Detection method for shield tunnel construction based on cosmic ray muons

Abstract

The present application relates to the field of muon detection, and specifically to a detection method for shield machine tunnel construction based on cosmic ray muons, which is used to detect the internal geological structure of the area where the tunnel construction is located when the shield machine is carrying out tunnel construction. A muon detector is installed on the shield machine, and the detection method includes: constructing a three-dimensional geological model of the area where the tunnel construction is located according to the geological data of the area where the tunnel construction is located; simulating the process of muons passing through the three-dimensional geological model to obtain the expected muon attenuation; obtaining the first measured muon data collected by the muon detector and determining the measured muon attenuation according to the first measured muon data; based on the measured muon attenuation and the expected muon attenuation, determining the internal structure information of the area where the tunnel construction is located. When using a shield machine for tunnel construction, the internal structure of the area where the tunnel construction is located can be determined in real time, and the density abnormality area in the area where the tunnel construction is located can be effectively identified and located.

Description

Technical Field

[0001] The present application relates to the field of muon detection, and in particular to a detection method for shield machine tunnel construction based on cosmic ray muons. Background Art

[0002] In the process of tunnel construction using shield machines, there are problems with the tunnel covering in the completed construction area and the unclear geological conditions in the unconstructed area ahead. At present, geological radar detection, ultrasonic detection and other methods are mainly used to detect the geological conditions of tunnel covering and unconstructed areas, but these methods have problems such as limited detection depth, inability to effectively penetrate thick coverings, insufficient resolution for complex geological structures, greater impact from environmental noise, and signal susceptibility to interference. These methods have limitations in detection depth and accuracy, especially in complex geological conditions such as soft soil stratification, cavities, underground rivers and isolated rocks, and it is difficult to provide accurate geological information. Summary of the invention

[0003] In order to overcome the problems existing in the related art, the present application provides a detection method for shield machine tunnel construction based on cosmic ray muons.

[0004] The present application embodiment provides a detection method for shield machine tunnel construction based on cosmic ray muons, which is used to detect the internal geological structure of the tunnel construction area when the shield machine is performing tunnel construction. The shield machine is equipped with a muon detector, and the detection method includes:

[0005] Constructing a three-dimensional geological model of the area where the tunnel is to be constructed based on the geological data of the area where the tunnel is to be constructed;

[0006] Simulating a process in which muons pass through the three-dimensional geological model to obtain an expected muon attenuation;

[0007] Acquire first measured muon data collected by the muon detector and determine a measured muon attenuation amount according to the first measured muon data;

[0008] Based on the measured muon attenuation and the expected muon attenuation, internal structure information of the area where the tunnel construction is located is determined.

[0009] In some exemplary embodiments of the present application, the simulating process of muons passing through the three-dimensional geological model to obtain the expected muon attenuation includes:

[0010] Generating initial muon data corresponding to the geographical location of the shield machine;

[0011] Using the initial muon data as a first simulated muon flux under open air conditions;

[0012] Simulating a process in which muons in the initial muon data pass through the three-dimensional geological model to obtain a second simulated muon flux after the muons pass through the tunnel construction area;

[0013] The expected muon attenuation is determined based on the first simulated muon flux and the second simulated muon flux.

[0014] In some exemplary embodiments of the present application, the detection method further includes:

[0015] Recording the data acquisition time of the muon detector acquiring the first measured muon data;

[0016] The ring number at which the muon detector is located when the first measured muon data is collected is determined according to the data collection time and the operation data of the shield machine; wherein the operation data includes the corresponding relationship between the position and time of the shield machine.

[0017] In some exemplary embodiments of the present application, the step of acquiring first measured muon data collected by the muon detector and determining a measured muon attenuation amount according to the first measured muon data includes:

[0018] Acquire second measured muon data of the muon detector under open-air conditions;

[0019] Correcting the second measured muon data according to the parameters of the muon detector to obtain corrected muon data;

[0020] Obtaining a correction factor according to the corrected muon data and the first simulated muon flux;

[0021] Correcting the second measured muon data using the correction factor to obtain corrected muon data;

[0022] The measured muon attenuation is obtained according to the corrected muon data and the first measured muon data.

[0023] In some exemplary embodiments of the present application, determining the internal structure information of the area where the tunnel construction is located based on the measured muon attenuation and the expected muon attenuation includes:

[0024] When the shield machine moves to a ring number, a first ratio of the measured muon attenuation and the expected muon attenuation corresponding to the ring number is determined. If the first ratio is greater than a first preset ratio or less than a second preset ratio, it is determined that there is a density anomaly area within the preset range where the ring number is located.

[0025] In some exemplary embodiments of the present application, the determining the internal structure information of the area where the tunnel construction is located based on the measured muon attenuation and the expected muon attenuation further includes:

[0026] When there are density anomaly areas within the preset range of a continuous preset number of ring numbers, at least each of the continuous preset number of ring numbers is determined as a target ring number; and the unit measured muon attenuation and the unit expected muon attenuation at a plurality of different zenith angles in each of the target ring numbers are determined;

[0027] Determine a second ratio of the unit measured muon attenuation to the corresponding unit expected muon attenuation at the plurality of different zenith angles;

[0028] The position and size of the density anomaly area are determined according to the second ratios corresponding to the multiple different zenith angles.

[0029] In some exemplary embodiments of the present application, determining the position and size of the density anomaly area according to the second ratios corresponding to the multiple different zenith angles includes:

[0030] generating a muon two-dimensional imaging map corresponding to each target ring number according to the second ratios corresponding to the multiple different zenith angles under each target ring number, wherein the muon two-dimensional imaging map is used to characterize the distribution of the second ratios corresponding to each zenith angle under different azimuth angles;

[0031] Determine the two muon two-dimensional imaging images as target muon two-dimensional imaging images;

[0032] Determining a target azimuth according to a distribution of the second ratio in the two target muon two-dimensional imaging images;

[0033] According to the second ratio corresponding to each of the zenith angles under the target azimuth angle, determine the zenith angle of the starting position of the density anomaly region in one of the target muon two-dimensional imaging images as the first zenith angle, determine the zenith angle of the starting position of the density anomaly region in another target muon two-dimensional imaging image as the second zenith angle, and determine the zenith angle of the ending position of the density anomaly region in one of the target muon two-dimensional imaging images as the third zenith angle;

[0034] The height position and width size of the density anomaly area are determined according to the first zenith angle, the second zenith angle, the third zenith angle and the spacing between the ring numbers corresponding to the two target muon two-dimensional imaging images.

[0035] In some exemplary embodiments of the present application, the detection method further includes:

[0036] Using an algebraic reconstruction technique algorithm, taking an initial density estimate as an initial value, and taking the first measured muon data as target data, performing an iterative operation to obtain a reconstruction result, until the error between the reconstruction result and the first measured muon data converges, and obtaining a three-dimensional distribution model of all voxel densities in the area where the tunnel construction is located;

[0037] According to the three-dimensional distribution model, the position and size of the abnormal density area are obtained.

[0038] In some exemplary embodiments of the present application, the muon detector is installed in the middle or rear of the shield machine, the detection surface of the muon detector is parallel to the ground, and the internal structure information is used to characterize the internal structure of the tunnel covering after the construction is completed.

[0039] In some exemplary embodiments of the present application, the muon detector is installed at the front of the shield machine, the detection surface of the muon detector is parallel to the ground or inclined toward the unconstructed area of ​​the tunnel, and the internal structure information is used to characterize the internal structure of the tunnel covering after partial construction and the internal structure of the partial unconstructed area.

[0040] The technical solution provided by the embodiments of the present application may include the following beneficial effects: when using a shield machine for tunnel construction, the detection method for shield machine tunnel construction based on cosmic ray muons of the present application is used, and the muon data is continuously collected and analyzed using the muon detector installed on the shield machine, and the measured muon attenuation is compared with the expected muon attenuation. The internal structure of the tunnel construction area, such as the tunnel covering and unconstructed area, can be determined in real time, and the density abnormality areas in the tunnel covering and unconstructed area can be effectively identified and located, thereby helping engineers to monitor and evaluate the geological conditions of the tunnel construction area in real time, and promptly identify and respond to potential risks.

[0041] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0043] Figure 1 It is a schematic diagram of the position, detection plane direction and field of view of a muon detector installed on a shield machine.

[0044] Figure 2 This is a schematic diagram showing the location, detection plane direction and field of view of a muon detector installed on another shield machine.

[0045] Figure 3This is one of the flow charts of a detection method for shield machine tunnel construction based on cosmic ray muons according to an exemplary embodiment of the present application.

[0046] Figure 4 It is a schematic diagram of the three-dimensional geological model of the area where the tunnel construction is located and the simulated field of view of the muon detector.

[0047] Figure 5 According to the exemplary embodiment of the present application Figure 3 Flowchart of step S302 in FIG.

[0048] Figure 6 This is the muon number distribution diagram of the first simulated muon flux under open air conditions.

[0049] Figure 7 This is the muon number distribution diagram of the second simulated muon flux after the muons pass through the tunnel construction area.

[0050] Figure 8 This is the muon population distribution diagram of the first measured muon data.

[0051] Fig. 9 According to the exemplary embodiment of the present application Figure 3 Flowchart of step S303 in FIG.

[0052] Fig.10 This is the muon number distribution diagram of the second measured muon data.

[0053] Fig.11 This is one of the test result pages of the muon detector when collecting muon data under open air conditions.

[0054] Fig.12 This is the second picture of the test result page when the muon detector collected muon data under open air conditions.

[0055] Fig.13 This is the second flow chart of a detection method for shield machine tunnel construction based on cosmic ray muons according to an exemplary embodiment of the present application.

[0056] Fig.14 This is an example of a one-dimensional data analysis using the measured and expected muon decays.

[0057] Fig.15 According to the exemplary embodiment of the present application Figure 3 Flowchart of step S304 in FIG.

[0058] Fig.16 According to the exemplary embodiment of the present application Fig.15 Flowchart of step S304-3 in FIG.

[0059] Fig.17 This is an example of a two-dimensional image of a muon.

[0060] Fig.18 It is a schematic diagram of the relationship between the height position and width dimensions of the density anomaly area and the first zenith angle, the second zenith angle and the third zenith angle.

[0061] Fig.19 This is the third flow chart of a detection method for shield machine tunnel construction based on cosmic ray muons according to the exemplary embodiment of the present application.

[0062] Fig. 20 This is one of the example graphs of a slice graph of a 3D distribution model.

[0063] Fig.21 This is the second example of a slice diagram of a three-dimensional distribution model.

[0064] Fig. 22 This is the third example of a slice diagram of a three-dimensional distribution model.

[0065] Fig.23 This is the fourth example of a slice diagram of a three-dimensional distribution model.

[0066] Fig.24 This is the fifth example of a slice diagram of a three-dimensional distribution model.

[0067] Fig.25 This is the sixth example of a slice diagram of a three-dimensional distribution model.

[0068] Fig.26 This is the seventh example of a slice diagram of a three-dimensional distribution model.

[0069] Fig. 27 This is the eighth example of a slice diagram of a three-dimensional distribution model.

[0070] Fig.28 This is the fourth flow chart of a detection method for shield machine tunnel construction based on cosmic ray muons according to the exemplary embodiment of the present application.

[0071] Fig.29 This is the fifth flow chart of a detection method for shield machine tunnel construction based on cosmic ray muons according to the exemplary embodiment of the present application. DETAILED DESCRIPTION

[0072] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of methods consistent with some aspects of the present invention as detailed in the appended claims.

[0073] In the process of tunneling with a shield machine, there is a problem of unclear geological conditions in the tunnel covering of the completed construction area and the unconstructed area ahead. At present, geological radar detection, ultrasonic detection and other methods are mainly used to detect the geological conditions of the tunnel covering and the unconstructed area, but these methods have problems such as limited detection depth, inability to effectively penetrate thick coverings, insufficient resolution for complex geological structures, greater impact from environmental noise, and susceptibility to signal interference. These methods have limitations in detection depth and accuracy, especially in complex geological conditions such as soft soil stratification, cavities, underground rivers and isolated rocks, and it is difficult to provide accurate geological information.

[0074] In order to solve the above technical problems, the present application provides a detection method for shield machine tunnel construction based on cosmic ray muons. A muon detector is installed on the shield machine, and a three-dimensional geological model of the area where the tunnel construction is located is constructed according to the geological data of the area where the tunnel construction is located, and the process of muons passing through the three-dimensional geological model is simulated to obtain the expected muon attenuation, obtain the first measured muon data collected by the muon detector, and determine the measured muon attenuation according to the first measured muon data. Based on the measured muon attenuation and the expected muon attenuation, the internal structure information of the area where the tunnel construction is located is determined. In this way, when a shield machine is used for tunnel construction, the muon detector installed on the shield machine is used to continuously collect and analyze muon data, and the measured muon attenuation is compared with the expected muon attenuation. The internal structure of the area where the tunnel construction is located, such as the tunnel covering and the unconstructed area, can be determined in real time, and the density abnormality area in the tunnel covering and the unconstructed area can be effectively identified and located, thereby helping engineers to monitor and evaluate the geological conditions of the area where the tunnel construction is located in real time, and timely identify and respond to potential risks.

[0075] For ease of understanding, first, the structures of the shield machine and the muon detector used in the detection method for shield machine tunnel construction based on cosmic ray muons provided in the exemplary embodiment of the present application are described as follows: Figure 1 and Figure 2 As shown in Figure 1, a muon detector is installed on the shield machine. A muon detector is a device used to detect cosmic ray muons. It is usually composed of a multi-layer structure and can measure the direction and position of muons. It can also use the energy loss and angle changes that occur when muons penetrate matter to perform imaging. Figure 1In the process, the muon detector is installed in the middle or rear of the shield machine, the detection plane of the muon detector is parallel to the ground, and the target area detected by the muon detector is the area within the field of view of the muon detector in the tunnel covering after the construction is completed. Figure 2 In the process, the muon detector is installed at the front of the shield machine, and the detection surface of the muon detector is inclined toward the unconstructed area of ​​the tunnel. The target area detected by the muon detector is the area in the tunnel cover after construction and the area in the unconstructed area within the field of view of the muon detector. One muon detector can be set, or multiple muon detectors can be set to expand the detection range. When multiple muon detectors are set, multiple muon detectors can be arranged along the circumference and axial direction of the shield machine to obtain a larger detection range.

[0076] In order to reduce the impact of mechanical vibration on the muon detector, a vibration isolation device can be installed in the muon detector, for example, a 1 cm thick rubber pad can be installed at each connection point in the muon detector. In order to further enhance the vibration isolation effect, a vibration isolation pad can be laid at the bottom of the muon detector, and the muon detector can be firmly fixed on the shield machine by welding.

[0077] like Figure 3 As shown, the detection method for shield machine tunnel construction based on cosmic ray muons shown in this exemplary embodiment includes:

[0078] S301. Construct a three-dimensional geological model of the area where the tunnel construction is located based on the geological data of the area where the tunnel construction is located.

[0079] The tunnel construction area includes the tunnel cover after the completion of construction and the unconstructed area. The geological data of the tunnel construction area may include the geological structure, lithological characteristics and groundwater distribution data of the tunnel construction area, which can be collected through geological survey reports, geological profiles, geological structure maps, etc.

[0080] Three-dimensional computer-aided design (CAD) modeling software can be used to construct a three-dimensional geological model of the area where the tunnel is located based on the geological data of the area where the tunnel is located. The three-dimensional geological model should describe in detail the density, thickness and distribution of different rock layers in the area where the tunnel is located to provide a comprehensive geological background.

[0081] S302, simulating the process of muons passing through the three-dimensional geological model to obtain the expected muon attenuation.

[0082] The muon attenuation can be expressed as the transmittance of the muons before and after they pass through an object. The transmittance is the ratio of the muon flux before and after the muon passes through the object. The muon flux refers to the number of muons passing through a certain area per unit time.

[0083] The expected muon attenuation in step S302 refers to the expected attenuation of muons after they pass through the internal structure of the area where the tunnel is under construction. The expected muon attenuation is obtained by simulating the process of muons passing through the three-dimensional geological model of the area where the tunnel is under construction. For example, when the target area detected by the muon detector is the area in the tunnel cover after construction and within the field of view of the muon detector, the expected muon attenuation is obtained by simulating the process of muons passing through the corresponding area in the tunnel cover in the three-dimensional geological model; when the target area detected by the muon detector is the area in the tunnel cover after construction and within the field of view of the muon detector in the unconstructed area, the expected muon attenuation is obtained by simulating the muons passing through the corresponding area in the tunnel cover in the three-dimensional geological model and the corresponding area in the unconstructed area.

[0084] The 3D geological model of the tunnel construction area and the simulated field of view of the muon detector are shown in the figure. Figure 4 shown.

[0085] In the exemplary embodiment of the present application, Figure 5 As shown, step S302 specifically includes:

[0086] S302-1. Generate initial muon data corresponding to the geographical location of the shield machine.

[0087] The Cosmic-ray Shower Generator (CRY) software can be used to generate the initial conditions of muon energy spectrum, angular distribution, and spatial distribution through random processes to simulate the number of muons generated at different latitudes. The simulated data comes from the distribution of muons at different angles in the sky. The software can generate the number of muons generated in different directions according to different latitudes and altitudes. By adjusting the muon generation parameters of the CRY software, the muon flux at the geographical location of the shield machine can be simulated as the initial muon data corresponding to the geographical location of the shield machine.

[0088] S302-2. Use the initial muon data as the first simulated muon flux under open-air conditions.

[0089] The initial muon data generated in step S302 - 1 does not pass through any object, and therefore the initial muon data is used as the first simulated muon flux under open-air conditions.

[0090] The muon number distribution diagram of the first simulated muon flux under open air conditions is shown in Figure 6 shown.

[0091] S302-3, simulating the process of muons in the initial muon data passing through the three-dimensional geological model, and obtaining a second simulated muon flux after the muons pass through the area where the tunnel construction is located.

[0092] Geometry and Tracking (Geant4) software is a simulation tool widely used in particle physics and detector physics, which can accurately simulate the interaction between muons and various substances. Through the powerful simulation function of Geant4 software, it is possible to track the path of muons in different geological media and record their energy loss, scattering angle and penetration probability.

[0093] The Geant4 software can be used to simulate the process of the muons in the initial muon data passing through the three-dimensional geological model of the area where the tunnel construction is located, and obtain the second simulated muon flux after the muons pass through the area where the tunnel construction is located. Specifically, during the simulation, the Geant4 software converts the three-dimensional geological model of the area where the tunnel construction is located into a geometric model, and gives it actual physical properties, such as density, material composition, etc., and then simulates the whole process of the muons in the initial muon data being incident from the top of the geometric model and passing through different rock formations. During the simulation process, the interaction between the muons and the geological medium is recorded in detail, including information such as energy loss, path deviation, and muon decay. The second simulated muon flux is obtained by simulating and statistically analyzing the path of the muons in the initial muon data.

[0094] The second simulated muon flux can be presented in the form of an expected muon population distribution diagram, which shows the number, energy distribution, and angular distribution of muons after passing through the tunnel construction area under different geological conditions.

[0095] The distribution of muons in the second simulated muon flux after the muons passed through the tunnel construction area is shown in the figure below. Figure 7 shown.

[0096] S302-4. Determine an expected muon attenuation based on the first simulated muon flux and the second simulated muon flux.

[0097] The ratio of the first simulated muon flux to the second simulated muon flux can be used as the expected transmittance of muons passing through the tunnel construction area, and the expected transmittance can be used as the expected muon attenuation after the muons attenuate through the tunnel construction area.

[0098] S303, obtaining first measured muon data collected by the muon detector and determining a measured muon attenuation amount according to the first measured muon data.

[0099] The measured muon attenuation in step S303 refers to the measured attenuation after the muon passes through the tunnel construction area. The first measured muon data may be the first measured muon flux after the muon passes through the tunnel construction area.

[0100] The muon number distribution diagram of the first measured muon data is as follows Figure 8 shown.

[0101] In this exemplary embodiment, a muon detector installed on a shield machine can be used to collect a first measured muon flux after muons pass through the tunnel construction area and a second measured muon flux under open air conditions. A data transmission system can be used to transmit the first measured muon flux and the second measured muon flux to a data processing center. In the data processing center, the first measured muon flux and the second measured muon flux can be pre-processed such as noise filtering, straight line discrimination, and data calibration, and then the measured muon attenuation can be calculated.

[0102] The muon detector used in this exemplary embodiment may include a double-layer detection structure, and each layer of the detection structure may include two detection units arranged orthogonally, and the detection unit may be composed of a plastic scintillator strip. The position resolution of each layer of the detection structure may determine the spatial resolution of the imaging, and the position resolution may be determined by the cross-sectional shape and side length of the plastic scintillator strip. The cross-sectional shape of the plastic scintillator strip may be rectangular, and the side length may be L, then the pixel resolution is L, and the position resolution is L / 12. The plastic scintillator strip may be coupled to the photosensitive device through silicone resin. The photosensitive device may convert the light signal generated by the plastic scintillator strip into an analog signal, and the electronic front end of the photosensitive device may be fixed on a polymethyl methacrylate (PMMA) end plate, and the analog signal may be converted into a digital signal after being amplified, identified and formed by a fast response amplifier board, and the digital signal may be transmitted to a data acquisition system. Each detection structure may be equipped with a data acquisition system, and each data acquisition system may collect signals from 200 photosensitive devices. The composite signal of the signals of the photosensitive devices of the two detection units of each layer of the detection structure may be transmitted to a computer through a local area network, and the software may make a trigger decision. The software development of the muon detector can include modules such as data preprocessing and muon flux imaging. Based on the QT system, a visual operating system including data processing, data storage and structural anomaly imaging can be developed to achieve a complete process from data acquisition to real-time visualization. The QT system is an application development framework, mainly used to develop applications with a graphical user interface.

[0103] In this exemplary embodiment, the distance between the two layers of detection structures of the muon detector can be 40 centimeters to optimize the detection viewing angle and improve the spatial resolution.

[0104] In this exemplary embodiment, the track position of the muon can be determined by two independent projections of the muon on the two-layer detection structure of the muon detector.

[0105] In the exemplary embodiment of the present application, Fig. 9 As shown, step S303 specifically includes:

[0106] S303-1. Obtain the second measured muon data of the muon detector under open air conditions.

[0107] In step S303-1, the muon detector may be first placed in an open-air environment at the geographical location of the shield machine, so as to collect second measured muon data under open-air conditions using the muon detector. The second measured muon data may be the second measured muon flux under open-air conditions collected by the muon detector.

[0108] The distribution of muon numbers in the second measured muon data is shown in Fig.10 shown.

[0109] S303-2. According to the parameters of the muon detector, correct the second measured muon data to obtain corrected muon data.

[0110] In step S303-2, the second measured muon data may be corrected by taking into account parameters such as the efficiency and sensitivity of the muon detector, so that the corrected muon data obtained after correction is consistent with the muon flux under open-air conditions at the actual geographical location of the shield machine.

[0111] S303-3. Obtain a correction factor according to the corrected muon data and the first simulated muon flux.

[0112] Although the muon detector has been installed in an open-air environment in step S303-1, tall buildings, such as those with more than dozens of floors, will still cause part of the field of view of the muon detector to be blocked, thereby reducing the muon flux measured by the muon detector and having a significant impact on the collection of the second measured muon data.

[0113] Fig.11 This shows the test results page of the muon detector collecting muon data under open air conditions. Fig.11 It can be seen that there is an obstacle in the upper right corner of the test result. After rotating the muon detector 170°, we get Fig.12 The test results page of the muon detector when collecting muon data under open air conditions is shown. Fig.12 It can be seen that the imaging results of the obstruction also rotated with the rotation of the muon detector. After analysis, it was determined that the obstruction was the tall building next to it.

[0114] In step S303-3, the corrected muon data is compared with the first simulated muon flux under open-air conditions obtained in step S302-2 to obtain a correction factor. The correction factor can represent the deviation between the actually measured muon flux and the theoretical value generated by the simulation, reflecting the impact of external factors, such as high-rise building shading, on the muon data collected by the muon detector.

[0115] S303-4. Use the correction factor to correct the second measured muon data to obtain corrected muon data.

[0116] In step S303-4, the correction factor obtained in step S303-3 may be multiplied by the second measured muon data to obtain corrected muon data, so as to eliminate the influence of the shielding of high-rise buildings or other buildings on the muon detector collecting muons in a specific direction, and obtain more accurate muon data. The corrected muon data can more accurately represent the muon flux under open-air conditions at the geographical location of the shield machine.

[0117] S303-5. Obtain the measured muon attenuation according to the corrected muon data and the first measured muon data.

[0118] In this exemplary embodiment, the first measured muon data may be the first measured muon flux after the muons pass through the tunnel construction area, the second measured muon data may be the second measured muon flux under open-air conditions at the geographical location of the shield machine, and the corrected muon data may be the corrected muon flux obtained after correction of the second measured muon flux.

[0119] In step S303-5, the ratio of the corrected muon data to the first measured muon data, that is, the ratio of the corrected muon flux to the first measured muon flux, can be used as the measured transmittance of the muon passing through the tunnel construction area, and the measured transmittance can be used as the measured muon attenuation after the muon passes through the tunnel construction area and attenuated.

[0120] In the exemplary embodiment of the present application, Fig.13 As shown, the detection method for shield machine tunnel construction based on cosmic ray muons also includes:

[0121] S1301, recording the data collection time when the muon detector collects the first measured muon data.

[0122] As the shield machine excavates the tunnel, the muon detector will collect data multiple times. Each time the muon detector collects data, the corresponding data collection time is recorded.

[0123] S1302. Determine the ring number where the muon detector is located when collecting the first measured muon data according to the data collection time and the operation data of the shield machine; wherein the operation data includes the correspondence between the position of the shield machine and the time.

[0124] The operation data of the shield machine includes the corresponding relationship between the position of the shield machine and time. The position of the shield machine when the first measured muon data was collected can be determined according to the data collection time of the first measured muon data. The muon detector is installed on the shield machine. Determining the position of the shield machine also determines the position of the muon detector when the first measured muon data is collected.

[0125] In tunnel engineering, each ring of a tunnel refers to the number of units assembled in the tunnel segments. The ring number of a tunnel refers to the number of the annular joints of the tunnel segments, which is used to identify the installation order and position of the tunnel segments. The ring number is usually marked on the annular joints of the tunnel segments for ease of construction and maintenance management. The position of the muon detector when the first measured muon data was collected can be used to obtain the ring number of the muon detector when the first measured muon data was collected, so as to accurately correspond the collected first measured muon data to the position of the tunnel construction area, so as to more accurately analyze the internal structure of the tunnel construction area. The dynamic evolution of the internal structure of the tunnel construction area can also be revealed by comparing the cross-ring data.

[0126] S304. Determine internal structure information of the area where the tunnel construction is located based on the measured muon attenuation and the expected muon attenuation.

[0127] In step S304, one-dimensional data analysis may be performed on the measured muon attenuation and the expected muon attenuation to determine the internal structure information of the area where the tunnel construction is located.

[0128] In an exemplary embodiment of the present application, step S304 includes: when the shield machine moves to a ring number, determining a first ratio of the measured muon attenuation and the expected muon attenuation corresponding to the ring number; if the first ratio is greater than a first preset ratio or less than a second preset ratio, determining that there is a density anomaly area within the preset range where the ring number is located.

[0129] Exemplarily, the first preset ratio and the second preset ratio may both be values ​​close to 1, and the first preset ratio is greater than the second preset ratio.

[0130] If the first ratio is less than or equal to the first preset ratio and greater than or equal to the second preset ratio, it means that the first measured muon flux actually measured in the tunnel is consistent with the expected second simulated muon flux, the geological conditions within the preset range of the ring number in the tunnel construction area are consistent with those in the three-dimensional geological model, and there is no density abnormality area; if the first ratio is greater than the first preset ratio, it means that the first measured muon flux actually measured in the tunnel is higher than the expected second simulated muon flux, and there is a soft area with lower density than that in the three-dimensional geological model within the preset range of the ring number in the tunnel construction area; if the first ratio is less than the first preset ratio, it means that the first measured muon flux actually measured in the tunnel is lower than the expected second simulated muon flux, and there is a denser area within the preset range of the ring number in the tunnel construction area than that in the three-dimensional geological model.

[0131] Fig.14 This is an example of a one-dimensional data analysis using the measured and expected muon decays. Fig.14The curve in the figure represents the expected muon decay, and the dots represent the measured muon decay. Fig.14 It can be seen that some points are above the curve, some points coincide with the curve, and some points are below the curve. The measured muon attenuation of the point above the curve is greater than the expected muon attenuation at the corresponding position in the curve. At this time, the first ratio is greater than 1, indicating that there is a soft area with lower density than the three-dimensional geological model at the position corresponding to the point in the tunnel construction area. The measured muon attenuation of the point coincident with the curve is equal to the expected muon attenuation at the corresponding position in the curve. At this time, the first ratio is equal to 1, indicating that the geological conditions at the position corresponding to the point in the tunnel construction area are consistent with those in the three-dimensional geological model. The measured muon attenuation of the point below the curve is less than the expected muon attenuation at the corresponding position in the curve. At this time, the first ratio is less than 1, indicating that there is a denser area than the three-dimensional geological model at the position corresponding to the point in the tunnel construction area.

[0132] It can be understood that when calculating the first ratio of the measured muon attenuation and the expected muon attenuation corresponding to the ring number, the entire muon flux detected by the muon detector can be used for calculation. At this time, the preset range is the entire field of view of the muon detector. The unit muon flux at a preset zenith angle detected by the muon detector can also be used for calculation. At this time, the preset range is the area corresponding to the preset zenith angle within the field of view of the muon detector.

[0133] Through the above one-dimensional data analysis, it is possible to determine whether there are areas of abnormal density in the area where the tunnel construction is located, laying the foundation for further imaging analysis.

[0134] In step S304, after determining that there is an abnormal density area in the tunnel construction area through one-dimensional data analysis, the position and size of the abnormal density area can be determined through two-dimensional imaging analysis.

[0135] In the exemplary embodiment of the present application, Fig.15 As shown, step S304 also includes:

[0136] S304-1. When there are density anomaly areas within the preset range of a continuous preset number of ring numbers, at least each of the continuous preset number of ring numbers is determined as a target ring number; and the unit measured muon attenuation and the unit expected muon attenuation at a plurality of different zenith angles in each target ring number are determined.

[0137] In step S304-1, at least the continuous preset number of ring numbers are determined as target ring numbers, which means that in addition to determining the continuous preset number of ring numbers as target ring numbers, other ring numbers can also be determined as target ring numbers. In this way, during the two-dimensional imaging analysis, not only the position and size of the density anomaly area can be determined, but also the muon two-dimensional imaging map of other ring numbers can be obtained, so that engineers can understand the geological conditions of other ring numbers.

[0138] The continuous preset number of ring numbers may include the ring number where the density anomaly region is located, and the ring numbers that are continuous in front of and continuous behind the ring number and can observe the density anomaly region through the muon detector. For example, the continuous preset number of ring numbers are the ring number where the density anomaly region is located, and the two ring numbers that are continuous in front of and continuous behind the ring number. The front here refers to the excavation direction of the shield machine when performing tunnel construction, and the rear refers to the direction opposite to the front.

[0139] The zenith angle refers to the angle between the incident direction of the light and the zenith direction. Specifically, the zenith angle is the angle between the incident light and the local zenith direction, that is, the angle between the incident light and the ground normal.

[0140] In step S304-1, the measured muon attenuation of the unit at multiple different zenith angles in the target ring number can be obtained by separating and counting the muon fluxes in different directions collected by the muon detector. The expected muon attenuation of the unit at multiple different zenith angles in the target ring number can be calculated by separating and counting the expected muon fluxes simulated using GRY software and Geant4 software. The multiple different zenith angles may include the zenith angles corresponding to all muons collected by the muon detector.

[0141] S304-2, determining a second ratio of the unit measured muon attenuation to the corresponding unit expected muon attenuation at multiple different zenith angles.

[0142] S304-3. Determine the position and size of the density anomaly area according to the second ratios corresponding to a plurality of different zenith angles.

[0143] In the muon two-dimensional imaging map, different second ratios can be displayed in different colors. In this way, the density anomaly area can be accurately identified from the muon two-dimensional imaging map, and then the back projection method can be used to calculate the position and size of the density anomaly area.

[0144] In the exemplary embodiment of the present application, Fig.16 As shown, step S304-3 specifically includes:

[0145] S304-3-1. Generate a muon two-dimensional imaging map corresponding to each target ring number according to the second ratios corresponding to multiple different zenith angles under each target ring number. The muon two-dimensional imaging map is used to characterize the distribution of the second ratios corresponding to each zenith angle under different azimuth angles.

[0146] In step S304-3-1, the second ratios corresponding to multiple different zenith angles under the target ring number are used to generate a muon two-dimensional imaging map corresponding to the target ring number. The muon two-dimensional imaging map is used to characterize the distribution of the second ratios corresponding to each zenith angle under different azimuths. The azimuth is the horizontal angle from the north direction line of a certain point to the target direction line in a clockwise direction, expressed in "degrees" and "mils", and is often used to determine the direction, indicate the target and maintain the direction of travel.

[0147] A third preset ratio and a fourth preset ratio can be set, and both the third preset ratio and the fourth preset ratio can be values ​​close to 1, and the third preset ratio is greater than the fourth preset ratio. In the muon two-dimensional imaging diagram, each second ratio is displayed in different colors according to the relationship between each second ratio and the third preset ratio and the fourth preset ratio. If the second ratio is less than or equal to the third preset ratio and greater than or equal to the fourth preset ratio, it means that the geological conditions within the preset range of the target ring number in the tunnel construction area are consistent with those in the three-dimensional geological model, and there is no abnormal density area, then the second ratio can be displayed in green; if the second ratio is greater than the third preset ratio, it means that there is a soft area with lower density than that in the three-dimensional geological model within the preset range of the target ring number in the tunnel construction area, then the second ratio can be displayed in red; if the second ratio is less than the first preset ratio, it means that there is a denser area than that in the three-dimensional geological model within the preset range of the target ring number in the tunnel construction area, then the second ratio can be displayed in blue.

[0148] Fig.17 An example diagram of a two-dimensional image of a muon is shown. Fig.17 The angle marked on the circle of the muon two-dimensional imaging diagram is the value of the azimuth angle, and multiple circles represent different zenith angles.

[0149] The generation process of the muon 2D image can be optimized, such as high-precision data fitting and interpolation algorithms, to ensure that the boundaries of the density anomaly area are clear and accurate. The muon 2D image shows the density differences in different parts of the tunnel construction area, clearly marking the soft areas or abnormally dense areas that may affect the safety of the tunnel structure. It not only shows the internal heterogeneity of the tunnel construction area, but also provides an important basis for 3D imaging and precise positioning. It is an important reference tool in the tunnel construction process, helping engineers to monitor and evaluate the geological conditions of the tunnel construction area in real time, and to identify and respond to potential risks in a timely manner.

[0150] S304-3-2. Determine the two muon two-dimensional imaging images as the target muon two-dimensional imaging images.

[0151] Two muon two-dimensional imaging images including the same density anomaly region can be determined as target muon two-dimensional imaging images.

[0152] S304-3-3. Determine the target azimuth according to the distribution of the second ratio in the two-dimensional imaging images of the two target muons.

[0153] According to the color distribution of the second ratio in the two target muon two-dimensional imaging images, the density anomaly area can be intuitively identified and the azimuth of the density anomaly area can be determined. After the density anomaly area is identified, the azimuth of the density anomaly area can be determined according to the value of the azimuth marked on the circumference of the target muon two-dimensional imaging image.

[0154] S304-3-4. According to the second ratio corresponding to each zenith angle under the target azimuth, determine the zenith angle of the starting position of the density anomaly area in one of the target muon two-dimensional imaging images as the first zenith angle, determine the zenith angle of the starting position of the density anomaly area in another target muon two-dimensional imaging image as the second zenith angle, and determine the zenith angle of the ending position of the density anomaly area in one of the target muon two-dimensional imaging images as the third zenith angle.

[0155] The first, second, and third zenith angles can be calculated using the following formulas.

[0156]

[0157] in, is the Muon zenith angle, The muon is incident on the two-layer detection structure of the muon detector. The difference in coordinates, The muon is incident on the two-layer detection structure of the muon detector. The difference in coordinates, is the distance between the two layers of detection structure of the muon detector.

[0158] The above formula can be used to calculate the muon zenith angle at the starting position of the density anomaly region in one of the target muon two-dimensional imaging images as the first zenith angle, calculate the muon zenith angle at the ending position of the density anomaly region in the target muon two-dimensional imaging image as the third zenith angle, and calculate the muon zenith angle at the starting position of the density anomaly region in another target muon two-dimensional imaging image as the second zenith angle.

[0159] S304-3-5. Determine the height position and width size of the density anomaly area according to the first zenith angle, the second zenith angle, the third zenith angle and the spacing between the ring numbers corresponding to the two target muon two-dimensional imaging images.

[0160] Fig.18 The relationship between the height position and width size of the density anomaly area and the first zenith angle, the second zenith angle and the third zenith angle is shown.

[0161] Depend on Fig.18 It can be seen that the height position of the density anomaly area can be calculated using the following formula.

[0162]

[0163] in, H is the distance from the right edge of the density anomaly region to the muon detector, that is, the height position of the density anomaly region, It is the first vertex angle. It is the second day's top corner. It is the distance between the two positions of the muon detector when collecting muon data for forming two target muon two-dimensional imaging images, that is, the spacing between the ring numbers corresponding to the two target muon two-dimensional imaging images.

[0164] Depend on Fig.18 It can be seen that the width dimension of the density anomaly area can be calculated using the following formula.

[0165]

[0166] W is the horizontal dimension of the density anomaly area, that is, the width dimension of the density anomaly area. H is the distance from the right edge of the density anomaly region to the muon detector, that is, the height position of the density anomaly region, It is the third celestial horn. It is the first vertex angle.

[0167] Two muon two-dimensional imaging images different from the above two target muon two-dimensional imaging images can be selected from muon two-dimensional imaging images corresponding to multiple target ring numbers to perform the above calculations. The calculations can also be performed at different target azimuth angles to increase the accuracy of the calculation results.

[0168] In the exemplary embodiment of the present application, three-dimensional imaging analysis can also be used to obtain the location and size of the density abnormality area in the area where the tunnel construction is located. Fig.19 As shown, the detection method for shield machine tunnel construction based on cosmic ray muons may also include:

[0169] S1901. Using an algebraic reconstruction technique algorithm, taking an initial density estimate as an initial value, and taking the first measured muon data as target data, performing iterative operations to obtain a reconstruction result, until the error between the reconstruction result and the first measured muon data converges, and obtaining a three-dimensional distribution model of all voxel densities in the area where the tunnel construction is located.

[0170] The Algebraic Reconstruction Technique (ART) algorithm is an iterative algorithm for image reconstruction. Its basic principle is to regard the image data as an unknown image matrix and gradually approximate the real image through an iterative process.

[0171] The ART algorithm was originally designed for conventional computed tomography (CT) reconstruction and Roentgen (X-ray) imaging applications, while muon imaging has the following unique features:

[0172] Muon penetration properties: Muons have relatively strong penetration ability in matter, but as the density of the penetrated matter increases, muons will decay. Therefore, it is usually necessary to deal with the attenuation effect of muon data.

[0173] Data sparsity: Muon imaging data is usually collected at a limited number of measurement points, which is different from the more uniform radiation collection method in X-ray imaging. Therefore, muon data is usually sparse, and different observation directions may be blocked by tunnels or other obstacles.

[0174] Measurement errors: The muon detectors of the muon imaging device have different sensitivities and the detection efficiency at different azimuth angles may be uneven, so the quality of the measurement data may be limited.

[0175] In this exemplary embodiment, in order to apply the ART algorithm to muon imaging, the ART algorithm is adjusted in the following aspects:

[0176] Consider attenuation effects: In traditional ART algorithms, the density of voxels is usually uniform or directly updated at each iteration. But in muon imaging, the attenuation effect needs to be taken into account in the reconstruction process. The density value of each voxel needs to be weighted and adjusted according to the penetration characteristics of the muon. An "attenuation coefficient" model can be introduced to describe the attenuation behavior of muons in different media. For example, an exponential decay model is used to adjust the density value of each voxel to make it more consistent with the attenuation characteristics of the muon.

[0177] Dealing with data sparsity: The sparsity of muon imaging data means that not all spatial voxels can be obtained through direct observation. Therefore, when inputting data, specific optimization strategies are required for the measurement points. For example, a projection reconstruction method is used to adapt to observation data in different directions and at different distances. Weighted averaging or smoothing of sparse data can be introduced into the algorithm to ensure that the algorithm can make full use of existing data while reducing the impact of missing data.

[0178] Muon detector efficiency correction: The difference in sensitivity of the muon detector in different directions will affect the data quality. Therefore, the efficiency of the muon detector needs to be corrected. A directional correction factor can be introduced for each direction of the muon detector, and these correction factors can be adjusted according to the actual measurement results in an iterative process.

[0179] Noise and error processing: Muon data may be affected by noise and muon detector errors, resulting in random errors in the measured data. In this case, regularization terms such as ridge regression can be introduced into the ART algorithm to balance the strictness of data fitting and the tolerance to noise in the reconstruction process, thereby improving the stability and accuracy of the reconstruction results.

[0180] Spatial resolution adjustment: The spatial resolution of muon imaging is different from that of ordinary CT imaging. It is usually coarse and limited by the sensitivity of the muon detector. Therefore, in the ART algorithm, the size of the voxel and the spatial resolution can be adjusted appropriately, or a multi-scale reconstruction method can be introduced to start from a low resolution and gradually optimize until the required accuracy is achieved.

[0181] The initial density estimate is the product of density and length.

[0182] In step S1901, the initial density estimate is used as the initial value, and the first measured muon data collected by the muon detector installed on the shield machine is used as the target data. The initial density estimate and the first measured muon data are input into the adjusted ART algorithm, and the ART algorithm performs iterative operations. In the iterative operation, the density value of each voxel is updated by comparing the difference between the simulated muon data and the first measured muon data, and the iterative process is repeated until the error value between the simulated muon data and the first measured muon data meets the set convergence standard, and finally a three-dimensional distribution model containing the density of all voxels in the tunnel construction area is output.

[0183] Figures 20 to 27 is an example of a slice plot of a 3D distribution model.

[0184] S1902. According to the three-dimensional distribution model, the location and size of the density anomaly area are obtained.

[0185] The three-dimensional distribution model obtained in step S1901 is a visual model that can be viewed from different angles, and can clearly show the internal structure of the tunnel construction area and the location and shape of the density anomaly area. Therefore, according to the three-dimensional distribution model, the location and size of the density anomaly area can be obtained.

[0186] For example, by Figures 20 to 27 The multiple different slices of the three-dimensional distribution model shown can accurately derive the location and size of the density anomaly area.

[0187] Three-dimensional imaging analysis provides more comprehensive geological information, enabling engineers to more accurately understand the size, depth and spatial distribution of density anomaly areas.

[0188] In an exemplary embodiment of the present application, the muon detector can be installed in the middle or rear of the shield machine, the detection surface of the muon detector is parallel to the ground, and the internal structure information is used to characterize the internal structure of the tunnel covering after the construction is completed.

[0189] In an exemplary embodiment of the present application, the muon detector can also be installed at the front of the shield machine, the detection surface of the muon detector is parallel to the ground or inclined toward the unconstructed area of ​​the tunnel, and the internal structure information is used to characterize the internal structure of the tunnel covering after partial construction and the internal structure of the partial unconstructed area.

[0190] In this exemplary embodiment, a three-dimensional geological model of the area where the tunnel construction is located is constructed, and simulation software is used to simulate the process of muons passing through the three-dimensional geological model to obtain the expected muon attenuation. The muon detector is used to collect muon data to obtain the measured muon attenuation, and the time when the muon detector collects data is recorded at the same time. Combined with the operating data of the shield machine, the muon data is accurately corresponded to the position of the area where the tunnel construction is located. According to the expected muon attenuation and the measured muon attenuation, one-dimensional data analysis and two-dimensional imaging analysis can be used to identify the density anomaly area in the area where the tunnel construction is located, and the position and size of the density anomaly area can be calculated. It is also possible to perform three-dimensional imaging analysis based on the initial density estimate and the muon data collected by the muon detector in the tunnel, and intuitively obtain the position and size of the density anomaly area. Help construction personnel to monitor and evaluate the geological conditions of the area where the tunnel construction is located in real time, and identify and respond to potential risks in a timely manner.

[0191] The exemplary embodiment of the present application provides a detection method for shield machine tunnel construction based on cosmic ray muons, which is used to detect the internal geological structure of the tunnel construction area when the shield machine is performing tunnel construction. The shield machine is equipped with a muon detector. Fig.28 As shown, the detection method for shield machine tunnel construction based on cosmic ray muons shown in this exemplary embodiment includes:

[0192] S2801. Construct a three-dimensional geological model of the area where the tunnel construction is located based on the geological data of the area where the tunnel construction is located.

[0193] S2802. Generate initial muon data corresponding to the geographical location of the shield machine.

[0194] S2803. Use the initial muon data as the first simulated muon flux under open air conditions.

[0195] S2804, simulating a process in which muons in the initial muon data pass through the three-dimensional geological model, and obtaining a second simulated muon flux after the muons pass through the area where the tunnel construction is located.

[0196] S2805. Determine an expected muon attenuation based on the first simulated muon flux and the second simulated muon flux.

[0197] S2806. Obtain the first measured muon data collected by the muon detector, record the data collection time when the muon detector collects the first measured muon data, and determine the ring number where the muon detector is located when collecting the first measured muon data based on the data collection time and the operating data of the shield machine; wherein the operating data includes the corresponding relationship between the position of the shield machine and the time.

[0198] S2807. Obtain the second measured muon data of the muon detector under open air conditions.

[0199] S2808. Correct the second measured muon data according to the parameters of the muon detector to obtain corrected muon data.

[0200] S2809. Obtain a correction factor according to the corrected muon data and the first simulated muon flux.

[0201] S2810. Use the correction factor to correct the second measured muon data to obtain corrected muon data.

[0202] S2811. Calculate the measured muon attenuation based on the corrected muon data and the first measured muon data.

[0203] S2812. When the shield machine moves to a ring number, determine a first ratio of the measured muon attenuation and the expected muon attenuation corresponding to the ring number. If the first ratio is greater than a first preset ratio or less than a second preset ratio, determine that there is a density anomaly area within the preset range where the ring number is located.

[0204] S2813. When there are density anomaly areas within the preset range of a continuous preset number of ring numbers, at least each of the continuous preset number of ring numbers is determined as a target ring number; and the unit measured muon attenuation and the unit expected muon attenuation at a plurality of different zenith angles in each target ring number are determined.

[0205] S2814, determining a second ratio of the unit measured muon attenuation to the corresponding unit expected muon attenuation at multiple different zenith angles.

[0206] S2815. Generate a muon two-dimensional imaging map corresponding to each target ring number according to the second ratios corresponding to multiple different zenith angles under each target ring number, wherein the muon two-dimensional imaging map is used to characterize the distribution of the second ratios corresponding to each zenith angle under different azimuth angles.

[0207] S2816. Determine the two muon two-dimensional imaging images as the target muon two-dimensional imaging images.

[0208] S2817. Determine the target azimuth according to the distribution of the second ratio in the two-dimensional imaging images of the two target muons.

[0209] S2818. According to the second ratio corresponding to each zenith angle under the target azimuth angle, determine the zenith angle of the starting position of the density anomaly region in one of the target muon two-dimensional imaging images as the first zenith angle, determine the zenith angle of the starting position of the density anomaly region in another target muon two-dimensional imaging image as the second zenith angle, and determine the zenith angle of the ending position of the density anomaly region in one of the target muon two-dimensional imaging images as the third zenith angle.

[0210] S2819, determining the height position and width size of the density anomaly area according to the first zenith angle, the second zenith angle, the third zenith angle and the spacing between the ring numbers corresponding to the two target muon two-dimensional imaging images.

[0211] In an exemplary embodiment of the present application, the muon detector can be installed in the middle or rear of the shield machine, the detection surface of the muon detector is parallel to the ground, and the internal structure information is used to characterize the internal structure of the tunnel covering after the construction is completed.

[0212] In an exemplary embodiment of the present application, the muon detector can also be installed at the front of the shield machine, the detection surface of the muon detector is parallel to the ground or inclined toward the unconstructed area of ​​the tunnel, and the internal structure information is used to characterize the internal structure of the tunnel covering after partial construction and the internal structure of the partial unconstructed area.

[0213] In this exemplary embodiment, a three-dimensional geological model of the area where the tunnel construction is located is constructed, and simulation software is used to simulate the process of muons passing through the three-dimensional geological model to obtain the expected muon attenuation. The muon detector is used to collect muon data to obtain the measured muon attenuation. At the same time, the time when the muon detector collects data is recorded, and combined with the operation data of the shield machine, the muon data is accurately corresponded to the location of the tunnel construction area. According to the expected muon attenuation and the measured muon attenuation, one-dimensional data analysis and two-dimensional imaging analysis can be used to identify the density anomaly area in the area where the tunnel construction is located, and the location and size of the density anomaly area can be calculated. Help construction personnel to monitor and evaluate the geological conditions of the area where the tunnel construction is located in real time, and identify and respond to potential risks in a timely manner.

[0214] The exemplary embodiment of the present application provides a detection method for shield machine tunnel construction based on cosmic ray muons, which is used to detect the internal geological structure of the tunnel construction area when the shield machine is performing tunnel construction. The shield machine is equipped with a muon detector. Fig.29As shown, the detection method for shield machine tunnel construction based on cosmic ray muons shown in this exemplary embodiment includes:

[0215] S2901. Obtain the first measured muon data collected by the muon detector, record the data collection time when the muon detector collects the first measured muon data, and determine the ring number where the muon detector is located when collecting the first measured muon data based on the data collection time and the operating data of the shield machine; wherein the operating data includes the corresponding relationship between the position and time of the shield machine.

[0216] S2902. Using an algebraic reconstruction technique algorithm, taking an initial density estimate as an initial value, and taking the first measured muon data as target data, performing iterative operations to obtain a reconstruction result, until the error between the reconstruction result and the first measured muon data converges, and obtaining a three-dimensional distribution model of all voxel densities in the area where the tunnel construction is located.

[0217] S2903. According to the three-dimensional distribution model, the location and size of the density anomaly area are obtained.

[0218] In an exemplary embodiment of the present application, the muon detector can be installed in the middle or rear of the shield machine, the detection surface of the muon detector is parallel to the ground, and the internal structure information is used to characterize the internal structure of the tunnel covering after the construction is completed.

[0219] In an exemplary embodiment of the present application, the muon detector can also be installed at the front of the shield machine, the detection surface of the muon detector is parallel to the ground or inclined toward the unconstructed area of ​​the tunnel, and the internal structure information is used to characterize the internal structure of the tunnel covering after partial construction and the internal structure of the partial unconstructed area.

[0220] In this exemplary embodiment, the first measured muon data is collected using a muon detector installed on a shield machine, and the time when the muon detector collects the first measured muon data is recorded, and combined with the operation data of the shield machine, the first measured muon data is accurately corresponded to the position of the tunnel construction area. According to the initial density estimation and the first measured muon data, the ART algorithm is used for iterative calculation to obtain a three-dimensional distribution model containing all voxel densities in the tunnel construction area, so as to help construction personnel monitor and evaluate the geological conditions of the tunnel construction area in real time, intuitively obtain the location and size of the density abnormality area, and timely identify and respond to potential risks.

[0221] Those skilled in the art will appreciate that all or part of the steps in the above method may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk. Alternatively, all or part of the steps in the above embodiment may also be implemented using one or more integrated circuits. The present invention is not limited to any particular form of combination of hardware and software.

[0222] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed in this application. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0223] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A detection method for shield machine tunnel construction based on cosmic ray muons, characterized in that: The invention is used for detecting the internal geological structure of the tunnel construction area when the shield machine is carrying out tunnel construction. The shield machine is equipped with a muon detector. The detection method includes: Constructing a three-dimensional geological model of the area where the tunnel is to be constructed based on the geological data of the area where the tunnel is to be constructed; Simulating a process in which muons pass through the three-dimensional geological model to obtain an expected muon attenuation; Acquire first measured muon data collected by the muon detector and determine a measured muon attenuation amount according to the first measured muon data; Determining internal structure information of the area where the tunnel construction is located based on the measured muon attenuation and the expected muon attenuation; The determining, based on the measured muon attenuation and the expected muon attenuation, the internal structure information of the area where the tunnel construction is located, comprises: When the shield machine moves to a ring number, a first ratio of the measured muon attenuation and the expected muon attenuation corresponding to the ring number is determined, and if the first ratio is greater than a first preset ratio or less than a second preset ratio, it is determined that there is a density anomaly area within the preset range where the ring number is located; The determining, based on the measured muon attenuation and the expected muon attenuation, the internal structure information of the area where the tunnel construction is located, further includes: When there are density anomaly areas within the preset range of a continuous preset number of ring numbers, at least each of the continuous preset number of ring numbers is determined as a target ring number; and the unit measured muon attenuation and the unit expected muon attenuation at a plurality of different zenith angles in each of the target ring numbers are determined; Determine a second ratio of the unit measured muon attenuation to the corresponding unit expected muon attenuation at the plurality of different zenith angles; The position and size of the density anomaly area are determined according to the second ratios corresponding to the multiple different zenith angles.

2. The detection method for shield machine tunnel construction based on cosmic ray muons according to claim 1, characterized in that: The simulating process of muons passing through the three-dimensional geological model to obtain the expected muon attenuation includes: Generating initial muon data corresponding to the geographical location of the shield machine; Using the initial muon data as a first simulated muon flux under open air conditions; Simulating a process in which muons in the initial muon data pass through the three-dimensional geological model to obtain a second simulated muon flux after the muons pass through the tunnel construction area; The expected muon attenuation is determined based on the first simulated muon flux and the second simulated muon flux.

3. The detection method for shield machine tunnel construction based on cosmic ray muons according to claim 1, characterized in that: The detection method further comprises: Recording the data acquisition time of the muon detector acquiring the first measured muon data; The ring number at which the muon detector is located when the first measured muon data is collected is determined according to the data collection time and the operation data of the shield machine; wherein the operation data includes the corresponding relationship between the position and time of the shield machine.

4. The detection method for shield machine tunnel construction based on cosmic ray muons according to claim 2, characterized in that: The step of acquiring first measured muon data collected by the muon detector and determining a measured muon attenuation amount according to the first measured muon data includes: Acquire second measured muon data of the muon detector under open-air conditions; Correcting the second measured muon data according to the parameters of the muon detector to obtain corrected muon data; Obtaining a correction factor according to the corrected muon data and the first simulated muon flux; Correcting the second measured muon data using the correction factor to obtain corrected muon data; The measured muon attenuation is obtained according to the corrected muon data and the first measured muon data.

5. The detection method for shield machine tunnel construction based on cosmic ray muons according to claim 1, characterized in that: Determining the position and size of the density anomaly area according to the second ratios corresponding to the multiple different zenith angles includes: generating a muon two-dimensional imaging map corresponding to each target ring number according to the second ratios corresponding to the multiple different zenith angles under each target ring number, wherein the muon two-dimensional imaging map is used to characterize the distribution of the second ratios corresponding to each zenith angle under different azimuth angles; Determine the two muon two-dimensional imaging images as target muon two-dimensional imaging images; Determining a target azimuth according to a distribution of the second ratio in the two target muon two-dimensional imaging images; According to the second ratio corresponding to each of the zenith angles under the target azimuth angle, determine the zenith angle of the starting position of the density anomaly region in one of the target muon two-dimensional imaging images as the first zenith angle, determine the zenith angle of the starting position of the density anomaly region in another target muon two-dimensional imaging image as the second zenith angle, and determine the zenith angle of the ending position of the density anomaly region in one of the target muon two-dimensional imaging images as the third zenith angle; The height position and width size of the density anomaly area are determined according to the first zenith angle, the second zenith angle, the third zenith angle and the spacing between the ring numbers corresponding to the two target muon two-dimensional imaging images.

6. The detection method for shield machine tunnel construction based on cosmic ray muons according to claim 1, characterized in that: The detection method further comprises: Using an algebraic reconstruction technique algorithm, taking an initial density estimate as an initial value, and taking the first measured muon data as target data, performing an iterative operation to obtain a reconstruction result, until the error between the reconstruction result and the first measured muon data converges, and obtaining a three-dimensional distribution model of all voxel densities in the area where the tunnel construction is located; According to the three-dimensional distribution model, the position and size of the abnormal density area are obtained.

7. The detection method for shield machine tunnel construction based on cosmic ray muons according to any one of claims 1 to 6, characterized in that: The muon detector is installed in the middle or rear of the shield machine, the detection surface of the muon detector is parallel to the ground, and the internal structure information is used to characterize the internal structure of the tunnel covering after the construction is completed.

8. The detection method for shield machine tunnel construction based on cosmic ray muons according to any one of claims 1 to 6, characterized in that: The muon detector is installed at the front of the shield machine, the detection surface of the muon detector is parallel to the ground or inclined toward the unconstructed area of ​​the tunnel, and the internal structure information is used to characterize the internal structure of the tunnel covering after partial construction and the internal structure of the partial unconstructed area.

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