On the Potential of Aerodynamic Pressure Measurements for Structural Damage Detection

Abstract

This study investigates the potential of using aerodynamic pressure time series measurements to detect structural damage in elastic, aerodynamically loaded structures. Our work is motivated by the increase in the dimensions of modern wind turbine blade (WTB) designs, whose complex behavior necessitates the adoption of improved simulation and structural monitoring solutions. In refining the tracking of aerodynamic interactions and their effects on such structures, we propose to exploit aerodynamic pressure measurements, available from a novel, cost-effective, and non-intrusive sensing system, for structural damage assessment on wind turbine blades. This proof-of-concept study is based on a series of wind tunnel experiments on an NACA 633418 airfoil. The airfoil is mounted on a vertically oscillating cantilever beam with structural damage introduced in the form of a crack by gradually sawing the cantilever beam close to its support. The pressure distribution on the airfoil is measured under diverse configurations of inflow conditions and structural states, including different angles of attack, wind velocities, heaving frequencies, and crack lengths. We further propose an algorithm, relying on convolutional neural networks (CNNs), for damage detection and rating based on the monitored signals. Analysis of the dynamics of the system using reference acceleration measurements and a finite element (FE) model and application of the suggested method on the experimental data indicate that aerodynamic pressure measurements on airfoils can indeed be used as an indirect approach for damage detection and severity classification on elastic, beam-like structures in mildly turbulent environments.