Skip to main navigation Skip to search Skip to main content

Localization of Electrodes based on Resistance Measurements

  • Sabrina Affortunati (Speaker)
  • Zagar, B. (Speaker)

Activity: Talk or presentationContributed talkscience-to-science

Description

This paper considers the problem of the localization of electrodes in a distributed sensor system. Especially in impedance tomography the localization of the electrodes is of great importance, since deviations from nominal positions affect the result of the inverse problem. Conformal mapping allows to obtain analytical solutions of the resistances for complex geometries. By measuring the resistances between the electrodes, an estimation of the distance between each pair of electrodes is possible. In the case of non-adjacent electrodes this result is biased by the other electrodes. The mass-spring-relaxation algorithm offers a possibility of an error-tolerant localization by only using distances between neighboring electrodes. However, the robustness against attaining local minima depends on the initial guess of the arrangement. To overcome this, the classical multidimensional scaling algorithm was used to obtain an initial guess of the positions of all elements in the network. The combination of the two algorithms is analyzed. A verification on simulated results with cylindrical electrodes demonstrates the effectiveness of the approach.
Period25 May 2023
Event titleI2MTC 2023
Event typeConference
LocationMalaysiaShow on map

Fields of science

  • 202039 Theoretical electrical engineering
  • 202016 Electrical engineering
  • 202027 Mechatronics
  • 202015 Electronics
  • 202037 Signal processing
  • 202014 Electromagnetism
  • 202036 Sensor systems
  • 202024 Laser technology
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202012 Electrical measurement technology
  • 202022 Information technology
  • 202021 Industrial electronics
  • 103021 Optics
  • 203016 Measurement engineering
  • 211908 Energy research
  • 101014 Numerical mathematics
  • 102003 Image processing

JKU Focus areas

  • Digital Transformation