Damage Detection and Localization using Random Decrement Technique on Metallic Plates

Technique with the capability of detecting and localizing damage of structures using naturally operating environments can provide a possibility of developing more efficient and simpler structural health monitoring systems. This passive sensing technique would eliminate the need of active actuation which requires power either from battery or ambients to generate controlled excitation source. In a recent study, self-Green's functions (GF) were reconstructed using auto-correlation (AC), combined with a damage index by comparing the differences in GFs between damaged and pristine metallic panels to locate the damage. In this paper, random decrement (RD) technique is proposed to reconstruct GF with computational efficiency. While the RD has been widely used for damage detection and structure parameter extraction in civil structures, in the frequency usually below 1 kHz; this study explores using RD up to 15 kHz for transient wave reconstruction and then damage localization. The concept is first validated through simulation for a plate structure, and the results show that the reconstructed self-Green's function match well with the one from the auto-correlation technique after approximately 10,000 averages of the RD signatures. For experimental verification, a flat aluminum panel and an integral stiffened aluminum panel were subjected to localized high-pressure air from the air compressor. A laser Doppler vibrometer (LDV) was automated to scan a 150 mm x 150 mm area to create a 13 x 13 2-D array signals for the pristine and damaged structures. GFs were reconstructed using RD and mean square deviation (MSD) was used for creating the damage imaging map. The result shows that the waveforms of GFs from the damaged panel are distinct from those from the pristine panel, provided the scanning positions belong to the same region with the damage. The waveform deviation was observed rather easily, indicating its damage detection capability. The result also shows that damage imaging results are in agreement with the real damage locations, which proves damage can be localized via proposed technique. The proposed automation and RD technique reduce inspection time by half in comparison with the one using auto correlation and manually inspection. It was found that for future structural design, stiffening ribs could be installed in the structure not only to strengthen the structure but also to assist damage detection with fewer monitoring locations.