2014
DOI: 10.1186/2196-4351-2-13
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Experimental analyses of metal-composite bonded joints: damage identification

Abstract: The advent of composite co-cured and co-bonded integrated construction in aircraft structures has lead to the replacement of fastened joints with bonded joints between the skins and the stiffeners. Skin-stiffener debondings could occur due to impact or other operational reasons and it is usually internal failure. Damage identification of bonded components, which are often vital elements in many structures, is crucial for the prevention of failure of the entire structure. Thus, different researchers have invest… Show more

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Cited by 7 publications
(5 citation statements)
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“…In a real-world application of SHM systems, one may be interested in obtaining the probabilistic RUL of the structure. In general, as well known and shown by Aeronautical Structure Group (GEA) from University of Sao Paulo, an SHM system relies on a network of sensors and on a non-destructive technique (NDT) such as Lamb waves or vibration-based methods [51][52][53][54] to evaluate the presence of damage in the structure. The data collected by the sensors can then be extracted and combined in the form of a damage metric in order to build a mapping function between the data and the damage state of the structure ("DI correlation" shown in Figure 8).…”
Section: Resultsmentioning
confidence: 99%
“…In a real-world application of SHM systems, one may be interested in obtaining the probabilistic RUL of the structure. In general, as well known and shown by Aeronautical Structure Group (GEA) from University of Sao Paulo, an SHM system relies on a network of sensors and on a non-destructive technique (NDT) such as Lamb waves or vibration-based methods [51][52][53][54] to evaluate the presence of damage in the structure. The data collected by the sensors can then be extracted and combined in the form of a damage metric in order to build a mapping function between the data and the damage state of the structure ("DI correlation" shown in Figure 8).…”
Section: Resultsmentioning
confidence: 99%
“…However, the solution of damage detection problem is still open, because many aspects can be investigated, for example, regarding the usage of piezoelectric (PZT) sensors for monitoring metal-composite bonded joints. The current study is based on the previous analyses performed by the authors research group (Aeronautical Structure Group) [22][23][24][25][26]. Mainly, Medeiros et al [22,23] performed a study of damage detection on a cantilever beam by using health monitoring metrics based on frequency response functions (FRFs), considering both numerical simulations and experimental vibration test data.…”
Section: Introductionmentioning
confidence: 99%
“…Hence, the authors concluded that vibration-based methods offered reliable results. Medeiros et al [26] investigated metal-composite bonded joints with fixedfixed boundary conditions by using a vibration-based method and finite element (FE) analyses. However, the numerical results did not show a good agreement with experimental data, because it was very difficult to simulate with accuracy the fixed boundary conditions.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years the connection of different materials has become more and more popular due to the development, in particular, of composite materials and bonding techniques. The number of such solutions has increased drastically in many industries, particularly in the automotive or aviation industry and others and is reflected by the growing year-to-year number of papers [30][31][32][33][34][35][36][37][38][39][40][41].…”
Section: Introductionmentioning
confidence: 99%
“…Due to the high-stress concentrations at the ends of the adhesive joint and degradation of the adhesive layer over time, such connections require periodic inspections in order to control and repair damages. Such monitoring can be made with the use of the traditional non-destructive techniques [45,53], vibration-based methods [35], digital image correlation [1,3] or c-scan inspection [54].…”
Section: Introductionmentioning
confidence: 99%