Research on Cutting Tool Edge Geometry Design based on SVR-PSO
preprint
OA: closed
Abstract
In order to optimize the design of tool edge, an intelligent method was used for modeling and optimization. The tool edge design method based on Support Vector Regression (SVR) and Particle Swarm Optimization (PSO) was proposed. By combining tool edge parameters and processing condition parameters, and learning from empirical data, a functional model was established between tool life, edge parameters, and processing condition parameters. Taking the tool life as the objective function, the optimal edge profile design parameters were solved under different processing condition parameters. The T-shape tool validates was taken as a case for verification. The SVR-PSO function model was established and solved based on the processing condition parameters, and the optimized edge design parameters and predicted tool life were obtained. The results showed that the deviation between the calculated and actual tool life was less than 6.4%. This method was feasible and practical, and has been applied in the design department of tool manufacturing companies.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
Source provenance
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00