Damage detection in composite materials structures under variable loads conditions by using fiber Bragg gratings and principal component analysis, involving new unfolding and scaling methods

Sierra-Pérez, Julián; Güemes, Alfredo; Mujica, Luis Eduardo; Ruiz, Magda

doi:10.1177/1045389x14541493

Cited by 16 publications

(9 citation statements)

References 34 publications

(52 reference statements)

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“…Continuously growth phenomena of fatigue-induced cracks were efficiently monitored via two experimental campaigns, using real-time strain measurements recorded from a network of FBGs. An innovative damage detection methodology (Sierra-Pérez et al, 2015) based on principal component analysis (PCA) was also proposed. Damage indices T 2 and Q were calculated based on FBG measurements on the wing section of an unnamed air vehicle.…”

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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“…Once wing skin strain under different loads is measured accurately, aircraft designers and engineers can obtain its ultimate limit states, which is important for reducing the risk of composite structural failures. Therefore, the accurate strain measurement for CFRP laminates is of great importance [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Strain Transfer Characteristic of a Fiber Bragg Grating Sensor Bonded to the Surface of Carbon Fiber Reinforced Polymer Laminates

Wang

Zhang

et al. 2018

Applied Sciences

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Structural health monitoring is of great importance for the application of composites in aircrafts. Fiber Bragg grating (FBG) sensors are very suitable for structure strain measurement. However, the strain measured by FBG sensors is different from the original strain in host materials. The relationship between them is defined as strain transfer. As composites are anisotropic, the traditional strain transfer model, which regards the elasticity modulus of host materials as a constant, is inadaptable. In this paper, a new strain transfer model is proposed for FBG sensors bonded to the surface of carbon fiber reinforced polymer (CFRP) laminates. Based on the measurement structure, the model is established and the transfer function is derived. The characteristics influencing the strain transfer are analyzed. The stacking directions, stacking numbers, and stacking sequences of CFRP laminates have a distinct effect on the transfer efficiency, which is different from the isotropy host materials. The accuracy of the proposed model was verified by experiments on a nondestructive tensile system, and the maximum model error is less than 0.5%. Moreover, the model was applied to the strain measurement of CFRP wing skin, which indicates that measurement errors decrease by 11.6% to 19.8% after the compensation according to the model.

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“…All of the approaches are based on multivariate statistical analysis. [5][6][7][8][9][10][11][12][13] However, to improve the accuracy of the expected results, and since these methods by themselves are unable-in some cases-to correctly classify different scenarios, the methodologies had to be enhanced using more complex and computationally expensive algorithms. Following the same goal but reducing significantly the computational cost, this article is focused on the development of a damage detection indicator-considering dynamic responses as random variables as in Mujica et al 14 -that combines a data-driven baseline model (reference pattern obtained from the healthy structure) based on principal component analysis (PCA) and univariate hypothesis testing.…”

Section: Introductionmentioning

confidence: 99%

Detection of structural changes through principal component analysis and multivariate statistical inference

Pozo

Arruga

Mujica

et al. 2016

Structural Health Monitoring

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Damage detection in composite materials structures under variable loads conditions by using fiber Bragg gratings and principal component analysis, involving new unfolding and scaling methods

Cited by 16 publications

References 34 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

Strain Transfer Characteristic of a Fiber Bragg Grating Sensor Bonded to the Surface of Carbon Fiber Reinforced Polymer Laminates

Detection of structural changes through principal component analysis and multivariate statistical inference

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