Load Monitoring by Means of Optical Fibres and Strain Gages

Airoldi, Alessandro; Sala, Giuseppe; Evenblij, Rolf; Koimtzoglou, Christos; Λούτας, Θεόδωρος; Carossa, Giovanni Marco; Mastromauro, Pasquale; Kanakis, Toni

doi:10.1007/978-3-319-22413-8_20

Cited by 10 publications

(7 citation statements)

References 11 publications

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“…This change of paradigm strongly relies on the possibility to continuously monitor some physical quantities that can give fundamental information on the status of the structure. Among them, loads and displacements can lead to important evaluations on the status of the structure [ 1 , 2 , 3 , 4 , 5 ] and can accurately guide the structural maintenance operations [ 6 ], thus consistently reducing the costs by avoiding unnecessary scheduled interventions and increasing the safety by determining critical conditions that require immediate actions. Moreover, the on-line monitoring of these quantities is crucial for the control of the morphing structures.…”

Section: Introductionmentioning

confidence: 99%

Experimental Shape Sensing and Load Identification on a Stiffened Panel: A Comparative Study

Esposito

Mattone

Gherlone

2022

Sensors

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The monitoring of loads and displacements during service life is proving to be crucial for developing a modern Structural Health Monitoring framework. The continuous monitoring of these physical quantities can provide fundamental information on the actual health status of the structure and can accurately guide pro-active condition-based maintenance operations, thus reducing the maintenance costs and extending the service life of the monitored structures. Pushed by these needs and by the simultaneous development in the field of strain sensing technologies, several displacement reconstruction and load identification methods have been developed that are based on discrete strain measurements. Among the different formulations, the inverse Finite Element Method (iFEM), the Modal Method (MM) and the 2-step method, the latter being the only one able to also compute the loads together with the displacements, have emerged as the most accurate and reliable ones. In this paper, the formulation of the three methods is summarized in order to set the numerical framework for a comparative study. The three methods are tested on the reconstruction of the external load and of the displacement field of a stiffened aluminium plate starting from experimentally measured strains. A fibre optic sensing system has been used to measure surface strains and an optimization procedure has been performed to provide the best fibre pattern, based on five lines running along the stiffeners’ direction and with a back-to-back measuring scheme. Additional sensors are used to measure the applied force and the plate’s deflection in some locations. The comparison of the results obtained by each method proves the extreme accuracy and reliability of the iFEM in the reconstruction of the deformed shape of the panel. On the other hand, the Modal Method leads to a good reconstruction of the displacements, but also exhibits a sensitivity to the choice of the modes considered for the specific application. Finally, the 2-step approach is able to correctly identify the loads and to reconstruct the displacements with an accuracy that depends on the modeling of the experimental setup.

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Section: Introductionmentioning

confidence: 99%

Experimental Shape Sensing and Load Identification on a Stiffened Panel: A Comparative Study

Esposito

Mattone

Gherlone

2022

Sensors

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“…Another method, sometimes referred to as the calibration matrix approach, reconstructs a set of loads minimizing an error functional comparing discrete strain measures with a numerical formulation of the same, function of the unknown loads. Many applications can be found in the literature of the calibration matrix approach spanning from railway transportation leveraging on the wheel‐rail contact force 25,26 to civil and aeronautical applications either at a numerical level 27,28 or experimentally 29–33 …”

Section: Introductionmentioning

confidence: 99%

Numerical and experimental verification of an inverse‐direct approach for load and strain monitoring in aeronautical structures

Colombo

Sbarufatti

Bosco

et al. 2020

Struct Control Health Monit

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“…Relevant studies of load prediction methods can be classified into two broad categories: frequency-domain methods [6], [7] and time-domain methods [8]- [10]. In frequencydomain methods, the frequency response functions and response spectrums of system are used to inversely calculate the load spectrums in modal coordinate system, then the load is derived through modal coordinate transformation.…”

Section: Introductionmentioning

confidence: 99%

Load Prediction of Space Deployable Structure Based on FBG and LSTM

Zhang

Song

2019

IEEE Access

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To predict the dynamic load of space deployable structure, a novel prediction method based on fiber Bragg grating (FBG) sensors and long short-term memory (LSTM) neural network is proposed. The FBG sensors can measure strain values of the structure. The LSTM establishes the relationship between the strain values and load without a complex dynamic model. The LSTM first works in training mode, its input is strain values and output is the load. Then, the LSTM works in the prediction mode, which takes the current strain values as input and uses the trained network model to predict load. The network of LSTM is simple, which can achieve good prediction effect and shorten the running time. To evaluate the effectiveness of the proposed method, numerical simulations and experiments of space deployable structure with single-point input load are employed. The results demonstrate that compared with the method based on traditional neural network, the max error, root mean square error, and consuming the time of the proposed method are reduced by more than 43%, 21%, and 67%, respectively. INDEX TERMS Space deployable structure, load prediction, long short-term memory neural network, fiber Bragg grating sensor.

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Load Monitoring by Means of Optical Fibres and Strain Gages

Cited by 10 publications

References 11 publications

Experimental Shape Sensing and Load Identification on a Stiffened Panel: A Comparative Study

Experimental Shape Sensing and Load Identification on a Stiffened Panel: A Comparative Study

Numerical and experimental verification of an inverse‐direct approach for load and strain monitoring in aeronautical structures

Load Prediction of Space Deployable Structure Based on FBG and LSTM

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