Structural Damage Detection Using Time Domain Periodogram Analysis

Before the advent of computers, scientists used time domain periodogram analysis (TDPA) for analysis of phenomena described by time-dependent parameters. Famous examples of this approach include investigations of periodicities in Sun activity, analysis of annual rings of trees and deposits of clays in large lakes, both of which are indicators of climate variations. These periodicities found by TDPA were later confirmed using modern Fourier transform-based methods. Since the advent of the computer era and the fast Fourier transform, TDPA has been almost completely abandoned. In this work, we develop a computer-based TDPA algorithm and demonstrate its' utility for determining the existence (Level 1) of structural damage. First, the TDPA is compared to a frequency domain periodogram analysis for synthetic signals with well-defined statistical properties. This comparison elucidates the features of the TDPA algorithm. Next, a damage existence `feature' is identified from the TDPA and is shown to be a reliable indicator of the existence of structural damage. This is demonstrated using simulated and actual experimental data.