Tunnel multi-parameter synchronous monitoring method based on seven-core optical fiber and fusion correlation early warning system

Abstract

The invention discloses a tunnel multi-parameter synchronous monitoring method based on a seven-core optical fiber and a fusion association early warning system. The system comprises a sensing module, a data acquisition module, a processing module and an early warning monitoring module, the sensing module comprises a seven-core optical fiber arranged in the tunnel, physical parameters in the tunnel are synchronously monitored through the seven-core optical fiber, and the physical parameters comprise temperature, strain and vibration; the data acquisition module is used for acquiring physical parameter data in real time through the sensing module; the processing module is used for demodulating and fusing the physical parameter data signal to obtain parameter information; and the early warning monitoring module is used for displaying the parameter information in a graphical mode for monitoring, and comparing the parameter information with a corresponding preset threshold value to judge whether the tunnel has a potential health risk so as to carry out early warning. According to the system, the seven-core optical fiber space division multiplexing technology is adopted, and comprehensive and real-time subway tunnel health monitoring and early warning can be provided through multi-parameter fusion measurement.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel health monitoring, and particularly to a method for synchronously monitoring multiple parameters of a tunnel based on a seven-core optical fiber and a fusion correlation early warning system. Background Art

[0002] As an important part of the urban transportation system, the stability and safety of subway tunnels directly affect public safety and urban operation. During the long-term operation of subway tunnels, various technical challenges in health monitoring and safety guarantee are faced. Traditional tunnel health monitoring methods, such as manual inspection, mechanical measurement, and GPS monitoring, all have significant limitations. These methods rely on intermittent data collection, cannot provide real-time or continuous monitoring, are difficult to capture the rapid changes in tunnel health, and have limited coverage, especially in areas with harsh environments. Moreover, traditional monitoring methods focus on the measurement of a single physical quantity, such as temperature, strain, or vibration, and have problems such as limited monitoring range, insufficient accuracy, and poor real-time performance. Especially under the temperature-strain cross-sensitivity effect, they cannot provide comprehensive and high-precision monitoring of multiple parameters simultaneously. In addition, these methods have high implementation costs and large labor intensities, and are not suitable for long-term continuous monitoring. Therefore, a tunnel health monitoring technology that can comprehensively monitor multiple parameters, has high precision, high sensitivity, long distance, and anti-interference ability is needed. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method for synchronously monitoring multiple parameters of a tunnel based on a seven-core optical fiber and a fusion correlation early warning system in view of the deficiencies of the prior art. The system of the present invention adopts the seven-core optical fiber space division multiplexing technology, and through multi-parameter fusion measurement, can provide comprehensive and real-time health monitoring and early warning of subway tunnels.

[0004] To achieve the above object, according to one aspect of the present invention, a fusion correlation early warning system for synchronously monitoring multiple parameters of a tunnel based on a seven-core optical fiber is provided, including: a sensing module, a data acquisition module, a processing module, and an early warning monitoring module;

[0005] The sensing module includes a seven-core optical fiber arranged in the tunnel. A first FBG core is arranged at the center position of the seven-core optical fiber, and the first FBG core is used to provide accurate measurement of local strain and temperature of the tunnel; the remaining 6 cores are evenly distributed at equal intervals in the circumferential direction; among them, the second FBG core and the third FBG core are symmetrically arranged according to the first FBG core, and the second FBG core and the third FBG core provide monitoring of local strain. The first BOTDA core and the second BOTDA core are symmetrically arranged according to the first FBG core, and the first BOTDA core and the second BOTDA core provide monitoring of distributed strain and temperature. The ROTDR core and The core is symmetrically arranged according to the first FBG core, the ROTDR core provides temperature monitoring, and the core provides vibration monitoring;

[0006] The data acquisition module is used to collect physical parameter data in real time through the sensing module;

[0007] The processing module is used to demodulate and fuse the physical parameter data signals collected by the data acquisition module to obtain parameter information;

[0008] The early warning monitoring module is used to display the parameter information in a graphical manner for monitoring, compare the parameter information with the corresponding preset threshold, and judge whether there is a potential health risk in the tunnel so as to give an early warning.

[0009] In the above solution, the seven-core optical fiber includes a circumferential seven-core optical fiber and a longitudinal seven-core optical fiber.

[0010] In the above solution, the longitudinal seven-core optical fiber is laid parallel along the crown and the two side haunches of the circular shield segment of the tunnel, and extends horizontally along the tunnel axis.

[0011] In the above solution, the circumferential seven-core optical fiber extends circumferentially along the inner arc surface of the circular shield segment of the tunnel, follows the principle of "Ω" type routing layout, and adjacent circumferential sensing optical fibers are connected by seven-core optical fibers arranged along the tunnel axis at the bottom of the tunnel.

[0012] In the above solution, the seven-core optical fiber is kept in close contact with the inner wall of the circular shield segment of the tunnel through a fiber clamp.

[0013] In the above solution, the distance between adjacent circumferential sensing optical fibers is 3-5m.

[0014] In the above solution, the early warning monitoring module includes a settlement early warning monitoring module, a circumferential deformation early warning monitoring module, a fire early warning monitoring module, and an external intrusion early warning monitoring module.

[0015] In the above solution, the settlement early warning monitoring module is used to perform multi-dimensional analysis on the monitoring data of distributed strain provided by the first BOTDA core and the second BOTDA core and the monitoring data of local strain provided by the second FBG core and the third FBG core to judge whether there is a settlement risk in the tunnel so as to give an early warning.

[0016] In the above solution, the circumferential deformation early warning monitoring module is used to perform multi-dimensional analysis on the monitoring data of circumferential strain provided by the first BOTDA core and the second BOTDA core and the monitoring data of local circumferential strain provided by the second FBG core and the third FBG core to judge whether there is a circumferential deformation risk in the tunnel so as to give an early warning.

[0017] In the above solution, the fire warning and monitoring module is used to perform multi-dimensional analysis and judgment on whether there is a fire risk in the tunnel based on the temperature monitoring data provided by the ROTDR fiber core and the first FBG fiber core and the vibration monitoring data provided by the fiber core, so as to issue a warning.

[0018] In the above solution, the external intrusion warning and monitoring module is used to perform multi-dimensional analysis and judgment on whether there is a risk of external intrusion in the tunnel based on the vibration monitoring data provided by the fiber core and the distributed strain monitoring data provided by the first BOTDA fiber core and the second BOTDA fiber core, so as to issue a warning.

[0019] According to another aspect of the present invention, there is provided a method for synchronously monitoring multi-parameters of a tunnel based on a seven-core optical fiber for the above-mentioned tunnel multi-parameter synchronous monitoring and fusion correlation warning system based on a seven-core optical fiber, including: synchronously monitoring physical parameters along the seven-core optical fiber in the tunnel through the seven-core optical fiber, where the physical parameters include temperature, strain, and vibration;

[0020] Real-time collecting physical parameter data through the seven-core optical fiber;

[0021] Demodulating and fusing the collected physical parameter data signals to obtain parameter information;

[0022] Displaying the parameter information in a graphical manner for monitoring, and comparing the parameter information with corresponding preset thresholds to judge whether there are potential health risks in the tunnel, so as to issue a warning.

[0023] In the present invention, through the innovative design of the seven-core optical fiber, the BOTDA sensing technology is applied to two fiber cores in the seven-core optical fiber to realize the synchronous measurement of strain and temperature in the tunnel; these two fiber cores are symmetrically arranged, which can effectively eliminate the strain-sensitive effect caused by fiber bending, thereby improving the measurement accuracy and stability. The measurement data of the two fiber cores are processed by averaging, further optimizing the accuracy of strain measurement. At the same time, the temperature data provided by the ROTDR fiber core is used as a temperature compensation source, effectively eliminating the temperature-strain cross-sensitivity effect, ensuring the reliability and high precision of the strain data. Utilizing the integrated design of the seven-core optical fiber, a single optical fiber can realize the synchronous monitoring of strain and temperature, breaking through the limitations of traditional single sensors.

[0024] The present invention integrates the FBG sensing technology into three cores of a seven-core optical fiber to achieve high-precision strain and local temperature monitoring of key parts of a tunnel. The three cores work together, enabling the FBG core to provide ultra-high-sensitivity strain data and accurately monitor minute deformations of the tunnel structure, such as segment cracking and structural damage. In addition, combined with the positioning data of the Raman temperature field, these cores can also perform targeted local temperature measurements. Using the seven-core optical fiber technology, the measurements of three different physical quantities are synchronized within the same optical fiber, greatly improving the spatial resolution and accuracy of strain and temperature measurements.

[0025] One core of the seven-core optical fiber in the present invention adopts a sensing technology dedicated to vibration monitoring in the tunnel. By monitoring the intensity change of the optical signal in the optical fiber, the core can accurately identify and locate the position of the external vibration source. The long-distance transmission characteristic of the optical fiber enables it to widely cover the tunnel area and achieve high-sensitivity and high-spatial-resolution vibration monitoring. Through the integrated design of the seven-core optical fiber, this core can synchronously collect data with other cores, real-time monitor the vibration changes of the tunnel, timely issue early warnings of abnormal vibrations, and provide guarantee for the safe operation of the tunnel.

[0026] One core of the seven-core optical fiber in the present invention adopts the ROTDR sensing technology and is specifically used for temperature monitoring. This core has high sensitivity to temperature changes and only responds to temperature change signals, and can obtain the temperature distribution data of the tunnel in real time. Through the design of the seven-core optical fiber, the temperature data provided by the ROTDR core can not only accurately monitor the spatial distribution of the tunnel temperature field, but also timely identify local temperature anomalies and provide a fire warning function. At the same time, the ROTDR core provides temperature compensation data for other cores (such as BOTDA and FBG), solves the problem of temperature-strain cross-sensitivity effect, and thus ensures the independent and accurate measurement of strain and temperature.

[0027] Through the above design of the seven-core optical fiber, the present invention realizes the highly integrated multiple sensing technologies.

[0028] Generally speaking, compared with the prior art through the above technical solutions conceived by the present invention, the following beneficial effects can be achieved:

[0029] (1) The present invention provides a tunnel multi-parameter synchronous monitoring, fusion and correlation warning system based on a seven-core optical fiber. The system synchronously measures multiple physical parameters (temperature, strain, vibration) in the same optical fiber, greatly improving the data acquisition efficiency and comprehensiveness of monitoring. At the same time, the multi-core optical fiber technology effectively solves the problem of cross-sensitivity between temperature and strain. Through the mutual calibration and compensation of each core, the accuracy and reliability of the data are improved. Therefore, the system of the present invention can not only comprehensively monitor problems such as tunnel deformation, settlement, and fire, but also accurately identify and locate intrusions and damages along the line, significantly enhancing the comprehensiveness, accuracy, and real-time performance of subway tunnel health monitoring.

[0030] (2) The tunnel multi-parameter synchronous monitoring, fusion and correlation warning system based on a seven-core optical fiber provided by the present invention can monitor and give early warnings on tunnel settlement, circumferential deformation, fire, and external intrusion in real time.

[0031] (3) By integrating a variety of sensing technologies in a single seven-core optical fiber, the seven-core optical fiber provided by the present invention significantly reduces the number of sensors and the number of installation points, thereby reducing the installation and maintenance costs. At the same time, the fiber optic sensing technology has strong anti-interference ability and stability, effectively reducing the system failure rate and maintenance frequency, and improving the long-term reliability and operation efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. And throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0033] Figure 1 It is the core layout diagram of the seven-core optical fiber in Embodiment 1 of the present invention.

[0034] Figure 2 It is the layout diagram of the longitudinal seven-core optical fiber in Embodiment 1 of the present invention.

[0035] Figure 3 It is the "Ω" - shaped layout diagram of the circumferential seven-core optical fiber in Embodiment 1 of the present invention.

[0036] Figure 4 It is the schematic diagram of the optical fiber fixture in Embodiment 1 of the present invention.

[0037] Figure 5 It is the flowchart of the multi-parameter demodulation processing of the seven-core optical fiber in Embodiment 1 of the present invention.

[0038] Figure 6 It is the flowchart of the tunnel multi-parameter synchronous monitoring method based on the seven-core optical fiber in Embodiment 2 of the present invention.

[0039] Figure 7 This is the flowchart of multi - disease associated early warning for tunnel health monitoring in Embodiment 2 of the present invention. Detailed implementation manners

[0040] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0041] It should be understood that the magnitude of the sequence numbers of the steps in the embodiments does not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0042] Embodiment 1

[0043] An embodiment of the present application provides a tunnel multi - parameter synchronous monitoring, fusion and associated early warning system based on a seven - core optical fiber, including: a sensing module, a data acquisition module, a processing module, and an early warning monitoring module;

[0044] The sensing module includes a seven - core optical fiber disposed in the tunnel. A first FBG core is disposed at the center of the circle of the seven - core optical fiber. The first FBG core is used to provide accurate measurement of local strain and temperature in the tunnel; the remaining 6 cores are evenly distributed circumferentially; among them, the second FBG core and the third FBG core are symmetrically disposed according to the first FBG core. The second FBG core and the third FBG core provide local strain monitoring. The first BOTDA core and the second BOTDA core are symmetrically disposed according to the first FBG core. The first BOTDA core and the second BOTDA core provide distributed strain and temperature monitoring. The ROTDR core and the core are symmetrically disposed according to the first FBG core. The ROTDR core provides temperature monitoring, the core provides vibration monitoring;

[0045] The data acquisition module is used to collect physical parameter data in real - time through the sensing module;

[0046] The processing module is used to demodulate and fuse the physical parameter data signals collected by the data acquisition module to obtain parameter information;

[0047] The early warning monitoring module is used to display the parameter information in a graphical manner for monitoring, and judge whether there are potential health risks in the tunnel by comparing the parameter information with the corresponding preset thresholds, so as to give an early warning.

[0048] Specifically, in this embodiment, the core layout diagram of the seven - core optical fiber is asFigure 1 As shown in the figure, the seven-core optical fiber in this embodiment includes 7 cores. A core is arranged at the central position of the seven-core optical fiber, and the remaining 6 cores are evenly distributed at equal intervals in the circumferential direction, and the distance between the 6 cores and the central core is half of the radius of the optical fiber. Specifically, the 7 cores of the seven-core optical fiber are respectively the first FBG core (core 7), the second FBG core (core 2), the third FBG core (core 5), the first BOTDA core (core 1), the second BOTDA core (core 4), the ROTDR core (core 6), core (core 3). In this embodiment, the two FBG cores (core 2 and core 5) and the two BOTDA cores (core 1 and core 4) are symmetrically arranged with the central core (core 7). The FBG cores and the BOTDA cores form a symmetric structure, which can synchronously monitor local strain and distributed strain, ensuring that the deformation of the tunnel structure at different positions and different scales is comprehensively monitored.

[0049] In this embodiment, through the reasonable spatial layout of the seven-core optical fiber, efficient and accurate monitoring of the entire cross-section and all time periods of the tunnel can be realized. The function allocation of each core optimizes the monitoring coverage of the system, and by integrating cores (FBG, BOTDA, ROTDR, ) containing multiple optical fiber sensing technologies in the same optical fiber, the system can synchronously measure multiple physical quantities such as temperature, strain, and vibration in the same optical fiber. This design significantly improves the accuracy, sensitivity, and real-time response ability of tunnel health monitoring, while effectively reducing the complexity and maintenance cost of the system.

[0050] Specifically, in this embodiment, the optical fiber sensing system adopts a three-dimensional layout strategy combining vertical and horizontal directions. The seven-core optical fiber includes a circumferential seven-core optical fiber and a longitudinal seven-core optical fiber. As Figure 2 shown, the longitudinal seven-core optical fiber is laid parallel to the crown and the two arch waists of the circular shield segment of the tunnel, and extends horizontally along the tunnel axis. As Figure 2 shown, the circumferential seven-core optical fiber extends circumferentially along the inner arc surface of the circular shield segment of the tunnel, following the principle of "Ω" type routing layout. Adjacent circumferential sensing optical fibers are connected by a seven-core optical fiber arranged along the tunnel axis at the bottom of the tunnel; in this embodiment, the distance between adjacent circumferential sensing optical fibers is 3m. Particularly, the seven-core optical fiber in this embodiment is kept in close contact with the inner wall of the circular shield segment of the tunnel through an optical fiber fixture, and the optical fiber fixture is as Figure 4 shown.

[0051] In this embodiment, the data acquisition module collects various physical parameter data in real time through the sensing module. Specifically, in this embodiment, the seven-core fiber optic space division multiplexing technology uses different types of cores to monitor the tunnel circumferential deformation, longitudinal settlement, fire, and external abnormal intrusion in real time, and can provide comprehensive, continuous, and reliable data support through an accurate seven-core fiber optic sensing network. Compared with traditional monitoring methods, the seven-core fiber optic sensing technology not only improves the accuracy and real-time performance of monitoring, but also can effectively avoid the interference of the external environment on the monitoring data, adapt to complex tunnel working environments, and provide strong technical support for tunnel safety management. The core application distribution of the seven-core fiber is as follows in the table:

[0052] Table 1 Core Application Distribution of Seven-Core Fiber

[0053]

[0054] Specifically, in the tunnel circumferential deformation monitoring: Based on the seven-core fiber optic space division multiplexing architecture, through the collaborative perception of the BOTDA core and the FBG core, the full-dimensional monitoring of the tunnel circumferential deformation is realized. Among them, the BOTDA core is continuously arranged along the tunnel circumference, and the full circumferential strain field distribution is obtained through the change of Brillouin frequency shift; the FBG core is embedded in the key nodes of the structure in the form of a high-density array to capture the local strain micro-variation characteristics. Through the optimization of the multi-core fiber spatial layout, the measurement data of the BOTDA and FBG cores are complementary in the time-space dimension. After being processed by the feature-level data fusion algorithm, the elastic deformation and plastic deformation components can be accurately decoupled, and the system spatial resolution reaches the centimeter level. This design enables a single fiber to synchronously achieve large-range continuous monitoring and precise positioning of local damage. Compared with the traditional discrete sensor scheme, the monitoring efficiency is increased by more than 70%.

[0055] In the tunnel longitudinal settlement monitoring: Aiming at the longitudinal mechanical behavior characteristics of the tunnel, the BOTDA core in the seven-core fiber is used to construct a strain sensing network. The BOTDA core is continuously laid along the tunnel axis, and the longitudinal strain base is obtained through Brillouin scattering spectrum analysis. At the same time, the FBG core is configured in the settlement-sensitive areas (such as segment joints, geological mutation sections, etc.) to form high-precision strain monitoring nodes. Through the multi-core fiber space division multiplexing technology, the system can simultaneously obtain the axial strain and bending strain parameters. Combining with the improved Kalman filtering algorithm, the vector solution of the longitudinal settlement amount and the horizontal displacement can be realized, and the positioning accuracy is better than ±0.25m, effectively identifying the differential settlement at the millimeter level.

[0056] In the tunnel fire monitoring: Innovatively integrate the ROTDR core, core and FBG temperature core in the seven-core fiber to construct a multi-physical field coupling perception system. The ROTDR core realizes the distributed monitoring of the tunnel full-section temperature field, and the temperature measurement accuracy reaches ±0.5°C; The fiber core uses phase modulation and demodulation technology to effectively distinguish environmental vibration from thermally induced strain noise; dedicated FBG temperature cores are densely arranged at 10-cm intervals in high-fire-risk areas. After the measurement data of the three cores are fused by multi-modal data fusion, a multi-dimensional correlation model of temperature-strain-vibration can be established to realize feature extraction of early fires and false alarm suppression.

[0057] In the monitoring of abnormal intrusion outside the tunnel: Through the collaborative perception of the vibration core and the BOTDA strain core in the seven-core optical fiber, the system constructs a dual-physical quantity verification mechanism for intrusion behavior. The fiber core uses a 40-m spatial resolution to locate vibration events. Combining with wavelet envelope analysis technology, 7 typical intrusion modes such as impact and cutting can be identified; the BOTDA strain core synchronously monitors the dynamic response of the structure at a 1-m resolution, and verifies the authenticity of the intrusion through strain mutation gradient analysis. After the dual-core data is subjected to joint time-frequency analysis, a three-dimensional feature matrix of intrusion energy-position-mode can be constructed. This design breaks through the technical bottleneck that traditional vibration monitoring is vulnerable to environmental interference and realizes intelligent discrimination of intrusion behavior in the true sense.

[0058] In this embodiment, the processing module is used to demodulate and fuse the physical parameter data signals collected by the data acquisition module to obtain parameter information. Specifically, the multi-core structure of the seven-core optical fiber enables different optical fiber technologies to work synchronously, and multiple data points such as temperature, strain, and vibration can be synchronously obtained using the same optical fiber. These data need to be processed and analyzed through signal demodulation and fusion, and the signal demodulation and fusion process is as follows:

[0059] I. Multi-parameter demodulation processing of seven-core optical fiber: For the structural safety monitoring requirements of subway tunnels, an integrated synchronous demodulation system based on the space division multiplexing technology of seven-core optical fiber is constructed. By integrating wavelength division multiplexing (WDM), time division multiplexing (TDM), and space division multiplexing (SDM) strategies, the purpose is to achieve multi-parameter high-precision synchronous monitoring of various diseases such as tunnel settlement, deformation, fire, and external intrusion.

[0060] 1) The system uses the seven-core optical fiber to independently allocate sensing functions: Cores 1 and 4 use a 1550-nm narrow-linewidth laser to detect Brillouin frequency shift (11 GHz frequency shift corresponds to strain), and combine frequency division multiplexing (FDM) to measure the longitudinal strain distribution of the tunnel (range 0-500 με) and accurately locate the deformation area; Cores 2, 5, and 7 monitor the local settlement (accuracy ±0.5 mm) and circumferential deformation (strain resolution 1 με) at the tunnel segment joints in real time through wavelength demodulation; Core 3 uses the backscattered Rayleigh scattering phase fluctuation of 1550-nm pulsed light to capture mechanical vibration signals (frequency 1-100 Hz) with a 10-m positioning accuracy, and effectively discriminates illegal intrusion (such as the vibration energy of drilling on the tunnel sidewall >0.5 mV2) or abnormal train vibration (acceleration >0.1 m / s​2 ); Fiber core 6 uses 1550nm pulsed laser to stimulate Raman scattering (anti-Stokes / Stokes intensity ratio in the 1450 / 1660nm band) to monitor the temperature field anomaly in the tunnel with a spatial resolution of 1m, and can quickly identify cable overheating (temperature rise rate > 2℃ / s) or fire hazards (temperature threshold > 70℃).

[0061] 2) Optimize resource allocation through three-level multiplexing technology: space division multiplexing realizes physical isolation of seven cores to avoid signal crosstalk; wavelength division multiplexing supports FBG fiber core and BOTDA fiber core to share C-band bandwidth; time division multiplexing enables ROTDR fiber core and The fiber cores time-share the pulse light source (50μs for temperature measurement in the T1 stage, and 50μs for vibration measurement in the T2 stage). At the hardware level, the pulse light source (1550nm DFB laser) and the continuous light source (tunable laser + narrow linewidth laser) are split to each fiber core through a coupler, and the reflected signal is separated by a dense wavelength division multiplexer (DWDM) and a Raman filter, and converted into an electrical signal by a photodetector array. Finally, the FPGA synchronization trigger circuit (timing error <1μs) controls the four-channel high-speed acquisition card (250MS / s) to achieve synchronous data capture. The data processing end uses a multi-parameter fusion algorithm. For example, the joint analysis of the strain mutation monitored by the BOTDA core and the temperature gradient abnormality monitored by the ROTDR core can distinguish between sedimentation deformation (strain changes but temperature stability) and fire (sudden temperature rise accompanied by local strain); combined The vibration spectrum and BOTDA strain changes can eliminate environmental interference (such as train vibration) and accurately identify intrusion events.

[0062] 3) The core monitoring functions of seven-core optical fiber in subway tunnels include:

[0063] Structural health diagnosis: FBG fiber core and BOTDA fiber core work together to monitor tunnel settlement (accuracy ±0.5mm) and circumferential deformation, and warn of structural damage such as segment misalignment and bolt loosening;

[0064] Fire prevention and control: The ROTDR fiber core monitors the temperature field of the cable compartment and electromechanical equipment area in the tunnel with a temperature resolution of 1°C, and triggers the automatic sprinkler system in combination with the temperature rise rate threshold;

[0065] Safety protection: The fiber core can be used to monitor vibration along the entire line, identify illegal drilling, intrusion and other destructive behaviors, with a positioning accuracy of 10m and a response delay of <500ms;

[0066] Data fusion decision: Through cross-validation of data from multiple cores in the seven-core optical fiber (such as a combination mode of vibration + temperature + strain mutation), the false alarm rate is reduced (<0.1%) and the reliability of the monitoring system is improved. For example: when core 1 detects that the strain rate of a certain section exceeds the threshold, the system automatically associates the temperature data of the corresponding position of core 6. If the strain continues to accumulate after eliminating the interference of thermal expansion, core 2, core 5, and core 7 are called to verify the local deformation, forming a "distributed-point" linkage diagnosis chain. Specifically, core 1 and core 4 find abnormal strain within a range of 100 meters, core 2, core 5, and core 7 show displacement at the joint, and core 6 eliminates the interference of leakage and cooling. It can be determined that the tunnel has a risk of settlement. Compared with manual inspections, this method can achieve the effect of early warning.

[0067] The system has significant engineering adaptability: the mechanical strength of the seven-core optical fiber meets the requirements of tunnel burial environment (tensile strength ≥ 40kN), and a monitoring section can be achieved every 3m when laid out circumferentially along the pipe segment; the hardware modules share the light source, splitter and acquisition card, and the cost is significantly lower than that of discrete systems; it supports integration with the tunnel BIM model, and real-time mapping of the structural status to a three-dimensional visualization platform, providing data support for subway operation and maintenance.

[0068] Specifically, the seven-core optical fiber multi-parameter demodulation processing workflow in this embodiment is as follows: Figure 5 As shown in the figure, the demodulation system structure is roughly divided into five parts: light source system (pulse and continuous light source), seven-core sensing optical fiber (subway tunnel), signal separation and detection, data acquisition and synchronous triggering, and data processing and application (server, monitoring platform), as follows:

[0069] (1) Light source system

[0070] ① Pulse light source group:

[0071] 1550nm DFB laser, generating 10ns narrow pulse, time-sharing drive ROTDR (temperature monitoring) and (Vibration Monitoring).

[0072] ②Continuous light source group:

[0073] FBG tunable laser: wavelength scanning range 1525-1565nm, scanning rate 10nm / s, covering the FBG array resonance wavelength.

[0074] BOTDA narrow linewidth laser: 1550nm stable output, linewidth <1MHz, used for Brillouin frequency shift detection.

[0075] (2) Seven-core optical fiber light sensing module for subway tunnels

[0076] ① Seven-core optical fiber distribution and monitoring:

[0077] Core 1 and Core 4: Monitor longitudinal settlement, circumferential deformation and external abnormal intrusion deformation.

[0078] Core 2, Core 5 and Core 7: Locally monitor settlement, deformation and temperature anomalies in the tunnel.

[0079] Core 3: Vibration monitoring to identify external intrusion.

[0080] Core 6: Raman temperature measurement to cover the tunnel temperature field.

[0081] (3) Signal separation and detection module

[0082] ① Reflection light processing (FBG / BOTDA):

[0083] Separate FBG (1525 - 1565nm) and BOTDA (1550nm ± 0.1nm) signals through a dense wavelength division multiplexer (DWDM).

[0084] The detector converts the optical signal into an electrical signal, with a strain resolution of 1 με and a temperature resolution of 0.1 °C.

[0085] ② Scattered light processing (ROTDR / ):

[0086] Raman filter: Extract the intensity ratio of 1450nm (anti-Stokes) and 1660nm (Stokes) light to calculate the temperature (accuracy ± 1 °C).

[0087] Balanced detector: Demodulate the 1550nm backward Rayleigh scattering phase fluctuation, with a vibration positioning accuracy of 10m.

[0088] (4) Data acquisition and synchronous triggering

[0089] ① FPGA synchronous trigger circuit:

[0090] Generate two-channel timing signals:

[0091] Sync1 (1kHz): Control the time-division switching of the pulsed light source (T1 stage: ROTDR temperature measurement for 50 μs, T2 stage: vibration measurement for 50 μs).

[0092] Sync2 (100Hz): Trigger the FBG wavelength scanning and BOTDA frequency shift detection.

[0093] ② High-speed acquisition card: Four-channel synchronous acquisition, sampling rate 250MS / s, timestamp alignment error < 1 μs.

[0094] (5) Data processing and application layer

[0095] ① Multi-parameter fusion algorithm:

[0096] Settlement analysis: Joint calculation of FBG wavelength shift and BOTDA strain distribution, with an accuracy of ±0.5 mm.

[0097] Fire determination: ROTDR temperature rise rate (>2℃ / s) + Vibration to eliminate interference.

[0098] Early warning of external intrusion: Abnormal BOTDA strain gradient (>5 με / m) + Abnormal vibration duration and frequency.

[0099] ② Visualization platform:

[0100] Integrated with the tunnel BIM / GIS model, real-time display of temperature, strain, and vibration thermal maps. Alarm information is pushed to the subway operation and maintenance system, with a response delay <500 ms.

[0101] (6) Key connections and signal flow

[0102] Optical path direction: Pulse / continuous light source → coupler → circulator → seven-core optical fiber → tunnel sensing section → signal separation module → detector.

[0103] Circuit control: FPGA trigger signal → light source modulation + acquisition card synchronization → data uploaded to the server → algorithm analysis → monitoring platform.

[0104] This flowchart fully presents the entire process from light source emission, signal multiplexing, data acquisition to intelligent analysis, meeting the requirements of multi-parameter and high-reliability monitoring of subway tunnels.

[0105] II. Fusion processing: In the multi-parameter safety monitoring system of modern subway tunnels, the data fusion architecture is crucial, which ensures the coordinated operation of various sensing technologies, thus realizing the comprehensive monitoring of tunnel structures, environments, and external disturbances. The design of this architecture follows a three-dimensional sensing network in the physical space, wavelength domain, and time domain, combined with the space-division multiplexing (SDM), wavelength-division multiplexing (WDM), and time-division multiplexing (TDM) technologies of seven-core optical fibers, aiming to provide accurate and real-time monitoring results through seamless data fusion.

[0106] 1) Bottom layer: Demodulation of the original optical signal into physical quantities

[0107] At the bottom layer, the original optical signal is first collected and demodulated through different cores in the seven-core optical fiber (such as BOTDA, φ-OTDR, ROTDR, and FBG). Each optical fiber sensing channel is processed by different demodulation technologies to obtain the corresponding physical quantity data. During this process, all data is converted from the original optical signal into physical quantities (strain, temperature, vibration intensity), and these data are forwarded to the next layer for spatio-temporal alignment.

[0108] 2) Middle layer: Space-time alignment

[0109] In the middle layer, data from different cores in the seven-core optical fiber needs to be space-time aligned. The main task of this layer is to ensure the unification of data from different cores in the spatial and temporal dimensions, ensuring the synchronous operation of all cores and the unified representation of data.

[0110] (1) Time alignment:

[0111] Due to the time differences in signal acquisition from different cores in the seven-core optical fiber, the system must ensure the time alignment of data through high-precision synchronous triggering technology. By using high-performance hardware platforms such as FPGA to generate precise timing signals, the data acquisition time points of each sensing module are strictly synchronized, thus avoiding data misalignment.

[0112] (2) Space alignment:

[0113] BIM (Building Information Modeling) mapping: The BIM model provides an accurate basis for space alignment. The strain / temperature data of the entire tunnel length provided by BOTDA and the local point-type monitoring data provided by FBG need to be mapped into the three-dimensional model of the tunnel. The position of each core in the BIM model is accurately calibrated to ensure the matching of data with the spatial position of the tunnel structure.

[0114] Data fusion and map overlay: The data from different cores are overlaid according to their corresponding positions in the BIM model to form a complete tunnel health status map. Through space alignment, the data of BOTDA and FBG can complement each other. BOTDA provides long-range deformation data of the tunnel, while FBG provides high-precision local monitoring data of key points.

[0115] (3) Challenges in data fusion and space-time alignment: Differences in precision, operating frequency, wavelength, etc. of different cores require the system to have a high degree of flexibility and robustness to ensure the accuracy during data fusion. For example, the distributed strain data of BOTDA and the point-type strain data of FBG need to be fused into a unified tunnel health model through a spatial interpolation algorithm.

[0116] 3) High layer: Evaluating the comprehensive risk index through Bayesian network

[0117] In the high layer, the system conducts risk assessment through a Bayesian network, and evaluates the overall safety risk of the tunnel by combining the comprehensive analysis of various sensing data.

[0118] (1) Construction of the Bayesian network model:

[0119] A Bayesian network is a probability-based model that correlates the data of different cores in a seven-core optical fiber through a conditional dependence graph and uses known data to infer unknown situations. In a Bayesian network, the observed data of each core serves as a node, and the conditional dependence relationship between different variables is represented by edges between the nodes. Through Bayesian inference, the system can make effective inferences under various uncertain conditions.

[0120] (2) Calculation of the comprehensive risk index:

[0121] Through Bayesian inference, the system fuses and calculates multiple sensing data to obtain a comprehensive risk index:

[0122] P(Failure) = ∑ i,j,k,l P(Settlement i )·P(Deformation j | Settlement i )·P(Fire k | Temperature Rise)·P(Intrusion l | Vibration)·w i,j,k,l

[0123] Among them, P(Failure) represents the total probability of a comprehensive failure occurring in the tunnel system and is the joint probability under all possible combinations of risk factors; Settlement i represents the i-th tunnel settlement state (such as slight settlement, moderate settlement, severe settlement), and P(Settlement i ) is its prior probability of occurrence; Deformation j represents the j-th tunnel deformation state (such as lateral deformation, longitudinal cracking), and P(Deformation j | Settlement i ) represents the conditional probability of deformation state j when settlement state i occurs; Temperature Rise represents the environmental event of abnormal temperature increase, and P(Fire k | Temperature Rise) represents the probability of a k-th level fire occurring when the temperature rises to a certain threshold; P(Intrusion l | Vibration) represents the probability of an l-th level intrusion event occurring under a specific vibration intensity; The weight coupling coefficient w i,j,k,l represents the correction of the synergistic effect of different risk combinations on the failure probability.

[0124] The above index combines multi-dimensional data such as tunnel settlement, deformation, temperature, and vibration, comprehensively considers the influence of different risk factors, and the risk index will be dynamically updated to evaluate the safety status of the tunnel based on the latest collected data.

[0125] (3) Risk warning and decision support:

[0126] Real-time warning mechanism: When the comprehensive risk index exceeds the set safety threshold, the system will issue a real-time warning. For example, if the strain rate monitored by the BOTDA fiber core exceeds 5 με / h and local deformation is verified by the FBG fiber core, the system will automatically call the Bayesian network for further analysis to determine whether there is a potential settlement risk. If the risk is confirmed, the system will issue a warning to the relevant departments in advance.

[0127] Decision support system: The system can not only provide warning information, but also put forward safety optimization suggestions by analyzing historical data, on-site real-time monitoring data and environmental change factors. The operation and maintenance personnel can make quick adjustments and interventions based on the analysis results provided by the system.

[0128] Through the comprehensive analysis of strict spatio-temporal alignment and Bayesian network, this data fusion architecture can realize the synchronous monitoring and intelligent warning of multiple tunnel parameters. Through the data fusion of the monitoring data of different fiber cores in the same optical fiber such as BOTDA, FBG, and ROTDR, the system can provide excellent performance in terms of high precision, real-time and reliability, meeting the high standards of subway tunnel safety monitoring.

[0129] In this embodiment, the warning and monitoring module includes a settlement warning and monitoring module, a circumferential deformation warning and monitoring module, a fire warning and monitoring module, and an external intrusion warning and monitoring module. Multiple potential disaster factors are often interrelated, and a single warning system is difficult to comprehensively evaluate multiple risks, which may lead to false alarms (for example, train vibration is misjudged as illegal intrusion) or missed alarms (such as failure to detect external intrusion in time). Therefore, through the fusion and real-time monitoring of multiple parameters, this embodiment realizes the real-time integration and analysis of multiple monitoring data such as temperature, strain, and vibration, which can effectively avoid false alarms and missed alarms that may be caused by a single monitoring method, and improve the accuracy and response speed of the warning system. The specific warning logic is expressed as:

[0130] I. Settlement warning and monitoring module

[0131] Settlement warning is mainly used to monitor the stability of the tunnel structure, especially in the case of long-term operation or the action of external factors, which may cause settlement or deformation of the tunnel. To ensure timely detection of potential settlement risks, the system will conduct multi-dimensional analysis by combining the monitoring data of the BOTDA fiber core and the FBG fiber core:

[0132] (1) BOTDA settlement monitoring:

[0133] By monitoring the Brillouin frequency shift, the BOTDA fiber core can provide distributed strain data over the entire length of the tunnel. When settlement occurs, there is usually a significant change in the strain gradient. The system sets the trigger condition for settlement warning as the strain gradient exceeding 0.05% / m continuously for 10 meters, that is, the strain change in a certain section of the tunnel exceeds the set threshold, indicating that the tunnel structure may have a settlement trend.

[0134] (2) FBG local strain verification:

[0135] By monitoring the small strain changes at key parts such as segment joints and bolt connections, the FBG fiber core can provide high-precision local strain data. When the BOTDA fiber core monitors the strain gradient change over the entire length, the FBG fiber core can further verify the local deformation. If the local deformation exceeds 50 με, the system will determine it as a possible settlement risk and trigger a warning.

[0136] (3) Data fusion and warning trigger:

[0137] If the BOTDA fiber core monitors that the continuous strain gradient exceeds the threshold and the local deformation verified by the FBG fiber core exceeds the standard, the system will automatically trigger a settlement warning, and highlight the affected area through the BIM model to prompt the operation and maintenance personnel to conduct inspections and interventions.

[0138] II. Circumferential deformation warning monitoring module

[0139] Circumferential deformation monitoring mainly focuses on the deformation of the tunnel's circular structure (such as segments, joints, bolts, etc.) under the action of force, especially the circumferential strain changes in the tunnel structure due to settlement or external forces. The BOTDA fiber core and the FBG fiber core in the seven-core optical fiber work together to provide accurate circumferential deformation data, helping the operation and maintenance personnel to detect potential structural problems in advance.

[0140] (1) BOTDA monitors circumferential strain changes:

[0141] BOTDA demodulation and circumferential strain: Through Brillouin scattering frequency shift technology, the BOTDA fiber core can monitor the strain distribution of the entire length of the tunnel in real time and identify the changes in circumferential strain. Circumferential strain usually occurs when there is local uneven stress or settlement in the tunnel's enclosure structure (such as segments), resulting in circumferential deformation. The BOTDA fiber core calculates the strain gradient by detecting the change in Brillouin frequency shift and accurately identifies the circumferential deformation of the tunnel.

[0142] Warning trigger condition: When the BOTDA fiber core monitors that the circumferential strain gradient of a certain section of the tunnel exceeds 0.1% / m, this indicates that the tunnel may have significant circumferential deformation. In particular, the circumferential strain change at the segment joints will be more significant. The system will trigger a warning to indicate possible structural deformation.

[0143] (2)Verification of local circumferential deformation of FBG:

[0144] Local circumferential strain monitoring: Fiber Bragg Grating (FBG) cores are deployed in key parts of the tunnel (such as segment joints and bolt connections). Then, by measuring the change in the reflection wavelength of the FBG, high-precision monitoring of local circumferential strain changes can be achieved. The FBG cores can provide micron-level strain data at parts of the tunnel with large circumferential forces (such as joints and crowns), capturing subtle changes in circumferential deformation.

[0145] Early warning trigger condition: When the local circumferential strain monitored by the FBG core exceeds 50 με, especially when obvious deformation occurs at segment joints or tunnel contact points, the system may determine it as structural deformation and send out an early warning signal.

[0146] (3)Circumferential deformation data fusion and early warning trigger:

[0147] Data fusion and linkage analysis: The data monitored by the Brillouin Optical Time Domain Analysis (BOTDA) core and the FBG core can be precisely identified for the circumferential deformation pattern through multi-dimensional fusion. The BOTDA core provides distributed strain data for the entire length of the tunnel, while the FBG core provides local high-precision strain data, further verifying the specific location of the deformation. Through the linkage of these two types of data, the system can comprehensively monitor the circumferential deformation of the tunnel.

[0148] Early warning mechanism: When the circumferential strain gradient in the full length range monitored by the BOTDA core exceeds the set threshold, and the local circumferential strain verified by the FBG core exceeds 50 με, the system will immediately trigger the circumferential deformation early warning and mark the deformation area for the operation and maintenance personnel to check in time and take corresponding safety measures.

[0149] III. Fire early warning monitoring module

[0150] The fire early warning system is achieved by monitoring temperature anomalies in the tunnel, especially the rate and range of temperature increase, which are usually precursor signals of a fire. The collaborative role of Raman Optical Time Domain Reflectometry (ROTDR), and the FBG core is crucial in this process. Each sensing module collaborates to provide accurate temperature and vibration information to help detect fire risks in real time.

[0151] (1)ROTDR temperature monitoring:

[0152] The ROTDR core uses the Raman scattering principle to provide precise temperature monitoring by analyzing the ratio of the intensities of anti-Stokes light and Stokes light. When the temperature exceeds 70 °C, the system first identifies it as a possible fire risk. Further analyzing the temperature rise rate, if the temperature increases by more than 5 °C / min, it is the high-temperature area in the initial stage of the fire.

[0153] (2) Vibration interference elimination:

[0154] Fire monitoring needs to eliminate the normal vibration interference caused by the operation of subway trains. The fiber core is used to monitor vibration signals. Through the spectral analysis of vibration signals, it can effectively distinguish the normal vibration caused by train operation and the abnormal vibration caused by fire. If the vibration signal of the fiber core does not show obvious abnormalities, it is confirmed that the temperature rise is not caused by a vibration source, and the fire risk is further investigated.

[0155] (3) FBG local temperature monitoring:

[0156] FBG local temperature monitoring: The FBG fiber core has extremely high spatial resolution and is especially suitable for monitoring the temperature of key areas inside the tunnel. The FBG fiber core can be used to monitor the temperature changes of local areas such as segment joints and bolt connections. Since fire is often accompanied by a sudden rise in local temperature, the FBG fiber core can provide temperature monitoring of these areas and further enhance the accuracy of fire warning.

[0157] Temperature anomaly verification: When the ROTDR fiber core detects that the overall temperature of the tunnel exceeds 70°C and the temperature rise rate exceeds 5°C / min, the FBG fiber core can further verify the local temperature anomaly to confirm whether a fire occurs in a certain local area. If the FBG fiber core monitors a sudden rise in temperature at some key parts (for example, the temperature exceeds 50°C), the system can further analyze the risk of this area and issue a more accurate warning.

[0158] (4) Data fusion and warning trigger:

[0159] Data fusion of multiple fiber cores: When the ROTDR fiber core detects that the temperature exceeds 70°C and the temperature rise rate exceeds 5°C / min, after the fiber core eliminates vibration interference, the local temperature monitoring provided by the FBG fiber core further verifies the abnormal area. All data will be fused on an efficient processing platform, combined with the temperature changes of the tunnel globally and locally, to accurately assess the fire risk.

[0160] Warning trigger mechanism: The system will automatically trigger a fire warning according to the data monitored by various fiber cores above. Once the fire risk is confirmed, the system will present the fire hot spot area through the real-time monitoring interface, and the operation and maintenance personnel will immediately receive the warning information. The system can not only locate the fire source but also accurately determine the location of the fire, helping the operation and maintenance personnel take prompt actions.

[0161] IV. External intrusion warning and monitoring module

[0162] The main objective of the tunnel external abnormal intrusion monitoring system is to detect external illegal intrusion behaviors (such as construction vibration, underground excavation, destructive activities, etc.), which may pose a significant threat to the structural safety of the tunnel. Through the combined application of the BOTDA fiber core and the fiber core, the system can efficiently and accurately monitor and analyze the vibration sources inside and outside the tunnel, thereby identifying abnormal intrusion behaviors and issuing early warnings in a timely manner.

[0163] (1) The fiber core is used for external vibration monitoring

[0164] Real-time monitoring of vibration signals: By precisely measuring the phase change in the optical fiber, the fiber core can promptly sense vibrations or disturbances from the outside world. Especially in the case of illegal construction or sudden impacts outside the tunnel, the fiber core can quickly identify the vibration source and locate its occurrence position. Through the analysis of the vibration spectrum, the system can distinguish the normal vibration of the subway train from the abnormal vibration caused by illegal intrusion, further verifying whether the abnormal signal belongs to external interference.

[0165] Spectrum analysis and intrusion identification: By performing real-time analysis on the spectrum of the vibration signal, the fiber core can not only identify the source of the vibration but also extract the frequency characteristics of the vibration signal. These spectrum data help accurately determine the type of vibration, such as the mechanical vibration of illegal excavation or the instantaneous disturbance caused by external impacts. This process helps the system exclude normal structural vibration interference and further improve the accuracy of intrusion detection.

[0166] (2) Application of BOTDA in intrusion early warning:

[0167] Strain monitoring and vibration linkage analysis: The BOTDA fiber core can measure the strain and monitor its changes throughout the entire length of the tunnel structure. When external vibration or impact causes deformation of the tunnel structure, the BOTDA fiber core can promptly detect this change. By cross-verifying with the vibration data of the fiber core, the system can confirm whether it is an external disturbance that causes the strain change in the tunnel. The linkage analysis of strain monitoring and vibration data greatly improves the system's accurate identification ability of external disturbance sources.

[0168] Structural deformation and risk identification: The BOTDA fiber core has extremely high resolution for the strain distribution of the tunnel structure and can capture local minute deformations, especially in areas vulnerable to external influences such as segment joints and tunnel contact points. When the BOTDA fiber core monitors that the strain exceeds the set threshold, the system will judge whether there is an abnormal intrusion based on the matching degree between this strain change and the vibration signal, further confirming potential risks.

[0169] (3) Data Fusion and Early Warning Trigger

[0170] Data Fusion and Joint Analysis: The BOTDA core provides strain monitoring data over the full length range, while the core provides vibration monitoring data for a local area. Through data fusion analysis, the system can corroborate the data of both to ensure the accuracy of intrusion signals. When the spectrum of the vibration signal is abnormal and the BOTDA core monitors a corresponding strain change at the location, the system will immediately determine it as a possible external disturbance source.

[0171] Early Warning Trigger Mechanism: When the system detects that the vibration intensity exceeds the set threshold, and the duration and frequency are abnormal, combined with the change in strain data, the system will trigger an intrusion warning. In addition, the system will also conduct a comprehensive evaluation based on multi-dimensional information such as the intensity, duration, and spectral characteristics of the vibration source to determine the severity of the intrusion event. The warning information will be displayed on the monitoring interface in real time, and the operation and maintenance personnel can quickly locate the intrusion source based on the alarm information and take effective emergency response measures.

[0172] In this embodiment, the early warning monitoring module is used to display the parameter information in a graphical manner for monitoring. Specifically, this embodiment provides a tunnel disaster early warning visualization platform, which provides an intuitive and graphical display of the tunnel health status through real-time monitoring data and early warning models, helping management personnel identify potential risks and make decisions. The main functions of the platform include:

[0173] (1) Real-time Monitoring Data Display: Display the real-time data of temperature, strain, vibration, etc. collected by BOTDA, FBG, ROTDR, and the core in the seven-core optical fiber, and display the data changes and trends through charts (such as line charts, bar charts, etc.).

[0174] (2) Early Warning Information Display: The platform displays early warning information at different levels according to the preset threshold, and provides a real-time early warning prompt box to display the warning type, location, and impact degree. At the same time, the historical early warning records help analyze the long-term health status of the tunnel.

[0175] (3) Multi-parameter Data Fusion and Analysis: By fusing multi-dimensional data provided by BOTDA, FBG, ROTDR, and the core in the seven-core optical fiber, evaluate potential risks, and identify abnormal patterns through spatio-temporal correlation analysis to trigger early warnings.

[0176] (4) 3D Visualization Model: Use BIM technology to perform three-dimensional modeling of the tunnel, display the distribution of monitoring data in real time, and highlight hot spots, such as areas with abnormal temperature or structural deformation.

[0177] (5) Emergency response and linkage mechanism: Automatically activate the emergency response mechanism according to the warning level, such as fire extinguishing, ventilation, or closing the affected area, and provide decision-making support in combination with AI algorithms.

[0178] (6) Data storage and analysis: The platform stores historical monitoring data, supports data backtracking and trend analysis, and helps predict future risks and accidents.

[0179] This platform integrates real-time monitoring, data analysis, and intelligent warning functions, providing comprehensive support for the safety guarantee of tunnel structures.

[0180] In summary, this embodiment provides a tunnel multi-parameter synchronous monitoring, fusion, and correlation warning system based on seven-core optical fibers. The system in this embodiment uses the space-division multiplexing technology of seven-core optical fibers and can provide comprehensive and real-time health monitoring and warning for subway tunnels through multi-parameter fusion measurement.

[0181] Embodiment 2

[0182] On the one hand, this application embodiment provides a tunnel multi-parameter synchronous monitoring, fusion, and correlation warning system based on seven-core optical fibers. The fusion and correlation warning system provided in this embodiment is basically the same as the fusion and correlation warning system provided in Embodiment 1, except that: in this embodiment, the distance between adjacent circumferential sensing optical fibers is 5m.

[0183] On the other hand, this application embodiment provides a tunnel multi-parameter synchronous monitoring method based on seven-core optical fibers for the tunnel multi-parameter synchronous monitoring, fusion, and correlation warning system based on seven-core optical fibers in Embodiment 1, as Figure 6 shown, including:

[0184] Synchronously monitor the physical parameters along the seven-core optical fiber in the tunnel through the seven-core optical fiber. The physical parameters include temperature, strain, and vibration;

[0185] Collect physical parameter data in real time through the seven-core optical fiber;

[0186] Demodulate and fuse the collected physical parameter data signals to obtain parameter information;

[0187] Display the parameter information in a graphical manner for monitoring, and judge whether there are potential health risks in the tunnel by comparing the parameter information with the corresponding preset thresholds, so as to give a warning.

[0188] Specifically, in this embodiment, relying on the ROTDR temperature sensing core, BOTDA distributed strain core in the seven-core optical fiber, and Vibration monitoring core, constructing a temperature-strain-vibration multi-dimensional sensing matrix. Among them, the ROTDR temperature core realizes real-time reconstruction of the tunnel full-section temperature field with a spatial resolution of 0.5 m. When a local temperature rise change exceeding the set threshold is detected, a primary fire warning is triggered; the BOTDA strain core synchronously obtains the circumferential and longitudinal strain distributions of the tunnel through Brillouin frequency shift demodulation technology with a spatial resolution of 1 m, and combines the adjacent fiber core temperature compensation algorithm to eliminate the thermally induced strain interference; The vibration core accurately captures abnormal vibration events with a spatial resolution of 40 m, and distinguishes mechanical shocks from normal operation vibrations through wavelet energy spectrum analysis.

[0189] Multi-parameter correlation analysis is achieved through the following technical path: First, establish a temperature-strain dual-domain feature matrix. When the ROTDR temperature core detects an abnormal temperature rise, synchronously retrieve the strain gradient data of the corresponding spatial coordinates of the BOTDA strain core. If a compressive strain of more than 0.05% appears in the same location and shows a radial diffusion characteristic, it is determined as a thermal deformation of the structure caused by fire; if the strain distribution shows uniform circumferential expansion, a circumferential deformation warning is triggered. For For the transient shock signals captured by the vibration core, the system automatically correlates the time-varying response data of the BOTDA strain core. When the vibration event and the strain mutation show strong correlation in the spatio-temporal dimension, it is confirmed as an external abnormal intrusion event.

[0190] In particular, aiming at the defect that traditional temperature monitoring is vulnerable to environmental interference, this embodiment innovatively introduces a multi-core cross-verification mechanism. That is, when the ROTDR temperature core detects an abnormal temperature rise, the data authenticity is verified through the adjacent FBG temperature calibration core, and at the same time, combined with the thermal-mechanical coupling characteristic analysis of the BOTDA strain core, the real fire and equipment thermal disturbances are effectively distinguished.

[0191] The solution of this embodiment breaks through the technical bottlenecks of traditional discrete sensors in terms of spatial synchronization and data fusion degree, realizes spatio-temporal synchronous perception of multiple physical quantities through the space division multiplexing architecture of seven-core optical fiber, and constructs an intelligent monitoring system with self-diagnosis ability. Its specific warning flow chart is as Figure 7 shown.

[0192] In summary, the present invention provides a method for synchronously monitoring and fusing correlation warning of tunnel multi-parameters based on seven-core optical fiber for the tunnel multi-parameter synchronous monitoring and warning system based on seven-core optical fiber, which can monitor and warn the tunnel settlement, circumferential deformation, fire, and external intrusion in real time.

[0193] It is easy for those skilled in the art to understand that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A tunnel multi-parameter synchronous monitoring, fusion and correlation warning system based on a seven-core optical fiber, characterized in that Including: A sensing module, a data acquisition module, a processing module, and an early warning and monitoring module; The sensing module includes a seven-core optical fiber arranged in the tunnel. A first FBG core is arranged at the center position of the seven-core optical fiber. The first FBG core is used to provide accurate measurement of the local strain and temperature in the tunnel. The remaining 6 cores are evenly distributed circumferentially. Among them, the second FBG core and the third FBG core are symmetrically arranged according to the first FBG core. The second FBG core and the third FBG core provide monitoring of local strain. The first BOTDA core and the second BOTDA core are symmetrically arranged according to the first FBG core. The first BOTDA core and the second BOTDA core provide monitoring of distributed strain and temperature. The ROTDR core and the φ-OTDR core are symmetrically arranged according to the first FBG core. The ROTDR core provides temperature monitoring, and the φ-OTDR core provides vibration monitoring; The data acquisition module is used to collect physical parameter data in real time through the sensing module; The processing module is used to demodulate and fuse the physical parameter data signals collected by the data acquisition module to obtain parameter information; The early warning and monitoring module is used to display the parameter information in a graphical manner for monitoring, and compare the parameter information with the corresponding preset threshold to determine whether there are potential health risks in the tunnel and thus issue an early warning.

2. The tunnel multi-parameter synchronous monitoring fusion correlation early warning system based on a seven-core optical fiber according to claim 1, wherein, The seven-core optical fiber includes a circumferential seven-core optical fiber and a longitudinal seven-core optical fiber.

3. The tunnel multi-parameter synchronous monitoring fusion correlation early warning system based on a seven-core optical fiber according to claim 2, wherein The longitudinal seven-core optical fiber is laid parallel to the crown and the two side haunches of the circular shield segment of the tunnel and extends horizontally along the tunnel axis.

4. The tunnel multi-parameter synchronous monitoring fusion correlation warning system based on a seven-core optical fiber according to claim 2, characterized in that, The circumferential seven-core optical fiber extends circumferentially along the inner arc surface of the circular shield segment of the tunnel, following the principle of "Ω" type wiring layout. Adjacent circumferential sensing optical fibers are connected by a seven-core optical fiber arranged along the tunnel axis at the bottom of the tunnel.

5. The tunnel multi-parameter synchronous monitoring fusion correlation early warning system based on a seven-core optical fiber according to claim 4, wherein The distance between adjacent circumferential sensing optical fibers is 3 - 5 m.

6. The tunnel multi-parameter synchronous monitoring fusion correlation early warning system based on a seven-core optical fiber according to claim 1, characterized in that, The early warning and monitoring module includes a settlement early warning and monitoring module, a circumferential deformation early warning and monitoring module, a fire early warning and monitoring module, and an external intrusion early warning and monitoring module; The settlement early warning and monitoring module is used to perform multi-dimensional analysis based on the monitoring data of the distributed strain provided by the first BOTDA core and the second BOTDA core and the monitoring data of the local strain provided by the second FBG core and the third FBG core to determine whether there is a settlement risk in the tunnel and thus issue an early warning.

7. The tunnel multi-parameter synchronous monitoring fusion correlation early warning system based on a seven-core optical fiber according to claim 6, characterized in that The circumferential deformation early warning and monitoring module is used to perform multi-dimensional analysis based on the monitoring data of the circumferential strain provided by the first BOTDA core and the second BOTDA core and the monitoring data of the local circumferential strain provided by the second FBG core and the third FBG core to determine whether there is a circumferential deformation risk in the tunnel and thus issue an early warning.

8. The tunnel multi-parameter synchronous monitoring fusion correlation early warning system based on a seven-core optical fiber according to claim 6, characterized in that The fire early warning and monitoring module is used to perform multi-dimensional analysis based on the temperature monitoring data provided by the ROTDR core and the first FBG core and the vibration monitoring data provided by the φ-OTDR core to determine whether there is a fire risk in the tunnel and thus issue an early warning.

9. The tunnel multi-parameter synchronous monitoring fusion correlation early warning system based on a seven-core optical fiber according to claim 6, characterized in that, The external intrusion warning and monitoring module is used to perform multi-dimensional analysis and judgment on whether there is a risk of external intrusion in the tunnel based on the vibration monitoring data provided by the φ-OTDR fiber core and the monitoring data of the distributed strain provided by the first BOTDA fiber core and the second BOTDA fiber core, so as to give an early warning.

10. A method for synchronous monitoring of multiple tunnel parameters based on a seven-core optical fiber for a tunnel multi-parameter synchronous monitoring, fusion and correlation warning system according to any one of claims 1-9, characterized in that, It includes: Synchronously monitor the physical parameters along the seven-core optical fiber in the tunnel through the seven-core optical fiber, and the physical parameters include temperature, strain, and vibration; Real-time collect the physical parameter data through the seven-core optical fiber; Demodulate and fuse the collected physical parameter data signals to obtain parameter information; Display the parameter information in a graphical manner for monitoring, and compare the parameter information with the corresponding preset threshold to judge whether there is a potential health risk in the tunnel, so as to give an early warning.

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