数控机床用刀具磨损状态识别方法  

Identification Method of Tool Wear State of CNC Machine Tools

作　　者：魏传峰 Wei Chuanfeng(Shandong ShuiLongwang Technology Co.,Ltd.,Jinan,Shandong 250308,CHN)

机构地区：[1]山东水龙王科技有限公司,山东济南250308

出　　处：《模具制造》2024年第8期150-152,155,共4页Die & Mould Manufacture

摘　　要：刀具磨损状态直接影响到数控机床加工质量,但现行方法存在一定的缺陷和不足,在实际应用中识别偏差较大,识别与真实一致性系数较低,难以达到预期的识别效果。为此,提出数控机床刀具磨损状态识别方法。利用声振传感器感知刀具声振信号,通过对声振信号小波变换得到信号调幅调频分量,利用回归分析模型确定刀具磨损量,识别刀具磨损状态,完成数控机床刀具磨损状态识别。经实验证明,设计方法识别偏差仅为0.01mm,识别与真实情况一致性系数在0.96以上,可以实现对数据机床刀具磨损状态精准识别。The tool wear state directly affects the machining quality of CNC machine tools,but the current method has some defects and deficiencies.In practical application,the identification deviation is large,the identification and the real consistency coefficient is low,and the identification can not achieve the expected recognition effect.Therefore,the identification method of the tool wear state of CNC machine tools in mechanical manufacturing is proposed.The acoustic and vibration sensor is used to sense the acoustic and vibration signal of the tool,and the amplitude modulation frequency modulation component of the signal is obtained by wavelet transform of the acoustic and vibration signal.The regression analysis model is used to determine the tool wear amount and identify the tool wear state,and the tool wear state identification is completed.The experiment proves that the identification deviation of the design method is only O.olmm,and the consistency coefficient between the identification and the real situation is above 0.96,which can realize the accurate identification of the tool wear state of the data machine tool.

关 键 词：数控机床 磨损状态 小波变换 回归分析模型 

分 类 号：TH162[机械工程—机械制造及自动化]