摘要
本研究通过分析铣刀渐进磨损过程的特点,从切削力、主轴端振动位移、主轴端振动加速度和主轴电机功率等信号中提取了8个反映刀具磨损状态的特征参数,提出用模糊模式识别多传感器信息融合技术监测铣刀后刀面磨损带宽度。在立式加工中心上的实验表明,模糊模式识别多传感器信息融合技术能够满足铣刀磨损监测要求,具有较强的有效性和工程实用性。
We first analyzed the characteristics of the progressive wear of a helical cutter. Then, eight characteristic parameters reflecting the conditions of helical cutter were selected from such information as cutting forces, vibrating displacement and acceleration at the spindle end, and power consumption of the main electromotor. The multl-sensor information fusion technique and fuzzy pattern recognition are integrated to monitor the width of major flank wear land of the cutter. Experiments on a vertical machining center confirmed that the multi-sensor information fusion technique integrated with fuzzy pattern recognition can meet the requirements of helical cutter wear monitoring with strong effectiveness and engineering practicability.
出处
《机械科学与技术》
CSCD
北大核心
2007年第9期1113-1117,共5页
Mechanical Science and Technology for Aerospace Engineering
基金
国家重点基础发展计划项目(2005CB724101)
国家自然科学基金项目(50575087)资助
关键词
立铣刀
磨损
监测
模式识别
信息融合
helical cutter
wear
monitoring
pattern recognition
information fusion
