Virtual vibration measurement using KLT motion tracking algorithm

Abstract

This paper presents a practical framework and its applications of motion tracking algorithms applied to structural dynamics. Tracking points (“features”) across multiple images is a fundamental operation in many computer vision applications. The aim of this work is to show the capability of computer vision (CV) for estimating the dynamic characteristics of two mechanical systems using a non contact, marker less and simultaneous Single Input Multiple Output (SIMO) analysis. KLT (Kanade-Lucas-Tomasi) trackers are used as virtual sensors on mechanical systems video from high speed camera. First we introduce the paradigm of virtual sensors in the field of modal analysis using video processing. To validate our method, a simple experiment is proposed: an Oberst beam test with harmonic excitation (mode 1). Then with the example of helicopter blade, Frequency Response Functions (FRFs) reconstruction is carried out by introducing several signal processing enhancements (filtering, smoothing). The CV experimental results (frequencies, mode shapes) are compared with classical modal approach and FEM model showing high correlation. The main interest of this method is that displacements are simply measured using only video at FPS (Frame Per Second) respecting the Nyquist frequency.