数控镗刀磨损与破损的声发射监测法  

The Acoustic Emission Monitoring Method of Tool Wear and Breakage in CNC Boring

作　　者：陈益林[1] 田正芳[1] 侯德政[1] 

机构地区：[1]张家界航空工业职业技术学院数控系,湖南张家界427000

出　　处：《机床与液压》2012年第10期111-113,共3页Machine Tool & Hydraulics

基　　金：湖南省教育厅资助科研项目(09C1307)

摘　　要：通过分析声发射传感器采集的刀具磨损状态信号,提取出反映刀具磨损状态的特征向量MFCC系数及差分系数,然后利用隐马尔可夫模型进行信号处理,建立了检测镗刀刀具状态的监测系统。实验结果表明:在刀具的正常磨损阶段,该监测系统可以实现刀具大致磨损量的预报;在刀具破损或损坏情况下,能够及时监测和预报刀具损坏状态。这种监测方法可用于实时在线监测,为刀具的磨损监测提供了一条切实可行的途径。Signals of acoustic emission sensors about tool wear were analyzed. MFCC coefficient and differential coefficient which were feature vectors reflecting tool wear were extracted, Signals were processed by hidden Markov model. A boring tool condition moni- toring system was established. Experimental results show that the tool monitoring system can roughly forecast tool wear in the normal wear stage, and also can timely monitor and forecast tool damage in the case of tool breakage or damage. This monitoring method can be used to real-time online monitoring of tool wear. It provides a practical way for tool condition monitoring.

关 键 词：镗刀磨损监测 梅尔系数 隐马尔可夫模型 声发射信号 

分 类 号：TH16[机械工程—机械制造及自动化]