Damage Detection by Template Matching of Scattered Waves

Abstract

A method based on template matching is presented to detect and locate damage in buildings following severe shaking by an earthquake. The templates are constructed by finite-element simulations of a suite of damage scenarios, with the solutions evaluated at the location (and orientation) of each sensor in the structure. The damage detection is carried out by cross-correlating the templates with recordings acquired from earthquakes. A dense distributed network of sensors is important for detecting anomalies in the presence of ambient noise. The cross correlation of the templates with themselves provides a measure of the resolution of the damage location.

A cost-effective neural network–based damage detection procedure for cylindrical equipment

“…Due to the large amount of data in time domain as well as the noise effects, they employed the independent component analysis (ICA). Massari et al 13 investigated a method based on the template matching to detect and locate the damage in buildings following severe earthquake shaking. Pakrashi et al 14 studied a statistical approach on the detection of the presence, the location, and the extent of an open crack from the first fundamental mode shape of a simply supported beam.…”