X-ray Baggage Scanner Crystallinity Analysis for Material Discrimination
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Solution Overview
Problem
Existing x-ray baggage scanners, including CT systems, fail to effectively discriminate between harmless materials and threat materials like plastic explosives due to limited confidence in identifying crystalline substances, leading to a high false alarm rate.
Innovation Solution
A processor is configured to determine the crystallinity of a substance by analyzing the histogram of detected x-ray photons and applying either a first or second process based on the crystallinity threshold, which includes determining the interplanar atomic d-spacing or effective atomic number and generating an independent atom model to improve material identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If XRD identification systems are used to measure d-spacings between lattice planes, then material discrimination is improved compared to conventional x-ray scanners, but identification confidence remains limited leading to false alarms
Solution Approach 1:
The patent changes the measurement parameter from d-spacing alone to a combination of d-spacing and peak intensity ratios. By incorporating peak intensity ratios (I2/I1) as an additional parameter, the system achieves more reliable substance identification while reducing false alarms. This parameter expansion allows differentiation between substances with similar d-spacings but different crystalline structures.
Solution Approach 2:
The patent creates a composite identification approach by combining multiple measurement parameters (d-spacing values and peak intensity ratios) into a unified identification system. This composite methodology integrates information from multiple diffraction peaks to form a more robust identification criterion, thereby improving both precision and reliability simultaneously.
2Device complexity
If conventional x-ray baggage scanners are used, then the system is simple and widely deployed, but they cannot discriminate between harmless materials and threat materials like plastic explosives
Solution Approach 1:
The patent applies partial action by implementing a simplified version of full XRD analysis. Instead of measuring complete diffraction patterns and performing complex phase identification, the system focuses on measuring specific d-spacing values and peak intensity ratios at predetermined positions. This partial measurement approach maintains device simplicity while achieving sufficient discrimination capability for security screening.
Solution Approach 2:
The patent enhances the functionality of conventional x-ray scanners by adding crystallinity analysis capabilities. The same x-ray detection hardware that captures transmission images is also used to measure diffraction peak positions and intensities, enabling the system to perform both imaging and material identification functions with a single device.
3Ease of operation
If d-spacing measurement alone is used to identify crystalline materials, then the identification process is straightforward, but false alarm rate increases due to limited confidence
Solution Approach 1:
The patent implements feedback by using peak intensity ratios to verify and confirm initial d-spacing-based identifications. The system first measures d-spacing to identify potential substances, then uses peak intensity ratios as a feedback mechanism to confirm or reject these identifications. This feedback loop significantly reduces false alarms while maintaining operational simplicity.
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 solution enhances the discrimination of materials, reducing false alarms by accurately identifying substances based on their crystallinity, thereby improving the effectiveness of explosive detection in baggage scanning.
Implementation Method 1
Whenever x-rays encounter a crystalline material, a plurality of regularly spaced atoms of the crystalline material diffract some of the x-rays to generate a diffraction pattern. The diffraction pattern is indicative of a crystal structure of the crystalline material
Implementation Method 2
The processor is configured to determine a histogram of detected x-ray photons versus a momentum transfer x of the x-ray photons of the substance
Data Source
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AI summary
A processor (190) configured to identify a substance (42) is provided. The processor is further configured to determine a diffraction profile of the substance, determine (403) the crystallinity based on the diffraction profile, and identify the substance based on the crystallinity of the substance.