Imaging methods, devices, computer equipment, and storage media for muon rays

Abstract

This invention relates to an imaging method, apparatus, computer device, and storage medium for muon rays. The imaging method includes: determining a three-dimensional structural model of a tunnel boring machine (TBM), the three-dimensional structural model including the structural information and equivalent density information of the TBM; correcting the muon flux data of the tunnel collected by a muon detector based on the three-dimensional structural model of the TBM to obtain corrected muon flux data, thereby eliminating interference caused by the TBM to the muon flux data; the muon detector is installed on the TBM; and the three-dimensional density distribution information of the tunnel is determined based on the corrected muon flux data. When detecting the geological structure of a tunnel based on muon imaging, the problem of detection distortion of the geological structure caused by the TBM can be eliminated.

Description

Technical Field

[0001] This invention relates to the field of geological exploration technology, specifically to an imaging method, apparatus, computer equipment, and storage medium for muon rays. Background Technology

[0002] During tunnel construction, the geological conditions in front of the tunnel boring machine (TBM) face have a significant impact on construction safety, tunneling efficiency, and engineering risks. Therefore, accurately detecting the geological structure in front of the TBM is a crucial issue in the field of geological surveying.

[0003] In related technologies, muon detectors are often used to collect muon ray information from the area to be detected, and the geological structure conditions of the area to be detected are imaged and displayed based on the muon ray information.

[0004] However, in related technologies, tunnel boring machines affect the absorption and scattering of muons, which seriously affects the muon imaging results and leads to distortion in the detection of geological structures. Summary of the Invention

[0005] To overcome the problems existing in related technologies, the present invention provides an imaging method, apparatus, computer equipment, and storage medium for muon rays.

[0006] According to a first aspect of the present invention, an imaging method for muon rays is provided, the imaging method comprising: A three-dimensional structural model of the tunnel boring machine is determined, wherein the three-dimensional structural model includes the structural information and equivalent density information of the tunnel boring machine; The muon flux data of the tunnel collected by the muon detector is corrected according to the three-dimensional structural model of the tunnel boring machine to obtain corrected muon flux data, so as to eliminate the interference of the tunnel boring machine on the muon flux data; the muon detector is installed on the tunnel boring machine. Based on the corrected muon flux data, the three-dimensional density distribution information of the tunnel is determined.

[0007] In some embodiments, the step of correcting the muon flux data of the tunnel collected by the muon detector based on the three-dimensional structural model of the tunnel boring machine to obtain corrected muon flux data includes: The energy attenuation and flux change of muon rays during their passage through the tunnel boring machine are determined based on the three-dimensional structural model of the tunnel boring machine. The muon flux data collected by the muon detector in the tunnel are corrected based on the energy attenuation and the flux change.

[0008] In some embodiments, determining the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine based on the three-dimensional structural model of the tunnel boring machine includes: The three-dimensional structural model of the tunnel boring machine is added as an independent medium layer to the muon ray imaging path model to calculate the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine.

[0009] In some embodiments, before determining the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine based on the three-dimensional structural model of the tunnel boring machine, the imaging method further includes: Based on the three-dimensional structural model of the tunnel boring machine and the geometric information of the tunnel, the area that can be penetrated by muons is determined; The muon ray imaging path model is determined based on the muon flux data corresponding to the muon-penetrable region.

[0010] In some embodiments, the imaging method further includes: Based on the three-dimensional density distribution information of the tunnel, the geological structure information of the tunnel is determined.

[0011] In some embodiments, the imaging method further includes: Based on the three-dimensional density distribution information of the tunnel, the reliability of the geological structure information of the tunnel is determined; The three-dimensional structural model of the tunnel is determined based on the credibility and the geological structure information of the tunnel.

[0012] In some embodiments, determining the three-dimensional structural model of the tunnel based on the confidence level and the geological structure information of the tunnel includes: When the credibility meets the set credibility conditions, the three-dimensional structural model of the tunnel is determined based on the current geological structure information of the tunnel; When the credibility does not meet the set credibility conditions, the three-dimensional structural model of the tunnel is determined based on the updated geological structure information of the tunnel.

[0013] According to a second aspect of the present invention, a muon imaging apparatus is provided, the imaging apparatus comprising: The first determining module is configured to determine the three-dimensional structural model of the tunnel boring machine, the three-dimensional structural model including the structural information and equivalent density information of the tunnel boring machine; The calibration model is configured to calibrate the muon flux data of the tunnel collected by the muon detector based on the three-dimensional structural model of the tunnel boring machine, so as to obtain calibrated muon flux data and eliminate the interference caused by the tunnel boring machine to the muon flux data; the muon detector is installed on the tunnel boring machine; The second determining module is configured to determine the three-dimensional density distribution information of the tunnel based on the corrected muon flux data.

[0014] According to a third aspect of the present invention, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the muon ray imaging method as described in the first aspect.

[0015] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the muon ray imaging method as described in the first aspect.

[0016] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: Due to the complex structure and high density of tunnel boring machines (TBMs), their cutterhead, main drive system, and metal components absorb and scatter muon rays. Therefore, by correcting the muon flux data collected by the muon detectors mounted on the TBM using a three-dimensional structural model that includes the TBM's structural information and equivalent density information, the influence of the TBM's structure and density on muon rays can be eliminated, thus eliminating the interference of the TBM on muon flux data at its source. Based on the corrected muon flux data, more accurate three-dimensional density distribution information of the tunnel can be obtained. Thus, when using muon imaging to detect the geological structure of the tunnel, the distortion in geological structure detection caused by the TBM can be eliminated.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] Figure 1 This is a schematic flowchart illustrating an imaging method for muon rays according to a first exemplary embodiment; Figure 2 This is a schematic flowchart illustrating an imaging method for muon rays according to a second exemplary embodiment; Figure 3 This is a schematic flowchart illustrating an imaging method for muon rays according to a third exemplary embodiment; Figure 4 This is a schematic flowchart illustrating an imaging method for muon rays according to a fourth exemplary embodiment; Figure 5This is a schematic diagram of a muon ray imaging method according to an exemplary embodiment; Figure 6 This is a block diagram of a computer device according to an exemplary embodiment.

[0020] In the picture: 100 - Computer equipment; 101 - Computing unit; 102 - ROM; 103 - RAM; 104 - Bus; 105 - Input / output interface; 106 - Input unit; 107 - Output unit; 108 - Storage unit; 109 - Communication unit. Detailed Implementation

[0021] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings.

[0022] When the following description relates to the accompanying 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. Rather, they are merely examples of methods consistent with some aspects of the invention as detailed in the appended claims. It should also be understood that the term "and / or" as used in this invention refers to any or all possible combinations comprising one or more of the associated listed items.

[0023] During tunnel construction, the geological conditions in front of the tunnel boring machine (TBM) face have a significant impact on construction safety, tunneling efficiency, and engineering risks. Therefore, accurately detecting the geological structure in front of the TBM is a crucial issue in the field of geological surveying.

[0024] In related technologies, muon detectors are often used to collect muon ray information from the area to be detected, and the geological structure conditions of the area to be detected are imaged and displayed based on the muon ray information.

[0025] However, in related technologies, tunnel boring machines affect the absorption and scattering of muons, which seriously affects the muon imaging results and leads to distortion in the detection of geological structures.

[0026] Therefore, due to the complex and high-density structure of tunnel boring machines (TBMs), their cutterhead, main drive system, and metal components absorb and scatter muon rays. Thus, by correcting the muon flux data collected by the muon detectors mounted on the TBM using a three-dimensional structural model that includes the TBM's structural and equivalent density information, the influence of the TBM's structure and density on muon rays can be eliminated, thereby eliminating the interference of the TBM on muon flux data at its source. Based on the corrected muon flux data, more accurate three-dimensional density distribution information of the tunnel can be obtained. This eliminates the problem of geological structure detection distortion caused by the TBM.

[0027] Embodiments of the present invention provide an imaging method for muon rays, such as... Figure 1 As shown, the imaging methods include: S110. Determine the three-dimensional structural model of the tunnel boring machine (TBM). The three-dimensional structural model includes the structural information and equivalent density information of the TBM.

[0028] The structural information of the tunnel boring machine in step S110 above includes at least one of the following: structural type, structural spatial location, and structural dimensions. The structural type includes at least one of the following: cutterhead, main drive system, shield shell, and trolley frame. The equivalent density information corresponds one-to-one with the structural type; for example, when the cutterhead material is alloy steel, the corresponding equivalent density is 7850 kg / m³. 3 When the shield material is steel, the corresponding equivalent density is 7850 kg / m³. 3 The equivalent density corresponding to the main drive system is 6800 kg / m³. 3 The equivalent density corresponding to the trolley frame is 5200 kg / m³. 3 The three-dimensional structural model of the tunnel boring machine (TBM) can be obtained by fusing the TBM's factory-designed computer-aided design (CAD) model with the TBM's three-dimensional laser scanning point cloud model. Its voxel size is 0.2m × 0.2m × 0.2m.

[0029] S120. Based on the three-dimensional structural model of the tunnel boring machine, the muon flux data collected by the muon detector is corrected to obtain corrected muon flux data, so as to eliminate the interference caused by the tunnel boring machine to the muon flux data; the muon detector is installed on the tunnel boring machine.

[0030] The muon detector in step S120 is installed on the tunnel boring machine (TBM), which includes: the muon detector is installed inside the matching trolley or the TBM body, and the muon detector faces the direction of the TBM's advance, for collecting muon flux data from the tunnel ahead of the TBM's advance direction.

[0031] The muon detector can be a plastic scintillator detector with an effective detection area of ​​0.5m × 0.5m. Two muon detectors can be installed, symmetrically positioned left and right behind the cutterhead inside the tunnel boring machine (TBM). For example, if the tunnel slab bottom height is 9m. The muon detectors are oriented towards the direction of TBM advancement, meaning they face the tunnel face at a pitch angle of +45°, covering a detection area of ​​0-30m diagonally above the tunnel face. Every time the TBM advances a preset distance, the muon detectors collect a set of muon flux data for the tunnel ahead in the direction of TBM advancement.

[0032] S130. Based on the corrected muon flux data, determine the three-dimensional density distribution information of the tunnel.

[0033] The three-dimensional density distribution information of the tunnel in step S130 above includes the density value and spatial location information of each voxel after the geological structure of the tunnel in front of the tunnel boring machine's advance direction is discretized in three-dimensional space.

[0034] The muon ray imaging method provided by the embodiments of the present invention can include the following beneficial effects: Due to the complex structure and high density of the tunnel boring machine (TBM), its cutterhead, main drive system, and metal components absorb and scatter muon rays. Therefore, by correcting the muon flux data collected by the muon detector installed on the TBM based on a three-dimensional structural model of the TBM, including its structural information and equivalent density information, the influence of the TBM's structure and density on muon rays can be eliminated, thereby eliminating the interference of the TBM on the muon flux data at the source. Based on the corrected muon flux data, more accurate three-dimensional density distribution information of the tunnel can be obtained. Thus, when detecting the geological structure of the tunnel based on muon imaging, the problem of detection distortion of the geological structure caused by the TBM can be eliminated.

[0035] In one embodiment, such as Figure 2 As shown, step S120 above, which involves correcting the muon flux data collected by the muon detector based on the three-dimensional structural model of the tunnel boring machine to obtain corrected muon flux data, includes: S210. Determine the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine based on the three-dimensional structural model of the tunnel boring machine.

[0036] S220. Based on energy attenuation and flux changes, the muon flux data of the tunnel collected by the muon detector is corrected.

[0037] In this embodiment, the structure of the tunnel boring machine with different densities produces different energy attenuation and flux changes in muon rays. By using quantitative indicators such as energy attenuation and flux changes to correct the muon flux data, the accuracy of the correction is improved.

[0038] In one embodiment, the step S210 above, which involves determining the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine based on the three-dimensional structural model of the tunnel boring machine, includes: The three-dimensional structural model of the tunnel boring machine was added as an independent medium layer to the muon ray imaging path model to calculate the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine.

[0039] In this embodiment, the three-dimensional structural model of the tunnel boring machine is introduced as an independent medium layer into the imaging path model of muon rays, so that each segment of the medium in the muon propagation path is accurately modeled, providing an accurate physical model basis for subsequent correction, thereby improving the imaging accuracy.

[0040] For example, the step S220 above, which corrects the muon flux data of the tunnel collected by the muon detector based on energy attenuation and flux change, includes: Calculate muon transmittance using the following formula: T = exp( Σ × ρ × L ); Where T is the muon transmittance, used to characterize energy attenuation and flux change; Σ is the muon mass attenuation coefficient; L is the path length of the muon ray through the tunnel boring machine; and ρ is the equivalent density of the tunnel boring machine, ρ = 7850 kg / m³.

[0041] Divide the muon flux data by the muon transmittance to obtain the corrected muon flux data.

[0042] Taking the passage of muon rays through the cutterhead of a tunnel boring machine (TBM) as an example, Σ = 0.00018 m² / kg, the path length of the muon rays through the cutterhead is L = 0.45 m, the equivalent density of the cutterhead is ρ = 7850 kg / m³, and T = exp( Σ × ρ × L) = 0.531. The measured muon flux data is 120 muons / minute. Dividing the muon flux data of 120 muons / minute by the muon transmittance of 0.531, we get the corrected muon flux data of 226 muons / minute.

[0043] In this embodiment, by correcting the muon flux data, the absorption and scattering interference of the tunnel boring machine metal on muons can be eliminated.

[0044] In one embodiment, such as Figure 3 As shown, before determining the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine based on the three-dimensional structural model of the tunnel boring machine in step S210 above, the imaging method further includes: S310. Based on the three-dimensional structural model of the tunnel boring machine and the geometric information of the tunnel, determine the area that can be penetrated by muons.

[0045] S320. Determine the muon ray imaging path model based on the muon flux data corresponding to the muon-penetrable region.

[0046] In this embodiment, the areas that can be penetrated by muons are determined in advance based on the three-dimensional structural model of the tunnel boring machine and the geometric information of the tunnel. Only the muon flux data corresponding to the areas that can be penetrated by muons are used in the muon imaging path model. The muon flux data corresponding to the undetectable areas blocked by the shield structure and surrounding rock are eliminated, which improves the imaging quality and reduces the computational complexity.

[0047] For example, the step S310 above, which determines the area that can be penetrated by muons based on the three-dimensional structural model of the tunnel boring machine and the geometric information of the tunnel, includes: Based on the three-dimensional structural model of the tunnel boring machine and the geometric information of the tunnel, a three-dimensional muon visible domain model is constructed. Visibility is determined for all spatial voxels in the 3D muon visibility field model to identify regions that can be penetrated by muons and regions that cannot be detected.

[0048] In this embodiment, by constructing a three-dimensional muon visibility domain model, visibility is determined for each voxel. The geometric path is used to determine whether the muon can effectively penetrate the tunnel boring machine structure to reach the spatial voxel. This clearly divides the spatial voxel into areas that can be penetrated by muons and areas that cannot be detected (areas completely blocked by the tunnel boring machine structure or surrounding rock). In the subsequent determination of the muon ray imaging path model and three-dimensional density distribution information, imaging relationships are established only for spatial voxels within the areas that can be penetrated by muons. This eliminates invalid data interference caused by undetectable areas, improves imaging quality, and reduces computational complexity.

[0049] For example, determining the three-dimensional density distribution information of the tunnel based on the corrected muon flux data in step S130 above includes: Based on the corrected muon flux data, a muon ray imaging path-space voxel projection matrix is ​​constructed. Using regularized inversion or compressed sensing inversion methods, the corrected muon flux data and the muon ray imaging path-space voxel projection matrix are taken as inputs. The three-dimensional density of metal in each space voxel is inverted to solve for the density value of each space voxel, thereby obtaining the three-dimensional density distribution information of the tunnel.

[0050] For example, the regularized inversion method can be the Algebraic Reconstruction Technique (ART) iterative regularized inversion algorithm, in which the size of the spatial voxel is 0.3m×0.3m×0.3m, the number of iterations is 200, and the relaxation factor is 0.05.

[0051] In this embodiment, the three-dimensional density distribution information of the tunnel is constructed based on the corrected muon flux data, thereby realizing the accurate reconstruction of the three-dimensional density distribution information of the geological structure in front of the tunnel boring machine's advance direction.

[0052] In one embodiment, the imaging method further includes: Based on the three-dimensional density distribution information of the tunnel, the geological structure information of the tunnel is determined.

[0053] In this embodiment, by further processing the three-dimensional density distribution information of the tunnel, it is converted into geological structure information of the tunnel that can be directly understood by construction personnel. This is beneficial for applying the muon imaging results to geological exploration and risk warning in shield tunneling.

[0054] For example, the types of geological structure information include at least one of the following: intact hard rock, geological boundary, fault fracture zone, weak interlayer, and cavity.

[0055] The above steps, which determine the geological structure information of the tunnel based on its three-dimensional density distribution information, include: Based on the three-dimensional density distribution information of the tunnel, the density gradient, directional change rate, and spatial continuity of each region are calculated. Based on density gradient, directional change rate, and spatial continuity, the types of geological structural information can be identified as intact hard rock, geological boundaries, fault fracture zones, weak interlayers, or cavities.

[0056] For example, density gradient, directional change rate, and spatial continuity can be characterized by density ranges. When the density range is [2600 kg / m³, 2800 kg / m³], the type of geological structure information is identified as intact hard rock. When the density range is [2000 kg / m³, 2300 kg / m³], the type of geological structure information is identified as fault fracture zone. When the density range is [1200 kg / m³, 1800 kg / m³], the type of geological structure information is identified as weak interlayer or cavity.

[0057] In this embodiment, the three-dimensional density distribution information is transformed into complete hard rock, geological boundaries, fault fracture zones, or weak interlayers that construction personnel can directly understand through density gradient, directional change rate, and spatial continuity, providing clear geological risk warning information for construction personnel.

[0058] In one embodiment, such as Figure 4 As shown, the imaging method also includes: S410. Based on the three-dimensional density distribution information of the tunnel, determine the reliability of the tunnel's geological structure information.

[0059] S420. Determine the three-dimensional structural model of the tunnel based on the reliability and geological structure information of the tunnel.

[0060] In this embodiment, the credibility determined based on the three-dimensional density distribution information of the tunnel is introduced, so that the results of muon imaging (i.e., geological structure information) have a clear basis for quality evaluation. The three-dimensional structure model of the tunnel based on the geological structure information and its credibility can more realistically represent the real geological structure conditions of the tunnel and improve the reliability of the imaging structure.

[0061] In one embodiment, the step S420 above, which involves determining the three-dimensional structural model of the tunnel based on the confidence level and the tunnel's geological structure information, includes: When the credibility meets the set credibility conditions, the three-dimensional structural model of the tunnel is determined based on the current geological structure information of the tunnel.

[0062] When the credibility does not meet the set credibility conditions, the three-dimensional structural model of the tunnel is determined based on the updated geological structure information of the tunnel.

[0063] In this embodiment, by determining whether the credibility meets the set credibility conditions, a three-dimensional structural model is directly generated when the credibility meets the set credibility conditions, and the geological structural information is automatically updated and iterated when the credibility does not meet the set credibility conditions. The updated geological structural information is used to determine the three-dimensional structural model, thus ensuring the reliability of the three-dimensional structural model.

[0064] For example, confidence includes at least one of the following: muon imaging path coverage, density gradient magnitude, and inversion residual stability.

[0065] The credibility meets the set credibility conditions, including at least one of the following: the muon imaging path coverage is greater than or equal to the coverage threshold, the density gradient magnitude is greater than or equal to the magnitude threshold, and the inversion residual stability is greater than or equal to the stability threshold.

[0066] In this embodiment, the coverage of the muon imaging path can reflect the sufficiency of sampling by the muon detector. The higher the coverage, the better the current geological structure information can characterize the true geological structure of the tunnel. The density gradient amplitude can reflect the clarity of the geological boundary. The higher the density gradient amplitude, the better the current geological structure information can characterize the true geological structure of the tunnel. The stability of the inversion residual reflects the stability of the three-dimensional density distribution information construction process. The better the stability of the inversion residual, the better the current geological structure information can characterize the true geological structure of the tunnel.

[0067] For example, the imaging method further includes: The tunnel boring machine's advance position, attitude angle, and construction parameters can be obtained in real time.

[0068] Based on the tunnel boring machine's advancing position, attitude angle, and construction parameters, the tunnel's penetrable area, three-dimensional density distribution information, geological structure information, and three-dimensional structural model are updated in real time.

[0069] Geological structure information obtained at different times is correlated according to time series to form a geological structure information distribution sequence.

[0070] In this embodiment, during the construction process, the tunnel boring machine's advancing position, attitude angle, and construction parameters are updated in real time. Based on this, the tunnel's penetrable area and geological structure information are updated in real time, which can ensure continuous and dynamic geological exploration capabilities for tunnel boring construction and avoid lag in geological structure information.

[0071] Embodiments of the present invention provide an imaging device for muon rays, such as... Figure 5As shown, the imaging device includes: a first determining module 501, a correction model 502, and a second determining module 503.

[0072] The first determining module 501 is configured to determine the three-dimensional structural model of the tunnel boring machine, which includes the structural information and equivalent density information of the tunnel boring machine.

[0073] Correction model 502 is configured to correct the muon flux data collected by the muon detector based on the three-dimensional structural model of the tunnel boring machine (TBM), obtaining corrected muon flux data to eliminate interference caused by the TBM on the muon flux data. The muon detector is installed on the TBM. The second determining module 503 is configured to determine the three-dimensional density distribution information of the tunnel based on the corrected muon flux data.

[0074] The imaging apparatus for muon rays provided in the embodiments of the present invention may include the following beneficial effects: Due to the complex structure and high density of tunnel boring machines (TBMs), their cutterhead, main drive system, and metal components absorb and scatter muon rays. Therefore, by correcting the muon flux data collected by the muon detectors mounted on the TBM using a three-dimensional structural model that includes the TBM's structural information and equivalent density information, the influence of the TBM's structure and density on muon rays can be eliminated, thus eliminating the interference of the TBM on muon flux data at its source. Based on the corrected muon flux data, more accurate three-dimensional density distribution information of the tunnel can be obtained. Thus, when using muon imaging to detect the geological structure of the tunnel, the distortion in geological structure detection caused by the TBM can be eliminated.

[0075] In one exemplary embodiment, a computer device is provided, including a processor and a memory, the memory storing a computer program, the processor executing the computer program to implement the steps of any of the above-described muon ray imaging methods.

[0076] In one exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of any of the above-described muon ray imaging methods. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, magnetic tape, a floppy disk, or an optical data storage device, etc.

[0077] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of any of the above-described muon ray imaging methods.

[0078] refer to Figure 6The following is a structural block diagram of a computer device that can be used as a reference for the present invention. The computer device 100 includes a computing unit 101, which can perform various appropriate actions and processes according to a computer program stored in a ROM 102 or a computer program loaded into a RAM 103 from a storage unit 108. The RAM 103 may also store various programs and data required for the operation of the computer device 100. The computing unit 101, ROM 102, and RAM 103 are interconnected via a bus 104. An input / output (I / O) interface 105 is also connected to the bus 104.

[0079] Multiple components in computer device 100 are connected to I / O interface 105, including: input unit 106, output unit 107, storage unit 108, and communication unit 109. Input unit 106 can be any type of device capable of inputting information into computer device 100. Input unit 106 can receive input numerical or character information and generate key signal inputs related to user settings and / or function control of computer device 100, and may include, but is not limited to, a mouse, keyboard, touchscreen, trackpad, trackball, joystick, microphone, and / or remote control. Output unit 107 can be any type of device capable of presenting information, and may include, but is not limited to, a monitor, speaker, video / audio output terminal, vibrator, and / or printer. Storage unit 108 may include, but is not limited to, a hard disk and an optical disk. Communication unit 109 allows computer device 100 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers, and / or chipsets, such as Bluetooth™ devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0080] The computing unit 101 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 101 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 101 performs the various methods and processes described above, such as the muon ray imaging method. For example, in some embodiments, the muon ray imaging method can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 108. In some embodiments, part or all of the computer program can be loaded and / or installed on the computer device 100 via ROM 102 and / or communication unit 109. When the computer program is loaded into RAM 103 and executed by the computing unit 101, one or more steps of the muon ray imaging method described above can be performed. Alternatively, in other embodiments, the computing unit 101 can be configured to perform the muon ray imaging method by any other suitable means (e.g., by means of firmware).

[0081] The computer device 100 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described muon ray imaging method.

[0082] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered illustrative only, and the true scope and spirit of the invention are indicated by the claims.

[0083] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. An imaging method for muon rays, characterized in that, The imaging method includes: A three-dimensional structural model of the tunnel boring machine is determined, wherein the three-dimensional structural model includes the structural information and equivalent density information of the tunnel boring machine; The muon flux data of the tunnel collected by the muon detector is corrected according to the three-dimensional structural model of the tunnel boring machine to obtain corrected muon flux data, so as to eliminate the interference of the tunnel boring machine on the muon flux data; the muon detector is installed on the tunnel boring machine. Based on the corrected muon flux data, the three-dimensional density distribution information of the tunnel is determined.

2. The imaging method according to claim 1, characterized in that, The step of correcting the muon flux data of the tunnel collected by the muon detector based on the three-dimensional structural model of the tunnel boring machine to obtain corrected muon flux data includes: The energy attenuation and flux change of muon rays during their passage through the tunnel boring machine are determined based on the three-dimensional structural model of the tunnel boring machine. The muon flux data collected by the muon detector in the tunnel are corrected based on the energy attenuation and the flux change.

3. The imaging method according to claim 2, characterized in that, The determination of the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine based on the three-dimensional structural model of the tunnel boring machine includes: The three-dimensional structural model of the tunnel boring machine is added as an independent medium layer to the muon ray imaging path model to calculate the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine.

4. The imaging method according to claim 2, characterized in that, Before determining the energy attenuation and flux change of muon rays during their passage through the tunnel boring machine based on the three-dimensional structural model of the tunnel boring machine, the imaging method further includes: Based on the three-dimensional structural model of the tunnel boring machine and the geometric information of the tunnel, the area that can be penetrated by muons is determined; The muon ray imaging path model is determined based on the muon flux data corresponding to the muon-penetrable region.

5. The imaging method according to claim 1, characterized in that, The imaging method further includes: Based on the three-dimensional density distribution information of the tunnel, the geological structure information of the tunnel is determined.

6. The imaging method according to claim 5, characterized in that, The imaging method further includes: Based on the three-dimensional density distribution information of the tunnel, the reliability of the geological structure information of the tunnel is determined; The three-dimensional structural model of the tunnel is determined based on the credibility and the geological structure information of the tunnel.

7. The imaging method according to claim 6, characterized in that, The process of determining the three-dimensional structural model of the tunnel based on the credibility and the geological structure information of the tunnel includes: When the credibility meets the set credibility conditions, the three-dimensional structural model of the tunnel is determined based on the current geological structure information of the tunnel; When the credibility does not meet the set credibility conditions, the three-dimensional structural model of the tunnel is determined based on the updated geological structure information of the tunnel.

8. A muon imaging device, characterized in that, The imaging device includes: The first determining module is configured to determine the three-dimensional structural model of the tunnel boring machine, the three-dimensional structural model including the structural information and equivalent density information of the tunnel boring machine; The calibration model is configured to calibrate the muon flux data of the tunnel collected by the muon detector based on the three-dimensional structural model of the tunnel boring machine, so as to obtain calibrated muon flux data and eliminate the interference caused by the tunnel boring machine to the muon flux data; the muon detector is installed on the tunnel boring machine. The second determining module is configured to determine the three-dimensional density distribution information of the tunnel based on the corrected muon flux data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the imaging method for muon rays as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the imaging method for muon rays as described in any one of claims 1 to 7.

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