FBG sensors for seismic control and detection in extradosed bridges

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#### International Journal on Smart Sensing and Intelligent Systems

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VOLUME 14 , ISSUE 1 (Feb 2021) > List of articles

### FBG sensors for seismic control and detection in extradosed bridges

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 14, Issue 1, Pages 1-13, DOI: https://doi.org/10.21307/ijssis-2021-013

Received Date : 18-March-2019 / Published Online: 08-July-2021

### ARTICLE

#### ABSTRACT

Robust fiber Bragg grating (FBG) sensors network to civil engineering structures is presented as real-time monitoring deviation against seismic effects. The network is based on FBG sensors. The base element is a special type of chirped FBG that is validated. The developed network is applied in one of the two towers of concrete and extradosed type of Rades-La Goulette Bridge in Tunisia that in aggressive environment, to enhance the installed conventional structural health monitoring system (SHMS). Precisely, tilt influences of seismic parameters are calculated. Test procedure and obtained results are discussed.

## Introduction

Structural health monitoring (SHM) has become increasingly valuable in recent years and is starting to be widely used in the field of structural engineering applications (Rodrigues et al., 2010). However, the necessity to have the precision resolution in real-time way in monitoring applications requires the manufacturer to look for new technologies. The novel technology found is the fiber Bragg grating (Sun et al., 2007; Vorathin et al., 2019). The implementation of such technology at design stage of the civil engineering structures is a good practice to the Master of the work which provides detailed knowledge of the behavior of these structures dice their exploitation in real-time way.

Actually, the fiber Bragg grating (FBG) technology has enormous progress to meet the requirements of industrial applications thanks to their advantages like great resolution with precision, high sensitivity, immunity from electrical and magnetic interference (Shen and Shen, 2008) and multiplexing (Kang et al., 2005). It mixes the optical sensing with the optical communication (Li et al., 2011). The FBG sensors can easily measure with proper installation: temperature, strain (Kerrouche et al., 2009), pressure, frequency, chemical, biological, biomedical, rate, flows, etc. But temperature and strain still the base of any FBG sensor. However, the design of the FBG uniform does not remain stable over time or at elevated stress. That is why we can have false results. To beat this difficulty, we proposed and developed a new design of FBG rather than the uniform type (Lu et al., 2008; Palaniappan et al., 2007). It is a special chirped FBG.

In the first part of this work, we present the new design of the FBG sensor which is validated. It gives a linear response to the strain and/or to the temperature with acceptable sensitivity in compared with all recent publications in this field. This element is the base element of the robust FBG sensors network that is applied, in a demonstrative example, in civil engineering structure in the second part of this work as SHMS. The test structure is one of the two towers of the bridge body of Rades-La Goulette in Tunisia. This work is the first of its style in Tunisia. The developed network will be used as little system for SHM applications for real-time monitoring. And so, the ultimate goal of this research is to improve the role of the conventional monitoring system that is already installed in this structural engineering (Kang et al., 2005; Kerrouche et al., 2009; Li et al., 2011; Lu et al., 2008; Palaniappan et al., 2007; Piot, 2009; Rodrigues et al., 2010; Shen and Shen, 2008; Sun et al., 2007; Vorathin et al., 2019), and to strengthening detections more selective and precise. The system proposed has been tested under particular conditions, where the tower is stressed.

This particular condition is the seismic problem, and for the first time their effect is calculated in civil engineering structure body using the technology FBG specially using our proposed SHMS since our location, the Mediterranean, in one of the locations that is subject to earthquake effects and their happening risks increase from one year to another in coastal areas. Therefore, the need for such a precise structural health monitoring system (SHMS) in all engineering structures like a bridge is mandatory. This little SHMS allows us to appreciate, continuous, the ability of the service of the tower when the bridge is completely installed, during his life, where we quantify the normal and exceptional vertical or horizontal tilt sustained by the structure body by an earthquake. Also this proposed SHMS able to indicate the potential and the degree of such effect. On the other hand, the first Bridge that used the FBG technology for its structural monitoring is the Beddington Trail in Canada (Raikar et al., 2011) where the manufacturers used 20 FBG sensors to measure the temperatures and strains.

Therefore, our purpose is to validate an SHMS based on FBG technology in engineering structures like bridges, stadiums, and buildings, and the test procedure and results obtained are discussed in detail. The error range found by this technology does not exceed 10 to 12. In Addition, our little SHMS allows us, absolutely, to reduce the cost of the monitoring and maintenance. On the other hand, in such structure engineering applications, the exact study of utilized systems and FBG sensors locations has an essential role to have the desired efficiency and efficiency monitoring.

## Special chirped FBG sensor

As a definition, the Bragg grating is a spectral filter that allows a part of the incident signal to be reflected and etched in the transmitted signal, see Figure 1. The central wavelength of this reflected and etched part is (Kang et al., 2005; Kerrouche et al., 2009; Li et al., 2011; Lu et al., 2008; Palaniappan et al., 2007; Piot, 2009; Raikar et al., 2011; Rodrigues et al., 2010; Shen and Shen, 2008; Sun et al., 2007; Vorathin et al., 2019):

$.(1)λB=2neffΛ(z)$
(1) with λ B is the central wavelength of the spectral signal reflected and etched by the Bragg grating, n eff is the effective refractive index of the fiber core, and Λ(z) is the grating period. The last is a constant in uniform case. In this work we have developed a new type which is a special chirped Bragg grating where the grating period is defined with:
$(2)Λ(z)={Λ0(1−cpz)for[0...z2]Λ0'(1+cpz)for[z2...z]$
(2) with Λ0 and Λ0′ are the nominal grating periods and c p is the chirp coefficient. It is defined in nm/cm. On the other hand, all the physical parameters of an FBG can be varied: profile of the effective refractive index, profile of the effective refractive index modulation, length, apodization, chirp coefficient, and whether the grating has a counterpropagating or copropagating coupling at a Bragg wavelength (Hill et al., 1997; Suresh and Tjin, 2005). For our proposed design of FBG, it watches a good performance. Figure 2 presents their reflected signal without the need for the apodized function. The reflected signal is calculated basis in matrix solution with the following parameters: Λ0 = 0.53 µm, Λ0′ = 0.5284 µm, c p = 1.5 nm/cm, n eff = 1.456, length of 4 mm, and average refractive index modulation equal to 2.5 × 10-4. And so we have λ B = 1.5424 µm. From Figure 2, we have the same shape of reflectivity if we compare it with reflectivity that is from the conventional shapes of FBG that are described in all research works (Kang et al., 2005; Li et al., 2011). Also, we have a reflectivity in the order 100%. In addition, our design presents robustness as the random fluctuations that are produced for different noises to the grating period, Λ(z), therefore automatically to the effective refractive index within a range ~ ±0.03%, which is a high value, of Λ(z) have not effect in any way the structure of the sensor design. In addition, if we exceed this value the fluctuations would destroy the period structure and divide the whole grating into lots of pieces, which results in interference among those pieces. So, we must be sure of the fluctuations values in the manufacturing process. However, our sensors design gives a large margin of security in the manufacturing process. On the other hand from the reflective spectrum of our FBG sensor, FWHM has a value of 0.226 nm which is very little value and can increase the multiplexing solution. So this proposed FBG is suitable for optical communication with grate long-term robustness.

##### Figure 1:

Illustration of the functional principle of FBG sensors.

##### Figure 2:

Reflective spectrum of FBG sensor.

On the other hand, we can characterize the robustness of our design by calculation the coupling coefficient, k. Basis in several references (Aubin, 2009; Hill et al., 1997), we can express this coefficient as:

$(3)K(z)=πδ¯neff(z)λB,zν$
(3) where λ B,z is the central wavelength of each uniform Bragg section in matrix solution, υ is a term of coherence which is taken equal to 1 and $δ¯neff(z)$ described the profile of the effective refractive index modulation, also for each uniform Bragg section.

In our case, we use an SMF doped-germanium optical fiber. The radius of the fiber core is equal to 4.6 µm, that of the optic cladding is of the order of 62.5 µm and that of the mechanical protective cladding is 125 µm. This type of fiber and the parameters mentioned above are used in the SHMS that will be presented in next sections of this paper.

In this part, we calculate the strain and temperature sensitivities in our FBG which acts as a sensor for monitoring applications. We remember that these sensitivities conduct to shift in Bragg wavelength, which is the basic function of an FBG sensor, as indicate the following expression (Kersey et al., 1997):

$(4)ΔλB=2neffΛz((1‒[neff22(p12‒v[p11+p12])])ε+[α+dneffdTneff]ΔT)$
(4) with Pij are the Pockel’s coefficients, υ is the Poisson’s ratio, ε is the applied strain, α is the fiber linear thermal coefficient, and ΔT is the temperature change. In addition, we can make the last expression simpler as (Vorathin et al., 2019):
$(5)ΔλBλB=(α+ξ)ΔT+(1‒ρ)ε$
(5) with α is the fiber linear thermal coefficient, ξ is the thermo-optic coefficient and $ρ=neff22(P12−v[P11+P12])$ is the effective photo-elastic coefficient (Kersey et al., 1997; Shen and Shen, 2008). This last has a numerical value; it is varied about 0.22 (Aubin, 2009) and 0.26 (Li et al., 2011) according to the material of the fiber. The sensitivities found are 1 pm/µε and 10 pm/°C, respectively, for strain and temperature as shown Figures 3 and 4.

##### Figure 3:

Strain performance of ICFBG sensor.

##### Figure 4:

Temperature performance of ICFBG sensor.

All the types of FBG as apodized, chirped, uniform, etc. are performing and make an accurate measurement, but our FBG is more robustness and their lifetime is more important even under continuous stress. And the obtained results confirm their good performances and accurate measurement even under random fluctuations. This new sensor is suitable for both optical communication and optical sensing in health monitoring applications due to the acceptable obtained sensitivities to strain and temperature, also due to the weak FWHM. On the other hand, in our SHMS installation, presented in the next section, our basic design is our FBG with all parameters defined above. In addition, we take FWHM as 0.3 nm instead of the real value of 0.226 nm for safety reasons when applied multiplexing.

## FBG sensors as SHMS in bridges

As we have talked before, the first bridge that used the FBG technology for its structural monitoring is the Beddington Trail Bridge in Canada. In addition, this is the first extradosed concrete road bridge built in Canada. Also, it is defined as the first smart highway bridge in Canada since it uses a smart SHM system. It began service on November 5, 1993. It uses 20 sensors for measuring strain and temperature along the whole of its length. An image of this bridge which has an average length of 21.03 m is shown in Figure 5. In addition, Table 1 gives other examples of bridges that use the FBG technology as the basis of its SHM system. This table is considered in agreement with the work of Rodrigues et al. (2010).

##### Table 1.

Examples of bridges that use the FBG technology as the basis of its SHMS.

##### Figure 5:

The Beddington Trail Bridge in Canada (Khalil et al., 2016).

On the other hand, Table 2 gives some examples of bridges that use fiber optic technology, and not the FBG technology, as the basis of his system of SHM. This table is also considered in agreement with the work of Rodrigues et al. (2010). And it is very clear from the two tables that the number of sensors in bridges using FBG is much more important than other technologies. This indicates that the technology is booming and very effective. It is growing from one year to another. On the other hand, all the technologies presented in this section are based on optical fibers includes the FBG. Thus, the measurement parameters for these different technologies as the SHMS are based on the different properties of the light propagating in the fiber include phase, intensity, wavelength, and polarization. As an example, the interferometric sensors and the Low Coherence sensors detect the light phase, while our FBG sensor detects the wavelength shift in agreement with the external factor. In addition, the FBG technology is the most effective and can be applied in structural supervision, specifically in civil structures, i.e. bridges as we have seen before. And in the same line, in the following section, we describe the bridge Rades-La Goulette in Tunisia, which is the first of its style in Africa with its system of SHM.

##### Table 2.

Examples of bridges that use fiber optic technology, and not the FBG technology, as the basis of SHMS.

## Rades-La Goulette bridge in Tunisia

Bridge Rades-La Goulette is the first of its style in Tunisia, and even in Africa. It belongs to the family of concrete extradossed bridges of stay-cable where the deck is suspended by cables from two pylons. This structure is opened to traffic on March 21, 2009. And the final construction cost is approximated by 100 million \$. For the location, the bridge spanning the channel of Lake Tunis, where he connects the area of Rades to the area of La Goulette. The main bridge has a length of 260 meters, a width of 23.5 meters, and a height of 20 meters. It is located in a coastal aggressive environment, see Figure 6. The opening movement is delayed for two years after the initial date of completion. The reason is certainly the nature of the soil, which is very fragile and aggressive. A general picture of the bridge is shown in Figure 7.

##### Figure 6:

Location of Rades-La Goulette Bridge in Tunisia.

##### Figure 7:

General illustration of the Bridge Rades-La Goulette and their two towers (a) demonstrative model, (b) and (c) realized model.

The semi-maritime environmental feature of the bridge and its location geotechnical cause rigorous aggression on its construction. All these properties absolutely accelerate aging. That is why Tunisia has decided to equip it with a system of SHM. On the other hand, manufacturers taking into account the respect of the seismic conditions of work and block their lateral movement. And for the SHMS, manufacturers install throughout the main bridge 55 sensors and a dozen cameras. These devices are connected to a control room where they allow management measured to trigger alerts and alarms in case of the presence of anomaly data. And all the devices of the SHMS are installed on a structure or in different spans of the structure under construction. Table 3 summarizes the various sensors installed in the bridge. This table is similar to that presented in Piot (2009) where the total number of sensors installed is 55. And outside of the measured parameters, we can classify the sensors according to the location where we can find two types. The first is installed on the bridge body, and the second is installed inside the bridge body. The first type, it is intended to measure the phenomena that affect the bridge body, such as wind and ambient temperature. The second type gives the responses of the bridge body against certain parameters such as loads, accelerations, strains, inclinometer, etc. Similarly from the table, the sensors can be classified also according to the static or dynamic measure. For the first type, the data are kind of slow. We can tell they are made with periods that exceed 10 min as the temperature and inclinometer pylons. And for the second type, the data are kind of fast. We can tell they are made with less than 1 sec as the wind and acceleration periods.

##### Table 3.

The various sensors installed in the Rades-La Goulette Bridge with these measurement parameters.

On the other hand, according to Table 3, we can know the places of installation of all the sensors:

• 2 anemometer sensors: they are of ultrasound type. They are located on the deck to measure the direction and speed of the wind. These last two parameters can influence and biases the bridge body.

• 12 load cell sensors: they are installed in the stay cables to monitor the load that they carry.

• 6 displacement sensors: they are installed in the end pieces of the deck. They give an idea of whether or not the support devices work properly and the thermomechanical behavior is in order.

• 5 low-frequency accelerometer sensors: they are installed in the deck to check the spectral response of the latter.

• 4 inclinometer sensors: they are located in the two towers. These sensors are used to calculate the rotations of these towers according to two axes.

• 7 vibrating wire strain sensors: they are installed in the concrete deck to measure the evolution of the constraints that exist.

• 19 temperature sensors: 18 sensors provide thermal information throughout the bridge body. They are installed in the concrete, the stay cables, and the support struts in addition to 1 sensor for the environment temperature which is installed on the bridge body.

On the other hand, for each sensor suppliers combine two terminals between which the sensor can grow without triggering an alert. These two terminals are defined by the providers and can set from the results obtained in experiments testing with a learning period. They present the safety margin of a sensor. And so in the case of exceeding one of the two terminals, alerts are instantly displayed in the general interface of the control software. And then the control software can send alerts or reports to the responsible.

## Result of integration of special chirped FBG sensors network on concrete extradosed tower under seismic effects

### Definition

In the conventional SHMS installed on the bridge Rades-La Goulette, we find a rotation control of the two towers along two axes with 4 sensors of type inclinometer sensors, 2 sensors for each tower. These sensors provide highly accurate results. However, we are interested to seismic effects on the inclination of the towers with FBG technology as the SHM system. And for the first time, according to our knowledge, the effect is calculated in civil engineering in the structure body using FBG and specially using our SHMS, which will be shown in the next section, because our location, Mediterranean, is one of the places which are subject to the effects of the earthquake and these risks occur increase from one year to the next year in coastal areas. Therefore, the need for such SHMS with precision in all structures like the bridges is required. And yet the large influences of earthquakes on structures, manufacturers do not include the measurement and detection of Earthquake effects during the construction of the bridge structure of Rades-La Goulette.

On the other hand, there are several types of towers. The type is selected depending on the application and depending on the location and environment. For example, we found towers: extradosed (Piot, 2009), concrete (Rodrigues et al., 2010), and steel, etc. Figure 8 gives an illustration of the towers in marine and terrestrial environments. As shown, for a sturdy tower, it must define a perfect distance under the sea level or under the ground level. For our studied tower, it is one of the two towers that constitute the body of Rades-La Goulette Bridge, which is of type extradosed. The tower length is 43 meters above sea level, it is distinguished by its triangular shape from the bridge deck, see Figure 7. And as we cannot work with the real tower, we are forced to use an imitated model for the simulation.

##### Figure 8:

Illustration of towers in (a) marine (www.dtrf.setra.fr) and (b) terrestrial environment (www.bv.transports.gouv.qc.ca).

To make a full monitoring of deflections from the vertical position of the tower, we propose to use three sensors named S1, S2, and S3 of type FBG sensor that presented in the first section of this paper. However, we are interested in computing only the sensitivity of strain which is 1 pm/με. In addition for reasons of cost and multiplexing, we use the three sensors of the same sensitivity to temperature and strain but with different Bragg wavelengths. This system of three FBG sensors network which is installed in a single optical fiber is our SHMS for seismic effects, see Figure 9. And the fiber parameters are the same as used in the first section. For our test, the three central wavelengths are: 1.5401 μ m for S1, and 1.5424 µm for S2, and 1.5449 µm for S3. These values are verified by simulation and by an optical spectrum analyzer (OSA). However, to have these three different central wavelengths, we make a slight stretching for the optical fiber for both side of the location of the Bragg grating in the manufacturing process of each FBG sensor, well as according to the wavelength that we desired to have and also according to our margin wavelength and the multiplexing way. In addition, for the three sensors, the FWHM value is taken equal 0.3 nm instead the real value of 0.226 nm. This value is effective for the reasons of safety and of multiplexing, if the number of sensors installed in the optical fiber is increased more. And the positions of these FBG sensors are located, assumed at the time of construction of the tower, as follows:

• The sensor S3 is installed in the bottom of the tower, i.e. 5 meters below sea level in compared to the actual tower.

• The sensor S2 is installed almost in the middle of the tower, i.e. 21.5 meters above sea level compared to the actual tower.

• -The sensor S1 is installed in the upper part of the tower, i.e. 42 m above the sea level in compared to the actual tower.

##### Figure 9:

Three FBG sensors network multiplexing in a single optical Fiber as SHMS for seismic effects.

Figures 9 and 10 illustrate the installation of the network of FBG sensors with multiplexing into the optical fiber and the installation of the latter with the sensors in the tower. On the other hand, the tower is installed in a coastal area. So it is in a semi-marine environment and to make it strong, it must be set in the perfect distance below the level of the sea. Similarly, it should mention that the total length of the tower has a large influence on the results of the sensors. Thus, this small SHMS allows us to appreciate, in continuous, the service capacity of the tower, and so the bridge, during his life, where we quantify the normal and exceptional vertical tilt supported by the body of the bridge due to an earthquake.

##### Figure 10:

Illustration of the SHMS installed into the tower to measure deflections from the vertical position due to an earthquake.

Otherwise, for the function of our SHMS, any effect due to the seismic parameters will exert a stress round about the three FBGs which constitute our SHMS. So shifts in the three Bragg wavelengths will be realized. Each shift is realized according to the power of the seism and according to the position of the FBG sensor. And the measure of the shift with OSA quantifies the deviation angle and thus estimates the service status of the bridge. The following paragraphs describe our tower under seismic problems that are increasingly actually and especially in the future because of environmental changes and the greenhouse effect. And for the first time, the seismic effects are calculated in civil engineering structures using the technology FBG. In addition, to accomplish the control task, we use measuring equipments in addition to the OSA: Laser Source, coupler, PC, and the connection of the optical fiber.

### Results under seismic effects

Firstly in this section, we define the various parameters of an earthquake. These parameters are:

• Focus or hypocenter: it is the fault zone where product failure. This area is the source of seismic waves.

• Epicenter: this is the area of the earth’s surface located vertically at the hypocenter. Geologists indicate that in this area the earthquake intensity is the largest.

• The magnitude: this is a measure of the energy of an earthquake. It is measured by the degree unit. And now, all energy of an earthquake is measured by the open scale named Richter. According to this scale, the increase of an earthquake by one degree is equivalent to multiplying by 30 the energy released by the previous degree.

• The intensity: this is an approximation parameter for the effects of an earthquake on the soil. It is usually measured by European macroseismic scale (EMS) which includes 12 degrees, wherein the first degree means an earthquake with imperceptible tremors and the last means a total change of the landscape.

• Frequency: this is the measured frequency of an earthquake.

• The duration of vibration: this is the time between the flow and the end of an earthquake.

In general, the seismic frequency is very variable and is about a few Hz. It depends mainly on the distance from the epicenter, the type of earthquake, and also the effects of sites namely: the amplification of the wave, bedrock vibrates at high frequency and low magnitude, whereas the soil vibrates at low frequency but with a high magnitude. In addition, when the seismic degree exceeds about 6° on the Richter scale, according to the history of earthquakes, we are not talking about bending or tilting of the tower since we have a destruction of the structure with a high percentage. For our application, we have chosen the parameters of our earthquake applied to our tower model as 60 km as the distance between the seismic epicenter and the location of the tower, the main frequencies of 5 to 25 Hz, and the magnitude from 0 to 4 degrees in the Richter scale. The last parameter defines quantitatively and characterizes the energy released by the earthquake. In the Richter scale and during the transition from one level to another higher level, the energy released is multiplied by 30. The duration of each test degree is chosen between 3 and 13 sec. And in the case of an experimental imitate model with a reduction scale and to be in line with an imitate reality and also to apply the proper frequencies of the seismic problem; we can install the imitate model of the tower in a sand/clay mixture in a little big water pregnant. The earthquake is provided thanks to the vibrating membrane and a semi engine that is located under the epicenter point, and the waves and their frequencies of seismic waves delivered to the semi-engine and so to the vibrating membrane are provided by a GBF of 5 to 25 Hz. And in this test, this multiplied energy is realized by the semi-engine characteristics.

Before seeing the response of the FBG sensor network, we simulated the points where the three FBG sensors are installed in order to calibrate results thereof. These points are defined as points of reference. The results of the tower response in these points when the seismic degree increases from 0° to 4° in Richter scale are shown in Figures 11-13. And according to the vertical deviation which is shown in these latter simulations, we calculate automatically the degree of tilt as shown by the curves in Figure 14. Specifically, according to the curves in Figures 11-13, it is clear that the three positions give three different deviation values. These values increase when the earthquake degree increases. The combined point with the sensor S1 which is installed in the upper part of a tower provides the highest value of deviation for each earthquake degree in comparison with the other two points. In addition, the combined point with the sensor S3 which is installed at the bottom of tower gives a lower value of deviation for each earthquake degree in comparison with the other two points. But from Figure 14, the three curves of the deflection angle provided by the three points are nearly the same. This indicates that we have good results and our simulations are in agreement. However, if we see well, these three curves depart from one another if more increases the degree of the earthquake. This is explained by the presence of cracks where its values increase progressively with the growth of earthquake degree. In the same context, we comment from our results of Figure 14, that when we pass from degree to the next degree, results of deviation and the deflection angle become very large relative to the previous measurement.

##### Figure 11:

Deviation response at the point where the sensor S1 is installed under seismic effects.

##### Figure 12:

Deviation response at the point where the sensor S2 is installed under seismic effects.

##### Figure 13:

Deviation response at the point where the sensor S3 is installed under seismic effects.

##### Figure 14:

Deflection angle of the tower given by the three points of reference where the sensors S1, S2, and S3 are installed in term of earthquake degree.

Now, we see the simulation results for our SHMS of the three FBG sensors under the seismic influence. The results of the simulation are presented in Figure 15. From the curve presented, which is the same for the three sensors, we note that the shift in the wavelength increases with an increasing degree of the earthquake. Specifically, this increase becomes increasingly important if the earthquake passes from one degree to the next degree. And for the first degree, we have a shift of 10 pm. And for the second degree, we have a shift of 30 pm. And for the third degree, we have a shift of 80 pm. And for the fourth degree, we have a shift of 290 pm. This is quite normal because if the level increases by one degree to another degree, the effects become important. In addition, the curve shown in Figure 15 is similar in behavior to the curve shown in Figure 14.

##### Figure 15:

Shifts of the wavelengths of the three FBG sensors network constituting the SHMS for seismic effects.

In order to calibrate the results of our SHMS with the results of tilt angles given by the reference points, we have the curve that shown in Figure 16. The obtained curve is a straight line which passes through the origin of equation:

$(6)DAngle=4.285×10−4×Wshift$

##### Figure 16:

The deflection angle of the tower as a function of wavelength shift of the FBG sensors constituting SHMS for seismic effects.

with D Angle is the tilt angle of the tower and W shift is the shift of the wavelength of any FBG sensor. And with a spectrum analyzer of 1 pm as resolution, the responsible of the structure can notice an inclination of 0.00025° in the tower. On the other side hand, to perform the operation of the network FBG sensors used as SHMS, a conditioner for the equation is necessary. Furthermore, we apply only low degree earthquakes which allow our FBG sensors to make shift based on the realized strains. Thus, the tilts and bending of the tower according to the equation produced. On the other hand, it is clear from the obtained results that when the seismic degree increases perceived shocks increase more and more and so the tilt angle increases significantly. In addition, the cracks will become bigger and their effect will be severe on the life of the tower. And if we exceed 4°, the tilt will become very important and if we exceed 6 to 7°, the tower will be destroyed by a large percentage and sensors give answers that are not understandable.

The obtained results are quite normal and consistent with the prediction results but they are given in a very precise manner with the network of FBG sensors. We can say that this small system of three special FBG sensors works properly as SHMS for tilt measurement caused by seismic effects and even by other effects of the same power. Thus, the results obtained in real-time confirm that the model FBG is Smart Sensor (Measures et al., 1994).

## Conclusion

Our goal is to validate a proposed SHMS in civil engineering structures such as bridges, stadiums, and buildings for seismic effects. Test procedure and results obtained are discussed in detail. The studied structure is one of two towers of Rades-La Goulette Bridge, which is installed in aggressive environment and coastal area. In addition, this bridge is the first work of its style in Tunisia and in Africa. On the other hand, the manufacturers do not take into account the control and the detection of the seismic effect in the installed SHMS, however, the seismic risk exists. The proposed SHMS is based on FBG technology, especially a new FBG design. This design is efficient as a strain and temperature sensors. Also, it is expand to the field of civil engineering. So, this paper provides a perspective for the construction of new civil engineering structures based on FBG sensors technology proposed as an SHMS in an aggressive environment, where an improve in the role of the conventional monitoring system, as electric monitoring, and strengthening detections more selective and precise is warranty.

The little SHMS network proposed of three FBG sensors is installed into the tower. The tower is stressed with seismic effects. As we know their happening risks increase from one year to another in coastal areas. The generated effects are mainly: flexion, deviation, tilt, and crakes. These effects are variables depending on the nature of the land crossed by seismic waves, the distance from the epicenter, the depth of the tower under and above the sea level and also the vulnerability of buildings of tower. In addition, we can mention that the depth of the tower under the sea level affects the obtained results and not the efficiency of the sensors used. For us, we are interested mainly in the tower deviation from its vertical position. The obtained results are the results of an imitate model where the FBG sensors allow us to see the tilt effects of seismic waves on the tower in each degree. They show high efficiency and thus allow a real time monitoring to the structure. In addition, these results are compatible with those expected because our little SHMS is based on FBG sensors characterized by error range does not exceed the 10-12, although imitate model do not take into account the exact topology between the seismic epicenter and the position of the tower where may be the seismic wave undergoes slight amplification. In addition, the bedrock of the tower is not defined exactly. Similarly, our results are confounded with the scale of seismic intensity used in Europe: EMS. Also, it is important to know that an earthquake is often followed by aftershocks. It should be expected. The aftershocks of magnitude are generally lower that the initial earthquake. In addition, in this part, we do not talk about the hydraulic system of a tower in semi-maritime zone. Otherwise, from observing the effects of an earthquake by FBG sensors network, we can characterize the severity of earthquake in surface.

The proposed SHMS network can be investigated too in all body of Rades-La Goulette Bridge but with a large number of FBG sensors to replace the maximum number of 55 conventional sensors which are installed as conventional SHMS and to ensure entire coverage of the bridge to monitoring: load, strains, temperature, cable-stayed extensometers, tilt, accelerometer, force, etc. But in this case, the result of tower tilts will be different because we have a new hydraulic system that is installed that respects the equilibrium and giving more rigidity to the tower. Also, we can apply this concept of FBG network to calculate the tsunami effects that attack the coastal area structures. Otherwise, the environment of our example is an earthquake zone nevertheless not subject to cyclical seismic vibrations being in a coastal area where the most from soils subjected to cyclic seismic vibrations. Thus, the manufactures will follow the rules of earthquake-resistant construction, solid foundation, chaining, since we never know exactly the date of the next earthquake.

## References

1. Aubin, S. 2009. Capteur de position innovants: Application aux Systèmes de Transport Intelligents dans le cadre d’un observatoire de trajectoires de véhicules. M.S. thesis, Toulouse University, France.
2. Hill, K. O. , Meltz, G. and Membre, I. E. E. E. 1997. Fiber Bragg grating technology fundamentals and overview. Journal of Lightwave Technology 15(8): 1263–1276.
3. Kang, D. H. , Park, S. O. , Hong, S. S. and Kim, C. G. 2005. The signal characteristics of reflected spectra of fiber Bragg grating sensors with strain gradients and grating lengths. NDT&E International 38: 712–718.
4. Kerrouche, A. , Boyle, W. J. O. , Sun, T. and Grattan, K. T. V. 2009. Design and in-the field performance evaluation of compact FBG sensor system for structural health monitoring applications. Sensors and Actuators A: Physical 151: 107–112.
5. Kersey, A. D. , Davis, M. A. , Patrick, H. J. , LeBlanc, M. , Koo, K. P. , Member, I. E. E. E. , Askins, C. G. , Putnzm, M. A. and Joseph Friebele, E. 1997. Fiber grating sensors. Journal of Lightwave Technology 15(8): 1442–1463.
6. Khalil, A. H. , Heiza, K. M. and El Nawawy, O. A. 2016. “State of the art review on bridges structural health monitoring applications and future trends”, 11th International Conference on Civil and Architecture Engineering, April 19–21.
7. Li, L. , Tong, X. L. , Zhou, C. M. , Wen, H. Q. , Lv, D. J. , Ling, K. and Wen, C. S. 2011. Integration of miniature Fabry-Perot fiber optic sensor with FBG for the measurement of temperature and strain. Optics Communications 284(6): 1612–1615.
8. Lu, C. , Lu, C. , Cui, J. and Cui, Y. 2008. Reflection spectra of fiber Bragg grating with random fluctuations. Optical Fiber Technology 14: 97–101.
9. Measures, R. M. , Alavie, T. , Maaskant, R. , Karr, S. , Huang, S. , Grant, L. , Guha-Thakurta, A. , Tadros, G. and Rizkalla, S. 1994. Fiber optic sensing for bridges. 4th International Conference on Short & Medium bridges, Halifax, pp. 8–11.
10. Palaniappan, J. , Wang, H. , Ogin, S. L. , Thorne, A. M. , Reed, G. T. , Crocombe, A. D. , Rech, Y. and Tjin, S. C. 2007. Changes in the reflected spectra of embedded chirped fibre Bragg gratings used to monitor disbanding in bonded composite joints. Composites Science and Technology 67: 2847–2853.
11. Piot, S. 2009. Une surveillance d’ouvrages en environnement côtier exemple du pont de Radès – La Goulette à Tunis. Coastal and Maritime Mediterranean Conference, Edition 1, Hannamet, Tunisia, pp. 295–300.
12. Raikar, U. S. , Lalasangi, A. S. , Kulkarni, V. K. and AKKi, J. F. 2011. Concentration and refractive index sensor for methanol using short period grating fiber. Optik 122: 89–91.
13. Rodrigues, C. , Félix, C. , Lage, A. and Figueiras, J. 2010. Development of a long-term monitoring system based on FBG sensors applied to concrete Bridges. Engineering Structures 32(8): 1993–2002.
14. Shen, J. and Shen, Y. 2008. Investigation of the structural and spectral characteristics of deposited FBG stacks at elevated temperature. Sensors and Actuators A: Physical 147: 99–103.
15. Sun, L. , Li, H.-N. , Ren, L. and Jin, Q. 2007. Dynamic response measurement of offshore platform model by FBG sensors. Sensors and Actuators A: Physical 136: 572–579.
16. Suresh, R. and Tjin, S. C. 2005. Effects of dimensional and material parameters and cross-coupling on FBG based shear force sensor. Sensors and Actuators A: Physical 120: 26–36.
17. Vorathin, E. , Hafizi, Z. M. , Aizzuddin, A. M. , Zaini, M. K. A. and Lim, K. S. 2019. Temperature independent chirped FBG pressure transducer with high sensitivity. Optics and Lasers in Engineering 117: 49–56.

### FIGURES & TABLES

Figure 1:

Illustration of the functional principle of FBG sensors.

Figure 2:

Reflective spectrum of FBG sensor.

Figure 3:

Strain performance of ICFBG sensor.

Figure 4:

Temperature performance of ICFBG sensor.

Figure 5:

The Beddington Trail Bridge in Canada (Khalil et al., 2016).

Figure 6:

Location of Rades-La Goulette Bridge in Tunisia.

Figure 7:

General illustration of the Bridge Rades-La Goulette and their two towers (a) demonstrative model, (b) and (c) realized model.

Figure 8:

Illustration of towers in (a) marine (www.dtrf.setra.fr) and (b) terrestrial environment (www.bv.transports.gouv.qc.ca).

Figure 9:

Three FBG sensors network multiplexing in a single optical Fiber as SHMS for seismic effects.

Figure 10:

Illustration of the SHMS installed into the tower to measure deflections from the vertical position due to an earthquake.

Figure 11:

Deviation response at the point where the sensor S1 is installed under seismic effects.

Figure 12:

Deviation response at the point where the sensor S2 is installed under seismic effects.

Figure 13:

Deviation response at the point where the sensor S3 is installed under seismic effects.

Figure 14:

Deflection angle of the tower given by the three points of reference where the sensors S1, S2, and S3 are installed in term of earthquake degree.

Figure 15:

Shifts of the wavelengths of the three FBG sensors network constituting the SHMS for seismic effects.

Figure 16:

The deflection angle of the tower as a function of wavelength shift of the FBG sensors constituting SHMS for seismic effects.

### REFERENCES

1. Aubin, S. 2009. Capteur de position innovants: Application aux Systèmes de Transport Intelligents dans le cadre d’un observatoire de trajectoires de véhicules. M.S. thesis, Toulouse University, France.
2. Hill, K. O. , Meltz, G. and Membre, I. E. E. E. 1997. Fiber Bragg grating technology fundamentals and overview. Journal of Lightwave Technology 15(8): 1263–1276.
3. Kang, D. H. , Park, S. O. , Hong, S. S. and Kim, C. G. 2005. The signal characteristics of reflected spectra of fiber Bragg grating sensors with strain gradients and grating lengths. NDT&E International 38: 712–718.
4. Kerrouche, A. , Boyle, W. J. O. , Sun, T. and Grattan, K. T. V. 2009. Design and in-the field performance evaluation of compact FBG sensor system for structural health monitoring applications. Sensors and Actuators A: Physical 151: 107–112.
5. Kersey, A. D. , Davis, M. A. , Patrick, H. J. , LeBlanc, M. , Koo, K. P. , Member, I. E. E. E. , Askins, C. G. , Putnzm, M. A. and Joseph Friebele, E. 1997. Fiber grating sensors. Journal of Lightwave Technology 15(8): 1442–1463.
6. Khalil, A. H. , Heiza, K. M. and El Nawawy, O. A. 2016. “State of the art review on bridges structural health monitoring applications and future trends”, 11th International Conference on Civil and Architecture Engineering, April 19–21.
7. Li, L. , Tong, X. L. , Zhou, C. M. , Wen, H. Q. , Lv, D. J. , Ling, K. and Wen, C. S. 2011. Integration of miniature Fabry-Perot fiber optic sensor with FBG for the measurement of temperature and strain. Optics Communications 284(6): 1612–1615.
8. Lu, C. , Lu, C. , Cui, J. and Cui, Y. 2008. Reflection spectra of fiber Bragg grating with random fluctuations. Optical Fiber Technology 14: 97–101.
9. Measures, R. M. , Alavie, T. , Maaskant, R. , Karr, S. , Huang, S. , Grant, L. , Guha-Thakurta, A. , Tadros, G. and Rizkalla, S. 1994. Fiber optic sensing for bridges. 4th International Conference on Short & Medium bridges, Halifax, pp. 8–11.
10. Palaniappan, J. , Wang, H. , Ogin, S. L. , Thorne, A. M. , Reed, G. T. , Crocombe, A. D. , Rech, Y. and Tjin, S. C. 2007. Changes in the reflected spectra of embedded chirped fibre Bragg gratings used to monitor disbanding in bonded composite joints. Composites Science and Technology 67: 2847–2853.
11. Piot, S. 2009. Une surveillance d’ouvrages en environnement côtier exemple du pont de Radès – La Goulette à Tunis. Coastal and Maritime Mediterranean Conference, Edition 1, Hannamet, Tunisia, pp. 295–300.
12. Raikar, U. S. , Lalasangi, A. S. , Kulkarni, V. K. and AKKi, J. F. 2011. Concentration and refractive index sensor for methanol using short period grating fiber. Optik 122: 89–91.
13. Rodrigues, C. , Félix, C. , Lage, A. and Figueiras, J. 2010. Development of a long-term monitoring system based on FBG sensors applied to concrete Bridges. Engineering Structures 32(8): 1993–2002.
14. Shen, J. and Shen, Y. 2008. Investigation of the structural and spectral characteristics of deposited FBG stacks at elevated temperature. Sensors and Actuators A: Physical 147: 99–103.
15. Sun, L. , Li, H.-N. , Ren, L. and Jin, Q. 2007. Dynamic response measurement of offshore platform model by FBG sensors. Sensors and Actuators A: Physical 136: 572–579.
16. Suresh, R. and Tjin, S. C. 2005. Effects of dimensional and material parameters and cross-coupling on FBG based shear force sensor. Sensors and Actuators A: Physical 120: 26–36.
17. Vorathin, E. , Hafizi, Z. M. , Aizzuddin, A. M. , Zaini, M. K. A. and Lim, K. S. 2019. Temperature independent chirped FBG pressure transducer with high sensitivity. Optics and Lasers in Engineering 117: 49–56.