Predictive maintenance

For wind turbines – especially in hard-to-access offshore wind farms – unplanned downtime can quickly become expensive. The answer lies in detecting critical changes before they develop into failures.

Continuous condition and structural health monitoring provides the data needed to identify emerging imbalances, material fatigue and other changes in critical components. ASC’s OS series accelerometers are engineered for these demanding measurement tasks.

ASC OS LN (Low Noise) sensors precisely capture even very small accelerations and low-frequency vibrations. While ASC OS MF (Medium Frequency) accelerometers provide the dynamic response required for monitoring higher-frequency vibration phenomena. Their robust design makes them ideal for reliable, long-term measurement in demanding wind energy environments.

Combined with intelligent monitoring systems, high-quality vibration data can reveal how faults are developing over time. Self-learning algorithms can then help predict future deterioration and define meaningful maintenance thresholds.

What’s in it for you? Maintenance when it’s needed – not simply when the calendar says so. This means optimized inspection intervals, fewer unexpected failures and greater turbine availability.

From condition monitoring to predictive maintenance: Better decisions start with better vibration data.

Bring us your wind turbine monitoring challenge and explore the right monitoring strategy.