基于连续小波变换的钻削力信号灰度矩特征提取

Gray Moment Feature Extraction from Drill Force Signals Based on Continuous Wavelet Transform

利用小波分析良好的时频特性,分析了钻削过程中钻削力信号在时间-尺度域中的变化特征,提出用“灰度矩”的概念来描述连续小波变换的统计特性,并通过实验研究了整个钻头磨损历程中钻削力信号小波变换结果的“1+1”阶矩的变化规律。结果表明:随着钻头磨损的增加,其“1+1”阶矩统计特征呈上升趋势,根据其变化特征可有效实现钻头磨损状态的监测。

By using the good time-frequency domain features of wavelet analyse, the continuous wavelet coefficients of the drill force signal during drill wear are studied. This paper puts forward a new statistics-gray moment and researches the changing rules of one-plus-one-order moment of this kind of the drill force signal in the whole course of drill wear through experiments. The results show that one-plus-one-order moment of the drill force signal takes on a rising trend along with the increase of drill wear, and the drill wear can be monitored effectively according to the changing characteristic of one-plus-one-order moment of the drill force signal.