Statistical updating of finite element model with Lamb wave sensing data for damage detection problems

Vanli, O. Arda; Jung, Sungmoon

doi:10.1016/j.ymssp.2013.06.015

Cited by 21 publications

(16 citation statements)

References 19 publications

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“…Bijudas et al [24] conducted experimental and numerical studies of "baseline-free" damage detection in a stiffened plate by timereversed Lamb waves. Vanli and Jung [254] employed hversion FEs in conjunction with statistical updating methods to improve the damage prediction capability. In [161] wave scattering at impact damages was investigated in sandwich panels.…”

Section: Low Order Finite Elementsmentioning

confidence: 99%

Simulation Methods for Guided Wave-Based Structural Health Monitoring: A Review

Willberg

Duczek

Vivar-Perez

et al. 2015

Applied Mechanics Reviews

117

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This paper reviews the state-of-the-art in numerical wave propagation analysis. The main focus in that regard is on guided wave-based structural health monitoring (SHM) applications. A brief introduction to SHM and SHM-related problems is given, and various numerical methods are then discussed and assessed with respect to their capability of simulating guided wave propagation phenomena. A detailed evaluation of the following methods is compiled: (i) analytical methods, (ii) semi-analytical methods, (iii) the local interaction simulation approach (LISA), (iv) finite element methods (FEMs), and (v) miscellaneous methods such as mass–spring lattice models (MSLMs), boundary element methods (BEMs), and fictitious domain methods. In the framework of the FEM, both time and frequency domain approaches are covered, and the advantages of using high order shape functions are also examined.

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Section: Low Order Finite Elementsmentioning

confidence: 99%

Simulation Methods for Guided Wave-Based Structural Health Monitoring: A Review

Willberg

Duczek

Vivar-Perez

et al. 2015

Applied Mechanics Reviews

117

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“…For example, numerous advance damage detection techniques, such as damage imaging [11] [12], maximum-likelihood estimation [13], diffraction tomography [14] [15], phased-array beamforming [16], model based approach [17] [18] and the Bayesian interface [19] [20] were developed for plate-like structures. In contrast, most GW based damage detection techniques for 1D waveguides were limited in identifying the existence and location of damage [21].…”

Section: Gw Damage Identificationmentioning

confidence: 99%

Guided wave-based identification of multiple cracks in beams using a Bayesian approach

2017

Mechanical Systems and Signal Processing

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“…In the practical applications of model updating, the measured data are often incomplete and include randomness. Based on the system variability, some authors proposed stochastic model updating techniques [48,49,50,51]. The main advantage of this approach is to add randomness in the model updating process.…”

Section: Introductionmentioning

confidence: 99%

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

Machado

Adhikari

Santos

et al. 2018

Mechanical Systems and Signal Processing

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Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

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Statistical updating of finite element model with Lamb wave sensing data for damage detection problems

Cited by 21 publications

References 19 publications

Simulation Methods for Guided Wave-Based Structural Health Monitoring: A Review

Simulation Methods for Guided Wave-Based Structural Health Monitoring: A Review

Guided wave-based identification of multiple cracks in beams using a Bayesian approach

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

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