Quantification of surface sensor representivity of primary crushed ore for bulk ore sorting

- Organization:
- The Australasian Institute of Mining and Metallurgy
- Pages:
- 12
- File Size:
- 995 KB
- Publication Date:
- Nov 10, 2020
Abstract
There are two fundamental methods for metalliferous sensing of primary crushed ore available for
deployment at operations. These methods can be classed as surface measurement techniques
(including XRF, LIBS, NIR, SWIR) or penetrative/semi-penetrative measurement techniques
(including PGNAA, PFTNA, GAA, MR). While the individual sensing technologies exploit different
physical phenomena to measure metal content, penetrative sensor measurements of grade are often
regarded to be superior to surface measurement techniques due to the much larger sampling volume
penetrative techniques provide.
Surface sensing techniques often utilise simpler, established technologies that have considerable
benefits in the speed of analysis, capital costs, ease of deployment, social license to operate and
operational safety.
This paper investigates whether surface sensing techniques achieve adequate sampling
representativity of primary crushed rock mass to provide economic benefit over penetrative sensing
technologies for bulk ore sorting applications.
The paper details the methodology used to assess whether surface XRF measurements change
throughout various stages of comminution, and increased surface exposure, from primary crushed
ore (top size of -175mm) to finely crushed product for assay (top size -2mm). The methodology was
applied to 2 ore mineralisation styles, across variable metals and grades, to identify any associated
opportunities and limitations to surface sensing techniques.
The results assist in developing a method to determine if surface sensing and measuring via XRF is
an adequate representation of the rock mass for bulk ore sorting applications and identify any
associated limitations in particle size distribution, mineralisation or natural deportment strength to
guide suitable application of surface sensing techniques.
Citation
APA:
(2020) Quantification of surface sensor representivity of primary crushed ore for bulk ore sortingMLA: Quantification of surface sensor representivity of primary crushed ore for bulk ore sorting. The Australasian Institute of Mining and Metallurgy, 2020.