This paper deals with a preliminary assessment of the performance of four Compressive Sampling (CS) algorithms used for Acoustic Emission (AE) signals delivered by a distributed Structural Health Monitoring (SHM) system. In particular, three random CS-based methods (i.e., Random Demodulation, Gaussian, and Bernoulli), already available in the literature, were evaluated and compared to a deterministic CS-based approach, called Deterministic Binary Block Diagonal (DBBD). The obtained experimental results show that the CS-based method relying on the DBBD outperforms the efficiency of the random CS-based approaches in terms of signal reconstruction quality. In particular, the figure of merit Recovery Error (RE) has been calculated and it is shown that REs are below 20% for compression ratios up to 6 in the case of DBBD CS method.

A CS-based acquisition method of acoustic emission signals from distributed SHM systems

Carni D. L.;Lamonaca F.;
2022

Abstract

This paper deals with a preliminary assessment of the performance of four Compressive Sampling (CS) algorithms used for Acoustic Emission (AE) signals delivered by a distributed Structural Health Monitoring (SHM) system. In particular, three random CS-based methods (i.e., Random Demodulation, Gaussian, and Bernoulli), already available in the literature, were evaluated and compared to a deterministic CS-based approach, called Deterministic Binary Block Diagonal (DBBD). The obtained experimental results show that the CS-based method relying on the DBBD outperforms the efficiency of the random CS-based approaches in terms of signal reconstruction quality. In particular, the figure of merit Recovery Error (RE) has been calculated and it is shown that REs are below 20% for compression ratios up to 6 in the case of DBBD CS method.
978-1-6654-8360-5
Acoustic Emission
Compressive Sampling
IoT Sensor Network
Remote Monitoring
Structural Health
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS 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: http://hdl.handle.net/20.500.11770/336242
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact