Detecting and measuring internal anomalies in tree trunks using radar data for layer identification

Abstract

Radar detection has proven to be an effective, nondestructive test for the determination of the quality of wood-based materials, especially in the wooden structures of ancient buildings and trees. However, the results are usually inaccurate, and it is difficult to interpret internal anomalies due to the moisture content of wood, individual differences, and other factors. In this paper, a new measurement method is proposed based on the use of ground-penetrating radar (GPR) for abnormality localization and imaging. Firstly, the time delay of the reflected signal in the inner trees is analyzed with matched filter and Hilbert detections. Secondly, the two approaches are compared with the use of a forward model, and the Hilbert algorithm is found to be more accurate. Thirdly, a laser scanner is used to collect contour data and determine the location and characteristics of internal tree anomalies. Lastly, the proposed method is tested on ancient willows at the Summer Palace. The results show that the error in the depth and area estimates of the anomalies was within 10% and 5%, respectively. Consequently, the GPR method for locating the anomalies in trees is feasible, and a laser scanner combined with contour data can present the size of the abnormal regions within the trees.