Feature extraction of wood-hole defects using empirical mode decomposition of ultrasonic signals

Holes and knots are common defects that occur in wood that affect its value for both structural and high-end aesthetic applications. When these defects are internal to wood they are rarely evident from visual inspection. It is therefore important to develop techniques to detect and analyse these defects both in standing trees prior to harvesting them and in processed timber and/or completed wooden structures. This paper presents an effective method to detect and analyse hole defects in wood. The method uses the recorded output wave signal from an ultrasonic device tested on rectangular wood samples. The ultrasonic wave signal is decomposed into its constructive modes using Empirical Mode Decomposition (EMD). This process decomposes a non-stationary nonlinear wave signal into its semi-orthogonal bases known as intrinsic mode functions (IMFs). A matrix of all IMFs (except the residual IMF) is then assembled and its covariance matrix derived. The research demonstrates through several experimental studies that the maximum eigenvalue of the proposed covariance matrix is more sensitive to hole defects in wood than traditionally used measures such as time-of-flight. The results provide evidence that the proposed damage sensitive feature (DSF) can successfully detect hole defects in hardwood samples but further work is recommended on its application to other materials. It is anticipated that this method will have wide applicability in the forestry and timber industries for aiding in product value determination.