ObjectiveStress wave tomography imaging technology has been popularly applied in wood nondestructive evaluation for many years. However, the anisotropy property of wood and the error of stress wave velocity inversion have great impact on the accuracy of tomography imaging. Therefore, it is important to improve the accuracy of the tomography image.

MethodBased on the traditional stress wave velocity inversion principle, this paper proposes a tomography imaging algorithm (ECIA) with velocity error correction mechanism. The proposed algorithm computes the wave velocity distribution of the grid cells of the wood cross-section by the least square QR decomposition (LSQR) iterative inversion, and then optimizes the tomography with a velocity error correction mechanism (ECM). To evaluate the performance of the proposed algorithm, several healthy and defective logs and ancient live trees in Yangzhou City of Jiangsu Province, southern China were selected as experimental samples, and the nondestructive testing procedures were finished. With the stress wave velocity data sets measured by PICUS equipment, ECIA algorithm was implemented, and the tomography images of log samples and live trees were generated.

ResultECIA algorithm detected the decay area accurately for log samples and live tree samples. ECIA algorithm had a higher accuracy than PICUS especially for the slight decay.

ConclusionECIA algorithm can generate accurately tomography images and be used for wood nondestructive evaluation.