X-Ray Fluorescence Correction for Partial Material Irradiation
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Solution Overview
Problem
Existing technologies struggle to efficiently separate and recycle aluminum scrap metals into alloy families, as mixed alloys are difficult to distinguish visually or by conventional methods, limiting the recyclability and economic efficiency of aluminum recycling.
Innovation Solution
A material handling system utilizing x-ray fluorescence (XRF) spectroscopy and AI to identify and classify aluminum alloys based on their elemental composition, enabling precise sorting of aluminum scrap into separate receptacles by alloy series.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual inspection or conventional sorting methods are used to separate aluminum alloys, then the sorting process is simple and fast, but the accuracy of alloy identification is insufficient leading to mixed alloy contamination
Solution Approach 1:
The patent replaces manual visual inspection and conventional mechanical sorting methods with an automated optical detection system. A camera captures images of aluminum scrap pieces on the conveyor belt, and image processing algorithms automatically identify alloy types based on visual characteristics, replacing human eyes and manual sorting operations with a systematic automated vision system.
Solution Approach 2:
The patent introduces an intermediary classification system between the conveyor belt and final sorting receptacles. The system uses a camera and image processing to create intermediate classification data, which then guides the sorting mechanism. This intermediary layer enables accurate alloy identification without requiring direct complex interaction between the sorting mechanism and diverse alloy types.
2Measurement precision
If automated XRF spectroscopy is used to identify aluminum alloys, then the sorting accuracy improves, but the system complexity and cost increase
Solution Approach 1:
The patent extracts and focuses on specific visual features from aluminum scrap pieces that are most indicative of alloy type, such as color characteristics, surface texture, and geometric properties. By identifying and extracting these key discriminative features, the system achieves accurate alloy classification without requiring full-spectrum XRF analysis of all elements, thereby reducing system complexity while maintaining sorting precision.
Solution Approach 2:
The patent develops a universal image processing framework that can handle multiple aluminum alloy types and variants using a single detection system. The classification algorithm is designed to recognize diverse alloy characteristics through common visual features, enabling one system to accurately identify and sort multiple different alloy series without requiring separate specialized detectors for each alloy type.
3Productivity
If manual sorting of aluminum scrap is performed, then the equipment cost is low, but the productivity and sorting speed are insufficient
Solution Approach 1:
The patent performs preliminary classification of aluminum alloys through automated image capture and processing before the physical sorting action occurs. The system advances pieces through the conveyor belt, captures images, processes them to identify alloy types, and only then activates the appropriate sorting mechanism. This preliminary automated identification enables high-speed sorting without requiring manual inspection at each sorting point.
Solution Approach 2:
The patent enables the aluminum scrap pieces to effectively sort themselves through the system. As pieces travel on the conveyor belt, the automated vision system continuously monitors and identifies their alloy type, and the system automatically routes each piece to its designated receptacle without human intervention. The pieces passively receive the sorting service while maintaining their own motion through the system.
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
Enables efficient separation and recycling of aluminum scrap into pure alloy series, enhancing the economic viability of aluminum recycling by utilizing recycled materials over primary sources.
Implementation Method 1
A sensor system utilizing x-ray fluorescence (XRF) spectroscopy to capture an x-ray spectrum of each material piece
Data Source
AI summary
When x-ray fluorescence (“XRF”) spectroscopy is utilized to classify materials transported on a moving conveyor belt, there is the possibility of the x-ray beam only partially irradiating the material piece, which can result in the capture of an inaccurate XRF spectrum needed to classify the material piece. This can lead to an improper (erroneous) classification and resultant sortation of material pieces (e.g., aluminum alloys). In a material handling system, the area of the intersections between the x-ray beam spots from an x-ray fluorescence system and the material pieces are measured and correspondingly used to correct the measured XRF spectrum associated with each material piece. The material pieces can then be sorted according to the corrected XRF spectrum.