长度分形维数在微铣刀磨损状态识别中的应用  

Recognition of Wear Condition of Micro Milling Tool Based on Length Fractal Dimension

作　　者：王志强[1,2] 宫虎 房丰洲 刘冰 

机构地区：[1]天津职业技术师范大学信息技术工程学院,天津300222 [2]天津微纳制造技术工程中心,天津300457

出　　处：《振动．测试与诊断》2016年第3期592-597,611,共6页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(90923038);国家重点基础研究发展计划("九七三"计划)资助项目(2011CB706703);天津市教委科研计划资助项目(20130404)

摘　　要：针对微铣刀磨损状态在线检测提出了一种新的方法。首先,通过采集待测刀具的铣削振动信号,并采用长度分形维数法提取其特征参量,同时设定微铣刀不同的磨损状态作为参考样本;然后,采集不同样本的多段时域信号,并提取特征参量,进而根据区间估计法确定参考样本的聚类域;最后,将待测刀具的特征参量与参考样本的聚类域进行比较来判断刀具的磨损状态。基于自行研制的微型三轴立式机床,对上述方法进行了实验验证。首先,确定了微铣刀后刀面刀尖处的最大磨损深度分别为0,5,10,15,20和45μm以及主切削刃崩刃7种参考样本下的长度分形维数聚类域;然后,分别提取10把待测刀具的分形维数特征参量,并与7个参考样本的聚类域进行比较。实验结果表明,各个待测刀具的特征参量均落在其实际磨损状态所对应的聚类域内,故采用长度分形维数的方法检测刀具磨损状态切实可行。A new method is presented to online detect the wear condition of a micro milling tool.The vibration signals of tested tools during the milling process are collected and analyzed in the time domain.Then,the length fractal dimensions of the tested tools are abstracted.Meanwhile,tools with different wear conditions are set as reference exemplars.Their clustering domain is obtained by collecting multistage time-domain signals of different exemplars and extracting their length fractal dimensions.Finally,the wear conditions of the tested tools are detected by comparing the length fractal dimensions of the tested tools with the clustering domain of the reference exemplars.The proposed method is experimentally verified based on the self-developed multifunctional micro machine.The clustering domain of seven reference exemplars is obtained,which includes the wear loss of micro milling cutter is 0,5,10,15,20,45μm,and tipping.Then,the length fractal dimensions of 10 tested tools are extracted and compared with the clustering domain of the seven reference exemplars.The results show that the length fractal dimension of each tested cutter falls in the clustering domain that corresponds to the actual wear condition.Thus,it is effective and feasible to monitor micro milling tool wear based on length fractal dimension.

关 键 词：微铣削 刀具磨损 振动响应 长度分形维数 特征参量 

分 类 号：TH17[机械工程—机械制造及自动化]