基于SSD和1.5维谱的滚动轴承故障诊断方法

Fault Diagnosis Method for Rolling Bearings Based on SSD and 1.5-Dimensional Spectrum

针对滚动轴承早期故障信号信噪比低、较难提取的问题,提出了基于奇异谱分解和1.5维谱的滚动轴承故障诊断方法。首先,利用SSD处理振动信号得到一组奇异谱分量;然后,根据峭度准则选取最佳分量并进行包络解调;最后,计算包络信号的1.5维谱并分析谱图中提取到的故障特征信息,实现故障类型的准确判定。试验结果表明,该算法能够有效提取轴承内、外圈早期微弱故障的特征信息,与单一方法及EMD相比具备更佳的诊断效果。

Aimed at low signal-to-noise ratio and difficult extraction of early fault signal of rolling bearings,a fault diagnosis method for rolling bearings is proposed based on singular spectrum decomposition(SSD)and 1.5-dimensional spectrum.Firstly,SSD is used to decompose vibration signal,and a set of singular spectrum components(SSC)are obtained.Then,the best component is selected according to kurtosis criterion,and the envelope demodulation is carried out.Finally,the 1.5-dimensional spectrum of envelope signal is calculated,and the fault feature information extracted from spectrum is analyzed to achieve an accurate determination of fault type.The experimental results show that the algorithm extracts characteristic information of early weak fault in inner and outer rings of the bearings effectively,and the diagnostic effect of the algorithm is better than that of single method and EMD.