A computational investigation of airfoil aeroacoustics for structural health monitoring of wind turbine blades. Issue 3 (18th December 2019)

• Record Type: Journal Article
• Authors: Traylor, Caleb; DiPaola, Milo; Willis, David J.; Inalpolat, Murat
• Is Part Of: Wind energy. Volume 23:Issue 3(2020)
• Page Start: 795
• Page End: 809
• Publication Date: 2019-12-18
• Subjects: acoustic sensing -- aeroacoustics -- flow noise -- passive damage detection -- structural health monitoring -- wind turbine blade; Wind power -- Periodicals; 621.312136
• DOI: 10.1002/we.2459
• Languages: English
• ISSNs: 1095-4244

Abstract

Abstract: A generalized computational methodology for reduced order acoustic‐structural coupled modeling of the aeroacoustics of a wind turbine blade is presented. This methodology is used to investigate the acoustic pressure distribution in and around airfoils to guide the development of a passive damage detection approach for structural health monitoring of wind turbine blades for the first time. The output of a k − ε turbulence model computational fluid dynamics simulation is used to calculate simple acoustic sources on the basis of model tuning with published experimental data. The methodology is then applied to a computational case study of a 0.3048‐m chord NACA 0012 airfoil with two internal cavities, each with a microphone placed along the shear web. Five damage locations and four damage sizes are studied and compared with the healthy baseline case for three strategically selected acoustic frequencies: 1, 5, and 10 kHz. In 22 of the 36 cases in which the front cavity is damaged, the front cavity microphone measures an increase in sound pressure level (SPL) above 3 dB, while rear cavity damage only results in six out of 24 cases with a 3‐dB increase in the rear cavity. The 1‐ and 5‐kHz cases show a more consistent increase in SPL than the 10‐kHz case, illustrating the spectral dependency of the model. The case study shows how passive acoustic detection could be used to identify blade damage, while providing a template for application of the methodology to investigate the feasibility of passive detection for any specific turbine blade.