基于BP神经网络的微孔钻削实时监测  

Real-time Monitoring on Micro-hole Drill Based on BP Neural Network

作　　者：李雪[1] 熊建桥[1] 邵秋萍[1] 欧益宝[1] 

机构地区：[1]南京工程学院机械工程学院,江苏南京211167

出　　处：《机床与液压》2010年第20期12-14,共3页Machine Tool & Hydraulics

基　　金：南京工程学院引进人才启动资金项目(KXJ08134;KXJ08133)

摘　　要：为防止微孔钻削过程中钻头折断,研制微孔钻削在线监测系统。该系统以主轴电机三相电流对应的电压信号为监测对象,应用神经网络建立钻头磨损状态与信号特征的关系模型,以此获取隐含微细钻头磨损状态的信息值。实验结果表明,应用此系统进行微孔钻削在线监测,可以有效避免微钻头的折断,提高钻头的利用率。An on-line micro-hole drilling monitoring and control system was developed to avoid the drill breaking during the process of micro hole drilling.By monitoring the voltage signal connected with 3 phase current of the spindle motor,a model between the drill wearing states and the signal characteristics was built based on neural network and the corresponding information that included connotative wearing states of micro-size drill was obtained.The test results show that on-line micro-hole drilling monitoring with the above system can avoid effectively the drill breaking and improve the utilization ratio of the drill.

关 键 词：神经网络 微孔钻削 实时监测 

分 类 号：TP206.1[自动化与计算机技术—检测技术与自动化装置]