ACO threshold segmentation algorithm based on regional dual thresholding optimization - Liu, Zhiqiang; Chen, Song; Wan, Jiaxing; Guo, Chengjun; Wang, Ye (International journal of advanced manufacturing technology, 2025)
Tool wear state is one of the important factors that directly affect the quality of workpiece processing, such as manual observation of tool wear; due to subjective factors and observation errors, this will lead to reduced processing productivity, workpiece damage, and so on. Aiming at the above problems, this paper proposes an online tool wear detection method based on ant colony optimization algorithm to calculate the regional optimal solution for tool wear, and then, based on dual-threshold optimization-seeking algorithm, to calculate the regional ideal solution. Experiments show that this algorithm solves the problem that the direct ACO algorithm (ant colony optimization algorithm) tool wear detection is easy to fall into the local optimal solution and solves the problem of not being able to recognize correctly due to the interference of strong light by the calculation of the regional optimal solution through the dual-threshold optimization-seeking algorithm. Verification experiments show that the algorithm is still able to automatically and effectively identify the size of the complete wear area when it is used for more complex wear area identification and has the characteristics of high identification accuracy and clear outline of the identification area.