Measurement of belt wear through edge detection of a raster image
Tools for determining belt wear are provided. Specifically, non-contact based systems and processes are described which enable a quick and accurate measurement of belt wear. Based on the measurements of belt wear, a wear condition for the belt can be determined. Information regarding the wear condition can then be used to determine an appropriate remedial measure for responding to the determined wear condition.
1. A method of measuring a wear condition of a belt, comprising:
obtaining a raster image of the belt, the raster image including image data for at least one feature of the belt including at least a portion of a rib not co-located with a belt edge;
analyzing the raster image of the belt;
based on the analysis of the raster image of the belt, determining physical dimensions of the at least one feature of the belt;
based on the determined physical dimensions of the at least one feature of the belt, determining a wear condition for the at least the portion of the rib;
preparing a report that includes the results of the analysis of the raster image of the belt and the determined wear condition for the belt; and
transmitting the report to a user device operated by at least one interested party.
2. The method of claim 1 , wherein the at least one feature of the belt comprises one or more belt ribs, wherein analyzing the raster image of the belt comprises:
converting a first image of the belt to a binary pixel data image of the belt, wherein the conversion of the first image to the black-and-white image is performed by:
determining a minimum threshold that corresponds to a minimum pixel value where a determined number of belt ribs equals an expected number of belt ribs;
determining a maximum threshold that corresponds to a maximum pixel value where a determining number of belt ribs equals the expected number of belt ribs; and
determining an average of the minimum threshold and maximum threshold and using the determined average as a threshold for converting the first image to the binary pixel data image.
3. The method of claim 2 , wherein the first image comprises a color image and wherein the determined threshold for converting the first image to the binary pixel data image corresponds to threshold values for red, green, and blue pixel color values.
4. The method of claim 2 , wherein the first image comprises a greyscale image and wherein the determined threshold for converting the first image to the binary pixel data image corresponds to a greyscale pixel value.
5. The method of claim 1 , wherein the user device to which the report is transmitted is the same device which captured the raster image of the belt.
6. The method of claim 1 , wherein the physical dimensions of the at least one feature of the belt are determined by determining a conversion value that when multiplied by a number of pixels corresponds to a physical dimension, wherein the conversion value is determined by calculating the number of pixels between a detected first edge of the belt and a detected second edge of the belt.
7. The method of claim 6 , wherein the detected first edge and detected second edge are detected as contours that traverse an entire length of a zoom window placed around at least one feature of the belt and the first and second edges of the belt.
8. The method of claim 1 , wherein the wear condition for the belt comprises at least one of good, bad, and questionable and wherein the wear condition for the belt is determined by comparing a detected distance between a first feature of the belt and a second feature of the belt and comparing the detected distance with an expected distance.
9. The method of claim 8 , wherein the expected distance is retrieved from an object database that comprises data about a plurality of different types of belts, wherein the data for each of the plurality of different types of belts includes one or more of belt identifier, rib count, rib profile, thresholds, wear history, and replacement history.
10. The method of claim 1 , further comprising modifying an operating parameter of equipment that is using the belt based on the wear data of the belt.
11. A method of measuring a wear condition of a belt, comprising:
obtaining a raster image of the belt, the raster image including image data for at least one feature of the belt;
analyzing the raster image of the belt;
based on the analysis of the raster image of the belt, determining physical dimensions of the at least one feature of the belt;
based on the determined physical dimensions of the at least one feature of the belt, determining a wear condition for the belt;
preparing a report that includes the results of the analysis of the raster image of the belt and the determined wear condition for the belt;
transmitting the report to a user device operated by at least one interested party; and
wherein the at least one feature of the belt comprises one or more belt ribs, wherein analyzing the raster image of the belt comprises:
converting a first image of the belt to a binary pixel data image of the belt, wherein the conversion of the first image to the black-and-white image is performed by:
determining a minimum threshold that corresponds to a minimum pixel value where a determined number of belt ribs equals an expected number of belt ribs;
determining a maximum threshold that corresponds to a maximum pixel value where a determining number of belt ribs equals the expected number of belt ribs; and
determining an average of the minimum threshold and maximum threshold and using the determined average as a threshold for converting the first image to the binary pixel data image.
12. The method of claim 11 , wherein the user device to which the report is transmitted is the same device which captured the raster image of the belt.
13. The method of claim 11 , wherein the physical dimensions of the at least one feature of the belt are determined by determining a conversion value that when multiplied by a number of pixels corresponds to a physical dimension, wherein the conversion value is determined by calculating the number of pixels between a detected first edge of the belt and a detected second edge of the belt.
14. The method of claim 13 , wherein the detected first edge and detected second edge are detected as contours that traverse an entire length of a zoom window placed around at least one feature of the belt and the first and second edges of the belt.
15. The method of claim 11 , wherein the wear condition for the belt comprises at least one of good, bad, and questionable and wherein the wear condition for the belt is determined by comparing a detected distance between a first feature of the belt and a second feature of the belt and comparing the detected distance with an expected distance.
16. The method of claim 15 , wherein the expected distance is retrieved from an object database that comprises data about a plurality of different types of belts, wherein the data for each of the plurality of different types of belts includes one or more of belt identifier, rib count, rib profile, thresholds, wear history, and replacement history.
17. The method of claim 11 , wherein the first image comprises a color image and wherein the determined threshold for converting the first image to the binary pixel data image corresponds to threshold values for red, green, and blue pixel color values.
18. The method of claim 17 , wherein the physical dimensions of the at least one feature of the belt are determined by determining a conversion value that when multiplied by a number of pixels corresponds to a physical dimension, wherein the conversion value is determined by calculating the number of average pixels between adjacent ribs.
19. The method of claim 17 , wherein the detected first edge and detected second edge are detected as the inner edges of the outermost regions.
20. The method of claim 11 , wherein the first image comprises a greyscale image and wherein the determined threshold for converting the first image to the binary pixel data image corresponds to a greyscale pixel value.