Passive acoustic damage detection of structural cavities using flow-induced acoustic excitations

Abstract

Cavities with different geometries represent the internal volumes of various engineering applications such as cabins of passenger cars, fuselages and wings of aircraft, and internal compartments of wind turbine blades. Transmissibility of acoustic excitation to and from these cavities is affected by material and cross-sectional properties of the structural cavity, as well as potential damage incurred. A new structural damage detection methodology that relies on the detectability of the changes in acoustic transmissibility across the boundaries of structural cavities is proposed. The methodology is described with a specific focus on the passive damage detection approach applied to cavity internal acoustic pressure responses under external flow-induced acoustic excitations. The approach is realized through a test plan that considers a wind turbine blade section subject to various damage types, severity levels, and locations, as well as wind speeds tested in a subsonic wind tunnel. A number of statistics-based metrics, including power spectral density estimates, band power differences from a known baseline, and the sum of absolute difference, were used to detect damage. The results obtained from the test campaign indicated that the passive acoustic damage detection approach was able to detect all considered hole-type damages as small as 0.32 cm in diameter and crack-type damages 1.27 cm in length. In general, the ability to distinguish damage from the baseline state improved as the damage increased in severity. Damage type, damage location, and flow speed influenced the ability to detect damage, but were not significant enough to prevent detection. This article serves as an overall proof of concept of the passive-based damage detection approach using flow-induced acoustic excitations on structural cavities of a wind turbine blade. The laboratory-scale results reveal that acoustic-based monitoring has great potential to be used as a new structural health monitoring technique for utility-scale wind turbine blades.