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Investigation of a quasi-distributed displacement sensor using the macro-bending loss of an optical fiber
Optical Fiber Technology 55 (2020) 102140
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Investigation of a quasi-distributed displacement sensor using the macrobending loss of an optical fiber
T
⁎
Yong Zhenga,b, Zheng-Wei Zhua,b, , Wang Xiaoa,b, Dong-Ming Gua,b, Quan-Xiang Denga,b a b
School of Civil Engineering of Chongqing University, Chongqing 400045, PR China Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University), Ministry of Education, Chongqing 400045, PR China
A R T I C LE I N FO
A B S T R A C T
Keywords: QDFODS Landslide monitoring OTDR FODS Field monitoring
In this paper a quasi-distributed fiber-optic displacement sensor (QDFODS) for landslide monitoring using an optical time domain reflectometer (OTDR) was demonstrated. The new sensor was connected in series by several fiber-optic displacement sensors (FODSs). Their configurations introduce power loss through the decrease of their fiber bowknot radius when displacement was applied. The decrease of the light intensity with displacement variation was reported. The proposed FODS had a maximum measurement distance and an effective initial measurement displacement of 36 mm and 0.98 mm. The authors performed the laboratory experiments, and the sliding damage of the rock mass with two-stage sliding was effectively predicted by the QDFODS. Further, a field monitoring application of the QDFODS was conducted to confirm the feasibility for determining the progressive deformation characteristics of the slope, such as the magnitude of movement and positions of the potential sliding surfaces. This capability demonstrates the promising applications of the QDFODS in the monitoring of civil engineering, especially slopes, foundation pits and tunnels.
1. Introduction
optical fiber, fiber-optic displacement sensors are mainly divided into several types: intensity modulation, phase modulation, polarization modulation and wavelength modulation [10,11]. Among these, the fiber-optic displacement sensors based on the macro-bending loss principle belong to the intensity-based fiber optical sensors, in which light transmission loss will increase suddenly under large curvatures [12]. In recent years, fiber-optic displacement sensors based on the fiber macro-bending loss have been proposed and investigated in the field of civil engineering, and the distributed optical fiber monitoring technologies based on optical time domain reflectometer (OTDR) have also achieved great progress [13,14]. Ansari et al. [15] developed a type of fiber loop-based crack sensor, and these crack sensors were coupled to a concrete structure in such a certain way that cracking would result in the change of the loop geometry, which generated large amount of bending loss. Sienkiewicz et al. [16] proposed a novel fiber-optic displacement sensor with the figure eight shape to be used for structural health monitoring of civil engineering, which can directly change the bending curvature of the optical fiber without an external mechanism to cause the bends. To improve the measurement accuracy of the series optical fiber bending loss displacement sensor based on OTDR, Higuchi et al. [17] used a different anchor for the installation of optical fiber sensors and conducted experiments, the data information was collected
It is well known that fiber-optic sensors developed at the end of the 1970s over the common mechanical and electronic counterparts, have obvious advantages including strong electromagnetic interference resistance, good electrical insulation, corrosion resistance, wide measurement range, small volume, and large transmission capacity, which have been extensively applied in structural health monitoring [1–4]. Among them, there are two main categories for fiber-optic displacement sensors, i.e. extrinsic and intrinsic sensors. The reflexive-type [5], the transmission-type [6] and interferometric fiber-optic displacement sensors [7,8] are extrinsic sensors, which are widely applied in diverse fields due to their high accuracies and large measurement ranges. This type of sensors simply use optical fiber as light transmission medium. The bend-loss type sensors, as the most widely used, are intrinsic sensors as well as have sensing and light guiding roles with simple constructions and innovation structures if designed by packager properly [2,9]. In practical applications, the optical fiber is prone to bend and causes macro-bending loss, which is not conducive to long-distance optical signal transmission. However, the fiber macro-bending loss in the field of fiber sensing is advantageous. Consequently, the external physical quantities can be detected by utilizing the fiber macro-bending loss effect. According to the principle that light wave is modulated in ⁎
Corresponding author at: School of Civil Engineering of Chongqing University, Chongqing 400045, PR China. E-mail address: [email protected] (Z.-W. Zhu).
https://doi.org/10.1016/j.yofte.2020.102140 Received 12 August 2019; Received in revised form 31 December 2019; Accepted 3 January 2020 1068-5200/ © 2020 Elsevier Inc. All rights reserved.
Optical Fiber Technology 55 (2020) 102140
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Fig. 1. Layout of the QDFODS for displacement monitoring (a) sketch of the QDFODS installed in the monitored rock-soil mass (b) multiplexing of several FODS units in one optical fiber.
design of sensors, sensor calibration and model experiments, field monitoring and data analysis were presented and discussed.
by ODTR, which proved this system was very economical and practical, however, some improvements needed be adopted to reduce the measurement error caused by the optical cable. Zhu et al. [18] inserted a bare optical fiber into a capillary steel tube and formed a bowknot bending modulator at the end of the capillary. As the monitoring method was based on borehole data, the sensor was buried in concrete, the capillary would bend and the geometry of the fiber bowknot decreased correspondingly as the cracks changed. We can know that the productive ability improved, but deficiency still existed for this sensor in monitoring tiny cracks. A novel distributed fiber optic sensor with a six-prism structure was invented to monitor tiny cracks in reference [19], and no a prior knowledge of crack location was required, which was characterized by a high sensitivity for the detection of small cracks whose opening is less than 0.8 mm. For further predicting the landslide deformation, a landslide monitoring early warning system based on macro-bending loss in polymer optical fiber was built, which consisted of three parts: mechanical converter, displacement fiber sensor and short messaging services gateway [20]. The sensor configured in this manner has sensitivity of (5.9 ± 0.2) dB/cm and displacement range of 40 cm. Meng et al. [21] invented a helical structure for a pavement optical fiber sensor based on bend loss. Chen et al. [9] designed a new type of crack fiber optic sensor. The sensing principle is that the optical fiber was wound around the shaft with a constant bending radius and the macro-bending loss was caused by a crack transfer device with a gear, which was well verified by model experiments. It can be seen from the above researches that these bend-loss type fiber-optic displacement sensors have been widely investigated and studied in structural engineering; however, relatively rare studies have been made in geotechnical engineering, such as slopes, foundation pits and dams. In addition, a large amount of researches about these sensors have been done and mainly concentrated on basic theory and laboratory experiments but rarely in field engineering. Remote monitoring of slope movement can be an effective approach for many unstable slopes. Slope movement can be characterized by the depth and areal extent of the failure plane, direction, magnitude, and rate; one or all of these variables can be measured. For deep-seated landslides with multi-sliding surfaces, the real-time monitoring of these variables seemed particularly difficult and important. The authors [22] have previously proposed a new fiber-optic displacement sensor with a bowknot bending modulator and deduced the theoretical mathematical relationship between the light source loss and the sliding distance by simplifying the optical fiber bowknot bending modulator to half of a four-leaved rose curve. The proposed sensor was simply and conceptually studied in the laboratory experiments; however, there existed some problems needed to be solved, such as robustness in field monitoring, determination of the potential sliding surfaces, and paving convenience. In this paper, in order to overcome above these problems, the authors designed a novel quasi-distributed fiber-optic displacement sensor (QDFODS) based on a bend mechanism induced by displacement for monitoring sliding deformation of the rock-soil mass. The aim of the paper is to demonstrate the feasibility and robustness of using the QDFODS to detect the inner deformation of the monitored slope. The
2. Structure and sensing principle of the sensor It is well known to all, bending loss is one of the most significant characteristics of the optical fiber, and the macro-bending loss will occur when the curvature radius of the fiber bending is much greater than its diameter [9]. The main reason for the macro-bending loss is the spatial filtering effect, which is a physical effect caused by the destruction of the total reflection conditions of the wave propagation, resulting in energy radiation outside of the fiber. The greater the degree of fiber bending, the more significant the spatial filtering effect, and the greater the fiber transmission loss. The macro-bending loss α c of the fiber can be expressed as follow [23]:
α c = Ae−BR
(1)
where R is the macro-bending radius of the fiber, and A and B are constants which are related to the fiber types and working states of the light source. Fig. 1a is a schematic diagram of the proposed QDFODS installed in the monitored rock-soil mass. This sensor is a distributed network system that is connected by a plurality of discrete optical fiber displacement sensors arranged on a spatially predicted position in a series structural form, and a public information transmission channel is shared by adopting the time division multiplexing bus topology technology, where the optical fiber plays only a light guiding role in the optical signal but not a sensing role. The several fiber-optic displacement sensor (FODS) units are connected from end to end and fixed to the two stainless steel connectors by binding. The optical fiber cable is connected by a fusion splice in each FODS unit (Fig. 1b). Fig. 2 shows the structure design of the independent FODS unit, which is constructed with stainless steel connectors, protective covers, acrylonitrile butadiene styrene (ABS) plastic pipes, capillary steel pipes and a singlemodule optical fiber with a bowknot bending modulator. The Φ1 stainless steel capillary penetrates through the Φ3 ABS plastic pipe which is extremely vulnerable to shear failure stresses to guarantee that the capillary can move freely in the plastic pipe embedded in mortar. The upper end of the capillary passes through the slot of a stainless steel connector and is bonded to the upper end of the Φ3 ABS pipe. The bottom of the capillary runs through the other connector at the bottom. A single module optical fiber is passed through the capillary and is wound into a bowknot at the bottom outside the monitored segment and placed into a stainless steel cover. The upper end of the optical fiber is connected to a light source detector through a fiber extraction aperture and armored cable. The fiber extraction aperture is closed by epoxy resin and the covers for protecting the bowknot bending modulator and the fiber are fixed to the two stainless steel connectors by banding. Next we will introduce the working principle of this sensor for landslide monitoring in detail. The proposed FODS is installed inside the monitored rock-soil mass (Fig. 3a), the sliding mass will exert a load 2
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similar to the figure eight shape of the fiber optic displacement sensor proposed by Sienkiewicz et al. [16]. The sensor does not require an external mechanism to increase to decrease the bend radius. The authors have conducted the theoretical analysis on this type of displacement sensor with a bowknot bending modulation, and the logarithmic function relationship between the retraction displacement S of the sensor and the relative fiber loss αb was derived as follows [22]:
S = C1 ln(αb + C2) − C1 ln(C2)
(2)
where C1, C2 are undetermined constants related to the fiber types, working states of the light source, and initial loss of the optical fiber, which can be determined through accurate calibration experiments. 3. Laboratory experiments 3.1. Sensor calibration Accurate calibration is required before any sensor is used. As mentioned above, the measured displacement and the relative loss of the fiber optic displacement sensor with a bowknot bending modulator designed in this paper is in a logarithmic relation, and the calibration constants C1, C2 are needed to be determined. The authors have carried out the laboratory calibration experiments on this type displacement sensor in the previous publication [22], and the results showed that when the initial dimensions D0 of the sensor were different, the effective initial measurement displacement, the maximum displacement range and the constants C1, C2 were all different. Therefore, in series of experiments performed later in this paper, the initial dimensions D0 were uniformly set at 34.56 mm, which was characterized by the maximum measurement displacement and effective initial measurement displacement of 36 mm and 0.98 mm, respectively. The calibration constants C1, C2 were determined as 59.952 mm and 15.491 dBm, respectively, and the correlation coefficient R2 was 0.998. The affordable loss resolution of the current interrogator is 0.05 dBm, the corresponding displacement of the sensor is 59.952 × ln (0.05 + 15.491) − 59.952 × ln15.491 = 0.193 mm. Therefore, the minimum displacement accuracy that the sensor can detect is 0.193 mm. However, the 0.1 dBm is considered as the initial significant fiber loss, which corresponds to the sliding displacement of 0.98 mm in the experiments, and is taken as the initial effective measurement displacement.
Fig. 2. Photograph and detailed design of the FODS unit.
on the sensor to cause its shear failure and a sliding distance lAB along the sliding surface. The ABS plastic pipe embedded in the mortar is extremely vulnerable to the shear damage, and the stainless steel capillary penetrates through the ABS plastic pipe; therefore, the capillary is not consolidated with the mortar and can move freely in the ABS plastic pipe. At this time, the capillary will have a corresponding retraction displacement S (namely the displacement of the optical fiber), which causes the curvature of the fiber bowknot to increase sharply and produces a large amount of the fiber loss captured by OTDR (Fig. 3b). OTDR as a non-destructive method for testing needs the access only to one end of an optical fiber. When the failure of fiber properties appears, there is a sharp change on a reflectogram. The OTDR locates the position of each sensing head and measures the induced displacement loss through the Rayleigh backscatter light signal. The optical loss based fiber optic sensor mainly consists of a light source, a bending modulator, optical fibers, and a light source detector. At present, the bending modulator structures mainly include saw-tooth [24,25], waviness, cylindrical shape, figure eight shape [16] and other types. In this paper an optical fiber bowknot bending modulator was designed to increase the sensitivity of the fiber to curvature (Fig. 3b), which is
Fig. 3. Schematic diagram of the FODS subject to a shear failure and the relationship between the sliding displacement and fiber loss (a) principle of measurement of the FODS subjected to a shear failure (b) photograph of the bowknot bending modulator. 3
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Fig. 4. Laboratory sliding damage experiment of the QDFODSs (unit: mm).
were carefully placed vertically into the instrument; meanwhile, light source detector was connected and debugged, and relevant parameters were configured. The hydraulic jack was used for loading and the sliding distances of the sliding masses were measured by the dial indicators. At the beginning of the experiment, only sliding mass 1 was loaded to move approximately half of the maximum measuring range of the sensor; then the sliding mass 1 and sliding mass 2 together were loaded until the sensor was damaged or the fiber loss signal could not be recorded in the light source detector OTDR (Type 6418) purchased from 41st Institute of China Electronics Technology Group Corporation, Hefei, Anhui, China. The sliding distances of the sliding mass 1 and sliding mass 2, and the light loss signal were measured simultaneously. The used fiber mounted of series sensors array is a simple module (Type G652B), purchased from the Wuhan Yangtze Optical Fiber and Cable Co., Ltd., Wuhan, Hubei, China. It is worth noting that the sensors were subjected to shear failure along two different shear planes, and to prevent the connectors of the sensing units (no.1 and no. 2) of the sensors, D1, D2, D3, from being at the shear plane, the bottom part of the no. 1 should be placed in the sliding mass 2 when these sensors, D1, D2, D3 were placed into the instrument. The purpose of this experiment is to discuss the capability and feasibility of the two different types of sensors for monitoring damage from rock mass. According to the calibration result of the sensors, the predicted displacements were computed by Eq. (2) based on the fiber loss collected by OTDR in the experiment, the relationship between the predicted and measured displacements of the sliding masses was given in Fig. 6. It can be seen that the predicted displacements obtained by the sensors increased with the increase of the tested shear displacements of the sliding masses, both exhibited relatively good linear relations, and their fitting curves and correlations were expressed as
3.2. Verification experiment It is well known to all, the occurrence of the discontinuous mechanical interfaces will be responsible for the instability or failure of rock slopes, which directly decreases the integrity of rock mass and changes the internal stress state. Especially, there are multiple discontinuous mechanical interfaces in rock mass, the overall strength and stability of deep rock slopes are greatly reduced. Therefore, in time and accurate forecasting of sliding displacement of rock slopes with multiple discontinuous mechanical interfaces is very important. To investigate the monitoring performance of the proposed QDFODS for predicting the sliding damage of rock mass, the authors designed a reinforced concrete shearing equipment with double shear planes as experimental instrument. The instrument was constructed with four components: sliding mass 1, sliding mass 2, sliding bed and reaction frame (Fig. 4). We fabricated two groups of different types of sensors in the experiment. Group 1 was one FODS with dimension of Φ 75 × 750 mm; group 2 was connected by two FODSs with dimensions of Φ 75 × 250 mm and Φ 75 × 500 mm, respectively. Each group had three sensors, numbered as C1, C2, C3 and D1, D2, D3, respectively. It is relatively common that the shallow sliding of the slope gradually induces the deep-seated overall sliding damage, called as the retrogressive landslide. The numbers 4, 3, 2 and 1 in the Fig. 5 represent the slip order of the sliding bodies of the retrogressive landslide. The failure mode of the retrogressive landslide is as follows: the lower part (slide body 1) slides first, which cause the upper parts (slide bodies 2, 3 and 4) to lose supports in turn and slide. Therefore, the following sliding damage experiment of rock mass was performed to investigate the monitoring effectiveness of these two groups of sensors for this slope failure condition. To begin the experiment, the prefabricated sensor models
Fig. 5. Block model of the retrogressive landslide and its corresponding conceptual experimental model. 4
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sensors C1, C2, C3 cannot be used for slope monitoring with multi-stage sliding. At the moment, the relationship between the predicted displacements and total sliding displacements of the sliding mass 1 and sliding mass 2 together was positively correlated and no breakpoint appeared. The fitting curves were continuous functions, and their correlation coefficients R2 exceeded 0.96, with the maximum and minimum RMSEs of 2.27 and 1.28 mm, respectively, and the positive correlation ratio values were between 0.941 and 1.015, which indicates that both displacements were linearly equal with high correlation. The sensors C1, C2, C3 could determine the magnitude of a rock slope slide but not the position of the potential sliding surface. As shown in Fig. 6b and Table 1, when the sensors D1, D2, D3 of group 2 were performed to monitor the deformation movement of the retrogressive landslide with two-stage sliding, we could observe the two attenuation “steps” of the fiber loss signal during the measurement, which could be used to determine the sequence and positions of the two-stages sliding. The first appearing attenuation “steps” corresponded to the initial-stage sliding and the second appearing attenuation “steps” corresponded to the later-stage sliding. The sensors D1, D2 and D3 were made of two sensing units no.1 (250 mm in height) and no.2 (500 mm in height), respectively; therefore, the position of the sliding surface of the first-stage sliding was within range of 0–250 mm, and the position of the sliding surface of the second-stage sliding was within range of 250–750 mm. At this time, the relationship between the predicted displacements and the total sliding displacements of the sliding mass 1 and sliding mass 2 together was positively correlated but a breakpoint for each fitting curve appeared. The fitting curves were discontinuous functions. It can be seen from Fig. 6b, the displacement prediction on the first-stage sliding of the sliding mass can be determined through the optical loss signal in the sensing unit no.1 of the sensors D1, D2, D3, and the second-stage sliding condition can be reconginzed by the optical loss signal in the sensing unit no. 2. In addition, the sliding displacements of the sliding masses can be effectively determined by the predicted displacements of the sensors, with the maximum and minimum RMSEs being 2.00 and 1.82 mm, respectively, and the positive correlation ratio values ranged from 0.926 to 1.170. Therefore, the sensors D1, D2, D3 can be effectively utilized for slope monitoring with multistage sliding, not only the internal displacements of the slope can be determined, but also the sequence and positions of multi-slip slope surfaces can be identified. The spatial resolution can reach 250 mm, or even smaller, it will be higher than that (generally is 500 mm) of the inclinometer tube and the quasi-distributed monitoring can be realized by connecting a series of sensors with fixed lengths end to end.
Fig. 6. Relationships between the predicted displacements from the QDFODS and the tested shear displacements by dial indicators of the sliding masses (a) group 1 (b) group 2.
follows, shown in Table 1:
yC1 = 0.941x − 0.922, R2 = 0.967, RMSE = 2.27 mm
(3a)
yC2 = 0.966x − 0.232, R2 = 0.985, RMSE = 1.28 mm
(3b)
yC3 = 1.015x − 1.215, R2 = 0.982, RMSE = 1.60 mm
(3c)
y1D1 = 0.926x − 1.558, R2 = 0.983; y2D1 = 1.170x − 26.373, R2 = 0.992, (4a)
RMSE = 2.00mm
y1D2 = 0.991x − 1.227, R2 = 0.994; y2D2 = 0.933x − 21.858, R2 = 0.986, (4b)
RMSE = 1.84 mm
y1D3 = 0.967x − 1.276, R2 = 0.980; y2D3 = 0.982x − 22.996, R2 = 0.969, (4c)
RMSE = 1.82 mm
4. In situ application
As shown in Fig. 6a and Table 1, when the sensors C1, C2, C3 of group 1 were performed to monitor the deformation movement of the retrogressive landslide with two-stage sliding, we could observe the only one attenuation “step” of the fiber loss signal during the measurement. However, this phenomenon (including the one “step” and its attenuation value) could also be caused by the same sensors if only the primary sliding at the one position was generated. Therefore, the
The authors in this section performed the application of the proposed QDFODS in a field slope located at Chongqing city, China (Fig. 7a). The aim of this work is to confirm its applicability and robustness in an actual geological environment and demonstrate workability. The geological structure is simple and no second-order folds and faults are found in the site. The rock stratum of the site is filled with
Table 1 Fitting results of segmented curves of the tested shear displacements and predicted displacements. Test group
Specimen model
Correlation coefficient The first loading
Group 1
Group 2
C1 C2 C3 D1 D2 D3
The second loading 0.967 0.985 0.982
0.983 0.994 0.980
0.992 0.986 0.969
RMSE (mm) The first loading
The second loading 2.27 1.28 1.60 2.00 1.84 1.82
5
Attenuation “step” number The first loading
The second loading Only one Only one Only one
One One One
Determination of sliding surface
Two Two Two
Can not Can not Can not Can Can Can
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Fig. 7. Photograph of the monitored slope site and layout of the monitoring equipment (a) the instrumented slope (b) the crown crack at slope crest (c) borehole (d) layout of the inclinometer and the proposed QDFODS.
and the position of the main potential sliding surface was 1.5–3.0 m underground, and the position of the secondary potential sliding surface was 0.0–1.0 m underground. In general, the accumulated inner deformation and its variation of the monitored slope were small, within an allowable range, and it remained basically stable. However, there was a shape increase of the slope’s deformation in the period of the partial excavation of the second-level slope (21 January to 25 February), which may be due to the fact that the effect of unloading of the slope toe caused by the excavation formed a shear outlet of landslide. Therefore, it was recommended to strengthen the later-stage monitoring of the first-level slope during excavation of the second-level slope to ensure the stability of the slope. We compared the predicted displacements by the QDFODS and the measured displacements by the inclinometer to discuss its feasibility in practical slope monitoring, and the comparison of the displacement profiles with time of two measuring instruments at different depths in the boreholes was shown in Fig. 9. It can be observed that the QDFODS could determine the sliding distances of two depth intervals in the borehole, which were 0.5–1.0 m underground and 2.0–2.5 m underground, respectively. In addition, the estimated displacement variation trend of the QDFODS was nearly identical to the trend of the inclinometer at the location of the main sliding surface; however, their displacement differences still remained. The predicted displacement curve by the QDFODS at the depth of 0.0–0.5 m is similar to that of the inclinometer at the depth of 0.5 m with an average absolute error of 13.53%. Meanwhile, the predicted displacement curve by the QDFODS at the depth of 1.5–2.0 m is similar to that of the inclinometer at the depth of 0.5 m, with an average absolute error of 17.06%. The main reasons were as follows: the proposed QDFODS and the inclinometer were considered as the cantilever beam structures in the slope, but their measurement principles were different. The QDFODS was subjected to shear failure while the inclinometer was bent deformation. The greater flexibility resulted in the greater deformation; therefore, the slope deformation measured by the inclinometer was larger than that of the QDFODS in the same depth range. Besides, the two measuring instruments have their own measurement errors. Through the above analysis, we can conclude that the QDFODS can basically reflect the internal movement of the slope, such as the position of the potential sliding surface and magnitude, which demonstrates that it is robust and capable of monitoring the field slope in actual environment.
debris, and the combination of rock formations is poor. It is mainly composed of artificial plain fill, and the underlying bedrock is mudstone and fine sandstone. The groundwater conditions in the site are poor, there are no phreatic water layer and stable water level, and no faults, landslides, and debris flows and other geological phenomena are found in the site and surrounding area. The slope is currently stable; however, considering the local steep slope and some crown cracks at the slope crest (Fig. 7b), as well as the stability evaluation of the slope site, the monitored slope was excavated with a stepped surface (Fig. 7a). The first-level slope has been completed, and the subsequent second-level slope is being prepared. To monitor the deformation of the first-level slope and the influence of the excavation and construction of the second-level slope on the overall slope stability, three boreholes with diameters of 110 mm were drilled as vertically as possible with a sag deviation of < 2° in the center position of the step between the firstlevel and second-level slopes (Fig. 7c). The FODS units were uniformly prefabricated into the cylinders 0.5 m in length with cement mortar at the construction site, and then the designed QDFODS comprehending eight FODS units was carefully placed into one borehole as vertically as possible. At the same time, an 8 m long inclinometer casing was buried adjacent to the QDFODS for comparison monitoring to further determine the sliding properties of the slope (Fig. 7d). The first monitoring was recorded on 31 December 2018, and by 3 June 2019, we have conducted 13 times data acquisitions including the inner slope displacement measured by the inclinometer and the fiber loss signal obtained from the QDFODS. We mainly focused on the deformation monitoring and analysis on the first-level slope, the relationship curve of the accumulated inner displacement of the slope measured by the inclinometer with the monitoring time was obtained, as shown in Fig. 8. It is worth noting that because there are too many data points, only the data with significant deformation of the slope at different depths are displayed in Fig. 8. It can be concluded that the accumulated sliding displacement of the first-level slope changed litter, the maximum value was 15.25 mm,
5. Discussion This paper proposed a novel QDFODS to monitor sliding deformation of the rock-soil mass based on the previous fiber-optic displacement sensor [22]. The sensor has been proved to be robust and effective in field slope monitoring. However, the advantages and limitations of the QDFODS for landslide monitoring need to be discussed before it can be used in geotechnical engineering. We don’t give the precision comparison results due to being influenced by the many factors, and the qualitative comparisons of the QDFODS and the previous fiber-optic displacement sensor are analyzed and concluded. The literature [22] demonstrated that this type of fiberoptic displacement sensor with bowknot bending modulation has a potential capability to detect slippage damage along the sliding mass. Simple and rough sensor design due to inadequate consideration by
Fig. 8. Relationship between the accumulated displacements measured by the inclinometer and the depths. 6
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Fig. 9. Relationship between the measured displacements by the inclinometer and predicted displacements by the proposed QDFODS at different depths in the boreholes.
paving convenience, determination of the potential sliding surfaces; in addition, the signal processing device is very simple and it is easy to realize wireless signal communication, which suggest that QDFODS has a promising prospect in landslide monitoring. Various optical fiber sensing technologies have been widely used in geotechnical engineering, such as, optical time domain reflectometry (OTDR), Brillouin optical time domain reflectometer/analysis (BOTDR/ A) [3] and fiber Bragg grating (FBG) [2], which make remote, real-time monitoring of slope movement possible. It is well known that FBG and BOTDR/A sensing technologies have remarkable cross-sensitivity to temperature and strain; however, temperature variation will result in a litter change of optical power transmitted in the fiber. A strain-freerelease sensor is usually adopted for temperature compensation without the effect of temperature cross-sensitivity. However, the strain produced by temperature variation is quite from a free temperature sensor as the temperatures underground and at ground level are different. Therefore, the landslide monitoring system based on OTDR technique without the effective of cross-sensitivity can be more accurately compared with other optical fiber sensing technologies. OTDR instrument has a large dynamic range and spatial resolution with a high accuracy for long-distance measurement of several kilometers, tens of kilometers and hundreds of kilometers, especially for the location of reflection events. The problem of resolution in OTDR measurement exists; however, in practical landslide monitoring, the possible location of crack or deformation (specific displacement) can be estimated in advance based on borehole data. The distance of optical fiber in landslide monitoring is usually within several kilometers, so the optimum measurement range is between 1.5 and 2 times the length of optical fiber to be measured. Therefore, the OTDR instrument can be used to detect and improve the accuracy of measurement.
designer brought about some deficiencies that needed to be solved. The fiber-optic displacement sensor cannot be connected in series to explore subsurface properties of slopes with multi-slip surfaces. In addition, the optical bowknot bending modulator is exposed to harsh environments and to protect it is a problem. The Φ2 tube should be pulled out once the mortar around the device reaches the initial setting to ensure that the Φ1 capillary can move freely inside the mortar, resulting in more work and difficulty. Therefore, the above related investigations about this sensor were mainly performed on basic theory and laboratory experiments due to the design limitations. Compared with the previous sensor [22], the QDFODS was designed with two stainless steel covers to protect the optical fiber and bowknot bending modulator and thus was robust in a harsh environment. The QDFODS comprehending several FODSs in series configuration can be used to monitor deformation of deep-seated landslides, which has been verified by a short-term monitoring result of a field slope engineering. Besides, the QDFODS models can be prefabricated at the construction site for paving convenience. This configuration that several fiber optic displacement sensors are disposed in series is common and reported in many publications. For instance, a quasi-distributed displacement-sensing configuration comprehending four displacement sensing heads along a standard single mode optical fiber in several locations with different intervals was presented which was characterized by maximum displacement response of 120 mm with a sensitivity of 0.027 dB/mm [26]. The use of a multiplexed fiber optic bend-loss type sensor with five sensor heads constructed by using only one optical fiber sensing line [15], which employed OTDR equipment to point-wisely measure the displacement of large structures such as bridges and buildings, was reported in 2006. This sensor designed in this paper is similar to these two cases. For landslide monitoring, localized or quasi-distributed sensors based on borehole monitoring is the common and cost-effective means, such as, probe inclinometer or in-place inclinometer, tiltmeters, TDR cable, FBG-based sensors [27–29]. Probe inclinometers need manual operation and cannot read data automatically and electronically. Inplace inclinometers are installed in the borehole with inclinometer casing, tilemeters are mainly mounted on the surface of the rock and soil to be measured, and TDR based on coaxial cable can automatically measure the slope, and its price is cheaper than inclinometer casing, but the actual sliding amount and direction of the slope cannot be determined. FBG-based sensors can realize multi-point measurement simultaneously by a single sensing system, which benefits from multiFBGs manufactured in a single fiber. Their higher sensitivity and precision make them to be widely used in civil engineering; however, the price is more expensive than the mentioned above. The QDFODS has a relatively low cost of $ 0.45/m and advantages of simple package,
6. Conclusions This paper reported a QDFODS using the macro-bending loss of an optical fiber for landslide monitoring. The laboratory experiments and field monitoring application of the QDFODS were performed in detail, the following conclusions are obtained: (1) The single FODSs (C1, C2, C3) could determine the magnitude of a rock mass slide with a ratio between both predicted and measured displacements ranging from 0.941 and 1.015, but not the positions of multi-slip slope surfaces, which was characterized by the maximum measurement displacement and effective initial measurement displacement of 36 mm and 0.98 mm, respectively. (2) The QDFODSs (D1, D2, D3) could be effectively used for detecting the multi-stage sliding of the rock mass. The sliding displacements 7
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of the sliding masses can be determined by the predicted displacements by the sensors, both ratio values were between 0.926 and 1.170. The positions of the sliding planes were deterimined with a spatial resolution of 250 mm, or even smaller. (3) The progressive deformation of the monitored slope in a short-term period was effectively predicted by the QDFODS, including the position of the potential sliding surface and magnitude, verifying that it is robust and reliable for monitoring the field slope in actual environment.
based on an optical interferometer, IEEE Sens. J. 17 (2017) 5523–5528. [8] C. Zhu, Y.Z. Chen, Y.Y. Zhuang, Y. Du, R.E. Gerald, Y. Tang, J. Huang, An optical interferometric triaxial displacement sensor for structural health monitoring: characterization of sliding and debonding for a delamination process, Sensors 17 (2017) 2696. [9] L. Cheng, Y.M. Li, Y.M. Ma, M.H. Li, F. Tong, The sensing principle of a new type of crack sensor based on linear macro-bending loss of an optical fiber and its experimental investigation, Sens. Actuators A Phys. 272 (2018) 53–61. [10] H.F. Hu, S.J. Sun, R.Q. Lv, Y. Zhao, Design and experiment of an optical fiber micro bend sensor for respiration monitoring, Sens. Actuators A Phys. 251 (2016) 126–133. [11] X.P. Ding, W. Wang, L.C. Fu, Classification and application principles of opticalfibre transducer, Spectrosc. Spect. Anal. 26 (6) (2006) 1176–1178. [12] H.T. Di, Sensing principle of fiber-optic curvature sensor, Opt. Laser Technol. 62 (10) (2014) 44–48. [13] H.T. Di, Y. Xin, J.Q. Jian, Review of optical fiber sensors for deformation measurement, Optik 168 (2018) 703–713. [14] N.M.P. Pinto, O. Frazao, J.M. Baptista, J.L. Santos, Quasi-distributed displacement sensor for structural monitoring using a commercial OTDR, Opt. Laser Eng. 44 (8) (2006) 771–778. [15] F. Ansari, R. Navalurkar, Kinematics of crack formation in cementitious composites by fiber optics, J. Eng. Mech. 119 (5) (1993) 1048–1061. [16] F. Sienkiewicz, A. Shukla, A simple fiber-optic sensor for use over a large displacement range, Opt. Lasers Eng. 28 (28) (1997) 293–304. [17] K. Higuchi, K. Fujisawa, K. Asai, et al., Application of new landslide monitoring technique using optical fiber sensor at Takisaka landslide, Japan, in: Proceeding of 1st North American Landslide Conference, Vail, Colorado, 2007, pp. 1073–1083. [18] Z.W. Zhu, D.Y. Liu, Q.Y. Yuan, B. Liu, J.C. Liu, A novel distributed optic fiber transduser for landslides monitoring, Opt. Laser Eng. 49 (2011) 1019–1024. [19] J.L. Zhao, T.F. Bao, U. Amjad, Optical fiber sensing of small cracks in isotropic homogeneous materials, Sens. Actuators A Phys. 225 (2015) 133–138. [20] A. Marzuki, M. Heriyanto, I.D. Setiyadi, S. Koesuma, Development of landslide early warning system using macro-bending loss based optical fibre sensor, J. Phys.: Conf. Ser. 662 (1) (2015) 012059. [21] L.J. Meng, L.B. Wang, H.C. Xiong, H.X. Wang, X.L. Guo, An investigation in the influence of helical structure on bend loss of pavement optical fiber sensor, Optik 183 (2019) 189–199. [22] Y. Zheng, D. Huang, Z.W. Zhu, Theoretical and experimental study on fiber-optic displacement sensor with bowknot bending modulation, Opt. Fiber Technol. 41 (2018) 12–20. [23] L.S. Zou, B. Zhang, Experimental study on micro-bending and bending loss of multimode fibers, Study Opt. Commun. 4 (1984) 44–51. [24] F. Luo, J.Y. Liu, N.B. Ma, T.F. Morse, A fiber optic microbend sensor for distributed sensing application in the structural strain monitoring, Sens. Actuators A Phys. 75 (1999) 41–44. [25] G.P. Xie, L.K. Seah, A. Anand, Optical time-domain reflectometry for distributed sensing of the structural strain and deformation, Opt. Laser Eng. 32 (2000) 437–447. [26] I.B. Kwon, C.Y. Kim, D.C. Seo, et al., Multiplexed fiber optic OTDR sensors for monitoring of soil sliding, in: Proceedings of the 18th Imeko World Congress Metrology for a Sustainable Development, Rio de Janeiro, Brazil, September, 2006, pp. 17–22. [27] T.D. Stark, H. Choi, Slope inclinometers for landslides, Landslides 5 (2008) 339–350. [28] J. Corominas, J. Moya, A. Lloret, J.A. Gili, M.G. Angeli, et al., Measurement of landslide displacements using a wire extensometer, Eng. Geol. 55 (2000) 149–166. [29] S.M.F. Aghda, K. Ganjalipour, K. Nabiollahi, Comparison of performance of inclinometer casing and TDR technique, J. Appl. Geophys. 150 (2018) 182–194.
CRediT authorship contribution statement Yong Zheng: Conceptualization, Data curation, Formal analysis, Writing - original draft. Zheng-Wei Zhu: Funding acquisition, Resources, Supervision. Wang Xiao: Investigation, Methodology, Project administration. Dong-Ming Gu: Writing - review & editing. Quan-Xiang Deng: Investigation, Project administration. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work is financially supported by Chongqing Natural Science Foundation of China (no. cstc2018jscx-msybX0271) and National Natural Science Foundation of China (no. 51478066). References [1] T.G. Tang, Q.Y. Wang, H.W. Liu, Experimental research on distributed fiber sensor for sliding damage monitoring, Opt. Laser Eng. 47 (1) (2009) 156–160. [2] Y. Zheng, Z.W. Zhu, W.J. Li, D.M. Gu, W. Xiao, Experimental research on a novel optic fiber sensor based on OTDR for landslide monitoring, Measurement 148 (2019) 106926. [3] X.Y. Bao, L. Chen, Recent progress in distributed fiber optic sensors, Sensors 12 (2012) 8601–8639. [4] E. Mesquita, T. Paixão, P. Antunes, et al., Groundwater level monitoring using a plastic optical fiber, Sens. Actuators A Phys. 240 (2016) 138–144. [5] H. Cao, Y. Chen, Z. Zhou, G. Zhang, Theoretical and experimental study on the optical fiber bundle displacement sensors, Sens. Actuators, A Phys. 136 (2) (2007) 580–587. [6] S. Binu, V.P.M. Pillai, V. Pradeepkumar, B.B. Padhy, C.S. Joseph, N. Chandrasekaran, Fibre-optic glucose sensor, Mat. Sci. C-Mater. 29 (1) (2009) 183–186. [7] C. Zhu, Y.Z. Chen, Y. Du, Y.Y. Zhuang, F.X. Liu, R.E. Gerald, J. Huang, A displacement sensor with centimeter dynamic range and submicrometer resolution
8
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Optical Fiber Technology journal homepage: www.elsevier.com/locate/yofte
Investigation of a quasi-distributed displacement sensor using the macrobending loss of an optical fiber
T
⁎
Yong Zhenga,b, Zheng-Wei Zhua,b, , Wang Xiaoa,b, Dong-Ming Gua,b, Quan-Xiang Denga,b a b
School of Civil Engineering of Chongqing University, Chongqing 400045, PR China Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University), Ministry of Education, Chongqing 400045, PR China
A R T I C LE I N FO
A B S T R A C T
Keywords: QDFODS Landslide monitoring OTDR FODS Field monitoring
In this paper a quasi-distributed fiber-optic displacement sensor (QDFODS) for landslide monitoring using an optical time domain reflectometer (OTDR) was demonstrated. The new sensor was connected in series by several fiber-optic displacement sensors (FODSs). Their configurations introduce power loss through the decrease of their fiber bowknot radius when displacement was applied. The decrease of the light intensity with displacement variation was reported. The proposed FODS had a maximum measurement distance and an effective initial measurement displacement of 36 mm and 0.98 mm. The authors performed the laboratory experiments, and the sliding damage of the rock mass with two-stage sliding was effectively predicted by the QDFODS. Further, a field monitoring application of the QDFODS was conducted to confirm the feasibility for determining the progressive deformation characteristics of the slope, such as the magnitude of movement and positions of the potential sliding surfaces. This capability demonstrates the promising applications of the QDFODS in the monitoring of civil engineering, especially slopes, foundation pits and tunnels.
1. Introduction
optical fiber, fiber-optic displacement sensors are mainly divided into several types: intensity modulation, phase modulation, polarization modulation and wavelength modulation [10,11]. Among these, the fiber-optic displacement sensors based on the macro-bending loss principle belong to the intensity-based fiber optical sensors, in which light transmission loss will increase suddenly under large curvatures [12]. In recent years, fiber-optic displacement sensors based on the fiber macro-bending loss have been proposed and investigated in the field of civil engineering, and the distributed optical fiber monitoring technologies based on optical time domain reflectometer (OTDR) have also achieved great progress [13,14]. Ansari et al. [15] developed a type of fiber loop-based crack sensor, and these crack sensors were coupled to a concrete structure in such a certain way that cracking would result in the change of the loop geometry, which generated large amount of bending loss. Sienkiewicz et al. [16] proposed a novel fiber-optic displacement sensor with the figure eight shape to be used for structural health monitoring of civil engineering, which can directly change the bending curvature of the optical fiber without an external mechanism to cause the bends. To improve the measurement accuracy of the series optical fiber bending loss displacement sensor based on OTDR, Higuchi et al. [17] used a different anchor for the installation of optical fiber sensors and conducted experiments, the data information was collected
It is well known that fiber-optic sensors developed at the end of the 1970s over the common mechanical and electronic counterparts, have obvious advantages including strong electromagnetic interference resistance, good electrical insulation, corrosion resistance, wide measurement range, small volume, and large transmission capacity, which have been extensively applied in structural health monitoring [1–4]. Among them, there are two main categories for fiber-optic displacement sensors, i.e. extrinsic and intrinsic sensors. The reflexive-type [5], the transmission-type [6] and interferometric fiber-optic displacement sensors [7,8] are extrinsic sensors, which are widely applied in diverse fields due to their high accuracies and large measurement ranges. This type of sensors simply use optical fiber as light transmission medium. The bend-loss type sensors, as the most widely used, are intrinsic sensors as well as have sensing and light guiding roles with simple constructions and innovation structures if designed by packager properly [2,9]. In practical applications, the optical fiber is prone to bend and causes macro-bending loss, which is not conducive to long-distance optical signal transmission. However, the fiber macro-bending loss in the field of fiber sensing is advantageous. Consequently, the external physical quantities can be detected by utilizing the fiber macro-bending loss effect. According to the principle that light wave is modulated in ⁎
Corresponding author at: School of Civil Engineering of Chongqing University, Chongqing 400045, PR China. E-mail address: [email protected] (Z.-W. Zhu).
https://doi.org/10.1016/j.yofte.2020.102140 Received 12 August 2019; Received in revised form 31 December 2019; Accepted 3 January 2020 1068-5200/ © 2020 Elsevier Inc. All rights reserved.
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Fig. 1. Layout of the QDFODS for displacement monitoring (a) sketch of the QDFODS installed in the monitored rock-soil mass (b) multiplexing of several FODS units in one optical fiber.
design of sensors, sensor calibration and model experiments, field monitoring and data analysis were presented and discussed.
by ODTR, which proved this system was very economical and practical, however, some improvements needed be adopted to reduce the measurement error caused by the optical cable. Zhu et al. [18] inserted a bare optical fiber into a capillary steel tube and formed a bowknot bending modulator at the end of the capillary. As the monitoring method was based on borehole data, the sensor was buried in concrete, the capillary would bend and the geometry of the fiber bowknot decreased correspondingly as the cracks changed. We can know that the productive ability improved, but deficiency still existed for this sensor in monitoring tiny cracks. A novel distributed fiber optic sensor with a six-prism structure was invented to monitor tiny cracks in reference [19], and no a prior knowledge of crack location was required, which was characterized by a high sensitivity for the detection of small cracks whose opening is less than 0.8 mm. For further predicting the landslide deformation, a landslide monitoring early warning system based on macro-bending loss in polymer optical fiber was built, which consisted of three parts: mechanical converter, displacement fiber sensor and short messaging services gateway [20]. The sensor configured in this manner has sensitivity of (5.9 ± 0.2) dB/cm and displacement range of 40 cm. Meng et al. [21] invented a helical structure for a pavement optical fiber sensor based on bend loss. Chen et al. [9] designed a new type of crack fiber optic sensor. The sensing principle is that the optical fiber was wound around the shaft with a constant bending radius and the macro-bending loss was caused by a crack transfer device with a gear, which was well verified by model experiments. It can be seen from the above researches that these bend-loss type fiber-optic displacement sensors have been widely investigated and studied in structural engineering; however, relatively rare studies have been made in geotechnical engineering, such as slopes, foundation pits and dams. In addition, a large amount of researches about these sensors have been done and mainly concentrated on basic theory and laboratory experiments but rarely in field engineering. Remote monitoring of slope movement can be an effective approach for many unstable slopes. Slope movement can be characterized by the depth and areal extent of the failure plane, direction, magnitude, and rate; one or all of these variables can be measured. For deep-seated landslides with multi-sliding surfaces, the real-time monitoring of these variables seemed particularly difficult and important. The authors [22] have previously proposed a new fiber-optic displacement sensor with a bowknot bending modulator and deduced the theoretical mathematical relationship between the light source loss and the sliding distance by simplifying the optical fiber bowknot bending modulator to half of a four-leaved rose curve. The proposed sensor was simply and conceptually studied in the laboratory experiments; however, there existed some problems needed to be solved, such as robustness in field monitoring, determination of the potential sliding surfaces, and paving convenience. In this paper, in order to overcome above these problems, the authors designed a novel quasi-distributed fiber-optic displacement sensor (QDFODS) based on a bend mechanism induced by displacement for monitoring sliding deformation of the rock-soil mass. The aim of the paper is to demonstrate the feasibility and robustness of using the QDFODS to detect the inner deformation of the monitored slope. The
2. Structure and sensing principle of the sensor It is well known to all, bending loss is one of the most significant characteristics of the optical fiber, and the macro-bending loss will occur when the curvature radius of the fiber bending is much greater than its diameter [9]. The main reason for the macro-bending loss is the spatial filtering effect, which is a physical effect caused by the destruction of the total reflection conditions of the wave propagation, resulting in energy radiation outside of the fiber. The greater the degree of fiber bending, the more significant the spatial filtering effect, and the greater the fiber transmission loss. The macro-bending loss α c of the fiber can be expressed as follow [23]:
α c = Ae−BR
(1)
where R is the macro-bending radius of the fiber, and A and B are constants which are related to the fiber types and working states of the light source. Fig. 1a is a schematic diagram of the proposed QDFODS installed in the monitored rock-soil mass. This sensor is a distributed network system that is connected by a plurality of discrete optical fiber displacement sensors arranged on a spatially predicted position in a series structural form, and a public information transmission channel is shared by adopting the time division multiplexing bus topology technology, where the optical fiber plays only a light guiding role in the optical signal but not a sensing role. The several fiber-optic displacement sensor (FODS) units are connected from end to end and fixed to the two stainless steel connectors by binding. The optical fiber cable is connected by a fusion splice in each FODS unit (Fig. 1b). Fig. 2 shows the structure design of the independent FODS unit, which is constructed with stainless steel connectors, protective covers, acrylonitrile butadiene styrene (ABS) plastic pipes, capillary steel pipes and a singlemodule optical fiber with a bowknot bending modulator. The Φ1 stainless steel capillary penetrates through the Φ3 ABS plastic pipe which is extremely vulnerable to shear failure stresses to guarantee that the capillary can move freely in the plastic pipe embedded in mortar. The upper end of the capillary passes through the slot of a stainless steel connector and is bonded to the upper end of the Φ3 ABS pipe. The bottom of the capillary runs through the other connector at the bottom. A single module optical fiber is passed through the capillary and is wound into a bowknot at the bottom outside the monitored segment and placed into a stainless steel cover. The upper end of the optical fiber is connected to a light source detector through a fiber extraction aperture and armored cable. The fiber extraction aperture is closed by epoxy resin and the covers for protecting the bowknot bending modulator and the fiber are fixed to the two stainless steel connectors by banding. Next we will introduce the working principle of this sensor for landslide monitoring in detail. The proposed FODS is installed inside the monitored rock-soil mass (Fig. 3a), the sliding mass will exert a load 2
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similar to the figure eight shape of the fiber optic displacement sensor proposed by Sienkiewicz et al. [16]. The sensor does not require an external mechanism to increase to decrease the bend radius. The authors have conducted the theoretical analysis on this type of displacement sensor with a bowknot bending modulation, and the logarithmic function relationship between the retraction displacement S of the sensor and the relative fiber loss αb was derived as follows [22]:
S = C1 ln(αb + C2) − C1 ln(C2)
(2)
where C1, C2 are undetermined constants related to the fiber types, working states of the light source, and initial loss of the optical fiber, which can be determined through accurate calibration experiments. 3. Laboratory experiments 3.1. Sensor calibration Accurate calibration is required before any sensor is used. As mentioned above, the measured displacement and the relative loss of the fiber optic displacement sensor with a bowknot bending modulator designed in this paper is in a logarithmic relation, and the calibration constants C1, C2 are needed to be determined. The authors have carried out the laboratory calibration experiments on this type displacement sensor in the previous publication [22], and the results showed that when the initial dimensions D0 of the sensor were different, the effective initial measurement displacement, the maximum displacement range and the constants C1, C2 were all different. Therefore, in series of experiments performed later in this paper, the initial dimensions D0 were uniformly set at 34.56 mm, which was characterized by the maximum measurement displacement and effective initial measurement displacement of 36 mm and 0.98 mm, respectively. The calibration constants C1, C2 were determined as 59.952 mm and 15.491 dBm, respectively, and the correlation coefficient R2 was 0.998. The affordable loss resolution of the current interrogator is 0.05 dBm, the corresponding displacement of the sensor is 59.952 × ln (0.05 + 15.491) − 59.952 × ln15.491 = 0.193 mm. Therefore, the minimum displacement accuracy that the sensor can detect is 0.193 mm. However, the 0.1 dBm is considered as the initial significant fiber loss, which corresponds to the sliding displacement of 0.98 mm in the experiments, and is taken as the initial effective measurement displacement.
Fig. 2. Photograph and detailed design of the FODS unit.
on the sensor to cause its shear failure and a sliding distance lAB along the sliding surface. The ABS plastic pipe embedded in the mortar is extremely vulnerable to the shear damage, and the stainless steel capillary penetrates through the ABS plastic pipe; therefore, the capillary is not consolidated with the mortar and can move freely in the ABS plastic pipe. At this time, the capillary will have a corresponding retraction displacement S (namely the displacement of the optical fiber), which causes the curvature of the fiber bowknot to increase sharply and produces a large amount of the fiber loss captured by OTDR (Fig. 3b). OTDR as a non-destructive method for testing needs the access only to one end of an optical fiber. When the failure of fiber properties appears, there is a sharp change on a reflectogram. The OTDR locates the position of each sensing head and measures the induced displacement loss through the Rayleigh backscatter light signal. The optical loss based fiber optic sensor mainly consists of a light source, a bending modulator, optical fibers, and a light source detector. At present, the bending modulator structures mainly include saw-tooth [24,25], waviness, cylindrical shape, figure eight shape [16] and other types. In this paper an optical fiber bowknot bending modulator was designed to increase the sensitivity of the fiber to curvature (Fig. 3b), which is
Fig. 3. Schematic diagram of the FODS subject to a shear failure and the relationship between the sliding displacement and fiber loss (a) principle of measurement of the FODS subjected to a shear failure (b) photograph of the bowknot bending modulator. 3
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Fig. 4. Laboratory sliding damage experiment of the QDFODSs (unit: mm).
were carefully placed vertically into the instrument; meanwhile, light source detector was connected and debugged, and relevant parameters were configured. The hydraulic jack was used for loading and the sliding distances of the sliding masses were measured by the dial indicators. At the beginning of the experiment, only sliding mass 1 was loaded to move approximately half of the maximum measuring range of the sensor; then the sliding mass 1 and sliding mass 2 together were loaded until the sensor was damaged or the fiber loss signal could not be recorded in the light source detector OTDR (Type 6418) purchased from 41st Institute of China Electronics Technology Group Corporation, Hefei, Anhui, China. The sliding distances of the sliding mass 1 and sliding mass 2, and the light loss signal were measured simultaneously. The used fiber mounted of series sensors array is a simple module (Type G652B), purchased from the Wuhan Yangtze Optical Fiber and Cable Co., Ltd., Wuhan, Hubei, China. It is worth noting that the sensors were subjected to shear failure along two different shear planes, and to prevent the connectors of the sensing units (no.1 and no. 2) of the sensors, D1, D2, D3, from being at the shear plane, the bottom part of the no. 1 should be placed in the sliding mass 2 when these sensors, D1, D2, D3 were placed into the instrument. The purpose of this experiment is to discuss the capability and feasibility of the two different types of sensors for monitoring damage from rock mass. According to the calibration result of the sensors, the predicted displacements were computed by Eq. (2) based on the fiber loss collected by OTDR in the experiment, the relationship between the predicted and measured displacements of the sliding masses was given in Fig. 6. It can be seen that the predicted displacements obtained by the sensors increased with the increase of the tested shear displacements of the sliding masses, both exhibited relatively good linear relations, and their fitting curves and correlations were expressed as
3.2. Verification experiment It is well known to all, the occurrence of the discontinuous mechanical interfaces will be responsible for the instability or failure of rock slopes, which directly decreases the integrity of rock mass and changes the internal stress state. Especially, there are multiple discontinuous mechanical interfaces in rock mass, the overall strength and stability of deep rock slopes are greatly reduced. Therefore, in time and accurate forecasting of sliding displacement of rock slopes with multiple discontinuous mechanical interfaces is very important. To investigate the monitoring performance of the proposed QDFODS for predicting the sliding damage of rock mass, the authors designed a reinforced concrete shearing equipment with double shear planes as experimental instrument. The instrument was constructed with four components: sliding mass 1, sliding mass 2, sliding bed and reaction frame (Fig. 4). We fabricated two groups of different types of sensors in the experiment. Group 1 was one FODS with dimension of Φ 75 × 750 mm; group 2 was connected by two FODSs with dimensions of Φ 75 × 250 mm and Φ 75 × 500 mm, respectively. Each group had three sensors, numbered as C1, C2, C3 and D1, D2, D3, respectively. It is relatively common that the shallow sliding of the slope gradually induces the deep-seated overall sliding damage, called as the retrogressive landslide. The numbers 4, 3, 2 and 1 in the Fig. 5 represent the slip order of the sliding bodies of the retrogressive landslide. The failure mode of the retrogressive landslide is as follows: the lower part (slide body 1) slides first, which cause the upper parts (slide bodies 2, 3 and 4) to lose supports in turn and slide. Therefore, the following sliding damage experiment of rock mass was performed to investigate the monitoring effectiveness of these two groups of sensors for this slope failure condition. To begin the experiment, the prefabricated sensor models
Fig. 5. Block model of the retrogressive landslide and its corresponding conceptual experimental model. 4
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sensors C1, C2, C3 cannot be used for slope monitoring with multi-stage sliding. At the moment, the relationship between the predicted displacements and total sliding displacements of the sliding mass 1 and sliding mass 2 together was positively correlated and no breakpoint appeared. The fitting curves were continuous functions, and their correlation coefficients R2 exceeded 0.96, with the maximum and minimum RMSEs of 2.27 and 1.28 mm, respectively, and the positive correlation ratio values were between 0.941 and 1.015, which indicates that both displacements were linearly equal with high correlation. The sensors C1, C2, C3 could determine the magnitude of a rock slope slide but not the position of the potential sliding surface. As shown in Fig. 6b and Table 1, when the sensors D1, D2, D3 of group 2 were performed to monitor the deformation movement of the retrogressive landslide with two-stage sliding, we could observe the two attenuation “steps” of the fiber loss signal during the measurement, which could be used to determine the sequence and positions of the two-stages sliding. The first appearing attenuation “steps” corresponded to the initial-stage sliding and the second appearing attenuation “steps” corresponded to the later-stage sliding. The sensors D1, D2 and D3 were made of two sensing units no.1 (250 mm in height) and no.2 (500 mm in height), respectively; therefore, the position of the sliding surface of the first-stage sliding was within range of 0–250 mm, and the position of the sliding surface of the second-stage sliding was within range of 250–750 mm. At this time, the relationship between the predicted displacements and the total sliding displacements of the sliding mass 1 and sliding mass 2 together was positively correlated but a breakpoint for each fitting curve appeared. The fitting curves were discontinuous functions. It can be seen from Fig. 6b, the displacement prediction on the first-stage sliding of the sliding mass can be determined through the optical loss signal in the sensing unit no.1 of the sensors D1, D2, D3, and the second-stage sliding condition can be reconginzed by the optical loss signal in the sensing unit no. 2. In addition, the sliding displacements of the sliding masses can be effectively determined by the predicted displacements of the sensors, with the maximum and minimum RMSEs being 2.00 and 1.82 mm, respectively, and the positive correlation ratio values ranged from 0.926 to 1.170. Therefore, the sensors D1, D2, D3 can be effectively utilized for slope monitoring with multistage sliding, not only the internal displacements of the slope can be determined, but also the sequence and positions of multi-slip slope surfaces can be identified. The spatial resolution can reach 250 mm, or even smaller, it will be higher than that (generally is 500 mm) of the inclinometer tube and the quasi-distributed monitoring can be realized by connecting a series of sensors with fixed lengths end to end.
Fig. 6. Relationships between the predicted displacements from the QDFODS and the tested shear displacements by dial indicators of the sliding masses (a) group 1 (b) group 2.
follows, shown in Table 1:
yC1 = 0.941x − 0.922, R2 = 0.967, RMSE = 2.27 mm
(3a)
yC2 = 0.966x − 0.232, R2 = 0.985, RMSE = 1.28 mm
(3b)
yC3 = 1.015x − 1.215, R2 = 0.982, RMSE = 1.60 mm
(3c)
y1D1 = 0.926x − 1.558, R2 = 0.983; y2D1 = 1.170x − 26.373, R2 = 0.992, (4a)
RMSE = 2.00mm
y1D2 = 0.991x − 1.227, R2 = 0.994; y2D2 = 0.933x − 21.858, R2 = 0.986, (4b)
RMSE = 1.84 mm
y1D3 = 0.967x − 1.276, R2 = 0.980; y2D3 = 0.982x − 22.996, R2 = 0.969, (4c)
RMSE = 1.82 mm
4. In situ application
As shown in Fig. 6a and Table 1, when the sensors C1, C2, C3 of group 1 were performed to monitor the deformation movement of the retrogressive landslide with two-stage sliding, we could observe the only one attenuation “step” of the fiber loss signal during the measurement. However, this phenomenon (including the one “step” and its attenuation value) could also be caused by the same sensors if only the primary sliding at the one position was generated. Therefore, the
The authors in this section performed the application of the proposed QDFODS in a field slope located at Chongqing city, China (Fig. 7a). The aim of this work is to confirm its applicability and robustness in an actual geological environment and demonstrate workability. The geological structure is simple and no second-order folds and faults are found in the site. The rock stratum of the site is filled with
Table 1 Fitting results of segmented curves of the tested shear displacements and predicted displacements. Test group
Specimen model
Correlation coefficient The first loading
Group 1
Group 2
C1 C2 C3 D1 D2 D3
The second loading 0.967 0.985 0.982
0.983 0.994 0.980
0.992 0.986 0.969
RMSE (mm) The first loading
The second loading 2.27 1.28 1.60 2.00 1.84 1.82
5
Attenuation “step” number The first loading
The second loading Only one Only one Only one
One One One
Determination of sliding surface
Two Two Two
Can not Can not Can not Can Can Can
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Fig. 7. Photograph of the monitored slope site and layout of the monitoring equipment (a) the instrumented slope (b) the crown crack at slope crest (c) borehole (d) layout of the inclinometer and the proposed QDFODS.
and the position of the main potential sliding surface was 1.5–3.0 m underground, and the position of the secondary potential sliding surface was 0.0–1.0 m underground. In general, the accumulated inner deformation and its variation of the monitored slope were small, within an allowable range, and it remained basically stable. However, there was a shape increase of the slope’s deformation in the period of the partial excavation of the second-level slope (21 January to 25 February), which may be due to the fact that the effect of unloading of the slope toe caused by the excavation formed a shear outlet of landslide. Therefore, it was recommended to strengthen the later-stage monitoring of the first-level slope during excavation of the second-level slope to ensure the stability of the slope. We compared the predicted displacements by the QDFODS and the measured displacements by the inclinometer to discuss its feasibility in practical slope monitoring, and the comparison of the displacement profiles with time of two measuring instruments at different depths in the boreholes was shown in Fig. 9. It can be observed that the QDFODS could determine the sliding distances of two depth intervals in the borehole, which were 0.5–1.0 m underground and 2.0–2.5 m underground, respectively. In addition, the estimated displacement variation trend of the QDFODS was nearly identical to the trend of the inclinometer at the location of the main sliding surface; however, their displacement differences still remained. The predicted displacement curve by the QDFODS at the depth of 0.0–0.5 m is similar to that of the inclinometer at the depth of 0.5 m with an average absolute error of 13.53%. Meanwhile, the predicted displacement curve by the QDFODS at the depth of 1.5–2.0 m is similar to that of the inclinometer at the depth of 0.5 m, with an average absolute error of 17.06%. The main reasons were as follows: the proposed QDFODS and the inclinometer were considered as the cantilever beam structures in the slope, but their measurement principles were different. The QDFODS was subjected to shear failure while the inclinometer was bent deformation. The greater flexibility resulted in the greater deformation; therefore, the slope deformation measured by the inclinometer was larger than that of the QDFODS in the same depth range. Besides, the two measuring instruments have their own measurement errors. Through the above analysis, we can conclude that the QDFODS can basically reflect the internal movement of the slope, such as the position of the potential sliding surface and magnitude, which demonstrates that it is robust and capable of monitoring the field slope in actual environment.
debris, and the combination of rock formations is poor. It is mainly composed of artificial plain fill, and the underlying bedrock is mudstone and fine sandstone. The groundwater conditions in the site are poor, there are no phreatic water layer and stable water level, and no faults, landslides, and debris flows and other geological phenomena are found in the site and surrounding area. The slope is currently stable; however, considering the local steep slope and some crown cracks at the slope crest (Fig. 7b), as well as the stability evaluation of the slope site, the monitored slope was excavated with a stepped surface (Fig. 7a). The first-level slope has been completed, and the subsequent second-level slope is being prepared. To monitor the deformation of the first-level slope and the influence of the excavation and construction of the second-level slope on the overall slope stability, three boreholes with diameters of 110 mm were drilled as vertically as possible with a sag deviation of < 2° in the center position of the step between the firstlevel and second-level slopes (Fig. 7c). The FODS units were uniformly prefabricated into the cylinders 0.5 m in length with cement mortar at the construction site, and then the designed QDFODS comprehending eight FODS units was carefully placed into one borehole as vertically as possible. At the same time, an 8 m long inclinometer casing was buried adjacent to the QDFODS for comparison monitoring to further determine the sliding properties of the slope (Fig. 7d). The first monitoring was recorded on 31 December 2018, and by 3 June 2019, we have conducted 13 times data acquisitions including the inner slope displacement measured by the inclinometer and the fiber loss signal obtained from the QDFODS. We mainly focused on the deformation monitoring and analysis on the first-level slope, the relationship curve of the accumulated inner displacement of the slope measured by the inclinometer with the monitoring time was obtained, as shown in Fig. 8. It is worth noting that because there are too many data points, only the data with significant deformation of the slope at different depths are displayed in Fig. 8. It can be concluded that the accumulated sliding displacement of the first-level slope changed litter, the maximum value was 15.25 mm,
5. Discussion This paper proposed a novel QDFODS to monitor sliding deformation of the rock-soil mass based on the previous fiber-optic displacement sensor [22]. The sensor has been proved to be robust and effective in field slope monitoring. However, the advantages and limitations of the QDFODS for landslide monitoring need to be discussed before it can be used in geotechnical engineering. We don’t give the precision comparison results due to being influenced by the many factors, and the qualitative comparisons of the QDFODS and the previous fiber-optic displacement sensor are analyzed and concluded. The literature [22] demonstrated that this type of fiberoptic displacement sensor with bowknot bending modulation has a potential capability to detect slippage damage along the sliding mass. Simple and rough sensor design due to inadequate consideration by
Fig. 8. Relationship between the accumulated displacements measured by the inclinometer and the depths. 6
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Fig. 9. Relationship between the measured displacements by the inclinometer and predicted displacements by the proposed QDFODS at different depths in the boreholes.
paving convenience, determination of the potential sliding surfaces; in addition, the signal processing device is very simple and it is easy to realize wireless signal communication, which suggest that QDFODS has a promising prospect in landslide monitoring. Various optical fiber sensing technologies have been widely used in geotechnical engineering, such as, optical time domain reflectometry (OTDR), Brillouin optical time domain reflectometer/analysis (BOTDR/ A) [3] and fiber Bragg grating (FBG) [2], which make remote, real-time monitoring of slope movement possible. It is well known that FBG and BOTDR/A sensing technologies have remarkable cross-sensitivity to temperature and strain; however, temperature variation will result in a litter change of optical power transmitted in the fiber. A strain-freerelease sensor is usually adopted for temperature compensation without the effect of temperature cross-sensitivity. However, the strain produced by temperature variation is quite from a free temperature sensor as the temperatures underground and at ground level are different. Therefore, the landslide monitoring system based on OTDR technique without the effective of cross-sensitivity can be more accurately compared with other optical fiber sensing technologies. OTDR instrument has a large dynamic range and spatial resolution with a high accuracy for long-distance measurement of several kilometers, tens of kilometers and hundreds of kilometers, especially for the location of reflection events. The problem of resolution in OTDR measurement exists; however, in practical landslide monitoring, the possible location of crack or deformation (specific displacement) can be estimated in advance based on borehole data. The distance of optical fiber in landslide monitoring is usually within several kilometers, so the optimum measurement range is between 1.5 and 2 times the length of optical fiber to be measured. Therefore, the OTDR instrument can be used to detect and improve the accuracy of measurement.
designer brought about some deficiencies that needed to be solved. The fiber-optic displacement sensor cannot be connected in series to explore subsurface properties of slopes with multi-slip surfaces. In addition, the optical bowknot bending modulator is exposed to harsh environments and to protect it is a problem. The Φ2 tube should be pulled out once the mortar around the device reaches the initial setting to ensure that the Φ1 capillary can move freely inside the mortar, resulting in more work and difficulty. Therefore, the above related investigations about this sensor were mainly performed on basic theory and laboratory experiments due to the design limitations. Compared with the previous sensor [22], the QDFODS was designed with two stainless steel covers to protect the optical fiber and bowknot bending modulator and thus was robust in a harsh environment. The QDFODS comprehending several FODSs in series configuration can be used to monitor deformation of deep-seated landslides, which has been verified by a short-term monitoring result of a field slope engineering. Besides, the QDFODS models can be prefabricated at the construction site for paving convenience. This configuration that several fiber optic displacement sensors are disposed in series is common and reported in many publications. For instance, a quasi-distributed displacement-sensing configuration comprehending four displacement sensing heads along a standard single mode optical fiber in several locations with different intervals was presented which was characterized by maximum displacement response of 120 mm with a sensitivity of 0.027 dB/mm [26]. The use of a multiplexed fiber optic bend-loss type sensor with five sensor heads constructed by using only one optical fiber sensing line [15], which employed OTDR equipment to point-wisely measure the displacement of large structures such as bridges and buildings, was reported in 2006. This sensor designed in this paper is similar to these two cases. For landslide monitoring, localized or quasi-distributed sensors based on borehole monitoring is the common and cost-effective means, such as, probe inclinometer or in-place inclinometer, tiltmeters, TDR cable, FBG-based sensors [27–29]. Probe inclinometers need manual operation and cannot read data automatically and electronically. Inplace inclinometers are installed in the borehole with inclinometer casing, tilemeters are mainly mounted on the surface of the rock and soil to be measured, and TDR based on coaxial cable can automatically measure the slope, and its price is cheaper than inclinometer casing, but the actual sliding amount and direction of the slope cannot be determined. FBG-based sensors can realize multi-point measurement simultaneously by a single sensing system, which benefits from multiFBGs manufactured in a single fiber. Their higher sensitivity and precision make them to be widely used in civil engineering; however, the price is more expensive than the mentioned above. The QDFODS has a relatively low cost of $ 0.45/m and advantages of simple package,
6. Conclusions This paper reported a QDFODS using the macro-bending loss of an optical fiber for landslide monitoring. The laboratory experiments and field monitoring application of the QDFODS were performed in detail, the following conclusions are obtained: (1) The single FODSs (C1, C2, C3) could determine the magnitude of a rock mass slide with a ratio between both predicted and measured displacements ranging from 0.941 and 1.015, but not the positions of multi-slip slope surfaces, which was characterized by the maximum measurement displacement and effective initial measurement displacement of 36 mm and 0.98 mm, respectively. (2) The QDFODSs (D1, D2, D3) could be effectively used for detecting the multi-stage sliding of the rock mass. The sliding displacements 7
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of the sliding masses can be determined by the predicted displacements by the sensors, both ratio values were between 0.926 and 1.170. The positions of the sliding planes were deterimined with a spatial resolution of 250 mm, or even smaller. (3) The progressive deformation of the monitored slope in a short-term period was effectively predicted by the QDFODS, including the position of the potential sliding surface and magnitude, verifying that it is robust and reliable for monitoring the field slope in actual environment.
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CRediT authorship contribution statement Yong Zheng: Conceptualization, Data curation, Formal analysis, Writing - original draft. Zheng-Wei Zhu: Funding acquisition, Resources, Supervision. Wang Xiao: Investigation, Methodology, Project administration. Dong-Ming Gu: Writing - review & editing. Quan-Xiang Deng: Investigation, Project administration. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work is financially supported by Chongqing Natural Science Foundation of China (no. cstc2018jscx-msybX0271) and National Natural Science Foundation of China (no. 51478066). References [1] T.G. Tang, Q.Y. Wang, H.W. Liu, Experimental research on distributed fiber sensor for sliding damage monitoring, Opt. Laser Eng. 47 (1) (2009) 156–160. [2] Y. Zheng, Z.W. Zhu, W.J. Li, D.M. Gu, W. Xiao, Experimental research on a novel optic fiber sensor based on OTDR for landslide monitoring, Measurement 148 (2019) 106926. [3] X.Y. Bao, L. Chen, Recent progress in distributed fiber optic sensors, Sensors 12 (2012) 8601–8639. [4] E. Mesquita, T. Paixão, P. Antunes, et al., Groundwater level monitoring using a plastic optical fiber, Sens. Actuators A Phys. 240 (2016) 138–144. [5] H. Cao, Y. Chen, Z. Zhou, G. Zhang, Theoretical and experimental study on the optical fiber bundle displacement sensors, Sens. Actuators, A Phys. 136 (2) (2007) 580–587. [6] S. Binu, V.P.M. Pillai, V. Pradeepkumar, B.B. Padhy, C.S. Joseph, N. Chandrasekaran, Fibre-optic glucose sensor, Mat. Sci. C-Mater. 29 (1) (2009) 183–186. [7] C. Zhu, Y.Z. Chen, Y. Du, Y.Y. Zhuang, F.X. Liu, R.E. Gerald, J. Huang, A displacement sensor with centimeter dynamic range and submicrometer resolution
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