滚动轴承复合故障的时频能量聚集谱诊断方法

Time-frequency energy aggregation spectrum diagnosis method for compound faults of rolling bearings

共振解调技术是轴承故障诊断领域中广泛应用的有效方法,其中解调频带的选取至关重要。传统解调方法仅能识别特征明显的单一轴承故障,而面对旋转机械轴承复合故障的异样微弱特征提取以及不同故障所引发的多个最优解调频带问题时往往难以奏效。为此,提出时频能量聚集谱诊断方法。该方法引入多重同步压缩变换,构造能量聚集的时频图,以解决最优解调频带精确性问题,同时提出能量聚集谱相对因子指标,通过指标实现强弱多故障特征频带综合提取、同步且准确输出,为旋转机械复杂动态信号中微弱和复合轴承故障特征提取与识别提供有利依据。试验结果表明,该方法能成功提取出轴承复合故障特征。

The resonance demodulation technology is an effective method widely used in the field of bearing fault diagnosis, in which the selection of demodulation frequency band is crucial. Traditional demodulation methods can only identify single bearing faults with obvious features, but it is often difficult to extract abnormal weak features for composite faults of rotating machinery bearings and is not effective to select multiple optimal demodulation bands caused by different faults. For this reason, a time-frequency energy aggregation spectrum diagnosis method was proposed. In the method, the multisynchrosqueezing transform was introduced to construct a time-frequency representation with high energy concentration in order to solve the problem of optimal demodulation band accuracy, and a relative factor index of energy aggregation spectrum was proposed, by virtue of which the comprehensive extraction, synchronization and accurate output of strong and weak multi-fault feature bands were realized. The method provides a favorable basis for the extraction and identification of weak and composite bearing fault features in complex dynamic signals of rotating machinery. The experimental results verified its good ability in successfully diagosing bearing compound faults.