Predictive model of fatigue crack detection in thick bridge steel structures with piezoelectric wafer active sensors

M. Gresil, L. Yu, Y. Shen, V. Giurgiutiu

Research output: Contribution to journalArticleResearchpeer-review

17 Citations (Scopus)

Abstract

This paper presents numerical and experimental results on the use of guided waves for structural health monitoring (SHM) of crack growth during a fatigue test in a thick steel plate used for civil engineering application. Numerical simulation, analytical modeling, and experimental tests are used to prove that piezoelectric wafer active sensor (PWAS) can perform active SHM using guided wave pitch-catch method and passive SHM using acoustic emission (AE). AE simulation was performed with the multi-physic FEM (MP-FEM) approach. The MP-FEM approach permits that the output variables to be expressed directly in electric terms while the two-ways electromechanical conversion is done internally in the MP-FEM formulation. The AE event was simulated as a pulse of defined duration and amplitude. The electrical signal measured at a PWAS receiver was simulated. Experimental tests were performed with PWAS transducers acting as passive receivers of AE signals. An AE source was simulated using 0.5-mm pencil lead breaks. The PWAS transducers were able to pick up AE signal with good strength. Subsequently, PWAS transducers and traditional AE transducer were applied to a 12.7-mm CT specimen subjected to accelerated fatigue testing. Active sensing in pitch catch mode on the CT specimen was applied between the PWAS transducers pairs. Damage indexes were calculated and correlated with actual crack growth. The paper finishes with conclusions and suggestions for further work.

Original languageEnglish
Pages (from-to)97-119
Number of pages23
JournalSmart Structures and Systems
Volume12
Issue number2
DOIs
Publication statusPublished - 1 Aug 2013
Externally publishedYes

Keywords

  • Acoustic emission
  • Active sensing
  • Crack detection
  • Finite element method
  • Piezoelectric wafer active sensor
  • Predictive modeling
  • Structural health monitoring

Cite this