The difference in density and wave velocity causes distinct wave impedance between air and wood, resulting in complex acoustic emission (AE) signals due to reflection on the wood’s surface. This study explores the suppression of AE signal reflection by modifying the structure of thin wood panels, utilizing the theory of acoustic black holes (ABH). Initially, a one-dimensional ABH structure was created by forming a wedge structure on one side of the specimen. Pencil-lead break (PLB) tests simulated sudden AE sources on the specimen’s surface. AE signals were collected using three equidistant sensors on the upper surface, with a sampling frequency of 2 MHz. The AE signal was then segmented into frequency bands using the differential method and analyzed in both time and frequency domains. Comparisons were made to understand the impact of the one-dimensional ABH on AE signal propagation. Results demonstrated that the one-dimensional ABH effectively suppressed AE signal reflection on the wood’s surface, reducing the high-frequency components by 18.31%, 20.83%, and 12.09% for each sensor, respectively. Furthermore, the experimental cut-off frequency of 0.98 kHz surpassed the theoretically calculated value of 0.39 kHz due to the disparity between the ABH structure’s thickness and the theoretical prediction.
To explore the propagation law of AE signal in wood, the propagation velocity of P-wave and S-wave and the energy attenuation law of different frequency components were studied By PLB (pencil-lead break) tests. Firstly, an improved time-difference-of-arrival (TDOA) method was designed to determine the arrive time. The propagation velocities of P-wave and S-wave were calculated. Then, the Young’s modulus was estimated by P-wave velocity. Finally, on the basis of eliminating the influence of standing wave, the energy attenuation models were obtained by numerical fitting and wavelet decomposition. The results showed that the improved TDOA algorithm can calculate the propagation velocity of P-wave and S-wave at the same time through one test, and the P-wave velocity can be used to estimate the Young’s modulus. P-wave propagated faster in soft wood, while S-wave propagated faster in hard wood. The higher the frequency of AE signal, the faster the energy attenuation.
Artificial AE sources were generated on the surfaces of Ulmus pumila, Zelkova schneideriana, Cunninghamia lanceolata, and Pinus sylvestris var. mongolica Litv. specimens. The AE transverse wave signal was decomposed into 3-layers detail signals by wavelet decomposition and reconstructed, and it was calculated based on correlation analysis. Then the longitudinal wave speed was calculated according to the time-difference-of-arrival (TDOA) method, and the wood dispersion phenomenon was studied. The results showed that the dispersion phenomenon of Ulmus pumila was obvious. The propagation speed of high-frequency signal was 2.38 times that of low-frequency signal. The ratio of high and low frequency propagation speed of soft wood was 1.72 and 1.73. The dispersion degree of Zelkova schneideriana was the weakest, and the propagation speed of the high frequency was 1.25 times of the low one. The ratios of longitudinal and transverse wave speeds of the four specimens were 4.59, 4.07, 4.24 and 4.2, respectively.
To investigate the effect of Zelkova schneideriana surface cracks on the longitudinal wave propagation characteristics of acoustic emission (AE). Different sizes and numbers of cracks were made on the surface of the specimen, the propagation characteristics of AE longitudinal waves along wood texture direction were studied. Firstly, five regular cracks with the same length, different width, depth and equidistant distribution were fabricated on the surface of the specimen. The burst and continuous AE sources were generated by lead core breakage and signal generator, and the AE signals were acquired by 5 sensors with sampling frequency was set to 500 kHz. Then, the propagation speed of AE longitudinal wave was calculated by Time Difference of Arrival (TDOA) based on lead core breakage. Finally, the 150 kHz pulse signals of different voltage levels generated by the signal generator were used as AE sources to study the influence of cracks on the attenuation of AE longitudinal wave energy. The results showed that the AE longitudinal wave propagation speed under the crack-free specimen was 4838.7 m.s-1. However, after the regular crack was artificially made, the longitudinal wave speed reduced to a certain extent, and the relative error of the change was not more than 9%. Compared with the energy decay rate of 1.29 in the crack-free specimen, the decay rate gradually increased to 2.08 with the increase of the crack cross-sectional area.
To study the propagation law of acoustic emission (AE) longitudinal waves in wood, the relationship among wave velocity, standing wave fundamental frequency and Young’s modulus of elasticity was studied, and the energy decay model of AE longitudinal waves along the grain direction was established. Firstly, the propagation velocity of the longitudinal wave was calculated using the time-difference method. Then, the relationship between the wave velocity and Young’s modulus of elasticity was analyzed and the method of calculating the longitudinal wave velocity using the fundamental frequency was proposed. Finally, using different levels’ pulse strings as AE sources, the attenuation law of AE signal energy with distance was studied. The results show that the longitudinal wave velocity can be estimated more accurately by using the standing wave fundamental frequency. The influence of Poisson’s ratio needs to be considered when calculating the Young’s modulus of elasticity by using the longitudinal wave velocity.
In order to explore the influence of wood’s anisotropic characteristics on Acoustic Emission (AE) signals’ propagation, the law of AE signals’ propagation velocity along different directions was studied. First, The center of the specimen’s surface was took as the AE source, then 24 directions were chose one by one every 15º around the center, and 2 AE sensors were arranged in each direction to collect the original AE signals. Second, the wavelet analysis was used to denoise the original AE signals, then the AE signals were reconstructed by Empirical Mode Decomposition (EMD). Finally, time difference location method was utilized to calculate AE signals’ propagation velocity. The results demonstrate that AE signals’ propagation velocity has obvious feature of quadratic function. In the range of 90º, as the angle of propagation direction increases, the propagation velocity of the AE signals presents a downward trend.
Through the time-frequency analysis of the propagation waveform of the acoustic emission (AE) signal propagating in the thin sheet of Pinus sylvestris var. mongolica, the propagation characteristics of the stress wave when propagating as a lamb wave was studied. An AE source was generated on the surface of the specimen, the discrete wavelet transform method was used to achieve AE signal de-noising and reconstruct the waveform of the AE signal. On this basis, the time difference positioning method was used to calculate the propagation velocity of lamb waves, and compared with the propagation characteristics of lamb waves in the metal specimen. The results show that the high-frequency mode of lamb waves attenuated sharply as they propagate in the thin wood sheet, indicating that the microstructure of wood has a significant low-pass characteristic for lamb waves. The average attenuation rates of lamb waves in metal and thin wood sheet were 87.1% and 75.7%, and the velocity was 4447.0 m.s-1 and 1186.3 m.s-1, respectively. This shows that AE signals can travel longer distances in the thin wood sheet, but the propagation velocity is significantly reduced.