Signal Processing and Damage Detection in a Frame Structure Excited by Chaotic Input Force

This paper discusses the development of a general time-frequency data analysis method, the Empirical Mode Decomposition (EMD) and Hubert Spectrum, and its application to structural health monitoring. The focus of this work is on feature extraction from structural response time series data. This is done by tracking unique characteristics of the adaptive decomposition components and developing a damage index based on previously introduced fundamental relationships connecting the instantaneous phase of a measured time series to the structural mass and stiffness parameters. Damage detection applications are investigated for a laboratory experiment of a simple frame (a model of a multi-story building) where damage is incurred by removing bolts at various locations. The frame is excited by a low dimensional deterministic chaos input as well as by broadband random signal. The time series output of the frame response is then analyzed with the EMD method. The time-frequency features and instantaneous phase relationships are extracted and examined for changes which may occur due to damage. These results are compared to results from other newly developed detection algorithms based on geometric properties of a chaotic attractor. Our results illustrate that the EMD and instantaneous phase detection approach, based on time-frequency analysis along with simple physics-based models, can be used to determine the presence and location of structural damage and permits the development of a reliable damage detection methodology.

Duke Scholars

Author Liming Salvino Civil and Environmental Engineering