Three-Dimensional Acoustic Wavenumber Spectroscopy for Structural Health Monitoring

Abstract

Acoustic wavenumber spectroscopy (AWS) is an effective technique for the assessment of millimeter-scale damage on large thin-walled structures such as airplanes, wind turbine blades, ship hulls, and water tanks. To date, acoustic wavenumber spectroscopy remains a nondestructive evaluation technology, as it requires significant human intervention. This research demonstrates how including automated three-dimensional geometry scanning in 360-degrees can work to extend the capabilities of AWS to structural health monitoring. First, we collect threedimensional geometry for our wavenumber analysis over complex geometries. We perform this for three different samples: 1) A large plate oriented normal to the scanner, 2) Two plates clamped at an angle, and 3) An intentionally bowed plate. Then we perform wavenumber estimation on the structures correcting for perspective errors based on the geometry information. In the future, we plan to reduce human involvement during the data collection process.