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Optimization of Sensor Placement for a Measurement System for the Determination of Local Magnetic Material Properties

Author

Listed:
  • Alice Reinbacher-Köstinger

    (Institute of Fundamentals and Theory in Electrical Engineering, Graz University of Technology, Inffeldgasse 18, 8010 Graz, Austria)

  • Andreas Gschwentner

    (Institute of Fundamentals and Theory in Electrical Engineering, Graz University of Technology, Inffeldgasse 18, 8010 Graz, Austria)

  • Eniz Mušeljić

    (Institute of Fundamentals and Theory in Electrical Engineering, Graz University of Technology, Inffeldgasse 18, 8010 Graz, Austria)

  • Manfred Kaltenbacher

    (Institute of Fundamentals and Theory in Electrical Engineering, Graz University of Technology, Inffeldgasse 18, 8010 Graz, Austria)

Abstract

The aim of this work is to optimize the sensor positions of a sensor–actuator measurement system for identifying local variations in the magnetic permeability of cut steel sheets. Before solving the actual identification problem, i.e., finding the material distribution, the sensor placement of the measurement setup should be improved in order to reduce the uncertainty of the identification of the material distribution. The Fisher information matrix (FIM), which allows one to quantify the amount of information that the measurements carry about the unknown parameters, is used as the main metric for the objective function of this design optimization. The forward problem is solved by the finite element method. The results show that the proposed method is able to find optimal sensor positions as well as the minimum number of sensors to achieve a desired maximum parameter uncertainty.

Suggested Citation

  • Alice Reinbacher-Köstinger & Andreas Gschwentner & Eniz Mušeljić & Manfred Kaltenbacher, 2024. "Optimization of Sensor Placement for a Measurement System for the Determination of Local Magnetic Material Properties," Mathematics, MDPI, vol. 12(14), pages 1-15, July.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:14:p:2220-:d:1436236
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    References listed on IDEAS

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    1. Jung, Yongsu & Lee, Ikjin, 2021. "Optimal design of experiments for optimization-based model calibration using Fisher information matrix," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
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