Study on wear state evaluation of friction stir welding tools based on image of surface topography

The status of the friction stir welding tool is an important factor affecting weld quality. The texture feature of the weld surface is the result of friction between tool and material. In this paper, friction stir welding experiments were performed on 2219 aluminum alloys with tools under different wear conditions to observe the changes in surface topography characteristics. The results show that the tool wear will lead to the confusion of the weld texture profile and the appearance of the local burr. Furthermore, we proposed a feature extraction method for weld surface images based on an improved local binary pattern algorithm, which can obtain local subtle feature changes. Euclidean distance similarity was used to evaluate the weld surface image, the results show that it has a good correlation with the wear state of the tool.

Automated summary

The study conducted friction stir welding experiments on 2219 aluminum alloys with tools under different wear conditions, and found that tool wear affects the texture feature of the weld surface. An improved local binary pattern algorithm was proposed for feature extraction from weld surface images, which can capture subtle local feature changes. Euclidean distance similarity was used to evaluate the weld surface image, showing a good correlation with the wear state of the tool.