Open Collections

Zhang, Yi Ran

University of British Columbia

Dual Energy X-ray Transmission (DE-XRT) technology has been widely used for hard rock ore sorting as well as for coal beneficiation purposes. Although there is an abundance of publications on research conducted using the DE-XRT system, there is a very limited number of publications discussing how the results are generated from the raw X-ray signal responses. Since the relative density values generated from the raw X-ray images could potentially alter the final DE-XRT result, it is important to study the image processing methods used to produce the relative density from raw X-ray images. In this thesis, the two known methodologies, the single curve method and dual material decomposition method (the name is used interchangeably with “dual curve method” in this study) were discussed and compared in two studies: a sulphide classification and sortability study (case 1) and a coal washability study (case 2). This thesis also attempts to use a more mathematical approach that takes into account all pixel values of the studied samples. In both case studies, the calibration curves used in single and dual curve methods are generated by evaluating the high and low pixel intensities on the H-L graph. The two sets of relative density results generated from the single curve and dual curve method are used to compare with the equivalent gold assay grades to classify rocks and perform sortability analysis in case 1. In case 2 they are used to compare with ash content and specific gravity (S.G.) plots to develop washability correlations. The results for case 1 show nearly identical performance on sulphide classification and sortability studies between the single curve and dual curve methods with the dual curve method slightly outperforming the single curve method. However, the DE-XRT results generated from both methods were not able to perform effectively “equivalent gold-grade” prediction. In case 2, although the dual material decomposition method outperformed the single curve method on all washability-related analyses, both methods were relatively effective at predicting ash content and S.G. and then could be effectively used for the prediction of washability curves.

Text; Still Image

2023-04-24

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/84457

Mining Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/