Dynamic Mode Decomposition for Resonant Frequency Identification of Oscillating Structures

Feature-tracking is widely used in the vibration community for its noninvasive way of extracting subtle motion. High-frequency optical features, such as edges, are prime candidates for motion estimation; however, their rapid motion can pose problems for computer vision techniques. Most vibration seen in video is unperceivable to the naked eye, which can make sub-pixel displacement extraction more complex. Phase-based motion magnification (PMM) is a computer vision technique that can amplify motion seen in video. A boost in the signal-to-noise ratio of a particular frequency band can permit further evaluation of higher order dynamics. A need for larger magnification is necessary to visualize and quantify resonant frequencies. This amplification can produce ringing effects which degrade image quality and key features such as edges. In this work, the use of dynamic mode decomposition (DMD) permits an unsupervised approach of extracting structural dynamic parameters from video. Out-of-plane resonant frequencies are estimated from a 2.7 (m) wind turbine blade. The findings are compared to current state-of-the-art methodologies such as traditional wired sensing. The determination of resonant frequencies ultimately fosters further understanding of large structure dynamics that are present in optical data.