耦合信号微分后对双谱的影响

为有效区分和分析相近工作状态的振动信号,提出了基于时间序列进行微分再求其双谱的方法以放大相似信号的差异。由于平稳随机过程的铣床振动信号的双谱具有高度相似性而难以区分的特点,文章通过对比分析多次微分后的双谱和双谱对角切片,结果表明:微分前具有高度相似性的双谱,在微分后呈现出了不同的差异性,并且这种差异性随着微分次数的增加变得愈加明显。因此,时间序列的微分运算可有效提取信号特征,以实现对高度相似性信号的区分与分析。由于在各种机械加工系统中,各种参数比如转速、材料及粗糙度等,都与信号的双谱特征有关,因此可以根据研究结果调整各种参数,从而达到改善系统功能的目的。

The affection of differentiated coupled signals on bispectrum

In order to distinguish and analyze the vibration signals of similar working states effectively, in this paper, the method of differential bispectrum based on time series was proposed to amplify the difference of similar signals. Milling machine vibration signals which obey a stationary random process were set to the research object and their bispectra were highly similar and difficult to distinguish. In this paper, the comparative analysis result of bispectra and bispectral diagonal slices after multiple differential demonstrates that the spectra which have a high degree of similarity before differentiated become different after differentiated, and some of these differences increase with the differential times. So the analysis indicates that the differential method is an effective feature extraction method, and with this method the vibration signals of highly similarity can be distinguished and analyzed. The coupling components in signals can be enhanced. Because in various machining systems, many parameters such as speed, material and roughness are relative to bispectral features, so the parameters can be adjusted according to the analysis results to achieve the purpose of improving system functionality.