摘要
研究了钻削过程中刀具在线磨损状态特征信号的提取方法。以轴向力和扭矩为监测信号,在普通钻床上建立起相应的实时信号数据采集系统,通过对信号进行幅域和频域分析,提取了特征信号随刀具磨损量增加的变化规律,为实现机械加工过程刀具状态的智能识别提供了依据。试验结果表明,该方法具有较好的抗干扰能力和较高的识别精度。
The extracting method of on-line wear character signal of drilling tool is studied. The signal collecting system is set up on the drilling machine with axial and torque force as monitoring signals. Based on the time domain and frequency domain analysis of tool wear signals, the rule of character signal variation according to the increasing tool wear is generalized to be used to deal with the intelligent identification of the degree of tool wear on-line. The experimental result shows that the system has good antidisturbing capability and high identification accuracy.
出处
《工具技术》
北大核心
2005年第8期79-82,共4页
Tool Engineering
基金
机械工业发展基金资助项目(项目编号:CF0013)
