A distributed fibre optic approach for providing early warning of Corrosion Under Insulation (CUI)

Journal Pre-proof A distributed fibre optic approach for providing early warning of Corrosion Under Insulation (CUI) Peter J. Thomas, Jon O. Hellevang PII:

S0950-4230(19)30331-6

DOI:

https://doi.org/10.1016/j.jlp.2020.104060

Reference:

JLPP 104060

To appear in:

Journal of Loss Prevention in the Process Industries

Received Date: 24 April 2019 Revised Date:

18 October 2019

Accepted Date: 25 January 2020

Please cite this article as: Thomas, P.J., Hellevang, J.O., A distributed fibre optic approach for providing early warning of Corrosion Under Insulation (CUI), Journal of Loss Prevention in the Process Industries (2020), doi: https://doi.org/10.1016/j.jlp.2020.104060. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

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A distributed fibre optic approach for providing early warning of Corrosion Under

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Insulation (CUI)

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Peter J Thomas * and Jon O Hellevang

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NORCE Norwegian Research Centre AS, P.O. Box 6031, NO-5892 Bergen, Norway

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Abstract

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A novel fully distributed fibre optic humidity sensor technology suitable for spatially continuous monitoring of

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water ingress under pipeline insulation is reported.

Results from controlled water ingress

tests are

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presented, where the fibre cables were mounted on pipes insulated with air gap cell glass and aerogel

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insulation. The experiments revealed that the fibre optic sensor responded to water ingress equivalent to <

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10 ml / metre pipe, under air gap cell glass insulation. The fibre optic measurements were validated by

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comparison with conventional calibrated point humidity sensors.

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reference optical fibre was used to effectively reduce the effect of temperature variations on the

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measurements. The ability of the sensor to monitor the spatial evolution of water ingress with cm scale

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resolution was demonstrated, as was the feasibility to make accurate water ingress measurement over 2 km

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fibre lengths. The technology could be used to assist targeted inspection campaigns aimed at minimizing the

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risk of Corrosion Under Insulation (CUI).

A compensation methodology using a

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* [email protected]

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Keywords: Corrosion under insulation; Fibre optic sensors; water ingress; relative humidity.

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1. Introduction

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Corrosion is a serious problem at large scale processing facilities comprising pipeline networks and

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containment vessels. Often such infrastructure needs to be insulated for various reasons such as for

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optimizing process efficiency, fireproofing, noise control, and personnel protection. There is a tendency for

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water from the environment, to penetrate the insulation and cause the underlying steel surfaces to corrode.

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Similarly, humid air can diffuse through imperfections in the insulation and condensate on steel surfaces

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leading to corrosion. This phenomena, known as corrosion under insulation (CUI), is particularly challenging 1

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because it is not generally known where and when the water penetrates (Winnik 2015). Measures taken to

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mitigate CUI risk include improved insulation design and installation practices (Javaherdashti

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2014,Pojtanabuntoeng 2015), the minimization of insulation use, and the application of protective coatings to

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the steel surfaces(Miyashita 2017). Because such measures alone are not sufficient for preventing CUI

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completely, Inspection and Maintenance (I&M) strategies are employed to reduce CUI risk further. Such

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strategies most often involve campaigns to periodically remove insulation in order to allow visual inspection

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of the surfaces. Such campaigns are resource demanding, and while risk based prioritization of inspections

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is carried out, considering factors such as insulation type, temperature and failure history and consequence,

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often the assumption is made that water has penetrated the insulation. This assumption often results in

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unnecessary removal of insulation from dry infrastructure, and results in delays to the inspection of

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infrastructure where water has penetrated the insulation. The later can result in failure to detect CUI, leading

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to unplanned process shutdowns, incurring high losses due to damage and operational downtime. Standard

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practices for risk based I&M planning (ASME 2009, DNV GL, 2010) often combine the assumption of water

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ingress with assumptions about the rate of corrosion of materials, given either by standard values or values

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derived from models. However, since the processes determining the corrosion rates of uninsulated materials

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are stochastic, non-linear, and not entirely understood (Melchers and Jeffrey, 2008, Melchers 2008),

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uncertainties on standard values for corrosion rates are high and must be applied with caution in risk

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calculations (Caines 2013, Seo 2015). Furthermore, most available standard corrosion rates and models

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apply only to non-insulated structures, therefore applying these to maintenance planning for insulated

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structures is even more problematic (Mokhtar, 2011, Caines 2015, Shekari 2017). A recent study highlighted

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that the presence of insulation significantly increases corrosion rates (Caines 2017).

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More efficient risk based I&M strategies may be possible where the prioritization of inspection jobs is aided

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by measurement data indicating where humidity and/or water has penetrated the insulation. The system

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providing such data should be cost effective and ideally provide relevant spatially continuous measurement

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data at all locations throughout an infrastructure, as water is often confined to a small region about an

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ingress point with a location that is impossible to predict. Candidate technologies for such a system include

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neutron backscatter (Javaherdashti 2014) and infrared imaging (Bagavathiappen, 2013), both of which can

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give an indication of moisture/water under insulation. However both of these techniques are impractical for

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permanent monitoring of large infrastructures due to their high cost and incompatibility with certain insulation

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types.

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available, prohibitively large numbers of these sensors would be required for providing satisfactory water

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detection capability over large infrastructure. (Ayello 2011). Networks of water activated passive radio 2

While point sensors for making humidity and water ingress measurements are commercially

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frequency Identification (RFID) tags could be installed relatively cheaply, but these would require manual

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scanning to retrieve a measurement, and lack memory such that only the current status is reported (Ayello

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2011).

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2012, Simonetti, 2015). While microwave techniques are suitable for permanent monitoring of large-scale

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structures, range is limited by the presence of bends and supports, and is not suitable for installations with

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cell glass insulation, a common insulation type.

Guided microwave techniques can also be used to detect the presence of wet insulation (Jones

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Fibreoptics can also be used for detecting water /humidity (Alwis 2013, Ascorbe 2017). One fibre optic

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sensor principle includes the use of elements in the sensing cable that swell with water uptake to introduce

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microbends onto the fibre. (Cho 2012, Bremer 2014). Another technique involves replacing part of the fibre

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cladding with a hydrophilic polymer coating with a refractive index that changes as a function of the ambient

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humidity (Cho 2011), modifying the wave guiding capacity of the fibre. In fibre Bragg grating (FBG) based

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humidity sensors the sensing mechanism is based on the expansion of a hygroscopic coating on water

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uptake, which transfers a strain on the fibre. (David 2012, Swanson 2015). While such sensors can be

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multiplexed into an array of discrete humidity sensors, such an array would not be able to provide spatially

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continuous information when applied to monitoring water ingress under insulation. For a given length of fibre

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the total number of sensor in the array would be limited by properties such as the loss coefficient and/or the

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optical bandwidth reflected at each point sensor. More recently, a fibre optic architecture providing spatially

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continuous humidity measurements has been reported (Thomas 2017, Thomas 2018). Like the FBG

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technology, the distributed humidity sensor relies upon the measurement of a hygroscopically induced strain

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in the fibre, using state-of-the-art optical frequency domain reflectometry (OFDR) technology (Kreger 2016).

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In principle, this type of sensor is ideal for detecting water ingress under pipeline insulation because the only

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component installed under the insulation is a passive optical fibre.

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detected at all locations where the sensing cable is installed, the chances of water being ingress being

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detected at any given location are maximized. This paper reports the results of experiments that were

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carried out order to assess the suitability of the distributed humidity sensing technology for water ingress

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monitoring of pipelines insulated with one of two common insulation types; air-gap cell glass and aerogel.

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Controlled experiments revealed that the fibre optic sensor responded to water ingress < 10 ml / metre pipe,

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under air gap cell glass insulation. The evolution of the fibre optic humidity measurements following water

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ingress indicated that as expected, water retention was low or high when using air gap cell glass and

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aerogel insulation respectively.

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conventional point humidity sensors. A compensation methodology using a reference optical fibre was used 3

Furthermore, as moisture can be

The fibre optic measurements were also validated by comparison with

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to effectively reduce the effect of temperature variations on the measurements. The ability of the sensor to

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monitor the spatial evolution of water ingress with cm scale resolution was demonstrated, as was the

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feasibility to make accurate water ingress measurement over 2 km fibre lengths. The technology could be

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used to assist targeted inspection campaigns aimed at minimizing the risk of Corrosion Under Insulation.

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2

Principal of fibre optic water ingress detection

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When laser light propagates along a standard optical fibre, random fluctuations in the fibre refractive index

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creates scattering centres that cause a small component, typically less than -80 dB, to be elastically

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backscattered along the fibre. This effect is known as Rayleigh backscatter, the optical path between the

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position of Rayleigh scattering centres
 are specific to any given fibre, and change with temperature and

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applied strains. The basis of the humidity senor described here can be considered to be a change in the

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separation of Rayleigh scattering centres ∆
 along a given section of fibre, due to a strain applied by a

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hygroscopic coating material that expands with the relative humidity (RH) conditions. Based on the

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optothermomechanical equation, an effective measured strain is defined as (Measures 2001, Kersey 1997):

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Δ =





=   ∆ +  Δ

(1)

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Where Δ is the measured strain change in an optical fibre due to humidity and temperature changes ∆RH

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and ∆T respectively. The humidity strain response coefficient is CRH = 1-pe, where pe is the photoelastic

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coefficient of the optical fibre. The temperature induced strain coefficient is CT =αF+ ξ, where αF and ξ are

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the thermal expansion and thermal optic coefficients of the optical respectively. Eqn. (1) assumes that the

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fibre strain is influenced only by temperature and humidity changes ∆T and ∆RH respectively. Eqn. (1)

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therefore ignores the influence of mechanical forces on the strain experienced by the fibre.

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applications, the distributed sensor should report a value for the relative humidity at each location, rather

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than a strain response that is also influenced by temperature. Therefore a sensing cable should not only

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comprise of a “measurement “ fibre that shows a high strain response to humidity/water (and temperature),

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but should also contain a “reference” fibre with a strain response dominated by temperature variations. When

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the two-fibre sensing cable is exposed to environmental change, the strain response of the reference fibre

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can be used to establish the temperature contribution to the strain response of the measurement fibre. As a

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result, the humidity contribution to the strain response becomes easily identifiable. Writing equation (1) for 4

For practical

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the measurement and reference fibres, it can be shown that humidity variations can be quantified using the

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following formula:

∆ =

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, ,  %&,

!," $ #,"

(2)

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Where the m and r subscripts relate to the strain and temperature/humidity coefficients for the measurement

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and reference fibres respectively.

132 133

In this work, Δ in equations (1) and (2) is measured in a distributed way, i.e. at all points along the fibre,

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using a technique known as Optical Frequency Domain Reflectometry (OFDR).

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wavelength homodyne interferometry (Soller, 2005), where the radiation from a tunable wavelength laser is

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coupled into a two path interferometer, one reference path and a measurement path containing the optical

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fibre under test. The two output beams from the interferometer, one of which contains the Rayleigh

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backscatter from the fibre under test, are combined at an optical detector to form interference fringes in the

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spectral domain, and converted into the time domain using the Fourier transform. The resulting spatial data

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contains the phase and amplitude information that describes the distribution of Rayleigh scattering centres

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and is used to recover the effective strain function. For a given section of fibre, the strain measurement is

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performed by transforming the corresponding data back into the spectral domain and then using complex

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cross correlation techniques to evaluate the spectral shift relative to that for same section before the strain

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was applied (Froggatt, 1998). The spatial resolution of OFDR measurements is inversely proportional to the

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spectral bandwidth of the scan range ∆f as Δ' ~ ) ⁄*+ Δ, , where ng is the group index of the optical fibre,

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and c is the speed of light in vacuum. For the system used during the investigations here, Δ,~ 5.2 THz,

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giving a spatial resolution of around 20 µm. In practice, the measurement resolution is limited in

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consideration of a number of factors including environmental noise, chromatic dispersion and computation

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time. The maximum fibre length that can be interrogated by OFDR is in general limited by the phase noise

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of the laser, and limitations in the interferometer triggering (Bao 2012).

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3

Experimental methods

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3.1. Fibre humidity and temperature response

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5

OFDR employs swept

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The distributed sensor configuration and the experimental setup used for the characterization experiments

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are shown in Fig.1. The OFDR interrogation unit was the same as the one described in (Thomas 2017). The

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sensing fibre was placed in a climatic chamber (Memmert CTC 256) for regulating the relative humidity and

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temperature conditions. Three types of test fibre were used. The first fibre type, “M1” (OFS SMT-A1310H)

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was the measurement fibre, with a 15 µm layer of polyimide coating, a high glass transition temperature

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material often used high temperature fibreoptic applications. Polyimide is also hydroscopic which facilitates a

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high strain response to humidity

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nm, attenuation coefficient <0.6 dB/km at 1550 nm, and a 125 µm cladding diameter. The reference fibres

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“R1” and “R2” have similar optical properties to M1, but have hydrophobic coatings that facilitate a low strain

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response to humidity. Fibre R1 was FBGS GmbH fibre with 60 µm layer of Ormocer®-T coating, and fibre R2

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was Fibrecore SM1500 fibre with a 60 layer of high temperature acrylate coating.

The optical properties of M1 are single mode cutoff wavelength of 1250

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3.2. Water ingress under insulation testing

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The ability of the sensor system to detect water ingress under insulation was tested using the setup in Fig2.

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The sensing cables consisted of a 6 mm diameter hard plastic tube containing one humidity measurement

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fibre and one temperature reference fibre. The tube was perforated with 3 mm diameter breathing holes

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approximately every centimeter along the tube length such that the fibres were exposed to humidity and

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temperature variations. Two experimental runs each covering approximately 1000 hours were carried out,

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where fibre optic humidity measurements were made every 30 minutes. The cables used in each separate

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run were identical, except for that temperature reference fibre R1 was used in run 1, and R2 was used in run

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2. For each run, the measurement and reference fibres were probed sequentially using the same OFDR

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interrogator and an optical switch. The cables were fixed in the 6 o clock position to two 2 m length, 4 inch

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diameter carbon steel pipe using adhesive tape. Care was taken to ensure the tape covered only a limited

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number of the breathing holes in the cable. One pipe was insulated with cell glass, and the other with

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aerogel insulation. The cell glass insulation was formed from two halves of thickness 35 mm, that were

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sealed together using Fosroc Nitoseal SC N sealant. The inner diameter of the annulus formed by the

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insulation was intentionally larger than the test pipe outer diameter in order to allow for the incorporation of

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an air gap. The thickness of the air gap was made to be uniform around the pipe using 10 mm thick silicone

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spacers fixed at numerous locations on the inner diameters of the cell glass. For the pipe sections fitted with

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aerogel insulation, a 5 mm thick blanket of Pyrogel X-TE insulation was held in place using adhesive tape.

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An outer aluminum cladding layer was also applied. A Dracol USB-TRH relative humidity point sensor was 6

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used to monitor the environment surrounding the test setup. During Run 2, further humidity point sensors

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were placed in holes made in the air-gap cell glass insulation at the 12 o clock position at three locations;

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near the centre and 40 cm from both ends of the pipe. A hole was made in the insulation at the 12 o clock

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position near one end of each pipe, through which water could be introduced from a 5 L reservoir. For the

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investigations here, the reservoir was filled wither with either deionized water or artificial seawater (35.5 g/L

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NaCl). During test run 1, four 5 litre water additions were made, the first water addition was deionized water,

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and the three subsequent additions were artificial seawater. Run 2 consisted of fresh water additions only.

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For draining, a hole was made in the insulation at the 6 o clock position near the opposite end of the pipe to

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the water inlet. In order to further promote draining, the pipe was angle slightly such that water could flow

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from the water inlet to the drain. During test run 1, air could be electrically pumped under the insulation at

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the same location as the water inlet. For both test runs, the temperature under the insulation was maintained

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at approximately 60 °C by circulating heated water through the pipes.

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3.3 Test of scalability to long fibres.

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In order to test the ability to measure hygroscopically induced strains over long fibres as would be required

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when applied to plant scale infrastructure, a 64 m long test fibre [see (Thomas 2017) for more details] was

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placed in a climate chamber and exposed to an increase in temperature and humidity, see figure 1. The

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resulting strain response in the test fibre was measured using the interrogator described in (Thomas 2017).

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A 2 km delay fibre was then installed between the interrogator and the test fibre, and the strain response of

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the test fibre was re-measured after applying the same change in humidity and temperature conditions.

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4

Results 4.1. Fibre humidity and temperature response

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Figure 3 shows the humidity induced strain response for the humidity measurement fibre M1, and reference

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fibre R1. From the gradients the responsivity coefficients are CRH,M1 = 1.31 με/%RH and CRH,R1 = 0.13

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με/%RH, which is consistent to the response of similar fibres reported elsewhere (Thomas 2017). The

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responsivity of R2 was similar to that for fibre R2(CRH,R2 = 0.12 με/%RH). The temperature response

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coefficient for all three fibres was measured as being close to 9.5 µε/°C.

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4.2. Water ingress under insulation testing

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Figure 4 (a) shows the average strain response data for M1 and R1 obtained during run 1 for the cable

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section installed under air-gap cell glass insulation. M1 shows a rapid (<30 mins) increase in strain response

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at the times where water was introduced under the insulation. This fast response time is consistent with

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detailed dynamic response times of similar fibre described elsewhere (Thomas 2018).

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response of R2 following water addition is consistent with a temperature-dominated response characteristic,

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and the cooling effect of the added water that was at ambient temperature. Following the deactivation of the

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heating system, the strain response of both M1 and R1 dropped by a similar amount in the following 24

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hours, which is consistent with the similar temperature sensitivity reported for the fibres in section 4.1.

The drop in strain

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The relative humidity data in figure 4 (b) was derived from the strain data in figure 4 (a), combined with

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equation 2. Since equation 2 gives changes in relative humidity, the absolute relative humidity was

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calculated by applying an offset. The offset was determined by referencing the ∆RH response of a section of

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the cable placed at ambient conditions, with the absolute value of the relative humidity value measured at

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the same location using a point sensor. The measurements in figure 4(b) indicate a rapid increase in relative

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humidity following water ingress followed by a gradual drop in humidity over the following 24 hours. This

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behavior is consistent with the good conditions for drainage and drying due to the air gap under the

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insulation, sloping pipe, and elevated temperature under the insulation. Rapid gravity assisted propagation of

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the water ingress along the entire pipe is confirmed by the average humidity peaking at high values. The

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decrease in relative humidity following the first water addition, appears to be more rapid than for subsequent

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additions. This observation is consistent with the first water addition comprising distilled water, while all other

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additions involved artificial seawater; it is well known that elevated water salinities are associated with lower

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evaporation rates (Al-Shammiri, 2002). Following periods of time where the air pumps were activated, the

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fibre optic measurements report a drop in relative humidity, which is indicative of the air flow providing

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effective drying under the air gap cell glass insulation. The stability of the fibre optic humidity measurement

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in the periods following the deactivation and reactivation of the pipe heater indicates that the method for

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calculating relative humidity described by equation 2 provides reasonable temperature compensation

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performance against the temperature sensitivity of M1.

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The relative humidity measurements derived from the section of cable installed under aerogel insulation

249

during run 1 are shown in figure 4 (c). Each water addition resulted in an increase in relative humidity, this is 8

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consistent with the insulation becoming increasingly saturated as more water is added. Similarly to the pipe

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with cell glass insulation, propagation of the water ingress along the entire pipe is confirmed by the average

252

humidity peaking at high values. At the end of run 1 when the metal cladding was removed, the aerogel

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insulation was wet to the touch. The lack of a decrease in relative humidity after the application of the air

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pumps, indicate that the air pumps were ineffective in generating any kind of air flow between the insulation

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and pipeline. This observation is reasonable since no air gap was present.

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From run 2, Figure 5 (a) shows the spatially averaged humidity measurements calculated using the strain

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responses of M1 and R2 in the section of sensor cable installed under air gap cell glass insulation. These

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measurements show a high level of consistency with the average relative humidity values calculated using

260

the three point sensors. Some deviation between the point and fibre optic sensor is to be expected, given

261

that they occupy different positions under the insulation. However the high level of consistency between the

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two data sets supports the validity of the fibre optic measurements, since the point sensors are humidity and

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temperature calibrated and can be assumed to be correct. Similar to the corresponding data from run 1, each

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water addition results in a sharp and rapid increase in relative humidity. In contrast to the run 1 data

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however, the relative humidity drops close to the pre water addition value for every water addition. This is

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most likely a result of the fact that all of the water additional were using distilled water in run 2, therefore

267

promoting evaporation and drying. The fibre optic humidity data from the cable installed under aerogel

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insulation in run 2, like the data from run 1, tends to high values after every water addition, as a result of the

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insulation becoming increasingly saturated, see figure 5(b).

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Figure 6 shows the magnitude of

the initial relative humidity changes following a water addition, as

272

measured by the fibre optic cable installed under air gap cell glass insulation, plotted against the volume of

273

water added. Extrapolation of the fitted curve indicates that the system is sensitive to instantaneous water

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additions of ~ 5.5 ml per metre of pipe, assuming that a 5% change in relative humidity is required to trigger

275

a water ingress alarm. This estimation assumes that the humidity resulting from each water addition is

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removed before making subsequent additions. This assumption seems reasonable upon observation of the

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data in figure 5(a). It is more difficult to provide a similar estimate of sensitivity when installed with aerogel

278

insulation, due to the rapid saturation of the insulation, and limited drying following the first water addition.

279

However the higher water retention characteristic of the aerogel would most likely have the effect of raising

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the system sensitivity since any water ingress is more likely to accumulate at one location, whereas in the air

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gap cell glass case, water is likely to spread out more, reducing the system response at any single location. 9

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All of the fibre optic humidity data presented thus far have been based on spatially average values over a 2

284

m section of pipe. Figures 4-6 are therefore representative of the data quality expected when the system is

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artificially limited to spatial resolution of 2 m. While for most situations this spatial resolution would be

286

sufficient, the system is capable of resolving humidity variations with cm resolution. This is demonstrated by

287

the data in figure 7, which shows the humidity profile under the entire length of air gap cell glass insulation, at

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different snapshots in time preceding and following a water addition. Before the water ingress, the fibre optic

289

measurements show the humidity is low everywhere along the pipe, and the humidity then increases sharply

290

at all locations following the addition. This initial increase is followed by a period of drying over the following

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24 hrs. The spatial humidity profile shows that the drying takes place most rapidly at the drain end of the

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pipe, and progresses towards the location of the initial water ingress. This is consistent with the water inlet

293

being closed after the water addition, while the drain remains open, providing better conditions for drying

294

under the insulation at that end of the pipe. These distributed fibre optic humidity measurements are also

295

largely consistent with the data from the point sensors, also shown in figure 7. The deviation between the

296

fibre optic data and point sensor data is likely due to the different spatial positioning of the sensors under the

297

insulation. Given that the fibre optic system is capable of resolving humidity variations with cm spatial

298

resolution, this implies the possibility for higher sensitivities to water ingress than that implied by the data in

299

figure 6, where the spatial resolution is artificially limited to 2 m through averaging. Using the increased

300

spatial resolution, higher sensitivities would be expected if the water accumulates at locations within a few

301

centimeters of the point of ingress.

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4.3. Test of scalability to long fibres.

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Figure 8 shows the humidity and temperature induced strain profile in the test fibre measured using the

306

setup shown in figure 1. The local modulations in the fibre stain occur with a spatial regularity of ~ 60 cm,

307

which is due to the coiling of the test fibre, and local variations in the temperature/humidity within the climate

308

chamber. The different step levels of the strain are partly due to the test fibre comprising of sections with

309

different hydroscopic coatings, and partly due to a consequence of different sections of the test fibre being

310

positioned at different locations throughout the climate chamber. All of these effects are described in more

311

detail in (Thomas 2017). Importantly for this demonstration, the strain variations along the test fibre shown in

312

Figure 8 are of a similar magnitude to those observed in fibres M1 and R1 during the water ingress testing,

313

see Figure 4(a). This fact, combined with the similarity between the test fibre strain profiles in Figure 8, 10

314

measured with and without the 2 km delay present fibre clearly demonstrates the feasibility to make

315

distributed humidity measurements over a 2 km range with a spatial resolution ~ 10 cm.

316 317

5

Discussion

318 319

A novel fully distributed fibre optic humidity sensor suitable for spatially continuous monitoring of water

320

ingress under pipeline insulation has been investigated.

321

one of which shows a large strain response to water, a second fibre with a low strain response to water is

322

used for temperature compensation. The sensing fibres strain responses to humidity and temperature were

323

characterized using a climate chamber. Results from two 1000 hour controlled water ingress tests were

324

presented, where sensing cables were installed on 2 m pipeline sections insulated with air gap cell glass and

325

aerogel insulation. The fibre optic sensor responded to water ingress less than 10 ml under air gap cell glass

326

insulation. The measurements showed that the air gap cell glass insulation provided good conditions for

327

draining, while the aerogel insulation became saturated following multiple water additions. The fibre optic

328

measurements were largely consistent with relative humidity measurements carried out using calibrated

329

point sensors. The ability of the fibre optic sensor to monitor the local spatial evolution of water ingress with

330

cm scale resolution was demonstrated, as was the ability of the system to make accurate water ingress

331

measurement over 2 km over fibre. The influence of mechanical forces acting on the fibre did not appear to

332

have a significant negative effect on the fibre optic humidity measurements. This was despite the presence

333

of liquids flowing through the test pipelines on which sensing fibres were mounted for the water ingress tests,

334

and significant air flow and ambient noise for measurements carried out when sensing fibres were placed in

335

a climate chamber. The technology could be used to provide spatially continuous water ingress data

336

covering large insulated structures, and could therefore be used to assist targeted inspection campaigns

337

aimed at minimizing the risk of Corrosion Under Insulation.

The sensing cable consists of two optical fibres,

338 339

Acknowledgements

340 341

The authors gratefully acknowledge the Research Council of Norway’s (RCN) Petromaks2 programme for

342

funding this work (Grant number 243595). We thank Adrian Haaland for invaluable assistance in helping us

343

set up the water ingress experiments.

344 345 11

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References

347

Al-Shammiri, M. (2002). Evaporation rate as a function of water salinity. Desalination, 150(2), 189-203.

348

Alwis, L, Sun, T., Grattan, K.T.V., “Optical fibre-based sensor technology for humidity and moist

349

measurement: Review of recent progress” Measurement 46, 4052-4074, 2013.

350

Ascorbe, J. Corres, J. M, Arregui, F. J., Matias, I.R “Recent Developments in Fibre Optics Humidity Sensors”

351

Sensors, 17, 893, 2017

352

ASME B31 Committee. (2009). ASME B31G-2009: manual for determining the remaining strength of

353

corroded pipelines. American Society of Mechanical Engineers.

354

Ayello, F., Hill, D., Marion, S., & Sridhar, N. (2011, January). Integrated sensor networks for corrosion under

355

insulation: Monitoring, cost reduction, and life extension strategies. In CORROSION 2011. NACE

356

International.

357

Bagavathiappan, S., Lahiri, B. B., Saravanan, T., Philip, J., & Jayakumar, T. (2013). Infrared thermography

358

for condition monitoring–A review. Infrared Physics & Technology, 60, 35-55.

359

Bao, X., & Chen, L. (2012). Recent progress in distributed fibre optic sensors. Sensors, 12(7), 8601-8639.

360

Bremer, K. Meinhardt-Wollweber, M., Thiel, T., Werner, G., Sun, T, Grattan, K.T.V., and Roth, B. “Sewerage

361

tunnel leakage detection using a fibre optic moisture-detecting sensor system” Sensors and Actuators A

362

220. 62-68, 2014.

363

Caines, S., Khan, F., & Shirokoff, J. (2013). Analysis of pitting corrosion on steel under insulation in marine

364

environments. Journal of Loss Prevention in the Process Industries, 26(6), 1466-1483.

365

Caines, S., Khan, F., Shirokoff, J., & Qiu, W. (2015). Experimental design to study corrosion under insulation

366

in harsh marine environments. Journal of Loss Prevention in the Process Industries, 33, 39-51.

367

Caines, S., Khan, F., Shirokoff, J., & Qiu, W. (2017). Demonstration of increased corrosion activity for

368

insulated pipe systems using a simplified electrochemical potential noise method. Journal of Loss Prevention

369

in the Process Industries, 47, 189-202.

370

Cho, S, Tamura, Y., and Matsuo, T., “Monitoring of Corrosion Under Insulation by Acoustic Emission and

371

Humidity Measurement” J Nondestruct. Eval. 30, 59-63, 2011.

372

Cho, T-S., Choi, K-S., Seo, D.C., Kwon I-B, and Lee, J-R. “Novel Fibre optic sensor probe with a pair of

373

highly reflected connectors and a vessel of water absorption material for water leak detection”, Sensors,

374

12(8), 10906-10919, 2012.

375

David, N.A, Wild, P.M., and Djilalo, N., “Parametric study of a polymer-coated fibre optic humidity sensor”

376

Meas. Sci. Technol. 23, 035103, 2012.

377

DNV. (2010). Risk Based Inspection of Offshore Topsides Static Mechanical Equipment. DNV-RP-G101. 12

378

Froggatt, M., and Moore, J. “High spatial resolution distributed strain measurement in optical fibre with

379

Rayleigh scatter” Applied optics, 37(10), 1735-1740, (1998)

380

Javaherdashti 2014, “Corrision Under Insulation (CUI): A review of knowledge and practice”, Journal of

381

Materials Science & Surface Engineering, Vol. 1(2). pp36-43

382

Jones 2012, “Use of Microwaves for the Detection of water as a cause of Corrosion under insulation” J

383

Nondestruct Eval, 31:65-76.

384

Kersey, A.D., Davis, M.A., Patrick, H.J., LeBlanc, M., Kao, K.P., Askins, C.G. Putnam, M.A. and Friebele,

385

E.J. “Fibre grating sensors”, IEEE J. Lightwave Technol. 15 (8) 1442–1463, 1997.

386

Kreger, S.T., Rahim, N. A. A., Garg, N., Klute, S.M., Metrey, D. R., Beaty, N., Jeans, J. W., Gamber, R.,

387

“Optical frequency domain reflectometry: principles and applications in fibre optics sensing” Proc. SPIE Vol.

388

9852, 2016.

389

Measures, R. M. “Structural monitoring with fibre optic technology” Academic press, 1 edition 2001.

390

Melchers, R. E. (2008). A new interpretation of the corrosion loss processes for weathering steels in marine

391

atmospheres. Corrosion Science, 50(12), 3446-3454.

392

Melchers, R. E., & Jeffrey, R. (2008). Modeling of long-term corrosion loss and pitting for chromium-bearing

393

and stainless steels in seawater. Corrosion, 64(2), 143-154.

394

Miyashita, J. (2017, April). Performance of Three Types of Coatings in a Simulated Corrosion under

395

Insulation Condition. In CORROSION 2017. NACE International.

396

Mokhtar, A. A., & Ismail, M. C. (2011). Probabilistic reliability assessment of an insulated piping in the

397

presence of corrosion defects. Journal of Applied Science, 11, 2063-2067.

398

Pojtanabuntoeng, T., Machuca, L. L., Salasi, M., Kinsella, B., & Cooper, M. (2015). Influence of Drain Holes

399

in Jacketing on Corrosion Under Thermal Insulation. Corrosion, 71(12), 1511-1520.

400

Seo, J. K., Cui, Y., Mohd, M. H., Ha, Y. C., Kim, B. J., & Paik, J. K. (2015). A risk-based inspection planning

401

method for corroded subsea pipelines. Ocean Engineering, 109, 539-552.

402

Shekari, E., Khan, F., & Ahmed, S. (2017). Probabilistic modeling of pitting corrosion in insulated

403

components operating in offshore facilities. ASCE-ASME Journal of Risk and Uncertainty in Engineering

404

Systems, Part B: Mechanical Engineering, 3(1), 011003.

405

Simonetti, F., Nagy, P. B., Bejjavarapu, S. M., Instanes, G., & Pedersen, A. O. (2015, May). Long-Range

406

Microwave Detection of Wet Insulation for CUI Mitigation. In CORROSION 2015. NACE International.

407

Soller, B.J., Gifford, D. K.m Wolfe, M. S and Forggatt, M. E. “High resolution optical frequency domain

408

reflectometry for characterization of components and assemblies“, Optics Express, 13(2), 666-674, 2005.

st

13

409

Swanson, A.J., Raymond, S.G., Janssens, S., Breukers, R.D., Bhuiyan, M. D.H., Lovell-Smith, J.W., and

410

Waterland, M.R., “Investigation of polyimde coated fibre Bragg gratings for relative humidity sensing” Meas.

411

Sci. Technol. 26, 125101, 2015.

412

Thomas P.J., and Hellevang, J.O, “A fully distributed fibre optic sensor for relative humidity measurements”

413

247, Sensor and Actuators B, 284-289, 2017

414

Thomas, P. J., & Hellevang, J. O. A high response polyimide fibre optic sensor for distributed humidity

415

measurements. Sensors and Actuators B: Chemical, 270, 417-423, 2018

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Winnik S, editor. Corrosion Under Insulation (CUI) Guidelines: Revised. Woodhead Publishing; 2015 Nov 26.

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Fig.1. The distributed sensor configuration and characterization setup. Key : x- fibre splice, CTF – coreless

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termination fibre.

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Fig. 2, Experimental setup for testing the response characteristics of the fibre optic technology to water

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ingress under insulation. CTF – coreless termination fibre.

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Fig. 3. Humidity induced strain response of the measurement fibre M1 and reference fibre R1.

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Fig. 4. Data obtained from the sensing cable during water ingress test run 1. The broken vertical lines

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correspond to times where water was introduced under the insulation. The dotted vertical lines at 750 and

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920 hours correspond to deactivation and reactivation of the pipe heater respectively. The black vertical line

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denotes the start of the drying out sequence using an air pump. a) Average strain response of fibres M1

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(blue line) and R1 (red line) in the cable section installed under the air gap cell glass insulation. (b) Relative

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humidity response derived from the data in (a). The inset shows the relative humidity response during the

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drying out sequence where the green and red vertical lines correspond to activation and deactivation of the

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air pumps respectively. (c) Average relative humidity response derived from measurements in the cable

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section installed under aerogel insulation.

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Fig. 5 Data obtained from the sensing cable during water ingress test run 2. The broken vertical lines

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correspond to times where water was introduced under the insulation. a) The black line shows the average

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humidity response derived from the strain response of M1 and R2 in the cable section installed under the air

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gap cell glass insulation. The blue shows the average humidity response of the three point sensors

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positioned near both ends and at the centre of the same pipe (b) the average humidity response derived

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from the strain responses of M1 and R2 in the cable section installed under aerogel insulation.

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Fig. 6. Plot showing the relationship between the volume of water added under air gap cell glass insulation

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and the maximum average fibre optic derived humidity response. The plot includes data from all water

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additions during test run 2. The inset shows the dataset limited to water additions for 100 ml or less. The

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black lines show a sigmoidal curve fit to the data.

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Fig. 7. Distributed fibre optic humidity sensing data and point humidity sensor data showing the spatial

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development of humidity under air gapped cell glass before and following a 5 L water addition during run 2. 15

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Water was introduced at a distance approximately 1.8 m from the drain end of the pipe. The data

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corresponds to 30 minutes before the water addition (red line for fibre optic humidity data, red squares for

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point sensor data), and following the water addition: one hour (black line, unfilled circle data points), 5.5

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hours (broken lines, unfilled triangles), 6.5 hours (dotted lines, unfilled squares) and 24 hours (blue line, blue

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squares). The spatial resolution of the data is 1 cm.

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Fig. 8. Measured strain response of a test fibre to a simultaneous increase in temperature and relative

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humidity. (a) Data when the test fibre was connected directly to the interrogator. (b) Data when a 2 km delay

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coil was connected between the interrogator and test fibre. The spatial resolution of the data is 10 cm.

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• • • • •

A novel fibre optic sensor technology for making distributed water ingress measurements is presented. Sensor cables comprised of a humidity/water sensing fibre, and a reference fibre that was used to compensate for temperature effects. Controlled water ingress tests were carried out with sensor cables installed on air-gapped cell glass and aerogel insulation. The fibre optic technology was able to resolve water ingress under air gap cell glass insulation equivalent to < 10 ml / meter pipeline The feasibility to make water ingress measurements on a 10 cm length scale over 2 km fibre was demonstrated.

The authors do not have any conflict of interests.