Abstract：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 to select multiple optimal demodulation bands caused by different faults. For this reason, the time-frequency energy aggregation spectrum diagnosis method is proposed. The method introduces multisynchrosqueezing transform to construct a time-frequency representation with high energy concentration to solve the problem of optimal demodulation band accuracy, and also proposes the relative factor index of energy aggregation spectrum to realize the comprehensive extraction, synchronization and accurate output of strong and weak multi-fault feature bands through the index, which 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 show that this method can successfully extract the bearing compound fault features.
袁静， 姚泽，胡雯玥，蒋会明，赵倩. 滚动轴承复合故障的时频能量聚集谱诊断方法[J]. 振动与冲击, 2023, 42(2): 285-292.
YUAN Jing， YAO Ze， HU Wenyue， JIANG Huiming， ZHAO Qian. Time-frequency energy aggregation spectrum diagnosis method for compound faults of rolling bearings. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(2): 285-292.
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