Condition Monitoring System for Planetary Journal Bearings in Wind Turbines Based on Surface Acoustic Wave...

Area of Science:

• Mechanical Engineering
• Renewable Energy Systems
• Condition Monitoring

Background:

• Planetary journal bearings are crucial for wind turbine gearbox performance, but are vulnerable to damage from abnormal events like contamination or oil starvation.
• Current condition monitoring for these bearings is limited, with existing studies lacking transferability to full-scale systems.
• Spontaneous bearing failures lead to significant turbine downtime and expensive repairs.

Purpose of the Study:

• To develop and evaluate a novel condition monitoring system for planetary journal bearings in wind turbine gearboxes.
• To assess the system's ability to detect critical operating states and predict bearing friction.
• To demonstrate the practical feasibility of advanced monitoring for wind turbine reliability.

Main Methods:

• A system test was conducted on an 850 kW wind turbine gearbox featuring planetary journal bearings.
• A novel condition monitoring system based on surface acoustic wave measurement was integrated and tested.
• A machine learning algorithm was developed to analyze monitoring signals and predict bearing friction states.

Main Results:

• The study successfully tested a novel condition monitoring system on a full-scale wind turbine gearbox.
• Surface acoustic wave measurements provided detailed insights into the condition of the journal bearings.
• The machine learning algorithm effectively evaluated monitoring signals and predicted bearing friction states.

Conclusions:

• The developed surface acoustic wave-based monitoring system is practically feasible for planetary journal bearings in wind turbines.
• This approach offers a reliable method for detecting critical states, preventing damage, and improving wind turbine gearbox reliability.
• The system has the potential to significantly reduce operational costs and downtime in wind energy.