ACO threshold segmentation algorithm based on regional dual thresholding optimization

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 pro...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology Vol. 140; no. 9-10; pp. 4875 - 4887
Main Authors: Liu, Zhiqiang, Chen, Song, Wan, Jiaxing, Guo, Chengjun, Wang, Ye
Format: Journal Article
Language:English
Published: London Springer London 01.10.2025
Springer Nature B.V
Subjects:
Algorithms
Ant colony optimization
CAE) and Design
Cameras
Computer-Aided Engineering (CAD
Cutting tools
Engineering
Heuristic
Industrial and Production Engineering
Mechanical Engineering
Media Management
Optimization algorithms
Original Article
Pheromones
Probability
Sensors
Tool wear
Vibration
Workpieces
The regional ideal solution
ACO algorithm
Dual-threshold optimization-seeking algorithm
The regional optimal solution
Tool wear
ISSN:0268-3768, 1433-3015
Online Access:Get full text
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Summary: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.
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-025-16473-z