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Autonomous Sensor System for Low-Capacity Wind Turbine Blade Vibration Measurement.

Diego Muxica1, Sebastian Rivera2,3, Marcos E Orchard4

  • 1Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes, Santiago 7620001, Chile.

Sensors (Basel, Switzerland)
|March 28, 2024
PubMed
Summary
This summary is machine-generated.

This study developed an autonomous on-blade sensor system for remote vibration measurement in wind turbines. The system reliably collected data for structural health monitoring, even in harsh conditions.

Keywords:
accelerometer-based sensor networkscondition monitoringdata acquisitionmodal analysisstructural health monitoringwind turbines

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Area of Science:

  • Engineering
  • Mechanical Engineering
  • Renewable Energy Systems

Background:

  • Wind turbine blades are critical components susceptible to damage.
  • Effective structural health monitoring (SHM) is essential for reliable wind energy generation.
  • Remote and autonomous monitoring solutions are needed for accessibility and cost-effectiveness.

Purpose of the Study:

  • To design, implement, and validate an on-blade sensor system for remote vibration measurement.
  • To assess the system's reliability in harsh weather conditions and remote locations.
  • To provide data for damage diagnosis and prognosis of wind turbine blades.

Main Methods:

  • Development of an autonomous on-blade sensor system for vibration measurement.
  • Deployment of the system on three low-capacity wind turbines, including one in remote Chile.
  • Recording of blade acceleration data in flapwise and edgewise directions.

Main Results:

  • Demonstrated reliable data acquisition and transmission from remote wind turbines.
  • Validated the system's capability for autonomous, long-term data recording without human intervention.
  • Collected vibration data suitable for extracting dynamic characteristics and enabling damage diagnosis.

Conclusions:

  • The developed on-blade sensor system is effective for autonomous, remote vibration monitoring of wind turbines.
  • The system provides a foundation for real-time, vibration-based structural health monitoring strategies.
  • This technology enhances the ability to monitor and evaluate the health of wind turbine blades over extended periods.