Contour Detection Algorithm for α Phase Structure of TB6 Titanium Alloy fused with Multi-Scale Fretting Features

Abstract Aiming at the problems of inaccuracy in detecting the α phase contour of TB6 titanium alloy. By combining computer vision technology with human vision mechanisms, the spatial characteristics of the α phase can be simulated to obtain the contour accurately. Therefore, an algorithm for α phase contour detection of TB6 titanium alloy fused with multi-scale fretting features is proposed. Firstly, through the response of the classical receptive field model based on fretting and the suppression of new non-classical receptive field model based on fretting, the information maps of the α phase contour of the TB6 titanium alloy at different scales are obtained; then the information map of the smallest scale contour is used as a benchmark, the neighborhood is constructed to judge the deviation of other scale contour information, and the corresponding weight value is calculated; finally, Gaussian function is used to weight and fuse the deviation information, and the contour detection result of TB6 titanium alloy α phase is obtained. In the Visual Studio 2013 environment, 484 metallographic images with different temperatures, strain rates, and magnifications were tested. The results show that the performance evaluation F value of the proposed algorithm is 0.915, which can effectively improve the accuracy of α phase contour detection of TB6 titanium alloy.