基于神经网络算法的GH4169插铣刀具寿命预测研究  

Research on Tool Life Prediction of GH4169 in Plunge Milling Based on Neural Network

作　　者：李锋[1] 陈振 赵德中 李晨旭 刘维伟[2] LI Feng;CHEN Zhen;ZHAO De-zhong;无(Xi'an Aviation University,Xi'an 710089;Northwestern Polytechnical University,Xi'an 710072)

机构地区：[1]西安航空学院,西安710089 [2]西北工业大学,西安710072

出　　处：《航空精密制造技术》2023年第4期17-20,共4页Aviation Precision Manufacturing Technology

基　　金：陕西省自然科学基础研究计划项目(2022JQ-503)。

摘　　要：为了研究GH4169插铣加工中切削参数对刀具寿命的影响规律,延长刀具使用寿命,设计了GH4169插铣参数与刀具寿命之间的正交试验。基于正交试验获得的样本数据,利用径向基函数神经网络和反向传播神经网络分别建立了GH4169插铣刀具寿命的预测模型,并对模型进行了训练、测试与验证。该方法可为GH4169插铣刀具寿命模型的建立,工艺参数的优选提供依据。To study the influence of cutting parameters on tool life in plunge milling GH4169 and improve tool life,the orthogonal test of GH4169 between plunge milling parameters and tool life was designed.Based on the sample data obtained from the orthogonal test,the prediction model of tool life in plunge milling GH4169 were established by radial basis function neural network and back-propagation neural network respectively,and the models were trained,tested and verified.The method can provide a basis for the establishment of GH4169 plunge milling tool life model and the optimization of cutting parameters.

关 键 词：GH4169 插铣加工 刀具寿命 径向基函数神经网络 反向传播神经网络 

分 类 号：TG147[一般工业技术—材料科学与工程]