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Moisture contamination detection in adhesive bond using embedded FBG sensors
Mechanical Systems and Signal Processing 84 (2017) 1–14
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Moisture contamination detection in adhesive bond using embedded FBG sensors Magdalena Mieloszyk a,n, Wiesław Ostachowicz a,b a Mechanics of Intelligent Structures Department, Institute of Fluid-Flow Machinery, Polish Academy of Sciences, 14 Fiszera Street, 80-231 Gdansk, Poland b Faculty of Automotive and Construction Machinery, Warsaw University of Technology, 84 Narbutta Street, 02-524 Warsaw, Poland
a r t i c l e i n f o
abstract
Article history: Received 14 October 2015 Received in revised form 30 June 2016 Accepted 2 July 2016
The paper presents an application of embedded fibre Bragg grating (FBG) sensors for moisture contamination detection in an adhesive bond between two composite elements. FBG sensors are a great tool to Structural Health Monitoring of composite structures due to their high corrosion resistance as well as their small size and weight. Adhesive bonds are very popular in many industrial branches. One of the major problem limits the use of an adhesive joints is they sensitivity on water form ambient. Even the 1% of moisture affects an adhesive bond layer strength. FBG sensors can be use for detection of even a small amount of moisture concentration (1–3% of sample weight). It can be also used for determination of moisture concentration changes during both soaking and drying processes. & 2016 Elsevier Ltd. All rights reserved.
Keywords: Fibre Bragg grating Moisture contamination Epoxy Adhesive bond
1. Introduction Composite elements (both CFRP (carbon fibre reinforced polymer) and GFRP (glass fibre reinforced polymer)) are widely used for load carrying structures in aircraft, marine, civil engineering, where the specific strength and specific modulus are of importance, e.g. aircraft wings, helicopter rotor blades, wind turbine blades. Adhesive bonds in comparison with conventional mechanical joining techniques of composite materials present numerous advantages such as: more homogeneous stress distribution, higher stiffness, high fatigue strength [1,2]. Adhesive bonds are also lightest in comparison with classical fastening techniques such as welding, riveting and mechanical fastening. So, in lightweight composite structures, adhesive bonding is the most appropriate joining technique [3]. For this reason, adhesive bonds are more and more popular in many industrial branches (e.g. automotive [2], aircraft [2,4]). The most common cause of environmental degradation in bonded joints involves the absorption of moisture into the adhesive layer [5,6]. Such problem especially occurs when an adhesive contains epoxy resin. When such material is exposed to hygrothermal environment, it absorbs moisture which greatly affects its thermo-mechanical properties that results in significant decreasing of the durability and reliability of the structural element with an adhesive joint [5]. The paper is organised as follows. Firstly, problems referred to moisture influence on epoxy based adhesives are presented. Then FBG (Fibre Bragg Grating) sensors and their utility for soaking process monitoring are presented and discussed. FBG sensors are used for measurement of strain induced by moisture in adhesive bond between two composite elements. n
Corresponding author. E-mail address: [email protected] (M. Mieloszyk).
http://dx.doi.org/10.1016/j.ymssp.2016.07.006 0888-3270/& 2016 Elsevier Ltd. All rights reserved.
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Finally, the conclusions from investigations are drawn. 1.1. Moisture influence on adhesive bond Moisture absorption is recognised to be one of the most important causes of impairing the mechanical properties of polymers and their composites due to physical changes at a microscopic level [7]. One of the problems with polymers (like epoxy) is their tendency to absorb moisture from ambient. The moisture affects a polymer properties, like dimensional stability, mechanical [5,8–10], chemical [8,10] and thermophysical properties [9,11]. The moisture (1% of water mass gain) influence for every epoxy and hardener combination results in: a lowering of Tg (glass transition temperature) by about 10 °C, a loss of about 10% in storage modulus and 15% in tensile strength [7]. Similar problems occur also for adhesive layers. The most important degradation effects due to moisture contamination in adhesive layers are: plasticisation [3,4,6] cracking [4] and hygroscopic expansion of the adhesive [3,6] and deterioration of the adherend/adhesive interface [3,4,6]. Moisture contamination occurs in an adhesive bond can also travel throughout adhesive/adherend interface [6] to composite material and affecting the fibre-matrix interface bond [9,12], leading to loss of mechanical integrity of whole structural element. It is worth mention that structural elements with adhesive bonds consist of parts with different material properties (e.g. coefficients of thermal expansion, moisture sensitivity). The different sensitivity of composite material and adhesive on moisture can results in similar problem like occurs in FRP composites, where material properties of matrix and fibres differ [11]. 1.2. Fibre Bragg grating sensors A Bragg grating is a permanent periodic modulation of the refractive index in the core of a single-mode fibre optic. It is made by exposing the core of the optical fibre to an interference pattern of intense UV laser light [13,14]. The length of a FBG sensor is typically in the range of 1–25 mm and depends on its application. The periodic perturbation in the core refractive index allows coherent scattering to occur for a narrow wavelength band of incident light travelling within the fibre core. A strong narrowband back reflection of light is generated, centred around the maximum reflecting wavelength λB value when the resonance condition, or phase match, is satisfied:
λB = 2neff Λ,
(1)
where neff is the effective refractive index and Λ is the periodicity of the perturbation [15]. Bragg wavelength change due to strain and temperature change are described by a relationship
ΔλB =( 1 − ρϵ ) ϵ+( α+ξ ) ΔT λB
(2)
where α means thermal expansion coefficient, ξ – thermooptic coefficient, ρε – elastooptic coefficient of fibre optic material. Longitudinal strains ε act on the periodicity of the perturbation Λ (photoelastic effect), while temperature affects both the effective refractive index neff (thermo-optic effect) and the periodicity of the perturbation Λ (thermoelastic effect) [16,17]. The key point of FBG sensors is their wavelength-encoded nature, which is the absolute parameter providing repeatable measurements [18]. FBG sensors can be written on both silica glass and polymer optical fibres [19]. FBG sensors written on silica fibre optics have many advantages like small size and weight, high multiplexing capabilities, immunity to electromagnetic field interference, high corrosion resistance (both water and chemicals) and no calibration needs [13,15,20–22]. FBG sensors are sensitive to both strain [23] and temperature [24]. The changes in those two parameters are linearly proportional to changes in the measured wavelength [15]. FBG sensors can be mounted onto a structure surfaces [16,25] or embedded [26–31] into the material of a structural element during the manufacturing process. They can be also included into adhesive layer during the process of joining two structural elements. Kim et al. [32] embedded FBG sensors in a wind turbine blade to its deflection estimation. FBG sensors can be used for adhesive bond lifetime monitoring [1]. Canal et al. [33] evaluated the feasibility of using FBG sensors to monitor the distribution of strains developed along the bonded region in single lap shear specimens. Sulejmani et al. [1] presented Bragg grating based shear stress optical sensors application for in situ disbond monitoring at adhesive bonds. The presented method allows to determine shear stress distribution in an adhesive bond line and detect a disbond of at least 100 mm while the exact loading level does not to be known. Nowadays FBG sensors are integral parts of SHM systems installed on different structures: bridges [16,22,28], offshore platforms [25,34], buildings [35], marine vessels [36,37] and aircraft structures [38–40]. The advantages of polymer FBG sensors are their inherent fracture resistance, low Young's modulus, high flexibility, high temperature sensitivity [19,41,42]. For composite application the most important are high temperature sensitivity, large strain range and the absence of buffer coating [42]. One of the main disadvantage of polymer FBG is strong loss of the transmitted signal so they have to be glued to silica fibre to be connected to measurement unit [19,41]. The other problem with polymer FBG is their negative thermo-optic coefficient that results in wavelength decrease with temperature increase
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[19,41]. So temperature change influence is not easy remove from measurements performed in ambient temperature. The FBG sensors sensitivity on humidity and temperature are strongly correlated [19]. Polymer FBG sensors are sensitive to relative humidity, temperature and strain [42]. This is in contrast to silica glass fibre FBGs which do not show any intrinsic humidity sensitivity, even a recoated silica FBG showed a humidity sensitivity 125 times lower than that of the polymer FBG [42]. The affinity for water of poly(methyl methacrylate) (PMMA) material commonly used in polymer FBG sensors, leads to a swelling of the fibre and an increase of refractive index, both of which contribute to an increase in the Bragg wavelength of a FBG written in the fibre [42]. This feature allows it to measure amount of water in air [19,42]. Rajan et al. [41] compared strain and temperature influence on silica and polymer (PMMA) FBG sensors with similar length (10 mm) embedded in composite material. Due to strong loss of the polymer they used short length (12 cm) fibres. The composite samples were unidirectional 0/0 GFRP with 8 layers. The embedded polymer FBG sensors outer diameters (240–260 mm) [41] are similar to typical silica glass fibres. Polymer FBG sensors are better candidate to measure temperature, while silica FBG sensors can more accurately measure strain in GFRP composite [41]. The idea of utility of FBG sensors for moisture detection is nowadays investigated by researchers around the world. The first type of relative humidity FBG sensors based on silica fibre optics covered by special moisture sensitive coats [43,44]. Lin et al. [45] developed a fibre optic humidity sensor fabricated by coating a moisture sensitive polymer film to FBG. Compared to conventional capacitive and resistive humidity sensor, the FBG coated with polyimide had unique advantages in terms of high measurement accuracy. The measured relative humidity range was from 11.3 to 97.3%. Another types are FBG sensors written on PMMA material. The sensitivity of polymer FBG sensors on humidity allows them to be applied for monitoring humidity level in food storage, paper manufacturing [42] or to quantifying the small amount of water present in jet fuel [46]. Zhang et al. [42] developed polymer FBG humidity sensor that was tested in environmental chamber in relative humidity in a range from 30% to 90% and fixed temperature (25 °C). Rajan et al. [47] developed relative humidity sensor system based on etched polymer FBG. The analysed relative humidity was in a range 10%–90%. Another types of optical fibres are microstructured optical fibres with numerous air-holes along the length of the cladding. Microstructural fibres are selective sensitive to only one measurand (axial strain, hydrostatic pressure or transverse loading) [1]. FBG incorporated microstructural fibres sensors can induce a contra-directional coupling between forward and backward fibre modes through resonant scattering and thus perform very well in strain, pressure and microfluidic refractive index sensing applications. FBG sensors written on such fibres can be used for microfluidic and gas sensing applications [48]. Woyessa et al. [49] analysed influence of annealing temperature on effect of humidity on PMMA based microstructured polymer optical FBG and the resulting humidity responsively. The humidity response was analysed at fixed temperatures: 25 °C, 50 °C and 75 °C for relative humidity in a range from 10 to 90%. The process of moisture absorption results in increasing of material volume. This process can be observed as internal strain changes, so it could be measured by embedded fibre optic sensors, e.g. FBG sensors. Karalekas et al. [5] analysed utility of long FBG sensors to monitor the effects of hygrothermal ageing on the axial strains in a cylindrical epoxy specimen with a centrally located optical glass fibre that contains a long Bragg grating sensor. The specimen was immersed in distilled water at 50 °C for 2330 h. The wavelength changes were used to measure resin conversion, coefficients of thermal expansion (CTE) and moisture expansion (CME) and to monitor strains induced by moisture. The FBG response also indicates the appearance of progressive debonding after sufficient exposure to moisture [5]. Lai et al. [7] performed similar experimental investigation on cylindrical specimens made of epoxy with an axially located optical fibre. Strain data from the sensor and from a micrometre were combined with experimental absorption curves to determine the resin's coefficient of moisture expansion. The data indicate that diffusion and CME depended on moisture concentration. Analysis of the experiments was carried out by numerical simulations of heat transfer, and moisture diffusion. The simulated results correlated well with the experimental data [7]. The distributed strains measured by long Bragg grating sensor were used to monitor the moisture induced strains during ageing and tracks debond growth at the interface, generated during ageing [50]. 1.3. Motivation As it was presented before even a small amount of moisture negative influenced on polymer (epoxy) strength parameters. Epoxy resin is one of the most important ingredients contained by many adhesives and composite matrix. FBG sensors due to small dimensions can be embedded in material without significant changes of its properties. From a variety of FBG sensor types presented in Section 1.2 FBG sensors written on silica glass fibres were chosen. The FBG sensors with special polymer coating are mostly applied for air humidity [43,44]. The advantage of using a polymer FBG sensor in this application could be the Young modulus value for PMMA (around 5.3 GPa [19]) that is similar to the glue (Table 1) in the adhesive layer presented in the paper on contrary to silica fibres used in the experimental investigation presented in the paper. But their main disadvantages are strong signal loss during transmission and negative thermooptic coefficient [19,41]. As it was described by Karalekas et al. [5] and Lai et al. [7] an embedded FBG sensor can be also used for moisture detection in epoxy specimen up to 6% of sample weight. The motivation of the investigation presented in the paper is determination of possibility of detection moisture (up to 3% of sample weight) in an adhesive layer between two composite elements.
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Table 1 Glue properties [51]. Parameter
Value
Unit
Tg (dry) Tg (wet) Tensile strength at 25 °C Tensile modulus at 25 °C Elongation at 25 °C at break Compressive strength at 25 °C Cure temperature Cure time
78 68 46 4.237 0.017 68.9 25–93 3–5
°C °C MPa GPa % MPa °C day
Additional parameters
Good gap filling capabilities Room temperature storage Low toxicity
Additionally the possibility of monitoring of soaking and drying processes based on FBG sensors strain measurements is considered. For the experimental investigation two FBG sensors base length (1 mm and 10 mm) were chosen. Both of them are used is SHM systems. The first one is typical for elastic or ultrasonic wave detection while the second one is for strain monitoring. The idea of the investigations is determination of possibility of utilisation FBG sensors being a part of SHM system also for moisture contamination detection.
2. Samples with FBG sensors embedded in adhesive layer The measurements were performed on three samples (denoted as A, B, C) consisted of two GFRP composite elements bonded together using adhesive (glue LOCTITE EA 9394 AERO form Henkel corporation Aerospace, USA). The adhesive is dedicated to bonding or repair aircraft elements. Its properties are collected in Table 1. According to the producer specification the adhesive contains epoxy resin. Every composite element has staking sequence as follows (0/90/0/90/90/0/90/0). Samples geometry is presented in Fig. 1. In the adhesive layers area FBG sensors with two different lengths (10 mm and 1 mm) are embedded. In the investigation commercial sensors made by Fiber Logic (1 mm) and HBM Fiber Sensing (10 mm) with acrylate coatings are used. The FBG sensors localisation schema is presented in Fig. 2 and Table 2. In sample A the sensors parallel to the sample axis were put as close to each other as it was possible. In the sample B one sensor with a length of 10 mm was put closer to the sample edge and additional sensor was put perpendicular to the sample axis. The sample C contains only one FBG sensor located in the middle of the sample. The embedment process was similar for every sample and divided into four stages. First one of the composite skins was covered with a glue layer on which FBG sensors were located according to description presented in Fig. 2 and Table 2. Then the sensors were covered by additional glue layer and in the last step the second composite skin was put on it. During curing process time the samples were under loading of additional weight in a purpose of receiving good bonding between the composite elements. The prepared samples were also investigated using THz spectrometry in a transmissive mode. The measurement equipment used in this experiment was the TPS Spectra 3000 THz Pulsed Imaging and Spectroscopy (from TerraView), supplied with a Large Sample Gantry Imaging system. The system provides continuous coverage in the range 40 GHz–
Fig. 1. A schema of a composite sample with an adhesive layer, g – the thickness of the adhesive layer.
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Fig. 2. A schema of FBG sensors location in adhesive layers. Table 2 Sample parameters and FBG sensors location in adhesive layers. Parameter
Sample A
B
C
Adhesive thickness [mm]
0.2
0.4
0.2
FBG sensors location FBG 1 mm FBG 10 mm
Parallel Parallel
Parallel Parallel and perpendicular
None Parallel
Distance [mm] between sample axis and parallel sensor FBG 1 mm FBG 10 mm
2 2
2 20
Between sample edge and perpendicular sensor FBG 10 mm
2
20
Fig. 3. THz spectrometry scans of A sample with marked fibre optics; THz λ1 – signal transmitted through the sample in a point with nominal thickness; THz λ2 – signal transmitted through the sample in a point where fibre optics are embedded; THz λ3 – signal transmitted through the sample in a point where sample is thicker.
10 THz. Three A-scans and B-scan of the A sample are presented in Fig. 3. The presented A-scans allow comparing THz waves registered for three different points. The first one (THz λ1) was measured for nominal sample thickness, the second one (THz λ2) for a place where fibre optics were embedded and the third (THz λ3) for locally thicker sample. The fibre optics are visible as circular disturbance on B-scan between 9.0 mm and 2.0 mm. When the wave meets something circular (like fibre optics) the strongest changes in the received signal are due to scattering process (THz λ2) so the received THz wave amplitude is lower and the signal peak is wider. When the sample is locally thicker (þ0.0002 m) the wave way through the sample is longer, so absorption and refractive index changes processes occurs (THz λ3). Such effect is visible on B-scan as additional local disturbances between 2.0 mm and 8.0 mm. Those observable results are due to different behaviour of THz wave and its interaction with the sample material.
3. Preliminary investigation Before moisture influence analysis starts all samples were preliminary investigated. Firstly changes of strain during adhesive layer curing process were monitored. Then FBG spectra registered before and after embedment process were compared. Finally the temperature changes influences on embedded FBG sensors were calculated. As it was expected
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Fig. 4. Strain changes during gluing process.
behaviour of all embedded FBG sensors do not depends on its location in samples but on sensor length. So in the following paragraphs the preliminary investigation results are presented for the A sample only. 3.1. Adhesive layer curing process Firstly the total strain values εc changes during curing process of the adhesive were measured by the embedded FBG sensors using interrogator si425-500 (Micron Optics) and measurement frequency 1 Hz. The measurement starts when FBG sensors were put into the adhesive layer. The total strain εc values were determined for every sensor from a relationship
ϵc ( t ) =
λmi ( t ) − λ b for i = 1, …, n, ( 1 − ρϵ ) λb
(3)
where λb means base Bragg wavelength, λm – Bragg wavelength from i-th measurement (n – number of measurements). According to the manufacturers’ specification (1 ρε) is equal to 0.890. The total strain εc values measured during gluing process by two FBG sensors are presented in Fig. 4. The gluing process was performed in room temperature 31 °C 70.5 °C. The achieved strain values are presented for 12 h interval, while the observed trend is presented as continuous line. According to the glue producer specification the curing process should be definitely finished up to 120 h. It is visible as a flat part of the strain curve. The strain values measured by 10 mm sensor are always higher than measured by 1 mm sensor. At the beginning of the gluing process the strain differences between 10 mm sensor and 1 mm sensor are about 6e 6, while during the process they decreased to 0.2–0.4e 6. When the curing process is finished the strain difference is about 3e 6. While the measurement error is assumed to be 1–2e 6. The presented process can be divided into two parts: before and after 144 h of measurement. The first one presents gluing process while the second part – differences in temperature influence on sensors originated from their spectra width. During the second part the temperature decrease from 31.5 °C to 29.5 °C. The glue curing process results also in formation of residual strain in adhesive layer despite the procedure was performed in almost stable temperature. 3.2. Spectra For every FBG sensor spectra were measured before and after the curing process end. The measurement was performed using Scan04 (Smart Fiber) interrogator. Comparison of spectra of two different length (1 mm and 10 mm) sensors is presented in Fig. 5. Spectra of the sensors registered before embedding process are denoted as (1), while after the embedding process – as (2). As it is clearly visible the embedding process results only in slightly decreasing of the amplitude of those two sensors. Additionally the 10 mm sensor was slightly compressed. The additional Bragg wavelength reflections are visible only for 10 mm sensor but they are not higher than 20% of sensor's reflectance. Because FBG are intrinsically sensitive to transverse stress and the obtained effect is not a pure wavelength shift but a broadening/splitting of the reflection band since transverse strain create birefringence [31] the additional peak origin is probably due to transverse strain occurrence being an effect of residual strain originated from curing process. It is worth noticed that the spectrum shape's strongly depends on the sensor length. The peak width at 50% reflectance
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Fig. 5. Comparison of FBG sensors’ spectra: (1) – before, (2) – after embedding process.
level is equal to 0.1 nm and 0.8 nm for 10 mm and 1 mm FBG sensor, respectively. It results in different noise level during measurements using those two sensors. 3.3. Temperature influence on FBG sensors Because the FBG sensors are much more sensitive to temperature changes than to strain changes, the strain values due to influence of temperature changes have to be determined. The experimental investigation was performed on dry samples in the heating chamber with thermal stability 72 °C. The exact temperature in the chamber was measured using Temperature Probe (os4200, Micron Optics). The thermal parameter of every embedded FBG sensor was determined. First, strain values were determined for every sensor using Eq. (3). Because in this case only temperature changes occur the strain εT is treated as thermal strain of the embedded sensor. The relationship between strain εT [mε] and temperature is described by an relationship
ε T (t ) = p∆T (t ),
(4)
where p [mε/°C] means empiric parameter determined for fibre optic material, ΔT – temperature difference. The parameter p depends on fibre optic and adhesive materials. Typically its value is about 10–15 mε/°C. The residual stress during curing can have significant effect on the mechanical properties. This results also in different temperature parameters values for FBG sensors glued on an composite sample surface and embedded into material [52].
Fig. 6. Comparison of temperature measured by FBG sensors.
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Due to this the p parameter was determined experimentally for sensors embedded into adhesive layer. For all sensors used in the measurement the temperature parameter p was determined experimentally and was equal to 9.15 mε/°C similar to the one described in [24]. The comparison of temperature determined by embedded FBG sensors with different length are presented in Fig. 6.
4. Moisture contamination detection In the next step the samples (A, B, C) were put into separated boxes filled with demineralised water and placed into temperature chamber with temperature (60 °C 72 °C). Every sample was put parallel to the box bottom. Samples were weighted periodically in a purpose of compare the FBG strain values with sample weight changes due to soaking process. The specimen weight was measured using laboratory weight with precision up to 10e 4 g that allows to measure changes in weight of the analysed material due to moisture influence. The relative water gain w(t) determined as,
w (t ) =
wk ( t )−wref wref
(5)
where wref is specimen weight at the dry state and wk(t) its weight at time t. Before measurements the samples were drying in 60 °C for 48 h and the moisture value in dry state was assumed as 0% (practically it should not be higher than 0.1%). Specimens were removed for weighting at appropriate intervals and were then placed back into environmental chamber. The weight measurement intervals were assumed according to theoretical investigation (Langmuir model). As it is presented in Fig. 7, they were equal to 6 h for first three measurements and then 24 h for the rest one. The influence of water on GFRP composite material was previously examined in a similar way as it was described for samples with embedded FBG sensors. The maximum amount of moisture that can be absorbed by a GFRP sample during 14 days of soaking is 1%. As its soaking characteristic was known its influence was removed on every step of the experimental investigation. Moisture absorption in epoxy adhesives cannot usually be accurately described by the Fick's second law [53]. The most widely accepted diffusion models to reproduce the water absorbed in polymers can be divided in two groups: multiphase diffusion (Langmuir model) and time dependent diffusion. The Langmuir diffusion model assumes that water can diffuse into the material, but some water molecules are also trapped inside the epoxy microstructure [53]. As for Fickian model, the solution can be approximated by [54]
⎧ ⎡ ⎛ Dt ⎞0.75⎤ ⎫ ⎪ ⎪ β β ⎡ M (t ) ≈ + exp ( −γt ) ⎨ 1 − exp ⎢ −7. 3 ⎜ 2 ⎟ ⎥ ⎬ ⎣ exp ( −βt )−exp ( γt ) ⎤⎦+⎡⎣ 1 − exp ( − βt ) ⎤⎦, ⎪ ⎪ β +γ ⎝ ⎠ β + γ s 4 g ⎢ ⎥ ⎣ ⎦ ⎩ ⎭
(6)
where D means diffusion coefficient, g – layer thickness [m], γ, β are constant referred to probability of water in each state, s – amount of moisture absorbed at saturation. Water content determined by calculations from Eq. (5) is presented in Fig. 7 and compared with the theoretical one (Eq.
Fig. 7. Comparison of water content [%] received from simulation and experiment.
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(6)). The calculated parameters were assumed as follow D ¼1.5e 12 [m2/s], γ ¼2e 1, β ¼4.1e 2. As it is visible the process is very fast during first 50 h and then the water content increasing very slowly. 4.1. Model The adhesive layer is assumed to be isotropic (εxx ¼ εyy), so the layer can be described as a two-dimensional adhesive layer of finite thickness g, under plane-strain condition The mechanical strain components (εxx, εzz, εxz) in two-dimensions are defined as [55],
ϵxx ( t ) = Sxx (t ) − αp ΔT (t ) − c Δw (t ) ϵzz ( t ) = Szz (t ) − αp ΔT (t ) − c Δw (t ) ϵxz ( t ) = Sxz (t )
(7)
where Sxx, Szz, Sxz are kinematic strain components, αp – isotropic linear coefficient of thermal expansion of polymer [m/m/ K], ΔT – temperature difference between actual temperature and reference temperature [K], c – isotropic linear coefficient of moisture expansion of polymer [m/m/RH%], where RH – relative humidity for environmental moisture concentration, Δw – moisture concentration difference [%] between actual an reference according to Eq. (5). Roy et al. [55] during their analysis assumed that shear strain does not play a significant role in assisting diffusion and calculated normal strains only. The same assumption will be also considered in the paper. Because FBG sensors can measure strain only in its axis direction and they are located parallel/perpendicular to the samples’ axis and they are in the middle of the adhesive material so they measured the normal strain only. It confirms that FBG sensors located perpendicular to adhesive layer thickness are useful for measurements of strain induced by moisture absorption process. The samples analysed in the paper are in water box inside environmental chamber, where temperature and humidity values are almost constant. The temperature is equal to 60 °C, and ΔT is assumed to be equal to 0 °C. The sample is not loaded by any external force so no kinematic strain occurs (Sxx ¼Syy ¼0). When no stress is applied, and when the polymer absorbs a concentration Δw of water (defined as the mass of absorbed water per unit mass of polymer), it is assumed to swell isotropically according to the linear law. So, the Eq. (7) are simplified to
ϵ xx ( t ) = c Δw (t ) ϵ zz ( t ) = c Δw (t )
(8)
Such a swelling law is observed in many polymers. Under assumption that the water uptake Δw is of a few percents the isotropic linear coefficient of moisture expansion of polymer has values of c 0.2–0.5 [56]. Based on Eq. (8) the theoretical moisture induced strain ε values were calculated using c parameter equal to 0.2 and 0.5, respectively. The achieved results are presented in Fig. 8. 4.2. Moisture induced strain FBG sensors embedded in adhesive layers were used for measurement of strain ε due to moisture influence. The total strain εc including both temperature and moisture influence was calculated using Eq. (3). Then the thermal strain εT was calculated using Eq. (4) and parameter p determined experimentally. So, the strain ε due to moisture influence was
Fig. 8. Theoretical strain values for c¼ 0.2 and c ¼0.5 calculated using simulation (continuous) and experimental (circles) values presented in Fig. 7.
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Fig. 9. Strain induced by moisture influence in adhesive bonds in the A and B samples.
calculated from a relationship
ϵ = ϵc − ϵT
(9)
Strain determined from FBG sensors wavelength changes for sensors from samples B and A are presented in Fig. 9. FBG sensor located perpendicular to the sample B axis is denoted as ┴ FBG while all parallel sensors as ║ FBG. Results achieved for 1 mm sensors were similar for both A and B samples. The FBG sensors with different base lengths located parallel to the sample B axis shows different values of strain ε. It is both due to sensors location (see Fig. 2) as well as their length. The ┴ FBG 10 mm sensor from sample B shows similar strain values as the 1 mm FBG sensor. The 10 mm FBG sensor is located in sample A closer to the sample edge than 10 mm FBG sensor in sample B. This allows comparing strain curves. Closes to the sample edge the strain values increased monotonically while in the middle of the sample the strain increased up to 1e 4 and then stopped for about 50 h. Then the process was continued between 150 h and 260 h. The strain values received after experimental investigation are similar to those received for theoretical calculation using Eq. (8) and c ¼0.5 (Fig. 8). Strain values versus percentage amount of moisture (up to 2%) for FBG sensors are presented in Fig. 10. As it is visible from the graphs 1 mm FBG sensor and perpendicular 10 mm FBG sensors strain measurements cannot be used for determination of amount of moisture higher than 1.5% (of the sample weight). For the 1 mm sensor, it is probably due to its length while for the 10 mm sensor - probably it is due to its location in the sample. Moisture causes swelling of the matrix which produces similar effects to thermal or chemical volume changes [52]. In the measurements presented in the paper the maximum moisture content in adhesive layer 2.3% and the volume change is noticeable.
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Fig. 10. Strain induced by moisture.
4.3. Method for determination of moisture concentration During an exploitation of a structure with an adhesive bond processes of drying and soaking alternate. FBG strain values can oscillate due to e.g. temperature changes as it was happened during the measurements present in the paper. It is possible to determine amount of moisture having experimental relationship between stain and moisture (like presented in Fig. 10). As it was described previously 1 mm sensor is not sensitive for moisture changes higher than 1.5%. The soaking and drying processes measurements are presented on sample C including one 10 mm FBG sensor. Every curve shape can be approximated by an appropriate number of straight lines. The slope of the straight line through two points A(x1, y1) and B(x2, y2), when x1≠x2, is given by a relationship
a =
( y2 −y1 ) ( x2 −x1)
(10)
The theoretical strain values presented in Fig. 8(b) were discretised with 1 h interval and the achieved points were connected by straight lines. Then the slope values a of the lines were calculated using Eq. (10). It allows to present moisture concentration in a function of slope values (Fig. 11). For better visibility the slope values a were multiplied by 1e7. The measured FBG strain values can be described by trends. Examples of trends determined during both soaking and drying processes are presented in Fig. 12. In a purpose of better visibility for all cases strain and time changes starts from point (0,0). The short description of every example is presented in Table 3. s For every case the trends were calculated for wavelength changes using dtrend procedure in Matlab . Then for every case strain εc values were determined using Eq. (3) then the temperature influenced strain εT was removed using Eq. (4). In the next step for every strain ε line the slope a of the line was determined. The calculated values of the a parameter (multiply by 1e7 for better visibility) are collected in Table 3. In a purpose of moisture determination the absolute value of a parameter were used, because the sign of the a parameter distinguish only drying and soaking processes.
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Fig. 11. Slope values (multiplied by 1e7) calculated for different moisture concentration; circles and pluses denoted different amount of moisture for points described in Table 3.
Fig. 12. Strain trends determined for sample with adhesive layer under both soaking and drying processes.
Using experimental relationship between strain and moisture concentration in the adhesive layer (Fig. 11) it is possible to determine moisture concentration occurred during different moments in time. The amounts of moisture concentration calculated for the examples of both soaking and drying processes (Table 3) are denoted in Fig. 11 by numbers referred to cases form Table 3 as well as circles and pluses symbols for soaking and drying processes, respectively.
5. Conclusion The paper presents the possibility of determination of moisture contamination concentration in an adhesive layer using embedded FBG sensors. Due to its small size and weight FBG sensors can be embedded into adhesive layer material.
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Table 3 Strain trends parameters. SENS a*1e7
w [%] Soaking/drying Information
1
3.33
2.04
Soaking
2
4.88
1.97
Soaking
3
6.69
1.87
Soaking
4 5
3.43 5.60
2.03 1.92
soaking Soaking
6 7 8
25.60 1.05 15.94 1.46 3.81 2.01
Drying Drying Drying
Measurement starts after putting the sample into demineralised water; previously the sample was in room environment with 60% humidity Measurement starts after putting the sample into demineralised water; the sample was dried previously for 3h Measurement starts after putting the sample into demineralised water; the sample was dried previously for 15 h Measurements starts after adding water to almost empty box. Measurement starts after putting the sample into demineralised water; the sample was dried previously for 6h Drying of the sample; there was no water in the box at the beginning of the measurement. Drying of the sample; there was 3 mm of water at the beginning of the measurement. Water evaporated during the measurement.
Moisture contamination due to diffusion process changes the volumetric parameters of the material induced strain. This strain can be measured by FBG sensors. As it was presented in the paper FBG sensors can be used for moisture detection in an adhesive layer even when the amount of moisture is no higher than 2% of the sample weight. FBG sensors with a base length equal to 1 mm are not enough sensitive for moisture changes higher than 1.5%. Experimental relationship between strain and moisture content can be used for monitoring both soaking and drying processes in an adhesive layer. For this purpose the slope of the line trends can be used. The utility of SHM system including FBG sensors for strain induced by moisture will be developed in the future. The authors wish to continue their work in this area of research in the future to overcome all the problems and difficulties encountered during the line of work presented in this paper.
Acknowledgement The research was supported by the project entitled: Non-invasive Methods for Assessment of Physicochemical and Mechanical Degradation (PBS1/B6/8/2012) granted by National Centre for Research and Development in Poland.
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Mechanical Systems and Signal Processing journal homepage: www.elsevier.com/locate/ymssp
Moisture contamination detection in adhesive bond using embedded FBG sensors Magdalena Mieloszyk a,n, Wiesław Ostachowicz a,b a Mechanics of Intelligent Structures Department, Institute of Fluid-Flow Machinery, Polish Academy of Sciences, 14 Fiszera Street, 80-231 Gdansk, Poland b Faculty of Automotive and Construction Machinery, Warsaw University of Technology, 84 Narbutta Street, 02-524 Warsaw, Poland
a r t i c l e i n f o
abstract
Article history: Received 14 October 2015 Received in revised form 30 June 2016 Accepted 2 July 2016
The paper presents an application of embedded fibre Bragg grating (FBG) sensors for moisture contamination detection in an adhesive bond between two composite elements. FBG sensors are a great tool to Structural Health Monitoring of composite structures due to their high corrosion resistance as well as their small size and weight. Adhesive bonds are very popular in many industrial branches. One of the major problem limits the use of an adhesive joints is they sensitivity on water form ambient. Even the 1% of moisture affects an adhesive bond layer strength. FBG sensors can be use for detection of even a small amount of moisture concentration (1–3% of sample weight). It can be also used for determination of moisture concentration changes during both soaking and drying processes. & 2016 Elsevier Ltd. All rights reserved.
Keywords: Fibre Bragg grating Moisture contamination Epoxy Adhesive bond
1. Introduction Composite elements (both CFRP (carbon fibre reinforced polymer) and GFRP (glass fibre reinforced polymer)) are widely used for load carrying structures in aircraft, marine, civil engineering, where the specific strength and specific modulus are of importance, e.g. aircraft wings, helicopter rotor blades, wind turbine blades. Adhesive bonds in comparison with conventional mechanical joining techniques of composite materials present numerous advantages such as: more homogeneous stress distribution, higher stiffness, high fatigue strength [1,2]. Adhesive bonds are also lightest in comparison with classical fastening techniques such as welding, riveting and mechanical fastening. So, in lightweight composite structures, adhesive bonding is the most appropriate joining technique [3]. For this reason, adhesive bonds are more and more popular in many industrial branches (e.g. automotive [2], aircraft [2,4]). The most common cause of environmental degradation in bonded joints involves the absorption of moisture into the adhesive layer [5,6]. Such problem especially occurs when an adhesive contains epoxy resin. When such material is exposed to hygrothermal environment, it absorbs moisture which greatly affects its thermo-mechanical properties that results in significant decreasing of the durability and reliability of the structural element with an adhesive joint [5]. The paper is organised as follows. Firstly, problems referred to moisture influence on epoxy based adhesives are presented. Then FBG (Fibre Bragg Grating) sensors and their utility for soaking process monitoring are presented and discussed. FBG sensors are used for measurement of strain induced by moisture in adhesive bond between two composite elements. n
Corresponding author. E-mail address: [email protected] (M. Mieloszyk).
http://dx.doi.org/10.1016/j.ymssp.2016.07.006 0888-3270/& 2016 Elsevier Ltd. All rights reserved.
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Finally, the conclusions from investigations are drawn. 1.1. Moisture influence on adhesive bond Moisture absorption is recognised to be one of the most important causes of impairing the mechanical properties of polymers and their composites due to physical changes at a microscopic level [7]. One of the problems with polymers (like epoxy) is their tendency to absorb moisture from ambient. The moisture affects a polymer properties, like dimensional stability, mechanical [5,8–10], chemical [8,10] and thermophysical properties [9,11]. The moisture (1% of water mass gain) influence for every epoxy and hardener combination results in: a lowering of Tg (glass transition temperature) by about 10 °C, a loss of about 10% in storage modulus and 15% in tensile strength [7]. Similar problems occur also for adhesive layers. The most important degradation effects due to moisture contamination in adhesive layers are: plasticisation [3,4,6] cracking [4] and hygroscopic expansion of the adhesive [3,6] and deterioration of the adherend/adhesive interface [3,4,6]. Moisture contamination occurs in an adhesive bond can also travel throughout adhesive/adherend interface [6] to composite material and affecting the fibre-matrix interface bond [9,12], leading to loss of mechanical integrity of whole structural element. It is worth mention that structural elements with adhesive bonds consist of parts with different material properties (e.g. coefficients of thermal expansion, moisture sensitivity). The different sensitivity of composite material and adhesive on moisture can results in similar problem like occurs in FRP composites, where material properties of matrix and fibres differ [11]. 1.2. Fibre Bragg grating sensors A Bragg grating is a permanent periodic modulation of the refractive index in the core of a single-mode fibre optic. It is made by exposing the core of the optical fibre to an interference pattern of intense UV laser light [13,14]. The length of a FBG sensor is typically in the range of 1–25 mm and depends on its application. The periodic perturbation in the core refractive index allows coherent scattering to occur for a narrow wavelength band of incident light travelling within the fibre core. A strong narrowband back reflection of light is generated, centred around the maximum reflecting wavelength λB value when the resonance condition, or phase match, is satisfied:
λB = 2neff Λ,
(1)
where neff is the effective refractive index and Λ is the periodicity of the perturbation [15]. Bragg wavelength change due to strain and temperature change are described by a relationship
ΔλB =( 1 − ρϵ ) ϵ+( α+ξ ) ΔT λB
(2)
where α means thermal expansion coefficient, ξ – thermooptic coefficient, ρε – elastooptic coefficient of fibre optic material. Longitudinal strains ε act on the periodicity of the perturbation Λ (photoelastic effect), while temperature affects both the effective refractive index neff (thermo-optic effect) and the periodicity of the perturbation Λ (thermoelastic effect) [16,17]. The key point of FBG sensors is their wavelength-encoded nature, which is the absolute parameter providing repeatable measurements [18]. FBG sensors can be written on both silica glass and polymer optical fibres [19]. FBG sensors written on silica fibre optics have many advantages like small size and weight, high multiplexing capabilities, immunity to electromagnetic field interference, high corrosion resistance (both water and chemicals) and no calibration needs [13,15,20–22]. FBG sensors are sensitive to both strain [23] and temperature [24]. The changes in those two parameters are linearly proportional to changes in the measured wavelength [15]. FBG sensors can be mounted onto a structure surfaces [16,25] or embedded [26–31] into the material of a structural element during the manufacturing process. They can be also included into adhesive layer during the process of joining two structural elements. Kim et al. [32] embedded FBG sensors in a wind turbine blade to its deflection estimation. FBG sensors can be used for adhesive bond lifetime monitoring [1]. Canal et al. [33] evaluated the feasibility of using FBG sensors to monitor the distribution of strains developed along the bonded region in single lap shear specimens. Sulejmani et al. [1] presented Bragg grating based shear stress optical sensors application for in situ disbond monitoring at adhesive bonds. The presented method allows to determine shear stress distribution in an adhesive bond line and detect a disbond of at least 100 mm while the exact loading level does not to be known. Nowadays FBG sensors are integral parts of SHM systems installed on different structures: bridges [16,22,28], offshore platforms [25,34], buildings [35], marine vessels [36,37] and aircraft structures [38–40]. The advantages of polymer FBG sensors are their inherent fracture resistance, low Young's modulus, high flexibility, high temperature sensitivity [19,41,42]. For composite application the most important are high temperature sensitivity, large strain range and the absence of buffer coating [42]. One of the main disadvantage of polymer FBG is strong loss of the transmitted signal so they have to be glued to silica fibre to be connected to measurement unit [19,41]. The other problem with polymer FBG is their negative thermo-optic coefficient that results in wavelength decrease with temperature increase
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[19,41]. So temperature change influence is not easy remove from measurements performed in ambient temperature. The FBG sensors sensitivity on humidity and temperature are strongly correlated [19]. Polymer FBG sensors are sensitive to relative humidity, temperature and strain [42]. This is in contrast to silica glass fibre FBGs which do not show any intrinsic humidity sensitivity, even a recoated silica FBG showed a humidity sensitivity 125 times lower than that of the polymer FBG [42]. The affinity for water of poly(methyl methacrylate) (PMMA) material commonly used in polymer FBG sensors, leads to a swelling of the fibre and an increase of refractive index, both of which contribute to an increase in the Bragg wavelength of a FBG written in the fibre [42]. This feature allows it to measure amount of water in air [19,42]. Rajan et al. [41] compared strain and temperature influence on silica and polymer (PMMA) FBG sensors with similar length (10 mm) embedded in composite material. Due to strong loss of the polymer they used short length (12 cm) fibres. The composite samples were unidirectional 0/0 GFRP with 8 layers. The embedded polymer FBG sensors outer diameters (240–260 mm) [41] are similar to typical silica glass fibres. Polymer FBG sensors are better candidate to measure temperature, while silica FBG sensors can more accurately measure strain in GFRP composite [41]. The idea of utility of FBG sensors for moisture detection is nowadays investigated by researchers around the world. The first type of relative humidity FBG sensors based on silica fibre optics covered by special moisture sensitive coats [43,44]. Lin et al. [45] developed a fibre optic humidity sensor fabricated by coating a moisture sensitive polymer film to FBG. Compared to conventional capacitive and resistive humidity sensor, the FBG coated with polyimide had unique advantages in terms of high measurement accuracy. The measured relative humidity range was from 11.3 to 97.3%. Another types are FBG sensors written on PMMA material. The sensitivity of polymer FBG sensors on humidity allows them to be applied for monitoring humidity level in food storage, paper manufacturing [42] or to quantifying the small amount of water present in jet fuel [46]. Zhang et al. [42] developed polymer FBG humidity sensor that was tested in environmental chamber in relative humidity in a range from 30% to 90% and fixed temperature (25 °C). Rajan et al. [47] developed relative humidity sensor system based on etched polymer FBG. The analysed relative humidity was in a range 10%–90%. Another types of optical fibres are microstructured optical fibres with numerous air-holes along the length of the cladding. Microstructural fibres are selective sensitive to only one measurand (axial strain, hydrostatic pressure or transverse loading) [1]. FBG incorporated microstructural fibres sensors can induce a contra-directional coupling between forward and backward fibre modes through resonant scattering and thus perform very well in strain, pressure and microfluidic refractive index sensing applications. FBG sensors written on such fibres can be used for microfluidic and gas sensing applications [48]. Woyessa et al. [49] analysed influence of annealing temperature on effect of humidity on PMMA based microstructured polymer optical FBG and the resulting humidity responsively. The humidity response was analysed at fixed temperatures: 25 °C, 50 °C and 75 °C for relative humidity in a range from 10 to 90%. The process of moisture absorption results in increasing of material volume. This process can be observed as internal strain changes, so it could be measured by embedded fibre optic sensors, e.g. FBG sensors. Karalekas et al. [5] analysed utility of long FBG sensors to monitor the effects of hygrothermal ageing on the axial strains in a cylindrical epoxy specimen with a centrally located optical glass fibre that contains a long Bragg grating sensor. The specimen was immersed in distilled water at 50 °C for 2330 h. The wavelength changes were used to measure resin conversion, coefficients of thermal expansion (CTE) and moisture expansion (CME) and to monitor strains induced by moisture. The FBG response also indicates the appearance of progressive debonding after sufficient exposure to moisture [5]. Lai et al. [7] performed similar experimental investigation on cylindrical specimens made of epoxy with an axially located optical fibre. Strain data from the sensor and from a micrometre were combined with experimental absorption curves to determine the resin's coefficient of moisture expansion. The data indicate that diffusion and CME depended on moisture concentration. Analysis of the experiments was carried out by numerical simulations of heat transfer, and moisture diffusion. The simulated results correlated well with the experimental data [7]. The distributed strains measured by long Bragg grating sensor were used to monitor the moisture induced strains during ageing and tracks debond growth at the interface, generated during ageing [50]. 1.3. Motivation As it was presented before even a small amount of moisture negative influenced on polymer (epoxy) strength parameters. Epoxy resin is one of the most important ingredients contained by many adhesives and composite matrix. FBG sensors due to small dimensions can be embedded in material without significant changes of its properties. From a variety of FBG sensor types presented in Section 1.2 FBG sensors written on silica glass fibres were chosen. The FBG sensors with special polymer coating are mostly applied for air humidity [43,44]. The advantage of using a polymer FBG sensor in this application could be the Young modulus value for PMMA (around 5.3 GPa [19]) that is similar to the glue (Table 1) in the adhesive layer presented in the paper on contrary to silica fibres used in the experimental investigation presented in the paper. But their main disadvantages are strong signal loss during transmission and negative thermooptic coefficient [19,41]. As it was described by Karalekas et al. [5] and Lai et al. [7] an embedded FBG sensor can be also used for moisture detection in epoxy specimen up to 6% of sample weight. The motivation of the investigation presented in the paper is determination of possibility of detection moisture (up to 3% of sample weight) in an adhesive layer between two composite elements.
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Table 1 Glue properties [51]. Parameter
Value
Unit
Tg (dry) Tg (wet) Tensile strength at 25 °C Tensile modulus at 25 °C Elongation at 25 °C at break Compressive strength at 25 °C Cure temperature Cure time
78 68 46 4.237 0.017 68.9 25–93 3–5
°C °C MPa GPa % MPa °C day
Additional parameters
Good gap filling capabilities Room temperature storage Low toxicity
Additionally the possibility of monitoring of soaking and drying processes based on FBG sensors strain measurements is considered. For the experimental investigation two FBG sensors base length (1 mm and 10 mm) were chosen. Both of them are used is SHM systems. The first one is typical for elastic or ultrasonic wave detection while the second one is for strain monitoring. The idea of the investigations is determination of possibility of utilisation FBG sensors being a part of SHM system also for moisture contamination detection.
2. Samples with FBG sensors embedded in adhesive layer The measurements were performed on three samples (denoted as A, B, C) consisted of two GFRP composite elements bonded together using adhesive (glue LOCTITE EA 9394 AERO form Henkel corporation Aerospace, USA). The adhesive is dedicated to bonding or repair aircraft elements. Its properties are collected in Table 1. According to the producer specification the adhesive contains epoxy resin. Every composite element has staking sequence as follows (0/90/0/90/90/0/90/0). Samples geometry is presented in Fig. 1. In the adhesive layers area FBG sensors with two different lengths (10 mm and 1 mm) are embedded. In the investigation commercial sensors made by Fiber Logic (1 mm) and HBM Fiber Sensing (10 mm) with acrylate coatings are used. The FBG sensors localisation schema is presented in Fig. 2 and Table 2. In sample A the sensors parallel to the sample axis were put as close to each other as it was possible. In the sample B one sensor with a length of 10 mm was put closer to the sample edge and additional sensor was put perpendicular to the sample axis. The sample C contains only one FBG sensor located in the middle of the sample. The embedment process was similar for every sample and divided into four stages. First one of the composite skins was covered with a glue layer on which FBG sensors were located according to description presented in Fig. 2 and Table 2. Then the sensors were covered by additional glue layer and in the last step the second composite skin was put on it. During curing process time the samples were under loading of additional weight in a purpose of receiving good bonding between the composite elements. The prepared samples were also investigated using THz spectrometry in a transmissive mode. The measurement equipment used in this experiment was the TPS Spectra 3000 THz Pulsed Imaging and Spectroscopy (from TerraView), supplied with a Large Sample Gantry Imaging system. The system provides continuous coverage in the range 40 GHz–
Fig. 1. A schema of a composite sample with an adhesive layer, g – the thickness of the adhesive layer.
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Fig. 2. A schema of FBG sensors location in adhesive layers. Table 2 Sample parameters and FBG sensors location in adhesive layers. Parameter
Sample A
B
C
Adhesive thickness [mm]
0.2
0.4
0.2
FBG sensors location FBG 1 mm FBG 10 mm
Parallel Parallel
Parallel Parallel and perpendicular
None Parallel
Distance [mm] between sample axis and parallel sensor FBG 1 mm FBG 10 mm
2 2
2 20
Between sample edge and perpendicular sensor FBG 10 mm
2
20
Fig. 3. THz spectrometry scans of A sample with marked fibre optics; THz λ1 – signal transmitted through the sample in a point with nominal thickness; THz λ2 – signal transmitted through the sample in a point where fibre optics are embedded; THz λ3 – signal transmitted through the sample in a point where sample is thicker.
10 THz. Three A-scans and B-scan of the A sample are presented in Fig. 3. The presented A-scans allow comparing THz waves registered for three different points. The first one (THz λ1) was measured for nominal sample thickness, the second one (THz λ2) for a place where fibre optics were embedded and the third (THz λ3) for locally thicker sample. The fibre optics are visible as circular disturbance on B-scan between 9.0 mm and 2.0 mm. When the wave meets something circular (like fibre optics) the strongest changes in the received signal are due to scattering process (THz λ2) so the received THz wave amplitude is lower and the signal peak is wider. When the sample is locally thicker (þ0.0002 m) the wave way through the sample is longer, so absorption and refractive index changes processes occurs (THz λ3). Such effect is visible on B-scan as additional local disturbances between 2.0 mm and 8.0 mm. Those observable results are due to different behaviour of THz wave and its interaction with the sample material.
3. Preliminary investigation Before moisture influence analysis starts all samples were preliminary investigated. Firstly changes of strain during adhesive layer curing process were monitored. Then FBG spectra registered before and after embedment process were compared. Finally the temperature changes influences on embedded FBG sensors were calculated. As it was expected
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Fig. 4. Strain changes during gluing process.
behaviour of all embedded FBG sensors do not depends on its location in samples but on sensor length. So in the following paragraphs the preliminary investigation results are presented for the A sample only. 3.1. Adhesive layer curing process Firstly the total strain values εc changes during curing process of the adhesive were measured by the embedded FBG sensors using interrogator si425-500 (Micron Optics) and measurement frequency 1 Hz. The measurement starts when FBG sensors were put into the adhesive layer. The total strain εc values were determined for every sensor from a relationship
ϵc ( t ) =
λmi ( t ) − λ b for i = 1, …, n, ( 1 − ρϵ ) λb
(3)
where λb means base Bragg wavelength, λm – Bragg wavelength from i-th measurement (n – number of measurements). According to the manufacturers’ specification (1 ρε) is equal to 0.890. The total strain εc values measured during gluing process by two FBG sensors are presented in Fig. 4. The gluing process was performed in room temperature 31 °C 70.5 °C. The achieved strain values are presented for 12 h interval, while the observed trend is presented as continuous line. According to the glue producer specification the curing process should be definitely finished up to 120 h. It is visible as a flat part of the strain curve. The strain values measured by 10 mm sensor are always higher than measured by 1 mm sensor. At the beginning of the gluing process the strain differences between 10 mm sensor and 1 mm sensor are about 6e 6, while during the process they decreased to 0.2–0.4e 6. When the curing process is finished the strain difference is about 3e 6. While the measurement error is assumed to be 1–2e 6. The presented process can be divided into two parts: before and after 144 h of measurement. The first one presents gluing process while the second part – differences in temperature influence on sensors originated from their spectra width. During the second part the temperature decrease from 31.5 °C to 29.5 °C. The glue curing process results also in formation of residual strain in adhesive layer despite the procedure was performed in almost stable temperature. 3.2. Spectra For every FBG sensor spectra were measured before and after the curing process end. The measurement was performed using Scan04 (Smart Fiber) interrogator. Comparison of spectra of two different length (1 mm and 10 mm) sensors is presented in Fig. 5. Spectra of the sensors registered before embedding process are denoted as (1), while after the embedding process – as (2). As it is clearly visible the embedding process results only in slightly decreasing of the amplitude of those two sensors. Additionally the 10 mm sensor was slightly compressed. The additional Bragg wavelength reflections are visible only for 10 mm sensor but they are not higher than 20% of sensor's reflectance. Because FBG are intrinsically sensitive to transverse stress and the obtained effect is not a pure wavelength shift but a broadening/splitting of the reflection band since transverse strain create birefringence [31] the additional peak origin is probably due to transverse strain occurrence being an effect of residual strain originated from curing process. It is worth noticed that the spectrum shape's strongly depends on the sensor length. The peak width at 50% reflectance
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Fig. 5. Comparison of FBG sensors’ spectra: (1) – before, (2) – after embedding process.
level is equal to 0.1 nm and 0.8 nm for 10 mm and 1 mm FBG sensor, respectively. It results in different noise level during measurements using those two sensors. 3.3. Temperature influence on FBG sensors Because the FBG sensors are much more sensitive to temperature changes than to strain changes, the strain values due to influence of temperature changes have to be determined. The experimental investigation was performed on dry samples in the heating chamber with thermal stability 72 °C. The exact temperature in the chamber was measured using Temperature Probe (os4200, Micron Optics). The thermal parameter of every embedded FBG sensor was determined. First, strain values were determined for every sensor using Eq. (3). Because in this case only temperature changes occur the strain εT is treated as thermal strain of the embedded sensor. The relationship between strain εT [mε] and temperature is described by an relationship
ε T (t ) = p∆T (t ),
(4)
where p [mε/°C] means empiric parameter determined for fibre optic material, ΔT – temperature difference. The parameter p depends on fibre optic and adhesive materials. Typically its value is about 10–15 mε/°C. The residual stress during curing can have significant effect on the mechanical properties. This results also in different temperature parameters values for FBG sensors glued on an composite sample surface and embedded into material [52].
Fig. 6. Comparison of temperature measured by FBG sensors.
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Due to this the p parameter was determined experimentally for sensors embedded into adhesive layer. For all sensors used in the measurement the temperature parameter p was determined experimentally and was equal to 9.15 mε/°C similar to the one described in [24]. The comparison of temperature determined by embedded FBG sensors with different length are presented in Fig. 6.
4. Moisture contamination detection In the next step the samples (A, B, C) were put into separated boxes filled with demineralised water and placed into temperature chamber with temperature (60 °C 72 °C). Every sample was put parallel to the box bottom. Samples were weighted periodically in a purpose of compare the FBG strain values with sample weight changes due to soaking process. The specimen weight was measured using laboratory weight with precision up to 10e 4 g that allows to measure changes in weight of the analysed material due to moisture influence. The relative water gain w(t) determined as,
w (t ) =
wk ( t )−wref wref
(5)
where wref is specimen weight at the dry state and wk(t) its weight at time t. Before measurements the samples were drying in 60 °C for 48 h and the moisture value in dry state was assumed as 0% (practically it should not be higher than 0.1%). Specimens were removed for weighting at appropriate intervals and were then placed back into environmental chamber. The weight measurement intervals were assumed according to theoretical investigation (Langmuir model). As it is presented in Fig. 7, they were equal to 6 h for first three measurements and then 24 h for the rest one. The influence of water on GFRP composite material was previously examined in a similar way as it was described for samples with embedded FBG sensors. The maximum amount of moisture that can be absorbed by a GFRP sample during 14 days of soaking is 1%. As its soaking characteristic was known its influence was removed on every step of the experimental investigation. Moisture absorption in epoxy adhesives cannot usually be accurately described by the Fick's second law [53]. The most widely accepted diffusion models to reproduce the water absorbed in polymers can be divided in two groups: multiphase diffusion (Langmuir model) and time dependent diffusion. The Langmuir diffusion model assumes that water can diffuse into the material, but some water molecules are also trapped inside the epoxy microstructure [53]. As for Fickian model, the solution can be approximated by [54]
⎧ ⎡ ⎛ Dt ⎞0.75⎤ ⎫ ⎪ ⎪ β β ⎡ M (t ) ≈ + exp ( −γt ) ⎨ 1 − exp ⎢ −7. 3 ⎜ 2 ⎟ ⎥ ⎬ ⎣ exp ( −βt )−exp ( γt ) ⎤⎦+⎡⎣ 1 − exp ( − βt ) ⎤⎦, ⎪ ⎪ β +γ ⎝ ⎠ β + γ s 4 g ⎢ ⎥ ⎣ ⎦ ⎩ ⎭
(6)
where D means diffusion coefficient, g – layer thickness [m], γ, β are constant referred to probability of water in each state, s – amount of moisture absorbed at saturation. Water content determined by calculations from Eq. (5) is presented in Fig. 7 and compared with the theoretical one (Eq.
Fig. 7. Comparison of water content [%] received from simulation and experiment.
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(6)). The calculated parameters were assumed as follow D ¼1.5e 12 [m2/s], γ ¼2e 1, β ¼4.1e 2. As it is visible the process is very fast during first 50 h and then the water content increasing very slowly. 4.1. Model The adhesive layer is assumed to be isotropic (εxx ¼ εyy), so the layer can be described as a two-dimensional adhesive layer of finite thickness g, under plane-strain condition The mechanical strain components (εxx, εzz, εxz) in two-dimensions are defined as [55],
ϵxx ( t ) = Sxx (t ) − αp ΔT (t ) − c Δw (t ) ϵzz ( t ) = Szz (t ) − αp ΔT (t ) − c Δw (t ) ϵxz ( t ) = Sxz (t )
(7)
where Sxx, Szz, Sxz are kinematic strain components, αp – isotropic linear coefficient of thermal expansion of polymer [m/m/ K], ΔT – temperature difference between actual temperature and reference temperature [K], c – isotropic linear coefficient of moisture expansion of polymer [m/m/RH%], where RH – relative humidity for environmental moisture concentration, Δw – moisture concentration difference [%] between actual an reference according to Eq. (5). Roy et al. [55] during their analysis assumed that shear strain does not play a significant role in assisting diffusion and calculated normal strains only. The same assumption will be also considered in the paper. Because FBG sensors can measure strain only in its axis direction and they are located parallel/perpendicular to the samples’ axis and they are in the middle of the adhesive material so they measured the normal strain only. It confirms that FBG sensors located perpendicular to adhesive layer thickness are useful for measurements of strain induced by moisture absorption process. The samples analysed in the paper are in water box inside environmental chamber, where temperature and humidity values are almost constant. The temperature is equal to 60 °C, and ΔT is assumed to be equal to 0 °C. The sample is not loaded by any external force so no kinematic strain occurs (Sxx ¼Syy ¼0). When no stress is applied, and when the polymer absorbs a concentration Δw of water (defined as the mass of absorbed water per unit mass of polymer), it is assumed to swell isotropically according to the linear law. So, the Eq. (7) are simplified to
ϵ xx ( t ) = c Δw (t ) ϵ zz ( t ) = c Δw (t )
(8)
Such a swelling law is observed in many polymers. Under assumption that the water uptake Δw is of a few percents the isotropic linear coefficient of moisture expansion of polymer has values of c 0.2–0.5 [56]. Based on Eq. (8) the theoretical moisture induced strain ε values were calculated using c parameter equal to 0.2 and 0.5, respectively. The achieved results are presented in Fig. 8. 4.2. Moisture induced strain FBG sensors embedded in adhesive layers were used for measurement of strain ε due to moisture influence. The total strain εc including both temperature and moisture influence was calculated using Eq. (3). Then the thermal strain εT was calculated using Eq. (4) and parameter p determined experimentally. So, the strain ε due to moisture influence was
Fig. 8. Theoretical strain values for c¼ 0.2 and c ¼0.5 calculated using simulation (continuous) and experimental (circles) values presented in Fig. 7.
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Fig. 9. Strain induced by moisture influence in adhesive bonds in the A and B samples.
calculated from a relationship
ϵ = ϵc − ϵT
(9)
Strain determined from FBG sensors wavelength changes for sensors from samples B and A are presented in Fig. 9. FBG sensor located perpendicular to the sample B axis is denoted as ┴ FBG while all parallel sensors as ║ FBG. Results achieved for 1 mm sensors were similar for both A and B samples. The FBG sensors with different base lengths located parallel to the sample B axis shows different values of strain ε. It is both due to sensors location (see Fig. 2) as well as their length. The ┴ FBG 10 mm sensor from sample B shows similar strain values as the 1 mm FBG sensor. The 10 mm FBG sensor is located in sample A closer to the sample edge than 10 mm FBG sensor in sample B. This allows comparing strain curves. Closes to the sample edge the strain values increased monotonically while in the middle of the sample the strain increased up to 1e 4 and then stopped for about 50 h. Then the process was continued between 150 h and 260 h. The strain values received after experimental investigation are similar to those received for theoretical calculation using Eq. (8) and c ¼0.5 (Fig. 8). Strain values versus percentage amount of moisture (up to 2%) for FBG sensors are presented in Fig. 10. As it is visible from the graphs 1 mm FBG sensor and perpendicular 10 mm FBG sensors strain measurements cannot be used for determination of amount of moisture higher than 1.5% (of the sample weight). For the 1 mm sensor, it is probably due to its length while for the 10 mm sensor - probably it is due to its location in the sample. Moisture causes swelling of the matrix which produces similar effects to thermal or chemical volume changes [52]. In the measurements presented in the paper the maximum moisture content in adhesive layer 2.3% and the volume change is noticeable.
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Fig. 10. Strain induced by moisture.
4.3. Method for determination of moisture concentration During an exploitation of a structure with an adhesive bond processes of drying and soaking alternate. FBG strain values can oscillate due to e.g. temperature changes as it was happened during the measurements present in the paper. It is possible to determine amount of moisture having experimental relationship between stain and moisture (like presented in Fig. 10). As it was described previously 1 mm sensor is not sensitive for moisture changes higher than 1.5%. The soaking and drying processes measurements are presented on sample C including one 10 mm FBG sensor. Every curve shape can be approximated by an appropriate number of straight lines. The slope of the straight line through two points A(x1, y1) and B(x2, y2), when x1≠x2, is given by a relationship
a =
( y2 −y1 ) ( x2 −x1)
(10)
The theoretical strain values presented in Fig. 8(b) were discretised with 1 h interval and the achieved points were connected by straight lines. Then the slope values a of the lines were calculated using Eq. (10). It allows to present moisture concentration in a function of slope values (Fig. 11). For better visibility the slope values a were multiplied by 1e7. The measured FBG strain values can be described by trends. Examples of trends determined during both soaking and drying processes are presented in Fig. 12. In a purpose of better visibility for all cases strain and time changes starts from point (0,0). The short description of every example is presented in Table 3. s For every case the trends were calculated for wavelength changes using dtrend procedure in Matlab . Then for every case strain εc values were determined using Eq. (3) then the temperature influenced strain εT was removed using Eq. (4). In the next step for every strain ε line the slope a of the line was determined. The calculated values of the a parameter (multiply by 1e7 for better visibility) are collected in Table 3. In a purpose of moisture determination the absolute value of a parameter were used, because the sign of the a parameter distinguish only drying and soaking processes.
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Fig. 11. Slope values (multiplied by 1e7) calculated for different moisture concentration; circles and pluses denoted different amount of moisture for points described in Table 3.
Fig. 12. Strain trends determined for sample with adhesive layer under both soaking and drying processes.
Using experimental relationship between strain and moisture concentration in the adhesive layer (Fig. 11) it is possible to determine moisture concentration occurred during different moments in time. The amounts of moisture concentration calculated for the examples of both soaking and drying processes (Table 3) are denoted in Fig. 11 by numbers referred to cases form Table 3 as well as circles and pluses symbols for soaking and drying processes, respectively.
5. Conclusion The paper presents the possibility of determination of moisture contamination concentration in an adhesive layer using embedded FBG sensors. Due to its small size and weight FBG sensors can be embedded into adhesive layer material.
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Table 3 Strain trends parameters. SENS a*1e7
w [%] Soaking/drying Information
1
3.33
2.04
Soaking
2
4.88
1.97
Soaking
3
6.69
1.87
Soaking
4 5
3.43 5.60
2.03 1.92
soaking Soaking
6 7 8
25.60 1.05 15.94 1.46 3.81 2.01
Drying Drying Drying
Measurement starts after putting the sample into demineralised water; previously the sample was in room environment with 60% humidity Measurement starts after putting the sample into demineralised water; the sample was dried previously for 3h Measurement starts after putting the sample into demineralised water; the sample was dried previously for 15 h Measurements starts after adding water to almost empty box. Measurement starts after putting the sample into demineralised water; the sample was dried previously for 6h Drying of the sample; there was no water in the box at the beginning of the measurement. Drying of the sample; there was 3 mm of water at the beginning of the measurement. Water evaporated during the measurement.
Moisture contamination due to diffusion process changes the volumetric parameters of the material induced strain. This strain can be measured by FBG sensors. As it was presented in the paper FBG sensors can be used for moisture detection in an adhesive layer even when the amount of moisture is no higher than 2% of the sample weight. FBG sensors with a base length equal to 1 mm are not enough sensitive for moisture changes higher than 1.5%. Experimental relationship between strain and moisture content can be used for monitoring both soaking and drying processes in an adhesive layer. For this purpose the slope of the line trends can be used. The utility of SHM system including FBG sensors for strain induced by moisture will be developed in the future. The authors wish to continue their work in this area of research in the future to overcome all the problems and difficulties encountered during the line of work presented in this paper.
Acknowledgement The research was supported by the project entitled: Non-invasive Methods for Assessment of Physicochemical and Mechanical Degradation (PBS1/B6/8/2012) granted by National Centre for Research and Development in Poland.
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