A novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors

Area of Science:

• Materials Science
• Analytical Chemistry
• Mining Engineering

Background:

• Gangue content in coal reduces combustion calorific value, necessitating complete separation for practical applications.
• Existing pseudo-dual-energy X-ray methods lack the required sorting accuracy for efficient gangue removal.

Purpose of the Study:

• To develop a novel multi-dimensional X-ray sorting algorithm for improved coal and gangue separation.
• To address the limitations of current X-ray sorting techniques using CdZnTe photon counting detectors.

Main Methods:

• The proposed algorithm involves five steps: preferred energy binning, transmittance sorting, and iterative R-value sorting (1D, 2D, 3D).
• Algorithm parameters were determined using 65 coal and gangue samples, with experimental validation on 110 additional samples.

Main Results:

• The novel multi-dimensional algorithm achieved a sorting accuracy of 99%.
• This represents a substantial improvement over the 60% accuracy of the pseudo-dual-energy X-ray method.

Conclusions:

• The developed algorithm demonstrates superior performance and practical feasibility for coal and gangue sorting.
• This photon counting detector-based approach can inform other two-substance X-ray sorting applications.