In situ damage monitoring in timber materials: acoustic emission pattern recognition approach based on Hilbert–Huang transform

Abstract

A key part of structural damage monitoring occurring in timber materials aims to identify the most relevant descriptors of critical damage mechanisms. The sudden release of stored energy during the damage process, known as the Acoustic Emission (AE), is a very suitable technique for in situ health monitoring applications. Various signal processing and pattern recognition techniques have been performed for damage feature extraction from AE signals. The purpose of this paper is to use the Hilbert–Huang transform (HHT), for relating a specific damage mechanism to its acoustic signature. The applicability of this local instantaneous frequency descriptor for damage characterization in timber materials is discussed. First, the HHT is used to identify the damage signature, by correlating the measured AE signals with known acoustic sources. Then, the performance of the Hilbert–Huang transform damage classification approach is evaluated.