Subway tunnel bottom plate leakage detection system and working method thereof

Abstract

The invention relates to a subway tunnel floor leakage detection system and a working method thereof, the system comprises a walking type detection vehicle, the walking type detection vehicle comprises a mobile frame, the mobile frame is provided with an excitation device, a detection unit and a signal acquisition device, the signal acquisition device is in communication connection with a data processing center, and the data processing center is in communication connection with the detection unit. The excitation device is used for impacting the surface of a tunnel structure to generate elastic waves, the detection unit is used for detecting elastic wave response signals and sending the elastic wave response signals to the signal acquisition device for storage, and the data processing center obtains the elastic wave response signals from the signal acquisition device, processes and analyzes the elastic wave response signals and identifies the position and severity of a leakage area. And generating a leakage area schematic diagram and visually displaying the leakage area schematic diagram. Compared with the prior art, on the premise that the tunnel structure is not damaged, automatic, efficient and accurate leakage detection and positioning can be achieved, the method is suitable for structural health detection and operation and maintenance management of the subway tunnel, and the method has the advantages of being high in detection efficiency, accurate in data processing and visual in visual analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering detection, and in particular to a subway tunnel floor leakage detection system and a working method thereof. Background Art

[0002] Subways are a vital component of urban transportation, and their operation and maintenance are crucial to their safe and stable operation. Leakage is a common problem in subway engineering inspections. Severe leakage can lead to corrosion of the concrete floor and rebar, and even structural collapse. Failure to promptly and effectively detect subway leaks can create significant safety hazards. Delayed repairs can severely impact travel efficiency and even lead to serious accidents.

[0003] The traditional method for detecting tunnel leakage involves equipping a tunnel inspection cart with a suction roller and a humidity sensor. The suction roller is held against the tunnel wall during movement, and the humidity sensor monitors changes in the roller's humidity to determine if leakage has occurred. This method is inherently inefficient and difficult to accurately determine. Existing research utilizes infrared and visible light image fusion processing technology, such as Chinese patent CN111899288A. This technology utilizes industrial cameras to capture infrared and visible light images of the area under test. Furthermore, by fusing infrared and visible light images, it combines the advantages of both images, enabling detection and identification of tunnel leaks even under harsh lighting conditions and with numerous interference factors. However, this method cannot accurately locate leaking areas within large subway tunnels. Summary of the Invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide a subway tunnel floor leakage detection system and its working method, which can automatically, efficiently and accurately perform leakage detection on subway tunnels and locate the leakage area.

[0005] The objectives of the present invention can be achieved through the following technical solutions: A subway tunnel floor leakage detection system includes a walking detection vehicle, the walking detection vehicle includes a mobile frame, an excitation device, a detection unit and a signal acquisition device are installed on the mobile frame, the signal acquisition device is communicatively connected to a data processing center, the excitation device is used to impact the surface of the tunnel structure to generate elastic waves, the detection unit is used to detect the elastic wave response signal and send it to the signal acquisition device for storage, the data processing center obtains the elastic wave response signal from the signal acquisition device and processes and analyzes it, identifies the location and severity of the leakage area, generates a schematic diagram of the leakage area and displays it visually.

[0006] Furthermore, the excitation device includes a sleeve, a hammer is arranged in the sleeve, and the hammer is connected to a controller for controlling the hammer to fall freely to hit the surface of the tunnel structure.

[0007] Furthermore, a plastic block is provided at the bottom end of the sleeve to prevent the hammer from rebounding and generating a secondary impact after hitting the surface of the tunnel structure.

[0008] Furthermore, the detection unit includes a plurality of array-arranged detectors for detecting elastic wave response signals at respective measurement points. The detectors are connected to each other, and to the movable frame, by soft cloth tapes.

[0009] Furthermore, a power supply is installed on the mobile frame for providing power to the excitation device, the detection unit and the signal acquisition device.

[0010] Furthermore, the movable frame is provided with an adjustment mechanism to adapt to different tunnel floor widths.

[0011] A method for detecting leakage in a subway tunnel floor comprises the following steps:

[0012] S1. Determine the inspection area and inspection plan based on the engineering data of the subway tunnel;

[0013] S2. Move the walking inspection vehicle above the inspection area, then activate the excitation device to apply impact to the tunnel structure surface, generating elastic waves that propagate inside the tunnel structure. The corresponding elastic wave response signals are received by the detection unit and stored in the signal acquisition device until the elastic wave response signals of all inspection points are collected and stored.

[0014] S3. Process all collected and stored elastic wave response signals, identify the location and severity of the leakage area by calculating the response energy, and generate a schematic diagram of the leakage area by calculating the proportional coefficient of the response energy and the cumulative void thickness.

[0015] Furthermore, the step S3 specifically includes:

[0016] S31, performing denoising and filtering on all collected and stored elastic wave response signals;

[0017] According to the propagation characteristics of elastic waves inside the tunnel structure, the effective time of data calculation response energy is adjusted, and the elastic wave signal data after the effective time is retained;

[0018] S32, calculating the response energy of each measurement point;

[0019] S33. Based on the response energy data of each measurement point, a regional energy distribution map is drawn. By data interpolation and regional gridding, combined with waveform characteristics and energy changes, the location and severity of the leakage area are identified;

[0020] S34. Obtain concrete samples of the tunnel structure, combine them with the corresponding response energy data, calculate the linear proportional coefficient between the response energy and the cumulative void thickness, draw a schematic diagram of the leakage area, and present the detection results in a visual manner.

[0021] Furthermore, the calculation formula for the effective time in step S31 is:

[0022] T=2h / v

[0023] Wherein, h is the thickness of the tunnel structure bottom plate structure, and v is the propagation velocity of elastic waves in the tunnel structure bottom plate.

[0024] Furthermore, the calculation formula for the response energy in step S32 is:

[0025]

[0026] Among them, a i is the amplitude of each elastic wave response signal collected within the effective time area.

[0027] Compared with the prior art, the present invention has the following advantages:

[0028] The present invention proposes a subway tunnel floor leakage detection system, including a walking inspection vehicle. The walking inspection vehicle adopts an integrated design and includes an excitation device, a detection unit, a signal acquisition device, and a mobile frame. The excitation device exerts an impact on the tunnel floor by hitting the surface of the tunnel structure, thereby exciting elastic waves; the detection unit synchronously acquires elastic wave response signals; the signal acquisition device is responsible for high-precision recording and storage of elastic wave response data of each measuring point. Finally, the data processing center processes and analyzes the elastic wave response signals, identifies the location and severity of the leakage area, generates a schematic diagram of the leakage area, and displays it visually. The present invention collects data by walking the inspection vehicle and performs background data analysis by the data processing center, which can realize non-destructive testing and can achieve automated, efficient, and accurate leakage detection and leakage area positioning without destroying the tunnel structure.

[0029] In the present invention, the excitation device consists of a hammer, a sleeve and a plastic block. By controlling the free fall of the hammer to hit the surface of the tunnel structure to generate elastic waves, and using the plastic block to prevent the hammer from rebounding and generating secondary impacts, the reliability of elastic wave excitation can be ensured, which is conducive to the subsequent data processing center to perform accurate data analysis.

[0030] In the present invention, the detection unit adopts a plurality of detectors arranged in an array, which can synchronously and real-timely collect elastic wave response signals of multiple measurement points, thereby improving the acquisition accuracy of elastic wave signals and more accurately identifying leakage areas.

[0031] The present invention first denoises and filters all collected and stored elastic wave response signals to reduce environmental noise and irrelevant interference. The effective time for calculating the response energy is then adjusted based on the propagation characteristics of elastic waves within the structure, retaining only elastic wave signal data after the effective time. The response energy at each measurement point is then calculated to create a regional energy distribution map. Through data interpolation and regional gridding, the location and severity of the leakage area are identified by combining waveform characteristics and energy changes. Furthermore, concrete samples from the tunnel structure are obtained and combined with the corresponding response energy data to calculate the linear proportional coefficient between the response energy and the cumulative void thickness, creating a schematic diagram of the leakage area. This method utilizes elastic waves to detect subway leakage, and through analysis of the response energy and visualization after sampling and calibration, it is possible to accurately locate the leakage area. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a schematic structural diagram of the walking inspection vehicle of the present invention;

[0033] Figure 2 Schematic diagram of the structure of the excitation device in the present invention;

[0034] Figure 3 Schematic diagram of the method flow of the present invention;

[0035] Figure 4 This is the first measurement signal frequency diagram of the No. 1 detector in the side trail measurement of mileage pile numbers SK8+405 to SK8+409 in the embodiment;

[0036] Figure 5 This is a schematic diagram of the plane void from milepost numbers SK8+405 to SK8+409 in the embodiment;

[0037] Explanation of the marks in the figure: 1. Excitation device, 2. Detector, 3. Signal acquisition device, 4. Power supply, 101. Hammer, 102. Sleeve, 103. Plastic block. DETAILED DESCRIPTION

[0038] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] Example

[0040] A subway tunnel floor leakage detection system includes a walking detection vehicle, such as Figure 1As shown, the walking inspection vehicle includes a mobile frame, on which are mounted an excitation device 1, a detection unit (composed of a plurality of detectors 2 arranged in an array), a signal acquisition device 3 and a power supply 4, wherein the signal acquisition device 3 is communicatively connected to a data processing center.

[0041] In this embodiment, the power source 4 adopts a high-capacity rechargeable battery to provide a stable and continuous power supply during actual measurement;

[0042] Excitation device 1 Figure 2 As shown, it consists of a hammer 101, a sleeve 102 and a plastic block 103. The elastic wave is generated by controlling the free fall of the hammer 101 to hit the surface of the tunnel structure, and the plastic block 103 is used to prevent the hammer 101 from rebounding and generating a secondary impact.

[0043] The geophone 2 uses a high-sensitivity longitudinal wave velocity sensor to record the elastic wave response signal at each measurement point. During the actual detection process, it is arranged in an array. Soft cloth tape is used to connect the geophones 2 and the geophones 2 to the mobile frame.

[0044] The signal acquisition device 3 is used to store elastic wave response signal data, and the data processing center obtains the elastic wave response signal from the signal acquisition device 3 and processes and analyzes it, identifies the location and severity of the leakage area, generates a schematic diagram of the leakage area and displays it visually.

[0045] In addition, the mobile frame is equipped with an adjustment mechanism that can flexibly adapt to the width of different tunnel floors.

[0046] The above-mentioned walking inspection vehicles adopt an integrated design, which is easy to carry and move, reduces the complexity of manual operation and improves inspection efficiency.

[0047] Based on the above system, a subway tunnel floor leakage detection method is implemented, such as Figure 3 As shown, the following steps are included:

[0048] S1. Determine the inspection area and inspection plan based on the engineering data of the subway tunnel;

[0049] Review relevant information on the subway tunnel project, including design drawings, construction records, and maintenance logs; collect and integrate structural parameters of the base plate and concrete material; determine the detector placement distances; and determine the inspection plan;

[0050] S2. Move the walking inspection vehicle above the inspection area, then activate the excitation device to apply impact to the tunnel structure surface, generating elastic waves that propagate inside the tunnel structure. The corresponding elastic wave response signals are received by the detection unit and stored in the signal acquisition device until the elastic wave response signals of all inspection points are collected and stored.

[0051] S3. Process all collected and stored elastic wave response signals, identify the location and severity of the leakage area by calculating the response energy, and generate a schematic diagram of the leakage area by calculating the proportional coefficient of the response energy and the cumulative void thickness.

[0052] This embodiment applies the above solution, and the specific contents are as follows:

[0053] 1. Preparation: This step aims to obtain relevant information about the subway tunnel project, provide basic data support for subsequent inspections, and ensure the scientificity and rationality of the inspection plan. This step includes the following sub-steps:

[0054] 101. Review relevant information of the tunnel to be inspected, including design drawings, construction records, maintenance logs, etc., and analyze the tunnel structure floor material and structural form;

[0055] 102. Based on the preliminary analysis results, combined with the actual project environment and testing requirements, clarify the testing objectives, delineate the specific testing area, and develop a detailed testing plan, including testing routes, measurement point distribution, detector layout distance, testing parameters, environmental influencing factors, etc., to ensure the operability and repeatability of the testing work;

[0056] Detection Phase: This phase uses elastic wave detection technology to obtain the response signal of the subway tunnel structure floor and assess the potential leakage location and extent. This phase includes the following sub-steps:

[0057] 201. Push the mobile inspection vehicle into the area to be tested and place it stably, ensuring that the detector is accurately aligned with the predetermined inspection point. The detector should ensure good contact with the tunnel structure floor surface to reduce signal attenuation and external environmental interference;

[0058] 202. Trigger the excitation device to make the hammer fall freely at a constant height and impact the surface of the tunnel structure floor, generating an elastic wave signal. To improve data stability, the same detection point can be stimulated multiple times to obtain better quality signal data;

[0059] 203. Collect data point by point according to the predetermined measuring points, and repeatedly trigger the excitation device at each measuring point to ensure the integrity and comparability of the data. All test data must record information such as time, location, and environmental factors for subsequent analysis.

[0060] 3. Data processing stage: Analyze the collected elastic wave signals to extract key features and generate visualization results. This step includes the following sub-steps:

[0061] 301. The original signal data was preprocessed using MATLAB software, and the effective time range of data calculation was adjusted to obtain stable response energy parameters.

[0062] Because elastic waves propagate uniformly within the structure being tested, if there are defects such as cracks, voids, or water seepage within the structure, the elastic waves will be reflected or scattered upon reaching that location, causing changes in the signal characteristics. Therefore, the valid time range of the data at each measurement point can be determined using the following calculation formula:

[0063] T=2h / v

[0064] Where h is the thickness of the structure's floor (unit: meters), and v is the propagation velocity of elastic waves in the structure's floor (unit: velocity, m / s). Based on this calculation formula, elastic wave signal data after time T is retained. This calculation method can be used to filter the effective signal range, avoid interference from irrelevant noise in data analysis, and thus improve the accuracy and reliability of leak detection.

[0065] In addition, the response energy calculation formula of each measurement point is:

[0066]

[0067] Among them, a i is the amplitude of each elastic wave response signal collected within the effective time area.

[0068] 302. Run the Python program to perform time and frequency domain analysis on the data processed by MATLAB, extract characteristic parameters, and generate a waveform graph. By comparing the waveform characteristics of different detection points, preliminarily identify areas where leakage may occur.

[0069] The calculated response energy is input into the Surfer software, and the interpolation algorithm is used to grid the measurement area. A schematic diagram of the subway leakage situation in the detection area is generated to visually present the detection results.

[0070] IV. Verification and Calibration: To ensure the accuracy of the test results, this step is verified through physical sampling and other means. This step includes the following sub-steps:

[0071] 401. Select representative measurement points and obtain concrete samples by coring or other minimally destructive testing methods;

[0072] 402. Conduct permeability tests, moisture content tests, crack depth analysis, etc. on the concrete at the sampling points to assess the actual leakage situation and compare and analyze it with the test results;

[0073] 403. Based on the comparison results, the linear proportional coefficient between the response energy and the cumulative void thickness in the detection method is obtained. This linear relationship is used for other detection points to determine the cumulative void thickness. Finally, a cumulative void thickness map within the detection area, i.e., a schematic diagram of the leakage area, is drawn.

[0074] This embodiment is aimed at a certain subway track structure and implements the following process based on the above-mentioned detection system and method:

[0075] 1. Preparation: Review relevant information on subway tunnel projects and establish a testing plan.

[0076] The inspection target is the subway sub-track structure. Based on site conditions, six survey lines were planned, covering the tunnel sidewalk area, the middle track area, and the tunnel mid-walk area. Each survey line uses a 3D array geophone dragging method along the tunnel longitudinal direction. Each survey line includes four measuring points / geophones, with 20 cm spacing horizontally and 20 cm spacing vertically, for a total length of approximately 200 meters. This example uses the measurement of the sidewalk and track slab from milepost numbers SK8+405 to SK8+409 as an example.

[0077] Second, during the testing phase, the testing instrument is moved above the testing area, ensuring stable contact between the instrument and the tunnel structure floor. The excitation device then applies an impact to the structure surface, causing elastic waves to propagate within the structure. The geophone receives and collects the corresponding response signals. After each measurement, the measuring vehicle is moved to the next testing point until all test points are complete.

[0078] The main equipment used in this step are power supply, excitation device, detector, signal acquisition device (portable computer) and mobile frame. The detector acquisition frequency is 100Hz.

[0079] Data Processing: The collected elastic wave signals are processed to generate waveforms, calculate response energy, and create a schematic diagram of the subway leakage situation. By comparing waveform characteristics in different areas, the location and severity of potential leakage points are identified. Analysis is then conducted based on actual project conditions to visualize the subway tunnel leakage situation.

[0080] MATLAB software was used to preprocess the raw signal data. The effective time range for data calculation was adjusted. The foundation thickness was set to h = 2m, the propagation velocity of elastic waves in C30 concrete was assumed to be v = 3600m / s, and the effective time was set to T = 2h / v = 1.11ms. Therefore, elastic wave signal data after 0.11ms was retained to obtain the response energy parameters for the corresponding time. A Python program was run to perform time and frequency domain analysis on the MATLAB-processed data, extract characteristic parameters, and generate a waveform graph. Figure 4The figure shows the first measurement signal frequency spectrum of geophone No. 1 during the sidewalk survey from mileposts SK8+405 to SK8+409. The left side shows discarded data, while the right side shows the data within the valid time. This example uses MATLAB for signal preprocessing and calculation, combined with Python for visual analysis, making the data processing more efficient and intuitive, and improving the accuracy of leak identification.

[0081] By comparing waveform characteristics at different test points, we can initially identify areas where leakage may occur. The calculated response energy is input into Surfer software, which uses an interpolation algorithm to grid the measurement area and generate a schematic diagram of the subway leakage situation within the test area, visualizing the test results. Finally, we create a distribution map of the impact response magnification within the block, thereby determining the leakage status of the test area.

[0082] 4. Verification and calibration: Drill core samples at selected locations on site, use drilling method or micro-destructive detection means to obtain concrete samples, compare them with the response energy of the test point, correct the linear proportional coefficient of the response energy and cumulative void thickness in the test method, use this linear relationship to determine the cumulative void thickness at other test points, and finally draw a cumulative void thickness map within the test area. Figure 5 Shown is a schematic diagram of the plane void from mileage pile numbers SK8+405 to SK8+409.

[0083] Through the above calibration method of comparing core sampling with schematic diagram, the accuracy of the test results can be further verified and the possibility of misjudgment can be reduced.

[0084] It should be noted that, in the absence of conflicts, the software in this embodiment may be replaced by other existing methods or technologies.

[0085] This system and method is based on the transmission characteristics of elastic waves within structures and is applied to actual tests for subway tunnel leakage detection, which has important practical engineering significance. This solution has the following beneficial effects:

[0086] (1) During the actual detection process, this solution only requires the use of an excitation device to generate elastic waves and a detector to collect the response signal. The entire process does not require large-scale destruction or invasive operations on the tunnel structure. This non-destructive detection method effectively reduces the impact on the tunnel structure, while saving the cost of subsequent maintenance and repair, and improving the economy and safety of engineering detection. This solution is applicable to different geological conditions and construction environments, can meet the detection needs of various subway tunnels, and improves the applicability of the project.

[0087] (2) This solution provides a subway tunnel leakage detection device that is easy to operate and highly adaptable. It uses an integrated detection vehicle and a three-dimensional array detector, so that the detection device can be stably and efficiently applied in complex tunnel environments, greatly improving the efficiency and adaptability of on-site detection.

[0088] (3) This solution provides a highly accurate, intuitive and reliable method for detecting leakage in subway tunnels. It utilizes the characteristics of elastic waves propagating evenly in the tunnel floor structure, as well as the reflection and scattering changes of the waveform when encountering defects such as cracks, cavities or water seepage, and uses the response energy to draw a leakage diagram to ensure the accuracy and reliability of the detection data.

Claims

1. A subway tunnel floor leakage detection system, characterized in that: The invention comprises a walking inspection vehicle, the walking inspection vehicle comprising a mobile frame, an excitation device (1), a wave detection unit and a signal acquisition device (3) mounted on the mobile frame, the signal acquisition device (3) being communicatively connected to a data processing center, the excitation device (1) being used to impact a tunnel structure surface to generate elastic waves, the wave detection unit being used to detect elastic wave response signals and send them to the signal acquisition device (3) for storage, the data processing center acquiring the elastic wave response signals from the signal acquisition device (3) and performing processing and analysis to identify the location and severity of a leakage area, generate a schematic diagram of the leakage area and perform visual display.

2. A subway tunnel floor leakage detection system according to claim 1, characterized in that: The excitation device (1) comprises a sleeve (102), a hammer (101) is arranged in the sleeve (102), and the hammer (101) is connected to a controller for controlling the hammer (101) to fall freely to hit the surface of the tunnel structure.

3. A subway tunnel floor leakage detection system according to claim 2, characterized in that: A plastic block (103) is provided at the bottom end of the sleeve (102) to prevent the hammer (101) from rebounding and generating a secondary impact after hitting the surface of the tunnel structure.

4. The subway tunnel floor leakage detection system according to claim 1, characterized in that: The detection unit comprises a plurality of detectors (2) arranged in an array, which are used to detect elastic wave response signals at respective measurement points. The detectors (2) are connected to each other, and the detectors (2) and the movable frame are connected by soft cloth belts.

5. The subway tunnel floor leakage detection system according to claim 1, characterized in that: A power supply (4) is installed on the mobile frame for providing power to the excitation device (1), the detection unit and the signal acquisition device (3).

6. The subway tunnel floor leakage detection system according to claim 1, characterized in that: The movable frame is provided with an adjustment mechanism to adapt to different tunnel floor widths.

7. A subway tunnel floor leakage detection method, applied to a subway tunnel floor leakage detection system as claimed in claim 1, characterized in that: The following steps are involved: S1. Determine the inspection area and inspection plan based on the engineering data of the subway tunnel; S2, moving the walking inspection vehicle to the top of the inspection area, then starting the excitation device (1) to exert an impact on the surface of the tunnel structure, generating elastic waves that propagate inside the tunnel structure, and receiving corresponding elastic wave response signals by the detection unit and storing them in the signal acquisition device (3), until the elastic wave response signals of all inspection points are collected and stored; S3. Process all collected and stored elastic wave response signals, identify the location and severity of the leakage area by calculating the response energy, and generate a schematic diagram of the leakage area by calculating the proportional coefficient of the response energy and the cumulative void thickness.

8. The method for detecting leakage in a subway tunnel floor according to claim 7, characterized in that: The step S3 specifically includes: S31, performing denoising and filtering on all collected and stored elastic wave response signals; According to the propagation characteristics of elastic waves inside the tunnel structure, the effective time of data calculation response energy is adjusted, and the elastic wave signal data after the effective time is retained; S32, calculating the response energy of each measurement point; S33. Based on the response energy data of each measurement point, a regional energy distribution map is drawn. By data interpolation and regional gridding, combined with waveform characteristics and energy changes, the location and severity of the leakage area are identified; S34. Obtain concrete samples of the tunnel structure, combine them with the corresponding response energy data, calculate the linear proportional coefficient between the response energy and the cumulative void thickness, draw a schematic diagram of the leakage area, and present the detection results in a visual manner.

9. The method for detecting leakage in a subway tunnel floor according to claim 8, characterized in that: The calculation formula of the effective time in step S31 is: T=2h / v Wherein, h is the thickness of the tunnel structure bottom plate structure, and v is the propagation velocity of elastic waves in the tunnel structure bottom plate.

10. The method for detecting leakage in a subway tunnel floor according to claim 8, characterized in that: The calculation formula of the response energy in step S32 is: Among them, a i is the amplitude of each elastic wave response signal collected within the effective time area.

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