Damage Modes Recognition of Wood Based on Acoustic Emission Technique and Hilbert–Huang Transform Analysis

Identifying the different damage modes of wood is great significance for monitoring occurrence, development, and evolution material damage. This paper presents research results application acoustic emission (AE) technology to analyze evaluate mapping relationship between pattern in fracture process AE signal. For three-point bending specimen with pre-crack, double cantilever beam specimen, single fiber tensile uniaxial compression test were performed, respectively. After post-processing analysis recorded signal, show that peak frequency an effective parameter identifying wood. In this study, empirical mode decomposition (EMD) signal can separate extract a variety contained The Hilbert–Huang transform (HHT) clearly describe distribution intrinsic function (IMF) components stages on time scale, calculate instantaneous energy accurately, which provides basis recognition lays foundation further accurate evaluation process.