An aeroacoustics-based approach for wind turbine blade damage detection

Y. Zhang*, F. Avallone, S.J. Watson

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

1 Citation (Scopus)
23 Downloads (Pure)


In this work, aimed at the development of an aeroacoustics-based wind turbine blade damage detection approach, the noise scattered from two airfoils with damage at the trailing edge or at the leading edge is investigated. Four trailing edge cracks (with width of 0.2, 0.5, 1.0 and 2.0 mm) and four leading edge erosion configurations (consisting of gouges and delamination) are investigated for a NACA 0018 and a DU96 W180 airfoil. Experiments are carried out under clean and turbulent inflow conditions. Acoustic measurements are performed in an anechoic wind tunnel with a microphone array. The trailing edge crack causes a tonal peak at trailing-edge-thickness-based Strouhal number approximately equal to St_h~0.1 under clean and low turbulence intensity inflow conditions (e.g. ~4% in this study). For a higher turbulence intensity (e.g., ~7%), the tonal peaks are not detectable. For the leading edge erosion case, under clean inflow conditions and minor damage levels, the amplitudes of the harmonics in the trailing edge noise spectra increase compared with the baseline. For moderate damage levels, the harmonics on the suction side shift to higher frequencies with lower amplitudes. For the highest damage levels, only broadband characteristics are present, where low-frequency contributions increase and high-frequency contributions decrease as the damage level increases. When introducing turbulent inflow, the leading edge impingement noise level decreases at medium-high frequency (above 1000 Hz) with increasing levels of erosion.
Original languageEnglish
Article number022088
Pages (from-to)1-10
Number of pages10
JournalJournal of Physics: Conference Series
Issue number2
Publication statusPublished - 2022
EventTORQUE 2022 - Delft, Netherlands
Duration: 1 Jun 20223 Jun 2022
Conference number: 9


Dive into the research topics of 'An aeroacoustics-based approach for wind turbine blade damage detection'. Together they form a unique fingerprint.

Cite this