The second project attempts to provide a technology for sorting used pallet parts by species to aid their reuse in reconstructed pallets. Species identification is a very difficult and time-consuming manual task, as used parts are often weathered and contaminated (dirty). Yet, species has a critical impact on pallet performance, and needs to be considered during assembly of reconstructed pallets. Preliminary tests indicate that magnetic resonance characterization, which has been applied to liquids inspection, may successfully distinguish important species groups. The pallet recycling industry is large, so such a technology is expected to have substantial impact.

Daniel L. Schmoldt, A. Lynn Abbott (VA Tech), Mark Schafer (Perceptron), and Timothy Rayner (Quantum Magnetics)

Accomplishments

• Previous studies demonstrated that voids, knots, and cross grain can be detected using ultrasonic inspection.
• Cooperative Research and Development Agreement has been signed with Perceptron to develop the inspection hardware and software for new pallet part inspection.
• Preliminary results suggest that magnetic resonance characterization can distinguish different wood species.

Current and Future Work

• Develop computer software to grade and sort pallet parts using the equipment provided by Perceptron.
• Pending funding support, conduct an extensive test of used pallet parts from 5 species groups (both clean and dirty) to determine if magnet resonance can be used for wood ID.

Technology Transfer Efforts

• Following completion of software and hardware developments, Perceptron plans to commercialize a system to grade and sort pallet parts.