ACOUSTIC
EMISSION & NDT SCIENTIFIC PUBLICATIONS
Acoustic Emission Condition Monitoring Of Wind Turbine Rotor
Blades:
Laboratory Certification Testing To Large Scale In-Service
Deployment
To appear in the proceedings of European Wind Energy Conference
- EWEC 2003
A G
Dutton, M J Blanch, P Vionis, D Lekou, D R V van Delft, P A
Joosse, A Anastassopoulos, D Kouroussis, T Kossivas, T. P.
Philippidis, T. T. Assimakopoulou, G Fernando, C Doyle, A Proust
Wind turbines
experience long term fluctuating variable amplitude fatigue
loads with occasional large amplitude stochastic peak loads. The
fatigue loads are usually characterised by a mean load with a
fixed amplitude oscillation superimposed; the stochastic peak
loads by modelled peak loads, such as the fifty year gust.
A methodology for
wind turbine blade monitoring using acoustic emission (AE) detection
of damage processes in the structure has been developed by the AEGIS
consortium, supported by the European Commission. The methodology
has been developed separately for the peak load events and the more
usual operational fatigue loading. It can be applied as an
enhancement to the conventional blade certification test and has the
potential to be adapted to large-scale field application of the
techniques on operational wind turbines.
Wind turbine blade
certification tests are carried out to validate design and
production. AE monitoring during all stages of a test can both
locate and characterise damage processes in blades, starting with
non-audible signals occurring due to damage propagation at
relatively low loads. Characteristic results are presented of AE
activity during peak loading events and fatigue blade tests to
failure in the laboratory.
The transfer of the
techniques to operating wind turbines is speculative, but the
results presented indicate the kind of results which could be
obtained from monitoring in-service machines. In particular, a
dedicated pattern recognition software has been developed which
could identify differences from turbine to turbine and help target
preventative maintenance. Validation of the software from laboratory
tests on blades is presented. Finally, the requirements for
successful deployment of AE condition monitoring in the field are
discussed.