A Broadband Frequency-to-Voltage Converter for Sinusoidal Signals Based on Filters Design

Anas S. Mohammed, Yaqub Mahnashi

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

3 Scopus citations

Abstract

The frequency-to-voltage converter is a versatile circuit that translates variations in frequency to a corresponding voltage level. However, converting high-frequency signals into a DC output voltage has been a challenging task. This paper proposes a new, yet simple, approach for converting the frequency into a DC output voltage of sinusoidal signals. The frequency-to-voltage conversion is achieved by utilizing the attenuation band of a filter. The paper provides a clear mathematical model and a relation between frequency and DC output voltage levels, with merely passive components for efficient power consumption. This technique is implemented to achieve wide frequency spectrum conversion that could extend to tens of MHz and beyond. The proposed scheme is verified experimentally in both low-frequency range, varying in sub-kilohertz, and as high as 40MHz.

Original languageEnglish
Title of host publicationProceedings - 2023 10th International Conference on Electrical and Electronics Engineering, ICEEE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages85-89
Number of pages5
ISBN (Electronic)9798350304299
DOIs
StatePublished - 2023
Event10th International Conference on Electrical and Electronics Engineering, ICEEE 2023 - Istanbul, Turkey
Duration: 8 May 202310 May 2023

Publication series

NameProceedings - 2023 10th International Conference on Electrical and Electronics Engineering, ICEEE 2023

Conference

Conference10th International Conference on Electrical and Electronics Engineering, ICEEE 2023
Country/TerritoryTurkey
CityIstanbul
Period8/05/2310/05/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Frequency-to-voltage converter (FVC)
  • RLC network
  • broad-band frequency-to-voltage converter
  • filter design

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Instrumentation
  • Artificial Intelligence
  • Computer Science Applications
  • Signal Processing

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