Aircraft icing detection via flow-induced ambient random noise: from theory to wind tunnel experiments

Aircraft icing is a serious threat to flight safety. This paper presents a passive approach to detect ice accreted on an airfoil using flow-induced random noise considering spatially-inhomogeneous transient excitations. Under the assumption of diffuse-field, by computing the cross-correlation of ambient vibration measured at two receivers and band-pass filtering it, the guided wave dispersion curve of the structure can be well-reconstructed, by which one can estimate the ice thickness by matching the reconstructed dispersion curve with its theoretical model. In practice, however, the diffuse-field assumption may not hold as spatially-inhomogeneous strong transient excitations exist. The associated directional wave propagation generates additional peaks in the cross-correlation and this contaminates the ice detection result. Therefore, this paper proposes a signal processing technique to identify and suppress the contributions from the transient source in the measurements, by which a reliable dispersion curve reconstruction and an accurate ice detection can be retrieved. The proposed method is shown to be efficient via a wind tunnel experiment. The passive ice detection method is specifically suitable for aircraft online monitoring because only passive sensors are needed which can be tiny, light, and mounted on the internal surface of fuselage skin without any influence on aircraft aerodynamics.