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Validation of a physics-based model of a rotating machine for synthetic data generation in hybrid diagnosis

Autor(en):


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Structural Health Monitoring, , n. 4, v. 16
Seite(n): 458-470
DOI: 10.1177/1475921716676053
Abstrakt:

Diagnosis and prognosis are key issues in the application of condition based maintenance. Thus, there is a need to evaluate the condition of a machine. Physics-based models are of great interest as they give the response of a modelled system in different operating conditions. This strategy allows for the generation of synthetic data that can be used in combination with real data acquired by sensors to improve maintenance. The article presents an electromechanical model for a rotating machine, with special emphasis on the modelling of rolling element bearings. The proposed model is validated by comparing the simulation results and the experimental results in different operating conditions and different damaged states. This comparison shows good agreement, obtaining differences of up to 10% for the modelling of the whole rotating machine and less than 0.6% for the model of the bearing.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1177/1475921716676053.
  • Über diese
    Datenseite
  • Reference-ID
    10562015
  • Veröffentlicht am:
    11.02.2021
  • Geändert am:
    19.02.2021
 
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