SciELO - Scientific Electronic Library Online

 
vol.110 issue6Principles of an image-based algorithm for the quantification of dependencies between particle selections in sampling studies author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

Related links

  • On index processCited by Google
  • On index processSimilars in Google

Share


Journal of the Southern African Institute of Mining and Metallurgy

On-line version ISSN 2411-9717
Print version ISSN 2225-6253

J. S. Afr. Inst. Min. Metall. vol.110 n.6 Johannesburg Jun. 2010

 

JOURNAL PAPER

 

Summary of results of ACARP project on cross-belt cutters

 

 

G.K. Robinson; M.D. Sinnott; P.W. Cleary

CSIRO Mathematics, Informatics and Statistics, Victoria, Australia

 

 


SYNOPSIS

A project was funded by the Australian coal industry to investigate the mechanisms that might lead to sample bias when using crossbelt cutters, in order to help coal industry personnel to make better decisions about the purchase, maintenance, and operation. It concentrated on DEM modelling of skew cutters. These are set at an angle to the belt with the intention of minimizing disturbance to the non-sampled material.
Two bias mechanisms are likely to cause bias for cross-belt cutters. Waves of material are bulldozed off the belt by the upstream side of the body of square cutters and material is thrown by the leading edges of cutter blades for all types of cross-belt cutters. These mechanisms cause some parts of the load of material on a belt to be over-represented.
The effects of these mechanisms cannot be made to be negligible, so cross-belt samplers cannot be trusted to produce unbiased samples, especially for segregated streams of material. However, it is possible to give a bound on the maximum likely bias. The grades of two portions of the stream can be estimated by stopping the belt and shovelling off 1/3 of the cross-section of the load on the belt into a container, concentrating on the final side of the belt and the top of the load. The remaining material should be put into another container and the difference in grade determined.
The maximum likely bias is typically about 10% of this difference.
For a cross-belt cutter, having an extraction ratio near to 100% is not a reliable indication that the cutter has little or no bias. Some bias mechanisms affecting cross-belt sample cutters make sample mass too high and some make it too low, so an extraction ratio near 100% can occur if two bias mechanisms are both active.

Keywords: sampling, DEM simulation, sample bias, accuracy, precision


 

 

“Full text available only in PDF format”

 

 

References

CLEARY, P.W. Large scale industrial DEM modelling, Engineering Computations, vol. 21, 2004. pp. 169-204.         [ Links ]

CLEARY, P.W. and ROBINSON, G.K. Evaluation of cross-stream sample cutters using three-dimensional discrete element modelling. Chemical Engineering Science, vol. 63, 2008. pp. 2980-2993.         [ Links ]

GY, P.M. Sampling of Particulate Materials. Revised edition. Elsevier. 1982.         [ Links ]

LYMAN, G, HAWTHORNE, C., and OSBORNE, D. An optimised hammer sampler design. Third World Conference on Sampling and Blending. 2007.         [ Links ]

ROBINSON, G.K., SINNOTT, M., and CLEARY, P.W. Do Cross-Belt Sample Cutters Really Need To Travel At 1.5 Times Belt Speed? World Conference on Sampling and Blending 3, J. Felipe and J.C. Koppe, (eds.) 2007. pp. 112-125, Porto Alegre, Brazil, 23-25th October.         [ Links ]

ROBINSON, G.K., SINNOTT, M., and CLEARY, P.W. Understanding bias for cross-belt cutter sampling of coal-ACARP Project C15072. CSIRO Report Number CMIS 2009/47. 2009.         [ Links ]

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License