Advanced Wood Damage Detection and Monitoring Using Instantaneous Frequency Analysis of Acoustic Emission Signals

In order to obtain the acoustic emission (AE) signals of hardwood and softwood in the process of bending failure, and to evaluate their damage degree, this article proposes a method to identify AE events based on the instantaneous frequency of the AE signal and dynamic monitoring of the wood damage based on the density statistics of AE events. First, air-dried Zelkova schneideriana and Pinus sylvestris var. mongolica samples were used for the bending test, and the original AE signal was collected using a three-channel NI USB-6366 high-speed data acquisition card. Second, a wavelet transform was used to reduce the noise of the original AE signal, and then the deformation AE, microfracture AE, and fracture AE events were defined according to the frequency domain distribution and causes of the AE signal and the damage images of the specimens. Finally, the Hilbert transform was used to obtain the instantaneous frequency of the AE signal, and then the occurrence densities of the three types of AE events were counted based on the instantaneous frequency. The density curves of AE events were then utilized to distinguish the damage characteristics of the two specimens, and to determine and predict the stress release and damage trends of wood under loading. The experimental results show that defining and counting AE events in the frequency domain based on the instantaneous frequency of the AE signal can better reflect the stress level of the material, so as to objectively evaluate and predict the degree and trend of wood damage.