Many researchers have proposed vibration‐based damage‐detection approaches for continuous structural health monitoring. Translation to real applications is not always straightforward because the proposed methods have mostly been developed and validated in controlled environments, and they have not proven to be effective in detecting real damage when considering real scenarios in which environmental and operational variations are not controlled. This work was aimed to develop a fully‐automated strategy to detect damage in operating tie‐rods that only requires one sensor and that can be carried out without knowledge of physical variables, e.g., the axial load. This strategy was created by defining a damage feature based on tie‐rod eigenfrequencies and developing a data‐cleansing strategy that could significantly improve performance of outlier detection based on the Mahalanobis squared distance in real applications. Additionally, the majority of damage‐detection algorithms presented in the literature related to structural health monitoring were validated in controlled environments considering simulated damage conditions. On the contrary, the approach proposed in this paper was shown to allow for the early detection of real damage associated with a corrosion attack under the effects of an intentionally uncontrolled environment.

Automatic Detection of Real Damage in Operating Tie‐Rods

Lucà Francescantonio.;Manzoni Stefano;Cigada Alfredo;Barella Silvia;Gruttadauria Andrea;
2022-01-01

Abstract

Many researchers have proposed vibration‐based damage‐detection approaches for continuous structural health monitoring. Translation to real applications is not always straightforward because the proposed methods have mostly been developed and validated in controlled environments, and they have not proven to be effective in detecting real damage when considering real scenarios in which environmental and operational variations are not controlled. This work was aimed to develop a fully‐automated strategy to detect damage in operating tie‐rods that only requires one sensor and that can be carried out without knowledge of physical variables, e.g., the axial load. This strategy was created by defining a damage feature based on tie‐rod eigenfrequencies and developing a data‐cleansing strategy that could significantly improve performance of outlier detection based on the Mahalanobis squared distance in real applications. Additionally, the majority of damage‐detection algorithms presented in the literature related to structural health monitoring were validated in controlled environments considering simulated damage conditions. On the contrary, the approach proposed in this paper was shown to allow for the early detection of real damage associated with a corrosion attack under the effects of an intentionally uncontrolled environment.
2022
Automatic damage detection
Continuous monitoring
Operational modal analysis
Real damage
Statistical pattern recognition
Structural health monitoring
Tie‐rod
Algorithms
Vibration
File in questo prodotto:
File Dimensione Formato  
sensors-22-01370-v3.pdf

accesso aperto

: Publisher’s version
Dimensione 5.79 MB
Formato Adobe PDF
5.79 MB Adobe PDF Visualizza/Apri

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/11311/1202493
Citazioni
  • ???jsp.display-item.citation.pmc??? 4
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 4
social impact