Structural Damage Identification Based on Integrated Utilization of Inverse Finite Element Method and Pseudo-Excitation Approach

Abstract

The attempt to integrate the applications of conventional structural deformation reconstruction strategies and vibration-based damage identification methods is made in this study, where, more specifically, the inverse finite element method (iFEM) and pseudo-excitation approach (PE) are combined for the first time, to give rise to a novel structural health monitoring (SHM) framework showing various advantages, particularly in aspects of enhanced adaptability and robustness. As the key component of the method, the inverse finite element method (iFEM) enables precise reconstruction of vibration displacements based on measured dynamic strains, which, as compared to displacement measurement, is much more adaptable to existing on-board SHM systems in engineering practice. The PE, on the other hand, is applied subsequently, relying on the reconstructed displacements for the identification of structural damage. Delamination zones in a carbon fibre reinforced plastic (CFRP) laminate are identified using the developed method. As demonstrated by the damage detection results, the iFEM-PE method possesses apparently improved accuracy and significantly enhanced noise immunity compared to the original PE approach depending on displacement measurement. Extensive parametric study is conducted to discuss the influence of a variety of factors on the effectiveness and accuracy of damage identification, including the influence of damage size and position, measurement density, sensor layout, vibration frequency and noise level. It is found that different factors are highly correlated and thus should be considered comprehensively to achieve optimal detection results. The application of the iFEM-PE method is extended to better adapt to the structural operational state, where multiple groups of vibration responses within a wide frequency band are used. Hybrid data fusion is applied to process the damage index (DI) constructed based on the multiple responses, leading to detection results capable of indicating delamination positions precisely.

Coupling of peridynamics and inverse finite element method for shape sensing and crack propagation monitoring of plate structures

“…The deformations obtained at the end of time integration are converted into strains for each PD material point with the formulas given in Eqs. (49)(50)(51). The strain values obtained here, namely the normal strains along the x -and y -axis and the xy -plane shear strains, are illustrated for both crack-free and crack-opening conditions as shown in Fig.…”

“…Particularly, the iQS4 element has recently gained a popularity for shape sensing applications on simple/complex geometries, e.g., ship and offshore structures [35][36][37][38][39] and stiffened aerospace panels [40][41], due to its merits for practical modelling of large-scale structures with low-cost sensor measurement and highly accurate displacement estimations [42][43]. Several studies have shown the superior applications of iFEM/iQS4 approach Coupling of peridynamics and inverse finite element method for shape sensing and crack propagation monitoring of plate structures for damage identification in monolithic/stiffened structures having isotropic/orthotropic material properties [44][45][46][47][48][49].…”

Towards Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

“…Several shape sensing applications with iFEM are available in the literature, based both on numerical and experimental case studies. However, although strain sensors can be applied to the whole structure when dealing with numerical case studies [ 44 , 54 ], their number and locations are one of the main constraints for practical applications [ 39 , 55 ]. Hardware limitations frequently limit the number of sensors available and their installation is subordinated to practical reasons, such as access to the structure.…”

“…In addition to shape sensing, iFEM has been also extended to damage detection in an SHM framework with different approaches, such as load-independent damage indices [ 44 , 55 ], damage parameters based on the Von Mises strain [ 36 , 63 ], damage indices based on the pseudo-excitation approach [ 54 ], and artificial neural networks [ 64 ]. However, these approaches are able to identify the presence and, in some cases, the location of damage in the structure (both metallic and composites) but not estimate its size, which is still an unexplored area of iFEM applications.…”

“…Furthermore, in this study, a rough estimation of the crack size could be performed from the damage index pattern since all the elements around the crack itself are covered by sensors. Similarly, Li et al [ 54 ] detected and quantified delamination on a composite material specimen with a dense sensor network. However, these approaches are only feasible in a numerical case study and cannot be performed in a real scenario, where only sparse sensor networks are allowed.…”