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Identification of tooth fault in a gearbox based on cyclostationarity and empirical mode decomposition

Autor(en):

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Structural Health Monitoring, , n. 3, v. 17
Seite(n): 494-513
DOI: 10.1177/1475921717704384
Abstrakt:

In the previous work, the cyclostationarity process, which is one of signal processing methods, has been used in health monitoring of the rotating machinery because of the superior detecting property of hidden periodicity. However, it is often difficult to acquire the information about the hidden periodicity due to the fault of the rotating machinery when the impact signal is low. Therefore, a certain preprocessing tool to extract the information about the impact signal due to the fault is required. This article presents the new detection process of tooth faults in a gearbox system based on the empirical mode decomposition algorithm which adaptively decomposes the signal into a set of intrinsic mode functions and the cyclostationarity process which identifies the hidden periodicity clearly in bi-frequency domain. The proposed method was demonstrated with a simulated signal and was applied to the detection of four types of conditions of tooth fault successfully.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1177/1475921717704384.
  • Über diese
    Datenseite
  • Reference-ID
    10562067
  • Veröffentlicht am:
    11.02.2021
  • Geändert am:
    19.02.2021
 
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