Improving Seaport Wharf Maintenance and Safety with Structural Health Monitoring System in High Salt and Humidity Environments

Abstract

Due to the harsh working conditions, the durability of the seaport wharf structure is poor compared with similar hydraulic structures. According to the structural characteristics of coastal port wharf and the particularity of a high salt and high humidity environment, the stress features of the coastal wharf structure are analyzed, and the health inspection indicators of the wharf structure are proposed. A fiber grating sensor-based structural health monitoring system for coastal high-pile piers is established. A corresponding system for detecting structural health is designed according to the standard structural section of the wharf’s front platform. The corresponding monitoring implementation scheme, sensor selection, and performance parameters are proposed. Finally, the realization technology and related indicators of data acquisition and transmission subsystem are given. The experimental results indicate that the waveform of the structural response to the wave load has a consistent sine wave pattern with the actual wave load. The maximum strain of the berthing pier appears at 4.35 m and 6.14 m, and the elevations reach $4.66 \mathsf{\mu }\mathsf{\epsilon }$ and $5.31 \mathsf{\mu }\mathsf{\epsilon }$, respectively. The strain at other positions also has an obvious change trend. The experimental results provide some help for the research of the wharf health monitoring system.

1. Introduction

A pier is a coastal structure that facilitates vessel berthing, goods loading and unloading, and passenger embarkation, making it a crucial component of harbor infrastructure. The stability of the terminal construction is closely related to the security of vessel berthing and loading/unloading operations since the terminal is in charge of loading, unloading, and circulating general products. In order to ensure secure port operations and manufacturing, it is essential to be informed about the safety conditions of the terminal structures. The southeast coast of China and other tropical monsoon climates experience high salt fog, high humidity, and high temperatures. These conditions can cause significant damage to industrial equipment, shortening their service life. To address this issue, anti-rust wax is selected for areas with high humidity, high temperature, and high salt, as it is resistant to extreme corrosion conditions and high permeability, effectively protecting equipment for extended periods. Therefore, it can effectively protect equipment for a long time and solve the problem of anti-corrosion prevention of equipment. However, due to the complex and harsh marine environment in which the wharf is located, the wharf structure not only bears a large load but also withstands loads such as soil, waves, currents, sea ice, tides, typhoons, earthquakes, ships, etc. Under harsh environmental conditions, the wharf structure is prone to damage, resulting in a decrease in the overall resistance of the structure. Combined with the natural aging and human factors of concrete materials, the safety state and service life of wharf structure are seriously affected [1,2]. The findings of the investigation reveal that the soft soil foundation experiences significant deformation during the utilization of the wharf, predominantly attributed to the excessive lateral deformation of the soil. Consequently, the resultant horizontal load on the wharf pile foundation exceeds its capacity, leading to failure of the pile-beam joint when the horizontal displacement reaches an excessive level. This, in turn, adversely affects the bearing capacity of the wharf. The phenomenon of soil creep further exacerbates the lateral displacement of the wharf, resulting in additional bending moment being imposed on the structure, leading to further deterioration of the structural members and joints. In extreme cases, the entire structure may be subject to capsizing, posing a serious threat to the safety and production of the wharf. Therefore, it is necessary to monitor the safety state of the wharf structure in real-time [3,4]. Ship impact force is a very important load in port engineering, especially in the construction of a large open wharf. The accurate determination of ship impact force is the guarantee of reasonable design and safe operation of the port.

Researchers have also done many studies in the field of terminal health monitoring of Internet of Things (IoT) sensors. Guo et al. (2021) [5] pointed out that in recent years, the health detection system of constructions had grown to be one of the research hotspots in the global scholarly community. In response to the demand for monitoring methods in the large-scale civil engineering health inspection systems at the domestic and international levels, they researched a method for monitoring the health of high pile pier structures based on the technology of fiber optic sensors. Zhou et al. (2022) [6] pointed out that vibration-based monitoring was a hot spot in the research on structural health monitoring of large-scale civil engineering. The performance of traditional structural damage detection methods mainly depends on the reasonable choice of damage features and classifiers. Handcrafted features or fixed classifiers are not the best choices for all structural damage scenarios. Combining finite element modelling and a one-dimensional convolutional neural network, a novel, fast, and accurate real-time structural damage detection framework for high-piled wharf foundations was proposed. The significant advantage of this method is that damage-related features can be extracted directly and automatically from the raw displacement response. Liu (2018) [7] pointed out that the covered sheet pile wharf, as a new type of structure, has no perfect theory and design method. The immaturity of conventional design methods and model tests is restricted by various conditions and cannot fully simulate the actual situation on site. The two-dimensional model was calculated using three finite element software. There are some differences between the three calculation results and the actual monitoring data, but the calculation results of ANSYS software are the closest, and the two-dimensional model can be used for engineering calculation. Zhang (2021) [8] pointed out that an effective fusion of data collected by multiple sensors was required to achieve an accurate assessment of structural health. In the case of a limited number of sensors, it was essential to confirm the proper location of the sensors and use suitable integration methods. To this end, a method for assessing healthy structure supported by evidence-based inference rules considering the optimal arrangement of sensors was proposed. An adaptive evolutionary strategy algorithm for discrete integer encoding covariance matrix based on finite element modal analysis was proposed to determine the scheme. Meanwhile, Fiber Bragg gratings (FBGs) are optical fibers that have been modified with a periodic variation in the refractive index along their length. This periodicity forms a “grating” that reflects light of a specific wavelength while allowing other wavelengths to pass through. FBGs are commonly used in optical fiber communication systems and as sensors in structural health monitoring due to their ability to measure strain, temperature, and other environmental parameters. Compared to traditional sensing methods, FBG sensors offer several advantages, including immunity to electromagnetic interference, high sensitivity, and the ability to monitor multiple parameters simultaneously. In addition, FBGs offer several advantages for structural monitoring in geological and civil structures. These include high accuracy, multiplexing capability, a non-intrusive and lightweight nature, and remote sensing capability [9]. FBGs have been used in a variety of applications, such as monitoring the health of concrete bridges [10] and measuring the deformation and cracking of large-scale reinforced concrete structures [11]. In the context of the Wharf Health Monitoring System Based on Internet of Things Sensor in High Salt and High Humidity Environment study, the use of FBGs is particularly valuable for monitoring the strain and temperature of the wharf structure and detecting changes caused by external factors such as wind, waves, and tides [12]. In conclusion, the literature indicate that the technology of structural health monitoring has made significant advancements globally, especially in recent years, with several large wharfs in China already equipped with, or in the process of installing, health monitoring systems. The wharf health monitoring system is a comprehensive and versatile system that integrates multiple disciplines and functions. The system is primarily based on bridge monitoring and detection techniques, augmented by signal processing, structural analysis, reliability assessment, and damage identification methods. These features facilitate the assessment of health and safety of the wharf structure, enabling the attainment of safety objectives.

The significance of wharf deformation monitoring is mainly manifested in two aspects. The practical significance lies in mastering the stability of geological structure and providing necessary information for safety diagnosis to find problems in time and take corresponding remedial measures in advance to eliminate accidents in the bud. The scientific significance is to verify the theory and empirical formula of engineering design and to establish correct and effective deformation prediction theory and method. In this regard, the novelty of this study lies in the development of a fiber Bragg grating (FBG) sensor-based health monitoring system for wharf structures in a high-salt environment. The study takes into account the specific characteristics of coastal port wharves and their harsh working conditions, resulting in poor durability compared to other hydraulic structures. The authors propose stress features and health inspection indicators for the wharf structure and establish a monitoring system for coastal high-pile piers, including a corresponding implementation scheme, sensor selection, and performance parameters. The experimental results demonstrate the feasibility of the proposed monitoring system, providing insights for future research in the area. Overall, this study’s contribution lies in its application of advanced sensing technologies to a specific problem, and its potential to have a significant impact on the maintenance and management of coastal port wharves.

2. Design of Wharf Structure Health Monitoring System

2.1. Analysis of Wharf Structure Health Monitoring Index

The terminal mainly consists of an upper structure, pile base, and wharf facilities. The terminals are divided into front caps and back caps, depending on the load. The front cap is composed of a panel, beam, track beam, pile cap, and pile and berthing member, which is mainly used for loading, unloading, and circulation of goods. Due to the combined action of gantry crane load, mobile machinery load, cargo loading and ship impact pressure, mooring pressure, squeezing pressure, and other additional outside pressures, the stress condition of the front pile cap is complicated. The ship impact force is likely to cause damage or fracture of the pile foundation of the quay structure, which seriously affects the security of the quay. Moreover, the chloride ion erosion ions in the marine environment can easily lead to steel corrosion and concrete cracking of reinforced concrete members, resulting in reduced durability of the structure [13,14]. With the accumulation of damage, the wharf structure is prone to panel collapse, beam fracture, the overall tilt of the structure, and even the overall overturning of the structure, resulting in major safety accidents. According to the damage characteristics of the above structure, the physical quantities of the wharf structure design and the wharf inspection evaluation mainly include the overall displacement of the wharf structure, pile stress, beam tension, track beam strength, panel tension, bank distortion, relative movement of beam, and the pile cap. The health monitoring indicators of pier structures can be broadly classified into three types, namely displacement, strain, and structural dynamic characteristics. Displacement mainly refers to the overall displacement of the wharf structure, including horizontal and vertical displacement of the structure [15,16]. The strain mainly refers to the strain state of the key components of the wharf structure. The key components should include pile foundation, beam, track beam, longitudinal beam, panel, and so on. Figure 1 shows the workflow diagram of the quay structure health detection system.

2.2. Research on Internet of Things Technology

IoT technology applies network technology to all things, constituting the “IoT”. For example, sensors are embedded in objects such as power grids, road networks, water networks, buildings, and dams, and then the “IoT” and “Internet” are integrated to achieve the integration of human society and physical systems. Its architecture is shown in Figure 2.

Figure 2 shows that the IoT system is divided into four layers, namely the sensor layer, network layer, information processing layer, and application layer. (1) The sensor layer is the base layer, located at the bottom of the four-layer structure. Its major functions are to recognize objects, perform environmental perception, and compile information. In addition, the main equipment includes readers, Radio Frequency Identification (RFID) tags and readers, Global Positioning System (GPS), video acquisition equipment, and wireless sensor nodes. The leading technologies include embedding, sensors, item recognition, and control technology. (2) The transport layer, also called the network layer, is in charge of delivering the data collected by the sensor layer effectively, reliably, and securely over various networks. It addresses the problem of data delivery, especially over long distances. (3) The main function of the information processing layer is to store, analyze, mine, understand, and process the data transferred from the network layer. The IoT connects billions of objects, and the information generated is massive. (4) Application layer is the driving force for the development of IoT. The main function is to provide users with a wealth of specific services based on the analysis of processed data [13,14,15]. Such as intelligent transportation, energy logistics, smart home, environmental monitoring, and green building. The application of IoT can be divided into monitoring, inquiry, control, scanning, and so on. The structure of the network layer is shown in Figure 3.

2.3. Deployment of the Health Monitoring System for Wharf Main Structure Based on Sensing Technology

The fiber grating sensor belongs to the fiber sensor with wavelength modulation nonlinear effect. In essence, a narrowband filter or reflector is formed in the fiber core, which optionally reflects the incoming wideband light and reflects the narrowband light that is modulated through the grating region and transmits it. The light continues to pass along the fiber, and the fiber grating sensor can be formed by encapsulating the fiber grating. Fiber optic temperature sensors offer many advantages over conventional sensors, such as high sensitivity, small size, corrosion resistance, electromagnetic radiation resistance, flexible optical path, and easy realization of telemetry [16,17,18,19]. However, in practical applications, the optical fiber temperature sensor based on intensity modulation is significantly affected by changes in light source power and line loss, resulting in poor long-term measurement stability. The optical fiber temperature sensor based on Fiber Bragg Grating (FBG) technology adopts wavelength coding technology in order to eliminate the influence of light source power waves on system loss, so it is suitable for long-term monitoring of structures [20,21,22,23]. Fiber Bragg grating sensors are embedded in large-scale civil structures for time-resolved and mass detection of internal strains and other parameters. They are currently the preferred sensors for structural health monitoring. It has the advantages of high precision, good long-term stability, corrosion resistance, and a quasi-distributed layout, which is suitable for the monitoring of this project. Table 1 shows the performance comparison of the two commonly used sensors and the FBG strain sensor and temperature sensor indicators used in this monitoring project sensor selection and layout.

The marine environment in which the wharf structure is located is characterized by water-related and strong corrosiveness. Traditional electrical sensors are not easy to survive in the highly corrosive seawater environment, and their applicability is limited. Therefore, FBG sensors are selected. Such sensors have the advantages of not being afraid of water and strong corrosion resistance. Compared with electrical sensors, FBG sensors have a wider application space in port engineering structural health monitoring [24,25,26]. FBG is a core grating with a periodic refractive index written in a range of bare fiber by a certain writing technology, which belongs to reflection-type grating and short-period grating. Such gratings can reflect the light of a specific wavelength in the broad-spectrum incident light, and all other wavelengths of light are transmitted. The wavelength of the reflected beam from the Bragg grating meets the following equation. Moreover, the FBG parameters are shown in Table 2.

(1)$\lambda =\frac{2n_{\mathrm{eff}}\mathsf{\Lambda }}{m}$

3. Design of Wharf Structural Health Monitoring System

3.1. System Hardware Design

The system hardware is the main component of the monitoring system as the main component of the data acquisition, the display part of the ship, and the remote transmission of the data. It is also very important to work to select the components of the hardware system and design the related functional circuits effectively. The hardware design part of the monitoring system includes the device selection and main circuit design of the ship-borne energy monitoring instrument and the ship-shore data communication module. Figure 4 shows the hardware system design framework.

Figure 4 shows that the core of the monitoring system designed is the single-chip microcomputer, the data acquisition module, the Beidou module, and the data communication module. The data display module at the end of the ship is the corresponding peripheral module in the monitoring system. The circuit constructed by using peripheral modules realizes the conditioning and transmission of sensor signals and communication signals. The system constructed adopts the general packet radio service (GPRS) network as the medium of ship-shore communication. The GPRS module should also have the characteristics of applying to the ship environment and have a communication interface connected with the data acquisition module, which can automatically reconnect and retransmit data after the network is disconnected. For the consideration of system development time, the mature GPRS modules on the market are selected for use.

The single-chip microcomputer is the core processing unit of the ship energy efficiency data acquisition module and processing. Selecting a single-chip microcomputer that meets the requirements is also a very important task. Through the analysis of the scheme of constructing the system, it shows that the single chip microcomputer should meet the following requirements besides all the resources needed to run: (1) It needs to have more than two channels for receiving the Beidou signal and bridge equipment output signal. (2) It needs to have one Controller Area Network (CAN) channel to send energy efficiency data to the CAN bus.

The minimum circuit system of the single-chip microcomputer consists of a power supply circuit, a crystal oscillator circuit, a reset circuit, and a Joint Test Action Group (JTAG) circuit. The minimum circuit system is designed in the selected single-chip microcomputer. Besides, the power supply circuit is taken as an example to design the circuit. The power source of the data acquisition module is converted from the voltage of 220 V on the ship into 24 V for the power supply. The electronic devices in the data acquisition module can work under two operating voltages, 5 V and 3.3 V, respectively. According to the law of energy conservation, the closer the voltage is, the higher the conversion efficiency. Therefore, the power supply circuit consists of two parts. One part is 24 V to 5 V and the other part is 5 V to 3.3 V.

In the 24 V to 5 V power supply circuit, U101 is the power management chip. LM575 is the switching power supply chip, and its input voltage range is 6 V~75 V. The resistors R208 and R209 are the matching resistors of the switching power supply chip. Through the combined action of the chip and the matching resistor, a stable +5 V voltage output was achieved. The function of the peripheral circuit is to realize the signal transmission between the key device module and the single-chip microcomputer. The peripheral circuit can adjust the transmission signal of the analog device into an electrical signal that can be recognized by the single-chip microcomputer. Additionally, the type of output signal of the key device determines the design requirements of the peripheral circuit. Based on the system requirements analysis, the signals that the peripheral circuit of the system needs to transmit are pulse signals and analog signals. The communication interface includes the SCI interface, RS485 interface, and CAN interface. Taking the CAN bus communication circuit design as an example, the peripheral circuit design is carried out.

In the schematic diagram of the CAN bus communication circuit, U405 is a transceiver for CAN bus communication, which can convert the differential level on the CAN bus into the logic signal of the single-chip microcomputer. The CAN TX1 sending pin of the microcontroller is connected to the pin1 pin of U405 through R407. The CAN1RX pin is connected through R409 and pin4 of U405. Pin6 in U405 is connected to CAN_L in the CAN network through a common mode inductance, and pin7 is connected to CAN_H in the same way. The function of C409 is to eliminate high-frequency harmonic noise.

3.2. System Software Design

The integrated intelligent health detection system with network communication technology has developed into a new networked intelligent health detection system with process data management and other functions due to the advancement of wireless transmission technology. The combination of the two allows for the acquisition, analysis, and assessment of structural stability of all sensor data at a distant computer terminal. This structural system contributes to the time-efficient application of data object information. Even if the scientific research personnel and engineering technicians are not at the control site, they can know the operation of the monitoring system and the real-time changes of the monitoring data at any time through the network.

The software structure design of the system is divided into upper-level software design and lower-level software design. Communication between upper-level software and lower-level software is carried out through GPRS. The overall software structure is shown in Figure 5.

The software architecture can be run in 8 steps, which are:

• (1). Run the system and initialize the configuration of the microcontroller.

• (2). Set the timing terminal cycle, complete data acquisition and processing in each set cycle, package the data through the serial port and send it to the remote transmission module.

• (3). Send AT command to wake up the GPRS module.

• (4). Check the GPRS signal strength.

• (5). After the GPRS module is successfully connected, the collected data and stored data will be sent to the shore-based energy efficiency monitoring platform, and it will judge every 10 min whether the connection is valid.

• (6). After the upper computer software receives from the lower computer, it first verifies the completeness and accuracy of the data. If the verification passes, the energy efficiency data are saved into the database.

• (7). The webpage requests data to be sent from the database server, and the database server returns the corresponding data.

• (8). The web page program parses the returned data and applies the data.

Analysis of the experimental results of the monitoring system

4. Analysis of Monitoring Results of Ship Pier under Wave Load

The experimental results presented in Figure 3, Figure 4 and Figure 5 demonstrate the successful implementation of the fiber grating sensor-based structural health monitoring system for coastal high-pile piers in a high salt and high humidity environment. The system was able to capture the dynamic response of the pier under wave load and ship collision load in real-time at a 25 Hz sampling frequency. The 25 Hz sampling frequency is used to collect the dynamic response of the pier under wave load in real-time. The time-domain strain diagram of the wave load response at each elevation of the caisson is shown in Figure 6.

Figure 7 shows the caisson wave load–strain amplitude. The above analysis shows that the waveform changes in the form of a sine wave under the impact of wave load, which is completely consistent with the actual wave load. The maximum strains of the ship piers appear at 4.35 m and 6.14 m, and the elevations reach $4.66\mathsf{\mu }\mathsf{\epsilon }$ and $5.31\mathsf{\mu }\mathsf{\epsilon }$, respectively. The strains at other positions also have obvious changing trends. These findings are significant because it demonstrates the ability of the monitoring system to accurately capture the response of the pier to wave load, which is important for ensuring the safety and maintenance of the structure.

Analysis of the Monitoring Results of the Impact Energy of the Caisson during the Docking Process

Figure 8 displays the time-domain strain diagram of the ship collision load response.

Figure 9 shows the response amplitudes of the ship collision load at each elevation of the caisson.

Figure 8 and Figure 9 indicate, from the analysis of the strain changes at each elevation of the caisson measured by the sensor, that the monitoring system works well, the dynamic response to the caisson when the ship is docked is well monitored, and the sensors at each position show good sensitivity. The maximum strain occurs at the height of the structure measured by the sensor. These findings are significant because they demonstrate the ability of the monitoring system to detect and measure the impact energy of the caisson during the docking process, which is important for ensuring the safety and maintenance of the structure.

Overall, the experimental results demonstrate the effectiveness of the fiber grating sensor-based structural health monitoring system in a high salt and high humidity environment for accurately capturing the dynamic response of coastal high-pile piers to wave load and ship collision load. The findings of this study are significant because they contribute to the development of novel monitoring systems that can enhance wharf safety and maintenance, which is important for ensuring the sustainable operation of seaports.

5. Conclusions

This research has made a noteworthy contribution to the civil engineering field through the introduction of a fiber optic grating sensing technology-based structural health detection system for coastal high-pile piers. The study proposed health detection indicators for wharf structures, designed an appropriate structural health detection system, and proposed a corresponding monitoring plan, sensor selection criteria, and performance parameters. Experimental results have validated the effectiveness of the monitoring system, with sensors demonstrating excellent sensitivity. The study highlights the need for further research on the long-term performance changes of high-piled wharf structures during their service life and the establishment of a unified wharf structure state-assessment standard for disaster early warning. In conclusion, the primary findings and contributions of this study can be summarized as follows:

• ○. The current study presents a novel structural health monitoring system for coastal wharves utilizing fiber optic grating sensors. The proposed system exhibits the capability to detect structural damage, assess the safety of the structure, and predict the remaining service life of the wharf structure. The study also analyzes the stress characteristics of coastal port wharf structures, leading to the proposal of health detection indicators that aid in understanding the critical stress areas of the wharf and enable effective monitoring.

• ○. Based on the standard structural section of the front deck of the wharf, a relevant structural health detection system was designed. The corresponding monitoring implementation plan, sensor selection, and performance parameters were proposed and can serve as a reference for designing health detection systems for other structures. Moreover, the study proposes a realization technology and related indexes of the data acquisition and transmission subsystem that ensure reliable data acquisition and transmission from the sensor system, resulting in a more efficient health monitoring system.

• ○. The performance of the proposed monitoring system is validated through experiments. The results demonstrate the effectiveness of the system, including the waveform changes in the form of the sine wave under the impact of wave load, the maximum strain on the pier appearing at 4.35 m and 6.14 m, and the elevations reaching 4.66 με and 5.31 με, respectively. The analysis of the strain changes at each elevation of the caisson measured by the sensor indicates that the monitoring system works well, and the sensors at each position exhibit good sensitivity.

• ○. The study also identifies the lack of systematic understanding of the long-term performance changes of high-piled wharf structures during their service life and the difficulty of establishing a unified wharf structure state assessment standard for disaster early warning. These findings highlight the need for further research on the health-monitoring technology of coastal wharf structures.

Overall, the study’s main contribution is the development of a fiber optic grating sensing technology-based structural health detection system for coastal high-pile piers, which can help to ensure the safety and longevity of coastal wharf structures. The study’s findings can be used as a reference for designing and implementing health detection systems for other structures, and the identified research gaps can guide future research in this area.

Author Contributions

Conceptualization, Y.L. and G.Z.; Methodology, P.Z.; Validation, P.Z. and G.Z.; Formal Analysis, Y.Y.; Investigation, Y.L.; Writing—Original Draft Preparation, P.Z.; Writing–Review & Editing, Y.L.; Funding Acquisition, Y.L. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Working flow chart of the structural health monitoring system.

Figure 2. IoT architecture.

Figure 3. Network layer system structure.

Figure 4. Schematic diagram of hardware design.

Figure 5. Overall software architecture.

Figure 6. Time-domain strain diagram of caisson response to wave load at various elevations. (a): Sensors at 0 m and 2.45 m; (b): Sensors at 4.35 m and 6.25 m.

Figure 7. The caisson wave load–strain amplitude.

Figure 8. Time-domain strain diagram in response to ship collision loads. (a) Sensors at 0 m and 2.45 m; (b) Sensors at 4.35 m and 6.25 m.

Figure 8. Time-domain strain diagram in response to ship collision loads. (a) Sensors at 0 m and 2.45 m; (b) Sensors at 4.35 m and 6.25 m.

Figure 9. Response amplitude of ship collision load at each elevation of caisson.

Table 1

Sensor metrics.

Performance	Resistance Strain	FBG Sensor
Precision	High	High	Range	$\pm 2000 \mathsf{\mu }\mathsf{\epsilon }$
Noise	Loud	Very low
Corrosion resistance	Very low	High	Resolution	$10 \mathsf{\mu }\mathsf{\epsilon }$
Stability	Bad	Very good
Zero drift	Have	Do not have	Temperature range	$-30 °\mathrm{C}\sim +80 °\mathrm{C}$
Equipment maturity	Mature	Mature
Price	Low	High

Table 2

The FBG parameters.

Type	Range	Resolution	Temperature
A	$\pm 2000 \mathsf{\mu }\mathsf{\epsilon }$	$1 \mathsf{\mu }\mathsf{\epsilon }$	−20 °C–+120 °C
B	$50 \mathrm{mm}$	$0.5 \mathrm{mm}$	−30 °C–+120 °C
C	$\begin{array}{c}-20 °\mathrm{C}\sim +\\ 120 °\mathrm{C}\end{array}$	0.1 °C	−20 °C–+120 °C
D	$\pm 2.0 \mathrm{g}$	$10 \mathsf{\mu }\mathrm{g}$	−25 °C–+65 °C

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