Damage Classification of Acoustic Emission using AEGIS Pattern Recognition Software From Ten Small Wind Turbine Blade Tests


Global Windpower, 2-5 April 2002, Paris, France

M. J. Blanch, D. A. Kouroussis, A. A. Anastassopoulos, V. N. Nikolaidis, A. Proust, A. G. Dutton, L. E. Jones, P. Vionis, D. J. Lekou, D R V van Delft, P. A. Joosse, T. P. Philippidis, T Kossivas, G Fernando


Current wind turbine blade certification requires static and fatigue tests on the blade, to assess whether the blade can sustain the applied loads. Within the scope of a current EC-funded research project, acoustic emission (AE) monitoring has been extensively applied during a series of 10 small blade tests. The AEGIS Pattern Recognition Software (PRS) was specially written and applied to the AE data to grade any “critical” class of AE data which might appear close to failure. This has enabled the formulation of specific criteria which can automatically assess criticality of damage both during static and fatigue testing.