Shield tunnel detection method based on natural ray muon

Abstract

The invention discloses a shield tunnel detection method based on natural ray muons, and relates to the technical field of shield tunnel detection, and the method comprises the steps: construction early warning, which is used for early warning stratum density abnormity; the accurate scanning is used for delineating an abnormal area; the construction quality control is used for ensuring proper measures; the construction early warning step specifically comprises the steps of obtaining ground contour information and muon detector position information, and performing forward modeling to obtain a theoretical muon survival rate; calculating an actual muon survival rate; comparing the theoretical muon survival rate with the actual muon survival rate, and calculating the difference significance of the two; if the saliency is smaller than the target threshold value, the shield tunneling machine continues to conduct tunneling forwards till the project is completed; and if the saliency is greater than the target threshold value, indicating that the stratum in the region has density abnormity, and giving out early warning by the system. The method does not use an artificial ray source, has the characteristics of non-invasion and capability of penetrating through a large-scale structure, and is very suitable for detection of an over-excavation area of a tunnel scene.

Description

Technical Field

[0001] The invention relates to the technical field of shield tunnel detection, and in particular to a shield tunnel detection method based on natural ray muons. Background Art

[0002] Tunnel engineering is an infrastructure construction activity that digs and builds passages under the surface. It is widely used in transportation, water conservancy, municipal administration and other fields. Shield technology, as a key construction method in tunnel engineering, is particularly suitable for the construction of soft water-bearing strata or deep underground lines. The advantages of shield technology are its high safety, fast excavation speed, small impact on ground traffic and facilities during construction, and no restrictions on climatic conditions. In tunnel engineering, the application of shield technology also includes tunnel support and lining. During shield excavation, appropriate support measures need to be taken to cope with water and soil pressure to ensure construction safety. With the continuous improvement of shield construction technology, the construction efficiency and quality of tunnel engineering have been significantly improved, but it also faces challenges such as high shield machine operation and maintenance costs, stratum deformation and settlement risks. There are many kinds of dangers in shield tunnel engineering, involving geological risks, construction risks and safety risks. Therefore, detailed surveys and designs should be carried out before construction to understand the geological environment and groundwater level, and to predict and evaluate geological risks.

[0003] At present, traditional detection methods such as geological radar have limited detection depth and can generally only effectively detect shallow areas of tens of centimeters, and are easily interfered by metals such as steel bars. Muon imaging technology uses the natural penetrating properties of cosmic ray muons to penetrate several meters or even more than ten meters behind the lining, accurately image the deep structure, and non-destructively detect the location, size and density of hidden cavities, providing key deep information for the long-term stability assessment of tunnel structures and avoiding the accumulation of potential deep diseases that may cause ground collapse. Summary of the invention

[0004] In order to solve the above technical problems, the present invention discloses a shield tunnel detection method based on natural ray muons, which provides early warning for ground collapse caused by accumulation of deep-seated diseases and complements the existing tunnel detection technology.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A shield tunnel detection method based on natural ray muons, comprising:

[0007] Construction early warning, used to warn of abnormal stratum density;

[0008] Precise scanning to identify abnormal areas;

[0009] Construction quality control, used to ensure that measures are appropriate;

[0010] The steps of construction early warning include:

[0011] Obtain ground contour information and muon detector location information, and forward model the theoretical muon survival rate;

[0012] Calculate the actual muon survival rate;

[0013] Compare the theoretical muon survival rate with the actual muon survival rate and calculate the significance of the difference between the two. If the significance is less than the target threshold, the shield machine continues to advance until the project is completed. If the significance is greater than the target threshold, it indicates that there is a density anomaly in the stratum in the area and the system issues an early warning.

[0014] The steps of precise scanning include: developing precise 3D inversion algorithm, using coarse-grained imaging and boundary recognition to optimize adaptive voxel selection, improving computational efficiency and accuracy; combining abnormal ray screening, building an automatic seed inversion algorithm, achieving high-precision reconstruction of abnormal areas, and enhancing the reliability of the system in complex environments. The steps of construction quality control include: developing a dynamic monitoring system, processing real-time data, and completing dynamic reconstruction of the target area; combining machine learning to develop a risk prediction model to support intelligent decision-making; using visualization technology to intuitively present analysis results, and enhancing the application value of the system in geological disaster prevention and resource development.

[0015] Optionally, the detection method also includes a long-term monitoring step, and after the tunnel excavation is completed, long-term monitoring is carried out on key sections to ensure the long-term stability and safety of the tunnel.

[0016] Optionally, the actual muon survival rate is calculated as follows:

[0017] Use the muon detector to measure the muon count on the surrounding unobstructed ground to obtain airborne measurement data;

[0018] The muon detector is used to measure the muon count in the tunnel and obtain measured data;

[0019] The ratio of the measured data to the air-measured data is the actual muon survival rate measured on site.

[0020] Alternatively, the formula for the significance of the difference between the theoretical muon survival rate and the actual muon survival rate is:

[0021] ;

[0022] in, is the significance, N is the actual muon survival rate, N0 is the theoretical muon survival rate, is the actual muon survival rate error. When it is greater than a certain target threshold, it is considered that there is a high possibility of a cavity in the stratum above the tunnel. If a density anomaly is to be accurately detected in a short period of time, the statistics can be increased by increasing the number of muon detectors, increasing the measurement points of muon detectors, or using muon detectors with large sensitive areas, thereby improving the detection accuracy. In addition, in the case of no sudden changes in the stratum and the surface medium, the existence of density anomalies can also be judged by the sudden changes in survival rate or statistical significance.

[0023] The beneficial effect of the present invention is that the detection method of the present invention does not rely on artificial radiation sources and has the characteristics of non-invasiveness. The technology can penetrate large-scale structures and is particularly suitable for complex and large-scale underground area detection. Unlike other geophysical exploration methods that face challenges in environments with harsh construction conditions, the method of the present invention has a strong anti-interference ability and can ensure the stability and accuracy of the detection results in complex environments. This enables it to provide a more efficient and safe solution in tunnel detection and over-excavation area applications where traditional methods are difficult to implement. Since there is no need for direct contact or use of artificial rays, the application of the method of the present invention is not only safer, but also can effectively improve the accuracy and efficiency of underground detection, and is particularly suitable for detection needs in geologically complex or special environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of a shield tunnel detection method based on natural ray muons of the present invention;

[0025] Figure 2 A schematic diagram of the principle of real-time muon monitoring during shield tunneling in a tunnel scenario according to an embodiment of the present invention;

[0026] Figure 3 A schematic diagram of a geological model according to an embodiment of the present invention;

[0027] Figure 4 The total count response of the muon detector corresponding to different-sized cavities at different detection times at a depth of 75 meters is shown for one embodiment of the present invention;

[0028] Figure 5 The total count response of the muon detector corresponding to different-sized cavities at different detection times at a depth of 25 meters is shown for one embodiment of the present invention;

[0029] Figure 6 The total count response of the muon detector corresponding to different-sized cavities at different detection times at a depth of 50 meters is shown for one embodiment of the present invention;

[0030] Figure 7 The total count response of the muon detector corresponding to different-sized cavities at different detection durations at a depth of 100 meters is shown for one embodiment of the present invention;

[0031] Figure 8 This is a diagram showing the simulation results of the minimum void size that can be detected by a muon detector at different depths and different detection times according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] A shield tunnel detection method based on natural ray muons, such as Figure 1 As shown, including:

[0034] (1) Construction early warning, used to warn of abnormal stratum density; specifically, it includes: obtaining ground contour information and muon detector location information, establishing a simple geological model, and forward modeling to obtain the theoretical muon survival rate; calculating the actual muon survival rate, using the muon detector to measure the muon count on the surrounding unobstructed ground to obtain airborne data; using the muon detector to measure the muon count in the tunnel to obtain measured data; the ratio of the measured data to the airborne data is the actual muon survival rate measured on site; comparing the theoretical muon survival rate with the actual muon survival rate, and calculating the significance of the difference between the two; if the significance is less than the target threshold, the shield machine continues to advance until the project is completed; if the significance is greater than the target threshold, it indicates that there is a density anomaly in the stratum in the area, and the system issues an early warning.

[0035] (2) Precision scanning to delineate abnormal areas; specifically, it includes: developing a precise three-dimensional inversion algorithm, using coarse-grained imaging and boundary recognition to optimize adaptive voxel selection, and improving computational efficiency and accuracy; combining abnormal ray screening to construct an automatic seed inversion algorithm, achieving high-precision reconstruction of abnormal areas, and enhancing the reliability of the system in complex environments.

[0036] (3) Construction quality control, which is used to ensure that measures are appropriate. Specifically, it includes: developing a dynamic monitoring system, processing real-time data, and completing dynamic reconstruction of the target area; developing a risk prediction model in combination with machine learning to support intelligent decision-making; and using visualization technology to intuitively present analysis results to enhance the application value of the system in geological disaster prevention and resource development.

[0037] (4) Long-term monitoring: After tunnel excavation is completed, long-term monitoring is carried out on key sections to ensure the long-term stability and safety of the tunnel.

[0038] When muons penetrate the strata or target objects, their flux will be affected by the medium (including medium density and thickness) due to the interaction with matter (including ionization loss, Coulomb scattering and absorption, etc.). Under the premise of knowing the surface muon flux, when muons pass through the strata and reach the muon detectors placed underground, the muon counts recorded by the muon detectors reflect their survival rate. If the stratum density is uniform, the survival rate of muons can be estimated by quasi-empirical formulas; but if there are low-density anomalies, such as underground voids or over-excavation areas, the muon loss is small, the flux increases, and the muon counts recorded by the muon detectors are more than expected; conversely, if there are high-density anomalies, such as metal ore bodies or high-density rocks, the absorption of muons is enhanced, resulting in a decrease in survival rate, and the detected muon counts are less than expected. By accurately measuring the changes in muon flux in different directions and combining the formation geometry information, the density distribution of the target area can be quantitatively imaged to detect abnormal structures, such as voids. If real-time measurement is required, it is necessary to answer whether enough muon events have accumulated within a reasonable time scale to determine the existence of density anomalies. For example Figure 2 As shown in the figure, one or more muon detectors are placed in the shield machine to continuously record the muon count in real time in the excavation direction, and a real-time actual muon survival rate is calculated at each interval. Compared with the theoretical muon survival rate (assuming there is no void), if there is a significant difference within the statistical range, it means that there may be voids in the stratum. If a void warning is issued, response measures can be taken to backfill the key points.

[0039] For the detection of cavities in the strata above the shield tunnel, the muon detector advances 2 m every 3 h along with the shield machine. It is approximately regarded as the muon detector measuring at each measuring point 2 m apart for 3 h. A simple geological model is established, as shown in the following figure: Figure 3 The muon count distribution of each point in the absence of voids is obtained by forward modeling, and then different density anomalies are placed. By comparing the difference between the muon counts of each measurement point in the case of placing different density anomalies and the muon count distribution in the case of no density anomaly, the position of the density anomaly can be determined.

[0040] In order to more intuitively represent the response of the muon detector to the void, we define: ;in, is the significance, N is the actual muon survival rate, N0 is the theoretical muon survival rate, is the actual muon survival rate error. In this embodiment, it is considered that the significance target threshold is 2. When >2, the total count of the muon detector will respond precisely to the void, and the accuracy of detecting anomalies can reach 95.45%.

[0041] In the constructed model, the tunnel diameter is 15 m, the top of the tunnel is 75 m from the ground surface, and the ground density is 2.4 g / cm 3 , a small flat muon detector with a sensitive area of ​​480 mm × 480 mm is placed at a height of 2 m from the bottom of the tunnel. Holes with side lengths of 1 m, 2 m, ..., 10 m are set above the tunnel, and different detection times are set, namely 3 h, 6 h, ..., 24 h. Under the same measurement time, for holes of different sizes, the above formula is used to calculate the significance of the difference in muon survival rate. The simulation results are shown in the figure below. Figure 4 As shown in Figure 2, different curves represent different detection durations. >2, the muon detector has an accurate response to the void. It can be seen that when the measurement time is 3 h and the side length of the void is greater than 7 m, >2, that is, the muon detector can only detect voids with a side length greater than 7 m. When the measurement time is 24 h and the side length of the void is greater than 4 m, >2, that is, the muon detector can accurately detect voids with a side length greater than 4 m.

[0042] In order to test the detection capability of the muon detector at different stratum depths, the model parameters were set to conduct simulation studies at depths of 25 m, 50 m, 75 m, and 100 m. Similarly, holes with different side lengths were set above the tunnel, and different detection times were set. The simulation results are shown in Figure 2. Figures 4 to 7 As shown in the figure, for a formation depth of 25 m, when only one muon detector is placed, it can accurately respond to voids with a side length greater than 3 m when the measurement time is 3 h. However, at a depth of 100 m, even if the measurement time is increased to 24 h, only voids with a side length of 6 m can be detected. It can be seen that with the increase of formation depth, the response ability of the muon detector to small-sized geological anomalies in a short time decreases sharply. Figure 8is the side length of the minimum void that the muon detector can detect at different depths and different detection times. It can be seen that as the detection time increases, the size of the void that the muon detector can detect at different depths becomes smaller and smaller, that is, the detection accuracy of the muon detector becomes higher and higher. Therefore, if you want to accurately detect small-volume voids in a short time, you can increase the number of muon detectors or use muon detectors with large sensitive areas to increase the statistics, thereby improving the detection accuracy.

[0043] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A shield tunnel detection method based on natural ray muons, characterized in that: include: Construction early warning, used to warn of abnormal stratum density; Precise scanning to identify abnormal areas; Construction quality control, used to ensure that measures are appropriate; The steps of construction early warning include: Obtain ground contour information and muon detector location information, and forward model the theoretical muon survival rate; Calculate the actual muon survival rate; Compare the theoretical muon survival rate with the actual muon survival rate and calculate the significance of the difference between the two. If the significance is less than the target threshold, the shield machine continues to advance until the project is completed. If the significance is greater than the target threshold, it indicates that there is a density anomaly in the stratum in the area and the system issues an early warning.

2. A shield tunnel detection method based on natural ray muons as claimed in claim 1, characterized in that: It also includes a long-term monitoring step. After the tunnel excavation is completed, long-term monitoring will be carried out on key sections to ensure the long-term stability and safety of the tunnel.

3. A shield tunnel detection method based on natural ray muons as claimed in claim 2, characterized in that: The actual muon survival rate is calculated as follows: Use the muon detector to measure the muon count on the surrounding unobstructed ground to obtain airborne measurement data; The muon detector is used to measure the muon count in the tunnel and obtain measured data; The ratio of the measured data to the air-measured data is the actual muon survival rate measured on site.

4. A shield tunnel detection method based on natural ray muons as claimed in claim 3, characterized in that: The formula for the significance of the difference between the theoretical muon survival rate and the actual muon survival rate is: ； in, is the significance, N is the actual muon survival rate, N0 is the theoretical muon survival rate, is the error of the actual muon survival rate itself.

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