Coating adherence in galvanized steel assessed by acoustic ...

Coating adherence in galvanized steel assessed by acoustic
emission wavelet analysis
Antolino Gallego a, *, José F. Gil a , Juan M. Vico a , José E. Ruzzante b , Rosa Piotrkowski c
Abstract
a E. U. Arquitectura Técnica, Universidad de Granada, 18071 Granada, Spain
b ENDE, Comisión Nacional de Energía Atómica, 1650 Pcia. Buenos Aires, Argentina
c ECyT, Universidad Nacional de General San Martín, 1653 Pcia. Buenos Aires, Argentina
Received 7 July 2004; received in revised form 18 October 2004; accepted 5 January 2005
Coating–substrate adherence in galvanized steel is evaluated by acoustic emission wavelet analysis in scratch tests on hot-dip galvanized
samples. The acoustic emission results are compared with optical and electron microscopy observations in order to understand
coating features related to adherence and to establish criteria aimed at improving the manufacture process.
Ó 2005 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Keywords: Coatings; Galvanized steel; Acoustic emission; Scratch test; Wavelet analysis
1. Introduction
Scripta Materialia 52 (2005) 1069–1074
An efficient solution to problems related to the durability
of reinforced concrete beams is obtained by using
a coating of Zn (galvanized steel) to protect steel reinforcement
from corrosion [1–3]. The use of this type of
coating has nowadays been extended to different metallic
applications. Although coating–substrate adherence
is high due to the creation of various Zn–Fe alloys during
the coating forming process [4], certain applications
require a special quality control. Nevertheless, there is a
lack of agreement on the type of adherence test to be
used and also on established quality control criteria.
In this paper we propose to evaluate the coating–substrate
adherence with the scratch test (ST) provided with
acoustic emission (AE). ST is generally used as a coating
adherence test [5–9]. Furthermore, AE is especially suit-
* Corresponding author. Tel.: +34 958 249 508; fax: +34 958 243 104.
E-mail address: antolino@ugr.es (A. Gallego).
1359-6462/$ - see front matter Ó 2005 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.scriptamat.2005.01.037
www.actamat-journals.com
able to evaluate the dynamic state of bulk and surface
defects by means of the analysis of elastic waves emitted
during microfracture processes [10]. It is nowadays used
in material science and engineering research [11]. Because
AE is typically a non-stationary process, wavelet
transform (WT) is a suitable tool for managing data
[12,13].
ST, AE and WT, previously applied to other metallic
coatings by some of the authors [14–16], have not yet
been reported in the literature with regard to the study
of galvanized material. We present in this paper the results
of these tests obtained for hot-dip galvanized samples
with variable coating thickness. In order to identify
different fracture mechanisms of the coating the acquired
AE signals were submitted to an analysis process
aimed at obtaining parameters or features, which could
then be correlated with optical microscopy (OM), scanning
electron microscopy (SEM) observations and
metallic chemical composition determination. The purpose
was to establish adherence levels in connection with
the manufacture process, in order to improve quality
control criteria.

1070 A. Gallego et al. / Scripta Materialia 52 (2005) 1069–1074
2. Experimental
2.1. Samples
Steel plate samples were 50 mm · 20 mm · 4 mm.
They were galvanized in a process that included the following
consecutive stages: degreasing bath at 80 °C,
elimination of iron oxide by immersion in an aqueous
solution of 15% hydrochloric acid at 35 °C, bath
containing aqueous ammonium chloride at 80 °C,
immersion in a Zn bath at 450 °C and air cooling. Samples
were then examined visually and the thickness of
the coatings was assigned by the induced currents
method.
Five batches of 20 samples each were obtained,
according to their average immersion time. The samples,
hanging on vertical wires, were slowly introduced into
the Zn bath. Due to this procedure, the immersion time
was then different for samples corresponding to the
same batch and also varied along each sample. For this
reason the coating thickness of each sample was nonhomogeneous.
The thickness assigned to each sample
was the average of three values measured at different
points, with a dispersion of 20%. Moreover, average values
were evaluated for each batch. According to these
results samples were classified according to coating
thickness as high (H) 200–220 lm, medium (M) 140–
150 lm and low (L) ffi 100 lm. Five samples of each
type were selected for the present investigation. They
were designated as Li, Mi, Hi (i =1...5).
2.2. Coating characteristics
Samples L5, M5 and H5 were cut transversally and
prepared for the metallographic studies. Coatings were
examined by OM and SEM and the metallic composition
was analyzed by energy dispersive X-ray (EDX)
analysis. Coatings were non-homogeneous and the matrix–coating
interface boundary and the exterior surface
were not flat at all. The different and well-known
Zn–Fe phases [4] were observed from steel to zinc
(see Fig. 1): gamma (a very thin and uniform layer
along the coating), delta (very well defined), zeta (with
columnar grains emerging from the delta/zeta interface)
and eta (almost pure Zn, present in a two phase region
together with small dispersed zeta grains). Zeta and eta
phases were intermingled and their distribution showed
a great variability along the coating. In some points the
zeta phase grains reached the exterior surface. These results
were obtained by optical and EDX composition
studies across coatings. Fig. 2 shows one of these
results.
2.3. Scratch tests
Scratch tests were performed under controlled conditions
with a device that consisted of a loaded probe with
a diamond indenter moving linearly along the sample at
constant speed and with linearly increasing force (0–
150 N) for 180 s (Fig. 3). The steadily increasing contact
load causes tensile stress behind the indenter tip (trailing
edge) and compressive stress ahead of the cutting tip
(leading edge). The detection system used was MIS-
TRAS 2001 from Physical Acoustics Corporation
(PAC). The piezoelectric sensor, with frequency band
100–1000 kHz, was attached with coupling wax on the
topside of the samples. Then signals passed through
pre-amplifiers (60 dB) and were measured by means of
the AEDSP-32/16B card. The threshold was set at
25 dB, and signals were digitized at 4 MHz/8 bits. In
the present paper, the hit parameters analyzed were energy
and cumulative energy throughout the test. ST
with AE were performed on samples Li, Mi, Hi
(i =1,..., 4).
Fig. 1. Transverse optical micrographs showing coating phases. Left: L-sample; Center: M-sample; Right: H-sample.

Fig. 2. L-Sample. Lower: Points where EDX measurements were
performed. Upper: Results. Fe contents: near 0%: eta phase; 1–9%:
zeta phase; 9–17%: delta phase; 17–99% gamma phase; 100%: steel.
Experimental error ± 0.01 at.%.
Diamond tip
Sensor
Load Cell
Sample
Load
3. Results and discussion
Scratch
Fig. 3. Experimental setup.
3.1. Optical and electron microscopy
Three scratches of approximately 1.1 cm were performed
on each sample. OM images with high magnification
were obtained along scratches on samples H1, M1
A. Gallego et al. / Scripta Materialia 52 (2005) 1069–1074 1071
AE Equipment
and L 1, and were composed as a unique image with standard
software. Scratches were also observed by SEM
and the metallic chemical composition along each
scratch was assessed with EDX, taking into account that
the penetration depth increases with the indenter advance.
Scratch lines widened as penetration increased.
Moreover, scratches were not straight lines; some deviation
occurred, which was especially noticeable in H samples.
This is due to the heterogeneity of the coating: the
diamond tip had to go around the heterogeneous obstacles
that could be zeta phase grains at the points where
they reached the surface. For the sake of brevity, we do
not include the optical microscope composite image
of scratches in the present paper.
A number of tiny marks appeared at the beginning of
the scratches, corresponding to plastic deformation of
the coating; however, the relevant feature in all images
(for all scratches and samples) was the presence of some
apparent transverse cracks that were revealed upon further
examination to be folds. This has the important
meaning that the failure was interfacial. As an example,
in Fig. 4a and b we can see optical and scanning electron
microscope images of a fold. Noticeable folds appeared
at roughly 50% and 70% of total scratch length in all
cases.
3.2. EDX determination
EDX and SEM were used to measure metallic chemical
composition along the central line of scratches for
each type of sample. In the first stages of scratching,
the Fe% was low enough to infer that only the eta phase
was reached. From an intermediate stage, measurements
suggest that the zeta phase was reached. This behavior
holds up to the final stage, indicating that the indenter
never touched the matrix, or even the delta and gamma
phases. Table 1 shows the results for one of the samples.
The metallic composition was determined at 21 successive
points along the center of a scratch. The nonuniformity
of the measured values, which exceeds
experimental errors, is consistent with the non-uniformity
of eta and zeta phase distribution.
3.3. Acoustic emission
Fig. 5 shows the parameters energy and cumulative
energy for scratches in the three types of sample. The
noticeable steps in cumulative parameters and the peaks
in energy, in graphs where the independent variable is
the % of total scratch length, are very close to the position
of the folds observed in micrographs.
3.4. Acoustic emission processed by wavelet analysis
AE is a non-stationary process, i.e. the power
spectrum changes with time, where short and long-time

1072 A. Gallego et al. / Scripta Materialia 52 (2005) 1069–1074
phenomena coexist. For this reason a scale-time procedure
like WT is an ideal tool to manage data. WT presents
advantages over alternative methods like the
short time Fourier transform (STFT) because suitable
temporal and frequency windows are simultaneously defined
along the calculation. WT applied to AE signals
enhances the sharpness of results, thus allowing further
conclusions.
A wavelet w(t) is an oscillating function of short
duration, temporarily localized around the center
t = 1/2. Its spectrum j^ wðxÞj 2 concentrates in a bilateral
band 0 < x1 6 jxj 6 x2. By means of dilatations and
displacements this mother function generates a family
of elemental functions or atoms, wjk(t) with localization
in time-scale, varying in an inverse proportion. By properly
choosing the wavelet w(t), the generated family constitutes
an orthonormal basis of the space of signals with
finite energy. Thus, given a signal s(t), it is possible to
represent it by the series [12,13]:
sðtÞ ¼ X X
where
cjk ¼
Fig. 4. Micrographs of folds. Sample H1, scratch 3. Left: Optical microscope image. Right: Scanning electron microscope image.
Table 1
Metallic composition (in at.%) at points of scratch 1, sample H1 Point 1 2 3 4 5 6 7 8 9 10 11
Fe(%) 0.96 0.31 0.32 0.38 0.23 0.21 0.26 0.37 1.11 0.87 0.51
Zn(%) 99.04 99.69 99.68 99.62 99.77 99.79 99.74 99.63 98.89 99.13 99.49
Point 12 13 14 15 16 17 18 19 20 21
Fe(%) 0.30 0.54 0.38 0.42 0.34 0.37 0.31 0.39 0.35 1.51
Zn(%) 99.70 99.46 99.62 99.58 99.66 99.63 99.69 99.61 99.65 98.49
Experimental error ± 0.01 at.%.
j
Z 1
1
k
cjkw jkðtÞ
sðtÞw jkðtÞdt
These coefficients summarize without any redundancy
the whole signal information. In addition, the energy
relation holds:
Z 1
1
jsðtÞj 2 dt ¼ X X
j
k
jcjkj 2
WT was applied to our signals in order to corroborate
the results shown in Section 3.3. and, if possible, to enhance
the time (or position along the scratch) location of
changes in the AE energy related to the development of
significant folds. WT with the Haar basis was employed
in calculations for simplicity reasons [12]. When compared
with other wavelets such as gaussian, symmlet
or Daubechies, the results were essentially the same.
Fig. 6 shows the energy-position-scale wavelet diagrams
for the AE data displayed in Fig. 5. More intense
colors correspond to higher acoustic energy. According
to our assumptions, going from lower to higher % position,
the first spots correspond to plastic deformation
and detachment of small zeta grains. Likewise, more intense
spots, located at definite % positions correspond to
zeta/delta, delta/gamma or gamma/steel interface separation.
These interface separations appear to be what
produces the folds observed in the micrographs. WT results
(Fig. 6) are more accurate than those obtained by
traditional AE signal processing (Fig. 5). The highest
values in AE energy (Fig. 6) corresponded quite well
with fold positions. In spite of the fact that the indenter
had not reached interfaces, the stress field produced by
increasing the contact force could have been sufficient
to induce the breakaway of successive layers.
It was observed that AE activity increased when
the coating thickness decreased in the studied range.

Energy (eu)
Energy (eu)
Energy (eu)
1.1
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Relative Position (%)
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
Relative Position (%) Relative Position (%)
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Relative Position (%)
A. Gallego et al. / Scripta Materialia 52 (2005) 1069–1074 1073
Accumulated Energy (eu)
Accumulated Energy (eu)
Accumulated Energy (eu)
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
45
40
35
30
25
20
15
10
5
Relative Position (%)
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
0
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Relative Position (%)
Fig. 5. Upper: sample H1, scratch 1. Middle: sample M1, scratch 3. Lower: sample L1, scratch 2. Left: acoustic energy. Right: accumulated acoustic
energy.
Fig. 6. Energy-position-scale wavelet diagrams. Red: highest energy, blue: lowest energy. Same samples and scratches as in Fig. 5. Left: H-sample.
Middle: M-sample. Right: L-sample. (For interpretation of the references in color in this figure legend, the reader is referred to the web version of this
article.)

1074 A. Gallego et al. / Scripta Materialia 52 (2005) 1069–1074
Moreover the steps in cumulative energy, which corresponded
to the development of significant folds, showed
up at lower % positions along the scratch (i.e. at lower
depths inside the coating) when the thickness was lower.
Therefore, coating performance improved when going
from lower to higher thickness in the studied range.
The results of the present paper constitute a step forward
in recommending the use of AE parameters as
indicators of coating failure, in on-line measurements,
instead of a posteriori microscopic determinations.
4. Conclusions
Acoustic emission proved to be a good technique for
assessing coating/matrix adherence of galvanized steel,
as it did in previously studied coatings on metallic samples
[14–16]. The coating breakdown could have occurred
by adherence failure at phase interfaces, but the
matrix would have never been touched by the indenter
in the range of forces applied in the present work (0–
150 N). Coating performance improved with thickness
in the range 100–200 lm. Future work will be related
to the evaluation and comparison of hot-dip and electrolytically
galvanized samples, with different coating
thicknesses and different degrees of corrosion.
Acknowledgments
The authors are grateful to EUROTEGA S.A., Granada,
Spain, for the galvanizing process, and to Eng.
J.L. Piqueras and PhD. J. Rodriguez (University of Granada)
for interesting discussions.
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