Wood Processing Line Machine Vision for Stone and Plastic Detection
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Solution Overview
Problem
Existing wood processing lines struggle to effectively detect and remove non-magnetic harmful objects like stones and plastic from trees, which can cause damage to chipper blades and quality deviations in the end product, as conventional methods such as metal detectors and digital image processing are inadequate.
Innovation Solution
A method and system utilizing machine vision with software means to automatically detect harmful objects on a conveyor by illuminating trees with indirect lighting, recording images with cameras, and recognizing hues, gradients, and three-dimensional information to identify and remove stones or plastic using neural networks and pattern recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a metal detector is used to detect harmful objects, then magnetic objects can be detected, but non-magnetic harmful objects like stones and plastic cannot be detected
Solution Approach 1:
The patent replaces the mechanical/magnetic detection system (metal detector) with an optical detection system (camera-based machine vision). The camera captures images of trees on the conveyor, and software algorithms analyze these images to detect harmful objects regardless of their magnetic properties, thus expanding detection capability to include stones, plastic, and other non-magnetic materials.
Solution Approach 2:
The patent changes the detection parameter from magnetic properties (detected by metal detectors) to optical properties (detected by cameras). By analyzing color, shape, size, and texture parameters in images, the system can identify harmful objects based on their visual characteristics rather than magnetic characteristics, enabling detection of a broader range of materials.
2Illumination intensity
If direct lighting is used to illuminate trees on the conveyor, then the area is well-lit for detection, but reflections and shadows interfere with image quality
Solution Approach 1:
The patent employs asymmetric lighting arrangements with multiple light sources positioned at different angles and heights. This asymmetric configuration ensures that no single reflection or shadow can dominate the entire image, and the overlapping light paths create uniform illumination that minimizes harsh contrasts and improves image quality for harmful object detection.
Solution Approach 2:
The patent uses multiple lighting devices that provide more illumination than strictly necessary, ensuring that even areas with potential reflections or shadows receive sufficient light. This excessive lighting approach compensates for the negative effects of reflections and shadows by ensuring adequate illumination across the entire conveyor area.
3Ease of operation
If manual monitoring is used to detect harmful objects, then operational simplicity is maintained, but detection reliability and productivity are reduced
Solution Approach 1:
The patent implements a self-monitoring system where the machine vision setup automatically detects harmful objects without requiring continuous manual inspection. The camera captures images and the embedded software automatically analyzes them to identify harmful objects, providing reliable detection while freeing operators from tedious manual monitoring tasks.
Solution Approach 2:
The patent replaces manual visual inspection with an automated optical detection system. The camera-based machine vision system continuously monitors the conveyor, providing reliable and consistent detection of harmful objects without the variability and fatigue associated with human operators, thereby improving both reliability and productivity.
4Reliability
If a trap is used to remove harmful objects, then objects smaller than the debarking drum openings can be removed, but objects that float on tree bundles or pass by the trap cannot be removed
Solution Approach 1:
The patent performs preliminary detection of harmful objects using the machine vision system before they reach problematic positions on the conveyor or escape the trap. By detecting objects early in the process, the system can alert operators or automatically stop the conveyor to prevent harmful objects from floating on tree bundles or passing by the trap unnoticed.
Solution Approach 2:
The patent implements a feedback mechanism where the machine vision system continuously monitors the conveyor and provides real-time information about detected harmful objects. This feedback allows for immediate corrective action, such as stopping the conveyor or alerting operators, ensuring that harmful objects are removed even when the trap mechanism alone is insufficient.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Ensures reliable detection and removal of harmful objects before they reach the chipper, preventing damage and quality deviations, while reducing the need for manual monitoring and minimizing reflections and shadows with ambient light covers.
Implementation Method 1
trees on the conveyor are illuminated with a lighting device using indirect lighting on a section of the conveyor covered with ambient light covers
Implementation Method 2
trees are recorded on the conveyor after the debarking drum using at least one camera as detection means for creating images
Data Source
AI summary
Processing trees using machine vision with a software, whereintrees are debarked with a debarking drum (12),harmful objects smaller than a selected dimension are removeddebarked trees are routed from the debarking drum over a trap,trees on a conveyor are illuminated,trees are recorded on the conveyor using at least one camera,a harmful object is automatically detected utilising machine vision by recognising hue information or gradients as elements from the image, registering the elements to the field of view, determining element distances in the field of view thus creating three-dimensional information, recognising patterns with the help of registered elements and three-dimensional information, and recognizing stones or plastic as harmful objects, with a criterion preselected with the help of patterns,the conveyor is automatically stopped,the harmful object is removed,trees are moved using the conveyor.