Method and system for rapidly detecting grouting cavity after tunnel lining

Abstract

The invention discloses a method and a system for rapidly detecting a grouting cavity after tunnel lining. Belongs to the technical field of civil engineering nondestructive testing. The method comprises the following steps: arranging a DAS optical fiber sensing array along a tunnel lining; exciting an artificial seismic source at a fixed interval and receiving a signal at a fixed offset; generating an equal offset section; calculating the theoretical travel time of the interface reflection wave of the grouting layer; an interface reflection amplitude is extracted on the section to generate a CBL curve, and meanwhile reflection wave travel time is extracted to generate a grouting travel time curve; by analyzing the amplitude anomaly and travel time deviation of the two curves, the cementing anomaly area is quickly identified, and the grouting cavity is positioned. The system comprises corresponding function modules. According to the method, the whole-section continuous coverage is realized by adopting distributed optical fiber sensing, a hyperbola joint interpretation mechanism is combined, the method has the advantages of high detection efficiency, strong anti-interference performance, intuitive field interpretation and the like, and the problems of low efficiency and dependence on complex inversion of a traditional method are solved.

Description

Technical Field

[0001] This invention relates to the field of non-destructive testing technology for tunnel lining engineering, and in particular to a rapid detection method and system for grouting voids after tunnel lining. Background Technology

[0002] Tunnels, as the backbone of modern underground transportation spaces, are crucial infrastructure for ensuring traffic flow. To ensure tunnel safety during construction and operation, continuous monitoring and accurate assessment of their safety and stability are essential for timely warnings of potential risks. Lining voids are a common tunnel defect, leading to stress concentration and redistribution around the void, severely impacting the tunnel structure's safety performance and accelerating the development of other lining defects. If not addressed promptly, lining voids can cause serious consequences such as arch collapse, lining cracking, and even overall instability, posing a serious threat to the long-term health of the tunnel structure. Therefore, accurately identifying grouting voids behind the tunnel lining is crucial for ensuring safe tunnel operation and is a vital component of tunnel health monitoring and anomaly early warning systems.

[0003] Currently, tunnel cavity detection methods can be divided into two categories: non-destructive testing (NDT) and destructive testing (DDT). NDT, primarily based on geophysical methods including ground-penetrating radar (GPR) and acoustic methods, has become the mainstream technology for tunnel lining quality inspection. GPR infers the structure and morphology of the medium behind the lining by analyzing the reflection characteristics of electromagnetic waves based on differences in the electrical properties of the medium. It is simple to operate and highly efficient, but easily interfered with by metal components such as steel reinforcement mesh and steel arches within the tunnel, making it difficult to effectively identify small-scale cavities behind the reinforcement. Acoustic methods utilize the acoustic properties of the medium, judging defects by changes in parameters such as the duration, amplitude, and frequency of ultrasonic waves propagating in concrete. They offer high resolution, but their detection method is single-point measurement, resulting in high costs for long-distance continuous detection, and the detection effect is significantly affected by the coupling state between the sensor and the concrete. Destructive testing methods, such as borehole imaging, can obtain more intuitive and accurate results, but they can cause localized damage to the lining structure and are only suitable for sampling inspections, making comprehensive coverage difficult, thus limiting their application scope.

[0004] In recent years, with the continuous expansion of tunnel construction, how to achieve real-time, comprehensive, and efficient detection of grouting voids in tunnel linings on-site has become one of the key issues in tunnel structural health monitoring. Existing methods have the following main problems and shortcomings in this regard: First, existing observation methods are mostly segmented (e.g., ground-penetrating radar) or single-point (e.g., acoustic probes) detection, requiring frequent movement of receiving equipment during the detection process, resulting in high time costs; Second, traditional non-destructive testing methods usually require inversion imaging of the collected data to aid interpretation, but the inversion process has characteristics such as nonlinearity and multiple solutions, requiring high-level data processing technology and making it difficult to quickly obtain detection conclusions on-site. Summary of the Invention

[0005] Therefore, the purpose of this invention is to provide a rapid detection method for grouting voids after tunnel lining. By deploying a distributed optical fiber sensor (DAS) array and combining it with a hyperbolic joint analysis mechanism, the complex geophysical imaging problem is transformed into morphological analysis of two intuitive curves, thus solving the long-standing problem of detecting grouting voids in tunnel engineering.

[0006] To achieve the above objectives, the present invention provides a method for rapid detection of grouting voids after tunnel lining, comprising the following steps: S1. A distributed acoustic sensing fiber optic array is laid along the tunnel lining, and an artificial vibration source is excited along the array at a fixed interval. S2. For each excitation source, acquire the DAS signal at a fixed offset distance, and generate an equioffset profile based on the DAS signals acquired from all sources. S3. Construct a tunnel lining structure model according to the layout rules in S1-S2 above, and repeatedly excite the seismic source to determine the theoretical travel time of the reflected waves from the first and second interfaces of the grouting layer. S4. On the equidistant offset profile, based on the theoretical travel time of the reflected wave from the first interface, the reflection amplitude information of each sensing position is extracted to generate a first parameter curve for characterizing the cementation state of the first interface. S5. On the equidistant profile, based on the theoretical travel time of the second interface, the actual travel time is extracted to generate a second parameter curve for characterizing the cementation state of the second interface. S6. By comprehensively analyzing the first parameter curve and the second parameter curve, identify the cementation abnormal area, thereby locating the grouting voids after lining.

[0007] Furthermore, the tunnel lining structure model includes a lining layer, a grouting layer, and a soil layer from the outside in; wherein, the lining layer and the soil layer are homogeneous media, and the grouting layer is a two-phase media, including cement and grouting cavities; the interface between the lining layer and the grouting layer is defined as the first interface, and the interface between the grouting layer and the soil layer is defined as the second interface.

[0008] Furthermore, the theoretical travel time of the reflected wave at the first interface is calculated using the following formula (1): ; Where t1 is the theoretical travel time of the reflected wave from the first interface. This is the offset distance. The thickness of the lining layer, The wave velocity is the wave velocity of the lining layer.

[0009] Furthermore, the theoretical travel time of the reflected wave at the second interface is calculated using the following formula (2): ; Where t2 is the theoretical travel time of the reflected wave from the first interface. The thickness of the grouting layer, v1 is the thickness of the lining layer; v2 is the wave velocity of the grouting cement; θ1 and θ2 are the reflection angles in the lining layer and the grouting layer, respectively.

[0010] Furthermore, by combining formulas (1) and (2), we can transform them into the following formula (3): Where p is the ray parameter.

[0011] Furthermore, for each artificial seismic source, the first arrival time of the DAS signal at the receiving location is picked up, and a record of a preset duration is extracted based on the first arrival time. All the extracted records are arranged in spatial order and normalized with the relative amplitude of the first arrival wave.

[0012] Furthermore, in S4, the first parameter curve is a cement-bonded logging curve, which is generated by extracting the peak amplitude within a preset tolerance range before and after the theoretical travel time of the reflected wave at the first interface on the equidistant profile, and then normalizing it; the second parameter curve is a grouting travel time curve, which is generated by picking the propagation time corresponding to the peak amplitude of the first arrival and after arrival of each reflected wave on the equidistant profile.

[0013] Furthermore, the normalization process includes: obtaining the reflection peak value corresponding to the known void region as the reference CBL value, and normalizing the peak amplitude of each channel using the reference CBL value. The closer the CBL value is to 1, the worse the bonding.

[0014] Furthermore, the comprehensive analysis includes: plotting the first parameter curve and the second parameter curve on the same coordinate system and comparing them with the equidistant profile; wherein, areas with relatively large amplitudes in the first parameter curve are identified as abnormal cementation at the first interface; areas with large deviations between the second parameter curve and the theoretical travel time of the second interface are identified as abnormal cementation at the second interface, with larger travel time deviations indicating poorer cementation; combining the two abnormal areas to locate grouting voids. Therefore, the final determination of grouting voids is: the area where the CBL curve amplitude significantly increases (close to 1) and there is a significant deviation between the grouting travel time curve and the theoretical travel time corresponds to the location of the void.

[0015] This invention also provides a rapid detection system for grouting voids after tunnel lining, comprising: A distributed fiber optic vibration sensing module is used to lay optical fibers along the tunnel lining and receive DAS signals. Artificial seismic source excitation module, used to excite artificial seismic sources along optical fibers at fixed intervals; The equal offset profile generation module is used to receive signals at a fixed offset distance from each seismic source and generate an equal offset profile. The theoretical travel time calculation module is used to determine the theoretical travel time of the reflected waves from the first and second interfaces based on the tunnel lining structure model. The first parameter curve generation module is used to extract the reflection amplitude based on the first interface theory travel time on the equidistant profile and generate the first parameter curve. The second parameter curve generation module is used to extract the travel time of reflected waves on the equidistant offset profile and generate the second parameter curve. The grouting void detection module is used to comprehensively analyze the first parameter curve and the second parameter curve to identify areas of abnormal cementation and locate grouting voids.

[0016] The rapid detection method for grouting voids after tunnel lining disclosed in this application has at least the following advantages compared to existing technologies: Traditional detection methods using ground-penetrating radar require manual pushing of equipment for segmented scanning; acoustic methods require point-by-point sensor deployment, a cumbersome and time-consuming process. In contrast, this application uses a DAS fiber optic sensor array deployed along the tunnel in one go, requiring only the excitation of a seismic source along the route. Traditional detection methods are single-point detections, while this application uses a DAS fiber optic sensor array, transforming detection from point-by-point scanning to linear array acquisition; the fiber optic receiving array in this application does not require movement, avoiding the time wasted on repeated equipment movement, achieving "deployment once, full-process acquisition"; traditional methods rely on complex data inversion imaging, a process that is nonlinear and prone to multiple solutions, requiring professionals to spend a significant amount of time processing on backend computers. This application, by generating equidistant profiles, CBL curves, and grouting travel-time curves, transforms the complex imaging problem into the analysis of intuitive curves. On-site personnel can quickly (even in real-time) observe curve anomalies and immediately judge the cementation status, essentially achieving "on-site acquisition, on-site results." Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the rapid detection process for grouting voids after tunnel lining in this embodiment. Figure 2 This is a conceptual diagram illustrating the rapid detection of grouting voids after tunnel lining in this embodiment; Figure 3 This is a schematic diagram of the actual model set in this embodiment; Figure 4 This is the equidistant cross-sectional view obtained by calculation in this embodiment; Figure 5 This is a combined interpretation diagram of the CBL curve grouting travel time curve in this embodiment; Figure 6 This is a schematic diagram of the geometric analysis for calculating the theoretical travel time in this application. Detailed Implementation

[0018] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] Example 1 like Figure 1 As shown, one embodiment of the present invention provides a method for rapid detection of grouting voids after tunnel lining, comprising the following steps: S1. A distributed acoustic sensing fiber optic array is deployed along the tunnel lining, and artificial seismic sources are excited along the array at fixed intervals. The acoustic sensing fiber optic array is connected to a distributed acoustic sensing (DAS) demodulation system to construct a fiber optic vibration sensing array. Vibration signals are excited along the fiber at fixed spatial intervals (i.e., shot spacing) to construct artificial seismic sources. After excitation, seismic wave field signals are received at a fixed offset. In constructing the artificial seismic sources, the spacing between excitation points should not be too large to ensure complete spatial coverage.

[0020] S2. For each excitation source, acquire the DAS signal at a fixed offset distance, and generate an equal offset profile based on the DAS signals acquired from all sources. The offset distance used when extracting DAS channels should be greater than the distance between excitation points, but should not be too large to ensure spatial resolution, preferably within 2 meters.

[0021] For each artificial vibration source corresponding to a DAS seismic trace, the first arrival time of the wavefield at that receiving location is picked up. Using the first arrival time as the reference time, DAS records within a certain period after the first arrival are extracted. All extracted DAS traces are arranged in spatial order and normalized with the relative amplitude of the first arrival wave to obtain an equioffset profile. Since waveforms are recorded at all locations on the DAS fiber with each strike, this application only takes one channel with a fixed offset. These data are arranged in spatial order to form an equioffset profile. Through fixed offset reception, the original data is compressed into a two-dimensional time-location profile. On the formed equioffset profile, each spatial location is a waveform curve containing multiple waves (direct wave, interface reflection wave, multiple waves, etc.).

[0022] S3. Construct a tunnel lining structure model according to the layout rules in S1-S2 above, and repeatedly excite seismic sources to determine the theoretical travel times of the reflected waves from the first and second interfaces of the grouting layer. On the formed equidistant profile, each spatial location is a waveform curve containing various waves (direct waves, interface reflected waves, multiple waves, etc.). Therefore, this step aims to determine which waveform segment corresponds to the first interface and which corresponds to the second interface. The theoretical travel time is calculated and used as a time window locator for positioning, enabling rapid and automatic capture of the waveforms of interest for the first and second interfaces.

[0023] The tunnel lining structure model consists of a lining layer, a grouting layer, and a soil layer, from the outside in. The lining layer and the soil layer are homogeneous media, while the grouting layer is a two-phase media, including cement and grouting cavities. The interface between the lining layer and the grouting layer is defined as the first interface, and the interface between the grouting layer and the soil layer is defined as the second interface.

[0024] This embodiment uses numerical simulation to illustrate the proposed method. Considering the actual spatial scale characteristics of tunnel lining, a three-layer model with a length of 100 meters and a depth of 50 centimeters is established, as follows: Figure 3 As shown, the lining layer is 30 cm thick, the grouting layer is 8 cm thick, and the soil and rock layer is 12 cm thick. Absorbing boundary conditions are set around the model. The propagation process of seismic waves in the model is simulated using acoustic wave equations, with a spatial grid size of 0.4 cm used during forward modeling. To simulate the actual tunnel scenario, the wave velocity is set to 4000 m / s for the lining layer, 3500 m / s for the grouting cement, 340 m / s for the cavities, and 800 m / s for the soil and rock layer. The seismic source is located at the bottom boundary of the model, using a broadband zero-phase wavelet, excited once every 60 cm, for a total of 166 excitations. After excitation, the seismic wave field is recorded using DAS at 1 meter to the right of each seismic source.

[0025] The theoretical travel time of reflected seismic waves is calculated using the seismic ray method. The propagation time is calculated using Snell's law and seismic wave kinematics. The first arrival time is picked up at the position where the signal starts. After the first arrival time is intercepted, the recording should ensure that the interception time exceeds the theoretical arrival time of the reflection at interface 2. The travel time tolerance interval for picking the peak amplitude of the reflection at interface 1 is ten time sampling points before and after the theoretical travel time.

[0026] like Figure 6 The theoretical travel time of the reflected wave from the first interface is calculated using the following formula (1): ; Where t1 is the theoretical travel time of the reflected wave from the first interface. This is the offset distance. The thickness of the lining layer, The wave velocity is the wave velocity of the lining layer.

[0027] The theoretical travel time of the reflected wave at the second interface is calculated using the following formula (2). ; Where t2 is the theoretical travel time of the reflected wave from the first interface. The thickness of the grouting layer, v1 is the thickness of the lining layer; v2 is the wave velocity of the grouting cement; θ1 and θ2 are the reflection angles in the lining layer and the grouting layer, respectively.

[0028] In this embodiment, the first arrival wave received by the DAS under this observation system is a direct wave within the lining layer. Therefore, in this embodiment, all obtained DAS channels have completely consistent first arrival times. Recordings 200 microseconds after the first arrival time of each channel are extracted; this length ensures that reflected waves from both interface 1 and interface 2 are preserved in the profile. Arranging the channels in spatial order yields an equidistant profile, such as... Figure 4 As shown.

[0029] S4. On the equidistant offset profile, based on the theoretical travel time of the reflected wave from the first interface, the reflection amplitude information of each sensing position is extracted to generate a first parameter curve for characterizing the cementation state of the first interface. Equations (1) and (2) are combined and transformed into the following form: Equation (3) Where p is the ray parameter.

[0030] The multiple excitation of the seismic source employs a broadband zero-phase wavelet, with excitation occurring every 60 centimeters. The seismic source is not fixedly positioned. For example, if the seismic source signal is excited by hammering, the first excitation involves striking the first seismic source location, then moving it a certain distance, such as 60 centimeters in this case, and striking it again. This is the second excitation, and so on, with each movement triggering an excitation. Therefore, this process can be understood as the result of a single exciter exciting multiple times at different locations; there is no fixed positioning, but rather excitation occurs at regular intervals.

[0031] The first parameter curve is obtained by extracting the peak amplitude within the theoretical travel time tolerance interval of the reflected wave from the first interface and then normalizing it. The tolerance interval consists of 10 time sampling points before and after the theoretical travel time.

[0032] In S4, the first parameter curve is a cement-bonded logging curve, which is generated by extracting the peak amplitude within a preset tolerance range before and after the theoretical travel time of the reflected wave at the first interface on the equidistant profile, and then normalizing it. Different cement materials, different lining sizes, and observation designs will all affect the final results. In other words, the degree of difference between the void area and the dense area in the two parameters of [CBL relative amplitude] and [interface 2 prediction travel time deviation].

[0033] S5. On the equidistant offset profile, based on the theoretical travel time of the second interface, the actual travel time is extracted to generate a second parameter curve characterizing the cementation state of the second interface; that is, the second parameter curve is the grouting travel time curve, which is generated by: picking the propagation time corresponding to the peak amplitude of the initial arrival and subsequent reflection waves of each channel on the equidistant offset profile. In this embodiment, the obtained CBL curve and the grouting travel time curve are shown in the figure. Figure 5 .

[0034] S6. By comprehensively analyzing the first parameter curve and the second parameter curve, identify the cementation abnormal area, thereby locating the grouting voids after lining.

[0035] The comprehensive analysis includes: plotting the first parameter curve and the second parameter curve in the same coordinate system and comparing them with the equidistant profile; wherein, the area with a relatively large amplitude in the first parameter curve is identified as the first interface cementation anomaly; the area with a large deviation between the second parameter curve and the theoretical travel time of the second interface is identified as the second interface cementation anomaly; and the grouting voids are located by combining the two abnormal areas.

[0036] When identifying voids by combining the CBL curve and the grouting travel time curve, the two should be plotted on a single graph and compared with the original cross-section for analysis. The cement bonding condition of the grouting layer interface 1 is judged by the relative amplitude of the CBL curve. Areas with large amplitudes have poor bonding and may contain voids. The cement bonding condition of the grouting layer interface 2 is judged by the difference between the grouting travel time curve and the predicted travel time of the reflected wave of the reflection interface 2. Areas with large deviations have poor bonding and may contain voids.

[0037] The presence or absence of grouting voids can be mapped to the interface bonding effect. For example... Figure 2 As shown, when both interfaces 1 and 2 of the grouting layer are well bonded and free of voids, the reflected energy at interface 1 is weak, while the reflected energy at interface 2 is strong and the ray path matches the theoretical path. This corresponds to a smaller CBL curve amplitude and the grouting travel curve coinciding with the theoretical travel curve. When interface 1 is well bonded and interface 2 is poorly bonded, i.e., the grouting is incomplete, the reflected energy at interface 1 remains weak, while the reflected energy at the free surface of the cement is strong, but the path no longer corresponds to the theoretical path. This corresponds to a smaller CBL curve amplitude and a deviation between the grouting travel curve and the theoretical travel curve. When both interfaces 1 and 2 are poorly bonded, i.e., no grouting is performed, the reflected energy at interface 1 is strong, and no further reflection occurs within the grouting layer. This corresponds to a large CBL curve amplitude (close to 1), and the grouting travel curve converges to the theoretical travel time of the reflection at interface 1.

[0038] Therefore, the location and shape of grouting voids can be quickly determined by combining the relative amplitude of the CBL curve, the deviation between the grouting travel curve and the theoretical travel curve, and the shape of the equidistant profile. Regions with large CBL curve amplitudes (close to 1), fluctuating grouting travel curves, and deviations from the theoretical travel curves correspond to the locations of voids.

[0039] In this embodiment, the location of the cavity, determined by combining the CBL curve and the grouting travel time curve, is as follows: Figure 5 As shown, the interpretation results are in good agreement with the actual situation of the model, and can effectively realize the rapid detection of grouting voids after tunnel lining.

[0040] Example 2 This invention also provides a rapid detection system for grouting voids after tunnel lining, comprising: The distributed fiber optic vibration sensing module is configured to lay fiber optics along the inner wall of the tunnel lining and connect to the distributed acoustic sensing (DAS) demodulation system to construct a fiber optic vibration sensing array. The artificial vibration source excitation module is configured to excite vibration signals along the optical fiber at fixed spatial intervals (i.e., the distance between the guns) to construct an artificial vibration source; The common offset profile generation module is configured to extract DAS receiver channels at a fixed offset after each artificial vibration source is excited. One seismic channel is extracted for each source, and the first arrival time of the excitation wave field of the source at the receiving position is picked up. Using the first arrival time as the reference time, DAS records within a period of time after the first arrival are extracted, and all extracted DAS channels are arranged in spatial order and normalized with the relative amplitude of the first arrival wave to obtain the equal offset profile. The reflected wave theoretical travel time calculation module is configured to calculate the theoretical travel time of the seismic wave reflected at grouting layer interface 1 (the interface between the lining layer and the grouting layer) and grouting layer interface 2 (the interface between the soil layer and the grouting layer) based on the thickness of the lining layer, the thickness of the grouting layer, the acoustic velocity of the lining material, and the selected offset distance. The CBL curve plotting module is configured to pick up the peak amplitude of the reflected wave theoretical travel time tolerance interval of each trace on the equi-offset profile, obtain the cement bonded logging (CBL) value of each trace, and excite the known cavity area (ungrown area) with the same source and observation system to obtain the reflection peak value corresponding to the cavity as the reference CBL value. The reference CBL value is used to normalize the CBL value of each trace and plot the CBL curve. The grouting travel time curve plotting module is configured to pick up the wave propagation time corresponding to the peak amplitude of the first and last reflected waves on the equidistant profile, and use the obtained travel time to plot the grouting travel time curve. The grouting void detection module is configured to combine CBL curves, grouting travel time curves, and equidistant profiles to quickly identify areas of abnormal cementation and predict the location of grouting voids after lining.

[0041] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for rapid detection of grouting voids after tunnel lining, characterized in that, Includes the following steps: S1. A distributed acoustic sensing fiber optic array is laid along the tunnel lining, and an artificial vibration source is excited along the array at a fixed interval. S2. For each excitation source, acquire the DAS signal at a fixed offset distance, and generate an equioffset profile based on the DAS signals acquired from all sources. S3. Construct a tunnel lining structure model according to the layout rules in S1-S2 above, and repeatedly excite the seismic source. Determine the theoretical travel time of the reflected waves from the first and second interfaces of the grouting layer according to the following formulas. The theoretical travel time of the reflected wave at the first interface is calculated using the following formula (1): ； Where t1 is the theoretical travel time of the reflected wave from the first interface. This is the offset distance. The thickness of the lining layer, The wave velocity of the lining layer; The theoretical travel time of the reflected wave at the second interface is calculated using the following formula (2). ; Where t2 is the theoretical travel time of the reflected wave from the first interface. The thickness of the grouting layer, v1 is the thickness of the lining layer; v2 is the wave velocity of the grouting cement; θ1 and θ2 are the reflection angles in the lining layer and the grouting layer, respectively; and p is the ray parameter. S4. On the equidistant offset profile, based on the theoretical travel time of the reflected wave from the first interface, the reflection amplitude information of each sensing position is extracted to generate a first parameter curve for characterizing the cementation state of the first interface. S5. On the equidistant profile, based on the theoretical travel time of the second interface, the actual travel time is extracted to generate a second parameter curve for characterizing the cementation state of the second interface. S6. By comprehensively analyzing the first parameter curve and the second parameter curve, identify the cementation abnormal area, thereby locating the grouting voids after lining.

2. The method for rapid detection of grouting voids after tunnel lining according to claim 1, characterized in that, The tunnel lining structure model includes a lining layer, a grouting layer, and a soil layer from the outside in; wherein, the lining layer and the soil layer are homogeneous media, and the grouting layer is a two-phase media, including cement and grouting cavities; the interface between the lining layer and the grouting layer is defined as the first interface, and the interface between the grouting layer and the soil layer is defined as the second interface.

3. The method for rapid detection of grouting voids after tunnel lining according to claim 2, characterized in that, Equations (1) and (2) are combined and transformed into the following form: Equation (3) Where p is the ray parameter.

4. The method for rapid detection of grouting voids after tunnel lining according to claim 1, characterized in that, For each artificial seismic source, the first arrival time of the DAS signal at the receiving location is picked up, and a record of a preset duration is extracted based on the first arrival time. All extracted records are arranged in spatial order and normalized with the relative amplitude of the first arrival wave.

5. The method for rapid detection of grouting voids after tunnel lining according to claim 1, characterized in that, In S4, the first parameter curve is a cement-bonded logging curve, which is generated by extracting the peak amplitude within a preset tolerance range before and after the theoretical travel time of the first interface reflected wave on the equidistant profile and then normalizing it; the second parameter curve is a grouting travel time curve, which is generated by picking the propagation time corresponding to the peak amplitude of the first arrival and after arrival of each reflected wave on the equidistant profile.

6. The method for rapid detection of grouting voids after tunnel lining according to claim 5, characterized in that, The normalization process includes: obtaining the reflection peak value corresponding to the known void region as the reference CBL value, and normalizing the peak amplitude of each channel using the reference CBL value.

7. The method for rapid detection of grouting voids after tunnel lining according to claim 1, characterized in that, The comprehensive analysis includes: plotting the first parameter curve and the second parameter curve in the same coordinate system and comparing them with the equidistant profile; wherein, the area with a large relative deviation in amplitude in the first parameter curve is identified as an abnormal cementation of the first interface; the area with a large deviation between the second parameter curve and the theoretical travel time of the second interface is identified as an abnormal cementation of the second interface; and the abnormal areas of the two are combined to locate grouting voids.

8. A rapid detection system for grouting voids after tunnel lining, characterized in that, include: A distributed fiber optic vibration sensing module is used to lay optical fibers along the tunnel lining and receive DAS signals. Artificial seismic source excitation module, used to excite artificial seismic sources along optical fibers at fixed intervals; The equal offset profile generation module is used to receive signals at a fixed offset distance from each seismic source and generate an equal offset profile. The theoretical travel time calculation module is used to determine the theoretical travel time of the reflected waves from the first and second interfaces based on the tunnel lining structure model. The theoretical travel time of the reflected wave at the first interface is calculated using the following formula (1): Where t1 is the theoretical travel time of the reflected wave from the first interface. This is the offset distance. The thickness of the lining layer, The wave velocity of the lining layer; The theoretical travel time of the reflected wave at the second interface is calculated using the following formula (2). Where t2 is the theoretical travel time of the reflected wave from the first interface. The thickness of the grouting layer, v1 is the thickness of the lining layer; v2 is the wave velocity of the grouting cement; θ1 and θ2 are the reflection angles in the lining layer and the grouting layer, respectively; and p is the ray parameter. The first parameter curve generation module is used to extract the reflection amplitude based on the first interface theory travel time on the equidistant profile and generate the first parameter curve. The second parameter curve generation module is used to extract the travel time of reflected waves on the equidistant offset profile and generate the second parameter curve. The grouting void detection module is used to comprehensively analyze the first parameter curve and the second parameter curve to identify areas of abnormal cementation and locate grouting voids.

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