A procedure for the identification of multiple cracks on beams and frames by static measurements

Caddemi, S.; Caliò, Ivo; Cannizzaro, Francesco; Morassi, Antonino

doi:10.1002/stc.2194

Cited by 13 publications

(8 citation statements)

References 36 publications

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“…Liu et al [14] presented a method for structural damage detection of statically loaded structures based on the change of internal force and displacement of the finite element model. Caddemi et al [15] successfully identified the local damage of Euler-Bernoulli beams based on static loads and boundary conditions under the interference of environmental noise. However, these studies based on static characteristics still have some shortcomings, such as the cost being high and the response data being easily disturbed by external factors.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Whale-Chimp Optimization Algorithm for Structural Damage Detection

et al. 2022

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Damage detection of structures based on swarm intelligence optimization algorithms is an effective method for structural damage detection and key parts of the field of structural health monitoring. Based on the chimp optimization algorithm (ChOA) and the whale optimization algorithm, this paper proposes a novel hybrid whale-chimp optimization algorithm (W-ChOA) for structural damage detection. To improve the identification accuracy of the ChOA, the Sobol sequence is adopted in the population initialization stage to make the population evenly fill the entire solution space. In addition, to improve the local search ability of the traditional ChOA, the bubble-net hunting mechanism and the random search mechanism of the whale optimization algorithm are introduced into the position update process of the ChOA. In this paper, the validity and applicability of the proposed method are illustrated by a two-story rigid frame model and a simply supported beam model. Simulations show that the presented method has much better performance than the ChOA, especially in dealing with multiple damage detection cases. The W-ChOA has good performance in both overcoming misjudgment and improving computational efficiency, which should be a preferred choice in adoption for structural damage detection.

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Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Whale-Chimp Optimization Algorithm for Structural Damage Detection

et al. 2022

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“…Dynamic ambient tests can be a valuable aid in calibrating FEM models to be used for the analyses [23], and they can also bring different behaviours of the various parts of complex buildings or blocks of houses to the forefront [24]. Similar techniques are employed in dynamic damage detection methods for structural health purposes [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Testing in Support of the Seismic Assessment of a Century Old Masonry Building Complex

et al. 2022

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The vulnerability assessment of existing masonry buildings is a largely investigated research topic with some aspects still to be faced. In historic towns, masonry buildings are aggregated and together confined, and their final appearance is derived from interventions and additions during their lives in different times and with different masonry textures or different construction materials. Demolitions and reconstructions of some parts were frequent, with the difficulty of now understanding the effectiveness of the mutual constraints. The seismic assessment of a case study of a 175-year-old building complex in Udine (Italy) provides an opportunity to use the results of ambient vibration tests to face the problem of modelling aggregate buildings for their seismic assessment. The “Padiglione Lodi” building complex was built in 1847 and extended and renovated several times afterwards. It was built mostly using URM with limited use of reinforced concrete. It consists of a main building and three wings (western, central and eastern). The inspections, experimental survey and analysis of the available documentation are used to suitably calibrate a Finite Element Model of the whole complex. Moreover, this allows the singling out of the central wing, as the unit needs more careful investigation. Non-destructive dynamic testing is then applied to the central wing in order to further validate the model and improve the knowledge of the interaction of the unit with the rest of the building. General remarks on the effective application of non-destructive dynamic analysis in conjunction with other methods to the seismic assessment of large URM building complexes are drawn.

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“…While the latter studies are limited to considering cracked FGM beams, this study is devoted to multiple cracked identification in frames made of FGM using the technique proposed in (Lien et al, 2019a) for multi-span beams. Cracked frame structures were considered in (Khiem, 2006;Caddemi and Caliò, 2013;Caddemi et al, 2018), but they consisted of cracked homogeneous Euler-Bernoulli beam elements. In this paper, first, we establish the dynamic stiffness model of a cracked FGM frame based on an explicit exact solution of free vibration in a multiple cracked FGM beam element.…”

Section: Introductionmentioning

confidence: 99%

Crack identification in functionally graded material framed structures using stationary wavelet transform and neural network

Khiem

Lien

Duc³

2021

J. Zhejiang Univ. Sci. A

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In this paper, an integrated procedure is proposed to identify cracks in a portal framed structure made of functionally graded material (FGM) using stationary wavelet transform (SWT) and neural network (NN). Material properties of the structure vary along the thickness of beam elements by the power law of volumn distribution. Cracks are assumed to be open and are modeled by double massless springs with stiffness calculated from their depth. The dynamic stiffness method (DSM) is developed to calculate the mode shapes of a cracked frame structure based on shape functions obtained as a general solution of vibration in multiple cracked FGM Timoshenko beams. The SWT of mode shapes is examined for localization of potential cracks in the frame structure and utilized as the input data of NN for crack depth identification. The integrated procedure proposed is shown to be very effective for accurately assessing crack locations and depths in FGM structures, even with noisy measured mode shapes and a limited amount of measured data.

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A procedure for the identification of multiple cracks on beams and frames by static measurements

Cited by 13 publications

References 36 publications

A Novel Hybrid Whale-Chimp Optimization Algorithm for Structural Damage Detection

A Novel Hybrid Whale-Chimp Optimization Algorithm for Structural Damage Detection

Dynamic Testing in Support of the Seismic Assessment of a Century Old Masonry Building Complex

Crack identification in functionally graded material framed structures using stationary wavelet transform and neural network

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