermal image; and

identifying, in the thermal image, groups of pixels having anomalous pixel values corresponding to temperature anomalies in the material.

26. The method of claim 25, wherein the filtering comprises:

scanning a filter window over the thermal image; and

at each scan position of the filter window, calculating a filtered pixel value for the pixel centred in the filter window, the filtered pixel value equal to one of;

a) the value of the mean of the pixels within the filter window; and

b) the value of a weighted average of the pixels within the filter window.

27. The method of claim 26, wherein the dimensions of the filter window correspond to the minimum dimensions of anomalies to be detected by the belt.

28. The method of claim 27, wherein the weighting of the weighted average is such that pixels closer to the centre of the filter window contribute more to the filtered pixel value than pixels further away from the centre of the filter window.

29. The method of claim 25, wherein the identifying comprises:

selecting first pixels in the thermal image having a pixel value exceeding a first predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected first pixels together.

30. The method of claim 29, wherein the identifying further comprises:

selecting second pixels in the thermal image having a pixel value exceeding a second predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected second pixels together.

31. The method of claim 29, further comprising determining whether each group of first pixels has size greater than a first predetermined threshold size and/or determining whether each group of second pixels has a size greater than a second predetermined threshold size.

32. The method of claim 25, further comprising receiving an indication of belt speed from the conveyor belt, the thermal image being assembled in dependence on the received conveyor belt speed indication.

33. The method of claim 25, further comprising receiving threshold criteria for identifying the temperature anomalies.

34. The method of claim 25, further comprising displaying, on a display, the thermal image data alongside an indication of the identified temperature anomalies.

35. The method of claim 34, wherein the indication comprises lines drawn around the anomalies in the thermal image.

36. A method for detecting temperature anomalies in material transported on a conveyor belt, the method comprising:

directing a two dimensional array of infrared detectors toward a surface of the conveyor belt;

generating thermal image data in dependence on received infrared radiation; and

processing the thermal image data to identify temperature anomalies in the material travelling on the surface of the conveyor belt, wherein the processing the thermal image data comprises;

receiving the thermal image data from the array of detectors, the thermal image data comprising a plurality of pixels each having a pixel value corresponding to a temperature value of the material detected by that pixel;

assembling a thermal image of the conveyer belt from the plurality of pixels;

filtering the thermal image to remove high frequency spatial information to remove small temperature anomalies from the thermal image; and

identifying, in the thermal image groups of pixels having anomalous pixel values corresponding to temperature anomalies in the material.

37. The method of claim 36, wherein the filtering comprises:

scanning a filter window over the thermal image; and

at each scan position of the filter window, calculating a filtered pixel value for the pixel centred in the filter window, the filtered pixel value equal to one of;

a) the value of the mean of the pixels within the filter window; and

b) the value of a weighted average of the pixels within the filter window.

38. The method of claim 37, wherein the dimensions of the filter window correspond to the minimum dimensions of anomalies to be detected by the belt.

39. The method of claim 38, wherein the weighting of the weighted average is such that pixels closer to the centre of the filter window contribute more to the filtered pixel value than pixels further away from the centre of the filter window.

40. The method of claim 36, wherein the identifying comprises:

selecting first pixels in the thermal image having a pixel value exceeding a first predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected first pixels together.

41. The method of claim 40, wherein the identifying further comprises:

selecting second pixels in the thermal image having a pixel value exceeding a second predetermined threshold temperature; and

grouping neighbouring or near neighbouring selected second pixels together.

42. The method of claim 40, further comprising determining whether each group of first pixels has size greater than a first predetermined threshold size and/or determining whether each group of second pixels has a size greater than a second predetermined threshold size.

43. The method of claim 36, further comprising receiving an indication of belt speed from the conveyor belt, the thermal image being assembled in dependence on the received conveyor belt speed indication.

44. The method of claim 36, further comprising receiving threshold criteria for identifying the temperature anomalies.

45. The method of claim 36, further comprising displaying, on a display, the thermal image data alongside an indication of the identified temperature anomalies.

46. The method of claim 45, wherein the indication comprises lines drawn around the anomalies in the thermal image.

47. A non-transitory machine-readable storage medium containing machine-readable instructions configured to cause a processor of a conveyor belt temperature anomaly detection system to perform operations for processing thermal image data to identify temperature anomalies in material travelling on a surface of a conveyor belt, the operations comprising:

receiving a plurality of scan lines of thermal image data associated with material travelling on the conveyor belt, the scan lines comprising a plurality of pixels having pixel values;

assembling a thermal image of the conveyor belt from the plurality of scan lines, the thermal image made up of the plurality of pixels;

filtering the thermal image to remove high frequency spatial information to remove small temperature anomalies from the thermal image; and

identifying, in the thermal image, groups of pixels having anomalous pixel values corresponding to temperature anomalies in the material.