Calibration strategy for a nondestructive wood characterization tool using optimized time-of-flight determination and material propagation analysis

Abstract Instrument calibration is essential to ensure measurement accuracy and reliability, particularly in wood characterization using non-destructive acoustic techniques. This study aims to develop and validate an improved calibration strategy for wood characterization tools. It focuses on integrating advanced algorithms into resource-constrained microcontroller systems. An optimized time-of-flight (ToF) detection algorithm based on the Akaike Information criterion (AIC) was implemented. The algorithm incorporates adaptive intelligent windows to autonomously identify the onset of acoustic waves, eliminating user intervention and enhancing repeatability. A suitable calibration material compatible with commercial piezoelectric sensors was identified and adapted for testing. Experimental investigations were carried out on cylindrical rods of various materials and lengths to measure acoustic wave propagation velocity, comparing results from two commercial systems and a laboratory-developed prototype. ToF measurements obtained with the prototype showed a high level of agreement with theoretical propagation times, outperforming commercial systems in accuracy and computational efficiency. These findings support the use of an aluminum bar as the reference calibration material, alongside the intelligent AIC algorithm, to ensure consistent and reliable measurements. The proposed calibration strategy offers a robust and repeatable solution for wood characterization applications. By optimizing computational efficiency and accuracy, this approach enables the integration of advanced acoustic measurement techniques into cost-effective, microcontroller-based systems, paving the way for broader adoption in industrial and research settings.