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

Authors :
Juncheng Tu
Lichuan Yu
Jian Zhao
Jianzhong Zhang
Dong Zhao
Source :
Forests, Vol 13, Iss 4, p 631 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

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

Details

Language :
English
ISSN :
19994907
Volume :
13
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Forests
Publication Type :
Academic Journal
Accession number :
edsdoj.7ea352928fcc4720a62fb1310414de4e
Document Type :
article
Full Text :
https://doi.org/10.3390/f13040631