An Integrated Prognostics Condition-Based Maintenance Approach to Reduce Premature Failure of Wind Turbines' Gearbox Components
Open AccessAbstract of PraxisAn Integrated Prognostics Condition-Based Maintenance Approach to Reduce Premature Failure of Wind Turbines’ Gearbox Components This research proposed an integrated prognostics condition-based maintenance (CBM) strategy to reduce the premature sudden failure of three-bladed horizontal axis wind turbine (HAWT) gearbox. It is apparent that the maintenance of wind turbine components in the growing renewable energy industry significantly affects the levelized cost of energy (LCOE) [8]. More than half of wind turbine failures stem from control systems and electric components, but these failures have low downtimes compared to the premature failure of critical components such as blades, gearboxes and generators, which accounts for 95% of the production downtime [9]. The integrated approach predicts and reduces the premature failure and the Remaining Useful Life (RUL) distribution of the gearbox to spot upcoming failure so maintenance can proactively be scheduled. It also utilizes instantaneously fluctuating variables encompassing environmental conditions such as temperature, wind speed and direction along with the parameters from the gearbox and rotor system. The method combines the data-driven predictive model with the physics-based degradation process of the gearbox to account for the turbine components’ complexity and lack of sufficient industry-wide failure data. Ultimately, this research will improve operation and maintenance (O&M;) cost, performance and system reliability of wind turbines.
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