关联维数在机械设备故障诊断中的应用研究

Study and Application of Correlation Dimension in Fault Diagnosis of Machinery

研究了混沌与分形的特征参数———关联维数的计算方法和参数的选择。以滚动轴承在正常、外圈故障、滚动体故障、内圈故障4种状态下的信号特征为标准样本,以其运行的实测信号为例,对时域信号进行了频谱分析,并进一步进行了关联维数分析。通过对滚动轴承振动信号的关联维数分析,证明了该轴承在4种不同标准状态下具有明显不同的关联维数特征。因此,按照相关性的大小,就可诊断出实测信号属于外圈故障状态信号。研究结果表明,关联维数分析方法在设备状态监测与故障诊断中,尤其是在非线性系统的故障诊断中显示出其独特的优势,具有较为广阔的应用前景。

The calculation of chaos and fractal characteristic parameter, the correlation, is studied. The gist for choosing its calculation parameters is analyzed. With normal and fault state signals of outside-rolling, roiling bearing, inside-rolling as the standard samples and ,working state signals as the example, the time-series signal is analyzed in the form of Fourier change and mere imoortant, the mean of correlation dimensions. The results of data analysis not only identify that the experimental signal belongs to the outside-rolling fault state, but also show that the bearing has different correlation dimensions in different work conditions. The analytical method of correlation dimensions will show its unique advantage in the aspect of condition monitoring and fault diagnosis of the equipment, especially the way of non-linear fault diagnosis, demonstrating its wide application prospect.