基于小波变换的旋转机械振动信号数据压缩方法的研究

Method of Data Compressing for Rotating Machinery Vibration Signal Based on Wavelet Transform

在分析了旋转机械振动信号的特点和小波变换在信号奇异性检测上的特性后 ,提出了利用小波系数表征信号的奇异性特征 ,及用信号的频谱来表征信号的整体特征。而用这二类数据表征信号时的数据量远远小于振动时域信号的数据量。因此本文提出了利用这二类信号对振动信号进行数据压缩的方法。通过仿真计算和对实际数据的计算证明 ,该方法既可以得到较高的信号压缩比又保留了信号的局部特征 ,有着很好的信号重构性。

In the paper, the general properties of rotating machinery vibration signals are summarized and the utility of wavelet tranform to detect the singularities of signal is reviewed. On this basis, a form of representation of a vibration signal is proposed, which is comprised of the decomposed wavelet coefficients and the specialized frequency components in the spectrum. The wavelet coefficients indicate the singularities of the signal, while the frequency components reflect its normal characteristics. The total data size of such a representation is far less than the original time domain data size and an approach for signal data compression is thus proposed. The presented method has been applied to some actual vibration signals as well as simulation signals with good results obtained in respect of data compression ratio and signal reconstruction.