A study on the extraction of characteristics of compound faults of rolling bearings based on ITD-AF-CAF

In view of the cyclostationary characteristics of vibration signals from aero-engine, the combination of cyclic autocorrelation function and intrinsic timescale decomposition (ITD) has been proposed. According to the proposed method, vibration signals are decomposed by ITD algorithm to obtain the au...

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Veröffentlicht in:Journal of Vibroengineering Jg. 23; H. 7; S. 1578 - 1590
Hauptverfasser: Ge, Xiangdong, Yu, Mingyue, Qiao, Baodong, An, Zhongyan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: JVE International Ltd 01.11.2021
Schlagworte:
Algorithms
Analysis
Sensors
China
ISSN:1392-8716, 2538-8460
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Zusammenfassung:In view of the cyclostationary characteristics of vibration signals from aero-engine, the combination of cyclic autocorrelation function and intrinsic timescale decomposition (ITD) has been proposed. According to the proposed method, vibration signals are decomposed by ITD algorithm to obtain the autocorrelation function of proper rotation components (PRC), based on which characteristic extraction and identification of compound faults of rolling bearings is made possible. To validate the effectiveness of method, an analysis has been given to the vibration signals of rolling bearings collected by sensors of different positions in different compound fault modes. As shown by results, the method combining ITD and cyclostationary theory can precisely and effectively extract the characteristic frequency relative to the type of faults and identify the compound faults.
ISSN:1392-8716
2538-8460
DOI:10.21595/jve.2021.21884