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INVESTIGATION OF FBG SENSORS AND

THZ SYSTEM AT CSIRO

Caleb Seal and Navaldeep Phokela

30th of November 2014

ABSTRACT

Over the course of our time at CSIRO we worked on two different projects. We first started working on detecting

leaks in pipes using a fibre Bragg grating array of sensors. We had begun to do preliminary measurements of

how the sensors responded to the pressure surrounding the sensors. However when it came to performing the

tests in the pipe while simulating leaks the sensor array stopped working. This meant that we were unable to

complete this experiment and moved onto optimising a terahertz imaging system and using it to take images of

a few small samples. The ability to be able to image objects that are hidden from view has massive applications

for security screening to prevent sharp metal objects from being taken into secure areas. This report is split up

into two sections, the first outlining the leak detection in water pipes and the second section goes on to explain

the terahertz imaging system.

Document Version

Status

v0.1

Issue Date 11/30/2014

Authors Navaldeep Phokela and Caleb Seal

Unit PHTN310 Industry Project

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CONTENTS

Abstract .................................................................................................................................................................. 1

Leak Detection in Pipes........................................................................................................................................... 3

Introduction ........................................................................................................................................................ 3

Theory ................................................................................................................................................................. 4

cROSS CORRELATION TECHNIQUE FOR TIME DELAY ESTIMATION................................................................. 5

Material properties of pipe and speed of sound principles ........................................................................... 5

Leak Physics Fundamentals ............................................................................................................................ 7

Fibre BragG grating Pressure Transducer ....................................................................................................... 7

Simulating Leak rates for creating different acoustic energies .................................................................... 10

Interrogator system ...................................................................................................................................... 11

Method ............................................................................................................................................................. 16

Calibration .................................................................................................................................................... 17

Leak rate ....................................................................................................................................................... 18

Pull through test ........................................................................................................................................... 18

Results .............................................................................................................................................................. 19

Calibration .................................................................................................................................................... 19

Discussion ......................................................................................................................................................... 20

Terahertz Imaging system..................................................................................................................................... 21

Introduction ...................................................................................................................................................... 21

Theory ............................................................................................................................................................... 21

Terahertz waves............................................................................................................................................ 21

Terahertz generator...................................................................................................................................... 22

Terahertz detector ........................................................................................................................................ 22

Design of imaging system ............................................................................................................................. 22

Method ............................................................................................................................................................. 24

Setup of cage system .................................................................................................................................... 24

Optimising the system .................................................................................................................................. 24

Taking images ............................................................................................................................................... 26

Results .............................................................................................................................................................. 27

Image capture from labview software.......................................................................................................... 27

Image capture of leaf .................................................................................................................................... 29

Image capture of mettalic objects concealed in items ................................................................................. 31

Discussion ......................................................................................................................................................... 32

Conclusion ............................................................................................................................................................ 34

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References ............................................................................................................................................................ 34

Figures .............................................................................................................................................................. 35

LEAK DETECTION IN PIPES

INTRODUCTION

The failures in urban water pipelines, such as leaks and bursts, which contribute to unnecessary waste of

increasingly scarce resources have dire social and environmental ramifications. The solution lies in employing a

new technique for leak detection called acoustic detection. Acoustic techniques have been proven useful in

water distribution systems. The role of leak detection equipment is to identify the sound/vibration induced by

the water escaping from pipes under pressure. When pressurized water leaks from a pipe, it creates a sound

which travels through the pipe wall, the water column and to the surface. As water passes through a leak hole,

its velocity increases. As such if the velocity is high enough, then the pressure at the leak point can drop below

the vapour pressure of the liquid and thus form vapour bubbles. The sound generation mechanism of a leak

signal can be a low frequency or a high frequency signature. More traditional techniques include using single

element listening devices using hydrophones/accelerometers which can detect a leak by their time domain or

frequency signatures and so localise the leak site. [1] However, these legacy techniques do not take in pipe

measurements nor make use of any cross correlation techniques.

The acoustic measurements are not limited to above ground as used in hydrophones but also includes in pipe

sensing which provide more mobility to the pipe network along with enhanced differentiation between a leak

induced signal and any unrelated perturbation. However, the techniques used have not utilized the cross

correlation methods to detect leak points. The key lies in being able to isolate the leak signal from other

background noise sources. The nature of acoustic wave propagation inside a pipeline is manifested by a change

in velocity and pressure. The challenging task however is being able to distinguish between a leaks induced

perturbations or other turbulence induced perturbations. [2]

In water distribution systems, a significant amount of water is lost due to leakage from distribution pipes. To

reduce leaks, a mechanism needs to be developed to locate and repair leaks. The acoustic leak detection

equipment is used to locate the leaks. Initially, we used listening rods and hydrophones to detect sound induced

by placing them in direct contact with pipes. This was followed by ground microphones being used to pinpoint

suspected leaks by listening for leak sounds on the pavement or soil directly above water pipes. Leak noise

corrugators are commonly used computer devices which can pinpoint an anticipated leak site. All in all there

exists an array of leak detection equipment available for commercial use. [3]

The acoustic measurements are not limited to above ground measurements as used in hydrophones but also

includes in pipe measurements which provide more mobility to the pipe network along with enhanced

differentiation between a leak induced signal and any unrelated perturbation. However, the techniques used

have not utilized the cross correlation methods to detect leak points. The key lies in being able to isolate the

leak signal from other background noise sources. The nature of acoustic wave propagation inside a pipeline is

manifested by a change in velocity and pressure. The challenging task however is being able to distinguish

between leak induced perturbations or other turbulence induced perturbations.

If we look at the evolution of progressive development of leak detection systems there were lots of quantum

leaps made in this area since 1994. Seaford and Harry (1994) provided a methodology based on a signal

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processing technique, a means to detect water leaks in pipes. [4] This method extracted acoustic patterns by

high order spectrum analysis generated by transducer signals to detect the leak site. In 2000, Savid and Mantozzi

postulated an acoustic emission technique based on power spectrum analysis. Although, this technique was a

significant improvement from its predecessor techniques there is a small caveat. It could not get rid of

background noises for enhanced differentiated between leak induced signals and background signals. In 2007

Toshitaka and Akira proposed a leak detection method which uses a Support Vector Machine (SVM). Field tests

showed that this method could distinguish leak signals from non-leak signals. With further field tests done its

cons for commercial use were identified and a better means of acoustic leak detection needed to be found.

However, all these methods have major drawbacks in use for commercial systems. A better technology and thus

technique needed to be discovered. Hence, in this experiment we use a complete different technique using Fibre

Bragg Gratings in a sensor array technology as pressure transducer to localise leak events.

The effectiveness of existing leak detection methods and equipment has been accurately demonstrated with

problems involving interfering signals from road traffic or other sources, causing signal attenuation. We explore

different measurement and analysis procedures to locate leaks including the frequency content of the leak

signal, the attenuation rate, as well as variation of the propagation velocity with frequency. The information

about these characteristics is required for proper judicious practice of instrumental and measurement

procedures including calculating propagation for the cross-correlation. We carry out all measures of acoustical

analysis based on a specially constructed experimental setup for simulating leak events under controlled

conditions. [5]

The objective of this report is to perform in pipe measurement of acoustic signatures of leaks and to do

experimental study to characterise the acoustic signature of leaks in water distribution systems through in pipe

measurements. When a leakage occurs through an orifice in a pressurised pipe, it creates a turbulent jet that

interacts with the pipe wall. The interaction results in turbulent pressure fluctuations that produces sound.

These signals travel through the pipe wall.

This project report aims to use an in pipe leak locating sensor array using fibre optic technology. The optical fibre

consist of two discretely positioned pressure transducers which measure water guided acoustic waves. This is in

an effort to localise the failure site. The array is engineered for deployment into a pressurised water pipeline

through a gland seal which sits within the water column inside the pipe. The fibre optic array successfully detects

the presence of a simulated leak event which registers an acoustic disturbance in the time domain. The time

delay between the signals at the sensing locations could be estimated using the cross-correlation technique in

an effort to infer the position of the acoustic source relative to the sensor pair. Since high frequency sound is

attenuated in pipes, this technology is designed to detect low frequency noise events.

The benefits of using this technology include:

- Ability to survey long distances across pipe networks

- Survey difficult to access locations within a pipe network

- Ability to employ sensors in close proximity to the leakage site

THEORY

This report investigates in pipe leak measurements using FBG sensor array technology to perform auto-

correlation to distinguish leak induced signals from non-leak signals by measuring small perturbations in

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pressure. [1] A prototype of this sensor array technology used in fibre optic systems is showcased in this report.

A sensor array consisting of two FBG sensors being used as pressure transducers for acoustic wave signal

detection along fibre optics. The array is engineered for detection of time domain and frequency domain

signatures as simulated leak events for acoustic disturbances. We gain insight into cross correlation methods for

time delay measurements. This experimental investigation also involves characterization of frequency content

of sound from their frequency signatures as a function of leak type, flow rate, pipe pressure as well as the

determination of attenuation rate and variation of propagation velocity with frequency. This is all made possible

from a prototype sensor array technology used in fibre optic systems.

The detection of a leak event is identified from an acoustic signal generated from the interaction of a turbulent

jet and pipe wall creating the pressure fluctuations causing sound. The generated leak induced acoustic signal is

below 1 kHz in frequency range due to the unsteady flow separation at the orifice. The sound travels through a

water column inside a pressurised system to detect low frequency noise events.

CROSS CORRELATION TECHNIQUE FOR TIME DELAY ESTIMATION

The auto-correlation function is used to analyse the time series of leak signals in an effort to determine the self-

similarity feature of the leak signal. The value of the autocorrelation function is used to extract/evaluate the

degree of self-similarity of the signal. [3]

The commonly used technique for leak detection in water distribution pipes is the correlation technique to

locate two measured signals on both sides of a leak. [2] We can regard the FBG sensors as access points on either

side of the location of the leak. If a leak exists, a distinct peak needs to be found after the cross-correlation of

two functions 𝑥1(𝑡) 𝑎𝑛𝑑 𝑥2(𝑡 + 𝜏) where 𝜏the time lag between the two sensors is. This gives the time delay

corresponding to the difference in arrival times between the acoustic signals at each sensor. The location of the

leak relative to the measurement points can then be found.

The effectiveness of the correlation technique is governed by the sensitivity of the Fibre Bragg Grating sensors.

The Fibre Bragg grating sensors are designed to be sensitive to acoustic signals to achieve sharp peak correlation

coefficients. The cross-correlation technique is used for source location. We measure acoustic signals using Fibre

Bragg Grating sensors on two access points on both sides of the suspected leak. The signals from the sensors are

input to an interrogator, which then computes the cross-correlation function of the two signals and presents a

result. The Fibre Bragg Grating sensors are placed at close proximity to a simulated leak where the data

measured includes two continuous time signals x1(t) and x2(t) where the cross-correlation function is

mathematically defined as

𝑅𝑥1𝑥2 = 𝐸[𝑥1(𝑡)𝑥2(𝑡 + 𝜏)]

Where E[] is the expectation operator and 𝑥1(𝑡), 𝑥2(𝑡 + 𝜏) are the two cross correlated signals.

The auto-correlation function is used to analyse the time series of leak signals in an effort to determine the self-

similarity feature of the leak signal. [3] The value of the autocorrelation function is used to extract/evaluate the

degree of self-similarity of the signal. If a leak is present between two sensor positions, a peak is seen in the

cross-correlation function. This yields a time delay which corresponds to a difference in arrival between the

signals at each sensor. The location of the leak relative to the measurement points is calculated. [6] The

localisation of a failure site results due to the synchronised positioning of the Fibre Bragg Grating sensors relative

to the to the leak site. The time delay is found due to the application of the cross-correlation technique to locate

the position of the acoustic source.

MATERIAL PROPERTIES OF PIPE AND SPEED OF SOUND PRINCIPLES

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The cross correlation technique relies heavily on sound travelling through a water column inside the pipe. For in

pipe measurements, we are looking at low frequency acoustic measurements where the low frequency sound

energy is not radiated out of the leak, but instead reflected towards the source. The high frequency sound energy

attenuates inside the pipe thus leaving behind low frequency signals for leak diagnostics.

The acoustic wave attenuation inside a pipeline occurs due to intrinsic absorption. Generally, the absorption

losses are purely a result of internal friction attributable to the work done at the material interface. A larger pipe

with a larger diameter attenuates higher frequencies and so the lower frequencies remain to be the most

abundant inside the pipeline.

The speed of sound in a fluid, is the rate of propagation of small disturbance pressure pulses through the fluid.

The formula used to calculate the speed of sound in water fluid is discussed here. The formula exhibits how

sound velocity in a pipe is directly influenced by the pipe material and its diameter. The theoretical speed of

sound in a water filled pipe is estimated by the mathematical expression is

𝑉𝑝 =𝑉0

√1 +𝐾. 𝑑𝐸. 𝑡

Where Vp = speed of sound in the pipe , V0 = speed of sound in open water , K = bulk modulus of water ,

E = elastic modulus of pipe material , d = inner diameter of pipe and t = pipe wall thickness .

We can calculate the theoretical speed of sound inside our pipe system by plugging in the parameters affecting

internal fluid and pipe properties with 𝑉0 = 1482𝑚/𝑠 , 𝐾 = 117 × 106 𝑘𝑃𝑎 , 𝐸 = 117 × 106𝑘𝑃𝑎 , 𝑑 =

101.6𝑚𝑚 , 𝑡 = 1.6𝑚𝑚. These are the actual parameters we are using for experimental measurement of our

pipeline.

𝑉𝑝 =1482

√1 +117 × 106 𝑘𝑃𝑎 × 101.6 mm

117 × 106 × 1.6𝑚𝑚

= 1005 𝑚/𝑠

This formula takes fluid and pipe properties into the computation. The major contributing factor for yielding a

certain wave velocity in a fluid filled medium is the pipe’s intrinsic properties. We assume that at a constant

temperature and gas pressure it does not have an influence on the speed of sound in water. Hence, it makes

sense that sound velocity in a pipe depends on and is influenced by the pipe material physics including its elastic

modulus, and ratio between the diameter and wall thickness.

Young’s modulus is another factor affecting the speed of sound in pipes. By definition, Young’s modulus

measures the stress divided by the strain. This is given by

𝐸 =𝑡𝑒𝑛𝑠𝑖𝑙𝑒 𝑠𝑡𝑟𝑒𝑛𝑔𝑡ℎ

𝑡𝑒𝑛𝑠𝑖𝑙𝑒 𝑠𝑡𝑟𝑎𝑖𝑛

If we were to analyse the speed of sound in a rigid pipe, it is material dependent however it does not change

too much according to if there is no water flow or additional flow in the system at a certain regulated pressure

level. An important fact to be noted is that air pressure inside the pipe does not change the acoustic wave speed

significantly. However, the speed of sound is steadier when there is an airflow in the pipe compared to no flow.

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The compressibility of the fluid also needs to be factored in into the equation in being able to determine the

disturbance of the signal which propagates at a finite velocity. [9]

LEAK PHYSICS FUNDAMENTALS

The leak is a noise source approximated as a point source emitting spherical waves

An acoustic wave in a pipe represents a perturbation of velocity and pressures which propagates as a

plane wave

Noise generated by a leak is a broadband noise source spanning a wide range of frequencies however

higher frequencies attenuate leaving the low frequency as dominant frequencies

Sound measurements in water are perceived differently to air in terms of sound loudness and so the

strength of the acoustic signal needs to be interpreted accordingly

All flow disturbances including pipe fittings, valves, leaks contribute to the intensity of the turbulent

noise

The acoustic signature observed by the interrogator is intrinsic to the experimental piping system used

It’s important to understand the impact of a leak in a leak free acoustic signature

The leak signature is more easily identifiable at the tapping point close to the sensors

Leak signal strength increases as the pipe pressure increases

The frequency band of the leak acoustic signature varies for the same pipe setup depending on the leak

size and the acoustic energy of the leak signal at the leak site

The size of the leak depends on the leak rate which dissipates different acoustic energies with higher

acoustic energies for higher leak rates

A reference acoustic spectrum of a leak pipeline at a specific leak rate will allow one to connect the

dots between acoustic energy and spectral content of the leak.

FIBRE BRAGG GRATING PRESSURE TRANSDUCER

The Fibre Bragg grating (FBG) technology is used as a sensing element inscribed at the core of the optical fibre.

A Fibre Bragg Grating sensor can be designed to measure acoustics as well as force, pressure and temperature.

The in pipe FBG sensor is specifically used for the detection and localization of acoustic events in a pressurised

pipe system.

The Fibre Bragg Grating sensor has some many advantageous attributes which includes electromagnetic

immunity (immunity to electromagnetic fields), high sensitivity, multiplexing ability, ability to be embedded in

composite materials(smart structure design), high durability immunity from chemically explosive media and

nuclear ionising radiation. [7, 8] The main application area resonating the natural use of FBGs is in optical sensing

for quasi distributed measurements of acoustic perturbations, pressure or acceleration. However, FBGs have

become the key fibre optic telecommunication device for multiplexing capabilities including WDM (wavelength

division multiplexing), spatial division multiplexing (SDM), and time division multiplexing (TDM).

Fibre Bragg Gratings have some distinguishing advantages as compared to other fibre optic sensing technologies

which makes them increasingly special. One of the biggest advantages is their (1) ability to give an absolute

measurement insensitive to fluctuations in the irradiance of an illuminating source, where the information is

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obtained by detecting the wavelength shift induced. (2) They can be ingrained into the fibre no matter how small

the fibre diameter may be which makes FBG sensors useful for different probe dimensions for applications

particularly in strain mapping or the human body for accurate temperature profiling.

Figure 1. A close up of a FBG sensor

A Fibber Bragg grating is formed by a periodic change in fibre core refractive index in the direction of propagation

of the optical radiation.

The Fibre Bragg Grating is a device used in telecommunications and sensor technology. A broadband light source

is launched into the fibre, it causes the Bragg wavelength to be reflected along the grating. Hence, the Fibre

Bragg Grating works as a spectral filter which reflects particular wavelengths at or close to the Bragg resonance

wavelength. The acoustic perturbations introduced into the sensing cable cause this behaviour. The Bragg

resonant wavelength is given by,

𝜆𝑏𝑟𝑎𝑔𝑔 = 2𝑛𝑒𝑓𝑓 Λ

The parameters that comprise this equation are 𝝀𝒃𝒓𝒂𝒈𝒈 which is the Bragg resonant wavelength, 𝒏𝒆𝒇𝒇 which is

the effective refractive index and 𝚲 which is the periodic variation of the FBG. The FBG can then be combined

into a transducer design to measure the physical parameters. A sensor array is formed by having multiple FBG

elements laid out across a single optical fibre where each elements reflects a different wavelength of light to

enable quasi distributed sensing of the leak induced acoustic wave signatures.

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FBGs are used in sensors to undertake spectral analysis of reflected light wavelengths where the Bragg resonant

wavelength is determined by various factors applying to the FBG, where this may affect the refractive index or

grating periodic variation and hence is an indirect measurement resulting from modifying physical or

geometrical properties of the FBG. Amongst other factors include temperature, mechanical deformation and

others. The pressure measurement is thus based on the deformation of the sensing part which includes shear,

bending and stretching of the fibre Bragg grating. Hence, in reality it is difficult to separate the effects of

measured and parasitic variables which may affect the same parameter.

When a stress is applied on the fibre Bragg grating in the direction of the fibre axis it results in an extension of

the physical dimensions results in a periodic variation. However, the influence of temperature may also affect

physical dimensions due to thermal expansion. . As the applied strain increases, the reflected Bragg wavelength

also increases in a linear fashion. In addition to strain sensing, the FBG can be combined with other transducer

designs to measure different physical parameters for different applications. After obtaining these different Bragg

spectral wavelengths, the interrogator system can be used to monitor the wavelength peak levels. [1]

An extended mathematical model of a shift in Bragg wavelength is given by the expression

Δ𝜆𝑏𝑟𝑎𝑔𝑔 = 2 (Λ𝜕𝑛𝑒𝑓𝑓

𝜕𝑙+ 𝑛𝑒𝑓𝑓

𝜕Λ

𝑑𝑙) Δ𝑙 + 2(Λ

𝜕𝑛𝑒𝑓𝑓

𝜕𝑙+ 𝑛𝑒𝑓𝑓

𝜕Λ

𝑑𝑙)Δ𝑇

The l denotes the FBG length while T denotes the temperature. The FBG spectrum deformation can also be

created by applying a strain by pressing the FBG to get a cross sectional shape. This deformation implies a

different effect on the resulting spectrum which has the capability to split it into two peaks where the central

frequency distance is equal to the fibre cross section deformation ratio. The distance between the two spectral

peaks can be defined by a second order polynomial functions given by

𝑓(𝑥) = 𝑎 × 𝑥2 + 𝑏 × 𝑥 + 𝜆𝑏𝑟𝑎𝑔𝑔 −𝜎

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With a and b being constants, 𝜆𝑏𝑟𝑎𝑔𝑔 being the Fibre Bragg Grating central wavelength and 𝜎 being the Fibre

Bragg grating wavelength. The spectral characteristics at different pressures are different in the sense that a

higher pressure causes a greater distance between the narrowband peaks on the I-MON while the smaller

distance will occur at the lowest pressures.

The reflectivity of the Bragg wavelength is estimated by

𝑅 = 𝑡𝑎𝑛ℎ2Ω

The full width half maximum (FWHM) bandwidth of the FBG grating is given by

∆𝜆 = 𝜆𝐵𝑠√(Δ𝑛

2𝑛)

2

+ (1

𝑁)

2

Where N is the number of grating planes and Δ𝑛

𝑛 is the index perturbation of the system, s is approximately 1.

The main change in the line width occurs due to change in modulation depth of the index perturbation in the

pipeline.

The pressure change Δ𝑃 due to change in acoustic pressure corresponds to a wavelength shift on the

interrogator system as follows

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The contribution to the fractional change in the optical propagation delay line arises due to a fractional change in the fibre diameter due to a negligible applied pressure relative to the change in refractive index and pipe length. This is given by,

Where E is Young’s modulus, P is the pressure, and p12 and p11 are the pressure parameters and v is the velocity.

SIMULATING LEAK RATES FOR CREATING DIFFERENT ACOUSTIC ENERGIES

If there isn’t a leak site, then the drop in pressure inside a linear water pipeline is linear. However, when a leak

is present then the pressure gradient changes and we have the two linear segments appearing with different

slopes. The leak propagates as a pressure wave where the negative pressure wave spreads at the speed of sound

in both directions along the pipeline. The leak position can then by calculated using arrival time of the pressure

wave at the distal and proximal Fibre Bragg grating sensor.

Figure 2. Leak experiment setup with pressure transducer positions

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INTERROGATOR SYSTEM

Figure 3. I-MON 245 Interrogator

The I-MON 256 interrogator offers real time spectrum monitoring of FBG sensors at line scan rates of 35 kHz at

high resolution and broad wavelength range. Some of the desirable traits of this interrogator include high

response speed, precision, accuracy, sensor multiplicity and higher cost.

In FBGs, the exposure through light produces a permanent increase in the refractive index of the fibre’s core,

creating a fixed index modulation according to the exposure pattern. This fixed index modulation is called the

grating. At each periodic refraction change a small amount of light is reflected. All the reflected light signals

combine coherently to one large reflection at a particular wavelength when the grating period is half the input

light's wavelength. This is the Bragg condition. Light signals at wavelengths other than the Bragg wavelength,

will pass the FBG without attenuation. This principle is shown below. This effect allows introducing several Bragg

reflectors in one fibre, as long as the reflected wavelengths are not overlapping; it is possible to identify each

individual measurement node. In this way many sensors can be connected in one single measurement chain.

The central wavelength of the measurement component satisfies the Bragg relation has a dependence on the

index of refraction and period of index of refraction variation in the FBG. These parameters are affected by a

change in strain (acoustic pressure) and thereby changing the reflected wavelength component.

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Figure 4: Interrogator Output spectrum

The interrogator consists of a broadband light source, an optical circulator/coupler, multiple photodiode/pre-

amplifier and a data processor/microcomputer. [10] The Fibre Bragg gratings are positioned on the sensing cable

to provide a sensor array. The reflected light from the fibre is launched into the I-MON interrogator which divides

the incoming light into multiple channels of different narrow band wavelengths. In order to avoid Fabry-Perot

interference effects among FBGs which may cause misleading spectral modulation, these FBGs are placed

further distant along the fibre from each other than the coherent length of the light reflected by FBGs.

Figure 5: Schematic illustration of AWG transmittance and FBG reflectance for interrogation

The interrogator system is used to interrogate all FBG elements in the array simultaneously to observe the

corresponding spectral Bragg wavelength peaks using a spectrometer. The interrogator system had multiple

input channels. By mechanically changing the wavelengths, the central wavelength of the two input channels

could be changed. The interrogator can optically multiplex by wavelength the two input channels and moreover

it can cover the entire band of the broadband light source. The interrogation is performed by direct detection

of light intensity between different input channels. The interrogator is perfect for multiplexing distributed FBG

sensors along an optical fibre since it enables high speed interrogation for 3 or more FBG sensors. [10]

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Figure 6: FBG Sensing Capabilities

This figure illustrates how the system can be used for Fibre Bragg Grating sensing. The periodic modulation of

refractive index on the Fibre Bragg Grating manufactured using DHG towers is created from a phase mask which

creates a narrow filter with peak reflectivity at a wavelength 𝝀 determined by the period of the FBG. A

broadband source consisting of a superluminescent diode (SLED) is used as a light source for the FBG sensing

system.

When we mount the FBG, it may be stretched or compressed due to structural changes. This may cause a change

in the FBG period. Subsequently, the peak reflectivity of the FBG is shifted according to the wavelength shift.

Each fibre can contain a multitude of FBG sensors which all have a different peak reflection wavelength.

We can determine the peak reflection wavelength and shift in peak wavelength on the basis of FBG sensing,

since the reflected wavelength is converted to pressure. The I-MON interrogation monitor is designed to

measure the reflection spectra from the FBG sensors, where this will provide data to the control electrons for

accurate peak determination.

INTERROGATOR MEASURED SPECTRA AND PEAK DETERMINATION

The reflected FBG spectra is sampled by the diode array with 256 pixel or 512 pixels. The average pixel spacing

in wavelength is similar for both I-MONs. The optical resolution (FWHM) of the I-MON is about 330 pm, which

is a typical FBG with a bandwidth of 200-300 pm where this means that each FBG is sampled by about 2 pixels

which is just enough to minimize wavelength non-linearity resulting from the pixel under sampling.

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Figure 7: Interrogator Spectra and Peak Determination of Gaussian Output

In the figure above, we may note that the optical response of the I-MON is Gaussian, with the FBGs Gaussian

apodized. Each dot represents an intensity signal from the discrete diodes in the FBG array. The Gaussian peak

fitting is computationally intensive, and it’s achieved using algorithms such as centre of gravity or centroid

algorithm.

WAVELENGTH CALIBRATION

The I-MON is wavelength calibrated at room temperature according to the following polynomial function

𝜆[𝑛𝑚] = 𝐴 + 𝐵1𝑝𝑥 + 𝐵2 𝑝𝑖𝑥2 + 𝐵3𝑝𝑖𝑥2 + 𝛽4𝑝𝑖𝑥3 + 𝛽5𝑝𝑖𝑥5 𝑝𝑖𝑥 = 0.255 𝑜𝑟 511

The equation above provides insight into the beam spot position on the image sensor and the optical

wavelength. The beam spot position can be determined by applying a Gaussian fit to the image sensor response

based on the wavelength calibration equation. The input light source is a super luminescent tuneable laser diode

coupled to a reference wavelength meter. The wavelength meter is set to measure the wavelength. The

coefficients in the equation above are set to measure for each I-MON unit. The number of pixel numbers

displayed on the image sensor relates to the magnitude of the wavelength. A short wavelength corresponds to

high pixel numbers where as a long wavelength corresponds to lower pixel numbers on the image sensor. This

is shown diagrammatically in the figure below,

Figure 8: Wavelength calibration and pixel number

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IMAGE SENSOR

The FBGs are sensed into an image onto a linear image sensor which converts incident light into an electrical

signal. The image sensor then outputs a photoelectric signal from each pixel for a certain time interval. The time

interval is called sample frequency which determines how fast the optical signals can be detected. The signal

gain is controlled by an on chip charge amplifier. The charge amplifier integrates the photo-diode current over

a certain time interval called the “exposure time”. The output signal can thus be optimized by adjusting the

exposure time. For example, even at low light levels, lengthening the exposure time increases the output signal

at a level where the signal can be easily processed.

INTERROGATOR SPECTRUM GRAPH

The spectrum graph (see Figure 2) is illustrated with the reflected response from two Fibre Bragg Gratings (FBGs).

The image sensor has 256/512 pixel elements but due to USB transfer limitations, the electronics only transfer

254/509 pixels. Thus, the software will only display 254/509 pixels. The x-axis can be displayed in either pixels

as in Figure 2 or directly on a calibrated wavelength axis. The spectrum graph shows the wavelength spectrum

of the measured signal, i.e., it shows the power readings in counts for each pixel in the diode array of the I-MON.

On a pixel axis the shorter wavelengths are imaged at the higher pixel numbers whereas the longer wavelengths

are imaged towards the lower pixel numbers.

The I-MON spectrum graph below is characteristic of the two sensing elements displaying their acoustic spectral

response due to a change in pressure at the distal and proximal sensor. This is expected output on the I-MON

which we were supposed to see for acoustic detection of a leak as picked up the interrogator system.

Figure 9: Output of Interrogator Spectrum Graph

16

METHOD

Figure 10: Equipment list

(1) SLED Source Box (2) +5V Power Supply (3) USB Cable (4) Cable Harness (5) SMF Patchcord FC/APC

(6) AC Power Cord

Figure 11: Interrogator

17

Figure 12: Fibre Optic Cable

CALIBRATION

This calibration of the Fibre Bragg Grating sensor involved accurate measurement electronics and software to

sense light reflections using Fibre Bragg Gratings. To simulate leak events, a linear pipe section of length 6.2

metres with a separation distance of 23cm between linear pipe elements. The linear pipe section was first de-

pressurized which can be verified by checking that the pressure regulator is showing 0 kPa pressure. After

ensuring the pressure regulator was giving a 0kPa pressure reading, the sensor array cable is fed through one of

the gland inlets for distal sensing near the tapping point. For correct insertion of the sensing array, loosen the

nuts protecting the gland inlet and gently feed through the sensing array across the linear section of the pipe.

The sensing cable will consist of two Fibre Bragg grating sensors. This includes a distal FBG sensor and a proximal

FBG sensor. Both sensors need to be positioned relatively closely to the tapping points. This is achieved by

making markings at various sections of the pipe. The sensing elements are denoted by their channel numbers 1

(distal FBG array) and 2 (proximal FBG array). This can be seen in the diagram below.

Figure 13: Leak event simulation schematic

Now turn on the pressure regulator to 200kPa and using the computer software and I-MON Interrogator System

observe the wavelength peaks given at 200 KPa pressure for the Fibre Bragg Gratings. A pressure calibration is

done such that we get a characteristic peak wavelength response from the Fibre Bragg Grating sensor arrays

18

which matches the typical peak wavelength positions on the spectrometer at these pressures. This is measured

on the computer software for data post processing. The computer software and the I-MON consisting of a

broadband light source, optical circulator/coupler, pre-amplifiers and photo-diode, and a data

processor/microcomputer enables the central wavelength changes to be seen with a change in external pressure

from the pressure regulator. As pressure is increased, the wavelengths successively decreases. The pressure and

wavelength values were transcribed. They were then plotted on excel for further data analysis.

LEAK RATE

Turn the system on by filling the pipeline with water subjected to a specific pressure calibrated by the pressure

regulator. Simulate a leak site at the tapping point to disrupt the linear pressure in the water pipeline prior to

the creation of the pressure wave. Place an appropriately sized bucket to hold the water underneath the leak

site. Three different leak rates were then simulated based on the degree at which the tap was open. The first

leak rate is simulated by a small turn for a small leak, a halfway turn and a full turn. These were realised by

indicator numbers marked on the pipeline using a marker. The water tap was on for 5 second or 10 seconds

depending on the leak rate and it was transferred to measuring beakers/scales to attain a volumetric

measurement. This volumetric measurement was in the order of a few litres on scale. To calculate the leak rate

we simply divide the volume in litres by the time taken in seconds to get a leak rate in Litres/second.

𝐿 =𝑉

𝑡

We will use these measurements for the pull through test by opening the tap to the same positions as used for

this test. These leak rates will come in useful for the next part of the experiment.

PULL THROUGH TEST

The first thing that forms part of the pull through test is determining the location of the sensors relative to the

pipeline. We determine the point in the sensor array where it will exit the gland seal through the outlet after

entering. The markings on the sensor array uses a marker such that the array can be positioned at the correct

locations inside the pipe. The sensor array uses a marker to position the channel 1 and channel 2 transducers at

the appropriate positons relative to the simulated leak sites. It’s important that during insertion of the sensor

array that the array enters from one end and exits from another. The pressure regulator was turned on to 200kPa

and the tap was turned on to simulate the disturbance present in the system. The tap being turned on marks a

simulate leak point where an acoustic perturbation exists and ideally it should be close to the sensing element

as marked on the sensing cable. The tap is turned on at certain leak rate. The output is then monitored on the

PC where a shift in wavelength of the Bragg spectral reflectance should be seen. The interrogator system should

ensure that the Brag reflected signal has divided the incoming light into channel 1 for the distal sensing element

and channel 2 for the proximal sensing element at different narrow band wavelengths. A Gaussian profile of the

spectral reflectance which is the measurement of the FBG needs to be observed on the computer output. The

cross talk is avoided by keeping the central wavelengths separated to keep the narrowband wavelengths on

separate channels. The spectral reflectance noise floor should be visible on the computer screen once launched

into the interrogator. This is repeated for different marked positions of sensors at different leak rates as

measured previously. For each leak rate and fibre position, post processing of the Bragg signal should allow

capture of the data. The data was then saved onto the local machine. Take measurements of the pipe to

determine the locations that sensors are to be located at. The frequency signatures obtained needs to different

19

according to the leak rates which should be adjusted by opening up to different degrees. The procedure was

repeated for each different leak rates.

RESULTS

CALIBRATION

The graphs below are from the calibration test that we performed on the sensors of the fibre array. These graphs

show the sensitivity of each of the individual sensors.

Figure 14: Calibration for sensor furthest from the light source

Figure 15: Calibration for sensor closest from the light source

20

DISCUSSION

The FBG sensors that we used in this experiment are designed to measure pressure. The graphs that we obtained in figure 14 and 15 show the response that these sensors have to changes in pressure. By performing a linear regression on the data an equation for the line is found. The slope of this line shows how the as the pressure surrounding the sensor increases the wavelength of the reflected light decreases. This was measured as 0.0009 nm/mmHg for the sensor furthest from the light source and 0.0011 nm/mmHg for the sensor closest to the light source.

Both sets of measurements for the sensors has a high R squared result of over 0.99 that indicates that the linear fit is a very good fit for the data obtained. This shows that the pressure that is surrounding the sensor is the major factor that is determining the wavelength of the reflected light from the FBG. All other variables that influence the FBG such as temperature are constant and so do not influence the results.

The error for the wavelengths recorded is 0.0005 nm because we are only given the wavelength to 3 decimal places. We can then use the equation of the line to calculate the difference in pressure that 0.0005 nm of the wavelength makes to the pressure that is obtained. This gives us a value of 0.6 mmHg difference for pressure for the smallest recordable change in wavelength using the FBG sensor. This is sufficient for measuring the acoustic waves travelling in the pipe as the pressure difference is much greater than 0.6 mmHg.

Using the equations of the lines from this calibration we are able to calculate the pressure from the wavelength detected on the interrogator. This is done by rearranging the equation to have the pressure as the subject. Using this method the pressure on the FBG can be calculated and so it can now be used for measuring the pressure in a water pipe.

The ability to measure pressure using the FBG sensors is required for detecting acoustic waves in the pipes.

Acoustic waves vary the pressure as they propagate. For leak detection in pipes it is the acoustic waves that are

needed to be recorded this has been shown previously and is the reason that hydrophones are currently used.

Because these FBG sensors have the ability to measure the pressure they can be used to measure acoustic waves

that are coming from the leak. With further testing investigations to determine if using cross correlation

techniques could be used to accurately determine the position of a leak between 2 sensors.

21

TERAHERTZ IMAGING SYSTEM

INTRODUCTION

For many years people have been interested in being able to see inside things without the need for physically

opening it up. This has been done with x-rays for many years to see inside the body to check for broken bones

and for security applications to detect sharp objects. Terahertz imaging opens up a new opportunity for being

able to see through objects as it passes through most objects but is absorbed by metallic objects and by water.

This allows this technology to be used for different security screening applications and has the potential to be

used for medical imaging. The purpose for our investigations into this technology was to see if improvements

could be made to the set up using a cage system to house the lenses. The goal was to see if the images obtained

could be enhanced because of an increased ability to focus the light onto the sample and then focus the light to

the detector.

THEORY

TERAHERTZ WAVES

Terahertz waves are a type of electromagnetic radiation that ranges from 0.3 to 3 terahertz or in wavelength

this is 1 mm to 100 μm. They are often called submillimeter waves because of this. They fit in the electromagnetic

spectrum at the end of the range of microwave but are also quite close to the infrared range of radiation. They

are safe for working around as it is a type of non-ionising radiation that only have any safety risks if using very

high intensities as there is some evidence to suggest that they may cause DNA to unravel inside cells.

Technology using terahertz waves is still mainly just being used in research with few commercial applications

currently available. There are however a great number of areas that terahertz technology has potential uses in

including medical, semiconductor manufacturing, security, communications and other areas of science. The

areas where imaging using terahertz waves is useful and these are the areas of security and the ability to detect

objects that are metallic and could be dangerous if taken into secure areas. There has also been research into

using this technology for medical imaging although as terahertz waves cannot travel far through water they are

only useful for imaging near the skin. [11]

The ability of terahertz waves to be able to image is due to its absorption in various materials and it being able

to pass through other materials. They are heavily absorbed in metals and by water. They can however pass

through non-metallic or materials not containing water. This allows them to take images of metallic objects by

scanning a terahertz beam across a sample and measuring the transmission through the object. This makes it an

ideal candidate for security applications where there is the need to be able to see inside bags looking for sharp

objects.

22

TERAHERTZ GENERATOR

There are numerous different methods for generating electromagnetic radiation in the terahertz range however

they are generally more difficult than producing lower frequency radio waves or the slightly higher frequency

infrared radiation. One method of generating radiation in the 0.3-3 THz range is to use a laser and then directing

the laser through a crystal that will then emit the terahertz waves. [12, 13]

The terahertz generator that is used in the system that is setup at CSIRO works by starting with a lower frequency

and then multiplying the frequency several times until it gets to 625 GHz. A RF frequency synthesiser is used

with a bandwidth of 2 to 16 GHz for the input to the multiplier chain. The frequency is then multiplied 48 times

to reach the required 625 GHz needed for terahertz imaging.

TERAHERTZ DETECTOR

In order to be able to capture images using terahertz radiation you are required to be able to detect the radiation

in order to know how much has been absorbed while traveling through the sample. Standard photodiodes will

not work at these terahertz frequencies and so a specialised device that is able to detect the terahertz radiation

is required. The equipment that is set up at CSIRO uses a VDI WR0.5 zero bias Schottky diode for recording the

radiation passing through the sample. This signal is then goes to a lock-in amplifier in addition to the frequency

from the chopper. This allows the lock in amplifier to achieve a cleaner signal from the diode.

DESIGN OF IMAGING SYSTEM

The design of the system for capturing images needs to be able to take the terahertz source and then collimate

it and then focus it to a point where the sample is to be placed. At the other side of the focus the radiation needs

to be collimated again before finally focusing it back to a point where the detector is located at. There are a few

different ways that this can be achieved. Either using parabolic reflectors or using a system of lenses.

The system at CSIRO used to use parabolic reflectors to focus the light to the location where the sample is placed.

The design of how there parabolic mirror is shown in figure 16 below.

23

Figure 16: Set up of parabolic mirrors

There are a few difficulties with using these parabolic mirrors because there are many different adjustments

that are required to be adjusted so that the terahertz waves become collimated correctly and focus to the

required points.

The next terahertz imaging system involved using a set of 4 lenses all with matching focal lengths. These lenses

are made from polytetrafluoroethylene (more commonly known as Teflon) that is transparent to the terahertz

radiation. The first lens is placed in front of the source so that it will collimate the light. The second lens is then

placed in front of this lens to focus the terahertz waves to a single point. After the focal point the third lens

collimates the radiation again before the fourth lens focus the light onto the detector.

Using these 4 lenses removes some of the adjustments that were present in the parabolic reflector set up

however there is still many adjustments to insure that the lenses are all positioned so that they are on the beam

axis. This is why a cage set up that holds the first 2 lenses and the last 2 lenses was set up in order to remove

some of the adjustments to maximize the signal that arrives at the detector.

24

Figure 17: set up of caged lenses

METHOD

The experiment to be carried out involved dismantling the old lens system that was already set up and replacing

it with a cage set up of lenses to reduce the number of adjustments and to improve the imaging system.

SETUP OF CAGE SYSTEM

The first step was to dismantle the lenses from the old mounts that had a separate mount for each lens. The

lenses were then removed and placed inside the new mounts that make up part of the age system. The cage

system that was to be set up had 2 sections, one where the lenses were further apart and the other where they

were positioned closer together. After placing the lenses in the new mounts and putting together the cages we

went on to begin optimising the system.

OPTIMISING THE SYSTEM

In order to take the best quality image using this system care needs to be taken when adjusting the lenses in

order to maximise the signal that traveling through the focus and then focused back on to the detector. By

maximising this it increases the signal to noise ratio so that a clearer image can be obtained. The first stage is to

position the first set of lenses located just in front of the source. These lenses take the terahertz wave and

collimate it and then focus it to a point after the lenses. The detector is relocated to this focus and the lenses

are adjusted to maximise the intensity of the terahertz wave. It is difficult to make these adjustments because

as you relocate the lenses you change the position of the focus and so the detector needs to be repositioned. In

25

addition to this you need to be careful that the detector is located at the centre of the lenses so that we are not

trying to focus the beam off to the side.

The next stage is to place the second set of lenses into the imaging set up. This set of lenses takes the terahertz

radiation after it has passed through the focus and then re collimated it before then focusing it to a point again

so that it can be picked up by the detector. Optimising the signal involved moving the position of the cage along

the rail it is attached to and adjusting the position of the source in x, y and z directions. By making changes to

each of the available adjustments one at a time and then re-doing the adjustments several times we were able

to maximise the signal to the detector. The x-y scanner was then able to be repositioned into the required

location at the focus point that was found when setting up the first cage.

The setup of the terahertz imaging system after setting up the cages and optimising the system is shown in figure

18.

26

Figure 18: Top view of THz imaging setup

TAKING IMAGES

After the optimisation of the terahertz imaging system is complete we are able to see how well the system is

able to take images of a few samples. The method for capturing images is straightforward and is controlled using

a computer running LabVIEW. First the sample is required to be mounted to the x-y mount so that as it moves

the sample will stay secured or otherwise it will distort the image that is recorded. This image system can only

capture small images of 60 mm x 60 mm and so you need to input an offset to where the image is going to start

27

recording otherwise you will be imaging the wrong area. You are able to measure this using a ruler to estimate

the offset and then using a LabVIEW program you can move the x-y mount to go to that location to test if the

measurements are correct.

Using the LabVIEW program that has been programed previously we are able to input the offset for our image

and change the size of the image taken by making various changes as described in the operation manual. Before

starting the capturing of the image the lock in amplifier has to be adjusted to make the scale at a good range.

The computer then controls the x-y mount and records the image and saves the image as a text file with the

signal at the detector recorded so that an image can be created from this data. The LabVIEW program then

displays this image and has a colour scale that can be adjusted to make the details in the images clear. The

program also makes an adjustment of 3 pixels for every second row because there is an offset between the x-y

mount traveling in one direction to the other direction.

RESULTS

IMAGE CAPTURE FROM LABVIEW SOFTWARE

After optimization of the THz system, the sample mounted on an arm was driven by a XY motor through the

beam focus spot for image scanning. This produces transmission properties of the sample as the sample is

scanned to a fixed focal point. The scanning is achieved by a linear XY motor stage by translating the sample in

the plane perpendicular to the beam axis. The images are produced due to an X-Y scanner moving in axial and

lateral directions to locate the sample and take the scan for the set imaging area it has been prescribed. The

position is set by executing the RUN button. The images took 12 minutes to acquire with an image size of 60mm

vs 60mm. The scanning time for the stage and x-y scanner was quite long. The spot size of the imaging system

was approximately 1mm. An area of approximately 60 mm vs 60 mm was scanned. A chopper wheel is placed in

front of the beam and is connected to a lock-in amplifier for acquiring a synchronised voltage response. The

lock-in amplifier acquires the voltage responses processed by the computer with the LabVIEW software installed

where the image is produced. The image capture system requires the use of three distinct programs to enable

digital image processing of the acquired images. These include Set Position.vi, Image Redisplay2.vi and the image

capture program THZAUG146.vi. [14]

Firstly, the scan position of the x-y positioner is set according to the settings shown below.

Figure 19 x-y position

28

Next, the program is started using the RUN button.

Figure 20: start location setup

The X and Y positioner offset was adjusted to where the image is going to start otherwise the whole image area

would not be scanned. After the location has been adjusted, the ‘start location setup’ button was pressed and

the X Y scanner was moved to that location. For our leaf sample and metallic objects concealed in purse samples,

the location setup was different since their relative sizes were different. Hence, the XY positioner had to be reset

every time a THz image of the sample need to be processed by the computer.

After setting the positon of each sensor, the image capture program was initialized. After initialization, the RUN

button was ran and the programme was started. There were two images produced which includes the

uncorrected image on the right and the corrected image on the left in terms of correcting pixel misalignments.

The corrected image should not have much of an offset and if so the image has to be recaptured.

Figure 21. Image Redisplay tool

We then use the image redisplay.vi software to play with the software and adjust the intensity distribution and

contrast on the image.

29

We can obtain a block diagram representation of the system architecture showing how the computer controls

the XY scanner positioner.

Figure 22. LabVIEW Block Diagram

IMAGE CAPTURE OF LEAF

The images were acquired using a detector set to a particular integration time per pixel on top of the time

incurred for positioning the XY scanner. The amplitude information of the leaf content showed the transmission

and reflection behaviour of the leaf. A 600GHz transmission achieved by the frequency multipliers showed a

good contrast on the leaf and greater penetration depth of the image.

Polar liquids such as water are absorptive. The absorption of the THz range of the electromagnetic spectrum

results due to rotational motions of dipoles within a material. The crystals formed from polar liquids are more

transparent due to the dipolar rotations exhibiting phonon resonances at the THz range. [13]

The THz transmission image of a leaf highlights key THz features however the higher water content in the leaf

veins exhibits higher attenuation. The image resolves minor details regarding the leaf’s veins and thickness. The

image recapture program was used to highlight the key features of the leaf including its veins by enhances

contrasting using the colour tool. We know that THz frequencies are sensitive to water content, and this could

be seen in the image feature capture. We analyse the image in terms of its frequency domain and time domain

representation to get a better idea of the transmission and reflection capabilities of THz imaging systems for leaf

matter. A 3D scan of the sample is performed in the plane perpendicular to the optical axis to map the entire

sample. Each measurement point along the scan corresponds to a pixel in the final THz image. The LabVIEW

30

software performs data acquisition of the scanned leaf sample with an image area of 60mm vs 60mm. The image

takes about 12 minutes for a complete scan. The reflection and transmission parameters are analysed in the

frequency and time domain. In a frequency domain transmission, the amount of water content has a

transmission dependence with a high level of water content being representative of the darker colours in the

image. In other words, the transmission power is a key indicator of the degree of water present in the leaf. In

analysing the frequency domain reflection, a high reflection level can be ascribed to high water content, in the

leaf. [11]The operating frequency of the THz transmission antenna was set to 200GHz to show greater level of

detail of water content difference due to the high transmission dependence of water. Hence, it is possible to

differentiate different leaves in terms of their water content using THz radiation as a mechanism to calculate

the frequency and time domain transmission and reflection parameters which can be collectively used to

determine the level of water in a leaf. [13] This makes THz technology useful in imaging organic matter such as

leaves. Furthermore, it demonstrates the advantages of THz radiation over millimetre waves for imaging.

However, by combining both regions of the electromagnetic spectrum, we can extract an even more powerful

image of the leaf with a THz broadband detector.

Figure 23: On the left we have a THz image of a leaf with a smaller field of view then the one on the right

The image on the left and right are of the same leaf however the image on the left suffered from pixel

misalignment when the XY positioner on the motorized stage was being reset with new X and Y position

coordinates by performing start location setup. The image on the left is offset slightly which is why an image

recapture is performed to get image on the right which has a wider field of view of the sample. We can also

note that the image recapture tool has been used differently for each sample acquired as the level of detail and

contrast is quite different even though the same leaf is used.

31

IMAGE CAPTURE OF METTALIC OBJECTS CONCEALED IN ITEMS

Figure 24: On the left there exists the scalpel in the bag and on the right the scissors

The scalpel and metal in the bag THz image typifies THz applications in security and compliance where distinct

signatures are detected for concealed items making THz imaging useful for security applications. This is because

THz radiation is good for screening metallic objects in items since metallic objects reflect the THz radiation. The

ability of THz light to interact differently with benign and sharp materials as a function of THz frequency yields a

useful manner for THz imaging security screening. The imaging technique is based on the use of THz

electromagnetic waves to detect concealed items through their characteristic transmission and reflection

spectra. The scissors and scalpel completely reflect THz waves. [16] This is because metals in general completely

reflect THz waves which makes then viewable inside bags. The image output we witness above is a THz reflection

image. The resulting spectral resolution resolving the spectral features of the target material is visible in both

images where the metallic object concealed in the bag is clearly highlighted by the spectral information given in

the frequency domain THz image. These images demonstrate the ability of THz radiation to see through

packaging materials to reveal concealed items.

We can analyse the electric field generation is because it enables absorption spectra to be detected directly

from the sample using precise signal to noise measurements. The absorption spectra reveals the features that

reflect THz radiation such as metallic objects like scissors and scalpels. Hence, the electric field distribution can

be used to map out the details of a THz image output. These spectral features can differentiate between the

metallic objects and non-metallic objects such as the purse by the relative intensities of each feature.

The formula used to calculate the ratio of THz electric field strengths before and after transmission is given by,

32

𝐸𝑆

𝐸𝑅

= 𝑇(𝑛)exp (−𝛼𝑑

2+

𝑖𝑛𝜔𝑑

𝑐0

)

Where d is the sample thickness, 𝜔 is the angular frequency of the radiation, 𝑐0 the speed of light in a vacuum

and T(n) being the reflection loss at the sample surface.

[16] We analyse the transmittance data bag for a bag containing the metal object concealed within. The

transmittance data can be converted to attenuation per layer by applying the following formula

10log (𝑃0 𝑃) = −10 log 𝜏 = 10𝐴⁄

Here 𝑃0 is the THz power incident on the sample, P is the THz power exiting one layer of the material, 𝜏 is the

material transmittance while A is the material absorbance. The parameter A is key for determining whether a

THz system is useful for screening applications.

Hence, we can use these technical parameters to analyse the transmittance data, and absorption to understand

how and why specific features are extracted of a typical organic or inorganic sample. These parameters explain

the images of the scalpel in the purse as well as the leaf matter showing its water content and anatomical

structures.

DISCUSSION

The reason why we use a THz system is to measure the transmitter or reflected terahertz energy incident upon

a sample processed to reveal spectral content, time of flight data, and signal strength. After generation of the

electromagnetic wave, we detect the EM transients on a detector. [12] The laser pulses strike the detector in

phase coherence with the transmitter. Scanning the sample enable a 2D image to be created which scans the

sample in an X-Y direction.

In THz imaging, since the THz images are acquired by observing the THz waves transmitted through or reflected

from a sample, the spatial resolution is limited by the diffraction limit of the THz wave source with a wavelength

as long as several hundred micrometres. Furthermore, the amplitude of the THz pulse is proportional to the local

electric field originating from the photo induced current generated by photo-induced carriers due to an

internally applied bias which eventually decays according to an integral time constant. [13] The THz pump beam

is scanned over the while sample while the THz signal is recorded at each pixel therefore enabling the THz image

to be formed. The sample scan speed was slow on the motorised stage however that did not affect the good

spectral resolution we achieved from the pump beam. The spectral resolution is determined by the spot size of

the THz pump beam, hence the beam size is focused and thus minimized.

In our THz system, we try to optimize the signal to noise ratio by using the correct detector frequency for a

certain THz transmission signal, using the correct intermediate optical caging system, reducing noise effects due

to moving parts in the mechanical construction of the motorized stage using the cage system and reducing the

noise floor of the lock-in amplifier. The reason behind the sharpness of the image using the THz system is due

to the cage system focusing the THz pulse onto the THz detector due to the lenses mounded in the cage system

to view the sample with excellent spectral resolution. The setup of the cage system enabled the maximum signal

to travel through the focus to the detector. For the detector, the THz wave is synchronised with the trigger pulse

generating a photo-current corresponding to the magnitude of the electric field of the THz pulse. The photo-

current signal which is a THz signal is measured using the lock-in amplifier. The maximum signal can be produced

by optimizing the system to maximize the signal to noise ratio. After the lens action, the THz wave is focused to

a point where the detector is relocated. This follows from precise geometrical optics and lens actions where the

lens maximize the intensity of the THz wave striking the detector. In the experiment it was quite difficult to place

33

the detector at the focus. The second stage of lenses re-collimate and refocus the THz wave to get maximum

signal on the detector. This was prone to human error as precise adjustments of the cage system had to be made

in x, y and z directions until maximum signal was obtained for the sharpest image. Hence, if the x, y and z

adjustment was done to optimize the system, then the THz image produced is not up to mark with the full

capability of the THz system, that is it can be a lot sharper and therefore a more accurate representation for the

sample under investigation. [14]

An image is composed of a distinct array of pixels identifying with a particular location coordinate. Each pixel

that needs to be drawn out on the screen needs to line with a particular physical point on the screen. However,

the reality is that the detection is imperfect and subjected to inherent effects including diffraction effects, optical

aberrations, motion of optical components and moving parts, defects in optical imaging systems which have a

significant impact on the shift of pixels and hence pixel misalignment causing a blurred image to appear. This is

further accentuated by mechanical misalignment which defocuses the beam even further. The blurred image

significantly affects the image quality. This is why pixel misalignments are critical. On the Image display program,

the corrected image and uncorrected image with the array of pixel elements is shown so one can see where and

how the pixel misalignments occurred when scanning the sample. To correct image distortion, LabVIEW could

be used to resize the array using the LabVIEW software environment.

The THz system requires optical elements with a high numerical aperture while the ideal optical resolution is

close to the diffraction limit. A standard high NA spherical lens in a THz system exhibits signal attenuation due

to significant thickness. Typically, for converging lenses the attenuation is higher near the optical axis than in the

peripheral regions. This increases the spherical aberrations of the lens. These spherical aberration lead to pixel

misalignment which eventually leads to a blurred image of the sample. [17]

The optical components may truncate the beam at a radius less than 2 beam width parameters, which may cause

undesired diffraction of the beam which eventually cause loss in transmit power from the pump beam from the

THz transmitter horn antenna. If the caging system is not perfectly set up, then it will may cause truncation of

the THz signal beam and aberration effects which will distort the THz field. The beam could also be easily de-

focused. Furthermore, the beam may undergo partial reflections causing it to travel back and forth in the optical

system again which causes loss in optical power in the detector. This may set up a standing THz wave inside the

THz cage system. This goes to show how lenses in the cage system need to be carefully positioned by

adjustments so that the signal at the detector is maximized so that the sample can be positioned at the focus

point. This enables the on axis THz wave to travel through the cage system uninterrupted to avoid truncation or

partial reflection, or spherical aberration effects. The position of the focus is dynamically changing by adjustment

made to the cage system and the so the detector and sample need to be positioned accordingly. To avoid these

effects, the radius the propagating beam at which truncation occurs and subsequently power loss due to an

edge, mirror, and lens in the cage system needs to be investigated. For a horn antenna transmitter feed, the far

field pattern needs to be known as that may avoid truncation in this quasi-optical system. The quasi-optical

system needs to be configured such that coupling of the beam produced by the feed horn antenna feeds it to

the receiver. The component size should be set according to the level of tolerance for beam truncation of the

THz pulse. The set-up of the experiment involving on axis signal beams needs to follow precise geometrical optics

to avoid error. [17]

For a broadband pulse, the width of the illumination spot is highly frequency dependent on the source antenna.

A strong wavelength dependence of the source beam waist exists hence the illuminating beam at the sample in

a Gaussian beam telescopic arrangement is also highly frequency dependent. Depending on the thickness of the

sample, diffraction effects factor in due to the optical path length through sample. It’s important to ensure that

the phase centre of the beam scattered by a sample is positioned at the input focal plane of the second pair of

34

parabolic mirrors so that the image of the sample is still focused onto the detector plane. This is achieved by

taking into consideration the distance to the next focusing element.

CONCLUSION

Unfortunately we were unable to complete the leak detection in pipes using fibre Bragg gratings experiment

and so were not able to gather the results that were required and so had to move on to a different project.

For the leak detection in pipes although we did not gather the full set of results we still gathered data from

changing the pressures on the sensors and were able to examine that as the pressure increased the wavelength

decreased with a linear relationship. Results from the sensors while simulating the leaks were unable to be

gathered because the sensor array broke. This meant that it was not possible to record vibrations using the

sensor array to determine how varying the position of the sensors in the pipe would make a difference to the

measurements recorded.

For the terahertz imaging set up we were able to successfully install and optimise a new lens setup. This allowed

us to successfully image both metallic and organic objects. The images that were obtained had good resolution

that allowed you to be able to see what the objects where even when contained inside other objects.

REFERENCES

1. Wang, D.H.-C., et al., In-pipe leak detection in pressured water pipe networks using fibre optic sensor.

2. Hunaidi, O. and W.T. Chu, Acoustical characteristics of leak signals in plastic water distribution pipes. Applied Acoustics, 1999. 58(3): p. 235-254.

3. Khulief, Y., et al., Acoustic detection of leaks in water pipelines using measurements inside pipe. Journal of Pipeline Systems Engineering and Practice, 2011. 3(2): p. 47-54.

4. Pal, M., N. Dixon, and J. Flint. Detecting & Locating Leaks in Water Distribution Polyethylene Pipes. in Proceedings of the World Congress on Engineering. 2010.

5. Gao, Y., et al., On the selection of acoustic/vibration sensors for leak detection in plastic water pipes. Journal of Sound and Vibration, 2005. 283(3): p. 927-941.

6. Yang, J., et al., Study on an improved acoustic leak detection method for water distribution systems. Urban Water Journal, 2013. 10(2): p. 71-84.

7. Kersey, A.D., et al., Fiber grating sensors. Journal of lightwave technology, 1997. 15(8): p. 1442-1463.

8. Rao, Y.-J., In-fibre Bragg grating sensors. Measurement science and technology, 1997. 8(4): p. 355.

9. Knudsen, H., Study of the Speed of Sound in Pipes and Pulse Reflections for Open and Closed Boundary Conditions and Non-Return Valves. 2008.

10. Sano, Y. and T. Yoshino, Fast optical wavelength interrogator employing arrayed waveguide grating for distributed fiber Bragg grating sensors. Lightwave Technology, Journal of, 2003. 21(1): p. 132-139.

11. Etayo, D., et al. Active THz imaging system to measure water content evolution in leaves. in SPIE Security+ Defence. 2011. International Society for Optics and Photonics.

12. Kitaeva, G.K., Terahertz generation by means of optical lasers. Laser Physics Letters, 2008. 5(8): p. 559.

13. Ward, J.S., et al. Tunable broadband frequency-multiplied terahertz sources. in Infrared, Millimeter and Terahertz Waves, 2008. IRMMW-THz 2008. 33rd International Conference on. 2008. IEEE.

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14. Murakami, H., et al., Scanning laser THz imaging system. Journal of Physics D: Applied Physics, 2014. 47(37): p. 374007.

15. Siegel, P.H., Terahertz technology. IEEE Transactions on microwave theory and techniques, 2002. 50(3): p. 910-928.

16. Tribe, W.R., et al. Hidden object detection: security applications of terahertz technology. in Integrated Optoelectronic Devices 2004. 2004. International Society for Optics and Photonics.

17. Filipovic, D.F., S.S. Gearhart, and G.M. Rebeiz, Double-slot antennas on extended hemispherical and elliptical silicon dielectric lenses. Microwave Theory and Techniques, IEEE Transactions on, 1993. 41(10): p. 1738-1749.

FIGURES

Figure 1

Wang, D.H.-C., et al., In-pipe leak detection in pressured water pipe networks using fibre optic sensor.

Figure 2

Wang, D.H.-C., et al., In-pipe leak detection in pressured water pipe networks using fibre optic sensor.

Figure 3

http://www.ibsenphotonics.com/products/interrogation-monitors/i-mon-oem/i-mon-256-oem

Figure 4

http://www.ibsenphotonics.com/products/interrogation-monitors/i-mon-oem/i-mon-256-oem

Figure 5

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Figure 6

http://www.ibsenphotonics.com/products/interrogation-monitors/i-mon-oem/i-mon-256-oem

Figure 7

http://www.ibsenphotonics.com/products/interrogation-monitors/i-mon-oem/i-mon-256-oem

Figure 8

http://www.ibsenphotonics.com/products/interrogation-monitors/i-mon-oem/i-mon-256-oem

Figure 9

http://www.ibsenphotonics.com/products/interrogation-monitors/i-mon-oem/i-mon-256-oem

Figure 10

Dense light Manual Super luminescent Operational Manual LED source

Figure 11

http://www.ibsenphotonics.com/products/interrogation-monitors/i-mon-oem/i-mon-256-oem

Figure 12

36

Dense light Manual Super luminescent Operational Manual LED source

Figure 13

Wang, D.H.-C., et al., In-pipe leak detection in pressured water pipe networks using fibre optic sensor.

Figure 14

Created on excel

Figure 15

Created on excel

Figure 16

Self created

Figure 17

Self created

Figure 18

Picture taken in lab

Fig 19

CSIRO THz System Operation Manual

Fig 20

CSIRO THz System Operation Manual

Fig 21

CSIRO THz System Operation Manual

Fig 22

CSIRO THz System Operation Manual

Fig 23

Obtained at CSIRO Lindfield

Fig 24

Obtained at CSIRO Lindfield