A Two-Channel DFT Spectrum Analyzer for Fluctuation Enhanced Sensing Based on a PC Audio Board.

low-frequency noise measurements signals elaboration sound boards spectrum analyzer

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
24 Jun 2021
Historique:
received: 09 06 2021
revised: 19 06 2021
accepted: 21 06 2021
entrez: 2 7 2021
pubmed: 3 7 2021
medline: 3 7 2021
Statut: epublish

Résumé

The main requirement for using the Fluctuation Enhanced Sensing technique is the ability to perform low-frequency noise measurements. The portability of the measurement system is also a quite desirable feature not limited to this specific application. In this paper, an approach for the realization of a dual channel spectrum analyzer that is capable of exploring frequencies down to DC, although based on a USB sound card, is proposed. The lower frequency range of the input signals, which is outside the frequency range of the sound board, is upconverted to higher frequencies by means of a very simple modulation board. Then, the entire spectrum is reconstructed numerically by proper elaboration. With the exception of the modulation board, the approach we propose does not rely on any specific hardware. Thanks to the efficiency of the spectra estimation and reconstruction software, which is based on a public domain library, the system can be built on a low-cost computer single board computer, such as the Raspberry PI3. Moreover, when equipped with an optical TCP/IP link, it behaves as a compact spectrum analyzer that along with the device under test can be placed into a shielded environment, thus being isolated from external electromagnetic interferences.

Identifiants

pubmed: 34202432
pii: s21134307
doi: 10.3390/s21134307
pmc: PMC8272233
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

Rev Sci Instrum. 2009 Nov;80(11):114702
pubmed: 19947746
Biosensors (Basel). 2020 Aug 09;10(8):
pubmed: 32784841

Auteurs

Emanuele Cardillo (E)

Department of Engineering, University of Messina, 98100 Messina, Italy.

Graziella Scandurra (G)

Department of Engineering, University of Messina, 98100 Messina, Italy.

Gino Giusi (G)

Department of Engineering, University of Messina, 98100 Messina, Italy.

Carmine Ciofi (C)

Department of Engineering, University of Messina, 98100 Messina, Italy.

Classifications MeSH