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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Bibliographic Details
Published in:Journal of Vibroengineering Vol. 23; no. 7; pp. 1578 - 1590
Main Authors: Ge, Xiangdong, Yu, Mingyue, Qiao, Baodong, An, Zhongyan
Format: Journal Article
Language:English
Published: JVE International Ltd 01.11.2021
Subjects:
Algorithms
Analysis
Sensors
China
ISSN:1392-8716, 2538-8460
Online Access:Get full text
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Summary: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