2019
DOI: 10.1007/s40091-019-00243-9
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Modal identification of localised damage in beams and trusses: experimental and numerical results

Abstract: The paper discusses the possibility of detecting local damages in complex structures typical of civil engineering, as multispan beams and trusses. Namely, it describes a procedure to identify localised cracks in structures in the elastic range of behaviour using only the values of natural frequencies in the intact configuration and in the damaged one evaluated by means of dynamic tests. The error minimisation procedure described in the paper selects the solution within a set of finite element models that simul… Show more

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Cited by 4 publications
(1 citation statement)
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References 25 publications
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“…In 2012, Beskhyroun et al propose a method based on wavelet transforms using dynamic responses recorded under excitation applied by an actuator, but this procedure shows some limitations under operating conditions [9]; Bowe et al presented in 2015 a method that exploits the analysis of the acceleration of vehicles resulting from the train-track interaction, but this method is not applicable in the presence of noise [10]; in the same year Gonzales and Karoumi studied a strategy based on artifcial neural networks (ANN) but the limits of this methodology lie in modeling the railway bridge as a simply supported beam that does not describe the complexity of the structure [11]. A review of the latest literature is listed in the bibliography [12][13][14][15][16][17][18][19][20][21]. It is known that most of these methods have identifed the existence of damage (the frst level of the SHM process), without fully reaching the goal of level 2 which is the localization of damage.…”
Section: Introductionmentioning
confidence: 99%
“…In 2012, Beskhyroun et al propose a method based on wavelet transforms using dynamic responses recorded under excitation applied by an actuator, but this procedure shows some limitations under operating conditions [9]; Bowe et al presented in 2015 a method that exploits the analysis of the acceleration of vehicles resulting from the train-track interaction, but this method is not applicable in the presence of noise [10]; in the same year Gonzales and Karoumi studied a strategy based on artifcial neural networks (ANN) but the limits of this methodology lie in modeling the railway bridge as a simply supported beam that does not describe the complexity of the structure [11]. A review of the latest literature is listed in the bibliography [12][13][14][15][16][17][18][19][20][21]. It is known that most of these methods have identifed the existence of damage (the frst level of the SHM process), without fully reaching the goal of level 2 which is the localization of damage.…”
Section: Introductionmentioning
confidence: 99%