Fractography combined with unsupervised pattern recognition of acoustic emission signals for a better understanding of crack propagation in adhesively bonded wood

Journal article (2019)

Authors

Gaspard Clerc Bern University of Applied Sciences, Technische Universität München
Markus G.R. Sause Universität Augsburg
Andreas J. Brunner Swiss Federal Laboratories for Materials Science and Technology (Empa)
Peter Niemz Bern University of Applied Sciences
J.W.G. van de Kuilen Technische Universität München, Bio-based Structures & Materials - CEG
Research Group
Bio-based Structures & Materials (CEG) (TU Delft)
More Info
expand_more

Published Date

2019

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Civil Engineering & Geosciences

Department

Engineering Structures

Research Group

Bio-based Structures & Materials

Abstract

In this paper, acoustic emission (AE) signals obtained during quasi-static crack propagation in adhesively bonded beech wood were classified using an unsupervised pattern recognition method. Two ductile one-component polyurethane (1C-PUR) adhesives with the same formulation except for one system being reinforced with short polyamide (~ 1 mm long) fibers were compared to a relative brittle phenol–resorcinol–formaldehyde (PRF) adhesive. Using only localized AE signals, it was shown that the signals originating from the crack propagation could be classified into two different clusters. Comparing the AE signals with a new fractography method, it was estimated that different clusters are due to distinct failure mechanisms, with signals of cluster 1 being associated with wood failure and signals of cluster 2 with adhesive failure. The obtained results suggest that for the PRF adhesive the wood fibers help to slow down the crack propagation. A similar but lesser effect was noted for the polyamide fibers added to the 1C-PUR adhesive matrix.

Files

Clerc2019_Article_Fractography... (.pdf)
(.pdf | 2.18 Mb)

Download not available