13th International Conference on Fracture June 16–21, 2013, Beijing, China -1- Acoustic Emission Technique (AET) for Failure Analysis in wood materials Frédéric LAMY 1, Mokhfi TAKARLI 1,*, Frédéric DUBOIS 1, Nicolas ANGELLIER 1 , Ion-Octavian POP 1 1 Groupe d’Etude des Matériaux Hétérogènes, Université de Limoges, Egletons 19300, Country, France * Corresponding author: Mokhfi.takarli@unilim.fr Abstract Understanding failure mechanisms of construction materials as well as their damage evolution are two key factors to improve design tools of structures. Depending on failure modes to be highlighted, and studied, several tests methods, and analysis tools have been developed, in particular AET. This latter is an experimental tool well suited for characterizing material behavior by monitoring fracture process. Despite the wide use of AET to characterize and monitor damage evolution of composite materials, few research studies focused on using AET to characterize the mechanical behavior of wood materials. In this work, the failure process in wood material under monotonic loading is studied by confronting three experimental methods; by analyzing stress-strain curves, AE measurements, and digital image acquisition. First, results show good correlation and complementarity between the used methods. Second, simple approach in analysis of AE signals (cumulative event and energy) gives important information about crack initiation and growth without the material. Moreover, advanced analysis of AE data (determination of source locations and the study of mechanism of individual events; study of amplitude distributions; investigation of frequency characteristics of emission events) will allows us to understand some key damage mechanisms such as the fracture process zone. Keywords Acoustic Emission, Cracking, Wood, Fracture Energy 1. Introduction Knowledge of the failure mechanisms of construction material as well as their damage evolution are two key factors to improve design tools of structures. In this context, Seismic Non-Destructive Techniques (NDT) which are based on stress wave propagation are interesting techniques for monitor structural integrity and characterize the behavior of materials when they undergo deformation, fracture, or both. These techniques can be divided into two methods: passive and active. This paper focuses on the Acoustic Emission Technique (AET) which is a passive method. Acoustic emission may be defined as transient elastic waves generated by the rapid release of strain energy in a material. A number of micro and macro processes contribute to both the deformation and the deterioration of a material under strain, resulting to a series of acoustic events. Thus, the events released by the material contain information regarding the general deformation process. Kawamoto and Williams [1] reported literature review on the feasibility of AET for monitoring defects in wood. The advantages and the disadvantages of this technique were also described. It was noted that the AE investigations for wood products can be classified into five fields: (i) monitoring and control during drying; (ii) prediction of deformation; (iii) estimation of strength properties; (iv) fracture analysis, and (v) machine control. This introduction focuses on fracture analysis by AET. Ansell [2] related the AE-strain characteristic from three softwoods tested in tension to mechanisms of deformations observed by scanning electron microscopy. The authors also reported correlation of EA total count with fracture toughness. Similar relationship was obtained by Suzuki and Schniewind [3] during cleavage failure in adhesive joints. Landis and Whittaker [4] compared the energy released by a mode I crack propagation in wood with the resulting acoustic emission energy. Results of the energy comparison indicated a good correlation. Reiterer et al., [5] investigated the mode I fracture behavior of softwoods and hardwoods under the splitting test associated to acoustic emission measurements. The measured AE parameters included cumulative counts, amplitude and frequency spectra. The results showed that
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