Enhanced Particle Filtering for Bearing Remaining Useful Life Prediction of Wind Turbine Drivetrain Gearboxes | Zendy

Fangzhou Cheng | Zendy; Liyan Qu | Zendy; Wei Qiao | Zendy; Liwei Hao | Zendy

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Enhanced Particle Filtering for Bearing Remaining Useful Life Prediction of Wind Turbine Drivetrain Gearboxes

Author(s) -

Fangzhou Cheng,

Liyan Qu,

Wei Qiao,

Liwei Hao

Publication year - 2018

Publication title -

ieee transactions on industrial electronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.393

H-Index - 287

eISSN - 1557-9948

pISSN - 0278-0046

DOI - 10.1109/tie.2018.2866057

Subject(s) - drivetrain , turbine , particle filter , wind power , condition monitoring , engineering , fault (geology) , resampling , wind speed , computer science , automotive engineering , control theory (sociology) , torque , kalman filter , artificial intelligence , mechanical engineering , physics , electrical engineering , thermodynamics , control (management) , seismology , meteorology , geology

Bearing is the major contributor to wind turbine gearbox failures. Accurate remaining useful life prediction for drivetrain gearboxes of wind turbines is of great importance to achieve condition-based maintenance to improve the wind turbine reliability and reduce the cost of wind power. However, remaining useful life prediction is a challenging work due to the limited monitoring data and the lack ...

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