1

Acquisition, visualisation and interpretation of pipeline corrosion

monitoring data

M. YJ TAN*1, F. VARELA1, Y. HUO1, F. MAHDAVI1 and K. WANG1

1 Institute for Frontier Materials and School of Engineering, Deakin University, 75 Pigdons Road,

Waurn Ponds, VIC 3216, Australia. * presenting author, mike.tan@deakin.edu.au

Abstract

Localised corrosion and coating failure occur frequently on underground metal structures such as oil

and gas pipelines and water mains that are often under the effects of dynamically changing soil

conditions, stray currents, coating disbondment and cathodic shielding. In order to ensure the safety

and durability of these assets, there is a need for visibility and understanding of corrosion and material

degradation processes occurring on these buried structures. Traditionally historical field inspection

data are used as the main source of knowledge for forecasting the degradation and service lives of

buried pipelines; however these data have limitations because of their lack of in-situ and site-specific

localised corrosion information. In order to overcome weaknesses in conventional asset management

tools, corrosion monitoring using variously designed probes/sensors has been employed as a means of

acquiring in-situ and site-specific data for the early warning of structural failure and life prediction.

This paper provides an overview of current status of corrosion monitoring in the pipeline industry and

a brief discussion on its future prospects. Cases are described to illustrate our current approaches to,

(i) monitoring and visualising passivity breakdown and localised corrosion of buried steel under the

effect of dynamic anodic transients; (ii) monitoring and visualising coating disbondment under

overprotection potential; and (iii) monitoring and visualising localised corrosion under a simulated

pipeline coating.

Keywords

Pipeline corrosion, corrosion monitoring, corrosion data, localised corrosion, coating degradation

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Introduction

The lack of visibility and understanding of corrosion and material degradation processes

occurring on ‘invisible’ metal structures such as underground pipelines is believed to be a

major contributor to corrosion induced oil & gas pipeline explosion and oil spill accidents

including the oil pipeline explosion incident occurred in the Chinese city of Qingdao, killing

62 people and wounding 136, and a similar explosion in Taiwan caused 32 deaths and 321

injuries [1-3]. These incidents clearly indicate the extreme consequences of structural failure

to the economy and the environment. There are significant amount of ‘invisible’

infrastructures around the world, which are vital for the provision of the world’s essential

services and the maintenance of its economic activities. For instance each square kilometre

of our major cities would host more than 30 kilometres of buried oil and gas pipelines, water

mains and electrical and telecommunications cables [1]. It is a major task to ensure the

safety, reliability and durability of these ‘invisible’ infrastructure assets. A major problem in

today’s management of these assets is the lack of sufficient corrosion and materials

degradation information required for the effective management of these assets. Traditionally

historical field inspection data are used as the main source of knowledge for forecasting the

degradation and service lives of underground structures. Existing asset management tools

used in the industry are usually computer software developed based on historical data and

probabilistic models. The hypothesis behind these models is that statistical analysis of

historical survey and inspection data could allow for structural lifetime assessment and

prediction. Unfortunately these models are often not sufficient for infrastructural systems that

are under localised corrosion attack and that are under the effect of dynamically changing

environmental conditions. This is because under these circumstances corrosion and materials

degradation are significantly affected by local environmental parameters such as soil and

water composition, oxygen level, humidity, salinity, pH, temperature, stray currents, and

biological organisms, as well as stray currents, coating disbondment and cathodic shielding.

The lack of in-situ and site-specific local corrosion information significantly hinders our

ability to provide sufficient warning and maintenance of these ‘hidden’ assets.

Current status of pipeline corrosion data acquisition and analysis

Currently the most common approach to collecting corrosion and materials degradation data

from buried oil and gas pipelines is through excavation and inline inspection using various

pipeline inspection techniques. For instance, Direct Current Voltage Gradient (DCVG)

survey can provide useful information about the integrity of pipeline coatings. Non-

destructive testing methods such as ultrasonic tests are widely used for field inspection of

cracks and corrosion damage. Automatic ultrasonic scanning and recording techniques

combined with computer techniques are also able to produce three-dimensional maps of the

corroded surface. Radiography makes use of the penetrating quality of short wave

electromagnetic beams to image corrosion and to determine pit depths and the degree of

thinning due to corrosion. Techniques such as eddy current are used to visualise initial cracks

caused by stress corrosion or corrosion fatigue. Eddy current technique detects surface

cracks, pits or other defects by measuring disturbed eddy currents on a material surface.

Based on these techniques and their combinations, equipment known as a ‘pig’ (structure

inspection gauge) has been developed for internal examination of pipes. The ‘pig’ follows the

flowing medium in the structure and records corrosion related data for analysis after it is

removed from the pipe. Review of major methods for inspecting and monitoring external

corrosion of on-shore transportation pipelines and for measuring coating disbondment has

been presented in references [4,5]. All these corrosion and coating inspection techniques are

very useful in pipeline corrosion and coating degradation data acquisition; however they are

able to detect corrosion only when sufficient damage has occurred to cause an accumulated

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change in the bulk material properties. These field inspection techniques are often expensive

(e.g. pigging of a pipeline can cost $1million or more). Field corrosion inspections occur

relatively infrequently (e.g. pigging of a pipeline is usually done only every 5-15 years),

usually coinciding with routine shutdown and maintenance, and therefore peak corrosion

rates and materials degradation are usually not detected.

Traditional methods of visualising and interpreting corrosion data are usually computer

software developed based on historical field inspection data and probabilistic asset

management models. The hypothesis behind these models is that statistical analysis of

historical survey and inspection data could allow for structural lifetime assessment and

prediction. For instance Li et al [6] used a Monte Carlo simulation technique to calculate the

remaining life of a structure. Lee et al [7] presented an intelligent failure prediction system

for oil and gas structure using an Euclidean-Support Vector Machines classification

approach. Senouci et al [8] developed a fuzzy-based model to predict the failure type of oil

pipelines using historical data of pipeline accidents. Peng et al [9] developed a fuzzy artificial

neural network model, which is based on a failure tree and fuzzy number computing model,

for predicting the failure rates of long-distance oil/gas pipelines and for identifying distressed

pipeline segments. These asset management tools are useful in providing an overall

assessment of the aging of a structure; however the success of these tools is heavily

dependent upon the availability and reliability of structural condition data. Another weakness

is that these models are often not suitable for infrastructural systems that are under localised

corrosion attack and that are under the effect of dynamically changing environmental

conditions.

Another approach of acquiring corrosion data is through corrosion monitoring using

probes/sensors. Corrosion probes could provide data to help overcome weaknesses in asset

management models such as those described above. Over the past decades, variously

designed corrosion probes have been reported in the historic literature for laboratory and

field corrosion testing and monitoring applications [10-17]. For instance, in the oil and gas

industry, corrosion monitoring techniques including corrosion coupons, ultrasonic testing

probes, electrical resistance probes and various electrochemical method based corrosion

probes have been utilised. Currently the most widely adopted corrosion monitoring

‘probe/sensors’ in the industry are steel coupons and Electrical resistance (ER) probes. In the

pipeline industry, steel coupons inserted into or buried next to the pipe are used to assess the

internal and external corrosion of structures. However it should be noted that corrosion

coupons have well-known limitations: they are considered to be offline, labour intensive, and

not easily configured for automation and control systems. They require long exposure period

to generate field test results and during this period corrosion may have already occurred to an

industrial structure. They require periodic removal of test specimen from the corrosive

environment for inspection/monitoring which is cumbersome and may alter the progress of

localised corrosion. They only detect the cumulative corrosion damage at the end of the

exposure period and provide little information on specific events that may have triggered this

damage. Although corrosion coupon test appears to be an easy task, there are in fact

problems that often lead to unsuccessful and misleading results. It is often due to the fact that

relatively little attention has been given to the corrosion mechanism and its effect on coupon

test results. In practice the severity of corrosion is often determined by the corrosion

mechanism especially localised forms of corrosion, and therefore failure in understanding

and simulating localised corrosion mechanism on corrosion coupons could be the main

reason that leads to failure of coupon tests reported in laboratory and industry. ER probe is

often referred to as an ‘intelligent’ weight-loss corrosion coupon. The ER probe monitoring

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corrosion by measuring the electrical resistance of a thin metal test wire (sensor element)

since the resistance of the wire increases as the wire becomes thinner due to corrosion

dissolution. ER corrosion monitoring has been applied in industry to provide an indicator of

environmental corrosivity for more than four decades. An advantage of ER probe is that it

provides cumulative metal loss values without the need to remove the samples from the

service environment. Another advantage of ER probes is that the technique is applicable to

both conductive and non-conductive corrosion environments. A major disadvantage of the

ER technique is that it is unable to detect localised corrosion since localised corrosion may

neither lead to significant metal dissolution, nor noticeable change in electric resistance. It

also has similar limitations as corrosion coupons in simulating the localised corrosion

mechanisms. ER measurements generally do not respond rapidly to a change in corrosive

conditions, and it was reported to take four days to respond to 1 mpy corrosion rate [18]. The

measurement sensitivity can be improved by decreasing the element thickness; however this

would shorten the service life of the probe element.

In the real world corrosion rates always change with time, and thus it is important to identify

the specific time periods and environment conditions of peak corrosion rates. For this reason

‘instantaneous’ corrosion monitoring techniques are important to continuously measure the

prevailing corrosion rates and provide quantitative data for use as a process variable for

integrated and automated corrosion management system. Instantaneous corrosion testing and

monitoring techniques are usually electrochemical in nature. They include corrosion potential

measurement, potentiodynamic polarisation, linear polarisation resistance (LPR),

electrochemical impedance spectroscopy (EIS), electrochemical noise analysis (ENA), the

wire beam electrode (WBE) method and many others. Electrochemical techniques rely on

electrochemical corrosion theory and the measurement of electrode potentials and currents

that are fundamentally related to the thermodynamics and kinetics of corrosion reactions.

Electrochemical corrosion testing and monitoring can be fast, sensitive and versatile for

detecting the rates of uniform corrosion, the tendency of localised corrosion, and a wide

range of corrosion-related phenomena and mechanism including the passivation behaviour

and galvanic corrosion. For instance, corrosion potential can be measured from pipeline test

points for assessing cathodic protection of buried pipelines. Unfortunately, the corrosion

potential on its own does not provide information on the rate of corrosion. The LPR and EIS

techniques are employed to measure corrosion rates using the Stern and Geary equation and

have been discussed in numerous publications. Although techniques such as LPR and EIS are

very useful for corrosion monitoring, care should be taken since these techniques are accurate

only under several fundamental assumptions. In principle, it only applies to a uniform

corrosion system with a stable corrosion potential. The corrosion process should involve only

one anodic and one cathodic reaction, with both under activation control. The Tafel constants

should be known; and there should be only negligible solution resistance.

Current challenges in pipeline corrosion monitoring

It should be noted that currently corrosion monitoring has not always been used successfully

in the pipeline industry. In some cases a corrosion probe is used with an expectation of

monitoring corrosion in a similar manner as using a thermometer to measure temperature.

Inevitably these practices could lead to confusing and misleading results. Issues associated

with corrosion testing and monitoring have been frequently reported in the literature [10-16].

For instance, Srinivasan and Kane [10-11] reported poor correlations between actual

corrosion behaviour of gas wells and corrosion monitoring data obtained from various

techniques including down-hole mounted coupons, radioactive sleeves, electrical corrosion

probes and inspection of pulled tubing. They found that actual pitting rates were between 2

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and 15 times the general corrosion rates monitored for various cases, and in some cases the

differences in corrosion rates obtained using different techniques varied by an order of

magnitude in value. Papavinasam et al [12-13] also reported significant concerns on some

testing and monitoring methodologies for evaluating corrosion inhibitors for oil and gas

pipeline applications. On the other hand, Tan et al [14-16] analysed fundamental limitations

in some electrochemical corrosion monitoring methods, especially in the measurement of

localised corrosion. Obviously, conventional electrochemical corrosion testing techniques

have major technological limitations in monitoring localised forms of corrosion, which is

responsible for some 70-90% of all corrosion failures. The cyclic polarisation method has

been used for determining localised corrosion susceptibility with varying degrees of success.

Electrochemical noise ‘signatures’ are considered to be valuable for detecting the occurrence

of localised corrosion events [19-24], however it should be noted that quantitative analysis of

localised corrosion using ENA parameters such as pitting factor remain controversial and

requires further investigation. These facts confirm difficulties and complexities in applying

probes for accurate and in situ corrosion data acquisition.

A basic principle that could underpin the use of corrosion probes or sensors is that corrosion

and materials failure are not accidental occurrences, they occur as the result of fundamental

thermodynamic instability of a metal or a material in a specific environment. Therefore

corrosion and materials failure occurring on a structure such as a pipeline would also occur

on a probe made of the same material and exposed to the same environmental condition. A

properly designed probe and measurement method should be able to detect such

thermodynamic instability and reaction kinetics from the probe surface, and therefore

facilitate the monitoring and prediction of corrosion [25].

This principle suggests that a challenge in corrosion monitoring is to design or select suitable

probes that are able to simulate a complicated corrosion mechanism in a particular

environment-material combination. The probe should be able to detect data related to a

targeted corrosion mechanism in order to determine the effects of corrosion mechanisms (e.g.

crevice corrosion under disbonded coatings) on corrosion kinetics and patterns. This

challenge is more acute when corrosion is affected by many inter-related variables such as

non-uniform temperature and pressure, heterogeneous metallurgy, inhomogeneous soil or

solution chemistry and thermo-mechanical conditions, local mechanical stress, coating

defects, and cathodic cathodic potential and excursions. Although it is well appreciated that

corrosion probes need to produce the same type of corrosion (uniform, pitting, crevice etc.) as

in the service exposure; relatively less consideration have been given to the effects of testing

conditions and environmental parameters on corrosion mechanism. Corrosion mechanisms

can be significantly affected by testing conditions and environmental parameters such as

specimen surface conditions, wear, abrasion, time of exposure and others. It is important to

note that different metals could respond differently to changes in environmental conditions.

For instance passive metals such as stainless steel and active metals such as mild steel can

respond differently to aeration. For instance, in the case of stainless steel, the corrosion

controlling factor is usually the passivity of the metal surface rather than oxygen

transportation.

Another challenge is to develop or select suitable measurement techniques that are able to

effectively and accurately detect data from corrosion probes that contain ‘predictor features’

signifying the occurrence of corrosion and materials failure. Techniques such as electrode

potential recording, polarisation and impedance measurements have been developed in the

past to detect thermodynamic, kinetic and localised corrosion related data. However it is well

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known that these conventional electrochemical methods can only be used for estimating

general corrosion behaviour because in principle they are based on the most fundamental

relationship in electrochemical kinetics, i.e Butler-Volmer equation, which only describes the

kinetics of uniform corrosion mechanism and thus does not apply to localised corrosion [14-

17]. Over the recent decades, new methods such as galvanic current mapping using multi-

electrode arrays and electrochemical noise analysis have been developed to detect ‘predictor

features’ signifying the occurrence of localised corrosion. These are discussed in cases

described below.

It can also be a challenge to use corrosion probes in complex environmental conditions such

as in highly resistive and inhomogeneous soil media. For instance, it can be difficult to set up

and maintain corrosion testing probes in underground conditions. In fact, although

electrochemical methods have been widely used in many industries for corrosion monitoring,

their application in the monitoring of external corrosion of buried structure has been very

limited. Conventional electrochemical polarisation based methods are difficult to be applied

in highly resistive conditions because the high resistance of soil often causes a huge potential

drop commonly referred to as IR drop that can cause significant corrosion rate measurement

errors [17].

Some recent progresses in pipeline corrosion monitoring

It is a highly challenging task to design corrosion probes or sensors, especially localised

corrosion probes, which are able to effectively simulate corrosion behaviour in actual service

environments and reliably evaluate the effects of various factors on corrosion processes, rates

and mechanisms. It is well appreciated that corrosion probes needs to simulate the actual

service exposure environment; however relatively less considerations have been given to the

effects of environmental parameters on corrosion patterns and mechanisms. It is not

uncommon to receive misleading test results due to inappropriate selection of testing

parameters and measuring techniques. A successful corrosion probe should be able to detect

the effects of major corrosion controlling factors on corrosion mechanism, process and rates.

The identification and understanding of major environmental factors that may control the

thermodynamics, kinetics and mechanism of a corrosion process is usually the first step to

successful corrosion probe design. The identification of corrosion controlling factors requires

good knowledge of the nature and mechanism of a corrosion process. Aeration is a critical

corrosion controlling factor that could affect corrosion in complex environmental conditions

such as buried pipelines. In the case of active mild steel corrosion in soil, the corrosion rate

determining factor is often the diffusion of oxygen to the metal surface. When cathodic

protection is applied on the steel, the corrosion control factor could be changed to high pH

induced passivity of the steel surface.

One recent progress in pipeline corrosion monitoring is the design of corrosion and coating

degradation probes by innovatively applying an electrochemically integrated multi-electrode

array known as the wire beam electrode (WBE). The WBE is an array of mini-electrodes

(namely wires) that are insulated from each other by a thin insulating layer. The working

surface of the WBE is electrochemically-integrated by coupling all the wire terminals in the

solid phase and by closely packing all the wires in the solid/electrolyte interface. This

electrochemical integration minimises the influence of the insulating layer on electron and

ion movements and thus the working surface of a WBE effectively could simulate a

conventional one-piece electrode surface in electrochemical activity and behaviour. Indeed

the results of test work have shown that similar corrosion patterns were produced over WBE

and conventional one-piece electrode surfaces when both were exposed to identical corrosion

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environments and this has been verified theoretically [14-17]. Two important characteristic of

the WBE method that are particularly valuable for the investigation of corrosion in complex

environmental conditions such as buried structures are, (i) WBE is applicable to high

resistance multi-phase environment; (ii) WBE can map corrosion processes on an

instantaneous and continuous basis. Instantaneous corrosion rate maps were determined from

corrosion potential and current distribution maps; and the corrosion rate maps were used to

calculate accumulated corrosion depth distributions. Over the past decades, many researchers

have employed variously designed coupled electrode arrays in studying and measuring

different corrosion processes, which are widely reported in the literature.

The capability of the electrode array based corrosion probes in detecting the initiation and

propagation of localised corrosion and coating failure is illustrated by several cases [26-29].

Figure 1illustrates a typical experimental configuration using an electrochemically integrated

multi-electrode array based probe to facilitate the in-situ monitoring and visualisation of

electrochemical processes occurring on buried steel surfaces under CP [26-27] and anodic

transient conditions [28]. The WBE probe used in this work consists of 100 closely packed

but isolated square shaped carbon steel electrodes (e.g. 2.44 mm x 2.44 mm) embedded in

epoxy resin. Similar electrochemical cells and experimental setup were used in various

experiments for studying various inter-related processes such as cathodic shielding and

localised corrosion [26-27], coating damage and disbondment [29]. More details on the

experimental and data analysis methods can be found elsewhere [26-29].

(a) (b)

Figure 1. (a) A typical experimental configuration and (b) field installation for performing

in-situ monitoring of electrochemical processes occurring on a WBE probe surface buried in

a soil cell under CP and anodic transient conditions [26-28].

Case 1: The monitoring of localised corrosion processes under disbonded coatings

Figure 2 presents the current density maps developed form the probe’s measurements at a CP

potential of -850 mVCSE. Cathodic current densities are displayed in negative values while

anodics in positives. The section of the electrode covered by the crevice is indicated at the

base of the first current density map. Although the probe provided information to generate

maps every 20 min during the immersion tests, only a three maps were selected to illustrate

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the general trends observed. In general large cathodic current densities where found at the

uncovered area, while current densities along the crevice were extremely low. Although the

current densities registered at the uncovered area remained constant throughout the test,

significant changes were observed within the crevice area. In this area, anodic current

densities were found at the beginning of the test that rapidly decrease in magnitude. After this

initial period, stable current densities minor to 1µA/cm2 were recorded throughout the

remaining of the test. More detailed data acquisition, visualisation and interpretation for

monitoring corrosion under disbonded coatings can be found in references [26-27].

Figure 2. Current density distribution data monitored at selected immersion times and

displayed maps at a CP potential of -850 mVCSE [26-27].

Case 2: The monitoring of dynamic corrosion under anodic stray currents

Significant effort has been made to systematically categorise and quantify the level and

nature of damage of pipeline as a result of CP excursions, there are still major difficulties in

drawing decisive conclusions because of the complexity of the electrochemical corrosion

processes occurring at the complicated soil/buried steel interface. Technological difficulties

in measuring buried steel corrosion under CP are believed to be the prime reason responsible

for the lack of conclusions on the exact effects of CP excursions on pipeline corrosion.

Currently potential recording is the most commonly used method for inspecting stray current

activities in the pipeline industry; however potential recording does not provide sufficient

information about corrosion rates and patterns. Weight-loss coupons have been used to

determine corrosion rates of steel buried in soil, however weight-loss coupons are unable to

provide in situ corrosion rate data required for quantifying the effects of relatively short

duration CP potential excursions. A major difficulty in stray current corrosion research is the

lack of reliable and reproducible experimental methodologies that are able to systematically

categorise and quantify the level and nature of damage as a result of various modes of CP

excursions. In this work, the WBE method has been applied for the first time as a new probe

for detecting localised corrosion initiation under various dynamic anodic transient influences.

Experiments have been carried out for measuring the effect of an anodic transient on the

corrosion of a steel WBE probe in a soil corrosion cell [28]. Typical series of results are

shown in Figure 3. A common phenomenon that was observed from these tests is that shortly

after an anodic transient was applied to a CP protected steel surface, anodic current and

corrosion activity dropped dramatically from an initial anodic current peak value. This has

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been explained by the passivity of steel under CP induced high pH condition. Another

phenomenon observed by inspecting the occurrence of local anodic currents in WBE maps

was that localised corrosion initiation occurred after a critical duration. This critical duration

could be explained by the breakdown of passivity under the effects of anodic transient

induced pH and surface chemistry changes. This work suggests that the WBE probe could be

used as an effective tool for monitoring localised corrosion initiation under the effect of

complex factors, as well as for the in-situ monitoring of stray current corrosion of buried steel

structures. More detailed data acquisition, visualisation and interpretation for monitoring

stray current corrosion under the effect of anodic transients can be found in reference [28].

Case 3: The monitoring of coating cathodic disbondment under overprotection

Cathodic disbondment is a major form of electrochemically induced coating failure that

frequently takes place at the metal/coating interface on cathodically protected steel

infrastructure such as pipelines. Extensive research over the past decades has developed good

understanding of the phenomenon, however currently there is no technique that can be used

to perform in-situ monitoring of its occurrence in the field. Traditional methods of evaluating

cathodic disbondment of pipeline coatings are based on ex-situ visual inspection of excavated

pipes. Figure 4 shows typical maps of local impedance amplitude (│Z│at 300 mHz) and a direct

current map measured after different periods of exposure of the probe to the test solution

under CP potential of -1.40 VAg/AgCl or -0.95 VAg/AgCl. It is clearly shown in maps (a) - (f) that,

under a CP potential of -1.40 VAg/AgCl, the impedance of electrodes surrounding the defect

area continuously decreased (to less than 105 ohm) over the 624 hours exposure period. These

low impedance areas expanded with the increasing exposure time, while electrodes located

far away the defect area maintained a high impedance of larger than 107 ohm after 624 hours.

These maps clearly indicate coating disbondment due to permeation of the test solution along

the disbonded coating/metal interface gap rather than absorption of the solution by the

coating. After 624 hours, as shown in Figure 4(f), the majority of electrodes on the probe

were disbonded. Direct current maps measured at -1.40 VAg/AgCl (not shown here) also show

similar coating disbondment processes and behavior. However, when the CP potential was

reduced from -1.40 VAg/AgCl to -0.95 VAg/AgCl, as shown in Figure 4 (g) and Figure 4 (h), the

impedance map still clearly shows the disbonded area, while the direct current map, on the

other hand, lost sensitivity and this coating disbonded area was not visible, as seen in Figure

4 (h). These results illustrates that local electrochemical impedance measurements using an

electrode array probe have significantly improved sensitivity for monitoring the propagation

of cathodic disbondment of defective coatings compared with the conventional overall

electrochemical impedance and local current measurements approaches. This new approach

also provides the opportunity of eliminating the effects of the low impedance coating defect

regions on the visibility of higher impedance regions deep in the disbond coating, facilitating

the probing of electrode processes and mechanisms in selected regions of heterogeneous

electrode surfaces. More detailed data acquisition, visualisation and interpretation for

monitoring stray current corrosion under the effect of anodic transients can be found in

reference [29].

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Figure 3. Monitoring of currents and WBE maps over a steel WBE buried in a soil cell under

three different CP and anodic transient conditions [28].

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Figure 4. Typical maps of impedance amplitude (│Z│at 300 mHz) and direct currents

measured over a coated probe after various periods of exposure and under different CP

potential [29].

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Future prospects

Structural health monitoring using corrosion probes is useful for preventing pipeline failure

incidents that are often due to the failure of high risk components in an unanticipated manner.

The need for structural health monitoring is particularly apparent when the operational life of

aged infrastructures is extended beyond their design life. Structural condition monitoring

could facilitate early warning of unexpected structural failure, and enable owners to prioritize

site survey and inspection operations, as well as to develop maintenance strategy for

managing older infrastructures rather than replace them.

Development of probe application rules

In order to fully realise the advantage of corrosion probes for providing site-specific and in-

situ warning of unexpected structure failures, corrosion probes should be placed at strategic

and ‘worst-case scenario’ high risk locations of a structure. For a buried pipeline, for instance,

typical high risk structure sites would be those with high stray current activities, low soil

resistivity, high underground water level, high concentration of corrosive species, and those

highly corrosion rate areas identified by pigging, field survey and historical excavations.

Other examples of high risk pipeline sections include non-piggable pipeline sections, areas

between cathodic protection units, pipeline water crossings, pipeline shoreline crossings,

horizontal directional drilling and pipelines in tunnels. These pipeline sections could present

the ‘worst-case scenario’ conditions that are crucial to the safety and reliability of an energy

pipeline. Pipeline sections of high economic and social significances may also be identified as

monitoring sites. Probes embedded at these strategic sites can be used to collect real-time and

site specific data that would contain critical ‘predictor features’ and parameters needed for

modelling and predicting localised corrosion, coating disbondment and degradation. Currently

understanding of these aspects has been limited and more advancements are needed in order

to develop rules and guidelines for future industry corrosion monitoring.

Development of data systems and IT platforms

Although probes can provide useful in-situ data from selected locations of an asset, there is a

need to integrate data from limited monitoring sites into the whole database by suitable

models in order to provide fuller coverage of a huge structure (e.g. a 1000km underground

pipeline). An information platform would enable the integration of various data inputs and

allow industry to cost effectively gather information on the in-service integrity of

assets/infrastructure, gain high levels of confidence in the condition of the asset, timely

maintenance, safety and continuous availability/operation of the asset. A solution is an

information platform for infrastructure health monitoring, failure prediction and life

extension. The idea is to develop a web-based information platform that can linkup multiple

industries and multi-disciplinary areas of research. The concept of this platform is a ‘big data’

system that ‘visualises’ what’s happening underground by taking and linking up different

sources of corrosion and materials degradation data available. It will include corrosion probes

as an in-situ corrosion monitoring information source. This platform will allow continued

data input from various information sources such as remote corrosion monitoring, industry

inspection; and the analysis and application of data for various purposes such as structural

failure prediction and life extension. For instance, risk assessment models can be employed to

prioritise the assets for maintenance and renewal. It basically. It will be a pipeline

management tool.

It is expected that corrosion monitoring will become much more widespread with further

development that will enhance the reliability of corrosion probes as a structural health

monitoring tool for early detection and diagnosis of corrosion, for providing industrial system

13

‘health’ alarm, for forecasting maintenance requirements, and for generating data for

integrated and automated corrosion management system.

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