Multi-Energy X-Ray Material Identification Calibration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for identifying materials using x or gamma rays in luggage inspection are not reliable, especially when measurements are done quickly, due to high uncertainty from short signal acquisitions, and struggle to differentiate between materials based on attenuation coefficients.
Innovation Solution
A calibration method that determines discrete measurable values for attenuation coefficients, calculates probability densities, and interpolates statistical parameters to identify the nature and thickness of materials, using spectrometric detectors to measure transmission or attenuation coefficients in specific energy bands, allowing for rapid and accurate material identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If short measurement times are used to increase inspection speed, then productivity is improved, but measurement precision deteriorates due to high uncertainty from short signal acquisitions
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing probability density functions for multiple materials during an offline calibration phase. These pre-computed statistical models enable rapid online identification without requiring long measurement times, thus maintaining both high inspection speed and accurate material identification even with short signal acquisitions
Solution Approach 2:
The patent transitions from direct coefficient comparison in one dimension to a multi-dimensional probability density space. By evaluating how well measured coefficients match pre-stored probability distributions across multiple dimensions, the system achieves robust material identification with limited measurement data, resolving the contradiction between speed and precision
2Device complexity
If simple attenuation coefficient comparison is used to identify materials, then device complexity is reduced, but reliability deteriorates when measurements are done quickly
Solution Approach 1:
The patent changes the identification approach from direct deterministic coefficient comparison to a probabilistic framework using pre-computed density functions. This parameter transformation enables reliable material identification under rapid measurement conditions while maintaining manageable system complexity through offline pre-processing
Solution Approach 2:
The system performs preliminary calibration offline to generate and store probability density functions for various materials. This advance preparation creates a reference library that enables reliable online identification without requiring complex real-time computations, thus improving reliability for quick measurements without significantly 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 method provides reliable and quick material identification, capable of distinguishing between materials with high accuracy even under short measurement times, enhancing the efficiency of luggage inspection processes.
Implementation Method 1
measuring, for this material, transmission or attenuation coefficients of an x radiation... determined from a comparison between a measurement of the radiation transmitted by the object and a measurement of the radiation without the object being inserted between the radiation source and the detector
Data Source
Figure 1A~1B
Figure 2
Figure 3~4
AI summary
A calibration method is disclosed, for a device for identifying materials using X-rays, including: a) determining at least one calibration material and, for each calibration material, at least one calibration thickness of this material, b) measuring, for each of the calibration materials and for each of the selected calibration thicknesses, attenuation or transmission coefficients for X radiation, c) calculating statistical parameters from said coefficients, d) determining or calculating, for each calibration material and for each calibration thickness, a presence probability distribution law, as a function of said statistical parameters.