Real-time structural health monitoring (SHM) acquires countless importance when applied to large-scale civil infrastructures, where the damage should be managed immediately to avoid both economic and human loss. Recent studies in the field of real-time identification of bridges generally assume linear time-varying (LTV) structural models, justified on the grounds that continuously varying traffic load may slightly change the structural behavior over time. Time-varying load also involves non-stationary input excitation, which cannot be modeled as Gaussian white noise, as in the traditional output-only identification methods, and may be characterized by time-varying frequency spectrum which could affect the effectiveness of commonly used identification algorithms. In this paper, the Modal Assurance Distribution (MAD) is employed for the dynamic identification of LTV structures. Based upon the instantaneous operating deflection shapes (ODSs) evaluated through the wavelet packet decomposition, the MAD represents the instantaneous ODS similarity between narrow-band signal components, highlighting the presence of time-varying modal responses. Compared to the most used traditional time-frequency representations (TFRs), representing the distribution of energy through the time-frequency plane, the MAD enables a clearer reading of the modal responses, facilitating their extraction for real-time damage identification. The practical application to a benchmark structure shows the potential of the MAD as a novel TFR which could give rise to a new family of system and damage identification methods.

Said Quqa, G.B. (2021). A Novel Time-Frequency Distribution for Real-Time Monitoring of Civil Infrastructures. Switzerland : Springer, Cham [10.1007/978-3-030-64594-6_34].

A Novel Time-Frequency Distribution for Real-Time Monitoring of Civil Infrastructures

Said Quqa
;
Giacomo Bernagozzi;Luca Landi;Pier Paolo Diotallevi
2021

Abstract

Real-time structural health monitoring (SHM) acquires countless importance when applied to large-scale civil infrastructures, where the damage should be managed immediately to avoid both economic and human loss. Recent studies in the field of real-time identification of bridges generally assume linear time-varying (LTV) structural models, justified on the grounds that continuously varying traffic load may slightly change the structural behavior over time. Time-varying load also involves non-stationary input excitation, which cannot be modeled as Gaussian white noise, as in the traditional output-only identification methods, and may be characterized by time-varying frequency spectrum which could affect the effectiveness of commonly used identification algorithms. In this paper, the Modal Assurance Distribution (MAD) is employed for the dynamic identification of LTV structures. Based upon the instantaneous operating deflection shapes (ODSs) evaluated through the wavelet packet decomposition, the MAD represents the instantaneous ODS similarity between narrow-band signal components, highlighting the presence of time-varying modal responses. Compared to the most used traditional time-frequency representations (TFRs), representing the distribution of energy through the time-frequency plane, the MAD enables a clearer reading of the modal responses, facilitating their extraction for real-time damage identification. The practical application to a benchmark structure shows the potential of the MAD as a novel TFR which could give rise to a new family of system and damage identification methods.
2021
European Workshop on Structural Health Monitoring
335
345
Said Quqa, G.B. (2021). A Novel Time-Frequency Distribution for Real-Time Monitoring of Civil Infrastructures. Switzerland : Springer, Cham [10.1007/978-3-030-64594-6_34].
Said Quqa, Giacomo Bernagozzi, Luca Landi, Pier Paolo Diotallevi
File in questo prodotto:
Eventuali allegati, non sono esposti

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: https://hdl.handle.net/11585/789497
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact