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Coherent optical frequency domain reflectometry for interrogation of bend-based fiber optic hydrocarbon sensors
Optical Fiber Technology 10 (2004) 79–90 www.elsevier.com/locate/yofte
Coherent optical frequency domain reflectometry for interrogation of bend-based fiber optic hydrocarbon sensors R.M. López,a,∗ V.V. Spirin,a,∗ M.G. Shlyagin,a S.V. Miridonov,a G. Beltrán,b E.A. Kuzin,b and A. Márquez Lucero c a División de Física Aplicada, CICESE, A.P. 2732, Ensenada, B.C., Mexico b INAOE, A.P. 51 y. 216, 7200 Puebla, Mexico c CIMAV, Complejo Industrial Chihuahua, CP. 31109, Chihuahua, Mexico
Received 19 October 2001; revised 28 July 2003
Abstract The paper presents distributed fiber optic bending sensor for petroleum hydrocarbon leak detection based on coherent optical frequency domain reflectometry (C-OFDR) technique. In order to introduce bending losses a sensitive polymer, which reversibly swells under hydrocarbon influence is employed. In this work we used lumped reflectors, namely fiber Bragg gratings, placed between distributed sensitive elements. Design of proposed sensor utilizes the principle of distributed detection with section localization (DDSL) of perturbation. Analysis of signal-to-noise ratio (SNR) for multireflectors system was performed. We have demonstrated that the C-OFDR technique with bending sensor is capable to detect hydrocarbon presence within a few minutes for 20-cm perturbation-length with spatial resolution about 0.5 m for strong perturbation. 2003 Elsevier Inc. All rights reserved. Keywords: Fiber optic distributed hydrocarbon sensor; Bragg grating; C-OFDR
1. Introduction Microbend and macrobend-based fiber optic sensors [1] are very attractive techniques for the distributed measurement of the pressure, temperature, displacement, etc., where the measurand can be associated with a periodic deformation of the fiber [2]. These techniques * Corresponding authors.
E-mail addresses: [email protected] (R.M. López), [email protected] (V.V. Spirin). 1068-5200/$ – see front matter 2003 Elsevier Inc. All rights reserved. doi:10.1016/j.yofte.2003.09.003
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may be extended to the fully distributed sensing of chemical agents, such as hydrocarbon, by using a special polymer, which bends the test-fiber in response to hydrocarbon influence [3–5]. As well known, the fiber optical sensors are very promising for using in hazard conditions due to its electrical and fire immunity. In this paper, we utilize distributed bend-based fiber optic sensor for hydrocarbon detection. Proposed technique is preferably oriented on the detection and localization of the hydrocarbon leakage that may lead to a significant environmental pollution. The perturbed region in distributed fiber optic loss sensors is usually localized by means of optical time-domain reflectometry (OTDR) [6]. As an alternatives to the standard OTDR a number of different measurement techniques, such as coherent optical frequency domain reflectometry C-OFDR [7–10], incoherent optical frequency domain reflectometry (I-OFDR) [11–13], and transmission-reflection analysis (TRA) [14,15] had been proposed. In comparison with the traditional OTDR technique the alternative techniques demonstrate set of advantages as well as some disadvantages. In this work for the hydrocarbon leak detection and localization we use coherent optical frequency domain reflectometry technique. C-OFDR technique allows avoiding “dead zone” problem, which is inherent in OTDR; it shows extremely high resolution, high sensitivity and potentially has low cost [7–10]. The paper presents the result of the experimental investigation of distributed hydrocarbon sensor based on C-OFDR technique with lumped reflectors placed along the test fiber. Analysis of the noise properties is also performed for such kind of systems.
2. Principle of operation The C-OFDR technique is based on an analysis of the beat signal generated by optical interference between a reference beam reflected from a fixed mirror and a signal beam coming from the test fiber when the optical frequency of the light source is swept. The beat frequency is proportional to the distance along the fiber if the optical frequency varies linearly with respect to time. The amplitude of the interference signal depends on intensity of backreflected light and light losses in the test fiber. Nevertheless, dependence of the interference signal on the beat frequency or so-called beat spectrum, represents the distribution of the backscattered optical power along the test fiber and can be used for detection of loss induced perturbations. Proposed sensor for hydrocarbon leak detection comprises of distributed sensitive elements, which induce additional losses in the test fiber in hydrocarbon presence, and Bragg gratings written in the core of the test fiber between the sensitive elements. Fiber optic Bragg gratings significantly increase the signal level allowing to eliminate any averaging procedure. Furthermore, the lumped reflectors are placed at fixed positions along the test fiber that allows to localize the perturbation region. For the detection and localization of the hydrocarbon presence with proposed sensor, the change of the beat spectrum was utilized. The perturbation manifests itself as decreasing of the peak signals for the gratings which was placed behind the loss region. Typical beat spectrum for 3 Bragg gratings separated by 12 m-length sensitive elements for 50 Hz sweep modulation frequency when all peaks from the gratings are clearly resolved is shown in
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Fig. 1. Beat spectrum (a) without gasoline influence, (b) thirty minutes under gasoline influence between first and second gratings, and (c) forty minutes under gasoline influence.
Fig. 1. Under the hydrocarbon influence between first and second gratings the value of beat signal for two last gratings significantly decrease due to an additional bending losses induced in the section between gratings. The position of the first downwarded peak allows to localize the perturbation with accuracy equal to the distance between adjacent gratings. For the strong perturbation that decreased the fiber transmission by more than 20 dB the change of the resulting beat spectrum can be interpreted as shift of the trailing edge of the beat spectrum (see the difference between curves (a) and (c) in Fig. 1). The operation mode of the proposed sensor can be characterized as distributed detection with section localization (DDSL) of the perturbation. Note, that proposed method can be used even if the reflectors are placed so closely, that corresponding peaks cannot be resolved as individual peaks.
3. Experimental results 3.1. Measurement of bending losses induced by swellable polymer First of all we estimate the value of additional bending losses that can be induced by swellable polymer in hydrocarbon presence. A white butyl rubber was used as the sensitive polymer in the DDSL hydrocarbon sensor. This material has good aging properties at elevated temperatures, and good chemical stability. It also resists weathering, sunlight, ozone, mineral acids, oxygenated solvents (ketones and alcohols), and water absorption [16,17]. Butyl rubber swells under hydrocarbon influence without dissolution and
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significant change of its mechanical properties. The swelling of the polymer can be readily converted to a mechanical response. Our study shows that butyl rubber can increase its volume for more than 2 times under gasoline influence [15,18]. Furthermore, its behavior is reversible, i.e., the white butyl rubber can be used over multiple wet-dry cycles. In our experiment, we tested the sensor only under gasoline influence, but qualitatively the same swelling behavior butyl rubber shows in a range of hydrocarbon fuels [4]. Since the chemical and climatic properties of the sensitive element mainly define the corresponding properties of the sensor, we expect to achieve good climatic performance of the proposed sensor. In our sensor single mode SMF-28 optical fiber and the swellable polymer were coupled mechanically together by soft wire winded around them (see Fig. 1). The fiber was placed inside especially-shaped small groove in the polymer that allows to avoid initial losses, but does not significantly increase the response time of sensor. Standard experimental setup was used for the measurement of the transmission of proposed sensor. To study the sensor response, 20- and 40-cm length of sensitive element were placed inside a vessel filled by gasoline. Under the gasoline influence butyl rubber swells and bends the fiber that changes the transmission of the test fiber. Figure 2 shows the change of transmission of the test fiber during wet-drying cycle. As we can see, losses up to 25 dB can be induced under gasoline influence even for 20-cm perturbation length. Our previous study shows that the biggest losses at fixed time can be induced for the wirewinding period approximately equal to 5–10 mm for both single and multimode fibers [3].
Fig. 2. Evolution of transmission of the test fiber during wet-drying cycle.
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Fig. 3. Experimental setup for DDSL hydrocarbon sensor testing.
3.2. Interrogation of bending sensors Experimental setup for DDSL hydrocarbon sensor testing is shown in Fig. 3. The light emitted from New Focus 6262 tunable laser operating at a wavelength about 1534.5 nm with the line width v less than 300 kHz was launched into the test fiber through a 3-dB coupler. The launched optical power was about 500 µW. An optical isolator was used to prevent any influence on the laser from a backreflected light. The backreflected light from the test fiber passed back through 3-dB coupler and mixed with the reference beam by means of 10/90 coupler. Photo detector New Focus 1811 was used for the signal measurement. The beat component of the photo current was analyzed by an electrical spectrum analyzer with a resolution about 100 kHz. The optical frequency of the laser was swept by variation of the cavity length of the laser. For this purpose, a triangular wave voltage was applied to a piezoelectric transducer which holds one laser mirror. As result, the laser wavelength was swept linearly inside the 10 GHz interval (see Fig. 3) with a modulation frequency up to 200 Hz and with optical frequency sweep rate up to 4 THz/s. The sensor is composed of three distributed sensitive elements with identical length equal to 12 m and three Bragg gratings placed at the end of each sensitive length. The Bragg gratings have been written in the core of the single-mode fiber by using a phase mask technique and fourth harmonic of Q-switched Nd:YAG laser at the wavelength of 266 nm. The gratings had a length about 1 mm each, and Bragg wavelength equal to 1535 nm. All gratings had a reflectivity about (2 or 3%), and reflection spectrum bandwidth about 0.3 nm. To study sensor response we placed 20-cm length of second sensitive element inside the straight narrow vessel filled by gasoline. Under the gasoline influence the polymer swells inducing the bending losses. It leads to decrease of the beat signals from second and third Bragg gratings. After 40 min the gasoline was removed from the vessel and the sensor was left for drying. Figure 4 shows dependencies of beat signals for three Bragg
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Fig. 4. Dependence of beat signal of Bragg gratings on time. Gasoline influence between 1st and 2nd gratings.
gratings versus time during wet-drying cycle. All beat signals return back to their initial state approximately at 200 min. Note that under gasoline influence a small variation of the beat signal from the first grating also takes place. We attribute this variation with the uncontrolled change of the state of polarization (SOP) of reflected light [19,20]. The gasoline presence can be detected when the level of beat signal decreases for a value, which exceeds the level of variations of signal. In the experiment this variation does not exceed 5 dB during wet-drying cycle (see the signal for the first Bragg grating in Fig. 4). Therefore, in the experiment we can clearly detect the gasoline presence within 8 min, because after this time the beat signal of second and third gratings decrease for more than 5 dB. The time response of the sensor depends on the length of the sensitive element under the gasoline influence If the length is greater, the response is faster (see Fig. 2). Moreover, the response time of the sensor can be significantly improved using optimal design of the sensitive element and eliminating the SOP instability Beat spectrum demonstrates qualitatively the same behavior when the gasoline effects on different sensitive elements of the DDSL sensor. Note that the SOP instability can be eliminated by using the polarization diversity receivers, or polarization average procedure [19]. Figure 5 shows the dependence of trailing edge shift versus a distance between gratings for strong losses and 50 Hz sweep modulation frequency. All data was recorded after 40 min of gasoline influence for different distances between gratings. Shift of trailing edge depends linearly on a distance between gratings. Figure 5 also demonstrates the shift of trailing edge of beat spectrum after 40 min of gasoline influence between two gratings separated by 1.5 m for 50 Hz sweep modulation frequency. As we can see, by measuring the shift of trailing edge of beat spectrum for strong perturbations we can localize the perturbation even if we cannot resolve the signals from adjacent gratings. As a rule, we measure the
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Fig. 5. Dependence of the shift of trailing edge of beat spectrum versus distance between gratings. (a) Shift of trailing edge of beat spectrum after 40-min of gasoline influence between two gratings separated by 1.5 m.
shift at half-level of peak value, but the value of this shift nearly the same (with accuracy about 10%) inside interval (0.2 to 0.7) of peak value of the signal (see Fig. 5a). The maximum length of the conventional C-OFDR based sensors is limited by the coherence length of used laser [8,9]. The coherence length of tunable New Focus 6262 laser is equal to 500 m. That gives the maximum length of the sensor equal to 250 m. However, decay and broadening of the detected peaks due to the sweep nonlinearity [20] reduce the maximum detectable range of the sensor to 150–180 m. Note, that using C-OFDR with so called phase-decorrelated reflected and reference lightwave [9] the range limitation imposed by the source coherence length can be coped. For an ideal optical source with zero linewidth the spatial resolution limit z = Vg /2B where Vg is group velocity of the light into the fiber and B is frequency-sweep span. A full sweep of 10 GHz limits the resolution to approximately 1 cm. However, in the real C-OFDR systems the spatial resolution limit is restricted by light source and receiver bandwidths [20]. Additional broadening of the reflection peak in our experiment was caused by intensity modulation of the light reflected from the spectral-selective Bragg gratings during the laser frequency-sweep and SOP instability. Nonlinearity in the optical frequency sweep will impose further worsening of the resolution, because the beat frequency corresponding to a given reflection peak varies during the data acquisition. The sweep nonlinearity is the most important limiting factor in the resolution [20]. As discussed above, the strong perturbation can be localized with proposed sensor by measuring of the shift of the trailing edge of beat spectrum. Therefore the random variation of the trailing edge gives us the real resolution limit for the strong perturbation. Experimental measurements show that the maximum random variation of the trailing edge shift
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corresponds to the maximum variation of the distance equal to ±0.3 m near the source end of the test fiber, and equal to ±0.5 m for the grating located at 100 m from the source. Note, that approximately the same spatial resolution can be obtained for relatively weak perturbations that decreased the fiber transmission by more than 5–10 dB.
4. Multiple reflections influence on signal-to-noise ratio As well known, the lumped reflectors significantly increase the signal strength but on other hand the noise originated due to multiple reflections from such reflectors can also restrict the performance of DDSL sensors. Below we analyze the influence of multiple reflections on the signal-to-noise ratio (SNR) for DDSL sensors. Let us consider the DDSL sensor with length L, which consists of a series of n independent lumped reflectors with identical reflectivity r, separated by equal distances (see Fig. 6). In this example, we assume that the signal is produced due to reflection from the last nth reflector at the end of fiber. The total noise, due to multiple reflections, consists of the components from 3, 5 . . . up to (2n − 3) reflections (see Appendix A). If we consider 3-reflection component only in the noise and neglect other components from more than 3 reflections, we obtain the upper limit for SNR as follows (see Appendix A) mS mN3 + PNP h mP0 r(1 − r)2(n−1) e−2αL = , (1) 0.5mP0 e−2αL r 3 (1 − r)2n−4 (n − 1)(n − 2) + PNP h √ √ where PNP h = NEP B, NEP is noise-equivalent power equal to 2.5 pW/ Hz for photodetector New Focus 1811, B = 100 kHz, m is a ramification coefficient equal to 0.45 for couplers used in the experiment, P0 = 500 µW, α = 0.19 dB/km, and L = 36 m. SNRup =
Fig. 6. (a) Schematic representation of the DDSL sensor. (b) Graph for calculation of number of paths for noise components.
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Fig. 7. Upper and lower SNR limits (a) for 5 reflectors and (b) for 30 reflectors.
To calculate the total noise power we need to summarize the noise components from all possible reflections: M = 2k + 1, where k = 1, . . . , n − 2. Taking into account the maximum number of combinations with M reflections Amax M (see Appendix A) we can find the lower limit for SNR: SNRlow =
0.5mP0 e
n−2 −2αL
k=1 r
mP0 r(1 − r)2(n−1)e−2αL 2k+1 (1 − r)2(n−k−1)
nC2(k−1) (n − 1)(n − 2) + PNP h
. (2)
Figure 7a presents the calculated SNR upper and lower limits versus reflection coefficient r for 4 sensitive elements separated by lumped reflectors. The upper and lower limits practically coincide for the reflectivity r below 0.03. As it follows from the data presented in Fig. 7a, for the lumped reflectors with the reflectivity about (2–3%), as was in our experiments, we can neglect the noise produced by multiple reflections. Nevertheless, with increasing the number of the sensitive elements, multiple reflections can significantly reduce the SNR. Figure 7b shows the lower and upper SNR limits versus reflection coefficient r for 30 lumped reflectors. The real SNR lies between these limits. For example, in order to obtain the SNR better than 3, the reflectivity of lumped reflectors must be less than 2.5%. Note that the same signal-to-noise analysis can be applied for the systems with lumped reflectors based on optical time domain reflectometry (OTDR), because only multireflection noise components with total path equal to signal path can reach the detector simultaneously with the signal.
5. Conclusions We have presented the operation of a distributed fiber optic sensor for hydrocarbon leak detection based on swellable polymer, which induce additional bending losses on the test fiber under hydrocarbon influence. Proposed sensor comprises distributed sensitive elements and Bragg gratings placed between them. C-OFDR technique was used for the bending sensors interrogation. The proposed method of measurement realizes distributed
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detection with section localization of the perturbation. The swelling of the 20-cm length of the sensitive polymer, which was used in the sensor, induced the additional losses up to 25 dB under gasoline influence. We have analyzed the influence of multiple reflections on the SNR of DDSL sensors and determined the SNR for any possible number of lumped reflectors with arbitrary reflectivity. It was shown that the proposed sensor allows to detect the gasoline presence within 8 min for 20-cm perturbation-length, and to localize strong perturbation with the accuracy about 0.5 m.
Acknowledgments We gratefully acknowledge financial support through Grant 32208E from Consejo Nacional de Ciencia y Tecnología, México. The authors would like to thank M.S. Miguel Farfán for technical help in the experiment. Appendix A. Signal to noise analysis Figure 6a presents the DDSL sensor, which consists of a series of n independent lumped reflectors with identical reflectivity r, separated by equal distances. Let us suppose that the signal is produced by the reflection from the last nth lumped reflector placed at the end of test fiber. The power of the signal S can be written as S = P0 r(1 − r)2(n−1)e−2αL ,
(A.1)
where P0 is launched into the test fiber optical power, α is loss coefficient in the test fiber, and L is its length. We consider that the noise is produced by only multiple reflections from the mirrors. In our analysis, we must take into account only those multiple reflections, which have total path 2L, since only these components produce the noise at the same beat frequency as the signal. Without loss of generality, we can assume that all distances between mirrors are equal to 1. Let us estimate the number of different paths for noise components with the total lengths equal to the signal path 2(n − 1) (see Fig. 6a). The number of reflections must be odd, because the noise components must return back, like the signal. The maximum number of reflections with total path 2(n − 1) is equal to (2n − 3). It takes place when light consequently reflects (2n − 3) times between the second and first mirrors only. First of all, let us consider the noise produced by only 3 reflections. The number of different paths in this case can be calculated using the graph presented in Fig. 6b. This figure shows all possible paths with 3 reflections when the first reflection occurs at (n−1)th mirror. As we can see, the total number of such combinations is (n−2). If the first reflection is from (n − 2)th mirror, there are only (n − 3) different possibilities to collect a total path equal to 2(n − 1) after three reflections. Furthermore, if the first reflection occurs at the second mirror, there is only one possible way to collect a total path equal to 2(n − 1). This case is marked as doted line in Fig. 6b. So, the total number of different paths with 3 reflections A3 is given by sum of arithmetic series: (n − 1)(n − 2) . (A.2) A3 = (n − 2) + (n − 3) + · · · + 1 = 2
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The calculation of the total number of different paths for general case with M reflections where M > 3, is complicated. Nevertheless we can easy find the upper limit of this total number. Indeed, 5 reflections can be considered as consequence of 2 and 3 reflections. The number of all possible paths with 2 reflections, without any restriction for a total collected path length is equal to number of combinations of 2 objects from a group of n objects n C2 . This value gives us the absolute maximum for the number of possible paths with 2 reflections. The number of different paths for remaining 3 reflections is less than (n − 1)(n − 2)/2, since we still gather same path length during 2 initial reflections and thereby, we must collect the path length less than 2(n − 1) during the last 3 reflections. Therefore, the number of different paths with 5 reflections is given by (n − 1)(n − 2) , (A.3) 2 and for M 3 reflections: (n − 1)(n − 2) AM nCM−3 = Amax (A.4) M , 2 where n CM−3 is number of combinations of M − 3 objects from a group of n objects. The power of the noise component suffering M reflections and having the same path as the signal can be written in the following form A5 < nC2
NM = P0 r M (1 − r)2n−1−M AM e−2αL ,
(A.5)
where AM is the number of different paths having the total length equal to 2L.
References [1] D.A. Nolan, P.E. Blaszyk, E. Udd, Optical fibres, in: Fibre Optic Sensor: An Introduction for Engineers and Scientists, Wiley, New York, 1991. [2] G.L. Mitchell, Intensity-based and Fabry–Perot interferometer sensors, in: Fibre Optic Sensor: An Introduction for Engineers and Scientists, Wiley, New York, 1991. [3] G. Beltran-Perez, E.A. Kuzin, J. Leon-Baez, R. Lopez, V.V. Spirin, A. Marquez-Lucero, Fiber bend losses produced by soft and swellable materials for hydrocarbon detection, Opt. Commun. 204 (2002) 145–150. [4] A. MacLean, C. Moran, W. Johnstone, B. Culshaw, D. Marsh, G. Andrews, A distributed fiber optic sensor for liquid hydrocarbon detection, SPIE 4328 (2001) 47–53. [5] R.M. López, V.V. Spirin, S.V. Miridonov, M.G. Shlyagin, G. Beltrán, E.A. Kuzin, Fiber optic distributed sensor for hydrocarbon leak localization based on transmission/reflection measurement, Opt. Laser Technol. 34 (6) (2002) 465–469. [6] M. Tateda, T. Horiguchi, Advances in optical time domain reflectometry, J. Lightwave Technol. 7 (1989) 1217–1224. [7] K. Tsuji, K. Shimizu, T. Horiguchi, Y. Koyamada, Spatial-resolution improvement in long-range coherent optical frequency domain reflectometry by frequency-sweep linearisation, Electron. Lett. 33 (1997) 408– 410. [8] K. Tsuji, K. Shimizu, T. Horiguchi, Y. Koyamada, Coherent optical frequency domain reflectometry for a long single-mode optical fiber using a coherent lightwave source and an external phase modulator, IEEE Photon. Technol. Lett. 7 (1995) 804–806. [9] K. Tsuji, K. Shimizu, T. Horiguchi, Y. Koyamada, Coherent optical frequency domain reflectometry using phase-decorrelated reflected and reference lightwave, J. Lightwave Technol. 15 (1997) 1102–1109. [10] R. Passy, N. Gisin, J.P. von der Weid, H.H. Gilgen, Experimental and theoretical investigation of coherent OFDR with semiconductor laser sources, J. Lightwave Technol. 12 (1994) 1622–1630.
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[11] R.I. MacDonald, Frequency domain optical reflectometer, Appl. Opt. 20 (1981) 1840–1844. [12] R.I. MacDonald, B.E. Swekla, Frequency domain optical reflectometer using a GaAs optoelectronic mixer, Appl. Opt. 29 (1990) 4578–4582. [13] S. Venkatesh, D.W. Dolfi, Incoherent frequency modulated cw optical reflectometry with centimeter resolution, Appl. Opt. 29 (1990) 1323–1326. [14] V.V. Spirin, M.G. Shlyagin, S.V. Miridonov, P.L. Swart, Alarm-condition detection and localization using Rayleigh scattering for a fiber optic bending sensor with an unmodulated light source, Opt. Commun. 205 (1–3) (2002) 37–41. [15] V.V. Spirin, M.G. Shlyagin, S.V. Miridonov, F.J. Mendieta, R.M. López, Fiber Bragg grating sensor for petroleum hydrocarbon leak detection, Opt. Lasers Eng. 32 (2000) 497–503. [16] P.W. Allen, Natural Rubber and the Synthetics, 1972. [17] M. Morton, Rubber Technology, 3rd Edition, 1987. [18] R.M. López, V.V. Spirin, M.G. Shlyagin, S.V. Miridonov, I. Márquez, A. Márquez, Coherent optical frequency domain reflectometry for interrogation of microbend and macrobend-based fiber optic hydrocarbon sensors, SPIE 4328 (2001) 114–121. [19] G. Mussi, P. Stamp, N. Gisin, R. Passy, J.P. von der Weid, Polarization effects in coherent optical frequencydomain reflectometry, IEEE Photon. Technol. Lett. 8 (11) (1996) 1513–1515. [20] J.P. von der Weid, R. Passy, G. Mussi, N. Gisin, On characterization of optical fiber network components with optical frequency domain reflectometry, J. Lightwave Technol. 15 (7) (1997) 1131–1141.
Coherent optical frequency domain reflectometry for interrogation of bend-based fiber optic hydrocarbon sensors R.M. López,a,∗ V.V. Spirin,a,∗ M.G. Shlyagin,a S.V. Miridonov,a G. Beltrán,b E.A. Kuzin,b and A. Márquez Lucero c a División de Física Aplicada, CICESE, A.P. 2732, Ensenada, B.C., Mexico b INAOE, A.P. 51 y. 216, 7200 Puebla, Mexico c CIMAV, Complejo Industrial Chihuahua, CP. 31109, Chihuahua, Mexico
Received 19 October 2001; revised 28 July 2003
Abstract The paper presents distributed fiber optic bending sensor for petroleum hydrocarbon leak detection based on coherent optical frequency domain reflectometry (C-OFDR) technique. In order to introduce bending losses a sensitive polymer, which reversibly swells under hydrocarbon influence is employed. In this work we used lumped reflectors, namely fiber Bragg gratings, placed between distributed sensitive elements. Design of proposed sensor utilizes the principle of distributed detection with section localization (DDSL) of perturbation. Analysis of signal-to-noise ratio (SNR) for multireflectors system was performed. We have demonstrated that the C-OFDR technique with bending sensor is capable to detect hydrocarbon presence within a few minutes for 20-cm perturbation-length with spatial resolution about 0.5 m for strong perturbation. 2003 Elsevier Inc. All rights reserved. Keywords: Fiber optic distributed hydrocarbon sensor; Bragg grating; C-OFDR
1. Introduction Microbend and macrobend-based fiber optic sensors [1] are very attractive techniques for the distributed measurement of the pressure, temperature, displacement, etc., where the measurand can be associated with a periodic deformation of the fiber [2]. These techniques * Corresponding authors.
E-mail addresses: [email protected] (R.M. López), [email protected] (V.V. Spirin). 1068-5200/$ – see front matter 2003 Elsevier Inc. All rights reserved. doi:10.1016/j.yofte.2003.09.003
80
R.M. López et al. / Optical Fiber Technology 10 (2004) 79–90
may be extended to the fully distributed sensing of chemical agents, such as hydrocarbon, by using a special polymer, which bends the test-fiber in response to hydrocarbon influence [3–5]. As well known, the fiber optical sensors are very promising for using in hazard conditions due to its electrical and fire immunity. In this paper, we utilize distributed bend-based fiber optic sensor for hydrocarbon detection. Proposed technique is preferably oriented on the detection and localization of the hydrocarbon leakage that may lead to a significant environmental pollution. The perturbed region in distributed fiber optic loss sensors is usually localized by means of optical time-domain reflectometry (OTDR) [6]. As an alternatives to the standard OTDR a number of different measurement techniques, such as coherent optical frequency domain reflectometry C-OFDR [7–10], incoherent optical frequency domain reflectometry (I-OFDR) [11–13], and transmission-reflection analysis (TRA) [14,15] had been proposed. In comparison with the traditional OTDR technique the alternative techniques demonstrate set of advantages as well as some disadvantages. In this work for the hydrocarbon leak detection and localization we use coherent optical frequency domain reflectometry technique. C-OFDR technique allows avoiding “dead zone” problem, which is inherent in OTDR; it shows extremely high resolution, high sensitivity and potentially has low cost [7–10]. The paper presents the result of the experimental investigation of distributed hydrocarbon sensor based on C-OFDR technique with lumped reflectors placed along the test fiber. Analysis of the noise properties is also performed for such kind of systems.
2. Principle of operation The C-OFDR technique is based on an analysis of the beat signal generated by optical interference between a reference beam reflected from a fixed mirror and a signal beam coming from the test fiber when the optical frequency of the light source is swept. The beat frequency is proportional to the distance along the fiber if the optical frequency varies linearly with respect to time. The amplitude of the interference signal depends on intensity of backreflected light and light losses in the test fiber. Nevertheless, dependence of the interference signal on the beat frequency or so-called beat spectrum, represents the distribution of the backscattered optical power along the test fiber and can be used for detection of loss induced perturbations. Proposed sensor for hydrocarbon leak detection comprises of distributed sensitive elements, which induce additional losses in the test fiber in hydrocarbon presence, and Bragg gratings written in the core of the test fiber between the sensitive elements. Fiber optic Bragg gratings significantly increase the signal level allowing to eliminate any averaging procedure. Furthermore, the lumped reflectors are placed at fixed positions along the test fiber that allows to localize the perturbation region. For the detection and localization of the hydrocarbon presence with proposed sensor, the change of the beat spectrum was utilized. The perturbation manifests itself as decreasing of the peak signals for the gratings which was placed behind the loss region. Typical beat spectrum for 3 Bragg gratings separated by 12 m-length sensitive elements for 50 Hz sweep modulation frequency when all peaks from the gratings are clearly resolved is shown in
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Fig. 1. Beat spectrum (a) without gasoline influence, (b) thirty minutes under gasoline influence between first and second gratings, and (c) forty minutes under gasoline influence.
Fig. 1. Under the hydrocarbon influence between first and second gratings the value of beat signal for two last gratings significantly decrease due to an additional bending losses induced in the section between gratings. The position of the first downwarded peak allows to localize the perturbation with accuracy equal to the distance between adjacent gratings. For the strong perturbation that decreased the fiber transmission by more than 20 dB the change of the resulting beat spectrum can be interpreted as shift of the trailing edge of the beat spectrum (see the difference between curves (a) and (c) in Fig. 1). The operation mode of the proposed sensor can be characterized as distributed detection with section localization (DDSL) of the perturbation. Note, that proposed method can be used even if the reflectors are placed so closely, that corresponding peaks cannot be resolved as individual peaks.
3. Experimental results 3.1. Measurement of bending losses induced by swellable polymer First of all we estimate the value of additional bending losses that can be induced by swellable polymer in hydrocarbon presence. A white butyl rubber was used as the sensitive polymer in the DDSL hydrocarbon sensor. This material has good aging properties at elevated temperatures, and good chemical stability. It also resists weathering, sunlight, ozone, mineral acids, oxygenated solvents (ketones and alcohols), and water absorption [16,17]. Butyl rubber swells under hydrocarbon influence without dissolution and
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significant change of its mechanical properties. The swelling of the polymer can be readily converted to a mechanical response. Our study shows that butyl rubber can increase its volume for more than 2 times under gasoline influence [15,18]. Furthermore, its behavior is reversible, i.e., the white butyl rubber can be used over multiple wet-dry cycles. In our experiment, we tested the sensor only under gasoline influence, but qualitatively the same swelling behavior butyl rubber shows in a range of hydrocarbon fuels [4]. Since the chemical and climatic properties of the sensitive element mainly define the corresponding properties of the sensor, we expect to achieve good climatic performance of the proposed sensor. In our sensor single mode SMF-28 optical fiber and the swellable polymer were coupled mechanically together by soft wire winded around them (see Fig. 1). The fiber was placed inside especially-shaped small groove in the polymer that allows to avoid initial losses, but does not significantly increase the response time of sensor. Standard experimental setup was used for the measurement of the transmission of proposed sensor. To study the sensor response, 20- and 40-cm length of sensitive element were placed inside a vessel filled by gasoline. Under the gasoline influence butyl rubber swells and bends the fiber that changes the transmission of the test fiber. Figure 2 shows the change of transmission of the test fiber during wet-drying cycle. As we can see, losses up to 25 dB can be induced under gasoline influence even for 20-cm perturbation length. Our previous study shows that the biggest losses at fixed time can be induced for the wirewinding period approximately equal to 5–10 mm for both single and multimode fibers [3].
Fig. 2. Evolution of transmission of the test fiber during wet-drying cycle.
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Fig. 3. Experimental setup for DDSL hydrocarbon sensor testing.
3.2. Interrogation of bending sensors Experimental setup for DDSL hydrocarbon sensor testing is shown in Fig. 3. The light emitted from New Focus 6262 tunable laser operating at a wavelength about 1534.5 nm with the line width v less than 300 kHz was launched into the test fiber through a 3-dB coupler. The launched optical power was about 500 µW. An optical isolator was used to prevent any influence on the laser from a backreflected light. The backreflected light from the test fiber passed back through 3-dB coupler and mixed with the reference beam by means of 10/90 coupler. Photo detector New Focus 1811 was used for the signal measurement. The beat component of the photo current was analyzed by an electrical spectrum analyzer with a resolution about 100 kHz. The optical frequency of the laser was swept by variation of the cavity length of the laser. For this purpose, a triangular wave voltage was applied to a piezoelectric transducer which holds one laser mirror. As result, the laser wavelength was swept linearly inside the 10 GHz interval (see Fig. 3) with a modulation frequency up to 200 Hz and with optical frequency sweep rate up to 4 THz/s. The sensor is composed of three distributed sensitive elements with identical length equal to 12 m and three Bragg gratings placed at the end of each sensitive length. The Bragg gratings have been written in the core of the single-mode fiber by using a phase mask technique and fourth harmonic of Q-switched Nd:YAG laser at the wavelength of 266 nm. The gratings had a length about 1 mm each, and Bragg wavelength equal to 1535 nm. All gratings had a reflectivity about (2 or 3%), and reflection spectrum bandwidth about 0.3 nm. To study sensor response we placed 20-cm length of second sensitive element inside the straight narrow vessel filled by gasoline. Under the gasoline influence the polymer swells inducing the bending losses. It leads to decrease of the beat signals from second and third Bragg gratings. After 40 min the gasoline was removed from the vessel and the sensor was left for drying. Figure 4 shows dependencies of beat signals for three Bragg
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Fig. 4. Dependence of beat signal of Bragg gratings on time. Gasoline influence between 1st and 2nd gratings.
gratings versus time during wet-drying cycle. All beat signals return back to their initial state approximately at 200 min. Note that under gasoline influence a small variation of the beat signal from the first grating also takes place. We attribute this variation with the uncontrolled change of the state of polarization (SOP) of reflected light [19,20]. The gasoline presence can be detected when the level of beat signal decreases for a value, which exceeds the level of variations of signal. In the experiment this variation does not exceed 5 dB during wet-drying cycle (see the signal for the first Bragg grating in Fig. 4). Therefore, in the experiment we can clearly detect the gasoline presence within 8 min, because after this time the beat signal of second and third gratings decrease for more than 5 dB. The time response of the sensor depends on the length of the sensitive element under the gasoline influence If the length is greater, the response is faster (see Fig. 2). Moreover, the response time of the sensor can be significantly improved using optimal design of the sensitive element and eliminating the SOP instability Beat spectrum demonstrates qualitatively the same behavior when the gasoline effects on different sensitive elements of the DDSL sensor. Note that the SOP instability can be eliminated by using the polarization diversity receivers, or polarization average procedure [19]. Figure 5 shows the dependence of trailing edge shift versus a distance between gratings for strong losses and 50 Hz sweep modulation frequency. All data was recorded after 40 min of gasoline influence for different distances between gratings. Shift of trailing edge depends linearly on a distance between gratings. Figure 5 also demonstrates the shift of trailing edge of beat spectrum after 40 min of gasoline influence between two gratings separated by 1.5 m for 50 Hz sweep modulation frequency. As we can see, by measuring the shift of trailing edge of beat spectrum for strong perturbations we can localize the perturbation even if we cannot resolve the signals from adjacent gratings. As a rule, we measure the
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Fig. 5. Dependence of the shift of trailing edge of beat spectrum versus distance between gratings. (a) Shift of trailing edge of beat spectrum after 40-min of gasoline influence between two gratings separated by 1.5 m.
shift at half-level of peak value, but the value of this shift nearly the same (with accuracy about 10%) inside interval (0.2 to 0.7) of peak value of the signal (see Fig. 5a). The maximum length of the conventional C-OFDR based sensors is limited by the coherence length of used laser [8,9]. The coherence length of tunable New Focus 6262 laser is equal to 500 m. That gives the maximum length of the sensor equal to 250 m. However, decay and broadening of the detected peaks due to the sweep nonlinearity [20] reduce the maximum detectable range of the sensor to 150–180 m. Note, that using C-OFDR with so called phase-decorrelated reflected and reference lightwave [9] the range limitation imposed by the source coherence length can be coped. For an ideal optical source with zero linewidth the spatial resolution limit z = Vg /2B where Vg is group velocity of the light into the fiber and B is frequency-sweep span. A full sweep of 10 GHz limits the resolution to approximately 1 cm. However, in the real C-OFDR systems the spatial resolution limit is restricted by light source and receiver bandwidths [20]. Additional broadening of the reflection peak in our experiment was caused by intensity modulation of the light reflected from the spectral-selective Bragg gratings during the laser frequency-sweep and SOP instability. Nonlinearity in the optical frequency sweep will impose further worsening of the resolution, because the beat frequency corresponding to a given reflection peak varies during the data acquisition. The sweep nonlinearity is the most important limiting factor in the resolution [20]. As discussed above, the strong perturbation can be localized with proposed sensor by measuring of the shift of the trailing edge of beat spectrum. Therefore the random variation of the trailing edge gives us the real resolution limit for the strong perturbation. Experimental measurements show that the maximum random variation of the trailing edge shift
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corresponds to the maximum variation of the distance equal to ±0.3 m near the source end of the test fiber, and equal to ±0.5 m for the grating located at 100 m from the source. Note, that approximately the same spatial resolution can be obtained for relatively weak perturbations that decreased the fiber transmission by more than 5–10 dB.
4. Multiple reflections influence on signal-to-noise ratio As well known, the lumped reflectors significantly increase the signal strength but on other hand the noise originated due to multiple reflections from such reflectors can also restrict the performance of DDSL sensors. Below we analyze the influence of multiple reflections on the signal-to-noise ratio (SNR) for DDSL sensors. Let us consider the DDSL sensor with length L, which consists of a series of n independent lumped reflectors with identical reflectivity r, separated by equal distances (see Fig. 6). In this example, we assume that the signal is produced due to reflection from the last nth reflector at the end of fiber. The total noise, due to multiple reflections, consists of the components from 3, 5 . . . up to (2n − 3) reflections (see Appendix A). If we consider 3-reflection component only in the noise and neglect other components from more than 3 reflections, we obtain the upper limit for SNR as follows (see Appendix A) mS mN3 + PNP h mP0 r(1 − r)2(n−1) e−2αL = , (1) 0.5mP0 e−2αL r 3 (1 − r)2n−4 (n − 1)(n − 2) + PNP h √ √ where PNP h = NEP B, NEP is noise-equivalent power equal to 2.5 pW/ Hz for photodetector New Focus 1811, B = 100 kHz, m is a ramification coefficient equal to 0.45 for couplers used in the experiment, P0 = 500 µW, α = 0.19 dB/km, and L = 36 m. SNRup =
Fig. 6. (a) Schematic representation of the DDSL sensor. (b) Graph for calculation of number of paths for noise components.
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Fig. 7. Upper and lower SNR limits (a) for 5 reflectors and (b) for 30 reflectors.
To calculate the total noise power we need to summarize the noise components from all possible reflections: M = 2k + 1, where k = 1, . . . , n − 2. Taking into account the maximum number of combinations with M reflections Amax M (see Appendix A) we can find the lower limit for SNR: SNRlow =
0.5mP0 e
n−2 −2αL
k=1 r
mP0 r(1 − r)2(n−1)e−2αL 2k+1 (1 − r)2(n−k−1)
nC2(k−1) (n − 1)(n − 2) + PNP h
. (2)
Figure 7a presents the calculated SNR upper and lower limits versus reflection coefficient r for 4 sensitive elements separated by lumped reflectors. The upper and lower limits practically coincide for the reflectivity r below 0.03. As it follows from the data presented in Fig. 7a, for the lumped reflectors with the reflectivity about (2–3%), as was in our experiments, we can neglect the noise produced by multiple reflections. Nevertheless, with increasing the number of the sensitive elements, multiple reflections can significantly reduce the SNR. Figure 7b shows the lower and upper SNR limits versus reflection coefficient r for 30 lumped reflectors. The real SNR lies between these limits. For example, in order to obtain the SNR better than 3, the reflectivity of lumped reflectors must be less than 2.5%. Note that the same signal-to-noise analysis can be applied for the systems with lumped reflectors based on optical time domain reflectometry (OTDR), because only multireflection noise components with total path equal to signal path can reach the detector simultaneously with the signal.
5. Conclusions We have presented the operation of a distributed fiber optic sensor for hydrocarbon leak detection based on swellable polymer, which induce additional bending losses on the test fiber under hydrocarbon influence. Proposed sensor comprises distributed sensitive elements and Bragg gratings placed between them. C-OFDR technique was used for the bending sensors interrogation. The proposed method of measurement realizes distributed
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detection with section localization of the perturbation. The swelling of the 20-cm length of the sensitive polymer, which was used in the sensor, induced the additional losses up to 25 dB under gasoline influence. We have analyzed the influence of multiple reflections on the SNR of DDSL sensors and determined the SNR for any possible number of lumped reflectors with arbitrary reflectivity. It was shown that the proposed sensor allows to detect the gasoline presence within 8 min for 20-cm perturbation-length, and to localize strong perturbation with the accuracy about 0.5 m.
Acknowledgments We gratefully acknowledge financial support through Grant 32208E from Consejo Nacional de Ciencia y Tecnología, México. The authors would like to thank M.S. Miguel Farfán for technical help in the experiment. Appendix A. Signal to noise analysis Figure 6a presents the DDSL sensor, which consists of a series of n independent lumped reflectors with identical reflectivity r, separated by equal distances. Let us suppose that the signal is produced by the reflection from the last nth lumped reflector placed at the end of test fiber. The power of the signal S can be written as S = P0 r(1 − r)2(n−1)e−2αL ,
(A.1)
where P0 is launched into the test fiber optical power, α is loss coefficient in the test fiber, and L is its length. We consider that the noise is produced by only multiple reflections from the mirrors. In our analysis, we must take into account only those multiple reflections, which have total path 2L, since only these components produce the noise at the same beat frequency as the signal. Without loss of generality, we can assume that all distances between mirrors are equal to 1. Let us estimate the number of different paths for noise components with the total lengths equal to the signal path 2(n − 1) (see Fig. 6a). The number of reflections must be odd, because the noise components must return back, like the signal. The maximum number of reflections with total path 2(n − 1) is equal to (2n − 3). It takes place when light consequently reflects (2n − 3) times between the second and first mirrors only. First of all, let us consider the noise produced by only 3 reflections. The number of different paths in this case can be calculated using the graph presented in Fig. 6b. This figure shows all possible paths with 3 reflections when the first reflection occurs at (n−1)th mirror. As we can see, the total number of such combinations is (n−2). If the first reflection is from (n − 2)th mirror, there are only (n − 3) different possibilities to collect a total path equal to 2(n − 1) after three reflections. Furthermore, if the first reflection occurs at the second mirror, there is only one possible way to collect a total path equal to 2(n − 1). This case is marked as doted line in Fig. 6b. So, the total number of different paths with 3 reflections A3 is given by sum of arithmetic series: (n − 1)(n − 2) . (A.2) A3 = (n − 2) + (n − 3) + · · · + 1 = 2
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The calculation of the total number of different paths for general case with M reflections where M > 3, is complicated. Nevertheless we can easy find the upper limit of this total number. Indeed, 5 reflections can be considered as consequence of 2 and 3 reflections. The number of all possible paths with 2 reflections, without any restriction for a total collected path length is equal to number of combinations of 2 objects from a group of n objects n C2 . This value gives us the absolute maximum for the number of possible paths with 2 reflections. The number of different paths for remaining 3 reflections is less than (n − 1)(n − 2)/2, since we still gather same path length during 2 initial reflections and thereby, we must collect the path length less than 2(n − 1) during the last 3 reflections. Therefore, the number of different paths with 5 reflections is given by (n − 1)(n − 2) , (A.3) 2 and for M 3 reflections: (n − 1)(n − 2) AM nCM−3 = Amax (A.4) M , 2 where n CM−3 is number of combinations of M − 3 objects from a group of n objects. The power of the noise component suffering M reflections and having the same path as the signal can be written in the following form A5 < nC2
NM = P0 r M (1 − r)2n−1−M AM e−2αL ,
(A.5)
where AM is the number of different paths having the total length equal to 2L.
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