Evaluation of the thin-skin approximation boundary element method for electromagnetic induction scattering problems

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    179 Downloads (Pure)


    A conductive object subject to an applied varying magnetic field will emit a secondary magnetic field or scattered field. The scattered field is dependent on the geometry of the object and its material properties (conductivity, permeability, etc). If we can calculate the scattered field for a given geometry (the scattering problem), we can infer the material properties from the detected electromagnetic response. Our motivation is the production of induction based classifiers for object and material classification. Applications include sorting of high value scrap metal and identifying UXO from clutter in landmine clearance. To this end, we require methods of solving the scattering problem quickly and accurately.

    In this paper, we evaluate the thin-skin approximation boundary element method. The method offers a particularly compact formulation of the scattering problem which is quick to solve.We compare this method to the more established finite element method. We find that larger objects at higher frequencies and conductivities appear to give good agreement between the two methods. However, the agreement breaks down for smaller objects even when the frequency or conductivity is relatively high for typical induction based sensing. This is especially true when the object has a complex geometry. This imposes limitations on the practical usefulness of this approach.

    Original languageEnglish
    Title of host publicationIEEE Sensors Applications Symposium (SAS), 2016
    Number of pages6
    ISBN (Electronic)978-1-4799-7250-0, 978-1-4799-7249-4
    Publication statusPublished - 20 Apr 2016


    Dive into the research topics of 'Evaluation of the thin-skin approximation boundary element method for electromagnetic induction scattering problems'. Together they form a unique fingerprint.
    • Electromagnetic Sensing Group

      Peyton, A., Fletcher, A., Daniels, D., Conniffe, D., Cheadle, E., Podd, F., Xu, H., Tesfalem, H., Davidson, J., Anderson, J., Tang, J., Hampton, J., Wilson, J., Barratt, K., Marsh, L., Chen, L., O'Toole, M., Lu, M., Ran, Q., Huang, R., Watson, S., Ozdeger, T., Van Verre, W., Yin, W., Gao, X., Tao, Y., Chen, Z., Regan, A., Li, J. & Cheng, Q.

      1/10/04 → …

      Project: Research

    Cite this