UTFacultiesETDepartmentsMS3Research ChairsDynamics Based MaintenanceProjectsFinished Research ProjectsLoad and Structural Health Monitoring of Offshore wind turbine blades (SLOWIND)

Load and Structural Health Monitoring of Offshore wind turbine blades (SLOWIND)

DURATION

Start: 01-07-2015
End: 30-09-2018

PARTNERS & FUNDING

WMC Knowledge Center, TNO, Pontis Engineering

This project is funded by TKI Wind op Zee (via RVO)

PROJECT WEBSITE

N.A.

STAFF

Francesco Lahuerta, Richard Loendersloot, Tiedo Tinga

DESCRIPTION

Wind turbine blades require periodic manual inspections. This often requires stopping and physical   access of inspectors and tools to the rotor, incurring both costs and downtime. It also brings along risks for the inspection crew. Existing sensor technologies are expected to fulfil the inspection requirements for blades.

The aim of the present project is the development of more efficient (embedded) monitoring systems to detect, localize and quantify damage in the rotor blades. This system will replace costly inspections and prevents unexpected downtime of the turbines, while adding prognostic capability, leading to a reduction in cost of energy.

The structural health of the wind turbine blades depends on the effects of fatigue, lightning and impacts, leading to delamination and cracks, erosion of the blade surface and failure of adhesive joints. To enable effective detection of these types of blade damage, the present project starts with the detailed characterization of typical failures in composite rotor blades, including damage progression modelling. Then two monitoring approaches are developed: load monitoring by embedded fiber optic sensors and structural health monitoring by a distributed network of piezo sensors. The developed sensing concepts are then demonstrated and validated on both coupons and full scale test articles. Finally, the two types of sensor networks will be integrated and prognostic methods will be proposed.

At the end of the project, a concept for advanced blade monitoring and prognostics based on a combination of fiber optic sensors and distributed piezo sensors will be available and its feasibility has been tested on laboratory scale as well as on full scale objects.