Donar DE-XRT Pro AI-Driven Sorting System

Wood waste recycling presents a unique sorting challenge: wood waste streams contain a mixture of wood of different quality grades and moisture levels, as well as hidden contaminants such as metals, stones, and high-density foreign objects, and the combinations of these materials are difficult to predict. For wood recyclers, the ability to efficiently classify wood by density and quality grade, while detecting and removing impurities, is the key to producing high-purity wood fractions.

The Donar DE-XRT Pro Series is an intelligent machine-vision-based sorting system tailored for this exact scenario. It employs a deep fusion of dual-energy X-ray transmission (DE-XRT) technology and high-resolution RGB (HR-RGB) VIS imaging, combined with proprietary deep learning AI algorithms, to perform real-time scanning of wood waste and jointly calibrate wood density, dual-energy ratio (DER), characteristic absorption rate, and surface features. Working in conjunction with high-performance air ejectors, the system efficiently recovers specific wood fractions and achieves high-precision removal of impurities within milliseconds.

Empowered by AI-driven surface feature recognition algorithms, the system can conduct deep learning training based on real production data, continuously optimizing the machine vision detection accuracy. This means the equipment’s performance is not fixed at the time of factory shipment; instead, it continuously adjusts and improves with the accumulation of production data, delivering stable and reliable sorting performance to help wood recyclers significantly improve recovery rates of each quality grade, eliminate hidden impurities, consistently deliver clean, high-purity wood products, effectively protect downstream equipment, significantly enhance recycling efficiency, and command a premium in the market.

Two X-ray Energy Levels:

Low-Energy X-Ray (20-50 keV)

High-Energy X-Ray (80-150 keV)

Softwood

✦ DER 1.1-1.3

✦ Density 0.35-0.55 g/cm³

Hardwood

✦ DER 1.5-1.8

✦ Density 0.65-1.05 g/cm³

MDF (Medium-Density Fiberboard)

✦ DER 1.2-1.6

✦ Density 0.65-0.80 g/cm³

Contaminants

✦ DER > 2.0

Technical Features

● Deep Fusion of Dual-Energy X-ray Transmission and High-Resolution RGB VIS Imaging

Achieves efficient wood quality grading and contaminant removal by measuring density differences, dual-energy ratio (DER), characteristic absorption rate, and surface features.

● Proprietary AI Deep Learning Algorithms

Trained against comprehensive identification and sorting standards, the system uses deep learning to replicate the surface-feature judgment logic of manual picking. The AI model can be continuously optimized with new production data, driving ongoing improvements in sorting accuracy.

● High-Performance Air Ejector 

Equipped with in-house, high-power, high-speed air ejectors, the system delivers high-precision material rejection and ensures long-term stable operation even under high-throughput sorting conditions.

● Multi-Specification Model Portfolio

Available in two models with belt widths of 1300 mm and 2000 mm, to meet varying throughput requirements.

Typical Application Scenarios

● Wood Waste Recycling Facilities

Performs material classification and contaminant removal on mixed wood waste cullet, enhancing the purity and stability of recycled wood fractions.

● Construction & Demolition (C&D) Wood Processing

Sorts demolition wood, waste timber, wood pallets, and other cullet, separating wood fractions from foreign objects such as metals and stones.

● Biomass Fuel Preparation

Separates combustible wood fractions from high-contaminant materials, improving the consistency of fuel feedstock and subsequent utilization efficiency.

● Engineered Wood & Panel Material Recycling

Classifies softwood, hardwood, MDF, and other components, providing relatively stable feed conditions for downstream panel production, fuel processing, or recycled wood material applications.

Specifications

Specifications are approximate and subject to change without notice. Lauffer Vision reserves all rights for modifications.