Inductive Sensor Array for Scrap Material Sorting
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Solution Overview
Problem
Current scrap metal sorting technologies face challenges in accurately classifying and sorting mixed scrap materials, particularly those with low mass, convoluted shapes, or coated with insulation, which often result in low signal detection and inefficient separation.
Innovation Solution
A system utilizing analog inductive proximity sensors arranged in arrays to detect and classify scrap materials based on conductivity, with a control unit processing analog signals to create a matrix representation of the conveyor belt, allowing for precise identification and sorting of metals and non-metals, including coated wires and mixed compositions, without the need for cleaning or washing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensors are used to detect scrap materials, then the system can operate with simpler hardware, but detection accuracy decreases for low mass, convoluted, or coated materials
Solution Approach 1:
The sensor array is divided into multiple independent sensor elements arranged in rows and columns, allowing each sensor to detect specific regions of the conveyor belt. This segmentation enables the system to handle complex detection tasks through coordinated operation of multiple simpler sensor units, improving overall detection accuracy without requiring a single overly complex sensor.
Solution Approach 2:
The patent introduces an intermediary processing system that receives signals from multiple sensors, creates a matrix representation of the conveyor belt, and identifies material properties through signal analysis. This intermediary layer enables accurate detection of low mass, convoluted, or coated materials by processing combined sensor data rather than relying on a single complex sensor.
2Productivity
If high-speed conveyor belts are used to increase processing throughput, then productivity improves, but the time available for detection and classification of each material piece decreases
Solution Approach 1:
The system performs preliminary detection and classification actions while materials are still on the conveyor belt at known positions. By predicting the future location of materials based on conveyor speed and current sensor readings, the system prepares classification decisions in advance, allowing high-speed operation without sacrificing accuracy.
Solution Approach 2:
The sensor array continuously scans the conveyor belt without interruption, and the control system continuously processes signals and updates the matrix representation. This continuous operation ensures that detection and classification actions occur without gaps, maintaining both high productivity and accurate classification even at high conveyor speeds.
3Measurement precision
If multiple sensor arrays are deployed to improve detection coverage, then measurement precision increases, but device complexity and cost increase
Solution Approach 1:
Multiple sensor elements are merged into a unified matrix representation that the control system processes as a single coherent data structure. This merging approach allows the system to leverage data from multiple sensors simultaneously, improving material identification accuracy while managing complexity through integrated processing rather than separate independent systems.
Solution Approach 2:
The sensor array and control system are designed with universal functionality to detect and classify various types of scrap materials (metals, plastics, coated materials, convoluted shapes) using the same hardware configuration. This multi-functionality reduces the need for specialized sensors for different material types, thereby improving identification accuracy across diverse materials without proportionally increasing device complexity.
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 achieves high-resolution sorting and classification of scrap materials, enabling efficient separation of metals and non-metals, including coated wires, with improved detection accuracy and reduced interference, allowing for effective reuse of sorted materials.
Implementation Method 1
A sensor array having a series of analog inductive proximity sensors with faces lying in a sensing plane
Data Source
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AI summary
A system has a conveyor for carrying at least two categories of scrap particles positioned at random on a surface of the conveyor, with at least some of the particles comprising metal. The system has a sensor array with a series of analog inductive proximity sensors arranged transversely across the conveyor. An active sensing end face of each sensor lies in a sensing plane, and the sensing plane is generally parallel with the surface of the conveyor. A control system of is configured to sample and quantize analog signals from the series of sensors in the array, and locate and classify a scrap particle on the conveyor passing over the array into one of at least two categories of material based on the quantized signals. A method for sorting the particles is also provided.