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Modal Acoustic Emission Analysis of Mode-I and Mode-II Fracture of Adhesively Bonded Joints


Abstract and Figures

Acoustic emission (AE) testing has previously been demonstrated to be well suited to detecting failure in adhesively-bonded joints. In this work, the relationship between the fracture-mode of adhesivelybonded specimens and the acoustic wave-modes excited by their failure is investigated. AE instrumented Double-Cantilever-Beam (Mode-I fracture) and Lap-Shear (Mode-II fracture) tests are conducted on similar adhesively-bonded aluminium specimens. Linear source-location is used to identify the source-to-sensor propagation distance of each recorded hit, theoretical dispersion curves are used to identify regions of the signal corresponding to the symmetric and asymmetric wave modes, and peak wavelet-transform coefficients for the wave-modes are compared between the two fracturemodes. It is demonstrated that while both fracture-modes generate AE dominated by the asymmetric mode, the symmetric mode is generally much more significant during Mode-II fracture than Mode-I. While significant scatter and overlap in results prevents the ratio of peak-wavelet transform coefficients from being a robust single classifier for differentiation between fracture-modes in most cases, other modal analysis methods, or integration of this parameter into multi-parameter methods in future work may result in more reliable differentiation. Understanding of the wave-modes excited by the different fracture-modes also has implications for source-location, as identification of the correct modes is critical for selection of suitable wave velocities.
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Alasdair R. Crawford, Mohamad G. Droubi, Nadimul H. Faisal
Acoustic emission (AE) testing has previously been demonstrated to be well suited to detecting failure
in adhesively-bonded joints. In this work, the relationship between the fracture-mode of adhesively-
bonded specimens and the acoustic wave-modes excited by their failure is investigated. AE
instrumented Double-Cantilever-Beam (Mode-I fracture) and Lap-Shear (Mode-II fracture) tests are
conducted on similar adhesively-bonded aluminium specimens. Linear source-location is used to
identify the source-to-sensor propagation distance of each recorded hit, theoretical dispersion curves
are used to identify regions of the signal corresponding to the symmetric and asymmetric wave modes,
and peak wavelet-transform coefficients for the wave-modes are compared between the two fracture-
modes. It is demonstrated that while both fracture-modes generate AE dominated by the asymmetric
mode, the symmetric mode is generally much more significant during Mode-II fracture than Mode-I.
While significant scatter and overlap in results prevents the ratio of peak-wavelet transform coefficients
from being a robust single classifier for differentiation between fracture-modes in most cases, other
modal analysis methods, or integration of this parameter into multi-parameter methods in future work
may result in more reliable differentiation. Understanding of the wave-modes excited by the different
fracture-modes also has implications for source-location, as identification of the correct modes is critical
for selection of suitable wave velocities.
1. Introduction
Structural adhesive bonding is increasingly being utilized across a wide range of industries,
such as the aerospace, renewable energy, marine and automotive industries. Adhesives offer
a variety of advantages over more conventional mechanical fastening methods, including
improved stress distribution, low weight, corrosion resistance, damping properties and the
ability to join dissimilar materials and composites. They are however susceptible to defects
introduced throughout manufacture and service life which can lead to catastrophic failure.
These defects can include disbonds or weak “kissing” bonds, introduced by surface
contamination of the adherends, voids, due to inadequate quantities of adhesive or air
entrapment during lay-up, porosity, due to volatiles or entrained air, cracks, due to thermal
shrinkage or applied stressed in service, and poor cure, occurring from improper mixing or
inadequate thermal exposure [1].
Due to these potential defects, non-destructive testing (NDT) and condition monitoring is vital
if adhesives are to be used in safety critical applications. Acoustic Emission (AE) testing has
been well proven in its ability to detect adhesive failure and, particularly for large structures,
the ability to provide continuous real-time monitoring over a large area is advantageous and
makes AE an appealing technique to complement more conventional NDT techniques, such
as ultrasound and resonant-frequency based methods.
01 - Modal Acoustic Emission analysis of mode-I
and mode-II fracture of adhesively-bonded joints
Multiple studies of adhesively bonded joints have demonstrated the ability of AE to detect
initiation and propagation of debonding and adhesive cracking through the correspondence
between AE and drops in load during various fracture tests [2-5], while studies such as those
by Croccolo and Cuppini [6] have demonstrated the ability to predict the final failure load of a
joint, based on the acoustic emissions at lower load. Differentiation between debonding and
adhesive cracking has also been achieved by Galy et al. [3] through clustering based on typical
AE parameters, while work by Bak and Kalaichelvan [7] used peak-frequency analysis to
differentiate between the failure mechanisms of adhesive failure, light fiber tear failure and
fiber tear failure during lap-shear tests of composite specimens.
Dzenis and Saunders [8] successfully utilized the statistical pattern recognition software Vallen
VisualClass to differentiate between Mode-I (crack opening), Mode-II (shear) and Mixed-mode
fatigue failures of adhesively bonded joints. While it was demonstrated that differentiation
between fracture-modes was possible, the method used, and results reported provided little
insight into the fundamental differences between the recorded waveforms. The differentiation
between fracture-modes is extremely valuable in the case of adhesive bonds, as there is vast
disparity in the strength of bonds dependent on the loading orientation. For this reason, most
adhesively bonded joints are designed to be loaded predominantly in Mode-II, and application
of unexpected Mode-I loadings may therefore lead to catastrophic failure. The study will look
further into the differences in AE occurring from different fracture-modes.
It has been demonstrated by Gorman [9], amongst others, that the orientation of an AE source
affects the amplitudes of the wave-modes propagating from it. In-plane sources are seen to
create a greater extensional/symmetric wave-mode, while out-of-plane sources are seen to
create a greater flexural/asymmetric wave-mode. This finding has been previously used in
modal AE analysis of composites to aid in differentiation between delamination (out-of-plane)
and fiber-breakage or matrix cracking (in-plane) [10-11]. Understanding of the wave-modes
generated is also crucial for accurate source location. Due to differing propagation velocities,
it is critical that velocities used in calculating source-location correspond to the wave-modes
for which arrival times have been detected.
The aim of this study was to investigate the wave-modes generated by Mode-I and Mode-II
fracture of adhesively-bonded joints and to identify whether modal analysis has the potential
to discriminate between fracture-modes in a similar manner to which it has been used to
discriminate between failure mechanisms of composites. To achieve this, AE instrumented
Double Cantilever Beam (DCB) (Mode-I) and Lap-Shear (LS) (Mode-II/Mixed-mode) tests
have been conducted on adhesively-bonded aluminum specimens and the resulting AE
analysed, using continuous wavelet-transforms and theoretical dispersion curves to identify
the resulting wave-modes.
2. Experimental Setup
2.1 Specimen preparation
Both specimen types were manufactured from 3.175 mm x 50 mm HE30TF aluminium bar.
Adherends were cut to 300 mm long for the DCB test, and 360 mm long for the lap shear test.
Specimen widths and lengths were chosen to be as large as was practical for the available
test equipment, to minimize the effects of edge-reflections in the results, and to allow significant
propagation distance for the wave modes to separate through dispersion. The adhesive
bonding process consisted of surface preparation, adhesive application and curing. The
specimens were initially rinsed with acetone, before being abraded with P400 grade abrasive
paper, rinsed with acetone again, and then cleaned with Loctite SF 7063. Silicone grease was
then carefully applied to a 60 mm long region of the DCB specimens to prevent bonding and
thus create a pre-crack. Loctite EA 3430, a relatively brittle two-part epoxy adhesive, was then
applied through a mixer-nozzle to the bond areas of one adherend for each of the specimens.
The bond area for the DCB specimens covered the entire specimen, aside from the pre-crack,
while the bond area for the shear specimens was a 50 mm x 50 mm square, located 70 mm
from the ends of the adherends. Small 0.5 mm thick aluminium shims were then added into
the adhesive to maintain a uniform bond thickness as the other adherends were placed on top.
Once assembled, weights totaling 4 kg were added on top of each specimen and they were
left to cure for a minimum of five days, at an average temperature of 19°C and humidity of
about 20%.
2.2 Mechanical testing
Both types of specimen were tested using an Instron 3382 universal testing machine (UTM),
controlled through BlueHill 3 software. Loading blocks were bonded to the DCB specimens to
allow them to be mounted to the machine in custom made yokes. Lap shear specimens had
tabs bonded to each end and were then clamped into the machine using 50 mm mechanical
jaws. The loading rates used were 0.5 mm/min, based on ASTM D5528 01 [12], and 1.3
mm/min, based on ASTM D1002-10 [13], for the DCB and lap shear specimens respectively.
DCB tests were run up to a crosshead displacement of 10 mm, while lap shear tests were run
until complete failure was achieved. Each test was conducted four times to ensure
2.3 Acoustic emission setup
Two Physical Acoustics Micro80D differential sensors were used. These were connected to a
PC with a NI PCI-6115 DAQ through; Physical Acoustics 2/4/6 variable-gain pre-amplifiers (set
to 60dB), an in-house built signal-conditioning unit (providing an additional 12dB gain), and a
NI BNC-2120 shielded connector block. The system was operated through LabVIEW software,
with the signals being recorded continuously at 2.5 MHz and saved in *.tdms format. Signal
processing and analysis was conducted after testing, using MATLAB.
The sensor locations used were both on the same sides of the specimens. On the DCB
specimens, as indicated in Figure 1, one sensor was located at the end of the pre-crack, and
the other 10 mm from the end of the specimen. On the lap shear specimens, illustrated in
Figure 2, the sensors were located either side of the bond area, at distances of 90 mm and
200 mm away from the center of the bond area. Sensors were coupled to the specimens with
a layer of silicone grease and secured using aluminium adhesive tape. As well as recording
AE, a video camera was used to record crack propagation for the DCB test to verify the position
of the crack-front. This approach could not be used effectively for the shear specimens due to
the speed of their failure.
Figure 1. Double Cantilever Beam experimental schematic
(not to scale)
Figure 2. Lap Shear experimental
schematic (not to scale)
3. Signal processing
As the system was recording continuously, the initial step was to isolate hits for further analysis
and to discard the noise. This was achieved by averaging the RMS value of the signal over
200 data points, to create something similar in form to the upper wave envelope, and then
applying upper and lower thresholds. Hits of significant amplitude were identified by crossings
of the upper threshold. The start and end of the hit were then identified by the nearest crossings
of the lower threshold before and after this point. Threshold values were set at 0.05 V and 0.15
V, chosen based on the level of noise present in the recorded signals.
The identified hits were transformed into the time-frequency domain by continuous wavelet
transform. In this case the Gabor wavelet was used, as this provides the best combination of
time and frequency resolution. An example of this transformation from time to time-frequency
domain is illustrated in the upper panels of Figure 3. Arrival times, corresponding to the A0
mode at 300 kHz, were determined as the first peak in the 300 kHz band of the wavelet
transform to exceed 70% of the maximum WT coefficient. These arrival times, and the
separation distance between the sensors, were used to estimate the linear source location of
each hit, and therefore the propagation distance from the source to each of the sensors. Hits
located as occurring from outwith the potential bond regions of the specimens were excluded
from further analysis.
Based on the identified propagation distances, the arrival times of both the S0 and A0 wave-
modes are calculated using the theoretical dispersion curves for the adherends (generated by
Vallen Dispersion software). The central panel of Figure 3 shows these dispersion curves,
modified by the propagation distance, overlaid on the wavelet transform plot of the signal. This
allows certain peaks in the wavelet transform plot to be attributed to these wave-modes.
To allow quantitative analysis of the contributions of each wave-mode, the corresponding
peaks within a certain frequency band were extracted. The frequency band around 300 kHz
was chosen as it is close to the resonant peak of the sensor and contains significant content
from both wave-modes. There is also significant enough dispersion at this frequency to
differentiate between the wave-modes in the time-domain. The lower panel of Figure 3 shows
the WT coefficients in the 300 kHz band with the S0 and A0 peaks marked. The ratio between
the amplitudes of these peaks was then used to investigate the difference between the
fracture-modes. In a small number of hits the wave-modes could not be clearly identified or
separated due to factors such as overlapping of hits, in such cases the hits were excluded from
further analysis.
Figure 3. Example of signal-processing method. Top: Original AE signal. Middle: Wavelet Transform
plot with overlaid dispersion curves indicating symmetric (S0) and asymmetric (A0) wave-modes.
Bottom: Wavelet Transform coefficients for 300 kHz frequency band, with S0 and A0 peaks marked.
4. Results
4.1 Load results
Typical examples of the loading curves and AE source location results for the tests are shown
in Figure 4. As expected, the loading characteristics of the two specimen types vary
significantly. The DCB tests result in an approximately linear increase in load as the adherends
deflect elastically in the pre-crack region until the maximum load is reached. This is followed
by multiple small drops in load as the adhesive fails in sections, and small rises in load between
these, as the adherends elastically deform again. The lap-shear tests however, exhibit an
approximately linear region of elastic deformation up to their maximum load, followed by
sudden complete failure in which the adherends completely separate. The maximum loads
withstood by the two specimens should be noted, as the DCB specimens withstood loads in
the region of only 50 N, while maximum loads applied to the lap-shear specimens were in the
region of 2000 N. This disparity highlights the potential importance of being able to discriminate
between fracture-modes during condition monitoring.
4.2 Failure mechanisms
The main failure mechanism observed in all specimens was adhesive failure, with the adhesive
layer separating from one adherend as the bond between adhesive layer and adherend failed,
while remaining bonded to the other adherend. In the DCB specimens, and to a lesser extent
in two of the lap-shear specimens, some adhesive cracking was also found. In some regions
the adhesive failure would occur at the interface with the upper adherend, and in other regions
it would occur at the lower adherend. The result being that the adhesive layer cracked between
these regions, allowing sections of the adhesive to remain attached to either adherend. Figure
5 shows annotated examples of the failure mechanisms present in both types of specimen.
4.3 Acoustic emission source locations
In both specimen types, a small number of hits were recorded during the initial linear portion
of the loading. Most hits however, correspond to significant drops in load as the adhesive fails.
In the DCB specimen hits are spread throughout the test as crack slowly propagates through
the specimen, whereas in the lap-shear test, AE activity is concentrated around the moment
of final failure. The AE source locations identified in the DCB tests generally correspond well
with the visually observed crack-front recorded with the video-camera, with the hits initially
being centered around the tip of the 60 mm pre-crack and then progressing further along the
specimens as the crack opens. While the AE source location results generally correspond well,
there is some variation and scatter which is believed to be due to a combination of the following
factors; the crack-front will not be uniform due to the inhomogeneous bond quality, so the
location of the crack-front recorded at one side will not necessarily be accurate through the
entire specimen width. The use of a linear source-location method, as opposed to 2D or 3D,
will also generally result in a small level of error as not all hits will occur directly between the
sensors. In the lap-shear specimens hits are concentrated within the bond area, as would be
expected, although some hits are identified as occurring out with the bond area. This may
again be due to the limitations of linear source-location but may also be due in some cases to
the incorrect identification of arrival times due to interference between overlapping hits, a
problem which can also occur in the DCB specimens but is much more prominent in the lap-
shear tests due to the limited time in which the hits all occur.
a. b.
AE Source Location
c. d.
Figure 4. Examples of loading curves and source locations. (a) Loading of DCB test. (b) Loading of
lap-shear test. (c) AE source location and visually observed crack length for DCB test. (d) AE source
location for lap-shear test.
Figure 5. Example of failure mechanisms observed. Left: DCB specimen showing adhesive failure and
cracking of the adhesive layer. Right: Lap-shear specimen showing only adhesive failure.
4.4 Modal acoustic emission analysis
The resulting ratios of the peak wavelet-transform coefficients corresponding to the S0 and A0
wave-modes are presented in Figure 6. Both fracture-modes can result in a wide range of S0/A0
ratios being generated. For the DCB tests, values range from 0.0169 to 0.4178 with an overall
mean and standard deviation of 0.085 and 0.0848 respectively. Lap-shear tests produced
values ranging from 0.0616 to 0.7197 and with an overall mean and standard deviation of
0.1902 and 0.1425.
Figure 6. Ratios of peak wavelet-transform coefficients at 300 kHz corresponding to S0 and A0 wave-
modes. (a) All hits analysed. (b) Mean and std. deviation for each test. (c) Overall mean and std.
deviation for the two test types.
5. Discussion
The WT coefficient peak ratios show that in both tests the A0 mode is dominant and that there
is significant overlap between the sets of results. There is however a clear trend indicating that
the S0 mode is generally greater in the Mode-II lap-shear tests than in the Mode-I DCB tests.
This result appears to be in line with previous work, as Mode-I failure creates a clear out-of-
plane source, very similar to the delamination of composites, which has previously been shown
to create a dominant A0 component.
While the loading in the Mode-II test is applied in-plane with respect to the adherends, any
failure occurring at the interface with the adhesive is occurring at the surface of the adherend
rather than near the mid-plane, as can be the case for other in-plane sources previously
investigated, such as fiber-failure or matrix cracking in composites. It has been previously
demonstrated by Hamstad et al. [14] that while a signal generated by an in-plane source
located on the mid-plane will be dominated by the symmetric mode, the same source, applied
away from the mid-plane, can create a signal dominated by the asymmetric mode. This
provides some explanation as to why both fracture-modes result in signals dominated by the
asymmetric mode, despite the loading orientation. Additionally, a lap-shear test is technically
not a pure Mode-II test, while the loading is predominantly in shear, bending of the adherends
can result in a small Mode-I crack-opening component, making it Mixed-mode and potentially
contributing further to the generation of the A0 mode.
As both fracture-modes have a significantly higher amplitude A0 than S0 mode, a suitably
chosen threshold can be used to consistently select the arrival time of the A0 mode, without
risk of accidental selection of the S0 arrival time. If the Mode-II tests had resulted in a greater
S0 component, then a more sophisticated method would be necessary to select arrival times
and calculate source locations.
The results presented by Dzenis and Saunders [8], analysed using Vallen VisualClass, clearly
demonstrated the possibility to differentiate between fracture-modes using AE, they did not
however provide much insight into the fundamental differences in the signals which allowed
this differentiation. The results presented in this work indicate that it is likely that the difference
in wave-modes excited during their tests will have been one of the significant factors
contributing to the differentiation which was achieved, while other differences may have also
occurred from features such as the specimen geometries causing variation in attenuation and
reflections. An increased understanding of these factors allowing differentiation will be
beneficial if attempts are made to utilize these techniques on full scale structures, rather than
small laboratory specimens, as any method used will need to suitably account for the
dispersion, attenuation and reflection which will be present in larger structures with potentially
irregular geometries.
The use of the WT peak ratio as a classifier to differentiate between fracture-modes may be
feasible when considering multiple hits, i.e. an entire test, however due to significant variation
between hits, and the overlap between tests, it would not be possible in most cases to identify
fracture-mode based on a single hit. Future work should therefore consider either; other
methods to assess the modal content of the signals which may yield clearer discrimination, or,
combining this parameter with others to form a more robust method of discrimination.
Differentiation between hits occurring from the adhesive failure and cracking of the adhesive
layer has not yet been attempted within this study, and it is recognized that results for each
test may include hits from both failure mechanisms which may exhibit different characteristics.
Future work should address this issue by conducting tests capable of isolating each of these
failure mechanisms to identify the defining characteristics of AE occurring
6. Conclusion
The aim of this study was to investigate, for the first time, the AE wave-modes generated by
Mode-I and Mode-II fracture of adhesively-bonded joints (aluminium metal-to-metal) and to
identify whether modal analysis has the potential to discriminate between fracture-modes in a
similar manner to which it has been used to discriminate between failure mechanisms of
composites. Differentiation between fracture-modes is particularly important in adhesive joints
due to the vast disparity in strength between joints in Mode-I and Mode-II loading, assessment
of loading conditions through AE could therefore provide a very useful tool for structural health
monitoring. Understanding of the wave-modes generated by different fracture-modes is also
important for accurate source location. Due to the differing propagation velocities of the modes,
it is critical that the velocity used in source location calculations corresponds to the wave-mode
for which arrival times have been detected. From the work conducted, the following has been
Use of linear source location to identify propagation distances and theoretical
dispersion curves to identify arrival times, has successfully identified regions of the
time-frequency domain corresponding to the fundamental S0 and A0 modes.
Modal analysis, based on investigation of the amplitude-ratio of peaks in the
continuous wavelet-transform corresponding to the S0 and A0 modes, has revealed
clear differences between Mode-I and Mode-II/Mixed-mode fracture. While signals
from both fracture-modes are dominated by the A0 mode, the S0 mode is generally
greater in the Mode-II tests than in the Mode-I.
As the amplitude of the A0 mode is consistently higher than that of the S0 mode, a
suitably chosen threshold can be used as a reliable method to select the arrival
time of the A0 mode for the purposes of source location.
Analysis of the amplitude-ratio of wavelet-transform peaks corresponding to the
wave-modes has been demonstrated to reveal differences between the fracture-
modes when considering each test. However, due to the variation between hits
within each test, and the overlap between results from the two test types, it is
generally not possible to distinguish between fracture-modes based on a single hit.
Future work should therefore focus on investigation of other methods to assess
modal content of the signals or on utilizing the wavelet peak ratio in combination
with other parameters to provide a more robust classifier.
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... The study provides guidance for locating and identifying AE events occurring within adhesive joints, but neither fracture tests nor adhesive cracking are examined. In [32], a modal AE analysis of mode I and mode II fractures is carried out. AE source events are analysed, and location and identification guidance is provided. ...
... However, these arrival times may also have corresponded to antisymmetric waves (A 0 ), or even mixed wave modes (S 0 + A 0 ). This is due to the limited propagation media of the DCB specimen, which may have produced reflections and couplings of different wave modes, as seen in [32]. A modal analysis of such AE events might help differentiate wave mode types, but such analyses are still the subject of study [32] and thus beyond the scope of the current work. ...
... This is due to the limited propagation media of the DCB specimen, which may have produced reflections and couplings of different wave modes, as seen in [32]. A modal analysis of such AE events might help differentiate wave mode types, but such analyses are still the subject of study [32] and thus beyond the scope of the current work. The AE data in Figs. 4 and 5 show that AE events are located in the interior of the adhesive layer, which is in agreement with [3] and [4] where large FPZs were detected in bonded joints, most notably when tough flexible adhesives were used. ...
The usual way to evaluate the fracture toughness of bonded joints is via experimental characterization of the critical strain energy release rate. Different test procedures and data reduction methods for mode I fracture characterization can be found in the literature, such as ISO-25217, where crack length measurement is required. However, obtaining an accurate visual determination of crack length is often a challenge due to large fracture process zones (FPZ) and difficulties in reaching the bonded path. To compensate, structural health monitoring (SHM) techniques such as embedded Fiber Bragg Grating (FBG), digital image correlation (DIC), backface strain gauges and ultrasonic inspection are used as crack length monitoring. However, experimental work demonstrates the need for experimentation with non-intrusive methods. In the present work, acoustic emission (AE) testing is proposed to measure mode I crack growth in bonded joints. This is valid both for rigid adhesives with a small FPZ ahead of the crack tip and for flexible adhesives in which a correlation between AE event location and external analytical and numerical models confirm that a large FPZ is behind the crack tip. A correlation between the AE source location, visual location and numerical models determines the nature of AE events during the fracture process.
Experimental studies was carried out. The purpose was to develop a method to test fiberglass pipelines in operating mode. The acoustic emission method was chosen as the main method of nondestructive testing, and visual and dimensional inspection was chosen as an additional method. Acoustic parameters and acoustic emission properties of fiberglass pipes were determined. It was found that acoustic emission sensors can be installed at distances of up to 9-18 m from each other. A series of loading tests was carried out to refine the methodology. Every loading case was performed until leakage registration. In most cases, leakage occurred near the fillet at pressures of 2.2…3.0 from the working pressure, which indicates a large margin of safety for fiberglass pipes. It is confirmed that the acoustic emission method allows early defect detection. Based on the acoustic emission data, 4 main stages of fiberglass pipes degradation were identified. Visual and dimensional inspection was informative only at stages III – IV. Stage IV in most cases corresponds to the leakage. Even early stage of depressurization was registered as continuous acoustic emission. Signals with amplitudes exceeding 60…80 dB were registered at all loading stages. The location map became informative after filtering events by acoustic emission parameters. A methodology for the testing of fiberglass pipes and fittings in operating mode was developed. It contains, in contrast to the currently valid standards, specific numerical values of various quantities related to both the preparation and carrying out of acoustic emission testing and the classification of the identified sources of acoustic emission according to the degree of danger and allows to evaluate the residual life of fiberglass pipelines. The most informative parameter was the activity of acoustic emission; therefore, it is recommended to carry out loading without holding the pressure. It is planned to carry out additional experiments to clarify the mechanisms of fracture acting at each of the 4 identified stages of degradation.
Structural Health Monitoring (SHM) systems are commonly integrated in bonded joints for different applications in order to detect and predict potential fatigue and damages caused by internal and external agents they are subjected to during their operation life. However, each of the current SHM systems presents some drawbacks, as the reduction of structural properties or the difficulty in its implementation. This work deals with the use of a Carbon Nanotube film (Bukypaper) as a sensor in double cantilever beam (DCB) bonded joint specimens for crack growth monitoring purposes. Buckypaper (BP) sheets were manufactured and integrated in adhesive film layers and its integration quality was studied by Scanning Electron Microscopy (SEM). The effect of the integration of different thickness BPs in the mechanical performance of the bonded joints was also assessed performing DCB fracture tests. Also, electro-mechanical tests were conducted using the BP as the sensor, monitoring the output in the electrical resistance during the crack propagation. It was observed the capability of BP to detect and locate the damage during the test with a linear dependence between the electrical resistance measured in the BP and the deduced crack growth, proving the potential of the BP to monitor self-sensing bonded joints.
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A database of wideband acoustic emission (AE) modeled signals was used in Part 1 to ex- amine the application of a wavelet transform (WT) to identify AE sources. The AE signals in the database were created by use of a validated three-dimensional finite element code. These signals represented the out-of-plane displacements from buried dipole sources in aluminum plates 4.7 mm thick and of small and large lateral dimensions. The surface displacement signals at three far-field distances were filtered with a 40 kHz high-pass filter prior to applying the WT. The WTs were calculated with AGU-Vallen Wavelet, a freeware software program. The effects of propagation distance, AE source type, and the depth of the AE source below the plate surface were examined. Specifically, a ratio of the WT magnitude (WT coefficient) from the fundamen- tal anti-symmetric mode to that from the fundamental symmetric mode was studied for correla- tion with the AE source type. The WT magnitudes were those corresponding to a particular group velocity and signal frequency for each mode. For sources in the large plate located at the same depth, the ratios were able to distinguish different source types and exhibited only small changes with increasing propagation distance. But, when the variable of depth of the source was introduced, the ratios did not uniquely classify the AE source type. In the case of the small cou- pon plate specimen, reflections from the specimen edges distorted and complicated the WTs. Since the current coupon database excludes (except for one case) the parameter of changes in the distance of the source from the coupon sides, a full examination of these complications was not possible.
Failure behaviour of two types of adhesively bonded joints (composite-to-metal, metal-to-metal) has been studied under failure modes (Mode I: double cantilever beam (DCB) and Mode II: three-point end notch flexures (3-ENF)) using acoustic emission (AE) technique. The bonded specimens were prepared using two types of adhesive bond materials with three variations of adhesive bond quality. The effect of the presence of interfacial defects along the interface on the residual strength of the joint has also been studied. It was possible using the maximum AE amplitude method to select the AE events of mechanical significance. However, it proved difficult to propose a definitive AE trait for the mechanical phenomena occurring within specific AE event signals, for all adhesive types, bond qualities, and substrate configurations; therefore, all specimen combinations. There was a notable shift in spectral energy proportion as the AE source of mechanical significance varied along the specimen length for specimen combinations. However, it was difficult to confirm this distinctive trait for all specimen combinations due to difficulty in confirming the location and exact mechanical source. The proposed measurement technique can be useful to assess the overall structural health of a bonded system and may allow identification of defects.
In this study a series of joint systems, consisting of aluminium substrates bonded using an epoxy adhesive, were produced. Several levels of adhesion were achieved by altering the substrate surface treatment and the curing cycle of the adhesive. The goal of this study was to produce reduced-strength epoxy-aluminium joints that could be used as reference samples for ultrasonic non-destructive testing (NDT) studies. There is clearly a continuing challenge to improve the quality of the adhesively-bonded joint inspection to ensure the durability of the bonds, to monitor repairs, and to evaluate the strength of the bonds. However, developing and qualifying innovative or advanced non-destructive testing requires an essential preliminary step: a method for repeatedly producing reduced-strength bonded test specimens must be developed. In this study, in addition to a rigorous protocol to produce bonded joints, complementary ultrasonic CSCAN were realised to validate the homogeneity of the joints and to ensure that samples met all requirements so as to be considered as reference samples. Mechanical tests were performed to evaluate the mechanical strength of each joint and Acoustic Emission (AE) was used during the tests in order to confirm the expected fracture mechanisms.
The characterization of fracture toughness or critical energy release rate of adhesive joint in composite structures is a key parameter. In the present study, fracture toughness of adhesively bonded composite joints is experimentally investigated for the basic fracture modes. Experiments are conducted on the double cantilever beam, end notched flexure and edge crack torsion specimens to determine the fracture toughness of three modes, namely mode-I, mode-II and mode-III. Specimens are bonded with epoxy adherent and cured at room temperature. The fracture toughness values of mode-II and mode-III are 2.6 and 4.6 times respectively of mode-I. Acoustic emission (AE) technique is also employed to aid in determining the fracture toughness of bonded joints. The results indicate that AE signals have good correlation with load-displacement behaviour to determine the fracture initiation stage especially in the mode-II loading.
The purpose of this present study is to monitor the failure modes of pure resin and single layer of adhesively bonded lap joints using acoustic emission (AE) technique under tensile loading. Parametric analysis is performed using AE count rate, cumulative counts, time, frequency, amplitude and duration on the AE data obtained during the tensile test of adhesively bonded lap joints. After preliminary investigations in the parametric analysis, it was seen that AE amplitude parameter changes with the different AE events, thus failure modes were characterized using frequency analysis. Fast fourier transform (FFT) analysis has been proposed to identify the importance of peak frequency content of each failure mode corresponding to the AE hits using frequency FFT analysis. Short time fast fourier transform resulting frequency is correlated with FFT analysis of AE data, to find the peak frequency ranges for each of the failure modes. Scanning electron microscope as complementary, post-test inspection method is used to find microscopic evidence for the assumed assignment of failure modes.
This paper proposes a very promising acquisition-analysis procedure to evaluate real-time damage in carbon fiber-reinforced polymer (CFRP) composite plates by means of the acoustic emission (AE) method. It shows how, by using appropriate acquisition frequency filters and very narrow time windows, it is possible to avoid reflection at boundaries and successfully split the A0 and S0 Lamb modes of the AE signals. After that, an appropriate algorithm —based on the comparison of strength of both modes in time and frequency domains— allows one to associate each AE event to a particular damage mechanism (delamination, fiber breaking and matrix micro-cracking). Experimental results from three point bending tests carried out on 22-layer CFRP samples, with delamination artificially induced by a Teflon film, clearly demonstrate the real-time evaluation of the induced delamination and the beginning and growth of new ones.
It is widely demonstrated in literature that the presence and the density of adhesive bonding defects are difficult to estimate with conventional non-destructive testing techniques once the parts are assembled together. For this reason it is very important to set up a new methodology capable of estimating the adhesive bonding defect and the final releasing moment of the assembled joints. The purpose of this paper is to verify the performance of the acoustic emissions technique when applied, as a non destructive one, in this field. Our investigation aimed to highlight the good correlation between the density of the adhesive defect (low, medium and high) and the cumulative counts of the acoustic emissions and to verify the accuracy of the estimated final releasing moment of the coupling.
Acoustic emission (AE) from pure and mixed mode fatigue fracture of adhesive composite joints was recorded and analyzed. Transient AE signal classification was attempted by a computational pattern recognition analysis. Good separation was achieved for pure mode AE signals from the double cantilever beam (mode I) and end notch fracture (mode II) tests. AE signals from the mixed mode lap joint test were found to be closer to the mode II fracture signals. The results may provide insight into the fracture mechanisms in joints and can be used for the development of mechanism-based predictive models of fracture and life.
As a result of its continuous and in situ detection capabilities, the acoustic emission (AE) technique is the prime candidate for damage monitoring in loaded composite structures. None of the AE analysis techniques used in laboratory studies has, however, proven to be capable of consistently dealing with the difficulties encountered in larger structures: large amount of data, the elimination of noise sources and the influence of wave propagation effects (attenuation, dispersion). This work will use the modal acoustic emission (MAE) technique as a more intelligent and efficient way of analysing AE results. AE waveforms obtained during tensile and bending testing of CFRP laminates will be presented. It will be demonstrated how taking into account the modal nature of AE waves can in future lead to more quantitative and accurate results.
Lead breaks (Hsu-Neilsen source) were used to generate simulated acoustic emission signals in an aluminum plate at angles of 0, 30, 60, and 90 degrees with respect to the plane of the plate. This was accomplished by breaking the lead on slots cut into the plate at the respective angles. The out-of-plane and in-plane displacement components of the resulting signals were detected by broad band transducers and digitized. Analysis of the waveforms showed them to consist of the extensional and flexural plate modes. The amplitude of both components of the two modes was dependent on the source orientation angle. This suggests that plate wave analysis may be used to determine the source orientation of acoustic emission sources. Keywords: acoustic emission, plate waves, source orientation * Work supported by NASA Langley Research Center Introduction In conventional acoustic emission (AE) testing, the elastic wave produced by an AE source is converted to a voltage signal by a resonant transduc...