摘要
系统地阐述了正交小波变换的概念和小波多分辨率分析的方法 ,并对不同刀具状态的振动信号进行分解和重构处理 ,获得了振动信号在不同频段的重构分量。根据各个频段重构分量在不同刀具状态下的变化特点 ,进而提取高频段重构分量的功率谱的频域统计值以及 [313～ 6 2 5Hz]频段重构分量的局部极大模线对应的平均Lipschitz指数作为监测特征。实验结果表明 :采用上述方法可有效实现刀具状态特征信息提取 ,较其它方法更加适用于钻削刀具状态监测。
This paper systematically studies the method of orthogonal wavelet transform and multi-scale analysis,and process the vibration signals in different cutter status by means of decomposition and reconstruction,obtaining the vibration signals in different frequency bands. According to the change of the reconstructed signals,the statistic in frequency domain of the reconstructed signals in high frequency band and the average of Lipschitz possessed by the wavelet local modulus maximum lines of the reconstructed signal in frequency band of 313Hz～625Hz is served as monitoring feature. The experiment shows that the feature of cutter state is effectively extracted by means of above method and much applicable to state monitoring of drilling cutter.
出处
《制造技术与机床》
CSCD
北大核心
2004年第7期20-23,共4页
Manufacturing Technology & Machine Tool
