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High-resolution distributed shape sensing using phase-sensitive optical time-domain reflectometry and multicore fibers

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Optics Express
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In this paper, a highly-sensitive distributed shape sensor based on a multicore fiber (MCF) and phase-sensitive optical time-domain reflectometry (φ-OTDR) is proposed and experimentally demonstrated. The implemented system features a high strain sensitivity (down to ∼0.3 µɛ) over a 24 m-long MCF with a spatial resolution of 10 cm. The results demonstrate good repeatability of the relative fiber curvature and bend orientation measurements. Changes in the fiber shape are successfully retrieved, showing detectable displacements of the free moving fiber end as small as 50 µm over a 60 cm-long fiber. In addition, the proposed technique overcomes cross-sensitivity issues between strain and temperature. To the best of our knowledge, the results presented in this work provide the first demonstration of distributed shape sensing based on φ-OTDR using MCFs. This high-sensitivity technique proves to be a promising approach for a wide range of new applications such as dynamic, long distance and three-dimensional distributed shape sensing.
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Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20763
High-resolution distributed shape sensing using
phase-sensitive optical time-domain
reflectometry and multicore fibers
ŁUKASZ SZOSTKIEWICZ,1,2,4,* MARCELO A. S OTO,1,5 ZHISHENG
YAN G,1ALE JA NDR O DOMINGUEZ-LO PEZ ,2ITXASO PAROLA,2
KRZY SZTOF MARKIEWICZ,2AN NA PYT EL,2,3 AGNIESZKA
KOŁAKOWSKA,2,3 MARE K NAPIERAŁA,2TOMASZ NASIŁOWSKI,2
AND LUC THEVENAZ1
1EPFL Swiss Federal Institute of Technology, Institute of Electrical Engineering, SCI STI LT, Station 11,
CH-1015 Lausanne, Switzerland
2InPhoTech sp. z o.o., ul. Dzika 12/15, 00-172 Warsaw, Poland
3Polish Centre for Photonics and Fibre Optics, Al. Racławickie 8 lok 12, 20-037 Lublin, Poland
4Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
5Permanent address: Department of Electronic Engineering, Universidad Técnica Federico Santa María,
2390123 Valparaíso, Chile
*lszostkiewicz@inphotech.pl
Abstract:
In this paper, a highly-sensitive distributed shape sensor based on a multicore
fiber (MCF) and phase-sensitive optical time-domain reflectometry (
ϕ
-OTDR) is proposed and
experimentally demonstrated. The implemented system features a high strain sensitivity (down to
0.3
µε
) over a 24m-long MCF with a spatial resolution of 10 cm. The results demonstrate good
repeatability of the relative fiber curvature and bend orientation measurements. Changes in the
fiber shape are successfully retrieved, showing detectable displacements of the free moving fiber
end as small as 50
µ
m over a 60cm-long fiber. In addition, the proposed technique overcomes
cross-sensitivity issues between strain and temperature. To the best of our knowledge, the results
presented in this work provide the first demonstration of distributed shape sensing based on
ϕ
-OTDR using MCFs. This high-sensitivity technique proves to be a promising approach for a
wide range of new applications such as dynamic, long distance and three-dimensional distributed
shape sensing.
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Distributed optical fiber sensors (DOFSs) offer the possibility to monitor a variety of parameters
(e.g. strain, temperature, vibration, etc.) continuously along the entire length of an optical fiber
with a very sharp spatial resolution [1]. Due to these unprecedented features, DOFSs are seen to
be the most suitable and promising technology for monitoring large structures using an optical
fiber as they provide a vast number of independent sensing points. The working principle of these
sensors is based on the analysis of the scattered light within the optical fiber due to either Rayleigh,
Brillouin or Raman scattering [2]. Whilst in recent years DOFSs have evolved dramatically,
resulting in an increase in the sensing resolution and a reduction in measurement times [35], the
vast majority of them have been confined to measuring strain and/or temperature profiles. The
main reason for concentrating so much on these two parameters is the relatively low insensitivity
of conventional single-mode optical fibers (ITU-T G.652) to other physical quantities. However,
due to the recent development of specialty optical fibers like few-mode fibers [6], photonic
crystal fibers [7,8] and hollow-core fibers [9], the breadth of potential applications for DOFSs
has got enlarged. The synergy between specialty optical fibers and DOFSs makes it now possible
#366906 https://doi.org/10.1364/OE.27.020763
Journal © 2019 Received 13 May 2019; revised 20 Jun 2019; accepted 28 Jun 2019; published 10 Jul 2019
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20764
to measure parameters that cannot be measured with the use of standard single-mode fibers,
such as pressure sensing [10], axial stress sensing [11], or gas concentration [12]. On the other
hand, multicore fibers (MCFs) were initially developed to face the capacity crunch of the optical
fiber networks based on single-core fibers [13]. The combination of MCFs with mode-division
multiplexing techniques has demonstrated an extraordinary potential to increase the transmission
capacity of optical fiber links [14]. However, due to the unique features of MCFs, they have
also found a niche market in the field of optical fiber sensing. They have been used successfully
as bending and curvature sensors [15,16], and in applications such as accelerometers [17] and
velocity sensors [18]. Nevertheless, one of the most promising sensing applications for MCFs
is the monitoring of the shape of an optical fiber (shape sensing) by analyzing the differential
strain distribution along its different cores. The first demonstration of a time domain analysis
distributed shape sensor on MCFs was recently published by Zhao et al., where the Brillouin
optical time domain analysis (BOTDA) technique was employed to extract the fiber shape [19].
However, other distributed sensing techniques that present a higher sensitivity than BOTDA have
not yet been explored for this application. One of these techniques is the so-called phase-sensitive
optical time domain reflectometry (
ϕ
-OTDR), which has a sensitivity level that is three orders of
magnitude superior to that of BOTDA [20]. It is therefore expected that much more sensitivity to
shape variations can be achieved by performing ϕ-OTDR measurements over MCFs.
In this paper, a novel highly-sensitive distributed shape sensor is proposed based on
ϕ
-OTDR
measurements over a MCF. Making use of the differential strain distribution of three cores of
a MCF, displacement measurements with extremely high precision and high spatial resolution
have now been experimentally demonstrated for the first time, to the best of our knowledge.
Measurements of relative strain and calculations of the absolute curvature and bend orientation
of the fiber are carried out, confirming good repeatability in all cases. Changes in the fiber
shape are calculated and illustrated, showing the capability to detect changes at a sub-millimeter
scale, being as small as 50
µ
m over a 60cm-long fiber span. The results presented in this work
positively contribute to the promising development of distributed curvature and bending sensors
based on
ϕ
-OTDR in MCFs, and pave the way to the implementation of a wide range of new
applications, such as dynamic, long range and three-dimensional distributed shape-sensing.
As of today, long range optical fiber sensors do not allow to perform efficient modal analysis
of long structures like bridges or buildings. Such situation is caused by the fact that one cannot
measure the direction of the deformation with high enough repetition rate in distributed manner.
Technique proposed and described below may be applicable for creating multi km distributed
vibration meter that gives the information not only about the amplitude of vibration but also
about its direction. Full information about movement of the infrastructure is a key for securing
safety of operation.
2. Shape sensing with multicore optical fibers
By measuring simultaneously the strain deviations of several cores within a MCF, whose geometry
is known, it is possible to extract the information about the curvature over each differential section
of the fiber [19]. In this study, a hole-assisted 7-core multicore fiber fabricated by InPhoTech is
used, with a central core and 6 outer cores arranged in a hexagonal array [see Fig. 1(a)]. This
fiber has an outer diameter of 135
µ
m, a core pitch dof 40
µ
m, and each core properties are
in line with ITU-T G.652 recommendation. Any three cores that are not arranged in a straight
line are sufficient to perform the analysis presented here. The three cores selected in this work
and the pitch distance dare depicted in Fig. 1(a). On the other hand, Fig. 1(b) represents an
analytical drawing of the cross section of the MCF in two different scenarios. The bottom
representation corresponds to the original position of the fiber, which is used as a reference for
the rest of the measurements. In this position, the three cores under test (C1, C2 and C3) lie on
the XY plane. The upper drawing represents the MCF subjected to a differential strain over the
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20765
fiber cross-section, as caused by a bending. In this case, the cores lie within a plane tilted by a
certain angle with respect to the reference, and their position is denoted as P1, P2 and P3. Their
coordinates are defined as:
Pi=(d cos θi,d sin θi,εi),(1)
where
θi
represents angles between the i-th core and the x axis, and
εi
represents the strain induced
in the i-th core. The coordinates of the central core position are defined as P0
=(0, 0, εconst.)
,
where
εconst.
is the common strain that all the cores undergo. At this point it is worth mentioning
that
εconst.
effect is the same like temperature effect. Since factor
εconst.
is not influencing both
curvature and bending orientation calculation, one can claim that the measurement is inherently
insensitive to temperature. This stays true if two conditions are fulfilled: all the cores at given
position exhibit the same temperature and all the cores are measured at the same time. In the
same way, one can define the location of a certain point P
=(d cos θb,d sin θb,εb+εconst.)
,
where
θb
represents the bending orientation and
εb=
dk is the strain induced by such bending
at the location of the point P(where k
=1/R
is the curvature associated with a given bending
radius R). Point Pcan be associated to a fictive core positioned exactly in the bending direction.
Fig. 1.
(a) Cross-section of the 7-core MCF used in the experiment. The colored circles
indicate the three cores selected for this analysis: red (bottom right): Core 2; blue (top
left): Core 4; green (top right) Core 5. (b) Analytical drawing of the MCF in two different
scenarios: bottom: origin position with all the cores within the XY plane; top: position
subjected to a bend with the cores displaced within a plane tilted by a certain angle with
respect to the reference position. Points C1, C2, C3 represent the fiber cores coordinates in
fiber cross section (XY plane). Points P0, P1, P2, P3 represent the fiber cores coordinates
(XY plane) and the measured strain value in each core. Vector
®
n
is a normal vector to a
plane fitted to the measured coordinates of P1, P2, P3. Point P represents the coordinates of
a fictive core positioned in the bending direction.
θb
is the bending orientation of the fiber
which is in line with the projection of the ®
nvector on the XY axis.
To calculate the position of point P, a normal vector
®
n=(nx,ny,nz)
is defined from the plane
formed by P1, P2 and P3, satisfying that
®
n=(P2P1)×(P3P1)
. Then, based on the xand y
coordinates of the normal vector ®
n, the bending orientation θbis defined as:
θb=arctan ny
nx
.(2)
The projection of vector
®
n
to XY plane (which is defined by fiber geometry) points at the same
direction as bending orientation
θb
. As the xand ycoordinates of point Pare known (due to
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20766
the known structure of the fiber), as well as the plane in which it is lying (given by the normal
vector
®
n
), the exact position of the point Pcan be determined by knowing the bending orientation.
Hence, the equation of the plane for this point can be defined as:
0=nxd cos θb+nyd sin θb+nzεb.(3)
Then, solving for the only unknown εb, the strain induced by bending can be written as:
εb=nx
nz
d cos θbny
nz
d sin θb,(4)
and the curvature of the fiber can be calculated directly from the strain as:
k=|εb/d|.(5)
Finally, the shape change of the fiber can be retrieved by means of the well-known Frenet-Serret
formulas [21,22]. As mentioned above, the methodology presented in this section is applicable
to any initial choice of three cores, as long as they are not arranged in a straight line within the
geometry of the MCF.
3. Experimental setup
The experimental setup employed in this work is shown in Fig. 2, which corresponds to a classical
high-performance implementation of a
ϕ
-OTDR sensor [20]. In this case, a distributed-feedback
(DFB) laser is used as a light-source, and the wavelength sweeping is carried out by tuning
the bias current of the DFB laser. In a first step, the output pulse is shaped by means of a
Mach-Zehnder electro-optical intensity modulator (EOM), obtaining a probe pulse of
1 ns,
which corresponds to a spatial resolution of 10 cm. The pulse waveform is externally shaped by
an electrical arbitrary waveform generator (AWG). To secure a sufficiently high extinction ratio
(ER) of the probe pulses, a second EOM is employed to gate the pulses, and hence, to further
reduce the out-of-pulse Rayleigh backscattered power (which provides no useful information and
potentially distorts the measurements). Then, the probe pulse power is boosted by means of an
erbium-doped fiber amplifier (EDFA). This amplification stage is followed by a variable optical
attenuator (VOA), which is used to accurately adjust the power launched into the sensing fiber and
to avoid non-linear effects such as modulation instability in the MCF [23]. After passing through
a circulator and before entering the fiber, an optical switch (OS) is inserted to enable comparable
measurements between the cores of interest in an automated manner. A fan-in/fan-out (Fi/o)
device (maximum insertion losses of
1.1 dB for each core) is connected to the output of the
OS, and it serves to couple the light from seven single-mode fibers to each core of the MCF. The
backscattered light within the fiber under test (FUT) comes out from port three of the circulator
and is amplified by means of an EDFA, thus enabling sufficient power to reach the detector. The
amplified spontaneous emission of the EDFA is filtered by a tunable band-pass optical filter
(BPOF), which isolates the signal of interest and limits the sources of noise. A photodiode (PD)
is used as a detector, which features a bandwidth of 3 GHz (enough to perform measurements
with a spatial resolution of 10 cm). As a final step, the electrical signal generated by the PD is
acquired by an oscilloscope with 4 GHz bandwidth.
The arrangement of the displacement setup is illustrated in Fig. 3. As can be seen, the MCF is
fixed to the base at point A, which limits the length of the moving section of the fiber (segment
AB) to
60 cm and ensures that comparable measurements are made. The fiber was placed
in protective tape in an non-twisted state at its whole length. The MCF is also attached to a
computer-controlled translation stage (point B in Fig. 3) elevated 31.3cm from the base. Two
precisely measured physical dimensions (35,5 cm and 12,8cm) indicate the level of initial tension
applied to the fiber. Due to the high sensitivity of the system, the moving stage is set to shift
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20767
Fig. 2.
Experimental setup of the phase-sensitive OTDR. DFB: distributed-feedback laser;
EOM: electro-optical modulator; AWG: arbitrary waveform generator; EDFA: erbium-doped
fiber amplifier; VOA: variable optical attenuator; OS: optical switch; Fi/o: fan-in/fan-out;
MCF: multi-core fiber; BPOF: band-pass optical filter; PD: photodiode.
upwards and downwards by steps of 2 mm, with a total vertical displacement range of 2 cm. The
total fiber length of the MCF is
24 m. Since range limiting factors for
ϕ
-OTDR setup are:
pulse power, extinction ratio of the pulse and loss of the fiber the measurement range can be
easily extended beyond 24 m of length to km range.
Fig. 3.
Displacement setup. The MCF is attached to the base at point A, and from there
60 cm of fiber are suspended in the air up to point B, fixed to a vertical translation stage.
To ensure that the measured traces allows for a sufficient contrast to properly extract the strain
measurements, a high visibility is necessary. The visibility is defined as:
Visibility =Imax Imin
Imax +Imin
,(1)
where
Imax
and
Imin
are respectively the maximum and the minimum intensity of the trace [24].
An example of the measured trace and the calculated visibility is shown in Fig. 4(a), where the
visibility is above 0.7 along the trace. The first section with a higher signal intensity (from 0 to
7 m) corresponds to the optical components used to address each particular core of the MCF.
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20768
An example of the calculated cross-correlation spectrum between two different measurements
corresponding to two different heights (0 and 10 mm) of the moving stage for one core is illustrated
in Fig. 4(b). As can be seen, there is a clearly visible shift (1.15 GHz) of the maximum peak as a
result of the induced strain.
Fig. 4.
(a) Example of the measured time trace for one of the cores of the MCF (blue line)
and the calculated visibility for it (green line). (b) Example of the calculated cross-correlation
spectrum between two different measurements corresponding to two different heights of the
moving stage for one core.
4. Shape sensing results
In order to measure the accumulated strain (
εb
) along the fiber, a series of frequency sweeps were
performed at each vertical position of the fiber (point B in Fig. 3). The frequency of the DFB
laser is swept in steps of 50 MHz, until covering a total frequency scanning range of 13.5 GHz.
Based on the strain sensitivity of silica fibers [20], this scanning frequency range provides a full
dynamic range of 89
µε
. Note that the strain is estimated as the sum of the computed strains
resulting from each increment in vertical position (relative strain values). Figure 5illustrates
the accumulated strain obtained in three of the cores with upward and downward displacements
shown in 3D [Figs. 5(a) and 5(c)] and in a 2D cut for a vertical displacement of 18 mm [Figs. 5(b)
and 5(d)]. As expected, there exists a strong correlation between the results obtained for both
directions of displacements. Upward and downward movement experience different sign of strain
measurement. Such sign change is not visible in Fig. 5(a) and 5(b) because vertical displacement
is referenced only with positive values in respect to the initial position. It can be noted that the
accumulated strain for the three cores is null up to the distance of 23 m, where the fiber is fixed
to the base (point A in Fig. 3). Hence, as expected, no strain variations are measured before this
position. From 23 m to
23.16 m, the Core 2 (red) experiences a positive strain (elongation),
whereas Cores 4 and 5 (blue and green respectively) undergo a negative strain (compression).
At
23.16 m there is a change in the curvature of the fiber (inflection point), and therefore, no
strain or compression is induced in any of the cores at that point. Subsequently, from
23.16 m
to 23.6 m (point B in Fig. 3), Core 2 experiences a negative strain or compression, whilst Cores
4 and 5 are subject to a positive strain or elongation. Interestingly, a symmetrical behavior of
Cores 2 and 4 (red and blue respectively) can clearly be observed in both Figs. 5(b) and 5(d),
from which their opposing locations within the geometry of the MCF can be inferred [see Fig. 1
(a)]. It should be emphasized that the strong correlation between these two graphs reinforces the
confidence in the presented technique and the implemented system.
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20769
Fig. 5.
(a) and (c) Accumulated strain due to vertical displacement, estimated as the
summation of the computed strain for each pair of vertical positions for three cores of
the fiber. (b) and (d) 2D view of the accumulated strain as a function of the fiber length
for a vertical displacement of 18 mm. In the upward displacement [(a) and (b)] the
first reference sweep is carried out at the lowest point (set at 0 mm of relative vertical
displacement) and consecutive measurements are obtained with upward displacements. In
the downward displacement [(c) and (d)] the first measurement is obtained at the highest
position (
+
20 mm of relative vertical displacement), while measurements are obtained with
downward displacements.
From the strain (
εb
) values obtained for each core, and making use of the equations presented
in section 2, the curvature (k) and the bend orientation (
θb
) of the fiber can be calculated along
its entire length. Figure 6(a) shows the retrieved curvature change for several positions of the
translation stage, beginning from the lowest vertical displacement (defined as 0 mm of relative
displacement), going upward to the highest position (
+
20 mm) and returning downward through
the same steps to the starting point. As expected, the obtained curvatures show strong repeatability
in the upward and downward directions, though an increment in the error can be observed as the
measurements advance. Curvature can have negative values starting from the inflection point if
one is not considering the angle at which such curvature is changing. Absolute curvature change
combined with angle measurement gives complete information about the relative shape. This is
because the results are based on cumulative measurements, and due to the intrinsically-static
acquisition time (each frequency scanning requires 270 steps), an incremental error is expected
toward the end of the set of measurements. This error was quantified from the difference of the
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20770
upward and downward pair of measurements at a fixed fiber length of 23.25 m, and the results
are illustrated in Fig. 6(b) as function of the measurement iterations. As can be seen, the greatest
error is obtained for the last iteration, which corresponds to a vertical displacement of 2 mm in
downward direction.
Fig. 6.
(a) Measured relative curvature as a function of the fiber length for several positions
of the moving stage, starting at the bottom (0mm elevation), shifting upwards to 20 mm
(continuous lines), and going back down to the original position (dotted lines). (b) Estimated
curvature error as a function of the measurement iterations (the last iteration corresponds to
the 2 mm vertical displacement in downward direction. This error was quantified from the
difference of the upward and downward pair of measurements at a fixed fiber length of 23.25
m) .
On the other hand, Fig. 7similarly depicts the calculated bend orientation as a function of the
fiber length for the same steps of the translation stage. As can be seen, the orientation of the
piece of fiber that is lying on the base, i.e., from 22.8 m to
22.95 m (point A in Fig. 3), remains
Fig. 7.
Bend orientation as a function of the fiber length for several relative vertical positions
of the moving stage, starting at 0 mm, shifting upwards to 20mm (continuous lines), and
going back down to the original position (dotted lines).
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20771
unchanged over the whole set of measurements. This result is expected as this fiber segment
is fixed to the base, and it is not exposed to any change. Beyond
22.95 m from the far end
of the fiber, the computed bend orientation of the fiber appears to be random, showing a strong
change in orientation before the curvature sign change (inflection point at
23.16 m), and later a
smoother shift until the fiber end. However, it can be seen that the pair of results obtained for the
same vertical position show a similar profile, which proves the repeatability of the system. An
exception can be observed in the last measurement referring to a relative vertical displacement
of 4 mm in the downward direction (4 mm in Fig. 7), which corresponds to the position with
the highest cumulative error. This error is particularly clear after the curvature sign change,
where several spurious peaks appeared. The biggest curvature changes seen from point 23.15
correspond to the well-defined constant angle measurement. The discontinuities seen before this
point are in line with what would be expected in an angle change graph and whilst this looks like
noise, in fact it is not, as illustrated by the repetitive nature of the measurements. Rapid changes
in fiber bending orientation seen from
22.95 m to
23.1 m correspond to fast changes in
curvature measurements form Fig. 6a). Such measurement can be explained by the influence of
protective tape mechanical properties. Well defined curvature measurements correspond to well
defined bend orientation. Such areas have the biggest impact on end shape change calculation.
Finally, the changes of the fiber shape are calculated by means of the Frenet-Serret formulas.
The results obtained for each height-position are illustrated in Fig. 8as a 3D graph and for
two different perspectives. The offset axis represents a change in the fiber-end-position in an
additional dimension caused by instabilities in the setup (for an ideal vertical translation of the
Fig. 8.
(a) 3D illustration of the retrieved shape of the fiber for different vertical positions in
steps of 2 mm (positive sign: upward displacement; negative sign: downward displacement).
(b) and (c) shape of the fiber as a function of the vertical displacement and the offset
respectively. The offset axis corresponds to a change in the fiber-end-position in an additional
dimension caused by instabilities in the setup.
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20772
fiber, the change in this axis would be null). The original position of the fiber (0 mm) is depicted
as a blue line over the AB-segment axis, and it is used as the reference for the following shapes
of the fiber. As can be seen, the obtained fiber shapes resemble successfully the changes in form
applied to the fiber by adjusting its vertical position, though a cumulative error is still present
in the last measurement (4 mm in downward direction). These results demonstrate the great
sensitivity of the proposed technique, verifying that changes as small as 0.05 mm in the position
of the far end of the fiber can be tracked efficiently over a 60 cm-long fiber. These small errors in
the retrieved positions are mainly due to the small instabilities caused by the movement of the
translation stage in a non-vertical direction, and yet, they are detected by this highly-sensitive
system.
It must be highlighted that it is straightforward to overcome strain-temperature cross-sensitivity
issues affecting
ϕ
-OTDR measurements with the proposed technique. Indeed, while different
strain values are expected to be measured in every core of the MCF when changing the shape
of the fiber, any temperature change can be simultaneously measured by all fiber cores. By
detecting the common variations of the cross-correlation spectral peaks of each core used in the
measurements, temperature changes can be easily identified. Additionally, it must be taken into
account that the central core of the MCF is in a neutral position, which is essentially affected
by the net longitudinal strain variations (not by the differential strain exploited here for shape
sensing) and temperature variations, which can be used to compensate the relative strain variations
measured along the side cores.
5. Conclusion
A highly-sensitive distributed shape sensor based on
ϕ
-OTDR in a MCF has been proposed and
validated, for the first time to the best of our knowledge. A high precision setup for differential
strain distribution measurements has been implemented demonstrating a high strain sensitivity
(down to
0.3
µε
) over a 24m-long MCF with a spatial resolution of 10 cm. Experimental
calculations of the cumulated strain, curvature and bend orientation of the fiber have been
carried out, confirming a good repeatability of the measurements. In addition, changes in the
fiber shape have been successfully retrieved from the analysis of just three cores of the fiber.
The great sensitivity of the proposed system has been demonstrated by detecting submillimeter
changes in the position of the fiber end (0.05 mm changes in a 60 cm-long fiber). In addition,
the proposed scheme avoids the commonly faced issues of cross-sensitivity between strain and
temperature, due to its differential working principle. The results presented here illustrate the
promising capabilities of the use of specialty optical fibers for distributed sensing, establishing
the foundations of a broad range of interesting new applications, such as dynamic and 3D shape
sensing. Since the proposed technique is based on conventional
ϕ
-OTDR measurements, the
method can be straightforwardly applied for long-range distributed shape sensing over tens of
kilometers.
Funding
Fundacja na rzecz Nauki Polskiej (FNP) (NODUS, TEAMTECH); Narodowe Centrum Badań i
Rozwoju (NCBR) (LIDER/103/L-6/14/NCBR/2015).
References
1. X. Bao and L. Chen, “Recent Progress in Distributed Fiber Optic Sensors,” Sensors 12(7), 8601–8639 (2012).
2. A. H. Hartog, An Introduction to Distributed Optical Fibre Sensors (Taylor & Francis Group, 2017).
3.
Z. Yang, M. A. Soto, D. M. Chow, P. Ray, and L. Thevenaz, “Brillouin Distributed Optical Fiber Sensor Based on a
Closed-Loop Configuration,” J. Lightwave Technol. 36(5), 1239–1248 (2018).
4.
A. Dominguez-Lopez, M. A. Soto, S. Martin-Lopez, L. Thevenaz, and M. Gonzalez-Herraez, “Resolving 1 million
sensing points in an optimized differential time-domain Brillouin sensor,” Opt. Lett. 42(10), 1903 (2017).
Research Article Vol. 27, No. 15 / 22 July 2019 / Optics Express 20773
5.
I. Steinberg, L. Shiloh, H. Gabai, and A. Eyal, “Over 100 km long ultra-sensitive dynamic sensing via Gated-OFDR,”
Proc. SPIE-24th Int. Conf. Opt. Fibre Sensors 9634, 1–4 (2015).
6.
A. Li, Y. Wang, Q. Hu, and W. Shieh, “Few-mode fiber based optical sensors,” Opt. Express
23
(2), 1139–1150
(2015).
7.
L. Zou, X. Bao, S. Afshar V, and L. Chen, “Dependence of the Brillouin frequency shift on strain and temperature in
a photonic crystal fiber,” Opt. Lett. 29(13), 1485–1487 (2004).
8.
J. Villatoro, V. Finazzi, V. P. Minkovich, V. Pruneri, G. Badenes, and J. Villatoro, “Temperature-insensitive photonic
crystal fiber interferometer for absolute strain sensing,” Appl. Phys. Lett. 91(9), 091109 (2007).
9.
Y. Lin, W. Jin, F. Yang, Y. Tan, and H. L. Ho, “Performance optimization of hollow-core fiber photothermal gas
sensors,” Opt. Lett. 42(22), 4712–4715 (2017).
10.
L. Zhang, Z. Yang, Ł Szostkiewicz, K. Markiewicz, T. Nasilowski, and L. Thévenaz, “Fully distributed pressure
sensing with ultra-high-sensitivity using side-hole fibers,” Proc. 26th Int. Conf. Opt. Fiber Sensors, 1–4 (2018).
11.
B. De Pauw, S. Goossens, T. Geernaert, D. Habas, H. Thienpont, and F. Berghmans, “Fibre bragg gratings in
embedded microstructured optical fibres allow distinguishing between symmetric and anti-symmetric lamb waves in
carbon fibre reinforced composites,” Sensors 17(9), 1948 (2017).
12.
Y. Lin, F. Liu, X. He, W. Jin, M. Zhang, F. Yang, H. L. Ho, Y. Tan, and L. Gu, “Distributed gas sensing with optical
fibre photothermal interferometry,” Opt. Express 25(25), 31568–31585 (2017).
13.
A. Ziolowicz, M. Szymanski, L. Szostkiewicz, T. Tenderenda, M. Napierala, M. Murawski, Z. Holdynski, L.
Ostrowski, P. Mergo, K. Poturaj, M. Makara, M. Slowikowski, K. Pawlik, T. Stanczyk, K. Stepien, K. Wysokinski, M.
Broczkowska, and T. Nasilowski, “Hole-assisted multicore optical fiber for next generation telecom transmission
systems,” Appl. Phys. Lett. 105(8), 081106 (2014).
14.
Y. Kokubun and M. Koshiba, “Novel multi-core fibers for mode division multiplexing: Proposal and design principle,”
IEICE Electron. Express 6(8), 522–528 (2009).
15.
G. M. H. Flockhart, W. N. MacPherson, J. S. Barton, J. D. C. Jones, L. Zhang, and I. Bennion, “Two-axis bend
measurement with Bragg gratings in multicore optical fiber,” Opt. Lett. 28(6), 387–389 (2003).
16.
L. Yuan, J. Yang, Z. Liu, and J. Sun, “In-fiber integrated Michelson interferometer,” Opt. Lett.
31
(18), 2692–2694
(2006).
17.
A. Fender, W. N. MacPherson, R. R. J. Maier, J. S. Barton, D. S. George, R. I. Howden, G. W. Smith, B. J. S. Jones,
S. McCulloch, X. Chen, R. Suo, L. Zhang, and I. Bennion, “Two-axis accelerometer based on multicore fibre Bragg
gratings,” IEEE Sens. J. 8(7), 1292–1298 (2008).
18.
L. Yuan, J. Yang, and Z. Liu, “A compact fiber-optic flow velocity sensor based on a twin-core fiber Michelson
interferometer,” IEEE Sens. J. 8(7), 1114–1117 (2008).
19.
Z. Zhao, M. A. Soto, M. Tang, and L. Thévenaz, “Distributed shape sensing using Brillouin scattering in multi-core
fibers,” Opt. Express 24(22), 25211–25222 (2016).
20.
Y. Koyamada, M. Imahama, K. Kubota, and K. Hogari, “Fiber-optic distributed strain and temperature sensing with
very high measurand resolution over long range using coherent OTDR,” J. Lightwave Technol.
27
(9), 1142–1146
(2009).
21. M. P. Do Carmo, Differential Geometry of Curves and Surfaces (Prentice-Hall, Inc, 1976).
22.
J. P. Moore and M. D. Rogge, “Shape sensing using multi-core fiber optic cable and parametric curve solutions,” Opt.
Express 20(3), 2967–2973 (2012).
23. G. P. Agrawal, Nonlinear Fiber Optics (Elsevier Inc., 2007).
24.
H. F. Martins, S. Martin-Lopez, P. Corredera, M. L. Filograno, O. Frazao, and M. Gonzalez-Herraez, “Coherent noise
reduction in high visibility phase-sensitive optical time domain reflectometer for distributed sensing of ultrasonic
waves,” J. Lightwave Technol. 31(23), 3631–3637 (2013).
... By measuring the strain distribution of the sensing fiber and processed with shape reconstruction algorithm, the shape sensing can be realized [2,3]. Several shape sensing methods were proposed, which are based on phase-sensitive optical time domain reflectometry (phase-OTDR) [4], Brillouin optical time-domain analysis (BOTDA) [5], Brillouin optical time domain reflectometry (BOTDR) [6], and fiber Bragg grating (FBG) [7][8][9][10]. ...
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Book
This book explains physical principles, unique benefits, broad categories, implementation aspects, and performance criteria of distributed optical fiber sensors (DOFS). For each kind of sensor, the book highlights industrial applications, which range from oil and gas production to power line monitoring, plant and process engineering, environmental monitoring, industrial fire and leakage detection, and so on. The text also includes a discussion of such key areas as backscattering, launched power limitations, and receiver sensitivity, as well as a concise historical account of the field’s development. Note from the author: I have had several requests for a full-text version: however, the copyright belongs to the publisher so I cannot provide this. However, the book may be obtained from https://www.routledge.com/An-Introduction-to-Distributed-Optical-Fibre-Sensors/Hartog/p/book/9781138082694 and from a number of bookshops.