Selective recovery of metallic scraps using electromagnetic tensor spectroscopy

Noushin Karimian, Michael O'Toole, Anthony Peyton

Research output: Contribution to conferencePaperpeer-review

Abstract

Automobile use continues to show significant increase year on year, with well over 1 billion vehicles now in use globally according to OICA figures. As a result, the recycling of end-of-life vehicles (ELV) has become a major concern, with legislative ELV recycling systems in place in many countries. In the EU for instance, ELV generate approaching 10 million tonnes of waste per year and around 75% of this is currently recycled or recovered, but this percentage falls well short of the 95% target for 2015 set by the ELV European directive. Automobile shredding residue (ASR) includes heavy metals as well as a mass of unclassified fine particles. The non-ferrous metal fraction in ELV scrap contains several metals/alloys; primarily aluminium, copper and brass, whose recovery is important for environmental, economic and resource conservation reasons. The separation of non-ferrous metals from ASR scrap is technically complex and existing technologies suffer from poor cost effectiveness. This paper present a new method for sorting of non-ferritic metallic scrap using electromagnetic tensor spectroscopy. The method combines a vision system, with a novel electromagnetic array to determine the electrical conductivity of each metal piece. The pieces can then be sorted based on conductivity into metal type. Crucial to this process is a fast metal identification algorithm, which allows the line to be operated at conveyor speeds of several m/s and which linearly scales in complexity with conveyor belt width. This study reports that the metal identification algorithms perform adequately when processing machined metal test samples with a wide range of shapes, without the use of any vision information. The challenge is to cope with the diverse range pieces in terms of shape and morphology. In doing so, a A1/4-scale EMTS system has been developed to prove the principle of the technique.

Original languageEnglish
Publication statusPublished - 1 Jan 2017
Event56th Annual Conference of the British Institute of Non-Destructive Testing, NDT 2017 - Telford, United Kingdom
Duration: 5 Sept 20177 Sept 2017

Conference

Conference56th Annual Conference of the British Institute of Non-Destructive Testing, NDT 2017
Country/TerritoryUnited Kingdom
CityTelford
Period5/09/177/09/17

Keywords

  • Automobile shredding residue (ASR)
  • Electrical conductivity
  • Electromagnetic array
  • Electromagnetic tensor spectroscopy (EMTS)
  • End-of-life vehicles (ELV)
  • Metal identification algorithm
  • Metallic scraps
  • Vision system

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  • Electromagnetic Sensing Group

    Peyton, A. (PI), Fletcher, A. (Researcher), Daniels, D. (CoI), Conniffe, D. (PGR student), Podd, F. (PI), Davidson, J. (Researcher), Anderson, J. (Support team), Wilson, J. (Researcher), Marsh, L. (PI), O'Toole, M. (PI), Watson, S. (PGR student), Yin, W. (PI), Regan, A. (PGR student), Williams, K. (Researcher), Rana, S. (Researcher), Khalil, K. (PGR student), Hills, D. (PGR student), Whyte, C. (PGR student), Wang, C. (PGR student), Hodgskin-Brown, R. (PGR student), Dadkhahtehrani, F. (PGR student), Forster, S. (PGR student), Zhu, F. (PGR student), Yu, K. (PGR student), Xiong, L. (PGR student), Lu, T. (PGR student), Zhang, L. (PGR student), Lyu, R. (PGR student), Zhu, R. (PGR student), She, S. (PGR student), Meng, T. (PGR student), Pang, X. (PGR student), Zheng, X. (PGR student), Bai, X. (PGR student), Zou, X. (PGR student), Ding, Y. (PGR student), Shao, Y. (PGR student), Xia, Z. (PGR student), Zhang, Z. (PGR student), Khangerey, R. (PGR student) & Lawless, B. (Researcher)

    1/10/04 → …

    Project: Research

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