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

Area of Science:

• Agricultural Engineering
• Non-destructive Testing
• Electromagnetics

Background:

• Internal voids significantly impact tropical tree health and pose economic risks to the wood and timber industries.
• Current inspection methods lack effectiveness for deep zonal monitoring of defects in trees.
• Microwave imaging presents advantages in mobility, processing speed, compactness, and resolution for such applications.

Purpose of the Study:

• To develop and validate an ultra-wide band (UWB) imaging system for detecting internal voids in tree trunks.
• To assess the system's performance under various conditions, including different sample sizes, void configurations, and material heterogeneities.

Main Methods:

• Proposed an ultra-wide band (UWB) imaging system utilizing UWB antennas and a reverse problem algorithm.
• Conducted experimental studies on cylindrical wooden models (100 and 140 mm diameters) with controlled voids.
• Validated the system through simulations and measurements on 3D printed models and a real rubber-wood trunk.

Main Results:

• The UWB imaging system successfully detected voids in 3D printed wooden models and a rubber-wood trunk.
• Experimental studies considered trunk sample sizes (16-30 cm), number/size of voids, and media heterogeneity.
• The system demonstrated high reliability and repeatability in void detection.

Conclusions:

• The proposed UWB microwave imaging system is effective for detecting internal voids in tree trunks.
• This technology offers a promising solution for deep zonal monitoring, mitigating financial losses in the wood industry.
• The system's reliability and repeatability support its potential for practical application in forest health assessment.