摘要
采用人工神经网络技术对与微钻头破损有因果关系的轴向力、扭矩和主电机电流等多种物理量进行信息融合,建立了适合于微小孔数控钻床的钻头破损在线监测系统,并验证了该系统对钻头破损的检出率达94.5%以上,证明了该系统在生产上应用的有效性。
Multi-information amalgamation is done for axial force,torque and main motor current and so on,which represent the causal relationship to micro-drills breakage,by using artificial neural network technology.An in-process monitoring system for micro-hole numerical control drill press is built up based on artificial neural networks. Experiments demonstrate the rate of checking out micro-drills breakage has reached 94.5% and the system has practicality value very well.
出处
《汽车工艺与材料》
2006年第11期21-23,共3页
Automobile Technology & Material
基金
吉林省科技发展计划项目(20010574)
关键词
微钻头
破损
状态监测
人工神经网络
信息融合
micro-drill
breakage
status monitoring
artificial neural networks
multi- information amalgamation
