Tomb non-destructive detection method and system

Abstract

The present invention provides a method and system for nondestructive detection of tombs. The method for nondestructive detection of tombs includes: constructing a system parameter model based on the tomb appearance data; generating an initial muon model; constructing a muon transport model based on the system parameter model and the initial muon model; setting a muon detector outside the tomb; and reconstructing a three-dimensional image of the interior of the tomb according to the muon data and the muon transport model acquired by the muon detector. The nondestructive detection system for tombs includes: a tomb appearance data measurement device; a muon detection device; a data processing device; and an image reconstruction device. By using the method and system for nondestructive detection of tombs of the present invention, it is possible to determine the imaging reconstruction method and detection device of the internal burial mound, tomb passage and underground palace structure of the tomb based on the unique advantages of natural background cosmic ray muons, such as extremely strong penetrating power, easy positioning of hidden cavities, not susceptible to interference, and no need for protection, and finally obtain muon imaging data of the internal structure of the tomb, and realize three-dimensional imaging of the internal structure of the tomb.

Description

Technical Field

[0001] The present invention relates to the field of tomb detection, and in particular to a method and system for non-destructive tomb detection. Background Art

[0002] my country is one of the four ancient civilizations in the world. Its thousands of years of brilliant history have left countless cultural relics and monuments. One of the most eye-catching monuments is the imperial tombs. From the Xia and Shang Dynasties to the Ming and Qing Dynasties, there are hundreds of imperial tombs with traces on the ground and clear eras. They are magnificent in architecture, exquisite in craftsmanship, and unique in style. They occupy an important position in the history of world culture, such as the Mausoleum of Qin Shihuang, Qianling Mausoleum, and the Ming Tombs. The structure of the burial mound, tomb path, and underground palace (Structure for Sealing Earth, Tomb Path and Underground Palace, STU) is an important parameter for exploring the internal information of the tomb, tracing the cultural research, and formulating cultural protection countermeasures. Usually, the burial mound is the above-ground building part of the imperial tomb and an important symbol of the tomb; the tomb path and underground palace are the underground building parts of the imperial tomb and are also important storage places for cultural relics. These three important parameters are the most important components of the main tomb. Obtaining the burial mound, tomb path, and underground palace structure inside the tomb without damage is a technical problem that needs to be solved urgently.

[0003] Traditional indirect detection methods are mainly divided into two categories. One is the inference method based on historical documents, which cannot determine the authenticity of the conclusion; the other is the detection method based on geophysics, such as magnetic detection, high-density resistivity, geological radar, gravity detection, etc. These methods can only indirectly measure the physical field or halo of the object to be measured. The measurement results need further quantitative inversion analysis to establish a connection with the object to be measured, which has inevitable multiple solutions. This type of method can only give inference information such as whether the tomb passage or underground palace exists and is complete. It is not intuitive and the inversion accuracy is also poor. At the same time, this type of method relying on the intermediate medium is also very sensitive to interference sources such as terrain undulations and magnetism in the measurement environment, which can easily affect the accuracy of the measurement results. In addition, this type of method does not achieve completely non-destructive detection. For example, high-density resistivity and gravity detection methods must be drilled or sampled along the measurement profile. Therefore, the current traditional indirect detection method will introduce a lot of uncertainty, and it is impossible to obtain the internal structure of the tomb completely non-destructively, and carry out corresponding scientific and technological archaeology and cultural relics protection work.

[0004] With today's technology, radiation imaging technology has been widely used in the fields of medicine and industry, realizing health monitoring of human body imaging, non-destructive testing of object imaging, etc. However, there is no disclosure of technology for using radiation imaging to achieve intuitive internal structure imaging for large tombs. Cosmic ray muons (muons), a natural background particle, are secondary particles from the interaction between high-energy cosmic rays from outer space and the atmosphere, and are commonly found in the environmental background. Muons have extremely strong penetrating power, with an average energy of about 4GeV, and can even penetrate high atomic number nuclear materials; compared with traditional X / γ / neutron imaging, muons come directly from the environmental background and do not require protection, which is absolutely safe for personnel and cultural relics; they also have unique advantages such as easy positioning of hidden voids and not easily affected by environmental interference. Of course, muon imaging technology also has certain problems. The counting rate is low, and the muon flux at sea level is about 10,000c / min / m 2 However, compared with fields such as nuclear material security inspections that require rapid imaging, tomb imaging does not have strict requirements on imaging time. If the internal structure of large tombs can be obtained through muon imaging, it can solve the technical bottlenecks of traditional indirect detection methods such as susceptibility to interference, low quantitative inversion accuracy, and inability to be completely lossless. However, it is difficult to achieve, mainly because of the research and development of cosmic ray muon imaging reconstruction methods and detection devices for large cultural relics tombs. Summary of the invention

[0005] The main purpose of the present invention is to provide a method and system for non-destructive detection of tombs to solve the problems of uncertainty and the like existing in the prior art.

[0006] According to a first aspect of the present invention, a method for nondestructive detection of tombs is provided, which is characterized in that it includes the following steps: constructing a system parameter model based on tomb appearance data; generating an initial muon model; constructing a muon transport model based on the system parameter model and the initial muon model; setting a muon detector outside the tomb; and reconstructing a three-dimensional image of the interior of the tomb based on the muon data and the muon transport model acquired by the muon detector.

[0007] Preferably, the tomb shape data is obtained through remote sensing technology.

[0008] Preferably, the initial muon model is generated by modifying the empirical formula model.

[0009] Preferably, a muon transport model is constructed based on the energy loss curve of muons in tombs and a scattering subtraction model.

[0010] Preferably, the step of reconstructing the three-dimensional image of the interior of the tomb includes first reconstructing the image from a single perspective, and then further performing multi-perspective reconstruction based on the single-perspective reconstruction result.

[0011] Preferably, the core theory of multi-view reconstruction is compressed sensing.

[0012] According to a second aspect of the present invention, a non-destructive detection system for tombs is provided, which is characterized in that it is arranged outside the tomb and includes: a tomb shape data measuring device for non-destructively measuring the tomb shape data; a muon detection device for detecting muon data; a data processing device for constructing a system parameter model based on the tomb shape data, generating an initial muon model, and constructing a muon transport model based on the system parameter model and the initial muon model; and an image reconstruction device for reconstructing a three-dimensional image of the interior of the tomb based on the muon data and the muon transport model.

[0013] Preferably, the muon detection device includes a plurality of groups of muon detectors distributed around the tomb.

[0014] Preferably, each group of muon detectors includes three layers of muon detection arrays.

[0015] Preferably, each layer of the muon detection array includes two groups of vertically placed plastic scintillator muon detection unit arrays.

[0016] Preferably, a layer of heavy metal material reflector is arranged between the two groups of plastic scintillator muon detection unit arrays.

[0017] Preferably, the cross section of the plastic scintillator muon detection unit is square, triangular, circular or hexagonal.

[0018] Compared with the prior art, the technical solution according to the present invention can address the urgent needs of exploring the internal structure and cultural origins of tombs and formulating cultural protection plans. Based on the unique advantages of natural background cosmic ray muons, such as extremely strong penetrating power, easy positioning of hidden voids, low susceptibility to interference, and no need for protection, it can break the deadlock in the development of this field restricted by traditional indirect detection and imaging technologies, and explore new imaging and reconstruction methods and detection devices for determining the internal burial mounds, tomb passages, and underground palace structures of large tombs by direct muon detection and imaging. Ultimately, muon imaging data of the internal structure of large tombs can be obtained, achieving a breakthrough in the current situation where it is difficult to perform three-dimensional imaging of the internal structure of large tombs. These achievements will provide important scientific basis for the scientific and technological archaeology and cultural relics protection practices of large tombs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] Figure 1 A flowchart of a non-destructive detection method for tombs according to an embodiment of the present invention is shown;

[0021] Figure 2 A schematic diagram of a non-destructive detection system for tombs according to an embodiment of the present invention is shown;

[0022] Figure 3 A schematic diagram of the overall technical route of the muon imaging reconstruction method and detection device according to an embodiment of the present invention is shown;

[0023] Figure 4 A schematic diagram of the design of a muon detector system according to an embodiment of the present invention is shown;

[0024] Figure 5 A schematic diagram of comparing CT and muon imaging projection data according to an embodiment of the present invention is shown;

[0025] Figure 6 A schematic diagram of 22 sampling reconstruction results of Compressed Sensing theory according to an embodiment of the present invention is shown;

[0026] Figure 7 A set of detector electronics construction schematics according to an embodiment of the present invention are shown.

[0027] Throughout the drawings, the same reference numbers are used to refer to the same or similar parts. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0029] In the following description, references to "one embodiment", "an embodiment", "an example", "an example", etc. indicate that the embodiment or example described above may include specific features, structures, characteristics, properties, elements or limitations, but not every embodiment or example necessarily includes the specific features, structures, characteristics, properties, elements or limitations. In addition, repeated use of the phrase "in one embodiment" may refer to the same embodiment, but does not necessarily refer to the same embodiment.

[0030] For the sake of simplicity, certain technical features well known to those skilled in the art are omitted in the following description.

[0031] Figure 1 A non-destructive detection method for a tomb according to an embodiment of the present invention is schematically shown. The method can be implemented near the tomb, or partially implemented in a remote location via a network.

[0032] In step S102, a system parameter model is constructed based on the tomb shape data. Preferably, the tomb shape data is obtained through remote sensing technology.

[0033] In step S104, an initial muon model is generated. Preferably, the initial muon model is generated by modifying the empirical formula model.

[0034] In step S106, a muon transport model is constructed based on the system parameter model and the initial muon model. Preferably, the muon transport model is constructed based on the energy loss curve of muons in the tomb and the scattering subtraction model.

[0035] In step S108, a muon detector is set outside the tomb. Those skilled in the art can clearly understand that the implementation order of the above steps can be adjusted as needed.

[0036] In step S110, a three-dimensional image of the interior of the tomb is reconstructed based on the muon data acquired by the muon detector and the muon transport model. Preferably, the image is reconstructed from a single perspective first, and then multi-perspective reconstruction is further performed based on the single-perspective reconstruction result. Preferably, the core theory of multi-perspective reconstruction is compressed sensing.

[0037] Figure 2 A nondestructive detection system for tombs according to an embodiment of the present invention is shown. The system is arranged outside the tomb and comprises: a tomb shape data measuring device 22; a muon detection device 24; a data processing device 26; and an image reconstruction device 28.

[0038] The tomb shape data measuring device 22 is used for non-destructive measurement of the tomb shape data. Preferably, the tomb shape data measuring device 22 is a remote sensing measurement device.

[0039] The muon detection device 24 is used to detect muon data. Preferably, the muon detection device 24 includes a plurality of groups of muon detectors distributed around the tomb. Preferably, each group of muon detectors includes a three-layer muon detection array. Preferably, each layer of the muon detection array includes two groups of vertically placed plastic scintillator muon detection unit arrays. Preferably, a layer of heavy metal material reflector is arranged between the two groups of plastic scintillator muon detection unit arrays. Preferably, the cross-section of the plastic scintillator muon detection unit is square, triangular, circular or hexagonal.

[0040] The data processing device 26 is used to construct a system parameter model based on the tomb shape data, generate an initial muon model, and construct a muon transport model based on the system parameter model and the initial muon model.

[0041] The image reconstruction device 28 is used to reconstruct the three-dimensional image of the interior of the tomb based on the muon data and the muon transport model.

[0042] The working mechanism of the novel large-scale cultural relic tomb cosmic ray muon imaging reconstruction method and detection device according to the present invention is described in detail below.

[0043] The overall technical route of the large-scale tomb cosmic ray muon imaging reconstruction method and detection device of the present invention is as follows: Figure 3 shown.

[0044] In order to detect the flux changes after the absorption-only interaction of cosmic ray muons with large tombs, it is necessary to first determine the energy loss mechanism and deduct the scattering effect.

[0045] In terms of determining the energy loss mechanism, muons are elementary particles with unit charge. Based on Monte Carlo Geant4 simulation, the energy loss mechanism of their classic ionization and excitation interactions with large limestone tombs was determined; in addition, since the speed of muons is close to the speed of light, they should also be regarded as relativistic particles to study the energy loss of radiation processes, mainly including bremsstrahlung, electron pair effect and photonuclear effect, to determine which form of energy loss is dominant, and finally draw the total energy loss curve of muons of different energies in large limestone tombs.

[0046] In terms of deducting the influence of scattering, the scattered muons are generated by the interaction with the Coulomb force of the nucleus as described by the Rutherford scattering cross section. The central limit theorem shows that the scattering angle obeys the Gaussian distribution. As shown in formula (1), based on the Moliere theory and the Monte Carlo Geant4 program, the relationship between the complex scattering angle distribution and the muon momentum, the composition of the tomb to be measured, the thickness, etc. is simulated to determine the scattering proportion, and then the corresponding scattering subtraction model is constructed to eliminate the influence of scattering on the flux measurement.

[0047]

[0048] Among them, σ θ Indicates the standard deviation of the scattering angle; L / L rad Indicated by the radiation length L rad The unit is the thickness of the object to be measured; p represents the momentum of the muon; βc represents the speed of the muon.

[0049] Next, in terms of the cosmic ray muon image algorithm and detection device for large tombs, Monte Carlo simulation of muon imaging was carried out.

[0050] The first step is to build a system parameter model of the tomb and the detector. Based on the STU data obtained from historical literature research and early comprehensive geophysical exploration methods as prior knowledge, remote sensing technology is combined with field measurement methods such as total stations to obtain digital data on the appearance of the tomb, and the system parameter model is established by integrating the prior STU information and the tomb appearance information. The aforementioned remote sensing technology refers to the use of detection instruments, without contact with the detection target, to record the electromagnetic wave characteristics of the target from a distance, and through analysis, reveal the characteristic properties of the object and its changes. The technologies that can be used to measure the topography of the tomb include but are not limited to synthetic aperture radar, three-dimensional laser scanning, drone aerial photography, GPS, etc. In addition to these long-distance measurement methods, instruments such as theodolites, levels, and total stations can also be used to measure the azimuth, elevation, and other information of the target to be measured at the measurement site. In addition, the low-noise muon detector system is optimized and designed. At present, there are three main types of detectors used for muon imaging: nuclear latex, gas, and scintillator detectors. Nuclear latex detectors are seriously affected by temperature and humidity, gas detectors are difficult to maintain airtightness and are expensive, and scintillator detectors are currently the most widely used technology. Plastic scintillators can be processed into various shapes according to application requirements. They are not easily affected by environmental interference, have high detection efficiency, and are low in cost. Compared with the former two, they are more suitable for field burial site measurements. Figure 4 As shown in the preliminary design scheme of the low-noise muon detector system adopted by the present invention, compared with the traditional two-layer plastic flash array, 1) three layers of plastic flash will be used to more accurately fit the muon track and eliminate the influence of noise such as accidental coincidence. Each layer is composed of two groups of vertically placed plastic flash detection unit arrays to record the muon incident track; 2) a reflector made of copper or lead heavy metal material is added between every two layers of plastic flash to increase the scattering probability of background events and reduce "false events" caused by accidental coincidence; 3) finally, the cross-sectional shape of the plastic flash unit is optimized. The cross-sectional shape of the plastic flash unit includes square, triangle, circle, hexagon, etc. Preferably, a triangular cross-sectional shape is used to obtain a smaller position resolution capability than the detection unit cross-section. By adjusting the ratio of the height to the base width of the triangular cross-section, the detector position resolution can be further improved, thereby guiding the detector system development plan and finally constructing a parameter model of the tomb and low-noise muon detector system.

[0051] The second step is to generate initial muons. There are many ways to generate muons, which can be roughly divided into two categories according to the means used: empirical formula method and Monte Carlo simulation method. Monte Carlo simulation method often involves the construction of a real atmospheric model and the simulation of specific physical processes, which requires a very large amount of calculation. In contrast, the empirical formula method is usually relatively simple in form, and it is very convenient to obtain the flux and angular distribution of cosmic ray muons at sea level by sampling the integral of the formula, so it is more suitable for application in the field of tomb imaging. One of the most classic models in the empirical formula method is the Gaisser model, but this model has the limitation of ignoring the effect of the earth's curvature on the muon decay rate, and is only applicable to small zenith angles θ < 70°, which does not meet the requirements of large zenith angles for large tombs. The shortcomings of the Gaisser model can be improved. In addition, there are some empirical formula models of sea level muon energy spectrum independent of the Gaisser model, such as the Reyna model, the Bugaev model, the Smith & Duller phenomenological model, etc. The present invention compares and corrects the existing common models that use empirical formulas to generate initial muons, and generates initial muons suitable for accurate simulation of large tombs.

[0052] The third step is to construct a muon transport model. Based on the interaction energy loss mechanism and scattering subtraction model, the deep penetration of muons in large limestone tombs with a thickness of hundreds of meters is considered. The proposed solution is to improve simulation efficiency and reduce statistical errors. First, the direction of the initial muons is predicted, and only valid muons pointing to the detector system are selected; at the same time, only the interaction between muons and matter is considered, and secondary particles are ignored to improve simulation efficiency; in addition, variance reduction techniques will be used to reduce statistical errors, realize accurate simulation of the muon transport model, and obtain flux projection data for image reconstruction.

[0053] The fourth step is to establish a detector measurement plan. Based on the models established in the previous three steps, optimize the design of parameters such as the number, position, and angle of detectors, and establish a measurement plan to guide on-site detection.

[0054] After Monte Carlo simulation, the STU scheme inside the large tomb was reconstructed in three dimensions based on the severely incomplete muon flux projection data.

[0055] The first step is to reconstruct the image under a single perspective. The reconstruction target of muon absorption imaging is the density value. First, based on the flux projection data obtained by the Monte Carlo simulation and the generated natural muon spectrum data, the mass thickness of the tomb is calculated according to formula (2). Then, based on the elevation data of the tomb shape measured by remote sensing technology such as radar, the track length of the muon passing through the mountain is inferred. Finally, the average density distribution image of muon absorption imaging under a single perspective is constructed by formula (3). Among them, The detector is Fluxes measured in zenith and azimuth directions; is The flux of initial muons in the direction; E min is the minimum energy of the initial muon that can penetrate the tomb and reach the detector; ρ(ξ) is the density distribution; is The average density distribution in the direction.

[0056]

[0057]

[0058] The second step is to reconstruct the 3D image from multiple perspectives. Based on the single-perspective reconstruction result of the first step, multi-perspective reconstruction is further performed. First, consider the data structure of sparse projection perspectives and complex projection data distribution, such as Figure 5 The figure shows a schematic diagram of the comparison between CT and muon imaging projection data, where the horizontal axis represents the projection angle and the vertical axis represents the projection position of the detector. The projection data of traditional X-ray CT three-dimensional imaging is regular and complete, both in terms of the projection angle and the projection data at each angle, while the two dimensions of muon projection data are severely sparse and incomplete. It is necessary to sort out and rearrange the data structures of these two dimensions respectively, and then back-project to obtain the track length of each muon passing through all the pixels in the area of ​​interest, and construct a track transmission matrix. Based on the compressed sensing theory that can accurately reconstruct the internal complex structure using only 22 sampled projection data, for example, preliminary three-dimensional imaging results of the tomb STU are obtained. The Compressed Sensing theory exploits the sparse characteristics of the signal, obtains discrete samples of the signal by random sampling under conditions that are much lower than the sampling rate of the traditional sampling method, and then perfectly reconstructs the signal through a nonlinear reconstruction algorithm. This theory is widely used in wireless sensor networks, medical image processing, biosensing, remote sensing image processing and other fields, such as Figure 6The figure shows 22 sampling reconstruction results of Compressed Sensing theory. The upper part of the figure is the original model, and the lower part is the 22 sampling reconstruction results. The present invention applies this theory to the field of muon absorption imaging for the first time, considering the sampling method of severely incomplete viewing angles and projection data, and establishes a severely incomplete data three-dimensional image reconstruction algorithm suitable for muon absorption imaging. Under the guidance of compressed sensing theory, when reconstructing signals based on the track transmission matrix to obtain the three-dimensional density distribution of the tomb STU, there are many reconstruction algorithms that can be used, including greedy algorithms, convex relaxation algorithms, iterative threshold algorithms, non-convex minimization algorithms, combined optimization algorithms, Bregam iterative methods, etc. These algorithms have their own advantages and disadvantages, and they will be flexibly selected according to needs in practical applications. Further consideration is given to the optimization scheme of the three-dimensional image of the tomb STU obtained using the Compressed Sensing theory, using the ordered subset maximum likelihood method to improve the image reconstruction speed, using the minimum total variation and bilateral filtering algorithms to denoise the image with minimal distortion, and constructing a reconstruction optimization model. Alternatively, a clustering algorithm or Bayesian inversion can be used to combine gravity measurement data to reconstruct three-dimensional images from multiple perspectives. Finally, the image segmentation method is used to identify different areas inside the tomb and obtain the STU three-dimensional segmentation image.

[0059] Finally, a low-noise muon absorption imaging device was developed and the internal structure of the tomb was reconstructed.

[0060] The low-noise muon absorption imaging direct detection device of the present invention is mainly composed of three parts: a detector system, a data acquisition and processing system, and an image reconstruction system. The detector system and the image reconstruction system are respectively implemented based on the low-noise detector system optimization design scheme obtained by Monte Carlo simulation and three-dimensional reconstruction and the three-dimensional image reconstruction algorithm for severely incomplete data. The design of the data acquisition and processing system is completed based on the Monte Carlo simulation detector design and the actual measurement environment of the tomb site. Figure 7 The schematic diagram of the electronic construction of a detector is shown as an example, specifically using 1cm 2 The plastic scintillator of 1m × 1m is used as the detection unit, and the optical fiber with a diameter of 1mm runs through the middle to output the light signal to the 6mm 2Silicon photomultiplier (SiPM) uses a 32-channel application-specific integrated circuit (ASIC) to read the SiPM output signal, which is converted into a digital signal by a 16-channel analog-to-digital converter (ADC) and then processed by a field programmable gate array (FPGA). The entire detector device will include three layers of detectors, with two sets of detector arrays on each layer. The effective detection area of ​​each set of detectors is 1m 2 , including 100 plastic scintillator detection units, 3 SiPMs, 4 ASICs, and 7 ADCs. Therefore, each detector device has a total of 600 plastic scintillator detection units, 18 SiPMs, 24 ASICs, 42 ADCs, and 1 FPGA processor to realize the data acquisition and processing process.

[0061] On this basis, according to the detector measurement guidance plan obtained by Monte Carlo simulation, historical documents and the ROI (region of interest) where the tomb STU is most likely to be located during on-site survey, three sets of low-noise muon absorption imaging detection devices developed by the present invention were placed around the tomb to construct the final actual measurement plan and obtain detection data; finally, the measured data were analyzed and processed, and compared and verified with the simulation results in the Monte Carlo simulation, ultimately achieving three-dimensional imaging of the tomb's internal structure STU of the burial mound, tomb passage and underground palace structure, and establishing corresponding archaeological and cultural protection plan countermeasures.

[0062] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0063] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of the claims of the present invention.

Claims

1. A non-destructive detection method for tombs, characterized in that: Includes steps: Determine the energy loss curve of muons in the tomb; Construct a system parameter model based on the tomb shape data; Generate an initial muon model; A muon transport model is constructed based on the energy loss curve of the muon in the tomb, the system parameter model and the initial muon model; A muon detector is set outside the tomb to detect the flux change after the muon interacts with the tomb absorption; The three-dimensional density image inside the tomb is reconstructed based on the muon data acquired by the muon detector and the muon transport model.

2. The non-destructive detection method for tombs according to claim 1 is characterized in that: The tomb shape data is obtained through remote sensing technology.

3. The non-destructive detection method for tombs according to claim 1 is characterized in that: The initial muon model is generated by modifying the empirical formula model.

4. The non-destructive detection method for tombs according to claim 1, characterized in that: The muon transport model is constructed based on the scattering subtraction model of muons in tombs.

5. The non-destructive detection method for tombs according to claim 1 is characterized in that: The step of reconstructing the three-dimensional density image inside the tomb includes first reconstructing the image under a single perspective, and then further performing multi-perspective reconstruction based on the single-perspective reconstruction result.

6. The non-destructive detection method for tombs according to claim 5 is characterized in that: The core theory of the multi-view reconstruction is compressed sensing.

7. A non-destructive detection system for tombs, characterized in that: Set outside the tomb, including: A tomb shape data measuring device, used for non-destructive measurement of tomb shape data; The muon detection device is used to detect the flux change data after the muon interacts with the tomb absorption; A data processing device, used to determine the energy loss curve of muons in the tomb, construct a system parameter model based on the tomb shape data, generate an initial muon model, and construct a muon transport model based on the energy loss curve of muons in the tomb, the system parameter model and the initial muon model; An image reconstruction device is used to reconstruct a three-dimensional density image inside the tomb based on the muon data and the muon transport model.

8. The non-destructive detection system for tombs according to claim 7, characterized in that: The muon detection device includes a plurality of groups of muon detectors distributed around the tomb.

9. The non-destructive detection system for tombs according to claim 8, characterized in that: Each group of muon detectors includes a three-layer muon detection array.

10. The non-destructive detection system for tombs according to claim 9, characterized in that: Each layer of the muon detection array includes two groups of vertically placed plastic scintillator muon detection unit arrays.

11. The non-destructive detection system for tombs according to claim 10, characterized in that: A layer of heavy metal material reflector is arranged between the two groups of plastic scintillator muon detection unit arrays.

12. The non-destructive detection system for tombs according to claim 10, characterized in that: The cross section of the plastic scintillator muon detection unit is square, triangular, circular or hexagonal.

Images