A tunnel above ground stratum cavity detection system and method integrated in a shield machine

Abstract

This invention discloses a ground cavity detection system and method integrated into a tunnel boring machine (TBM). The system includes M×N detection arms embedded behind the TBM cutterhead. A striking hammer is installed at the end of at least one detection arm, and accelerometers are installed at the ends of the remaining arms. Each detection arm is equipped with an independent drive mechanism and a strain gauge pressure sensor. The striking hammer and drive mechanism are controlled by a host computer. Data collected by the accelerometers and strain gauge pressure sensors is transmitted to the host computer, and the drive mechanism controls the extension and retraction of the detection arms. In terms of engineering applicability, the highly integrated and automated design of this detection system enables it to adapt to the harsh environment at the front end of the TBM, simplifies operation, and significantly improves its reliability and convenience in real construction scenarios.

Description

Technical Field

[0001] This invention belongs to the field of underground cavity detection, and specifically relates to a cavity detection system and method for the strata above a tunnel integrated into a tunnel boring machine. Background Technology

[0002] Tunnel construction using the shield tunneling method is carried out in a closed environment throughout the entire construction process, with complex and highly concealed conditions. Adverse geological features such as karst and cavities caused by mining subsidence within the strata above the tunnel arch pose significant safety hazards during both construction and operation. Failure to detect and promptly grout these hidden cavities can easily lead to serious accidents such as excavation face instability and sudden ground collapse, causing severe economic losses and casualties. Therefore, there is an urgent need to invent a cavity detection system and method that can work in conjunction with the shield tunneling machine to directly target the strata above the tunnel arch with high precision. This would fill the current technological gap, provide accurate and timely information for simultaneous grouting and other treatment measures, and significantly improve the proactive safety assurance capabilities of tunnel construction.

[0003] Currently, the cavity detection technologies and methods applied to tunnel engineering mainly include ground detection, tunnel interior detection, and detection integrated into the tunnel boring machine.

[0004] Ground-based detection technologies operate on the Earth's surface and mainly include high-density electrical resistivity tomography (EDT), ground-penetrating radar (GPR), micro-motion surface wave exploration, and seismic imaging. While they cause minimal interference to the surface, they are difficult to deploy due to limitations imposed by urban buildings, pipelines, and traffic activities, and data quality is easily affected. For deeply buried tunnels, signal attenuation is severe, making it difficult to accurately identify small cavities; furthermore, detection is separated from tunnel boring machine (TBM) excavation operations, failing to meet the construction needs for real-time guidance of grouting.

[0005] Traditional geophysical exploration methods in tunnels are implemented inside the tunnel, including seismic reflection and ground-penetrating radar (GPR). These methods directly target the surrounding rock of the tunnel, enabling more accurate identification of cavities, fissures, and adverse geological formations ahead of the tunnel face or behind the lining. GPR offers high resolution and flexible operation, and is widely used for lining quality inspection. Seismic reflection is effective at detecting large-scale anomalies at depth, but its limitations due to tunnel space, the complexity of data acquisition and interpretation, the existence of a detection "blind zone" above the tunnel arch, and the need for manual sensor deployment, making the process cumbersome and slow. GPR is primarily used for detecting shallow voids behind the lining, has a limited detection range, and cannot effectively identify cavities in the original strata.

[0006] Integrated detection systems for tunnel boring machines (TBMs) primarily rely on a small number of sensors installed on the cutterhead or shield body, depending on tunneling vibrations (a passive source) for coarse sensing. While enabling real-time monitoring during construction without interrupting tunneling, they currently depend mainly on vibration signal analysis, making them susceptible to mechanical noise interference. They also suffer from technical challenges such as uncontrollable signals and complex data processing. Furthermore, their ability to identify small cavities or precise boundaries is limited, limiting their use for risk warning rather than precise imaging. They struggle to achieve stable, high-precision imaging and location of cavities above the tunnel.

[0007] In recent years, research on the detection of cavities in the strata above tunnels has included patents such as CN119666983 A (a method and system for detecting cavities behind the walls of subway shield tunnels) and CN118114150A (an adaptive tunnel cavity identification method and device based on acoustic vibration detection technology). Both patents utilize acoustic vibration detection technology to detect cavities in the tunnel lining after segment installation. CN119620230A relies on electromagnetic wave technology and image data fusion methods to assess cavity defects in operating tunnels, but its resolution for deep cavities is limited, and it does not address the issues of cavity detection and grouting treatment during shield tunneling construction. Summary of the Invention

[0008] This invention addresses the common technical problems of traditional detection methods, such as poor real-time performance, insufficient detection accuracy and reliability, and the detection direction mainly targeting the front of the tunnel face, resulting in blind spots in the tunnel arch area. It provides a tunnel cavity detection system and method integrated into the tunnel boring machine, which solves the problem of accurate positioning and identification of cavities above the tunnel arch, and improves detection speed and real-time performance.

[0009] The present invention adopts the following technical solution:

[0010] An improved system for detecting cavities in the strata above a tunnel, integrated into a tunnel boring machine (TBM), comprises M×N detection arms embedded behind the cutterhead of the TBM. A striking hammer is installed at the end of at least one detection arm, and accelerometers are installed at the ends of the remaining arms. Each detection arm is equipped with an independent drive mechanism and a strain gauge pressure sensor. The striking hammer and drive mechanism are controlled by a host computer. Data collected by the accelerometers and strain gauge pressure sensors is transmitted to the host computer. The drive mechanism controls the extension and retraction of the detection arms. When the extended detection arm contacts the stratum interface above the tunnel, the strain gauge pressure sensor monitors the pressure between the detection arm and the stratum interface in real time. When the pressure reaches a set threshold, the host computer controls the drive mechanism to stop working.

[0011] Furthermore, the probe arm is installed inside the housing compartment of the shield body of the tunnel boring machine. The driving mechanism is a hydraulic cylinder mounted on a support. The support is fixed to the inner wall of the shield body of the tunnel boring machine. The hydraulic cylinder drives the probe arm to extend or retract from the housing compartment and to extend and retract radially along the shield body.

[0012] Furthermore, the hydraulic cylinder is fixed to the support by a fixed flange and bolts.

[0013] Furthermore, the hydraulic cylinders are connected to the hydraulic pump station inside the tunnel boring machine.

[0014] Furthermore, the support is a cylindrical support.

[0015] Furthermore, the hammer or accelerometer is connected to the multi-channel data acquisition box via an aviation plug and a cable running through the inside of the probe arm.

[0016] Furthermore, a strain gauge pressure sensor is integrated in the middle of the probe arm and connected to the host computer via a cable running through the inside of the probe arm.

[0017] Furthermore, when there is one striking hammer, it is installed on the 1×1 probe arm; when there are two striking hammers, they are installed on the 1×1 and M×N probe arms respectively.

[0018] A detection method, applicable to the above-mentioned detection system, is improved by comprising the following steps:

[0019] Step 1, System initialization and probe arm extension:

[0020] When the main control system of the tunnel boring machine issues a "stop tunneling" signal, the detection system is activated, and the host computer activates each hydraulic cylinder to cause the M×N detection arms to extend out of the shield's receiving chamber in sequence.

[0021] Step 2, Establishing dynamic coupling:

[0022] Each strain gauge pressure sensor feeds back the pressure readings between the M×N probe arms and the formation interface to the host computer. The host computer dynamically adjusts the pressure of each hydraulic cylinder and controls the hydraulic cylinder to stop working when the pressure between the probe arm and the formation interface reaches a preset threshold.

[0023] Step 3, passive source surface wave signal acquisition:

[0024] Accelerometers on all probe arms synchronously acquire continuous background vibration signals for a duration of T1, and transmit the acquired surface wave data to the host computer in real time.

[0025] Step 4, Surface wave analysis and screening of low-velocity anomalies:

[0026] The host computer inverts the shear wave velocity profile of the strata above the tunnel. If no low-velocity anomaly is found, proceed to step 7; if a low-velocity anomaly is found, proceed to step 5.

[0027] Step 5, Active source reflected wave data acquisition:

[0028] The host computer triggers the hammers sequentially. When each hammer is triggered, all accelerometers synchronously collect the reflected wave signal for a duration of T2. This process is repeated K times, and the collected reflected wave data is transmitted to the host computer.

[0029] Step 6, Reflected wave imaging and result output:

[0030] The host computer first superimposes the reflected wave data, then begins data processing to generate a depth migration profile, depicting the spatial morphology of the anomalous body; based on the reflected wave imaging results and combined with the shear wave velocity profile, it generates a detection report containing the spatial location and morphological characteristics of the anomalous body.

[0031] Step 7, System reset and probe arm retraction:

[0032] Regardless of whether any anomalies are detected, after data collection and analysis are completed, the host computer activates each hydraulic cylinder to retract the M×N probe arms into the shield's containment chamber in sequence, and notifies the tunnel boring machine's main control system to proceed to the next step.

[0033] Furthermore, in step 3, T1 is 300 seconds, in step 5, T2 is 0.1 seconds, K is 3, and the morphological features in step 6 include coordinates and dimensions.

[0034] The beneficial effects of this invention are:

[0035] The detection system disclosed in this invention has a striking hammer (controlled seismic source) or an accelerometer (detector) installed in each detection arm. All detection arms together constitute a detection system comprising a controlled seismic source and a linearly arranged array of detectors, used to achieve passive source surface wave detection and active source reflected wave detection of cavities in the strata above the tunnel arch. The detection arms can automatically extend during the tunnel boring machine's (TBM) excavation intervals, tightly coupling the controlled seismic source and detectors to the exposed rock and soil surface of the tunnel arch, and automatically retract after detection to adapt to the complex space at the front end of the TBM. To ensure the coupling quality between the controlled seismic source and detector at the end of the detection arm and the exposed rock and soil surface of the tunnel arch, a strain gauge pressure sensor is integrated in the middle of each detection arm. This allows for real-time monitoring of the pressure between the detection arm and the stratum interface during extension, and the pressure threshold can be adjusted according to different rock and soil surface parameters. In terms of engineering applicability, the highly integrated and automated design enables the detection system to adapt to the harsh environment at the front end of the TBM, is easy to operate, and significantly improves the reliability and convenience of implementation in real construction scenarios.

[0036] The detection method disclosed in this invention improves efficiency by integrating a telescopic detection arm into the tunnel boring machine (TBM) and setting a timing control that is linked to the TBM's tunneling cycle. This allows the detection operation to be completed automatically during the TBM's "advance-stop" intervals, significantly improving the timeliness of detection. It overcomes the shortcomings of traditional methods, such as poor real-time performance, low automation, and difficulty in conducting accurate in-situ detection in complex construction environments. This provides accurate, timely, and reliable geological data for engineering treatment measures such as synchronous grouting.

[0037] In terms of detection quality and accuracy, to address the blind spots and insufficient resolution of traditional advanced geological prediction methods above tunnels, a collaborative approach of "automatic screening of passive source surface waves and fine imaging of active source reflected waves" is adopted, combined with an intelligent coupling mechanism of pressure feedback, to obtain information on the strata above the tunnel, determine the existence, location and scale of cavities, and achieve real-time, in-situ, and high-precision detection of hidden cavities in the strata above the tunnel arch. This enables early identification of geological anomalies and risk sources in the strata above during construction, and proactive prevention and control of major construction safety risks such as excavation face instability and surface collapse.

[0038] In summary, this invention provides a real-time, efficient, and accurate solution for detecting cavities in the strata above the tunnel arch by means of a telescopic probe arm, intelligent coordination of passive and active source detection, and coordinated operation with the tunnel boring machine excavation process. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the location of the detection system disclosed in this invention;

[0040] Figure 2-1 This is a front view of the array of probe arms disclosed in this invention;

[0041] Figure 2-2 This is a top view of the array of probe arms disclosed in this invention;

[0042] Figure 3 This is a schematic diagram of the probe arm disclosed in this invention during extension and retraction;

[0043] Figure 4 This is a schematic diagram showing the position of the strain gauge pressure sensor on the probe arm;

[0044] Figure 5 This is a schematic flowchart of the detection method disclosed in this invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this invention clearer, the 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 merely illustrative and not intended to limit the invention.

[0046] Example 1, such as Figure 1 As shown, in order to solve the technical challenge of real-time, in-situ, and high-precision detection of cavities 3 in the strata above the tunnel arch during shield tunneling construction, this embodiment discloses a tunnel cavity detection system 2 integrated into the shield machine 1. This system can work in conjunction with the shield machine to perform in-situ detection of cavities in the strata above the tunnel arch and provide accurate detection results.

[0047] For example Figure 2-1 , 2-2 As shown, the detection system includes M columns × N rows of detection arms embedded in the rear side 5 of the shield machine cutterhead. The columns are along the tunneling direction of the shield machine, and the first row is closer to the cutterhead. The distance between adjacent columns is D1, and the distance between adjacent rows is D2.

[0048] A striking hammer is installed at the end of at least one probe arm as a controllable vibration source, and high-sensitivity accelerometers are installed at the ends of the remaining probe arms as detectors. When there is one striking hammer, it is installed on the 1×1 probe arm; when there are two striking hammers, they are installed on the 1×1 and M×N probe arms respectively.

[0049] Each probe arm is equipped with an independent drive mechanism and a strain gauge pressure sensor. The hammer and drive mechanism are controlled by a host computer. Data collected by the accelerometer and strain gauge pressure sensor are transmitted to the host computer. The drive mechanism controls the extension and retraction of the probe arm. When the extended probe arm contacts the ground interface above the tunnel, the strain gauge pressure sensor monitors the pressure between the probe arm and the ground interface in real time to ensure signal coupling quality. When the pressure reaches a set threshold, the host computer controls the drive mechanism to stop working. The host computer has pre-stored pressure thresholds corresponding to different ground types (such as hard rock and soft soil).

[0050] like Figure 3 As shown, in this embodiment, the probe arm 6 is installed inside the receiving chamber of the tunnel boring machine (TBM) shield. The driving mechanism is a hydraulic cylinder 7 mounted on a support 8. The support is a cylindrical seat fixed to the inner wall of the TBM shield 10. The hydraulic cylinder drives the probe arm to extend or retract from the receiving chamber, extending and retracting radially along the shield. The hydraulic cylinder is fixed to the support by a fixing flange 9 and bolts.

[0051] Port A on the hydraulic cylinder is the oil inlet, and port B is the oil return port. The hydraulic cylinder is connected to the hydraulic pump station inside the tunnel boring machine. The hydraulic pump station controls the hydraulic cylinder through oil circuits to extend and retract the probe arm.

[0052] For example Figure 4As shown, the impact hammer or accelerometer 11 is connected to the multi-channel data acquisition box via an aviation connector and a cable running through the inside of the probe arm to achieve signal acquisition and excitation. A strain gauge pressure sensor 12 is integrated in the middle of the probe arm and connected to the host computer via a cable running through the inside of the probe arm. The host computer is installed in the tunnel boring machine control room and can control the contact force between the probe arm and the soil layer above the tunnel arch, as well as process the data acquired by the multi-channel data acquisition box.

[0053] This embodiment also discloses a detection method applicable to the aforementioned detection system. This method automatically embeds the "extend-collect-reset" operation process of the detection system into the "stop-segment installation-advance" construction interval of the tunnel boring machine, achieving collaborative operation with the tunnel boring machine. For example... Figure 5 As shown, it includes the following steps:

[0054] Step 1, System initialization and probe arm extension:

[0055] When the main control system of the tunnel boring machine issues a "stop tunneling" signal, the detection system is activated, and the host computer activates each hydraulic cylinder to cause the M×N detection arms to extend out of the shield's receiving chamber in sequence.

[0056] Step 2, Establishing dynamic coupling:

[0057] Each strain gauge pressure sensor feeds back the pressure readings between the M×N probe arms and the ground interface to the host computer. The host computer compares the real-time pressure value with the preset threshold and dynamically adjusts the pressure of each hydraulic cylinder so that the pressure between each probe arm and the ground interface quickly and stably reaches the preset threshold. When the pressure between the probe arm and the ground interface reaches the preset threshold, the hydraulic cylinder is controlled to stop working, thereby ensuring that all detectors and controllable seismic sources form a consistent and reliable physical coupling with the ground above the tunnel arch.

[0058] Step 3, passive source surface wave signal acquisition:

[0059] Using the noise inside the tunnel as a passive source, the accelerometers on all probes synchronously collect continuous background vibration signals for a duration T1 (e.g., 300 seconds) and transmit the collected surface wave data to the host computer in real time.

[0060] Step 4, Surface wave analysis and screening of low-velocity anomalies:

[0061] The host computer inverts the shear wave velocity profile of the strata above the tunnel. If no low-velocity anomaly is found, proceed to step 7; if a low-velocity anomaly is found, proceed to step 5.

[0062] Step 5, Active source reflected wave data acquisition:

[0063] The host computer triggers the hammers sequentially. When each hammer is triggered, all accelerometers synchronously collect a reflected wave signal for a duration of T2 (e.g., 0.1 seconds). To ensure data quality, this process can be repeated K times (e.g., 3 times). The collected reflected wave data is then transmitted to the host computer.

[0064] Taking two striking hammers as an example, the striking hammer in the first row is triggered first, and the remaining M×N-2 accelerometers start collecting data for a duration of T2 seconds; then the striking hammer in the Mth row is triggered, and the remaining M×N-2 accelerometers continue to collect data for a duration of T2 seconds. The above process can be repeated K times.

[0065] Step 6, Reflected wave imaging and result output:

[0066] The host computer first superimposes the reflected wave data, then begins data processing to generate a depth migration profile, depicting the spatial morphology of the anomalous body (loose or hollow); based on the reflected wave imaging results and combined with the shear wave velocity profile, a detection report containing the spatial location and morphological characteristics (coordinates, size, etc.) of the anomalous body is generated.

[0067] Step 7, System reset and probe arm retraction:

[0068] Regardless of whether any anomalies are detected, after data collection and analysis are completed, the host computer activates each hydraulic cylinder to retract the M×N probe arms into the shield's containment chamber in sequence, and notifies the tunnel boring machine's main control system to proceed to the next step.

Claims

1. A tunnel cavity detection system integrated into a tunnel boring machine, characterized in that: It includes M×N probe arms embedded in the rear of the tunnel boring machine cutterhead. At least one probe arm is equipped with a hammer at its end, and accelerometers are installed at the ends of the remaining probe arms. Each probe arm is equipped with an independent drive mechanism and a strain gauge pressure sensor. The hammer and drive mechanism are controlled by a host computer. The data collected by the accelerometers and strain gauge pressure sensors are transmitted to the host computer. The drive mechanism controls the extension and retraction of the probe arm. When the extended probe arm contacts the ground interface above the tunnel, the strain gauge pressure sensor monitors the pressure between the probe arm and the ground interface in real time. When the pressure reaches a set threshold, the host computer controls the drive mechanism to stop working.

2. The tunnel cavity detection system integrated into a tunnel boring machine according to claim 1, characterized in that: The probe arm is installed inside the housing chamber of the shield body of the tunnel boring machine. The driving mechanism is a hydraulic cylinder mounted on a support. The support is fixed on the inner wall of the shield body of the tunnel boring machine. The probe arm is driven by the hydraulic cylinder to extend or retract from the housing chamber and to extend and retract radially along the shield body.

3. The tunnel cavity detection system integrated into a tunnel boring machine according to claim 2, characterized in that: The hydraulic cylinder is fixed to the support by a fixed flange and bolts.

4. The tunnel cavity detection system integrated into a tunnel boring machine according to claim 2, characterized in that: The hydraulic cylinder is connected to the hydraulic pump station inside the tunnel boring machine.

5. The tunnel cavity detection system integrated into a tunnel boring machine according to claim 2, characterized in that: The support is a cylindrical seat.

6. The tunnel cavity detection system integrated into a tunnel boring machine according to claim 2, characterized in that: The hammer or accelerometer is connected to the multi-channel data acquisition box via an aviation plug and a cable that runs through the inside of the probe arm.

7. The tunnel cavity detection system integrated into a tunnel boring machine according to claim 2, characterized in that: The strain gauge pressure sensor is integrated in the middle of the probe arm and is connected to the host computer via a cable that runs through the inside of the probe arm.

8. The tunnel cavity detection system integrated into a tunnel boring machine according to claim 1, characterized in that: When there is one hammer, it is installed on the 1×1 probe arm; when there are two hammers, they are installed on the 1×1 and M×N probe arms respectively.

9. A detection method applicable to the detection system of claim 2, characterized in that, Includes the following steps: Step 1, System initialization and probe arm extension: When the main control system of the tunnel boring machine issues a "stop tunneling" signal, the detection system is activated, and the host computer activates each hydraulic cylinder to cause the M×N detection arms to extend out of the shield's receiving chamber in sequence. Step 2, Establishing dynamic coupling: Each strain gauge pressure sensor feeds back the pressure readings between the M×N probe arms and the formation interface to the host computer. The host computer dynamically adjusts the pressure of each hydraulic cylinder and controls the hydraulic cylinder to stop working when the pressure between the probe arm and the formation interface reaches a preset threshold. Step 3, passive source surface wave signal acquisition: Accelerometers on all probe arms synchronously acquire continuous background vibration signals for a duration of T1, and transmit the acquired surface wave data to the host computer in real time. Step 4, Surface wave analysis and screening of low-velocity anomalies: The host computer inverts the shear wave velocity profile of the strata above the tunnel. If no low-velocity anomaly is found, proceed to step 7; if a low-velocity anomaly is found, proceed to step 5. Step 5, Active source reflected wave data acquisition: The host computer triggers the hammers sequentially. When each hammer is triggered, all accelerometers synchronously collect the reflected wave signal for a duration of T2. This process is repeated K times, and the collected reflected wave data is transmitted to the host computer. Step 6, Reflected wave imaging and result output: The host computer first superimposes the reflected wave data, then begins data processing to generate a depth migration profile, depicting the spatial morphology of the anomalous body; based on the reflected wave imaging results and combined with the shear wave velocity profile, it generates a detection report containing the spatial location and morphological characteristics of the anomalous body. Step 7, System reset and probe arm retraction: Regardless of whether any anomalies are detected, after data collection and analysis are completed, the host computer activates each hydraulic cylinder to retract the M×N probe arms into the shield's containment chamber in sequence, and notifies the tunnel boring machine's main control system to proceed to the next step.

10. The detection method according to claim 9, characterized in that: In step 3, T1 is 300 seconds, in step 5, T2 is 0.1 seconds, K is 3, and the morphological features in step 6 include coordinates and dimensions.

Images