Health Control of Tree Trunk Utilizing Microwave Imaging and Reverse Problem Algorithms

利用微波成像和逆问题算法进行树干健康控制

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Abstract

The voids in their trunk significantly affect tropical trees' health. Both the wood and timber industries may face substantial financial losses because of the lack of an effective technique to inspect the defected trees through deep zonal monitoring. Microwave imaging offers the advantages of mobility, processing time, compactness, and resolution over alternative imaging methods. An ultra-wide band (UWB) imaging system consisting of UWB antennas and a reverse problem algorithm is proposed. Several conditions, such as the size of trunk samples (16-30 cm), number of targets, size of voids, heterogeneity of media, and number of layers, are considered in experimental studies. Based on these studies, cylindrical wooden models with 100 and 140 mm diameters, one void at the center, and three voids in different locations were 3D printed. After proving the system's ability through simulation and measurements on 3D models, a rubber-wood trunk with a length of 75 cm was cut into smaller pieces. The images created utilizing the measured data showed that the system could detect voids in the rubber trunk. Furthermore, the system indicated a high percentage of reliability and repeatability.

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