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ELECTROCHIMICA
DIRECT°
4
ELSEVIER
Electrochimica Acta 49 20042787-2793
www.elsevier.com/locate/electacta
A practical evaluation of electrochemical noise parameters
as indicators of corrosion type
H.A.A. Al-Mazeedi, R.A. Cottis
Corrosion and Protection Centre, UMIST,P.O. Box 88, Sackville Sfree4 ManchesterM6O JQD, UK
Received 3 May 2003; accepted 6 January 2004
Available online 30 April 2004
Abstract
While electrochemical noise EN measurement has been used in corrosion monitoring for many years, the true capabilities of the technique
and the optimal methods for extracting useful information from the collected data are only now becoming clear. This paper examines the
information that can be obtained from EN measurement, both from a theoretical and a practical perspective.
2004 Elsevier Ltd. All rights reserved.
Keywords: Electrochemical noise; Corrosion monitoring; Linear polarization resistance; Corrosion inhibition; CO2 corrosion
1. Introduction
Conventional electrochemical convsion monitoring using
the linear polarization rnsistance LPR method is well es
tablished for the determination of average cormsion rate.
The method is rnlatively simple to implement and reliable,
except in a few well-debned cases where the requirnd con
ditions are not met. Morn rncently the electrochemical noise
EN method has been studied by many rnseaith groups and
implemented as a pmctical cormsion monitoring system by
a few pioneers see 1I for a rncent review. In many appli
cations though not all the electrochemical noise rnsistance
Rn, determined as the standard deviation of the potential
noise divided by the standard deviation of the cuntnt noise,
has been found to be compamble to the linear polarization
rnsistance Rn, determined by LPR. However, Rn tends to be
mther more variable thanR, and it offers littleadvantage it
might be claimed that Rn requirn less complex measumment
equipment, but this is barely signibcantwith the low cost of
modem electronics. Whern EN does offer the pmspect of
signibcant benebts compared to LPR is in the detection of
localized corrosion. The noise is pmduced by fluctuations
in the electrochemical pmcess, and larger fluctuations will
typically be indicative of a morn localized process. A num
0Corresponding author. Tel.:
+
44-161-236-3311;
fax: + 44-161-228-7040.
E-mail address: [email protected]
R.A. Cottis.
0013-4686/S - see front matter
2004 Elsevier Ltd. All rights reserved.
doi: 10. 1016/j.electacta.2004.01.040
ber of parameters have been proposed for the identibcation
of localized corrosion; these are described below. They have
been subjected to theoretical analysis, and to experimental
tests, but none of these tests have been comprnhensive. The
oretical analyses necessarily make a number of assumptions
about the noise genention pmcess, while most experimen
tal studies have examined only one or two of the pmposed
pammeters or have been based on mther limitedthtasets. In
this paper, a statistical approach is used to compare the dis
crimination ability of some of the pammeters that have been
proposed for the identibcationof the mte or especially the
type of the corrosion pmcess. A relatively large dataset is
used appmximately 3500 points, corrnsponding to 1000 h
of testing, and each point corrnsponding to a 1024 sample
time rncord, based on studies of two cormsion systems.
2. Electmchemical noise measurement
The conventional EN measurement method uses thne
electrodes. Two of these me working electmdes, between
which the electmchemical currnnt noise ECN is measurnd
using a zero-resistance ammeter ZRA, so that the two
working electrodes me at the same potential. At the same
time the electmchemical potential noise, EPN, is measurnd
as the fluctuationin the potential of the working electrode
pair relative to a reference electrode. In labontory work the
refernnce electmde is typically a tme reference electmde
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H.A.A. Al-Mazeedi, R.A. Coil/s /ElectrochiniicaActa 492004 2787-2 793
such as the satunted calomel electmde, SCE, while in cor
rosion monitoring applications the reference electrode may
be nominally identical to each of the two working electmdes.
The latter conbguntion modibes the behaviour since the
reference electrode is also producing noise, but this can be
corrected for if the thite electmdes can be assumed to be
similar 2I.
frequency, is being calculated fmm a measurement made at
a low frequency. For a detailed explanation maders are re
ferred to
or to standard shot noise texts, but an analogy
may help readers to appreciate how the analysis works:
Consider the Bow of trathc down a mad, with a bxed av
enge rate of carriage of people. if the number of peo
ple passing a bxed point each minute is measumd many
times, and the properties of the distribution of the ob
served number of people is studied, it will be reasonably
obvious that the standard deviation will be larger if all the
people alt in buses canying 50 people, nther than cars
with one person each car. This is a shot noise pmcess, as
suming that the movements of each vehicle a unaffected
by other vehicles, and it can be shown that the avenge
number of passengers can be determined from an analysis
of the observed mean and standard deviation.
2.]. EN analysis methods
Having measured the ECN and EPN, the next problem
is how to interpmt the data obtained. Them is, as yet, no
general theoretical description of the chancteristics of EN
data, but an analysis is available for the special case of a
shot noise process.
Shot noise is pmduced when the current takes the form
of a series of statistically independent packets of charge,
with each packet having a short duntion.1 The total charge
passing in a given sample interval is then a sample fmm a
binomial distribution,which, ifthe avenge number of pulses
in the sample interval is masonably large, approximates to
a normal distributionwith known properties.
if this theory is applied to EN, thne pammeters can be
obtained: 1corr the avenge cormsion current, q the avenge
charge in each event, and f the fmquency of events.
Only two of these pammeters are independent, since
I corr
= CJfn
It is not possible to measure Icorr, q and f directly, but it is
possible to estimate them from the measumd ECN and EPN:
BBr
-
corr
n
=
q
Bb
n
-
‘corr
-
-
-
-
q
82b
whem Iii isthe standard deviation of current, LIE the standard
deviation of potential and b the bandwidth of measumment.
It should be noted that f, q and similar statistical pa
rameters pmvide an avenge value over the period the term
‘calculation sample interval’ is used hem to indicate thispe
riod, which may or may not be the same as the measurement
sample interval, depending on how the calculation is per
formed for which they have been calculated. Furthermom,
f is essentially an estimate of the number of events occur
ring withinthe calculation sample interval. The derivation of
the theory assumes that high fmquencies have been excluded
fmm the measurement. Some commentators have been con
fused by the fact thatfn, which typically has a relatively high
1
In this context, short means short relative to the period of the
frequencies being used in the analysis, so if we conbne ourselves to
frequencies of the order of 0.01 Hz, events lasting for 10 s can still be
considered to be short
In the case of electrochemical noise, it is necessaiy to
infer the number of events occuning each second, since
we cannot measum it directly, but otherwise the analysis is
exactly equivalent to that for the road analogy.
The theomtical analysis assumes that them are a reason
ably large number of events occurring in each calculation
interval since this is necessaiy for the distribution to be
appmximated by a normal distribution, so the calculation
sample interval is ideally reasonably long, i.e. the measure
ment should cormspond to a low fmquency. For this mason,
a better method of estimating the shot noise pammeters is
probably to use estimates of the low fmquency power spec
tral density PSD of potential and curmnt, as this permits
mom precise selç9tion of the fmqueny of the meas.yrement.
In this case. 97/ his mplaced by Wand lIE’ hisre
placed by W, where ‘‘i and
are the PSD of curmnt
and potential
Having obtained ‘corr’ q and fn, the next question is how
they mlate to the nature of the cormsion pmcess. As only two
of the pammeters a independent, we only need to consider
two of them, and for most purposes it is most relevant to
consider ‘corr and fn
clearly describes the avenge corrosion nte in a way
that will be familiar to all corrosion engineers.
fn describes the frequency of events. In general, it is ex
pected that high fmquency events will tend to occur all
over the surface, and the cormsion will therefom be ma
sonably uniform. In contmst low fmquency events must
be removing mlatively large amounts of material at indi
vidual locations, and the corrosion willtypically be rather
localized. Thus fn pmvides an indicator of the localization
of corrosion, with a small fn indicating localized corro
sion, and a large f indicating uniform corrosion.
* ‘corr
*
Other pammeters that have been used for the identibcation
of localized corrosion typically have a less well-debned the
oretical basis. One of the brstpammeters proposed was the
coethcient of variation of curmnt-the standard deviation of
cuntnt dividedby the mean curmnt. The coefkient of varia
____
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H.A.A. Al-Mazeedi, R.A. Coals /ElectrochiniicaActa 492004 278 7-2 793
tion is a standard statistical term, and it isused to indicate the
mlative variability of a distribution. The problem with using
it for the interpretation of EN data is that itis only validfor a
single-sided distributioni.e. a distributionwhere every point
can only be positive or every point can only be negative-an
example might be the number of peas in each packet of a
batch of frozen peas. In the case of EN as normally mea
sured, the measured curmnt is expected to be centred on
zero, and the distributionis denitely not single-sided. Con
sequently the coefcient of variation is an unwliable pamm
eter it can be shown 141 that for ideal data the coefcient
of variation is expected to be pmportional to the number of
samples used in the measurement, and independent of any
mal electrochemical properties of the system being studied.
An obvious limitation of the coefcient of variation of
curmnt is that it is iniiite in the event that the mean current
happens to be exactly zem. In order to overcome this lim
itation, the localization index sometimes called the pitting
index was introduced. This is dened as the standard devia
tion of current divided by the rm.s. curmnt. As the expected
value of the rm.s. current is, Iean + I oise this results in
the localization index tending to the coefcient of variation
when the latter is much less than 1, and to 1 when the co
efcient of variation is gmater than 1. In other words it is
effectively the coefcient of variation limited to a maximum
value of 1. Consequently it suffers the same limitations as
the coefcient of variation.
A valid form of the coefcient of variation is obtained
by dividing by ‘corr rather than the mean current, since the
measumd curmnt noise is arguably a noise in 1corr, and 1corr
is clearly single-sided. if it is assumed that Icorr can be de
rived from Rn, then the "tme coefcient of variation" can be
obtained:
1J
tme coefcient ofvariation
11/
=
-
I corr
=
B
A similar pammeter, described as the Pitting Factor, has
been used by Eden and Bmene
In this case ‘corr was
obtained by another method harmonic analysis, and a
form of specimen aita normalization was used see below
for further discussion of this, but the nal msult is ex
pected to behave in a similar way to the tme coefcient of
variation. Furthermore, both of these pammeters ait pro
portional to the standard .eviation of potential, and hence
inversely pmportional to 7. For this mason they alt not
considemd further-other than questions associated with
area and bandwidth normalization, they can be considered
as equivalent to fn.
3. Area and bandwidth normalization
Cormsion scientists and other electmchemists am used to
the idea that curmnts in electrochemical systems can be nor
malized for specimen size by using the current divided by
2789
the specimen ama-the current density. Probably because
of the familiarity of this approach, them is a tendency to as
sume that is also correct to normalize the standard deviation
of curmnt by dividing by the specimen area. Similarly, elec
tmchemical potential is genenlly independent of specimen
ama, and it is therefom assumed that this also applies to the
standard deviation of potential. Both of these assumptions
am incormct-if the noise fmm individual areas of the spec
imen can be assumedobe independent, then !I is expected
to be pmportional to A, whem A is the specimçp area and
A. if this
1E is expected to be inversely pmportional to
behaviour is obtained, then the cormct area normalization
for the shot noise pammeters is as might be expected; q is
independent of area, and fn is proportional to ama, so can
be reported as events per second per unit area.
For the other localization indicators that have been pmposed, the cormct area normalization is rather counter in
tuitive. As an example, the tme coefcient of variation has
been dened above in terms of the standard deviation of
current divided by the cormsion current. It is tempting to as
sume that this dimensionless msu4is correct. However, Ili
is expected to be pmportional to A, while Icorr is pmpor
tional to A, so the tme coefcieijt of variation is expected
to be inversely pmportional to A, and should therefore be
reported with units of cm.
In addition, it should be appreciated that the measumd
standard deviation is a function of measumment bandwidth.
This is properly handled in the shot noise analysis, but ig
nomd in most other pammeters.
While these factors should be understood when analysing
EN data, it should also be appreciated that the effects of
specimen ama and measumment bandwidth am only of ma
jor signicance when they are changed. As most measum
ments includingthose reported here use constant specimen
ama and measurement bandwidth, the mnking of msults will
generally be cormct.
4. Experimental
The experimental work pmsented in this paper had the
objective of understanding the tmnsient corrosion processes
that occur during the depletion of an inhibitor. Two sys
tems wem used, steel in mixtures of nitrite and chloride,
and steel in CO2 satunted solution with thioacetamide as
an inhibitor In both cases the steel used was a mild steel
to B5970:080A15. The nitrite-chloride solutionswem based
on distilledwater, to which varying amounts of sodium chlo
ride and/or sodium nitrite wem added. The C02 system was
based on 3% NaC1, saturated with CO at ambient pressum
the satuntion with C02 also sewed to deaente the solu
tion, and with the pH adjusted to 5.5 with HC1 or NaOH.
In order to examine the effect of changes in the com
position, one solution was mplaced by another at intervals
thmugh the test. This was achieved by pumping solution
into and out of the test vessel using a two-channel peristaltic
2790
H.A.A. Al-Mazeedi, R.A. Coil/s /ElectrochiniicaActa 492004 2787-2 793
Table 1
Experimental sequences
Experiment
Solution
Duration h
Corrosion type
Label
la
lb
ic
lOOppmNO2°+ l000ppmCl0
l000ppm NO20 + l000ppm Cl0
l0000ppm NO20 + l000ppm Cl0
25
25
25
Pitting
Pitting changing to inhibition
Inhibition
P1
2a
2b
100 ppm NO2
lOOppmNOi°+ l000ppmCl0
25
167
Inhibition
Pitting
12
P2
3a
3b
l000ppm Cl0
lOOppmNOi°+ l000ppmCl0
25
168
Uniform corrosion
Pitting
Ui
P3
4
3% NaC1 saturated with CO2 pH 5.5
136
Uniform corrosion
U2
Sa
Sb
3% NaC1 saturated with CO2 pH 5.5
3% NaC1 saturated with CO2 pH 5.5
lppm thioacetamide
50
192
Inhibition
Pitting changing to uniform corrosion
13
U4
6a
6b
3% NaC1 saturated with CO2 pH 5.5 + lppm thioacetamide
As above, but CO2 bubbling stopped, and exposed to the air
50
117
Inhibition
Pitting/uniform corrosion
*
+
pump. This msulted in an exponential decay in composition,
with a time constant of approximately 500 s.
The sequences of solutions used, together with the corm
sion behaviour observed, am summarized in Table 1.
The cormsion type indicated in Table 1 was inferred from
visual observation of the sample, coupled with the behaviour
of these systems as reported by earlier workers especially
in the case of the chloride/nitrite system and visual inter
pmtation of the electrochemical noise time records. The La
bel given in Table 1 am used in the gums to indicate the
various test sequences, sections labelled ‘*‘ have not been
plotted, in one case because the type ofcorrosion varied sig
nicantly over the period of the test, and in the other case
because the test duplicated other data
Electmchemical noise thta wem obtained using the con
ventional thite electrode technique
A saturated calomel
reference electmde was used to measure the potential of
a pair of mild steel working electmdes. The sampling
quency was 1 Hz.
In a practical monitoring situation it seems probable that
two pammeters will be derived fmm EN measumments:
1. A measure of the average corrosion nte. This will almost
inevitably be based on Rn.
2. A measure of the tendency to localization of the corro
sion. A range of pammeters, including those indicated
above, have been proposed for this purpose.
Thus a key test for any localization indicator is its ability
to discriminate between different types of corrosion. In order
to evaluate thisfor the data obtained inthis work, a statistical
C
10000
100000
1000000
10000000
R11 ohm/cm2
-uniform corrosion
fit
5. Analysis pmcedurcs
a
1000
Ii
U3
-c
100
*
-pitting
-inhibition
Fig. 1. Cumulative probability plot for R11 for all of the corrosion systems tested see Table 1 for an explanation of the labels used.
H.A.A. Al-Mazeedi, R.A. Coals /ElectrochiniicaActa 492004 278 7-2 793
0.8
j06
0.4
It
=
E
=
C-
0.2
0
1 001J
f, Hz/mY
Fig. 2. Cumulative probability plot forfn for all of the corrosion systems tested.
-M
0
0
0
ci
>
It
=
E
=
C
0,01J1
0,001
0,01
0,1
1
10
q nC
Fig. 3. Cumulative probability plot for q for all of the corrosion systems tested.
0.8
0.6
=
E
0.4
8
0.2
Ccv
Fig. 4. Cumulative probability plot for coef cient of variation of current for all of the corrosion systems tested.
2791
2792
H.A.A. Al-Mazeedi, R.A. Cottis /ElectrochimicaActa 492004 2787-2 793
-M
0
0
ci
>
It
=
E=
0
0.J1
0.01
0.1
LI
Fig. 5. Cumulative probability plot for localization index for all of the corrosion systems tested.
approach has been used. To test the ability of individual
pammeters to discriminate the type or nte of corrosion,
the cumulative probability has been plotted for each set of
conditions. This is determined by the following algorithm
using q as an example:
two conditions, if the plots overlap, then there is no
ability to discriminate between them this is, of course,
correct if the corrosion behaviours am similar, while if
there is no overlap, then there is a good discrimination
ability.
As we can obtain two independent pammeters from a
conventional EN measumment, then it is potentially possible
to use them in combination to impmve the discrimination.
This situation has been tested by plotting all of the data as
individual points in a plot of one pammeter against the other.
This pmduces ‘clusters’ of points for each set of conditions,
and in this case it is possible to assess qualitatively whether
or not clusters can be discriminated by looking at the overlap
between them.
1. Sort all of the values of q for a given environment into
ascending order.
2. Then the cumulative probability for each value is n/’N +
1, where n is the position in the sorted list, and N is the
total number of entries in the list.
By comparing the cumulative probability plots for two
different conditions, we can determine the effectiveness
with which the pammeter can distinguish between the
1 J0J00
1 00J00
x
EC.,
E
1 00J0
x
xx
-
xx
QZ
I.
U
*
0
U
1 0J0
*
_s
100
.
_I
1 J0
1
10
100
1000
10000
ioooo
iodoooo
U
U
10000000 100000000
fI Hz cm2
Fig. 6. Plot of R11 vs.
corrosion.
f
for all of the systems tested open circles correspond to inhibition, closed squares to uniform corrosion and crosses to pitting
H.A.A. Al-Mozeedi, R.A. Coals /ElectrochiniicoActo 492004 278 7-2 793
The resultsthat have been obtained me shown in Figs. 1-5.
It can be seen thatfn pmvides a rnlatively good discrim
ination of localized cormsion, with a boundary of about
3000 Hz cm. As the tme coef dent ofvariation and pitting
factor me essentially equivalent to f other than the com
plications of area and bandwidth normalization discussed
above, they will have the same discrimination ability. In
contmst the conventional coef cient of variation and lo
calization index have relatively poor discrimination ability
with signi cant overlap between differnnt types of cormsion.
Note, for example that the rightmost four traces in Figs. 4
and 5 corrnspond to two systems that were pitting, and two
that wern suffering uniform corrosion, so these pammeters
cannot discriminate between these two types of corrosion.
Similarly, q appears to discriminate between inhibition
and cormsion whether uniform or localized, with a small
charge less than about 0.01 nC being indicative of inhibi
tion.
In Fig. 6, Rn is plotted as a function Offn. It is clif cult to
distinguish the various systems in this monochrome plot a
colour version of the plot is available fmm RAC, but it can
be seen that the three types of cormsion occupy differnnt
legions:
* Pitting corrosion has a low value of fn.
* Passive/inhibited samples have a high value of Rn and a
highvalue Offn note thatthe thioacetamide inhibited CO2
system has a rnlatively low inhibitionef ciency, so R for
this system is much lower than for the nitrite inhibited
system, giving the cluster of inhibited points to the right
of the plot.
* Geneml cormsion has a high value offn and a low value
of Rn.
Thus these pammeters allow a useful and reasonably in
tuitive categorization of the rate and type of cormsion, par
ticularly when used together
2793
Similar plots can be pmduced for Rn and q and Rn and
the other pammeters. Owing to the relationship between Rn
and q this plot is just a tmnsformation of the Rn versus fn
plot as is a plot of fn against q, and does not provide any
additional information.
6. Conclusions
EN measurnment pmvides useful information about the
rate of cormsion through Rn and localization of cormsion
through a mnge of pammeters, including the chancteristic
frnquency, fe.
Other measures for the identi cation of localization of
corrosion notably the localization index me unduly in u
enced by the mean current, and they me consequently less
reliable thanfn.
Cumulative pmbability plots pmvide a useful indicator of
the effectiveness of the various pammeters at discriminating
between different types of cormsion.
Acknowledgements
Ms Al-Mazeedi has been supported by the Kuwait Insti
tute for Scienti c Reseaith.
References
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[41 R.A. Cottis, in: J.D. Sinclair, E. Kalman, M.W. Kendig, W. Plieth,
W.H. Smyrl Eds., Electrochemical Society Proceedings PV2001-22
on Corrosion and Corrosion Protection, 2001.
[51 D.A. Eden, B. Breene, Corrosion/2003, Paper 361, NACE, 2003.