USNR introduces new veneer scanning system: NV4G

Published on March 14, 2024 Time: loading...

USNR recently brings their 4th generation veneer scanning system – NV4G. This innovation is capable to deliver and uses all the latest in machine vision technology coupled with deep learning AI. It also helps to create a paradigm shift in solution accuracy that achieves a new level of defect detection, making grading solutions more accurate and more profitable.

The utilization of specialized camera and lighting technology of NV4G significantly enhances the distinction between high-quality wood and its defects. The NV4g stands out in its ability to precisely identify various imperfections such as voids, splits, and closed defects across a wide variety of wood species. What sets the NV4g apart from its competitors is its unparalleled accuracy, consistency, and reliability in performing these tasks.

The NV4g offers users the flexibility to fine-tune clip solutions, aiming to maximize grade recovery or categorize clipped veneer based on its grade. This capability is supported by the system’s feature that allows for the customization of clipping algorithms, ensuring that clip parameters can be adjusted to accommodate various requirements such as trash, FT, random, small panel, and large panel scenarios. Furthermore, the option to merge defects or divide them (by clipping at the center of the defect) enables users to modify clipping algorithms to achieve an optimal balance of recovery, capacity, and product quality.

Benefits of deep learning AI

Increases the speed and accuracy of defect detection
Significantly reduces the time required for start-up and commissioning of auto-grading systems
Enables the accurate identification of defects unique to a species, region, or grade, that would otherwise be difficult and time-consuming to identify using conventional methods
Delivers more value and recovery through advanced optimization
Easier to use than a traditional neural net classifier

Industry Leading Technology

Defect & full sheet tracking resolution – 0.025 in.
Moisture Clip – Automatically adjusts clips for moisture content when interfaced to a green-end moisture meter
The NV4g combines moisture data with grade providing a true moisture sort and accurate clip adjustment based on moisture, i.e. knot density has a large effect on shrinkage in the dryer.
The comprehensive software package provides all production reporting: grade distribution, downtime, and specie run.
Also allows for “virtual” clipping using stored ribbon data and parameter setting changes enabling the user to optimize clipping strategy based on specific needs.
The NV4g provides the user the ability to fully integrate the system with USNR’s GEM (green veneer moisture meter), clipper controls and USNR’s multi-point diverter system (MPDS).

Apart from several unique features, the NV4G combines a color camera, true color LED light and neural network classification algorithms to accurately and reliably optimize green veneer clipping solutions, which enables the user to optimize defect clipping based on downstream processes, product requirements, and of course the grade.