基于模糊聚类的刀具磨损量在线监测方法

A Method of On-Line Monitoring Tool Wear Based on Fuzzy Classification

研究在加工过程中刀具磨损量实时监测和预报 .针对神经网络在监测刀具磨损量中存在的缺点 ,在选择合适的模糊聚类标准样本的基础上 ,利用模糊聚类方法 ,加以适当推理 .实验分析表明 ,该方法在刀具磨损量在线监测中具有较好的容错性和可分析性 .在标准样本合适的条件下 ,利用模糊聚类方法能够正确地进行在线监测和预报刀具磨损量 .

Fuzzy classification was used to monitor and predict tool wear. To overcome the defect of monitoring tool wear using NN, based on choosing suitable standard fuzzy classification samples, fuzzy classifying scheme and proper reasoning were used to monitor and predict the value fo cutting tool's flank wear. It was proved by cutting experiments that the method is strong robust and analyzable. Based on the choice of suitable standard fuzzy classification samples, the fuzzy classification method can correctly monitor and predict the cutting tool's wear.