Application of structural health monitoring techniques to composite wing panels

Romano, Fulvio; Ciminello, Monica; Sorrentino, Assunta; Mercurio, Umberto

doi:10.1177/0021998319843333

Cited by 19 publications

(13 citation statements)

References 37 publications

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“…The optical fiber does not need any engraved sensors and they provide strain readings with a much denser spatial resolution than FBGs. Researchers from several fields showed an intense interest on SHM applications utilizing distributing sensing technique over the last years (Glisic and Inaudi, 2012; Romano et al, 2019). A non-model-based SHM system was proposed by Ciminello et al (2018).…”

Section: Introductionmentioning

confidence: 99%

Strain-based health indicators for the structural health monitoring of stiffened composite panels

Milanoski

Λούτας

2020

Journal of Intelligent Material Systems and Structures

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A common defect of composite-stiffened structures is the disbond at the interface between the two constituents (skin/stringer), as a result of inefficient manufacturing process or foreign object impacts in service. Generally, discontinuities within the volume of an elastic solid medium, subjected to mechanical load, cause anomalies on the strain field in the near vicinity of the discontinuity. Utilizing this observation, this work investigates the effect of artificially induced disbonds in the skin/stiffener interface of an aeronautical-grade generic element. A structural health monitoring methodology is developed, leveraging on numerically simulated strains along the stringer foot which aims to assess the health state of the panel as the size of the disbonds increases. The study is implemented using a parametric finite element model generating various disbond scenarios. Longitudinal strain values are acquired at the exact points where in reality actual fiber Bragg grating sensors will be located. Two types of commonly utilized strain-based health indicators are evaluated, and their drawbacks are revealed and discussed. A new health indicator is proposed that proves its capability to monitor growing disbonds while being both load- and baseline-independent.

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Section: Introductionmentioning

confidence: 99%

Strain-based health indicators for the structural health monitoring of stiffened composite panels

Milanoski

Λούτας

2020

Journal of Intelligent Material Systems and Structures

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“…In the near future, structural health monitoring (SHM) systems will be capable of implementing all four levels of SHM, namely: damage detection, localization, quantification, and remaining useful life estimation (prognosis), [1][2][3][4][5] with sustainable levels of performance in complex components under varying operational and environmental conditions. In order to reach this milestone, a number of common challenges facing current SHM techniques in different fields, that is, aerospace, mechanical, and civil structural systems, needs to be addressed.…”

Section: Introductionmentioning

confidence: 99%

Statistical guided-waves-based structural health monitoring via stochastic non-parametric time series models

Amer

Kopsaftopoulos

2021

Structural Health Monitoring

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Damage detection in active-sensing, guided-waves-based structural health monitoring (SHM) has evolved through multiple eras of development during the past decades. Nevertheless, there still exist a number of challenges facing the current state-of-the-art approaches, both in the industry as well as in research and development, including low damage sensitivity, lack of robustness to uncertainties, need for user-defined thresholds, and non-uniform response across a sensor network. In this work, a novel statistical framework is proposed for active-sensing SHM based on the use of ultrasonic guided waves. This framework is based on stochastic non-parametric time series models and their corresponding statistical properties in order to readily provide healthy confidence bounds and enable accurate and robust damage detection via the use of appropriate statistical decision-making tests. Three such methods and corresponding statistical quantities (test statistics) along with decision-making schemes are formulated and experimentally assessed via the use of three coupons with different levels of complexity: an Al plate with a growing notch, a carbon fiber-reinforced plastic (CFRP) plate with added weights to simulate local damage, and the CFRP panel used in the Open Guided Waves project, all fitted with piezoelectric transducers under a pitch-catch configuration. The performance of the proposed methods is compared to that of state-of-the-art time-domain damage indices (DIs). The results demonstrate the increased detection sensitivity and robustness of the proposed methods, with better tracking capability of damage evolution compared to conventional approaches, even for damage-non-intersecting actuator–sensor paths. In particular, the Z statistic emerges as the best damage detection metric compared to conventional DIs, as well as the other proposed statistics. Overall, the proposed statistics in this study promise greater damage sensitivity across different components, with enhanced robustness to uncertainties, as well as user-friendly application.

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“…e monitoring ability of composite materials has become the biggest weakness restricting their development. erefore, it is very important to monitor the local damage and development status of the composite structure in real time for its safe application [2,3]. So, in situ structural health monitoring (SHM) of 3D braided composites is a very important research topic.…”

Section: Introductionmentioning

confidence: 99%

Strain-Sensing Characteristics of Carbon Nanotube Yarns Embedded in Three-Dimensional Braided Composites under Cyclic Loading

Bai

Ding

Jia

et al. 2021

Discrete Dynamics in Nature and Society

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Carbon nanotube yarns are embedded in three-dimensional (3D) braided composites with five-axis yarns, which are used as strain sensors to monitor the damage of 3D braided composites. In the cyclic mechanical loading experiment, the strain-sensing characteristics of 3D braided composites were studied by in situ measuring the resistance change of the embedded carbon nanotube yarn. The 3D five-directional braided composite prefabricated part based on carbon nanotube yarns was developed, and the progressive damage accumulation experiments were carried out on carbon nanotube yarns and specimens embedded in carbon nanotube yarns. The research results show that there is a good correlation between the change of relative resistance of the carbon nanotube yarn and the strain of the composite specimen during cyclic loading and unloading. When the tensile degree of the specimen increases beyond a certain range, the carbon nanotube yarn sensor embedded in the specimen shows resistance hysteresis and produces residual resistance. Therefore, the fiber can better monitor the progressive damage accumulation of 3D five-direction braided composites.

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Application of structural health monitoring techniques to composite wing panels

Cited by 19 publications

References 37 publications

Strain-based health indicators for the structural health monitoring of stiffened composite panels

Strain-based health indicators for the structural health monitoring of stiffened composite panels

Statistical guided-waves-based structural health monitoring via stochastic non-parametric time series models

Strain-Sensing Characteristics of Carbon Nanotube Yarns Embedded in Three-Dimensional Braided Composites under Cyclic Loading

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