A Method and System for Monitoring Tunnel Leakage Based on Laser Scanning and Brillouin Sensing
By combining 3D laser scanning with Brillouin sensing, risk areas are identified and sensing fibers are deployed in a differentiated manner. This solves the problems of continuous dynamic monitoring of tunnel water leakage and high cost in existing technologies, and enables timely response and accurate location of early trace leakage.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA STATE RAILWAY GRP CO LTD
- Filing Date
- 2026-03-12
- Publication Date
- 2026-06-30
AI Technical Summary
In existing technologies, three-dimensional laser scanning cannot achieve continuous dynamic monitoring, and distributed fiber optic sensing is insufficient for responding to early trace leaks and has high deployment costs.
Combining 3D laser scanning and Brillouin sensing, continuous sensing and positioning are achieved by identifying risk areas and using differentiated deployment of sensing fibers, including high-density S-shaped winding, medium-density dual-line parallel, and low-density single-line straight deployment, with the fiber adopting a double-layer encapsulation structure.
It enables continuous dynamic monitoring of tunnel water leakage, reduces costs, and can respond promptly to early trace leaks, forming an integrated solution for early identification, precise deployment, real-time monitoring, and visualized backtracking.
Smart Images
Figure CN122306319A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of tunnel seepage monitoring technology, specifically to a method and system for monitoring tunnel seepage based on laser scanning and Brillouin sensing. Background Technology
[0002] In existing technologies, although three-dimensional laser scanning can provide high-precision spatial information, it cannot achieve continuous dynamic monitoring; although distributed fiber optic sensing has real-time monitoring capabilities, it usually adopts a uniform deployment method, resulting in insufficient response to early trace leaks, and the deployment is blind and costly. Summary of the Invention
[0003] To address the aforementioned problems, this invention provides a method and system for monitoring tunnel water leakage based on laser scanning and Brillouin sensing, aiming to propose an integrated solution for early identification, precise deployment, real-time monitoring, and visualized backtracking of tunnel monitoring.
[0004] According to a first aspect of the present disclosure, a method for monitoring tunnel leakage based on laser scanning and Brillouin sensing is provided, comprising the following steps: A 3D laser scanner was used to acquire spatial geometric point cloud data and reflection intensity data of the tunnel interior wall; Risk area identification and classification based on spatial geometric point cloud data and reflection intensity data; The results of risk area identification and classification are transformed into an executable sensor network deployment plan; The physical implementation of sensing optical fiber is based on the sensor network deployment scheme. The sensing optical fiber adopts a double-layer encapsulation structure, with the inner layer being a communication-grade tight-buffered optical fiber and the outer layer being water-swellable rubber. Using the deployed sensing optical fibers, continuous sensing and localization of leakage events are achieved based on Brillouin optical time-domain analysis technology. The fiber optic positioning data is mapped onto a 3D tunnel model, and abnormal events are mapped in 3D. Finally, the location of the leakage point and the risk zone are displayed in the 3D tunnel model.
[0005] A further technical solution of the present invention is to further support leakage path tracing and impact range assessment in the three-dimensional tunnel model.
[0006] A further technical solution of the present invention is as follows: the identification of risk areas is achieved by quantifying the leakage probability index. The typical reflection intensity reference value of the dry surface and the typical reflection intensity reference value of the water surface are established respectively, and the typical reflection intensity reference value of the dry surface and the reflection intensity data of any coordinate point (x,y) are established. The leakage probability index is the ratio of the two differences and is negatively correlated with the reflection intensity data of the coordinate point (x,y).
[0007] A further technical solution of the present invention is: the risk area classification is achieved by quantifying connected regions. The comprehensive risk value is achieved, and the comprehensive risk value is related to the region. The weighted sum of the internal average leakage probability index, the area of the region, and the average gradient intensity of the region boundary is positively correlated.
[0008] A further technical solution of the present invention is to transform the identification and classification results of risk areas into an executable sensor network deployment scheme, specifically including: for high-risk areas, a high-density S-shaped coiled deployment is adopted; for medium-risk areas, a medium-density dual-line parallel deployment is adopted; and for low-risk areas, a low-density single-line straight deployment is adopted. Each deployment method is achieved by the same continuous Brillouin sensing optical fiber through folding-back laying.
[0009] A further technical solution of the present invention is as follows: In the high-density S-shaped winding arrangement, the radius of curvature at each bend is not less than the curvature threshold, wherein the curvature threshold is the ratio between the product of the Young's modulus of the optical fiber and the radius of the optical fiber cladding, and the allowable stress of the material.
[0010] A further technical solution of the present invention is as follows: based on Brillouin optical time-domain analysis technology, continuous sensing and localization of leakage events are performed, specifically including: quantifying the change in Brillouin frequency shift at position z along the optical fiber, wherein the change is the sum of strain data and temperature change data at position z, wherein the strain data is the product of strain coefficient and optical fiber strain at position z, and the temperature change data is the product of temperature coefficient and temperature change at position z.
[0011] A further technical solution of the present invention is: the temperature change at position z is obtained by laying temperature compensation optical fibers in the tunnel; The radial compressive strain generated by the expansion of water-swelling rubber on the optical fiber is converted into axial strain through the Poisson effect, which is the optical fiber strain at position z.
[0012] A further technical solution of the present invention is: continuous sensing and localization of leakage events, which is further achieved through system spatial resolution. The system spatial resolution is directly proportional to the speed of light and inversely proportional to the product of twice the refractive index of the optical fiber and the spectral width of the detection pulse.
[0013] A further technical solution of the present invention is: mapping fiber optic positioning data to a three-dimensional tunnel model and performing three-dimensional mapping of abnormal events, specifically including: The coordinates of the 3D laser scanning point cloud are transformed to the global coordinate system using a pre-calibrated transformation matrix. For an anomalous event located at a distance s from the starting point on an optical fiber, what are its coordinates in three-dimensional space? It is obtained by integration along the spatial path of the optical fiber.
[0014] According to a second aspect of the present disclosure, a tunnel leakage monitoring system based on laser scanning and Brillouin sensing is provided, the system comprising: The three-dimensional holographic data acquisition module is used to acquire spatial geometric point cloud data and reflection intensity data of the tunnel inner wall using a three-dimensional laser scanner; The intelligent assessment and zoning module for leakage risk is used to identify and classify risk areas based on spatial geometric point cloud data and reflection intensity data. The sensor network adaptive deployment planning module is used to transform the identification and classification results of risk areas into an executable sensor network deployment plan. The fiber optic packaging and collaborative deployment module is used to physically realize the sensing fiber based on the sensor network deployment scheme. The sensing fiber adopts a double-layer packaging structure, with the inner layer being a communication-grade tight-fitting fiber and the outer layer being water-swellable rubber. The dynamic sensing and localization module for leakage events is used to continuously sense and locate leakage events using the deployed sensing optical fibers and based on Brillouin optical time domain analysis technology. The 3D visualization traceability and diagnosis module is used to map fiber optic positioning data to a 3D tunnel model and perform 3D mapping of abnormal events, ultimately displaying the location of leakage points and risk zones in the 3D tunnel model.
[0015] This disclosure provides a method and system for monitoring tunnel seepage based on laser scanning and Brillouin sensing. It enables continuous dynamic monitoring of tunnel seepage. For high-risk areas, a high-density S-shaped coiled deployment is used; for medium-risk areas, a medium-density dual-line parallel deployment is used; and for low-risk areas, a low-density single-line straight deployment is used. All deployment methods are achieved by the same continuous Brillouin sensing optical fiber through folding and rewinding. This deployment not only reduces costs but also enables timely response to early, minute leaks, forming an integrated solution of "early identification—precise deployment—real-time monitoring—visualized backtracking." It is suitable for early identification, precise location, and real-time monitoring of seepage in underground engineering projects such as railway tunnels, highway tunnels, subway tunnels, and water conservancy tunnels, and is particularly suitable for long tunnels, high-risk sections, and critical infrastructure requiring high monitoring accuracy.
[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description
[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.
[0018] Figure 1This is a flowchart of the tunnel seepage monitoring method based on laser scanning and Brillouin sensing according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the risk zoning assessment process according to an embodiment of the present invention; Figure 3 This is a schematic diagram of risk zoning and differentiated deployment in an embodiment of the present invention; Figure 4 This is a structural diagram of a tunnel seepage monitoring system based on laser scanning and Brillouin sensing, according to an embodiment of the present invention. Detailed Implementation
[0019] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present invention are shown in the drawings, not the entire structure.
[0020] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. The process can be terminated when its operation is complete, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.
[0021] The following embodiments are provided for a proposed method and system for monitoring tunnel seepage water based on laser scanning and Brillouin sensing: like Figure 1 As shown, a method for monitoring tunnel seepage water based on laser scanning and Brillouin sensing includes the following steps: S1. Use a 3D laser scanner to obtain spatial geometric point cloud data and reflection intensity data of the tunnel inner wall; S2. Identify and classify risk areas based on spatial geometric point cloud data and reflection intensity data; S3. Transform the identification and classification results of risk areas into an executable sensor network deployment plan; S4. Physical implementation of sensing optical fiber based on sensor network deployment scheme, wherein the sensing optical fiber adopts a double-layer encapsulation structure, the inner layer is communication grade tight-buffered optical fiber, and the outer layer is water-swellable rubber. S5. Using the deployed sensing optical fibers, based on Brillouin optical time domain analysis technology, continuous sensing and localization of leakage events are carried out. S6. Map the fiber optic positioning data to the 3D tunnel model and perform 3D mapping of abnormal events. Finally, display the location of the leakage point and the risk zone in the 3D tunnel model. In a preferred embodiment, the 3D tunnel model further supports leakage path tracing and impact range assessment.
[0022] In the specific implementation of S1, a high-precision 3D laser scanner is used to simultaneously collect spatial geometric point cloud data of the tunnel inner wall. With reflection intensity data Among these, reflectance intensity data is a key feature for identifying leakage areas, and its mathematical expression is the scanning location. The function is given. Due to laser absorption, the reflectivity of leaking areas and damp surfaces is significantly reduced, forming low-value dark areas in the reflectance intensity image, satisfying the relationship: , in This is a typical reference value for the reflectance intensity of dry lining.
[0023] Risk area identification is achieved by quantifying the leakage probability index. The typical reflection intensity reference value of the dry surface and the typical reflection intensity reference value of the water surface are established, and the typical reflection intensity reference value of the dry surface and the reflection intensity data of any coordinate point (x,y) are also established. The leakage probability index is the ratio of the two differences and is negatively correlated with the reflection intensity data of the coordinate point (x,y).
[0024] The specific implementation process of S2 is as follows: Figure 2 As shown, based on reflection intensity data The following quantitative model enables the automatic identification and classification of risk areas: Preliminary quantitative model of leakage probability: , in, The leakage probability index is the coordinate point (x, y). This represents a typical reference value for the reflectance intensity of a water surface. The model transforms optical differences into a continuous probability distribution.
[0025] The tunnel image is segmented and classified into regions. The risk level is determined by quantizing the connected regions. The comprehensive risk value is achieved, and the comprehensive risk value is related to the region. The weighted sum of the internal average leakage probability index, the area of the region, and the average gradient intensity of the region boundary is positively correlated.
[0026] In the specific implementation process, the regional risk level comprehensive assessment model is as follows: For connected regions (i.e., potential "dark spots"), its overall risk value Calculated by the following formula: , in: For the region Internal average leakage probability; For the area, For normalized reference area; The average gradient intensity at the region boundary reflects the activity of the leakage front. , , The weighting coefficients are determined based on engineering experience and historical data to satisfy... .
[0027] according to The numerical range divides the tunnel into high-altitude areas. ,middle ,Low Three risk areas, among which , This is a preset threshold.
[0028] The identification and classification of risk areas are transformed into an executable sensor network deployment scheme, which includes: for high-risk areas, a high-density S-shaped coiled deployment is adopted; for medium-risk areas, a medium-density dual-line parallel deployment is adopted; and for low-risk areas, a low-density single-line straight deployment is adopted. Each deployment method is achieved by the same continuous Brillouin sensing fiber through folding-back laying.
[0029] In practice, the risk assessment results are transformed into an executable sensor network deployment plan. It adaptively plans differentiated fiber optic deployment paths and densities based on different risk levels. High-risk areas In a high-density S-shaped coiled arrangement, the radius of curvature at each bend is not less than a curvature threshold, which is the ratio between the product of the fiber's Young's modulus and the fiber cladding radius, and the allowable stress of the material. Specifically, a high-density S-shaped coiled arrangement is adopted, with the U-shaped loop amplitude set as follows: The vertical spacing is To ensure the mechanical properties of the optical fiber, the radius of curvature at all bends is... Must meet: , in, This represents the Young's modulus of the optical fiber. The radius of the fiber cladding is _____. This represents the allowable stress of the material.
[0030] medium-risk areas The network is laid out in a low-density, single-line straight-line configuration, primarily to ensure global network connectivity.
[0031] low-risk areas The network is laid out in a low-density, single-line straight-line configuration, primarily to ensure global network connectivity.
[0032] like Figure 3 As shown, high-density S-shaped layout, medium-density dual-line parallel layout, and low-density single-line straight layout are all achieved by using the same continuous Brillouin sensing fiber through a fold-back installation. Specifically, the dual-line parallel layout is formed by laying the "outbound" and "return" segments of the fiber in parallel with a fixed spacing in space. The two fiber segments are connected at the endpoints of the dual-line parallel area by a U-shaped fold-back bend that meets the minimum bending radius requirement. The starting end of the S-shaped layout is connected to the end of the "return" segment of the adjacent dual-line parallel layout or the end of the single-line straight layout.
[0033] In the specific implementation of S4, the physical realization of the sensing unit involves a double-layer encapsulation structure for the sensing optical fiber: the inner layer is a communication-grade tight-buffered optical fiber, and the outer layer is water-swelling rubber (WSR). When the WSR comes into contact with water, its volume expansion rate... It can be represented as: , in, The coefficient of thermal expansion of the material. For contact time, The water concentration is [value missing]. This expansion induces radial compressive strain on the optical fiber. This is then converted into axial strain through the Poisson effect. .
[0034] Based on Brillouin optical time-domain analysis technology, continuous sensing and localization of leakage events are performed. Specifically, this includes quantifying the change in Brillouin frequency shift at position z along the optical fiber. This change is the sum of strain data and temperature change data at position z, where the strain data is the product of the strain coefficient and the fiber strain at position z, and the temperature change data is the product of the temperature coefficient and the temperature change at position z.
[0035] The temperature change at location z is obtained by laying temperature-compensated optical fibers in the tunnel; The radial compressive strain generated by the expansion of water-swelling rubber on the optical fiber is converted into axial strain through the Poisson effect, which is the optical fiber strain at position z.
[0036] Continuous sensing and localization of leakage events are further achieved through system spatial resolution, which is directly proportional to the speed of light and inversely proportional to the product of twice the fiber refractive index and the detection pulse spectral width.
[0037] In practice, continuous sensing and precise location of leakage events are achieved based on Brillouin Optical Time Domain Analysis (BOTDA) technology. Its physical basis is Brillouin dispersion radio frequency shift. With fiber strain Linear relationship with temperature T: , in: This represents the Brillouin frequency shift at position z along the fiber. The strain coefficient (approximately 0.05 MHz / με ); This is the temperature coefficient (approximately 1.0 MHz / ℃). , These represent the strain and temperature change at position z, respectively.
[0038] Temperature-compensated optical fibers can be laid in the tunnel to obtain... This allows us to obtain the strain primarily reflecting the expansion of the packaged WSR upon contact with water. By solving the above equations and combining them with the signal propagation time, the spatial location of the leak point can be achieved, thus increasing the system's spatial resolution. Determined by the following formula: , Where c is the speed of light and n is the refractive index of the optical fiber. To detect the spectral width of the pulse.
[0039] The fiber optic positioning data is mapped to a 3D tunnel model, and 3D mapping of abnormal events is performed, specifically including: The coordinates of the 3D laser scanning point cloud are transformed to the global coordinate system using a pre-calibrated transformation matrix. For an anomalous event located at a distance s from the starting point on an optical fiber, what are its coordinates in three-dimensional space? It is obtained by integration along the spatial path of the optical fiber.
[0040] In the specific implementation process, deep fusion and visualization of multi-source monitoring data and 3D models are achieved. Key steps include: Data spatial registration: Mapping fiber optic positioning data (one-dimensional length coordinates s) to a three-dimensional tunnel model. First, using a pre-calibrated transformation matrix T, the laser scanning point cloud coordinates are... Transform to global coordinate system : , 3D mapping of events: For an abnormal event located on an optical fiber at a distance s from the starting point, its coordinates in 3D space. Obtained by integration along the optical fiber spatial path: , in, For fiber optic path in length The unit tangential vector at a given location is determined by the fiber optic routing trajectory in the 3D model.
[0041] Finally, the location of the leakage point, risk zone and historical evolution are highlighted in the 3D model, supporting leakage path tracing and impact range assessment.
[0042] Another embodiment is a tunnel leakage monitoring system 400 based on laser scanning and Brillouin sensing, the system 400 including: The three-dimensional holographic data acquisition module 410 is used to acquire spatial geometric point cloud data and reflection intensity data of the tunnel inner wall using a three-dimensional laser scanner; The intelligent assessment and zoning module 420 for leakage risk is used to identify and classify risk areas based on spatial geometric point cloud data and reflection intensity data. The sensor network adaptive deployment planning module 430 is used to transform the identification and classification results of risk areas into an executable sensor network deployment plan. The fiber optic packaging and collaborative deployment module 440 is used to physically realize the sensing fiber based on the sensor network deployment scheme. The sensing fiber adopts a double-layer packaging structure, with the inner layer being a communication-grade tight-fitting fiber and the outer layer being water-swellable rubber. The leakage event dynamic sensing and localization module 450 is used to continuously sense and locate leakage events using the deployed sensing optical fibers and based on Brillouin optical time domain analysis technology. The 3D visualization traceability and diagnosis module 460 is used to map fiber optic positioning data to a 3D tunnel model and perform 3D mapping of abnormal events, ultimately displaying the location of leakage points and risk zones in the 3D tunnel model.
[0043] In addition to the modules described above, the device may also include other components; however, since these components are not relevant to the embodiments of this disclosure, their illustrations and descriptions are omitted here.
[0044] The other specific working processes of the tunnel leakage monitoring system 400 based on laser scanning and Brillouin sensing are described in the above-described embodiment of the tunnel leakage monitoring method based on laser scanning and Brillouin sensing, and will not be repeated here.
[0045] In this document, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a step or method that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such a step or method.
[0046] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.
Claims
1. A tunnel water leakage monitoring method based on laser scanning and Brillouin sensing, characterized in that, Includes the following steps: A 3D laser scanner was used to acquire spatial geometric point cloud data and reflection intensity data of the tunnel interior wall; Risk area identification and classification based on spatial geometric point cloud data and reflection intensity data; The results of risk area identification and classification are transformed into an executable sensor network deployment plan; The physical implementation of sensing optical fiber is based on the sensor network deployment scheme. The sensing optical fiber adopts a double-layer encapsulation structure, with the inner layer being a communication-grade tight-buffered optical fiber and the outer layer being water-swellable rubber. Using the deployed sensing optical fibers, continuous sensing and localization of leakage events are achieved based on Brillouin optical time-domain analysis technology. The fiber optic positioning data is mapped onto a 3D tunnel model, and abnormal events are mapped in 3D. Finally, the location of the leakage point and the risk zone are displayed in the 3D tunnel model. 2.The tunnel leakage water monitoring method based on laser scanning and Brillouin sensing according to claim 1, wherein, Risk area identification is achieved by quantifying the leakage probability index. The typical reflection intensity reference value of the dry surface and the typical reflection intensity reference value of the water surface are established, and the typical reflection intensity reference value of the dry surface and the reflection intensity data of any coordinate point (x,y) are also established. The leakage probability index is the ratio of the two differences and is negatively correlated with the reflection intensity data of the coordinate point (x,y).
3. The tunnel seepage monitoring method based on laser scanning and Brillouin sensing according to claim 2, characterized in that, The classification of risk zones is achieved by quantifying the integrated risk value of a connected zone which is positively correlated to the weighted sum of the average leakage probability index within the zone , the area of the zone and the average gradient strength of the zone's border. 4.The tunnel leakage water monitoring method based on laser scanning and Brillouin sensing according to claim 1, wherein, The identification and classification of risk areas are transformed into an executable sensor network deployment scheme, which includes: for high-risk areas, a high-density S-shaped coiled deployment is adopted; for medium-risk areas, a medium-density dual-line parallel deployment is adopted; and for low-risk areas, a low-density single-line straight deployment is adopted. Each deployment method is achieved by the same continuous Brillouin sensing fiber through folding-back laying.
5. The tunnel seepage monitoring method based on laser scanning and Brillouin sensing according to claim 4, characterized in that, In a high-density S-shaped coiled arrangement, the radius of curvature at each bend is not less than the curvature threshold, which is the ratio between the product of the Young's modulus of the optical fiber and the radius of the optical fiber cladding, and the allowable stress of the material.
6. The tunnel seepage monitoring method based on laser scanning and Brillouin sensing according to claim 1, characterized in that, Based on Brillouin optical time-domain analysis technology, continuous sensing and localization of leakage events are performed. Specifically, this includes quantifying the change in Brillouin frequency shift at position z along the optical fiber. This change is the sum of strain data and temperature change data at position z, where the strain data is the product of the strain coefficient and the fiber strain at position z, and the temperature change data is the product of the temperature coefficient and the temperature change at position z.
7. The tunnel seepage monitoring method based on laser scanning and Brillouin sensing according to claim 6, characterized in that, The temperature change at location z is obtained by laying temperature-compensated optical fibers in the tunnel; The radial extrusion strain generated by the expansion of water-swelling rubber on the optical fiber is converted into axial strain through the Poisson effect, which is the optical fiber strain at position z.
8. The tunnel seepage monitoring method based on laser scanning and Brillouin sensing according to claim 7, characterized in that, Continuous sensing and localization of leakage events are further achieved through system spatial resolution, which is directly proportional to the speed of light and inversely proportional to the product of twice the fiber refractive index and the detection pulse spectral width.
9. The tunnel seepage monitoring method based on laser scanning and Brillouin sensing according to claim 1, characterized in that, The fiber optic positioning data is mapped onto a 3D tunnel model, and 3D mapping of abnormal events is performed, specifically including: The coordinates of the 3D laser scanning point cloud are transformed to the global coordinate system using a pre-calibrated transformation matrix. For an anomaly event located at a distance s from the starting point on an optical fiber, what are its coordinates in three-dimensional space? It is obtained by integration along the spatial path of the optical fiber.
10. A tunnel seepage monitoring system based on laser scanning and Brillouin sensing, characterized in that, The system includes: The three-dimensional holographic data acquisition module is used to acquire spatial geometric point cloud data and reflection intensity data of the tunnel inner wall using a three-dimensional laser scanner; The intelligent assessment and zoning module for leakage risk is used to identify and classify risk areas based on spatial geometric point cloud data and reflection intensity data. The sensor network adaptive deployment planning module is used to transform the identification and classification results of risk areas into an executable sensor network deployment plan. The fiber optic packaging and collaborative deployment module is used to physically realize the sensing fiber based on the sensor network deployment scheme. The sensing fiber adopts a double-layer packaging structure, with the inner layer being a communication-grade tight-fitting fiber and the outer layer being water-swellable rubber. The dynamic sensing and localization module for leakage events is used to continuously sense and locate leakage events using the deployed sensing optical fibers and based on Brillouin optical time domain analysis technology. The 3D visualization traceability and diagnosis module is used to map fiber optic positioning data to a 3D tunnel model and perform 3D mapping of abnormal events, ultimately displaying the location of leakage points and risk zones in the 3D tunnel model.