Multi-Time Scale Modeling Strategy for Bearing Life Prognosis

Shuangwen Sheng, Robert X. Gao

Research output: Contribution to conferencePaperpeer-review

1 Scopus Citations


Prediction of a bearing service life is traditionally achieved by empirical or physical models, which have their own strengths and limitations. In an effort to combine the strengths of these modeling approaches, this research investigates the concept of Multi-Time Scale Modeling (MTSM). Specifically, a MTSM strategy for bearing life prognosis is developed by correlating experimentally acquired bearing vibration data with physics based model of microscopic growth of crack size. The strategy is composed of a fast scale empirical model (e.g., root mean square value of vibration), a slow scale physical model (e.g., change of crack length over one loading cycle), and a model coupling mechanism (e.g., bidirectional mapping functions). The fast and slow scale models are obtained by polynomial regression analysis and using the concept of the Paris Law, respectively. The coupling mechanism is established through introduction of dynamic mass into the model. The improvement in bearing service life prediction, obtained by the presented MTSM strategy is experimentally validated.

Original languageAmerican English
Number of pages8
StatePublished - 2010
Event2009 ASME Dynamic Systems and Control Conference, DSCC2009 - Hollywood, CA, United States
Duration: 12 Oct 200914 Oct 2009


Conference2009 ASME Dynamic Systems and Control Conference, DSCC2009
Country/TerritoryUnited States
CityHollywood, CA

NREL Publication Number

  • NREL/CP-500-49007


  • bearing life
  • MTSM
  • multi time scale modeling
  • turbine
  • wind energy


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