Imaging method and system based on cosmic ray muon transmission

Abstract

The invention discloses an imaging method and system based on cosmic ray muon transmission, which are applied to a control mechanism, and the control mechanism is electrically connected with at least one detection module. The imaging method based on cosmic ray muon transmission comprises the steps that the response state of at least one detection module is obtained, the detection module comprises a plurality of sensor units, and the sensor units are arranged in a string shape. And preprocessing the response state to obtain muon flux in unit area, unit time and unit solid angle. Based on the topographic data, the landform data and the muon flux, the density distribution in the muon ray irradiation range is reversely deduced through a preset algorithm. And performing visual imaging based on a density distribution result. According to the method, the working efficiency of muon geological imaging is improved, the system complexity is reduced, the adaptability in a narrow working environment is remarkably enhanced, and an efficient and convenient solution is provided for the fields of geological exploration, engineering detection and the like.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of geological exploration and imaging technology, and in particular to an imaging method and system based on cosmic ray muon transmission. Background Art

[0002] There are three main sensors commonly used for cosmic ray muon detection: nuclear emulsion, gas and plastic scintillator. Among them, plastic scintillator is easy to use, low-cost, light and flexible, and is more suitable for imaging detection of large objects in the field.

[0003] The commonly used method for field observation of muons is to place a detector that can sense muon bombardment events at the observation point. The detector consists of two parallel plates, each of which is composed of overlapping XY strip plastic scintillator pixel arrays. When a muon particle is incident and bombards a plate, the corresponding X and Y strip scintillators of the plate are lit, and the photons are captured by the photomultiplier tube and converted into electrical signals. The signal of the arrival of the muon is then identified by the circuit, from which the specific position of the muon bombardment on the plate can be known; the bombardment position of the second plate can be obtained by the same operation; the position on the two plates can determine the incident direction and angle of the particle. By placing the detector in a fixed position for a period of time, the number and flux of muons arriving at the detector in each ray direction within its visible range can be counted. For a fixed plate area and a fixed spacing, the range of ray angles of the common bombardment event that can be observed is limited. In actual work, the pitch angle and orientation of the plate can be adjusted as needed to achieve coverage of all zenith angles and azimuth angles.

[0004] In addition to taking photos at a fixed point, the muon detector can also be aimed at the detection target from different positions and directions, and then use the cross-rays of multiple points to perform tomography (similar to medical CT). For example, the muon detector can be placed around the mountain at the foot of the mountain, or observe directly upward at a series of measuring points in an underground tunnel.

[0005] When muons travel through an object, they interact with the medium and lose energy. The total energy lost by a muon before it disappears in the medium is proportional to the length of its path and the density distribution along the path. Through high-precision topographic and geomorphological measurements, the path length of each muon ray can be accurately obtained under the condition that the detector position is known. In this way, the information on the number of muons in different ray directions can be used to infer the density distribution within the range of the muon ray irradiation, thereby realizing internal density structure imaging.

[0006] However, existing muon detectors and imaging methods have the following obvious disadvantages:

[0007] 1. The equipment is complex, large, and bulky: In order to obtain more accurate azimuth information, traditional detectors need to set up a large number of XY plastic scintillators on the front and rear detector plates to form a large number of observable ray directions. The more XY strips are divided, the higher the spatial resolution, which can usually reach 64x64. In order to ensure a certain particle bombardment cross-sectional area, the X and Y strips need to have a certain width. In order to improve the accuracy of orientation, there needs to be enough spacing between the front and rear detector plates. As a result, the size, volume, and weight of the muon detector are very large, which is not convenient for field deployment, and it is also difficult to use in small spaces such as underground, tunnels, and monuments. At the same time, a multi-channel high-speed acquisition card or multiple high-speed acquisition cards are required to independently collect signals from each plastic scintillator, which is expensive, power-hungry, and inconvenient to repair and maintain.

[0008] 2. Low efficiency: The incidence, travel and detection of muons are somewhat random, so in order to obtain statistically reliable muon data, it is necessary to accumulate enough muon events over a long period of time. The number of muons detected per unit time is related to the distance between the front and rear detector plates. The larger the distance, the smaller the solid angle and the higher the ray resolution, but the longer it takes to accumulate enough particles. Traditionally, whether it is photographic imaging at a single point (similar to X-ray examination photos) or tomographic imaging of multi-point observations (similar to medical CT examinations), what is pursued is high resolution, and the images given are composed of many pixels (or voxels). It usually takes several days, months or even a year to obtain such an image. Summary of the invention

[0009] The embodiment of the present invention provides an imaging method and system based on cosmic ray muon transmission, which not only improves the working efficiency of muon geological imaging and reduces the system complexity, but also significantly enhances the adaptability in a small working environment, providing an efficient and convenient solution for the fields of geological exploration, engineering detection, etc.

[0010] To achieve the above-mentioned object, in a first aspect, the present invention provides an imaging method based on cosmic ray muon transmission, which is applied to a control mechanism, wherein the control mechanism is electrically connected to at least one detection module, and the imaging method based on cosmic ray muon transmission comprises:

[0011] Acquiring a response state of the at least one detection module, wherein the detection module comprises a plurality of sensor units, and the plurality of sensor units are arranged in a series;

[0012] Preprocessing the response state to obtain the muon flux per unit area, per unit time, and per unit solid angle;

[0013] Based on the terrain data, the topographic data and the muon flux, the density distribution within the irradiation range of the muon rays is inferred through a preset algorithm;

[0014] Based on the density distribution results, visualization imaging is performed.

[0015] In one embodiment of the present invention, the detection module further comprises a substrate, the plurality of sensor units are coaxially arranged in a string-like manner in a common normal direction on the substrate, and the spacings between the plurality of sensor units are the same or different.

[0016] In one embodiment of the present invention, the preprocessing of the response state to obtain the muon flux per unit area, per unit time and per unit solid angle comprises:

[0017] Determining the solid angle range of the muon particle incident according to the response state;

[0018] The number of muon particles received in each solid angle range is counted, and the number of muon particles is normalized by the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time to obtain the muon flux per unit area, per unit time and per unit solid angle.

[0019] In one embodiment of the present invention, the reverse calculation of the density distribution within the muon ray irradiation range based on the terrain data, the topography data and the muon flux by a preset algorithm includes:

[0020] Acquiring terrain data and landform data of the surrounding environment of the detection module;

[0021] Based on the terrain data, the landform data and the muon flux, the density distribution within the irradiation range of the muon rays is inferred by a preset algorithm;

[0022] Wherein, the preset algorithm is:

[0023]

[0024] in, is the muon flux theoretically detected by the same incident trajectory without any obstruction, α is the attenuation coefficient, L is the ray length, and ρ is the average density of the object passed by the muon ray within the range covered by each solid angle combination.

[0025] In a second aspect, the present invention provides an imaging system based on cosmic ray muon transmission, which is applied to a control mechanism, wherein the control mechanism is electrically connected to at least one detection module, and the imaging system based on cosmic ray muon transmission includes: an acquisition module, a first generation module of the acquisition module, and a second generation module. The acquisition module is used to acquire the response state of the at least one detection module, wherein the detection module includes a plurality of sensor units, and the plurality of sensor units are arranged in a string. The acquisition module is used to pre-process the response state to obtain the muon flux per unit area, unit time, and unit solid angle. The first generation module is used to reversely infer the density distribution within the muon ray irradiation range through a preset algorithm based on terrain data, topographic data, and the muon flux. And the second generation module is used to perform visual imaging based on the result of the density distribution.

[0026] In one embodiment of the present invention, the detection module further comprises a substrate, the plurality of sensor units are coaxially arranged in a string-like manner in a common normal direction on the substrate, and the spacings between the plurality of sensor units are the same or different.

[0027] In one embodiment of the present invention, the obtaining module comprises:

[0028] A determination unit, used to determine the solid angle range of the muon particle incidence according to the response state;

[0029] The obtaining unit is used to count the number of muon particles received in each solid angle range, and normalize the number of muon particles data by the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time to obtain the muon flux per unit area, per unit time and per unit solid angle.

[0030] In one embodiment of the present invention, the first generation module includes:

[0031] An acquisition unit, used to acquire terrain data and landform data of the surrounding environment of the detection module;

[0032] A generating unit, configured to infer the density distribution within the irradiation range of the muon ray based on the terrain data, the landform data and the muon flux through a preset algorithm;

[0033] Wherein, the preset algorithm is:

[0034]

[0035] in, is the muon flux theoretically detected by the same incident trajectory without any obstruction, α is the attenuation coefficient, L is the ray length, and ρ is the average density of the object passed by the muon ray within the range covered by each solid angle combination.

[0036] In a third aspect, the present invention provides an electronic device, comprising:

[0037] at least one processor; and

[0038] a memory communicatively coupled to the at least one processor;

[0039] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the imaging method based on cosmic ray muon transmission as described above.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium, comprising a computer program and instructions, which, when executed on a computer, enables the computer to execute the imaging method based on cosmic ray muon transmission as described above.

[0041] Compared with the prior art, the imaging method and system based on cosmic ray muon transmission according to the present invention have the following beneficial effects:

[0042] 1. Lightweight and low cost: The present invention significantly reduces the size and weight of the detector by arranging multiple sensor units in a string. Compared with the complex multi-pixel array structure in traditional detectors, this innovative arrangement greatly simplifies the structural design, making it easier to deploy in the wild and in small spaces. At the same time, it reduces the number and complexity of sensor units, directly reduces the cost and power consumption, and achieves the goal of lightness and low cost.

[0043] 2. Balance between efficiency and resolution: The present invention can simultaneously implement observations of multiple different solid angles by adjusting the spacing and number of sensor units, thereby finding a balance between resolution and acquisition efficiency. When the spacing between sensor units is small, although the resolution is improved, the acquisition efficiency may be reduced; conversely, when the spacing is increased, the acquisition efficiency is improved but the resolution is reduced. Users can flexibly adjust according to actual needs to achieve the optimal choice between accuracy and efficiency. This flexibility ensures that the best working effect can be achieved in different application scenarios.

[0044] 3. Enhanced detection reliability: The detection module design of the present invention is equivalent to setting up a multi-layer detection board to detect muon events. Through the joint action of multiple sensor units, the redundancy and reliability of detection are improved; at the same time, based on the statistics of the number of muon particles within multiple solid angles, the probability of the direction range of the muon source ray and the reliability probability of the muon event can be further evaluated, effectively reducing non-muon exogenous false alarm interference, thereby significantly enhancing the reliability of detection;

[0045] 4. Modularity and easy maintenance: The detection module of the present invention is highly modular in design, and the connections and circuits between the sensor units are relatively simple, which is convenient for maintenance and distributed observation. In addition, since the number of sensor units is reduced and the structure is simple, the overall data volume is extremely small, which makes it easy to transmit data back through wireless transmission and other means, reducing the complexity of data transmission and processing, and further improving the maintainability and ease of use of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a schematic flow chart of an imaging method based on cosmic ray muon transmission in Embodiment 1 of the present invention;

[0047] Figure 2 is a schematic structural diagram of an imaging system based on cosmic ray muon transmission in Embodiment 2 of the present invention;

[0048] Figure 3 It is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention;

[0049] Figure 4 is a schematic diagram of the arrangement of multiple sensor units on a detection module in a specific embodiment of the present invention;

[0050] Figure 5 is a schematic diagram of a muon event recognition process of a sensor unit in a specific embodiment of the present invention;

[0051] Figure 6 is a schematic flow chart of muon bombardment event information processing in a specific embodiment of the present invention;

[0052] Figure 7 is a schematic diagram of a plurality of detection modules located at the foot of a mountain to detect the internal structure of the mountain in a specific embodiment of the present invention;

[0053] Figure 8 It is a schematic diagram of a plurality of detection modules in a specific embodiment of the present invention being located inside a tunnel to detect the structure inside the top plate above the tunnel or to predict in advance unfavorable geological bodies;

[0054] Fig. 9 It is a schematic diagram of a plurality of detection modules in a specific embodiment of the present invention being located in a borehole to detect geological structures around the borehole.

[0056] 1-Detection module, 2-Sensor unit DETAILED DESCRIPTION

[0057] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, rather than to limit the embodiments of the present invention. It is also necessary to explain that, for ease of description, only parts related to the embodiments of the present invention are shown in the accompanying drawings, rather than all structures.

[0058] For ease of understanding, the main implementation concepts of the embodiments of the present invention are first briefly described.

[0059] As an emerging detection method, cosmic ray muon detection technology has broad application prospects in the fields of geological structure detection and monitoring, large and medium-sized artificial structure inspection and flaw detection. At present, commonly used muon detectors are mainly composed of plastic scintillators, photomultiplier tubes and other sensors and electric pulse signal sampling and recording circuits. They infer the internal density distribution of the research object by sensing muon bombardment events. However, the existing technology has obvious disadvantages such as complex, large, bulky equipment, and low efficiency, which limits its application in the field and in small spaces.

[0060] The inventors have discovered the above-mentioned defects in the prior art and have provided an imaging method and system based on cosmic ray muon transmission, aiming to solve the problems existing in the prior art, improve detection efficiency, reduce system complexity, and increase adaptability to small working environments. By innovating the sensor arrangement and the method of detecting the internal density of objects, a lightweight, low-cost, and efficient muon imaging technology is achieved.

[0061] Embodiment 1

[0062] Figure 1 is a flow chart of an imaging method based on cosmic ray muon transmission in Embodiment 1 of the present invention, such as Figure 1 As shown, embodiment 1 provides an imaging method based on cosmic ray muon transmission, which is applied to a control mechanism, wherein the control mechanism is electrically connected to at least one detection module, and the imaging method based on cosmic ray muon transmission includes:

[0063] Step S100, obtaining a response state of the at least one detection module, wherein the detection module includes a plurality of sensor units;

[0064] Specifically, step S100 involves obtaining the response state of at least one detection module. The detection module here is a key component, which includes multiple sensor units. Specifically, these sensor units may be, for example, plastic scintillators, which can sense the bombardment events of cosmic ray muons. When a muon particle is incident on a sensor unit, the unit will generate a response, and this response state is then acquired by the control mechanism. By acquiring these response states, the control mechanism can determine the incidence of the muon particles and provide basic data for subsequent imaging processing. This step is an important part of the imaging method, which ensures that the system can accurately capture the information of the muon particles, thereby providing reliable data support for subsequent terrain density distribution inversion and imaging.

[0065] Step S200, preprocessing the response state to obtain the muon flux per unit area, per unit time, and per unit solid angle;

[0066] Specifically, step S200 is a key step in preprocessing the acquired detection module response state. This step involves an in-depth analysis of the response state data to determine the solid angle range of the muon particle incidence. Subsequently, by counting the number of muon particles received within each solid angle range, and normalizing these data by the effective cross-sectional area of ​​the sensor, the receiving solid angle range, and the observation time, the muon flux per unit area, unit time, and unit solid angle is obtained. This preprocessing process ensures the accuracy and reliability of the subsequent density distribution inversion and imaging results, and is an important basis for achieving efficient and accurate cosmic ray muon transmission imaging.

[0067] Step S300, based on the terrain data, the topography data and the muon flux, the density distribution within the irradiation range of the muon ray is inferred by a preset algorithm;

[0068] Specifically, step S300 is to infer the density distribution within the range of muon ray irradiation based on the terrain data, landform data and muon flux through a preset algorithm. Specifically, firstly, the terrain data and landform data of the surrounding environment of the detection module are obtained, which provide the path length and surface morphology information of the muon ray. Then, combined with the muon flux per unit area, unit time and unit solid angle obtained by preprocessing, a preset algorithm (such as ) to calculate the average density of the object that the muon ray passes through within each solid angle combination. This algorithm takes into account the theoretical muon flux detected for the same incident trajectory without any obstruction The attenuation coefficient α and the ray length L can be used to accurately infer the density distribution within the range of muon ray irradiation. This step is the key to achieving cosmic ray muon transmission imaging. It combines topographic information and muon flux data, and infers the density structure inside the object through algorithms, providing efficient and convenient solutions for geological exploration, engineering detection and other fields.

[0069] Step S400, performing visual imaging based on the density distribution result;

[0070] Specifically, after the density distribution within the range of muon ray irradiation is inferred through a preset algorithm, these density distribution data are used to construct or generate internal imaging of the research object. Specifically, this step converts the density distribution results obtained by inversion into visual images, which can clearly show the density structure inside the detected object, thereby helping users to identify and analyze geological features, anomalies or structures inside the object. The implementation of this step enables the imaging method based on cosmic ray muon transmission to not only provide accurate density distribution data, but also display the detection results in an intuitive way, providing a more convenient and efficient solution for geological exploration, engineering detection and other fields.

[0071] In this embodiment, the detection module further comprises a substrate, the plurality of sensor units are coaxially arranged in a string-like manner in a common normal direction on the substrate, and the spacings between the plurality of sensor units are the same or different;

[0072] Specifically, the present invention proposes a key detection module design, which includes multiple sensor units, and these sensor units are arranged on a substrate in a specific manner. The substrate is a carrier of the sensor unit, which provides stable support and connection, ensures that the sensor unit can be arranged and fixed in a predetermined manner, and multiple sensor units are arranged on the substrate in a certain order and direction. The central axes of all sensor units are located on the same straight line, that is, they are all arranged along the same axis. In addition, the distances between the sensor units can be equal or different. The equal spacing arrangement can provide a uniform detection range, while different spacings can be adjusted according to specific detection requirements to achieve more flexible and efficient detection. The advantages brought by this design are significant. First, by arranging in series, the size and weight of the detector can be significantly reduced, making it easier to deploy in the field and in a small space. Secondly, by adjusting the spacing and number of sensor units, multiple observations with different solid angles can be implemented simultaneously, so as to find a balance between different resolutions and acquisition efficiencies. In addition, this design also enhances the reliability of detection and reduces the complexity and cost of the system.

[0073] Based on the above analysis, it can be seen that the detection module design achieves efficient and accurate detection of cosmic ray muons through innovative sensor unit arrangement, providing an efficient and convenient solution for geological exploration, engineering detection and other fields.

[0074] In this embodiment, step S200 includes:

[0075] Step S201, determining the solid angle range of the muon particle incident according to the response state;

[0076] Specifically, the response state refers to the state of the electrical signal generated by the detection module after receiving the bombardment of muon particles, and these states are usually recorded in binary form (such as 1 for muon detection and 0 for no detection). When a muon particle bombards a sensor unit in the detection module, the unit will emit photons, which are captured by the photomultiplier tube and converted into electrical signals, and the control mechanism analyzes and records the response state of each sensor unit, and according to the response state of the sensor unit (that is, which units are activated and which are not activated), the control mechanism can infer the approximate direction of the muon particle incidence. Since multiple sensor units are coaxially arranged in a string-like common normal direction, when multiple units are activated, a solid angle range can be formed, which indicates the direction in which the muon particle may be incident. For example, the detection module consists of four sensor units, and they are arranged at equal intervals. If sensor unit 1 and sensor unit 2 are activated, and the other units are not activated, it can be inferred that the probability that the muon particle comes from the solid angle range sandwiched by these two units is the highest. If sensor units 1, 2, and 3 are activated, and other units are not activated, the probability that the muon particles come from the larger solid angle range sandwiched by units 1 and 3 is higher. In this way, all possible solid angle combinations can be counted, and the number of muon particles received in each solid angle range can be determined. However, when the detection module is tilted, the actual measured zenith angle range may not be consistent with the true zenith angle range of the muon incidence. Therefore, when performing subsequent data processing, the zenith angle needs to be corrected to ensure the accuracy of the results.

[0077] Based on the above analysis, it can be seen that step S201 determines the solid angle range of muon particle incidence by analyzing the response state of the detection module. This step is the basis for the subsequent calculation of the muon flux per unit area, per unit time and per unit solid angle, and the inverse calculation of the density distribution within the muon ray irradiation range.

[0078] Step S202, counting the number of muon particles received in each solid angle range, and normalizing the number of muon particles by the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time, to obtain the muon flux per unit area, per unit time and per unit solid angle;

[0079] Specifically, according to the response state of the detection module, the solid angle range of the muon particle incidence is determined, which can be achieved by analyzing the response of each sensor unit. For each solid angle range, the number of muon particles received within the range is counted, which can be done by recording the muon events detected by each sensor unit during the observation time. The statistical muon particle number data is normalized to eliminate the influence of the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time. The normalization formula can be expressed as: in represents the muon flux, N represents the number of muon particles received, S represents the effective cross-sectional area of ​​the sensor, and t represents the observation time. Represents the receiving solid angle range. Through normalization processing, the muon flux per unit area, unit time and unit solid angle can be obtained, which is an important basic data for the subsequent inversion of density distribution. For example, there is a detection module composed of four sensor units, and the spacing between the sensor units is equal. During the observation time, the control mechanism records the response of each sensor unit and counts the number of muon particles received in each solid angle range. In the first solid angle range (determined by sensor units 1 and 2), 100 muon particles were received; in the second solid angle range (determined by sensor units 2 and 3), 80 muon particles were received; and so on, the number of muon particles in other solid angle ranges is counted. Assume that the effective cross-sectional area of ​​the sensor is 1cm 2 , the observation time is 1 hour, and the receiving solid angle range is 1°; according to the normalized formula, the muon flux within the first solid angle range is calculated: Similarly, the muon flux in other solid angle ranges is calculated. Through normalization processing, the muon flux data in each solid angle range is obtained, which can be used for subsequent topography and landform measurement and density distribution inversion. This method not only improves the efficiency and accuracy of muon detection, but also provides an efficient and convenient solution for geological exploration, engineering detection and other fields.

[0080] In this embodiment, step S300 includes:

[0081] Step S301, obtaining terrain data and landform data of the surrounding environment of the detection module;

[0082] Specifically, the terrain data usually includes information such as the height, slope, and terrain undulation of the location of the detection module. These data can be obtained through GPS measurement, remote sensing technology, topographic maps, etc. In field detection, the accuracy of terrain data is crucial to determining the path length and angle of muon rays. The topographic data describes the surface features around the detection module, such as mountains, rivers, vegetation, etc. These data can be obtained through remote sensing images, topographic maps, on-site surveys, etc. Topographic data is of great significance for understanding the obstructions and scatterers that muon rays may encounter during propagation. After obtaining the terrain and topographic data, these data need to be processed and analyzed so as to be combined with the muon flux data to infer the density distribution within the range of muon ray irradiation. Taking mountain detection as an example, it is assumed that multiple detection modules are arranged at the foot of the mountain to detect the density distribution inside the mountain. In step S301, the following terrain and topographic data need to be obtained: the terrain data uses GPS to measure the specific position and elevation of each detection module, and obtains the overall topographic map of the mountain through remote sensing technology, including information such as slope and height. In addition, for example, a geological profile of a mountain can be obtained to understand its internal structure. Geomorphic data uses remote sensing images to identify the features of the mountain surface, such as the direction of the mountain, the distribution of rivers, and the coverage of vegetation. On-site surveys of geomorphic features at the foot of the mountain, such as rock type and soil texture, are conducted. After obtaining these topographic and geomorphic data, the density distribution inside the mountain can be inferred through a preset algorithm in combination with muon flux data.

[0083] Based on the above analysis, it can be seen that step S301 plays a vital role in the imaging method based on cosmic ray muon transmission. By obtaining accurate terrain and landform data, the necessary geometric and physical parameters can be provided for the subsequent density distribution inversion, thereby improving the accuracy and reliability of imaging.

[0084] Step S302, based on the terrain data, the landform data and the muon flux, reversely inferring the density distribution within the muon ray irradiation range through a preset algorithm;

[0085] Specifically, the preset algorithm may be, for example: Where ρ is the average density of the object through which the muon ray passes within the range covered by each solid angle combination; α is the attenuation coefficient, which indicates the rate at which the muon loses energy when traveling through the medium; is the muon flux theoretically detected under the same incident trajectory without any obstruction; is the actual measured muon flux; L is the ray length, i.e. the path length of the muon in the medium. The specific process of reverse calculation is: according to the terrain data and landform data, determine the incident trajectory and ray length L of the muon ray. Use the muon flux data obtained by the detection module to calculate the actual measured muon flux Will Muon flux detected by theory By comparison, combined with the attenuation coefficient α and the ray length L, the density distribution within the range of muon ray irradiation is inferred using the preset algorithm. Figure 7 (as shown): Multiple detection modules are arranged obliquely around the mountain at the foot of the mountain to ensure that most of the mountain is covered by the solid angle. The response state of the muon particles is obtained through the detection module, and the muon flux per unit area, unit time and unit solid angle is obtained by preprocessing. The real terrain and size data of the measured area are obtained by using technologies such as oblique photography or SLAM. According to the terrain data and landform data, the zenith angle and ray length of the muon incidence are corrected. The density distribution inside the mountain is inferred using the preset algorithm and the obtained muon flux data. The density distribution results are integrated to generate imaging results inside the mountain, which are used to analyze the density structure and anomalies inside the mountain.

[0086] Based on the above analysis, it can be seen that by innovating the sensor arrangement and the method of detecting the internal density of the object, a lightweight, low-cost, and highly efficient muon imaging technology has been realized. Step S302 is a key step in which the density distribution within the range of muon ray irradiation is inferred through a preset algorithm, providing an efficient and convenient solution for geological exploration, engineering detection and other fields.

[0087] In this embodiment, the step S400 specifically includes:

[0088] Color mapping is set according to the density value, so that different density areas are represented by different colors in the imaging. At the same time, transparency is set to show the internal structure. These parameters can be adjusted according to actual needs to achieve the best visual effect. In order to enhance the realism of the imaging, lighting and shadow effects can be set. These parameters can simulate natural lighting conditions to make the imaging results more vivid and realistic.

[0089] Download and process the surface elevation image map of the detected area as the basic framework of the 3D geological model. Map the density distribution data obtained by inversion onto the 3D geological model to ensure that the density information within each grid or voxel is accurately represented.

[0090] Select appropriate imaging techniques, such as volume rendering, raycasting, etc., according to actual needs. These techniques can achieve efficient 3D imaging with the support of the computing resources of the control mechanism. The control mechanism executes the imaging algorithm to generate imaging results based on the set parameters and 3D geological model data. The imaging results can be static images, animations, or interactive 3D models.

[0091] Select the appropriate output format according to the application scenario, such as image file, video file or 3D model file. The control agency displays the generated imaging results to relevant personnel or users, which can be done in various ways such as visualization software, web interface or virtual reality device.

[0092] Figure 4 is a schematic diagram of the arrangement of multiple sensor units on a detection module in a specific embodiment of the present invention; Figure 5 is a schematic diagram of a muon event recognition process of a sensor unit in a specific embodiment of the present invention; Figure 6 is a schematic flow chart of muon bombardment event information processing in a specific embodiment of the present invention;

[0093] Figure 7 is a schematic diagram of a plurality of detection modules located at the foot of a mountain to detect the internal structure of the mountain in a specific embodiment of the present invention; Figure 8 It is a schematic diagram of a plurality of detection modules in a specific embodiment of the present invention being located inside a tunnel to detect the structure inside the top plate above the tunnel or to predict in advance unfavorable geological bodies; Fig. 9 It is a schematic diagram of a plurality of detection modules in a specific embodiment of the present invention being located in a borehole to detect geological structures around the borehole.

[0094] In a specific embodiment of the present invention, Figure 4 As shown, a typical form of the detection module is given. The detection module is composed of multiple single plastic scintillators (multiple sensor units) arranged in a string, which is different from the arrangement of each detection plane of the traditional device divided into multiple pixels. In this embodiment, the number of the multiple sensor units is four, but the present invention is not limited to this. Each sensor unit has a square plastic scintillator sensor; the four sensor units are coaxially arranged in the normal direction, and the four sides are aligned. When a muon particle bombards a sensor unit, the sensor unit has a certain probability of emitting photons, which are converted into electrical signals by the photomultiplier tube, and then amplified and shaped by the front-end circuit. After the bombardment signal is recognized by the readout circuit, the detection unit gives an electronic indication of the arrival of the muon, such as a high level (1) when the arrival of the muon is detected, and a low level (0) when no muon arrives. The process is as follows Figure 5 As shown; that is, each sensor unit has a plastic scintillator sensor, a photomultiplier tube, a front-end circuit and a readout circuit.

[0095] like Figure 6 As shown, taking four sensor units arranged at equal intervals as an example, the control mechanism (such as a computer, a single-chip microcomputer and an embedded system, as long as it can perform the data processing and analysis described below, an MCU or a CPU) analyzes and records the 1 and 0 states of each sensor unit, and determines which sensor unit the muon particle has bombarded based on the 1 and 0 states. Figure 4In the above example, if the output state of the detection unit of sensor unit 1 and sensor unit 2 (sensor unit 2 and sensor unit 3 or sensor unit 3 and sensor unit 4) is 1, and the output state of other detection units is 0, it can be judged that the probability of the muon particle coming from the solid angle included by the red line is the highest, the probability of coming from the solid angle included by the green line is lower (because there is a certain probability of muon emitting light after bombardment), and the probability of coming from the solid angle included by the blue line is the lowest. If the output state of the detection unit of sensor unit 1, sensor unit 2 and sensor unit 4 (sensor unit 1, sensor unit 3 and sensor unit 4) is 1, and the output of other detection units is 0, the probability of the muon coming from the solid angle included by the blue line is higher, and the detection unit of sensor unit 3 (or sensor unit 2) may have missed the record. If the output state of the detection unit of sensor unit 1, sensor unit 2 and sensor unit 3 (sensor unit 2, sensor unit 3 and sensor unit 4) is 1, and the output of other detection units is 0, the probability of the muon coming from the solid angle included by the green line is higher. Among them, the above-mentioned sensor unit No. 1 is Figure 4 The lowermost sensor unit, sensor unit No. 2 is located in front of sensor unit No. 1 (above in the figure), sensor unit No. 3 is located in front of sensor unit No. 2 (above in the figure), and sensor unit No. 4 is located in front of sensor unit No. 3 (above in the figure).

[0096] According to the above analysis, it can be counted that when N sensor units are arranged at equal intervals, there are N-1 possible combinations of solid angles; however, when the N sensor units are arranged at non-equal intervals, the zenith angle range of muon incidence is determined according to the maximum spacing of the sensor units. Taking four sensor units as an example, when the output state of sensor unit 1 and sensor unit 2 (sensor unit 2 and sensor unit 3 or sensor unit 3 and sensor unit 4) is 1, and the output state of other sensor units is 0, the solid angle range from which the muon particle originates is determined by the actual spacing between sensor unit 1 and sensor unit 2 (sensor unit 2 and sensor unit 3 or sensor unit 3 and sensor unit 4); when the detection unit output state of sensor unit 1, sensor unit 2 and sensor unit 3 (sensor unit 2, sensor unit 3 and sensor unit 4) is 1, and the output of other detection units is 0, the solid angle range from which the muon particle originates is determined by the spacing between sensor unit 1 and sensor unit 3 (sensor unit 2 and sensor unit 4). According to the number and spacing of sensor units, there are M possible combinations of solid angles. By counting the solid angle range of each muon source, the final data obtained is the number of muons received under each solid angle combination (the data is normalized by the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time to obtain the muon flux per unit area, unit angle and unit time). Unit: cm -2 s -1 sr -1 , represents the number of muons received in 1 square centimeter area, 1 second time and 1 degree solid angle. Figure 4 As shown in the figure, when the detection module is placed vertically, the zenith angle range calculated by the system through the spacing is consistent with the actual zenith angle range of the muon incidence, but the detection module is placed tilted (such as Figure 7 When measuring the zenith angle, the zenith angle should be corrected according to the inclination angle of the instrument. Then, the real terrain and size data of the measured area are obtained by using technologies such as oblique photography or SLAM, and then the muon incidence trajectory, i.e., the ray length L, is obtained to perform ray length correction:

[0097]

[0098] That is, the average density ρ of the object that the muon rays pass through within the range covered by the solid angle combination can be obtained. is the muon flux theoretically detected under the same incident trajectory without any obstruction, and α is the attenuation coefficient, which can be obtained by simulation or actual measurement.

[0099] by Figure 4For example, if the average density shown in the solid angle range between the blue line is less than the average density in the solid angle range between the blue and red lines, it means that there may be a relatively low-density anomaly on the side of the detection module axis (dashed line), such as a cavity, fracture, etc. If the average density shown in the solid angle range between the blue line is greater than the average density in the solid angle range between the blue and red lines, it means that there may be a relatively high-density anomaly on the side of the detection module axis (dashed line), such as a rock, ore body, etc.

[0100] The average density data obtained from observations can also be used for quantitative density structure inversion; if observations are carried out at multiple different locations to enrich the ray coverage, tomographic imaging can also be achieved.

[0101] like Figure 7 As shown, the detection module can be used to detect the inside of the mountain at the foot of the mountain. Multiple detection modules are arranged obliquely around the mountain. At this time, the zenith angle of the central axis of the detection module is not 0, and the detector spacing and number are required to make the mountain completely (or mostly) covered by the solid angle. Then, the collected data is corrected for the zenith angle and the ray length, and the average density of the object passed by the muon ray within the range covered by the solid angle combination can be obtained, that is, the density distribution inside the mountain.

[0102] like Figure 8 As shown in the figure, the detection module can be deployed in the tunnel to detect the tunnel roof or the front of the tunnel face. Multiple detection modules are evenly deployed along the tunnel, where the detection module used to detect the tunnel roof is placed vertically (the zenith angle of the instrument's central axis is 0), and the detection module used to detect the tunnel face is placed obliquely. Similarly, the collected data is corrected for the zenith angle and the ray length, and the density distribution above the tunnel roof and in front of the tunnel face (the tunnel face) can be obtained to detect whether there are low-density geological disasters such as cavities and water injection holes.

[0103] like Fig. 9 As shown, the detection module can also be arranged in the borehole to detect the formation around the borehole. The detector can be placed along the direction of the borehole, along the wall of the hole at intervals of depth, to detect the formation around the borehole.

[0104] Based on the above analysis, the present invention uses a number of single plastic scintillators (sensor units) arranged in a string, which can simultaneously implement observations of multiple different solid angles, corresponding to different resolutions and acquisition efficiencies. The larger the sensor unit spacing, the higher the resolution (smaller solid angle) and the lower the acquisition efficiency (fewer particles in a certain period of time); conversely, the lower the resolution, the higher the acquisition efficiency. For users, they can freely choose the balance between accuracy and efficiency. In situations where accuracy is emphasized, a large solid angle can be selected for acquisition; in situations where efficiency is emphasized, a fast acquisition method (large solid angle) can be selected while meeting the resolution requirements.

[0105] Each sensor unit is not necessarily square, but can be round or other shapes that are easy to process. The size of each sensor unit is not necessarily exactly the same (these differences can be eliminated by normalization); and the spacing between sensor units is not necessarily equal, and can be adjusted as needed.

[0106] The sensor unit used to detect muon particles can be made of other sensing materials such as liquid scintillators in addition to plastic scintillators.

[0107] like Figure 5 As shown, during the information processing of the muon bombardment event, the basis for judging which plastic flash sensor unit the muon particle bombarded can be not only the 1 or 0 state, but also the unshaped electrical signal collected by the acquisition card, that is, the control mechanism is the acquisition card, and the acquisition card can be electrically connected to the front-end circuit or the readout circuit.

[0108] Embodiment 2

[0109] Figure 2 is a schematic diagram of the structure of an imaging system based on cosmic ray muon transmission in Embodiment 2 of the present invention, such as Figure 2 As shown, embodiment 2 provides an imaging system based on cosmic ray muon transmission, which is applied to a control mechanism, wherein the control mechanism is electrically connected to at least one detection module, and the imaging system based on cosmic ray muon transmission includes: an acquisition module, a first generation module of the acquisition module, and a second generation module. The acquisition module is used to acquire the response state of the at least one detection module 1, wherein the detection module 1 includes a plurality of sensor units 2. The acquisition module is used to pre-process the response state to obtain the muon flux per unit area, unit time, and unit solid angle. The first generation module is used to infer the density distribution within the muon ray irradiation range through a preset algorithm based on terrain data, topographic data, and the muon flux. And the second generation module is used to perform visual imaging based on the result of the density distribution.

[0110] In this embodiment, the detection module 1 further comprises a substrate, and the plurality of sensor units 2 are coaxially arranged in a string-like manner in a common normal direction on the substrate, and the intervals between the plurality of sensor units 2 are the same or different.

[0111] In this embodiment, the obtaining module includes:

[0112] A determination unit, used to determine the solid angle range of the muon particle incidence according to the response state;

[0113] The obtaining unit is used to count the number of muon particles received in each solid angle range, and normalize the number of muon particles data by the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time to obtain the muon flux per unit area, per unit time and per unit solid angle.

[0114] In this embodiment, the first generating module includes:

[0115] An acquisition unit, used to acquire terrain data and landform data of the surrounding environment of the detection module 1;

[0116] A generating unit, configured to infer the density distribution within the irradiation range of the muon ray based on the terrain data, the landform data and the muon flux through a preset algorithm;

[0117] Wherein, the preset algorithm is:

[0118]

[0119] in, is the muon flux theoretically detected by the same incident trajectory without any obstruction, α is the attenuation coefficient, L is the ray length, and ρ is the average density of the object passed by the muon ray within the range covered by each solid angle combination.

[0120] The various variations and specific examples of the imaging method based on cosmic ray muon transmission provided in Example 1 are also applicable to the imaging system based on cosmic ray muon transmission provided in this example. Through the above detailed description of an imaging method based on cosmic ray muon transmission, those skilled in the art can clearly understand the implementation method of an imaging system based on cosmic ray muon transmission in this example, so for the sake of brevity of the specification, it will not be described in detail here.

[0121] Embodiment 3

[0122] Figure 3 is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention, such as Figure 3 As shown, the third embodiment further provides an electronic device 300 , which may include: a processor 301 and a memory 302 .

[0123] The memory 302 is used to store programs; the memory 302 may include volatile memory (English: volatile memory), such as random-access memory (English: random-access memory, abbreviated: RAM), such as static random-access memory (English: static random-access memory, abbreviated: SRAM), double data rate synchronous dynamic random access memory (English: Double Data Rate Synchronous Dynamic Random Access Memory, abbreviated: DDR SDRAM), etc.; the memory may also include non-volatile memory (English: non-volatile memory), such as flash memory (English: flash memory). The memory 302 is used to store computer programs (such as applications, functional modules, etc. that implement the above method), computer instructions, etc., and the above computer programs, computer instructions, etc. can be partitioned and stored in one or more memories 302. And the above computer programs, computer instructions, data, etc. can be called by the processor 301.

[0124] The above-mentioned computer programs, computer instructions, etc. may be stored in partitions in one or more memories 302 . And the above-mentioned computer programs, computer instructions, etc. may be called by the processor 301 .

[0125] The processor 301 is used to execute the computer program stored in the memory 302 to implement each step of the method involved in the above embodiment.

[0126] For details, please refer to the relevant description in the previous method embodiment.

[0127] The processor 301 and the memory 302 may be independent structures or integrated structures. When the processor 301 and the memory 302 are independent structures, the memory 302 and the processor 301 may be coupled and connected via a bus 303 .

[0128] The electronic device of this embodiment can execute the technical solution in the above method, and its specific implementation process and technical principle are the same, which will not be repeated here.

[0129] Embodiment 4

[0130] Embodiment 4 also provides a computer-readable storage medium, including a computer program and instructions. When the computer program or instructions are executed on a computer, the computer executes the imaging method based on cosmic ray muon transmission of any embodiment of the present invention.

[0131] Computer-readable storage media include: USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks, and other media that can store program codes.

[0132] This embodiment also provides a computer program product, which includes: a computer program, which is stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device executes the solution provided by any of the above embodiments.

[0133] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the disclosure of the present invention can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0134] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. An imaging method based on cosmic ray muon transmission, applied to a control mechanism, wherein the control mechanism is electrically connected to at least one detection module, characterized in that: The imaging method based on cosmic ray muon transmission comprises: Acquiring a response state of the at least one detection module, wherein the detection module comprises a plurality of sensor units, and the plurality of sensor units are arranged in a series; Preprocessing the response state to obtain the muon flux per unit area, per unit time, and per unit solid angle; Based on the terrain data, the topographic data and the muon flux, the density distribution within the irradiation range of the muon rays is inferred through a preset algorithm; Based on the density distribution results, visualization imaging is performed.

2. The imaging method based on cosmic ray muon transmission according to claim 1, characterized in that: The detection module further includes a substrate, and the plurality of sensor units are coaxially arranged in a string-like manner in a common normal direction on the substrate, and the spacings between the plurality of sensor units are the same or different.

3. The imaging method based on cosmic ray muon transmission according to claim 1, characterized in that: The preprocessing of the response state to obtain the muon flux per unit area, per unit time and per unit solid angle includes: determining the solid angle range of the muon particle incidence according to the response state; The number of muon particles received in each solid angle range is counted, and the number of muon particles is normalized by the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time to obtain the muon flux per unit area, per unit time and per unit solid angle.

4. The imaging method based on cosmic ray muon transmission according to claim 1, characterized in that: The reverse calculation of the density distribution within the muon ray irradiation range based on the terrain data, the landform data and the muon flux by a preset algorithm includes: Acquiring terrain data and landform data of the surrounding environment of the detection module; Based on the terrain data, the landform data and the muon flux, the density distribution within the irradiation range of the muon ray is inferred by a preset algorithm; Wherein, the preset algorithm is: in, is the muon flux theoretically detected by the same incident trajectory without any obstruction, α is the attenuation coefficient, L is the ray length, and ρ is the average density of the object passed by the muon ray within the range covered by each solid angle combination.

5. An imaging system based on cosmic ray muon transmission, applied to a control mechanism, the control mechanism is electrically connected to at least one detection module, characterized in that: The imaging system based on cosmic ray muon transmission comprises: an acquisition module, configured to acquire a response state of the at least one detection module, wherein the detection module comprises a plurality of sensor units, and the plurality of sensor units are arranged in a series; An obtaining module is used to pre-process the response state to obtain the muon flux per unit area, per unit time and per unit solid angle; A first generation module is used to infer the density distribution within the irradiation range of the muon ray based on the terrain data, the landform data and the muon flux through a preset algorithm; and The second generating module is used to perform visual imaging based on the density distribution result.

6. The imaging system based on cosmic ray muon transmission according to claim 5, characterized in that: The detection module further includes a substrate, and the plurality of sensor units are coaxially arranged in a string-like manner in a common normal direction on the substrate, and the spacings between the plurality of sensor units are the same or different.

7. The imaging system based on cosmic ray muon transmission according to claim 5, characterized in that: The obtaining module comprises: A determination unit, used to determine the solid angle range of the muon particle incidence according to the response state; The obtaining unit is used to count the number of muon particles received in each solid angle range, and normalize the number of muon particles data by the effective cross-sectional area of ​​the sensor, the receiving solid angle range and the observation time to obtain the muon flux per unit area, per unit time and per unit solid angle.

8. The imaging system based on cosmic ray muon transmission according to claim 5, characterized in that: The first generation module comprises: An acquisition unit, used to acquire terrain data and landform data of the surrounding environment of the detection module; A generating unit, configured to infer the density distribution within the irradiation range of the muon ray based on the terrain data, the landform data and the muon flux through a preset algorithm; Wherein, the preset algorithm is: in, is the muon flux theoretically detected by the same incident trajectory without any obstruction, α is the attenuation coefficient, L is the ray length, and ρ is the average density of the object passed by the muon ray within the range covered by each solid angle combination.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the imaging method based on cosmic ray muon transmission as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The invention comprises a computer program and instructions. When the computer program or the instructions are run on a computer, the computer is enabled to execute the imaging method based on cosmic ray muon transmission as claimed in any one of claims 1 to 4.

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