Velocity Error Correction Based Tomographic Imaging for Stress Wave Nondestructive Evaluation of Wood

Abstract

Stress wave testing has been applied in the nondestructive evaluation of wood for many years. However, the anisotropy property of wood and the limited number of sensors prevent an accurate stress wave velocity measurement and the high resolution of tomographic inversion. This paper proposes a tomographic imaging algorithm (IABLE) with a velocity error correction mechanism. The proposed algorithm computed the wave velocity distribution of the grid cells of wood cross-sections by the least square QR decomposition (LSQR) iterative inversion, and then optimized the tomography with a velocity error correction mechanism (ECM). To evaluate the performance of the proposed algorithm, several healthy and defective logs and live trees were selected as the experimental samples, and the nondestructive testing procedures were finished. With the stress wave velocity data sets measured via a PiCUS 3 stress wave testing instrument, the IABLE algorithm was implemented, and the tomographic images of the log samples and live trees were generated. The experimental results demonstrated the effectiveness of the proposed imaging algorithm for the nondestructive evaluation of wood.