Characterization of impact damage in fibre reinforced composite plates using embedded FBG sensors J....

Characterization of impact damage in fibre reinforced composite plates using

embedded FBG sensors

J. Frieden*, J. Cugnoni, J. Botsis, Th. Gmür

CompTest2011 5th International Conference on

Composites Testing and Model Identification14 Feb 2011 - 17 Feb 2011,

Ecole Polytechnique Fédérale de Lausanne, Switzerland

Swiss National Science Foundation, grant N° 116715

Objectives

Primary objective of this work:

• Impact localization and damage identification in CFRP plates with FBG sensors

Methods:

• Interpolation-based impact localization method using high rate FBG signals

• Inverse numerical-experimental damage identification method based on eigenfrequency changes and homogenized damage model

Objectives

Primary objective of this work:

• Impact localization and damage identification in CFRP plates with FBG sensors

Today’s focus:

• Influence of impact damage on the plate’s eigenfrequencies measured with FBG sensors

• Experimental characterisation of impact damage

• Finite element model of the plate with impact damage that reproduces the change of eigenfrequencies

Application

Introduction: Materials and specimen

CFRP cross-ply plate with 28 UD plies

[0°2, 90°2, 0°2, 90°2, 0°2, 90°2, 0°2]s

Embedded FBG sensors

Reference: Frieden J. et al, Composite Structures, 2010

Cross-section of plate

Sensitivity of eigenfrequencies to damage

Intact plate:Experimental modal analysis

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Damaged plate:Experimental modal analysis

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Impact1.7J – 6.7J

Experiment carried out on 8 plates using different impact energies.

Sensitivity of eigenfrequencies to damage

Relative frequency changes as a function of impact energy

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High resolution X-ray computed tomographySkyScan, model 1076 Aluminium filter : 1 mm thickness X-ray source voltage : 100 kV X-ray source power : 10 W Exposure time : 1750 ms

Experimental damage characterization

Damaged CFRP plate

Experimental damage characterization

Impact Location

Intralaminar cracks are rare and their occurrence is limited to a region located just beneath the impact point

Cross-section (Cut through plate thickness)Impact energy : 5.1 J

CT Resolution: 9 μm/pixelDistance between cross-section images: 9 μmTotal of 10 000 imagesConvert to black & white images

2 mm

Experimental damage characterization

Absorbed energy per unit of delamination area of 280 J/m2.

Detailed 3D delamination model

FE model in Abaqus 6.8-2:• Numerical modal analysis• 20-nodes brick elements with reduced

stiffness matrix integration• Mesh interfaces without node

connection between plies• Element size : 2 mm x 2 mm

Discrete delamination model

FE model in Abaqus 6.8-2:• Numerical modal analysis• 20-nodes brick elements with reduced

stiffness matrix integration• Mesh interfaces without node

connection between plies• Element size : 2 mm x 2 mm

Eigenfrequency changes are mainly due to delamination type damage

Homogenized damage model

Projected damage shape:•Rhombic area

Diagonal damage tensor D:Affected:•Transverse shear moduli

Not affected:•Longitudinal, transverse and through-the-thickness Young’s moduli•In-plane shear modulus•Poisson’s ratio

Incident energy [J] 3.37 5.06 6.75 6.75

Projected area [cm2] 10.7 16.0 20.7 20.6

Length [mm] 56.7 72.0 87.4 81.6

Width [mm] 37.8 47.2 47.3 47.3

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GDG

GDG

Material properties:•Through-the-thickness homogenized material properties

Homogenized damage model

Diagonal damage tensor D:Affected:•Transverse shear moduli

Not affected:•Longitudinal, transverse and through-the-thickness Young’s moduli•In-plane shear modulus•Poisson’s ratio

Values of D13 and D23 identified through least square optimization:Minimize error between experimentally measured frequency change and numerically calculated frequency change

Projected damage shape:•Rhombic area

Material properties:•Through-the-thickness homogenized material properties

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131313

1ˆ

1ˆ

GDG

GDG

Homogenized damage model

Diagonal damage tensor D:Affected:•Transverse shear moduli

Not affected:•Longitudinal, transverse and through-the-thickness Young’s moduli•In-plane shear modulus•Poisson’s ratio

Values of D13 and D23 identified through least square optimization:Minimize error between experimentally measured frequency change and numerically calculated frequency change

Incident energy [J] 3.37 5.06 6.75 6.75

D13 [%] 84.4 86.1 88.4 91.9

D23 [%] 85.5 90.2 92.5 93.9

Projected damage shape:•Rhombic area

Material properties:•Through-the-thickness homogenized material properties

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131313

1ˆ

1ˆ

GDG

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Prediction of eigenfrequency changeExperimentally measured damage size

Using the previously determined values of D13 and D23

Damage identification procedure

Values of D13 and D23 are fixed to 94 %

Parameters to identify:

• Damage position

• Damage surface

• Damage aspect ratio

Reduce discrepancy between experimentally measured eigenfrequency changes and numerically calculated eigenfrequency changes

Iterative minimization algorithm: Levenberg-Maquardt

Application example

Impact energy: 3.4 J

Predict the impact location

Identify damage size and position

Application

Reference measurements before impact:

• Arrival time delays for interpolation-based localization method

• Eigenfrequencies of intact plate

Application: Reference data

• Non-destructive hammer impacts• Grid of 3 x 3 reference points• Acquisition rate of FBG sensors : 1 GHz• Arrival time delays obtained by threshold method

Application: Reference data

• Non-destructive hammer excitation• Grid of 3 x 3 reference points• Acquisition rate of FBG sensors : 100 kHz• Eigenfrequencies obtained by modal curve fitting

FRF

Application: Impact

• Impact with energy of 3.4 J• Acquisition rate of FBG sensors : 1 GHz

Application: Impact

• Impact with energy of 3.4 J• Acquisition rate of FBG sensors : 1 GHz

Application: Identification of damage

Experimental data

Application: Identification of damage

Parameters to identify:

• Damage position

• Damage surface

• Damage aspect ratio

Initial guess for the damage identification:

• Predicted impact location

• Damage surface = 1 cm2

• Damage aspect ratio = 1

Experimental data

Application: Identification of damage

Convergence graph

Identification resultsPredicted eigenfrequency changes

compared to experimental eigenfrequency changes

Conclusion

• Embedded FBG sensors provide very accurate strain data for modal analysis and acoustic wave sensing.

• The eigenfrequency changes can be mainly attributed to delamination type damage.

• The simple homogenized damage model allows to reproduce the eigenfrequency changes.

• The damage size can be identified by a numerical-experimental optimization method based on eigenfrequency changes.

Thank you

Introduction: Fast FBG interrogation

FBG sensors for modal analysis

1st mode

3rd mode

2nd mode

4th mode