FBG sensor system for trailing edge chord-wise hinge rotation measurements

Ciminello, Monica; Concilio, Antonio; Flauto, Domenico; Mennella, F.

doi:10.1117/12.2012017

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…FBG sensors can be used in morphing wings to monitor the shape of the wing. Deflections in variable-camber wings (Figure 9) have been determined from the strain in a metal plate or a hinge measured using FBG sensors (Ciminello et al, 2013; Li et al, 2013a). The actual shape of a twisting wing actuated by SMAs can be monitored with an array of FBG sensors and a neural network (Mieloszyk et al, 2011a, 2011b).…”

Section: Sensorsmentioning

confidence: 99%

Morphing aircraft based on smart materials and structures: A state-of-the-art review

Sun

Guan

Liu

et al. 2016

Journal of Intelligent Material Systems and Structures

284

137

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A traditional aircraft is optimized for only one or two flight conditions, not for the entire flight envelope. In contrast, the wings of a bird can be reshaped to provide optimal performance at all flight conditions. Any change in an aircraft’s configuration, in particular the wings, affects the aerodynamic performance, and optimal configurations can be obtained for each flight condition. Morphing technologies offer aerodynamic benefits for an aircraft over a wide range of flight conditions. The advantages of a morphing aircraft are based on an assumption that the additional weight of the morphing components is acceptable. Traditional mechanical and hydraulic systems are not considered good choices for morphing aircraft. “Smart” materials and structures have the advantages of high energy density, ease of control, variable stiffness, and the ability to tolerate large amounts of strain. These characteristics offer researchers and designers new possibilities for designing morphing aircraft. In this article, recent developments in the application of smart materials and structures to morphing aircraft are reviewed. Specifically, four categories of applications are discussed: actuators, sensors, controllers, and structures.

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Section: Sensorsmentioning

confidence: 99%

Morphing aircraft based on smart materials and structures: A state-of-the-art review

Sun

Guan

Liu

et al. 2016

Journal of Intelligent Material Systems and Structures

284

137

View full text Add to dashboard Cite

show abstract

“…They used actual flight test data to monitor the vibration and loads signature during flight conditions. As a part of the European Smart Intelligent Aircraft Structures project, Ciminello et al [20] developed an in-flight shape monitoring system that uses the chordwise strain distribution obtained from a network of FBG sensors for an adaptive trailing edge device.…”

Section: Fbg Monitoring Of Large Scale Structuresmentioning

confidence: 99%

Large Scale Applications Using FBG Sensors: Determination of In-Flight Loads and Shape of a Composite Aircraft Wing

Nicolas¹,

Sullivan²,

Richards

2016

Aerospace

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Abstract:Technological advances have enabled the development of a number of optical fiber sensing methods over the last few years. The most prevalent optical technique involves the use of fiber Bragg grating (FBG) sensors. These small, lightweight sensors have many attributes that enable their use for a number of measurement applications. Although much literature is available regarding the use of FBGs for laboratory level testing, few publications in the public domain exist of their use at the operational level. Therefore, this paper gives an overview of the implementation of FBG sensors for large scale structures and applications. For demonstration, a case study is presented in which FBGs were used to determine the deflected wing shape and the out-of-plane loads of a 5.5-m carbon-composite wing of an ultralight aerial vehicle. The in-plane strains from the 780 FBG sensors were used to obtain the out-of-plane loads as well as the wing shape at various load levels. The calculated out-of-plane displacements and loads were within 4.2% of the measured data. This study demonstrates a practical method in which direct measurements are used to obtain critical parameters from the high distribution of FBG sensors. This procedure can be used to obtain information for structural health monitoring applications to quantify healthy vs. unhealthy structures.

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“…Moreover, Alvarenga et al [9] also utilized FBGs for realtime wing deflection measurements on lightweight UAVs. Moreover, Ciminello et al [10] proposed a method for in flight shape monitoring in which a network of FBG sensors were utilized for chord wise strain distribution measurements. Additionally, FBG sensors were utilized in the work by Nicolas et al [11] for estimating the out of plane loads as well as the shape of the wing deflection.…”

Section: Introductionmentioning

confidence: 99%

Localization and Estimation of Bending and Twisting Loads Using Neural Networks

Bilal

Ünel

Yıldız

et al. 2020

IECON 2020 the 46th Annual Conference of the IEEE Industrial Electronics Society

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In this paper a neural network based modeling approach is proposed for localization and estimation of loads acting on aircraft wings from full field depth measurements. These measurements can be provided by a multitude of sensors such as depth cameras. Depth cameras have many advantages over other intensity sensors in that they can work in low light conditions and they are invariant to texture and color changes. First, an autoencoder is proposed to extract maximum informative data from the depth images and encode them at a much smaller dimension. Next, to develop the models for localization and estimation of loads, supervised multinomial classification and logistic regression networks are proposed, where the encoded depth features are utilized as input in both networks. The performance of the proposed method is validated on a composite wing subject to concentrated and distributed loads, during which the proposed methods for localization and estimation of loads achieved very high accuracies of 94.3% and 92.7%, respectively.

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FBG sensor system for trailing edge chord-wise hinge rotation measurements

Cited by 3 publications

References 8 publications

Morphing aircraft based on smart materials and structures: A state-of-the-art review

Morphing aircraft based on smart materials and structures: A state-of-the-art review

Large Scale Applications Using FBG Sensors: Determination of In-Flight Loads and Shape of a Composite Aircraft Wing

Localization and Estimation of Bending and Twisting Loads Using Neural Networks

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