频带能量特征法在声发射刀具磨损监测系统中的应用  

Application of Frequency Band Energy Character Method in Cutter Wear Monitoring System Using Acoustic Emission

作　　者：聂鹏[1] 王东磊[1] 徐涛[1] 关山[2] 

机构地区：[1]沈阳航空工业学院 [2]吉林大学

出　　处：《工具技术》2009年第2期24-27,共4页Tool Engineering

基　　金：沈阳市人才专项基金资助项目(项目编号:07syrc04)

摘　　要：基于对声发射(AE)信号特点的分析和小波包分解理论对不平稳信号特征提取的优势,提出一种利用AE信号的能量变化来监测刀具磨损状态的方法。该方法利用db8小波基对AE信号进行5层小波包分解,将分解后各频带上的能量值作为特征参数,并组成特征向量。分别提取在新刀和刀具磨损状态下的特征向量,根据其变化即可判别刀具磨损的程度。试验结果验证了该方法在刀具磨损判析中的可用性。Based on the characteristic analysis of acoustic emission （AE） signals and the advantages of wavelet packets decomposition theory in the nonsteady signal feature extraction, a method to judge the cutter wear state by means of the energy variable of AE signals is proposed. The method uses db8 wavelet packet to decompose AE signal into 5 level, taking the decomposed signal energy in frequency bands as characteristic parameters, and then use these characteristic parameters to compose characteristic vector. The characteristic vectors under new cutter condition and cutter wear condition are extracted respectively, so that the cutter wear degree can be distinguished according to the variance contribution of character values. The usability of this method is verified by the test results.

关 键 词：刀具磨损 声发射信号 小波包分解 频带能量 特征提取 

分 类 号：TG580.6[金属学及工艺—金属切削加工及机床] TN911.72[电子电信—通信与信息系统]