Embedded Fastener Detection and Removal in Recycled Wood
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Solution Overview
Problem
Existing systems are inefficient in autonomously removing embedded fasteners from recycled wood products, particularly distinguishing and extracting threaded and non-threaded fasteners, which hinders effective recycling processes.
Innovation Solution
A system comprising an X-ray scan module, optical sensor, and fastener extractor modules, including non-threaded and threaded fastener extractors, autonomously detects and removes fasteners by generating a virtual model, identifying fastener positions and orientations, and executing precise extraction schedules using multi-axis stages and actuators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual fastener removal methods are used, then operational flexibility is maintained, but productivity is low and labor costs are high
Solution Approach 1:
The system segments the fastener removal process into distinct functional modules: X-ray scanning module for detection, optical sensing module for verification, virtual model generation, and extraction modules for execution. This segmentation enables automated high-speed processing while maintaining manageable system complexity through modular design.
Solution Approach 2:
The patent replaces manual mechanical fastener removal with an automated system combining X-ray imaging, computer vision, and robotic extraction mechanisms. This substitution dramatically increases productivity by eliminating manual labor while the modular architecture keeps device complexity manageable.
2Productivity
If automated fastener detection systems are implemented, then productivity increases, but measurement precision is required to distinguish fastener types
Solution Approach 1:
The detection system is segmented into two specialized modules: an X-ray scanning module that provides internal structural information for fastener detection, and an optical sensing module that captures surface visual characteristics. This segmentation allows each module to optimize for its specific function, achieving both high detection speed and precise fastener type identification.
Solution Approach 2:
The patent introduces a virtual model generation step that acts as an intermediary between raw sensor data and fastener identification. The system compiles X-ray and optical scan data into a virtual model, which then enables accurate differentiation between threaded and non-threaded fasteners while maintaining high detection speed through automated image processing.
3Measurement precision
If comprehensive scanning is performed on all wood products, then measurement precision improves, but loss of time increases due to processing duration
Solution Approach 1:
The system performs preliminary comprehensive scanning using X-ray and optical sensors to create complete virtual models of all wood products before extraction operations begin. This preliminary action ensures no fastener is missed, achieving maximum detection precision while the subsequent extraction process operates efficiently on pre-identified targets, minimizing overall processing time.
Solution Approach 2:
The patent implements continuous scanning and processing operations where the conveyor system moves wood products through the scanning zone without interruption. Multiple sensors operate simultaneously and continuously, compiling data in real-time to generate virtual models on-the-fly, thereby maintaining measurement precision while minimizing time loss through uninterrupted processing.
4Manufacturing precision
If specialized extraction modules for different fastener types are used, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The extraction system is segmented into specialized modules: a non-threaded fastener extractor module with gripping mechanisms for nails and staples, and a threaded fastener extractor module with rotational extraction mechanisms for screws. This segmentation enables each module to achieve high extraction accuracy for its specific fastener type while the modular design manages overall device complexity through standardized interfaces and control integration.
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
The system effectively distinguishes and removes various types of fasteners from recycled wood, enhancing the recyclability of wood products by accurately identifying and extracting embedded fasteners, thereby improving the efficiency and quality of the recycling process.
Implementation Method 1
an X-ray scan module (112)... configured to receive a recycled wood workpiece (115)... and includes an X-ray sensor facing the scan volume
Data Source
AI summary
A method includes: receiving a recycled wood workpiece populated with a set of metal fasteners; accessing an internal imaging scan; detecting the set of metal fasteners embedded in the recycled wood workpiece based on internal features detected in the internal imaging scan; for each metal fastener in the set of metal fasteners, extracting an initial position and an initial orientation of the metal fastener from the internal imaging scan; generating a virtual model of the recycled wood workpiece based on the internal imaging scan; accessing an image captured by an optical sensor; detecting a first metal fastener in the recycled wood workpiece; deriving a first position and a first orientation of the first metal fastener; and, in response to identifying the first metal fastener analogous to an initial metal fastener in the virtual model, isolating the first metal fastener in the virtual model and generating a fastener removal schedule.