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Shape Sensing 2021-2024

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 11992

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Prof. Dr. Marco Gherlone

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Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy
Interests: multilayered composite and sandwich structures; structural health monitoring; shape sensing; finite element method
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Structural Health Monitoring/Management (SHM) is the latest technology utilizing advanced sensor networks for real-time monitoring and assessment of structural integrity. This technology is of an increased interest for application to existing and next generation aerospace and naval vehicles and structures. Current areas for application of SHM include civilian and military aircraft, spacecraft, naval and off-shore structures, and civil engineering structures, such as bridges and tunnels. The massive amounts of sensor data can be processed and analyzed using physics-based inverse and direct discretization methods, similar to the widely used direct Finite Element Method for structural analysis and design. Damage detection can also be inferred from the processed in-situ temperature and strain-sensor data, thus enabling improved maintanance of structural components based on the actual structural loads sustained during operational service environment.

This Special Issue is focuced on bringing together the latest advances in physics-based solution methods suitable for the large-scale structural applications to enable real-time structural health monitoring of aerospace, civil, and marine structures. The topics include but are not limited to:

Shape sensing
Inverse Finite Element Methods
Modal reconstruction methods
Methods for real-time damage assessment
Methods for real-time delamination damage assessment in laminated composite structures
Sensor optimization methods and studies
Advanced and affordable strain sensor technologies for large-scale applications
Method for material characterization inferred from sensor data

Prof. Dr. Marco Gherlone
Guest Editor

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (6 papers)

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Research

17 pages, 7218 KiB

Open AccessArticle

Strain Measurement with Optic Fibers for Structural Health Monitoring of Woven Composites: Comparison with Strain Gauges and Digital Image Correlation Measurements

by Carlo Boursier Niutta, Andrea Tridello, Raffaele Ciardiello and Davide S. Paolino

Sensors 2023, 23(24), 9794; https://doi.org/10.3390/s23249794 - 13 Dec 2023

Viewed by 733

Abstract

In this work, the strains measured with optic fibers and recorded during tensile tests performed on carbon/epoxy composite specimens were compared to those recorded by strain gauges and by Digital Image Correlation (DIC). The work aims at investigating the sensitivity of embedded and glued optic sensors for structural health monitoring applications in comparison with strain gauges and the full field strain map of the DIC. Acrylate, polyimide optic fibers, and three strain gauge sizes are considered to compare the three techniques. Results show hard polyimide-coated sensors are more sensitive to the material pattern than soft acrylate-coated fibers, which also require extensive adhesion length. The work shows a comparable size of strain gauges and material meso-structure is also critical for properly assessing material properties. The Young’s modulus computed with the three different techniques is used to define a strategy that supports the selection and the proper size of the adopted strain measuring system for structural health monitoring of composite materials. Full article

(This article belongs to the Special Issue Shape Sensing 2021-2024)

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21 pages, 18309 KiB

Open AccessArticle

Hybrid Shell-Beam Inverse Finite Element Method for the Shape Sensing of Stiffened Thin-Walled Structures: Formulation and Experimental Validation on a Composite Wing-Shaped Panel

by Marco Esposito, Rinto Roy, Cecilia Surace and Marco Gherlone

Sensors 2023, 23(13), 5962; https://doi.org/10.3390/s23135962 - 27 Jun 2023

Cited by 4 | Viewed by 1145

Abstract

This work presents a novel methodology for the accurate and efficient elastic deformation reconstruction of thin-walled and stiffened structures from discrete strains. It builds on the inverse finite element method (iFEM), a variationally-based shape-sensing approach that reconstructs structural displacements by matching a set of analytical and experimental strains in a least-squares sense. As iFEM employs the finite element framework to discretize the structural domain and as the displacements and strains are approximated using element shape functions, the kind of element used influences the accuracy and efficiency of the iFEM analysis. This problem is addressed in the present work through a novel discretization scheme that combines beam and shell inverse elements to develop an iFEM model of the structure. Such a hybrid discretization paradigm paves the way for more accurate shape-sensing of geometrically complex structures using fewer sensor measurements and lower computational effort than traditional approaches. The hybrid iFEM is experimentally demonstrated in this work for the shape sensing of bending and torsional deformations of a composite stiffened wing panel instrumented with strain rosettes and fiber-optic sensors. The experimental results are accurate, robust, and computationally efficient, demonstrating the potential of this hybrid scheme for developing an efficient digital twin for online structural monitoring and control. Full article

(This article belongs to the Special Issue Shape Sensing 2021-2024)

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20 pages, 8977 KiB

Open AccessArticle

Variable Thickness Strain Pre-Extrapolation for the Inverse Finite Element Method

by Dario Poloni, Daniele Oboe, Claudio Sbarufatti and Marco Giglio

Sensors 2023, 23(3), 1733; https://doi.org/10.3390/s23031733 - 03 Feb 2023

Viewed by 1894

Abstract

The inverse Finite Element Method (iFEM) has recently gained much popularity within the Structural Health Monitoring (SHM) field since, given sparse strain measurements, it reconstructs the displacement field of any beam or shell structure independently of the external loading conditions and of the material properties. However, in principle, the iFEM requires a triaxial strain measurement for each inverse finite element, which is seldom feasible in practical applications due to both costs and cabling-related limitations. To alleviate this problem several techniques to pre-extrapolate the measured strains have been developed, so that interpolated or extrapolated strain values are inputted to elements without physical sensors: the benefit is that the required number of sensors can be reduced. Nevertheless, whenever the monitored components comprise regions of different thicknesses, each region of constant thickness must be extrapolated separately, due to thickness-induced discontinuities in the strain field. This is the case in many practical applications, especially those concerning fiber-reinforced composite laminates. This paper proposes to extrapolate the measured strain field in a thickness-normalized space, where the thickness-induced trends are removed; this novel method can significantly decrease the number of required sensors, effectively reducing the costs of iFEM-based SHM systems. The method is validated in a simple but informative numerical case study, highlighting the potentialities and benefits of the proposed approach for more complex application scenarios. Full article

(This article belongs to the Special Issue Shape Sensing 2021-2024)

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29 pages, 14558 KiB

Open AccessArticle

Sensor Placement Optimization for Shape Sensing of Plates and Shells Using Genetic Algorithm and Inverse Finite Element Method

by Maryam Ghasemzadeh and Adnan Kefal

Sensors 2022, 22(23), 9252; https://doi.org/10.3390/s22239252 - 28 Nov 2022

Cited by 7 | Viewed by 3028

Abstract

This paper reports the first investigation of the inverse finite element method (iFEM) coupled with the genetic algorithm (GA) to optimize sensor placement models of plate/shell structures for their real-time and full-field deformation reconstruction. The primary goal was to reduce the number of sensors in the iFEM models while maintaining the high accuracy of the displacement results. Here, GA was combined with the four-node quadrilateral inverse-shell elements (iQS4) as the genes inherited through generations to define the optimum positions of a specified number of sensors. Initially, displacement monitoring of various plates with different boundary conditions under concentrated and distributed static/dynamic loads was conducted to investigate the performance of the coupled iFEM-GA method. One of these case studies was repeated for different initial populations and densities of sensors to evaluate their influence on the accuracy of the results. The results of the iFEM-GA algorithm indicate that an adequate number of individuals is essential to be assigned as the initial population during the optimization process to ensure diversity for the reproduction of the optimized sensor placement models and prevent the local optimum. In addition, practical optimization constraints were applied for each plate case study to demonstrate the realistic applicability of the implemented method by placing the available sensors at feasible sites. The iFEM-GA method’s capability in structural dynamics was also investigated by shape sensing the plate subjected to different dynamic loadings. Furthermore, a clamped stiffened plate and a curved shell were also considered to assess the applicability of the proposed method for the shape sensing of complex structures. Remarkably, the outcomes of the iFEM-GA approach with the reduced number of sensors agreed well with those of the full-sensor counterpart for all of the plate/shell case studies. Hence, this study reveals the superior performance of the iFEM-GA method as a viable sensor placement strategy for the accurate shape sensing of engineering structures with only a few sensors. Full article

(This article belongs to the Special Issue Shape Sensing 2021-2024)

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19 pages, 13778 KiB

Open AccessArticle

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

by Marco Esposito, Massimiliano Mattone and Marco Gherlone

Sensors 2022, 22(3), 1064; https://doi.org/10.3390/s22031064 - 29 Jan 2022

Cited by 12 | Viewed by 1898

Abstract

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. Full article

(This article belongs to the Special Issue Shape Sensing 2021-2024)

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15 pages, 5416 KiB

Open AccessArticle

Shaping the Design Features of a Dynamometer for Measuring Resistance Biaxial Components of Symmetrical Coulters

by Jacek Marcinkiewicz, Mikołaj Spadło, Zaneta Staszak and Jarosław Selech

Sensors 2022, 22(1), 272; https://doi.org/10.3390/s22010272 - 30 Dec 2021

Viewed by 1655

Abstract

The article lays out the methodology for shaping the design features of a strain gauge transducer, which would make it possible to study forces and torques generated during the operation of symmetrical seeder coulters. The transducers that have been known up until now cannot be used to determine forces and torques for the coulter configuration adopted by the authors. For this purpose, the design of the transducer in the form of strain gauge beams was used to ensure the accumulated stress concentration. A detailed design was presented in the form of a 3D model, along with a transducer body manufactured on its basis, including the method for arranging the strain gauges thereon. Moreover, the article discusses the methodology of processing voltage signals obtained from component loads. Particular attention was paid to the methodology of determining the load capacity of the transducer structure, based on finite element method (FEM). This made it possible to choose a transducer geometry providing the expected measurement sensitivity and, at the same time, maintaining the best linearity of indications, insignificant coupling error, and a broad measurement range. The article also presents the characteristics of the transducer calibration process and a description of a special test stand designed for this purpose. The transducer developed within the scope of this work provides very high precision of load spectrum reads, thus enabling the performance of a detailed fatigue analysis of the tested designs. Additionally, the versatility it offers makes it easy to adapt to many existing test stands, which is a significant advantage because it eliminates the need to build new test stands. Full article

(This article belongs to the Special Issue Shape Sensing 2021-2024)

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