Impact Damage Detection in CFRP Composite via Electrical Resistance Tomography by Means of Statistical Processing

Cagáň, Jan; Michalcová, Lenka

doi:10.1007/s10921-020-00677-2

Cited by 23 publications

(13 citation statements)

References 32 publications

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“…Recently published works [11,12,15,16] have shown the capability of EIT for the detection and localization of laboratory made damages on FRP composites, such as through-thickness holes, surface cuts, drill rivets, implanted razor blades, and local indentations. Despite of its poor spatial resolution, EIT is susceptible to minor conductivity variations [17], which makes it a promising technique for detection of damages that would disrupt the conductive network, including cracks and delaminations created during low velocity impact events.…”

Section: Introductionmentioning

confidence: 99%

“…Throughthickness holes were created with different diameters and at two locations of the specimen to evaluate the capability of EIT to detect multiple defects and its sensitivity to defect size. Differently from the studies reported in the literature, which use twill or plain fabrics [12,[15][16][17][18][19], the present work was conducted on unidirectional carbon fibre fabrics, having different layup configurations. It is relevant to study composites with this fabric construction, as these are frequently used in advanced application, such as aerospace and aeronautics.…”

Section: Introductionmentioning

confidence: 99%

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Damage localization on CFRP composites by electrical impedance tomography

Rocha

Fernandes²,

Ferreira³

et al. 2022

Materials Today Communications

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Damage localization on CFRP composites by electrical impedance tomography

Rocha

Fernandes²,

Ferreira³

et al. 2022

Materials Today Communications

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“…To address the different SHM levels, a variety of SHM techniques is available, including, but not limited to, acoustic emission (AE), 1,2 guided waves, 3–5 strain sensing, 6,7 vibration-based methods, 8–10 eddy currents, 11–13 and electrical impedance tomography. 14–16 Each technique has its own strengths and the selection of SHM techniques should rely on its application purposes. For example, vibration-based methods can be employed for anomaly detection, but are not suitable for precise damage characterization due to their inherent global approach.…”

Section: Introductionmentioning

confidence: 99%

Fusion-based damage diagnostics for stiffened composite panels

Broer

Galanopoulos

Benedictus

et al. 2021

Structural Health Monitoring

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Conducting damage diagnostics on stiffened panels is commonly performed using a single SHM technique. However, each SHM technique has both its strengths and limitations. Rather than straining the expansion of single SHM techniques going beyond their intrinsic capacities, these strengths and limitations should instead be considered in their application. In this work, we propose a novel fusion-based methodology between data from two SHM techniques in order to surpass the capabilities of a single SHM technique. The aim is to show that by considering data fusion, a synergy can be obtained, resulting in a comprehensive damage assessment, not possible using a single SHM technique. For this purpose, three single-stiffener carbon–epoxy panels were subjected to fatigue compression after impact tests. Two SHM techniques monitored damage growth under the applied fatigue loads: acoustic emission and distributed fiber optic strain sensing. Four acoustic emission sensors were placed on each panel, thereby allowing for damage detection, localization, type identification (delamination), and severity assessment. The optical fibers were adhered to the stiffener feet’ surface, and its strain measurements were used for damage detection, disbond localization, damage type identification (stiffness degradation and disbond growth), and severity assessment. Different fusion techniques are presented in order to integrate the acoustic emission and strain data. For damage detection and severity assessment, a hybrid health indicator is obtained by feature-level fusion while a complementary and cooperative fusion of the diagnostic results is developed for damage localization and type identification. We show that damage growth can be monitored up until final failure, thereby performing a simultaneous damage assessment on all four SHM levels. In this manner, we demonstrate that by proposing a fusion-based approach toward SHM of composite structures, the intrinsic capacity of each SHM technique can be utilized, leading to synergistic effects for damage diagnostics.

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“…Based on the different electrical features of the object in the sensitivity field, the ET techniques could be divided into electromagnetic tomography (EMT), electrical capacitance tomography (ECT), electrical impedance tomography (EIT), and electrical resistance tomography (ERT). Based on the principle of electromagnetic induction, the EMT can reconstruct the distribution state of the magnetic permeability for the medium in the sensitivity field [1][2][3][4][5][6]; Based on the principle of capacitance sensitivity, the ECT can reconstruct the distribution state of the dielectric constant for the medium in the sensitivity field [7][8][9][10][11][12][13][14][15][16][17]; Based on the principle of impedance sensitivity, the EIT can reconstruct the distribution state of the complex admittance for the medium in the sensitivity field [18][19][20][21][22][23][24]; Based on the principle of resistance sensing, the ERT can reconstruct the distribution state of the dielectric resistivity/conductivity for the medium in the sensitivity field [25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of a Finite Element Model for Electrical Resistance Tomography of Human Lungs

Xiao¹

2021

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To improve the reconstruction quality of electrical resistance tomography (ERT) images, this paper designs and optimizes the finite element model for human lungs. According to the computer tomography (CT) scan image on human chest, the entire simulation domain was divided into a region of lungs, heart, and spine, and a region of adipose tissue, and the boundary curve equations of each region were derived by the improved particle swarm optimization (PSO). Based on the prior knowledge, a structural model was established for human lungs; the ERT forward problem was solved by the finite element model based on grid reconstruction, and the calculated boundary voltage of sensitivity field was taken as the theoretical value. Next, two optimization goals were set up: improving the calculation accuracy of forward problem, and easing the ill-conditionedness of the sensitivity matrix; two variables were configured: the number of layers of the finite element model in each region, and the polar diameter ratio of the finite element nodes on each layer to the finite element nodes on the boundary of each region corresponding to the same polar angle. On this basis, the finite element model was optimized by the improved PSO to adapt to human lung ERT. Simulation results show that, under the same experimental conditions, the proposed finite element model could solve the forward problem more accurately, improve the ill-conditionedness of the sensitivity matrix and the Hessian matrix, and make the sensitivity distribution more uniformly, thereby enhancing the accuracy of image reconstruction.

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Impact Damage Detection in CFRP Composite via Electrical Resistance Tomography by Means of Statistical Processing

Cited by 23 publications

References 32 publications

Damage localization on CFRP composites by electrical impedance tomography

Damage localization on CFRP composites by electrical impedance tomography

Fusion-based damage diagnostics for stiffened composite panels

Design and Optimization of a Finite Element Model for Electrical Resistance Tomography of Human Lungs

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