Non-destructive testing of composite materials by means of active thermography-based tools

Non-destructive testing of composite materials by means of active thermography-based tools

Accepted Manuscript Review Non-Destructive Testing of Composite Materials by means of Active Thermography-Based Tools Miguel Lizaranzu, Alberto Lario,...

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Accepted Manuscript Review Non-Destructive Testing of Composite Materials by means of Active Thermography-Based Tools Miguel Lizaranzu, Alberto Lario, Agustín Chiminelli, Ibán Amenabar PII: DOI: Reference:

S1350-4495(15)00051-1 INFPHY 1749

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Infrared Physics & Technology

Received Date:

20 October 2014

Please cite this article as: M. Lizaranzu, A. Lario, A. Chiminelli, I. Amenabar, Non-Destructive Testing of Composite Materials by means of Active Thermography-Based Tools, Infrared Physics & Technology (2015), doi: http://

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Non-Destructive Testing of Composite Materials by means of Active Thermography-Based Tools Miguel Lizaranzu1, Alberto Lario1, Agustín Chiminelli 1, Ibán Amenabar



Research, Development and Technological Services Area. Aragon Institute of Technology (ITA). C/ María de Luna 8,, 50018 Zaragoza - Spain 2

Inspection and Measurement Department, IDEKO-IK4 Technological Centre, C/ Arriaga industrialdea 2, E-20870 Elgoibar, Spain

Abstract Infrared analysis tools are nowadays widely used for the non-destructive testing of components made up in composite materials, belonging to many different industrial sectors. Being a noncontact method, its capability for the inspection of large areas in short periods of time justifies the great number of works and technical studies that can be found in this field. The growing interest in the technique is also supported by the development, during recent years, of increasingly powerful equipment and data analysis tools. In order to establish a base of knowledge to assist defect identification in real components inspections, the design and manufacturing of inspection samples including controlled defects, is a frequently used strategy. This paper deals with the analysis, by means of transient active thermography, of a set of inspection patterns made out of different composite materials and configurations that can be found in the wind turbine blade manufacturing industry. The design and manufacturing of these patterns are described, including different types of representative defects, stack configurations and composite manufacturing techniques. Reference samples are then inspected by means of active thermography analysis tools and the results obtained are discussed. Keywords: Composite Materials, Defects, Non-destructive testing, Infrared Thermal Analysis. Corresponding Author: Miguel Lizaranzu [email protected] ,Tel.: (+34) 976 011178; Fax: (+34) 976 011 89. Instituto Tecnológico de Aragón (ITA, C/ María de Luna 8, 50018 Zaragoza - Spain Lead Author: Miguel Lizaranzu Fernández, PhD. Order of Authors: Miguel Lizaranzu Fernández, PhD; Alberto Lario, Junior Researcher; Agustín Chiminelli PhD; Ibán Amenabar, Senior Researcher.

1 Introduction Infrared-based tools, such as thermal imaging technologies, are nowadays widely adopted for the inspection of components and structures in industrial sectors such as aeronautics, transport, wind power, civil engineering and electronics, among others. [1-8] In contrast with passive thermography, active thermography (AT) requires the component under study being stimulated by an external source. The thermal excitation needed to conduct the analysis can be provided by means of different devices, including mechanical (vibrothermography) [9,10], electrical (Eddy current thermography) [11] or thermal systems (step heating, flash, lock-in, pulsed/transient), [12-15]. In short, the idea is to obtain information about the presence of internal defects from the thermal response of the part being analysed, since these will influence, in some way, the flow of the heat through the material. Once a component is excited, its thermal response is analysed, usually recorded by means of a thermographic camera and afterwards processed using specific analysis software. The final result is, in most cases, a set of thermal images representing the surface heat emission in which contrasts generated by the presence of internal defects can be detected and identified. This graphic representation can be built not only from the time response emission of the part itself, but also as result of different analytic operations applied to the original signals. Several studies have shown good or even excellent results in using active thermography NDT capabilities applied to different composite materials configurations and defects typologies: delaminations [6,16], impact damage [17], adhesive and welded bond defects [2,18], reparation patches [3,19], fatigue damage [20],different nature inclusions [21], etc. The use of inspection reference gauges or samples including known and controlled defects prove to be a key tool for defining inspection strategies, optimising parameters, and defects recognition, as well as for establishing the inherent limitations and sensitivity thresholds of the method [1,3,4,14,15,17,18,22,23]. This paper mainly focuses on defects that can be found in the manufacturing of wide composite structures, particularly on wind turbine blades, in which a wide range of different materials and configurations can be involved, depending on the design and processing strategies. Therefore,

different base materials (carbon fibre, glass fibre), processes (pre impregnated fibre, resin infusion) and configurations (monolitic, sandwich and adhesive joint) were considered in the study.

2 Sample design and manufacturing Three samples were proposed for the study, each of them containing a set of controlled defects, which were chosen taking into account the inherent features of the manufacturing conditions and processes involved. Table 1 summarises the samples configuration.



Adhesive joint


Size [mm]





24mm [0º] 40 600g/m2 UD CE

5mm [0º]5 1600 g/m2 UD GE 5mm Epoxy Adhesive 5-10-20mm [0º]40 1600 g/m2 UD GE

0,3mm Gel Coat 2 mm 1200g/m2 TX Glass 10mm PCV foam core 80g/m2 2 mm 1200 g/m2 TX Glass


Defect size [mm]

Defect thickness [mm]




Polyethylene film



Silicone paper



Cutter blade



Depth [mm]






20 (all width)



Massive adhesive void


Non sticking zone with the upper substrate

30x30 --


Inclusions of pre-cured adhesive drops


Air voids entrapment


Dry fibre.


0,3 --

Gel coat disposition non uniform (drops)

2 to 10

Table1: Materials and configuration of the manufactured samples

2.1 Carbon fibre sample A monolithic 24 mm-thick [0º]40 lay-up of 600g/m2 carbon/epoxy pre-preg (CE) Sparpreg from GURIT sample was manufactured by means of vacuum bag compaction and oven curing. Intermediate vacuum compactions at different stages of the stack sequence were performed, in order to ensure no air entrapment in the process. Three types of defects were introduced in the stacking sequence at different depths: delaminations, inclusions and fibre wrinkles.


For delamination simulations, polytetrafluoroethylene (PTFE) films are often used [1,4,13], looking for interlaminar discontinuity between layers. However, the inclusion of this film inside the laminate affects the heat flow, since a new layer is inserted in the stack sequence. Small thicknesses of PTFE films are commonly used, in order to minimize this undesirable effect [4]. In this sense, a different technique for the generation of the artificial de-lamination has been used in this work, seeking a more realistic simulation method. Two pre-cured single-layer plies were introduced inside the laminate and, in order to avoid localised thickening, equal patches were cut off from the preimpregnated layers to be filled subsequently with the pre-cured layers. Following this technique, three de-laminations were introduced in the carbon fibre laminate at depths of 2mm, 4mm and 10mm. Then, inclusions of different materials, such as polyethylene film (0.08mm thickness) and silicone paper (0.08mm thickness) from pre-preg material supports, metallic pieces from cutter blades (0.3mm thickness) and latex pieces from gloves (0.065mm thickness) were introduced at depths of 2mm, 4mm and 10mm. Finally, a wrinkle was created by double bending one pre-preg layer, increasing the total local thickness of the piece by 1.6 mm. The wrinkle was formed at a depth of 15mm. The sample design is represented in figure 1, and figure 2 shows the sample once manufactured.

Fig 1: Carbon sample design

Fig 2: Carbon sample manufactured

2.2 Adhesive joint sample For the manufacturing of the adhesive joint sample, a bond between two pre-cured substrates made of glass fibre/epoxy resin pre-preg was proposed. The lower substrate used had a thickness of 5mm and the upper one had an increasing thickness of 5mm, 10mm, and 20mm, defining this way three different inspection zones (A, B and C respectively). The joint was made by means of an epoxy bi-component adhesive. 2

In a first step, both substrates were manufactured from 1600 g/m pre-preg UD glass fibre/epoxy resin (WE91-1 from Gurit), using vacuum compaction and cured in oven following the specifications of the material supplier. Then, a thick layer of adhesive Spabond 340LV was spread over the lower substrate, and four different types of defects were included: -

30mm-diameter massive adhesive void across the whole 5mm thickness.


30x30mm non sticking zone on the upper substrate, by means of pre-cured thin films of


adhesive placed between the top surface of the bulk adhesive and the top substrate. -

Inclusions of pre-cured adhesive scraps.


Air void entrapment by means of air injection inside the adhesive mass.

This set of defects was introduced at the three different zones of the sample. Finally, metallic gauges were used on the perimeter to ensure a uniform 5mm-thick adhesive thickness bond. A curing cycle of 72 hours at 25ºC was applied under uniform compacting pressure prior to the final sample mechanisation. Figure 3 represents a schematic view of the sample design. Figure 4 shows the adhesive sample, once manufactured.

Fig 3: Adhesive sample design

Fig 4: Adhesive sample manufactured

2.3 Sandwich sample The sandwich configuration sample was manufactured using resin infusion (RI) moulding process. As main defect, dry fibre zones were induced, one of the most critical defects in liquid resin processes. The sample consists on a 10mm-thick 100gr/m2 PCV core and two 1200g/m2 layers of tri-axial glass fibre fabric as reinforcements, together with low viscosity infusion epoxy resin, PRIME 20LV from Gurit. A standard vacuum-assisted infusion resin process was applied. As mentioned, dry fibre zones were generated, by means of a infusion mesh, that allows to control the front resin flow during the process. The part was then cured in oven, following the cycle recommended by the resin manufacturer. In a second phase, a gel coat layer of 0.3mm thickness was placed at the side of the sandwich, compacted by vacuum and cured for 48 hours at room temperature. This way a dry fibre zone was obtained, covered by a gel coat layer. Figure 5 represents the sample design and figure 6 shows the sample ready for inspection.

Fig 5: Sandwich sample design

Fig 6: Sandwich sample manufactured

3 Active Thermography inspections

3.1 Pulsed active thermography: brief introduction Pulsed or transient active thermography is one of the most popular IR-based inspection techniques. The part to be analyzed is heated by an external source during a predetermined period of time and with a specific power profile. The resulting thermal surface radiation of the component is monitored using a thermographic camera. The response of the part will depend on the properties of its constituent materials: thermal (conductivity, diffusivity, effusivity, and specific heat), spectral (emissivity, absorption, reflection) and others (porosity and density) [3, 24-26]. The thermal diffusivity of a material is the measure of its thermal inertia, i.e. gives information about how quickly a material reaches its thermal equilibrium. Diffusivity is given by:


k ρC p


where α is the thermal diffusivity (m2s-1), k is the thermal conductivity (Wm-1K-1), ρ is the density (kg -3



m ) and Cp is the specific heat capacity (J kg K ).

Considering a one-dimension solution for a semi-infinite isotropic solid [27], the temperature of the part, at a time (t) and depth (z), is given as:

T( z ,t ) = T0 +

 z2   exp − kρC p tπ  4αt  Q


where Q is the energy absorbed by the surface (J/m2), T0 is the initial temperature (K), k is the -1 -1


thermal conductivity (Wm K ), ρ is the density (kg m ) and Cp is the specific heat capacity (J kg 1



K ).

At the surface (z=0), Eq.(2) can be written, as:

T( 0,t ) = T0 +



e tπ 1/2

where e is the thermal effusivity (W s



m K ), a measure of a material’s ability to exchange

thermal energy with its surroundings. Thermal effusivity can be obtained by:

e = kρC p


Once the component is excited, the heat front travels through the specimen. As time elapses, the presence of defects (voids, pores, inclusions, etc.) inside the material structure, which thermal properties differ from the substrate ones, affect the heat flow within the material, leading to temperature gradients on the surface. Thermographic cameras register the surface thermal radiations and represent them as thermograms, where temperature gradients along the surface are shown as image bright contrasts.

3.2 Experimental set up and thermogram representations For this work, the equipment used for the samples inspections comprises two 2.5 kW power halogen lamps, an excitation source, IR-non destructive testing hardware, a PC+software for Transient and lock-In (AT-Automation Technology), and a thermographic camera (FLIR Systems, model P660). [28, 29] The evaluation method used in the inspections is the pulsed (or transient method), both in reflexion (heat source and camera at the same side of the sample) and transmission (heat source and camera at opposite sides of the sample) mode set ups.

The post-processing signal involves, in a first step, the construction of a polynomial function, approximating the measured signal pixel by pixel. Further calculation approaches are based on this polynomial expression, removing noises and enhancing the quality of the results [30, 31]. Two approaches were considered for this project: root model and e-model The root model option builds the polynomial function with a root approach for the analytic approximation of the measured temperature signal, since the e-model option uses a polynomial function with an exponential approach. In both cases, even if the complete data sequence is used for calculating the result image, the evaluation is only applicable in the temperature profile dropping interval. Different evaluation alternatives are then suitable; being the most extended the reconstruction of the infrared image sequence analytic approximation, and its 1


and 2


derivations. The first

derivation provides particularly useful information, since it is easy to detect inflection points in the time evolution of the surface temperature, produced when the thermal front reaches a defect which affects somehow its propagation rate. This will depend, as explained before, on the nature and geometry of the defect. Pulse phase evaluations were also used in the tests. In this case, a Fourier transform of the recorded signal is performed. This method gives both an absolute signal and a phase spectrum as a function of the frequency. By way of an example, Figure 7 shows different possibilities for the thermogram representations obtained from the carbon/epoxy sample described above, applying a root model analysis. Three pairs of curves were plotted, corresponding with the surface heat radiation at three points of the th

sample, and their 5 degree polynomial approximation. Point “A” had no defect inside, Point “B” had a 0.3mm metallic part, placed at a depth of 2mm and Point “C”, had an insert made from a 0.065 mm-thick latex piece, placed at a depth of 2mm. The two thermograms represented correspond to the radiation sequence and the first derivate, extracted both at t=66s. With point A being the radiation reference (no defect), the dark zone at B in the sequence image indicates a lower temperature in the surface. This is due to the higher thermal effusivity of the metallic insert that increases the heat transfer ratio, “cooling” the surface. This effect is also

represented in the first derivate image, which shows a clear indication of this point, that to say, a higher cooling ratio in this particular zone. The opposite phenomenon occurs at point C, where the latex piece acts as a barrier to the heat flow into the composite stack. A higher surface temperature is then detected, together with lower cooling ratios.

Figure 7: Heat emission curves and post-processing alternatives.

3.3 Experimental results Next, the inspection results are described for the three samples analysed. Table 2 summarises the tests parameters defined for each case.


AT Method

External heating input [s]

Registration time [s]

Excitation source modulation

Carbon monolitic laminate

























Glass fibre adhesivated sample Sandwich sample

Table 2: Active Thermography tests parameters

Modulation Images min. - max. recorded [%]

Evaluation method / representation Root model / Sequence Root Model / Pulse Phase Root Model / 1st derivate e-model / 1st derivatereconstruction

3.3.1 Carbon fibre sample Figures 8 and 9 were obtained from the time sequence of the surface heat radiation signal, taken at different times (27s and 38s respectively). As can be seen, almost all defects close to the surface (2mm depth) were detected. Clear indications represent the presence of lower effusivity materials with respect to the base material: de lamination (1), silicone paper (2) and latex (4) inclusions. In the other side, the presence of the metallic blade (3) generates a darker zone, as explained before. The wrinkle presence, not clearly visible at the first registration shots, appears later as a narrow vertical dark band (5). In the other side, polyethylene inclusion cannot be detected. Further analysis have shown that at the curing temperatures, the polyethylene film melts.

Fig 8: Carbon sample thermogram: sequence (t27s)

Fig: 9 Carbon sample thermogram: sequence (t38s)

3.3.2 Adhesive sample With regard to the zone with a thickness of 5mm on the upper substrate (left side on Figure 10), all four defects can be observed from the TA inspection results: (1) massive adhesive void, (2) air bubbles trapped, (3) pre-cured adhesive scraps and (4) lack of adhesion. However, as the top layer thickness increases (10mm and 20mm) no defects can be clearly detected with a reflexion set up.

Fig 10: Adhesive joint sample thermogram: pulse Phase st

Figures 11 and 12 correspond with the graphic representation of the 1 derivate of the surface radiation time sequence, at different elapsed times, t=54 s and t=165 s. Firstly, all the defects were detected at zone A of the sample (5mm thickness substrate), including a non-controlled air entrapment (5). Furthermore, as time elapses, the massive void present at zone B (10mm thickness substrate) was detected as a dark signal (6).

Fig 11: Adhesive joint sample thermogram.1st derivate (t54s)

Fig 12: Adhesive joint sample thermogram. 1st derivate (t165s)

3.3.3 Sandwich sample Figure 13 corresponds to the first derivate of the signal, at early stages of the inspection. Dry fibre indications start to raise (1 and 2), with gel coat drops accumulation and thickness irregularities being clearly visible as dark indications (3 and 4). Figure 14, taken from the signal reconstruction, shows a dry fibre zone easily detected as a wide clear zone (1), together with some impregnation defects following the +-45º fibre layout (2).


Fig 13: Sandwich sample thermogram. 1 derivate (t1.5s)

Fig 14: Sandwich sample thermogram. Signal reconstruction (t7s)

4 Conclusions The results obtained in this study active confirm that Active Thermography is a suitable method for defect detection in composite material parts. Concerning the samples analysed in this study some points are worth highlighting. The inspection of the carbon sample gave good results when the defects were near the surface being inspected (2m-3mm). For this particular sample a new technique has been proposed for controlled realistic de lamination reproduction, based on the layout of pre-cured pairs of single layers. This methodology has shown to be effective to generate controlled de-laminations without the introduction of films/inserts that can mislead the conclusions about the actual detection capacity.

Concerning the adhesive sample, reflexion set up offers good results with 5mm-thick substrates, but for 10mm-thick substrates transmission set up shows to be a more powerful option. However, transmission set up can hardly provide information about the defect depth, since the heat flow has to travel through the whole material thickness before being detected by the camera.

The results obtained in the infusion panel with a presence of dry fibre are very clear. Sandwich configurations usually fit well with active thermography capabilities, since “low” thickness skins are supported by usually low conductivity core materials. Obviously, only reflexion set up is suitable for this kind of configuration.

The most remarkable features of active thermography have been corroborated during this paper, such as easy test set up (no contact needed), short inspection times (seconds in most cases), and the possibility of inspecting large areas. The results do depend on the thermographic camera resolution, heat sources, and required minimum defect size/accuracy ratio, but areas of around 0.5m2 -1m2 or even higher can be taken as a reference.

It is also important to bear in mind the limitation of this method, such as the depth, nature and dimensions of defects, and the fact that its presence must imply a heat flow distortion inside the

part, at least locally. In this sense, ratios defect diameter/depth=1 are commonly taken as a reference for establishing the active thermography method capabilities. Some others considerations must be also taken into account. The implementation of a particular inspection strategy to different parts or configurations is not obvious, since the results strongly depend on geometries, thickness, materials, etc. Therefore, in order to achieve a robust inspection tool, the features and details of the part should be known: geometry, materials, configurations, etc., together with a good definition of the type of defects to be detected. A proper design and an accurate manufacturing of reference samples including controlled defects is essential in order to establish, prior to the inspection, test parameters, post-processing strategies and defect identification criteria.

Tables Table 1: Materials and configuration of the manufactured samples Table 2: Active Thermography tests parameters

Figures Fig 1: Carbon sample design Fig 2: Carbon sample manufactured Fig 3: Adhesive sample design Fig 4: Adhesive sample manufactured Fig 5: Sandwich sample design Fig 6: Sandwich sample manufactured Fig 7: Heat emission curves and post-processing alternatives Fig 8: Carbon sample thermogram: sequence (t27s) Figure 9: Carbon sample thermogram: sequence (t38s) Figure 10: Adhesive joint sample thermogram: pulse phase st

Figure 11: Adhesive joint sample thermogram: 1 derivate (t54s) Figure 12: Adhesive joint sample thermogram: 1st derivate (t165s) st

Figure 13: Sandwich sample thermogram: 1 derivate (t1.5s) Figure 14: Sandwich sample thermogram: signal reconstruction (t7s) Funding sources This work has been developed as a part of a public found project “Proyecto Singular Estratégico Alexandría”, supported by the Spanish Ministry of Science and Innovation and cofinanced by

Fondo Europeo de Desarrollo Regional (FEDER).

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• • • • •

Active Thermography is evaluated as NDT technique, analyzing different composite materials configurations A set of samples are manufactured, including a monolithic layup, a sandwich configuration and a bonded joint. Defects such as inclusions, voids, bubbles, de laminations, lack of adhesion, wrinkles and dry fiber zones are introduced. Samples are inspected covering different methods for heating, evaluation and postprocessing methods. Results are analyzed and compared in terms of detection capabilities.