Method for automatic detection and measurement of wear of a drilling tool based on machine vision

Abstract

This invention provides a machine vision-based automatic detection and measurement method for drill tool wear, comprising the following steps: Steps S1-S2, acquiring images of worn drill tools and new drill tools; Step S3, preprocessing the images to obtain preprocessed images; Step S4, performing image segmentation and edge extraction on the preprocessed images to obtain the tool edges; Step S5, obtaining the edge image of the worn area of ​​the drill tool based on the tool edges; Step S6, calculating the number of pixels in the worn area; Step S7, fitting sub-pixel edge curves; Step S8, calculating the number of pixels in the maximum worn width; Step S9, calculating the pixel equivalent; Step S10, calculating the worn area and maximum worn width of the worn drill tool as wear data based on the pixel equivalent, the number of pixels in the worn area, and the number of pixels in the maximum worn width. In summary, this method can achieve high-precision automatic detection of drill tool wear.

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