In modern industry, the wide use of reliable and sophisticated sensors with their connection to internet has introduced the phenomena of Big Data, especially in the field of condition monitoring systems (CMSs) in e-maintenance applications. In particular, in the case of vibration signals, high-performance acquisition systems are required, characterized by anti-aliasing filtering and high uniform sampling rate, in order to properly digitalize the meaningful frequency content of the signals. In this context, the capability of non-uniform random sampling (RS) is assessed in this work. While in different fields, such astronomy, structural and biomedical studies, the RS is a problem to be resolved, due to the unavailability of samples at specific instants (missing data problem), in the field of fault detection & diagnosis (FDD), RS can be a chosen sampling method thanks to its advantages: Anti-aliasing property and low average sampling rate. Therefore, this paper focuses on studying the anti-aliasing property of the random sampled data, verifying the criterion proposed in literature for establish the Nyquist frequency, and analyzing its sensitivity to the sampling parameters. This study is carried out using simulated signals and computing the spectral window, giving the Nyquist frequency for different random sampling parameters; moreover, a spectral analysis method, the Schuster periodogram, is used to verify when the spectrum is actually free of alias. The results show that the Nyquist frequency depends on the numerical accuracy of the randomly generated time instants.

On the Nyquist frequency of random sampled signals

Hamadache M.
Primo
;
D'Elia G.;Dalpiaz G.
Ultimo
2019

Abstract

In modern industry, the wide use of reliable and sophisticated sensors with their connection to internet has introduced the phenomena of Big Data, especially in the field of condition monitoring systems (CMSs) in e-maintenance applications. In particular, in the case of vibration signals, high-performance acquisition systems are required, characterized by anti-aliasing filtering and high uniform sampling rate, in order to properly digitalize the meaningful frequency content of the signals. In this context, the capability of non-uniform random sampling (RS) is assessed in this work. While in different fields, such astronomy, structural and biomedical studies, the RS is a problem to be resolved, due to the unavailability of samples at specific instants (missing data problem), in the field of fault detection & diagnosis (FDD), RS can be a chosen sampling method thanks to its advantages: Anti-aliasing property and low average sampling rate. Therefore, this paper focuses on studying the anti-aliasing property of the random sampled data, verifying the criterion proposed in literature for establish the Nyquist frequency, and analyzing its sensitivity to the sampling parameters. This study is carried out using simulated signals and computing the spectral window, giving the Nyquist frequency for different random sampling parameters; moreover, a spectral analysis method, the Schuster periodogram, is used to verify when the spectrum is actually free of alias. The results show that the Nyquist frequency depends on the numerical accuracy of the randomly generated time instants.
2019
978-3-030-11219-6
978-3-030-11220-2
Random sampling; Nyquist frequency; Spectral window; Alias and anti-aliasing; Condition monitoring system
File in questo prodotto:
File Dimensione Formato  
2019 - Springer CMMNO 2018 - Hamadache DE GD.pdf

solo gestori archivio

Descrizione: On the Nyquist Frequency of Random Sampled Signals - Springer 2019
Tipologia: Pre-print
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 648.31 kB
Formato Adobe PDF
648.31 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
10.1007@978-3-030-11220-232.pdf

solo gestori archivio

Descrizione: Full text editoriale
Tipologia: Full text (versione editoriale)
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 2.17 MB
Formato Adobe PDF
2.17 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2439296
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact