Calibration Method for Monitoring Hygro-Mechanical Reactions of Pine and Oak Wood by Acoustic Emission Nondestructive Testing

Abstract

The main issue of wood is its sensitivity to Relative Humidity (RH) variations, affecting its dimensional stability, and thus leading to crack formations and propagations. In situ structural health monitoring campaigns imply the use of portable noninvasive techniques such as acoustic emission, used for real-time detection of energy released when cracks form and grow. This paper proposes a calibration method, i.e., acoustic emission, as an early warning tool for estimating the length of new formed cracks. The predictability of ductile and brittle fracture mechanisms based on acoustic emission features was investigated, as well as climate-induced damage effect, leading to a strain-hardening mechanism. Tensile tests were performed on specimens submitted to a 50% RH variation and coated with chemicals to limit moisture penetration through the radial surfaces. Samples were monitored for acoustic emission using a digital camera to individuate calibration curves that correlated the total emitted energy with the crack propagation, specifically during brittle fracture mechanism, since equations provide the energy to create a new surface as the crack propagates. The dynamic surface energy value was also evaluated and used to define a Locus of Equilibrium of the energy surface rate for crack initiation and arrest, as well as to experimentally demonstrate the proven fluctuation concept.

Calibration of Acoustic Emission Parameters in Relation to the Equilibrium Moisture Content Variations in a Pinus sylvestris Beam

“…Tensile tests were performed using a UTM (MTS-Measure Test Simulate ® [18]), by applying a displacement rate of 0.5 mm/min. During each tensile test, two types of fracture progressions were distinguished: brittle-like and ductile-like fracture progressions [16]. They differ in the rate of deformation of a material-the former being elastic and fast, the latter being plastic and slow-as well as in terms of the type of released energy.…”

“…In accordance with the procedure described in [16], the distribution of each acoustic emission parameter occurring during brittle phenomena was analyzed in order to identify the acoustic fingerprint of the species. Moreover, the cumulative sum of AE parameters was used to evaluate the sensitivity of AE with respect to dryness along the longitudinal and radial directions of the beam, and hence investigate the effect/impact of EMC changes on the mechanical properties of wood.…”

“…The acoustic waves propagate inside wooden material in different ways according to the type of wood [11] or the directionality of wood (radial, tangential, or longitudinal) within the same wood species [10]. Therefore, the acoustic emission monitoring has a wide variety of applications: it is an early warning technique that is useful for preventive detection of the stability of a structure before it can suffer damage from earthquakes or landslides [12]; it can be useful to detect the type and direction of grains in a wood [13]; and it can estimate moisture content in wooden objects [14,15] pinpointing its response to environmental variability [10,16].…”

Influencing Factors in Acoustic Emission Detection: A Literature Review Focusing on Grain Angle and High/Low Tree Ring Density of Scots Pine

“…The investigation showed that the most monitored acoustic Eeission parameters were amplitude (A), energy (E) and counts (C), which were frequently studied against time, crack length and load (even in their cumulative form) with their distribution often highlighted. Among the parameters less frequently studied there are the frequency characteristics [11,[16][17][18][19][20][21], other parameters such as the energy release rate (G) [22], the fracture toughness (K) [23,24], root mean square of the signal voltage (RMS) [25][26][27], density surface energy value (DSV) [16,23], stress (σ), strain (ε) [20,[28][29][30][31][32] and modulus of elasticity (MoE) [32,33].…”

“…Other works propose mathematical formulations for example as model to express the relationships between surface roughness and chip thickness [25], to compare experimental data to the theoretical ones [16], or to define the location algorithm used for the burst source location in wood specimens [30]. In Shao et al [39] a theoretical approach was presented in the study of the fractal theory applied to examine the fracture surfaces of five types of woods.…”