Introduction

Acoustic emission (AE) is the emission of sound waves in the audible and ultrasonic range, which is caused be microscopic fractures, friction of fracture surfaces, outflow of liquids, transport process in capillaries of other effects (Niemz et al. 2022). The AE has been studied for nearly half a century in the field of wood and wood-based materials. The AE technique includes determining the physical and mechanical properties of wood, as well as grading, drying, and detecting defects of wood based on the AE of wood when subjected to loads (Hu et al. 2021a, Zhao et al. 2020). The AE has been widely used in healthy monitoring of wood constructions including wood timber, shear wall, and other component of wood buildings and products (Yin et al. 2021). The focus of AE is the investigation of the relationships between structure and properties of wood. However, the vibrational properties of wood were rarely investigated.

It is known that AE in wood can appear as a result of mechanical stresses caused by mechanical, external loading or wood-internal sorptive stresses (Raczkowski et al. 1994). So far, many publications (Krajewski et al. 2020, Yan et al. 2022, Wu et al. 2021, Nasir et al. 2019, Niu and Huang 2022, Tang et al. 2022) had reported the basic knowledge of AE generated by external loading and AE applied to monitor the AE generated by wood-internal sorptive stresses in wood products and structures. Ozyhar et al. (2013) determined the moisture-dependent elastic characteristics of beech wood by means of ultrasonic waves.

Researchers have tried to obtain more accurate AE signals to know the position and details of cracks in wood and wood constructions. However, AE characteristic signals of wood are affected by many factors, such as wood species (Perrin et al. 2019, Xu et al. 2020, Ansell 1982, Lin et al. 2022, Liu et al. 2023), moisture content (Sato et al. 1984, Fu et al. 2021), density (softwood and hardwood) (Ansell 1982, Reiterer et al. 2000, Chen et al. 2006), wood grains (Brémaud et al. 2011, Boccacci et al. 2022), loading types (Chen et al. 2006, Ohuchi et al. 2011) and the distance between the AE source and the transducers (Lukomski et al. 2017, Pan et al. 2022, Zhao et al. 2022, Zhu et al. 2022). Most studies were mainly focused on how these factors influenced AE characteristic signals and their relationships with mechanical properties of wood (Rescalvo et al. 2020). The most important factors influencing AE of wood are the structure (density, fiber length, particle geometry, type, and percentage of adhesive, etc.), the moisture content, and the history (e.g., fungal infections or insect attack, mechanical or climate pre-stress) of wood and wood-based material (Niemz et al. 2022).

All above studies indicated that：1) ratio of earlywood to latewood had significant effect on AE signals when subjected to tensile load (Ansell 1982); 2) AE signals of wood decreased in high moisture content (Sato et al. 1984); 3) AE counts of softwoods were higher than those of hardwoods when cracked in mode I compact tension tests, while in torsion load condition, opposite results were obtained (Sato et al. 1984), which suggested that loading types seriously influenced AE events. In addition, Perrin et al. (2019) investigated the effects of wood species on AE signals under four-point bending load condition, which reported that unique AE signal appeared for each kind of wood species indicating that the more diverse the wood species was, the more characteristic the AE signal was. This contributes to classify the different wood species.

Above research confirmed that AE signal has potential in evaluating wood mechanical properties. However, there are still many aspects of AE properties unknown. The aim of this study was to obtain and compare the AE characteristics of four commonly used wood species. In this study, the maximum acoustic pressure and power spectrum of four commonly used wood species under three-point bending load condition using notched bending samples. Specifically,

1) the physical and mechanical properties of the four wood species were studied; 2) the mechanical and acoustic characteristics of the four wood species were determined using notched bending test method; 3) failure modes of notched bending samples were analyzed based on fractal dimension theory; 4) the relationship between vibrational characteristics and fractal dimension was fitted.

Materials and methods

Materials

The four wood species used in this study were Poplar (Populus tomentosa Carrière), Mahogany (Swietenia mahagoni (L.) Jacq.), Beech (Fagus orientalis Lipsky), and Ash (Fraxinus excelsior L.). All above wood lumbers were bought from local commercial wood supplier (Nanjing, China) and stored in the woodshop of Nanjing Forestry University for more than 12 months and reached air dry condition.

Specimen preparation

Figure 1 shows the dimensions of the samples used in this study. All these samples were cut from full-size lumbers of each species. The samples for three-point bending tests measured 300 mm × 20 mm × 20 mm (length × width × thickness) according to the ASTM D4761-19 (2019). The dimensions of sample for notched bending test were the same with those of three-point bending test except a notch measured 5 mm × 10 mm × 20 mm (height × width × depth) at the middle of length, and 1 mm initial cracks at the notch corners were made using a knife. Among these four wood species, the boundary of earlywood and latewood of ash wood were clear. Therefore, for ash wood samples, the notched bending test samples with initial cracks at earlywood and latewood were prepared. Other wood species were not distinguished earlywood and latewood.

Experimental design

Table 1 shows the experimental design, which indicates that there are 108 samples prepared in this study with 12 replications for each combination of wood species and testing methods. After bending tests, the clear samples measured 20 mm × 20 mm × 20 mm were cut at the non-destruction parts for measurements of specific gravity (SG) and moisture content (MC) with 10 replications for each species.

Testing methods

Three-point bending

The three-point bending tests were conducted according to ASTM D4761-19 (2019). The load was controlled by displacement with a loading rate 5 mm/min. The bending modulus of elasticity (MOE) and the modulus of rapture (MOR) of the four wood species were calculated using Equation 1 and Equation 2, respectively. The first loading point was 200 N, and second loading point was 700 N, which were selected to ensure the wood kept in elastic stage. The MOE can be calculated according to Equation 1. Then the load continued until samples completely failed. The MOR is available using Equation 2.

Where E is bending modulus of elasticity (MPa); σ is bending modulus of rapture (MPa); ∆P is change of load in elastic range (N); ∆f is change of deflection corresponding to ∆P (mm); l, b and h are length, width, and height (mm) of samples, respectively; Pmax is the ultimate load when samples fracture (N).

Notched bending

Figure 2 shows the setup for the notched bending tests and vibrational properties tests. The loading condition was the same with that of three-point bending test, the span was 240 mm. Meanwhile, a non-touched microphone sensor (with a pre-amplifier built in) was set in front of the notched corner with 5 mm (Figure 2) used to record the vibrational signal generated during the cracks propagation when subjected to the notched bending load. The universal testing machine did not stop loading until reaching the maximum load. The universal testing machine and computer recorded the load and deflection data, and the FFT analyzer (CF9200, ONOSOKKI, Japan) recorded the vibrational signals including maximum acoustic pressure and power spectrum. The specific settings of the FFT were that 1) the sample frequency ranged from 0 kHz to 4 kHz with a sample point of 2018; 2) the threshold of the microphone was 1 Pa to filter environmental noise. The main testing procedure was that: 1) turn on the FFT analyzer and set the parameters according to above descriptions; 2) start loading until sample fail with a loading speed of 5 mm/min controlled by displacement; 3) output the data, i.e., time, deflection, and load, from the universal testing machine, and vibrational signals, i.e., frequency, amplitude, and acoustic pressure, were also outputted from the FFT analyzer.

Specific gravity and moisture content

After finishing the three-point bending tests and notched bending tests, the SG and MC were measured using the samples cut from the tested three-point samples according to the ASTM D2395-17 (2022) and the ASTM D4442-20 (2020), respectively.

Statistical analysis

The basic physical, mechanical properties, and acoustic characteristics of the four types of wood species were analyzed using analysis of variance (ANOVA) general linear method (GLM) procedure. Mean comparisons using the protected least significant difference (LSD) multiple comparison procedure was conducted if any significant was identified. All these analyses were performed at 5% significance level using the SPSS 22.0 (IBM 2013). Fractal dimensions were calculated using the Fraclab 2.2 toolbox (INRIA 2017) built in the MATLAB R2014a (MathWorks 2014). The specific calculation procedure of fractal dimensions of power spectrum followed our former work (Hu et al. 2021b).

Results and discussion

Basic physical and mechanical properties

Figure 3 shows the typical load and deflection curves of the four wood species when subjected to three-point bending load, which indicates that the failure modes of ash, beech and poplar are ductile, and that of mahogany is nearly brittle. Table 2 further shows the mean comparisons of basic physical (SG and MC) and mechanical properties (ultimate load, MOE, and MOR) of all evaluated wood species. All testing results of dependent variables evaluated were in normality distributions. Significant differences of SG exist between the four wood species. The specific order of SG from high to low is Ash (Fraxinus excelsior L.), Beech (Fagus orientalis Lipsky), Mahogany (Swietenia mahagoni (L.) Jacq.), and Poplar (Populus tomentosa Carrière). In case of MC, Ash (Fraxinus excelsior L.) wood had significantly higher MC than Beech (Fagus orientalis Lipsky) and Mahogany (Swietenia mahagoni (L.) Jacq.) followed by Poplar (Populus tomentosa Carrière), but the difference between Beech (Fagus orientalis Lipsky) and Mahogany (Swietenia mahagoni (L.) Jacq.) was not significant. The values of all mechanical properties of the four wood species had the same trends that Ash (Fraxinus excelsior L.) and Beech (Fagus orientalis Lipsky) had significantly greater values than those of Poplar (Populus tomentosa Carrière) and Mahogany (Swietenia mahagoni (L.) Jacq.), but no significantly difference was found between Ash (Fraxinus excelsior L.) and Beech (Fagus orientalis Lipsky) wood. Here, the ultimate load, MOE, and MOR of Poplar (Populus tomentosa Carrière) were all significantly higher than Mahogany (Swietenia mahagoni (L.) Jacq.), which was opposite to the relative values of their density. This may lie to the brittle failure of Mahogany (Swietenia mahagoni (L.) Jacq.) shown in Figure 3.

Mechanical and acoustic properties of notched bending samples

Figure 4 shows a combination of typical load-deflection, acoustic pressure-time, and power spectrum (amplitude-frequency curve) of an ash wood sample. In theory, the acoustic pressure and power amplitude reached their peak values when the load reached the maximum value. Meanwhile, the amplitude-frequency curves indicate the energy releasing process. The greater the amplitude is, the more the energy releasing is, and the larger the area generated by fracture is. Based on the above theory, the fractal dimensions of power spectrum curve (FDPS) were used to indicate the morphology of fracture surface indirectly.

Table 3 shows the ultimate load, maximum acoustic pressure and FDPS of notched bending tested samples. The maximum acoustic pressure of mahogany was significantly higher than those of Poplar (Populus tomentosa Carrière), Beech (Fagus orientalis Lipsky), and Ash (Fraxinus excelsior L.). There were no significant differences between poplar, beech, and ash. Combining the failure modes and load-deflection curves shown in Figure 5, it can be found that the failure mode of mahogany under notched bending test was also brittle, and the other three wood species were ductile, which was consistent with three-point bending test. Above results also confirmed the results of other researchers (Lukomski et al. 2017) that mahogany was more sensitive to notched corner than the other three wood species.

Relationships between acoustic pressure and FDPS

For further analysis, the acoustic characteristics, Figure 6 shows the relationships between maximum acoustic pressure and FDPS fitted using linear regression method regarding each wood species as independent sample and population sample, respectively.

Table 4 shows the fitting equations and their corresponding correlation coefficients when four wood species were regarded as independent and population samples. It indicated that there were linear positive proportional relationships between maximum acoustic pressure and FDPS regardless of four wood species seen as independent or population samples, which suggested that the relationship maybe suitable to other wood species, but further studies need to be conducted to confirm it. Ash wood had the highest correlation coefficient of 0,904 among the four wood species, which owned to that the grains of ash wood samples are straight during samples preparation. The correlation coefficients of the other three wood species were all bigger than 0,76 which satisfied the engineering application (Zhou et al. 2022a, Zhou et al. 2022b, Tao and Yan 2022).

Failure modes of notched ash wood samples

Figure 7 shows the typical failure modes and their corresponding amplitude-frequency curves of ash wood samples when subjected to notched bending load, which indicates that there are three types of failure modes including single crack at latewood (Figure 7a), single crack at earlywood (Figure 7b), and double cracks at earlywood (Figure 7c).

Table 5 shows the mean maximum amplitude and FDPS of the ash wood samples corresponding to three typical failure modes, which indicates that the maximum amplitude and FDPS values of ash wood samples with single crack generated at latewood were greater than those of earlywood. The maximum amplitude of ash wood samples with double cracks generated at earlywood was lower than those of single cracks at earlywood, but the FDPS was slightly higher than single cracks at earlywood. Meanwhile, there were two peaks in amplitude-frequency curves when the double cracks generated at earlywood, whereas, one peak when single cracks generated. Therefore, the amplitude-frequency curves and FDPS could be indicators for predicting where and numbers of cracks generated when subjected to notched bending load. Previous study also supported this point (Hu and Zhang 2022).

Conclusions

In this study, the mechanical properties and acoustic emission of four commonly used wood species were studied through using power spectrum analysis method (PSAM) and fractal theory. Following conclusions were drawn.

The modulus of elasticity (MOE) and modulus of rapture (MOR) of the four wood species evaluated were ash, beech, poplar, and mahogany from high to low, and MOE and MOR had the same changing trends.

Although the specific gravity of mahogany was greater than poplar, the MOE and MOR of mahogany were lower than those of poplar. Because brittle fracture was occurred to mahogany when subjected to three-point bending and notched bending loads.

Mahogany had the highest acoustic pressure among the four wood species, which indicated that brittle fracture generated higher acoustic pressures. There were positive linear proportional relationships between four wood species and fractal dimensions of power spectrum (FDPS).

The number of peaks in acoustic pressure-frequency curve of ash wood and its FDPS could be used to predict where and number of cracks generated when subjected to notched bending load.

Acknowledgements

This study was supported by Scientific Research Foundation of Metasequoia Teacher (163104060), and A Project from International Cooperation Joint Laboratory for Production, Education, Research, and Application of Ecological Health Care on Home Furnishing.

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Author notes

^♠Corresponding author: hwg@njfu.edu.cn