基于改进的BP神经网络对切削参数的优化选择  

Optimization Choice of Cutting Parameter Based on Improved BP Neural Network

作　　者：赵韩[1] 冯宝林[1] 董晓慧[1] 吴振华[1] 

机构地区：[1]合肥工业大学机械与汽车工程学院,合肥230009

出　　处：《机床与液压》2008年第F05期213-215,226,共4页Machine Tool & Hydraulics

基　　金：国家科技攻关计划项目(2005BA201A83-01);安徽省科技局攻关项目支持(40120513)

摘　　要：为了在切削零件时能合理选择切削参数并充分发挥机床的效能,建立了改进的BP神经网络,用样本集来训练和检测BP神经网络。实现了对切削参数的优化选择和切除率的预测,为切削参数的选择提供了理论依据。实例表明,采用BP神经网络优选的切削参数进行加工,能明显地降低成本、提高生产效率。In order to reasonably choose cutting parameter and fully exert machine potential when cutting components, improved BP neural network was established and it was trained and examined with the sample collection. Optimization choice of cutting parameter and forecast of excision rate was carried out and it provides the theory basis for cutting parameter choice. The examples indicate that it could obviously reduce the cost and enhance production efficiency to carry on the processing by optimal cutting parameter of BP neural network.

关 键 词：切削参数 BP算法 改进的神经网络 优化选择 

分 类 号：TH162[机械工程—机械制造及自动化]