农机化研究2025，Vol.47Issue(8)：259-265,7.DOI:10.13427/j.issn.1003-188X.2025.08.036
沙柳平茬刀具减磨优化
Optimization of Wear Reduction of Salix Cheilophila Cutting Tools Based on PSO-BP Neural Network Combined with GA Algorithm
摘要
Abstract
Salix cheilophila is one of the major shrubs for sand fixation and windbreak in northwest China.Mechanized cutting of Salix cheilophila plants plays an important role in ecological protection and socio-economic development.However,severe wear of circular saw blades has been a main technical bottleneck restricting working efficiency and cutting effects.To optimize the wear-resistant design of circular saw blades for Salix cheilophila cutting,this study collected wear degradation data of different tooth structures through field experiments.PSO(Particle Swarm Optimization)algorithm op-timized BP(Back Propagation)neural network model was established based on the wear data for predicting the wear amount of circular saw blades.Then,the trained PSO-BP neural network model was combined with GA(Genetic Algo-rithm),with minimum wear amount as the optimization goal,to search for the optimal parameters of circular saw blade tooth structure.The results showed that the established model successfully realized multi-objective optimization of struc-tural parameters such as front angle,rear angle and front bevel grinding angle of circular saw blades.The optimized circu-lar saw blade parameters achieved minimum wear,thereby enhancing the wear resistance of circular saw blades.This study provides a new design concept to further improve the cutting and wear resistance of circular saw blades for Salix chei-lophila cutting.It offers important technical support to improve the working efficiency of Salix cheilophila cutting and is beneficial to ecological protection and sustainable agriculture development.关键词
沙柳/平茬圆锯片/减磨优化/PSO-BP神经网络/遗传算法Key words
Salix cheilophila/circular saw blade/optimization of wear reduction/PSO-BP neural network/genetic algo-rithm分类
金属材料引用本文复制引用
韩志武,刘志刚,常涛涛,裴承慧,张鹏峰,张建强..沙柳平茬刀具减磨优化[J].农机化研究,2025,47(8):259-265,7.基金项目
内蒙古自治区科技计划项目(2021GG0423) （2021GG0423）
内蒙古自治区自然科学基金项目(2021MS05006) （2021MS05006）
