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Requirement-Adapted Enhancement of a Faraday Rotation Magnetometer’s Output

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

Magnetic microstructures are a useful tool to encode information. In order to repeatedly make use of this information a non-destructive measurement system is needed. Such a system would be applicable to many technical problems, however, within this contribution we discuss a method to analyse the magnetic pattern of the security thread used in banknotes specifically. In order to assess the quality of the threads’ magnetic patterns during their production, a previous study used a Faraday Rotation Magnetometer (FRM). An FRM is a magneto-optical – and therefore non-destructive and non-contacting – setup based on the Faraday effect, which correlates the strength of a magnetic field with the rotation of polarised light. Albeit meeting the required specifications, this FRM’s amplitude resolution wasn’t sufficient to allow meaningful quantitative measurements. Hence, within this contribution we discuss the suitability and scope of an FRM for quantitative measurements of magnetic microstructures. We present a generalised version of the previous FRM and characterise it with regard to its amplitude, spatial, and temporal resolution. We point out ways to enhance the signal and show the limitations of such measures separately as well as comprehensively. From this we derive a way to estimate the feasibility of an FRM as a quantitative measurement device for a given set of parameters. Furthermore, this contribution may be used as a build and signal enhancement guideline for a similar setup.
OriginalspracheEnglisch
TitelComputer Aided Systems Theory – EUROCAST 2019 - Revised Selected Papers, Part II
Herausgeber*innenRoberto Moreno-Díaz, Alexis Quesada-Arencibia, Franz Pichler
VerlagSpringer
Seiten52 – 58
Seitenumfang7
ISBN (elektronisch)978-3-030-45096-0
ISBN (Print)9783030450953
DOIs
PublikationsstatusVeröffentlicht - Mai 2020

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band12014 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Wissenschaftszweige

  • 202012 Elektrische Messtechnik
  • 202014 Elektromagnetismus
  • 202036 Sensorik
  • 202 Elektrotechnik, Elektronik, Informationstechnik
  • 202016 Elektrotechnik
  • 202027 Mechatronik
  • 202037 Signalverarbeitung
  • 103021 Optik

JKU-Schwerpunkte

  • Digital Transformation

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