Intelligent identification method and system based on meteorite authentication system

Abstract

The application discloses an intelligent identification method and system based on a meteorite authentication system. The method first performs quantitative detection of physical indexes such as specific gravity, hardness and magnetism on samples according to an authoritative meteorite authentication system to complete preliminary screening; then, at least one precision detection is performed on the samples screened, including microscopic structure, element composition, quantum physical characteristics or isotope tracing detection, to obtain precision data; finally, the meteorite authentication system is taken as a core judgment basis, the preliminary screening result is intelligently fused with the precision detection data, and a final identification result of the sample is output. The method establishes a standardized identification process with the authoritative authentication system as the core and multi-level detection data as the support, and effectively improves the authority, coverage range and accuracy of the conclusion of the meteorite identification.

Description

Technical Field

[0001] This invention relates to the fields of astromineralogy, meteorite identification, and multi-technology fusion analysis, and particularly to an intelligent identification method and system based on a meteorite authentication system. Background Technology

[0002] Currently, meteorite identification primarily relies on a combination of traditional techniques such as compositional analysis and microscopic observation. Conventional methods typically use a single chemical indicator, such as nickel content, as a key criterion, combined with empirical observation of morphology elements like the fusion crust and regmaglypts under a microscope. For more in-depth analysis, instrumental techniques such as X-ray fluorescence spectroscopy, scanning electron microscopy, and even oxygen isotope analysis are employed. However, the application of these techniques often depends on the experience of the identification personnel for selection and combination, lacking a systematic framework for integrating the various test data. Essentially, it is an identification model based on expert experience and employing multiple techniques piecemeal.

[0003] Existing technological solutions have gradually revealed multiple problems in practical applications. First, the identification process lacks a unified, authoritative, and quantifiable core knowledge system as its guiding principle. Over-reliance on single standards such as "nickel content" is insufficient to cover scientifically proven new types like nickel-free meteorites, while the determination of physical characteristics such as fusion crust, specific gravity, and hardness has long lacked standardized norms, resulting in a highly subjective and low-repeatability identification process. Second, various testing technologies are fragmented, failing to form a standardized hierarchical process from macroscopic physical screening to microscopic structural verification and precise elemental and isotopic analysis. This creates standard gaps and technical blind spots in the identification of special types such as ultralight meteorites and rare earth meteorites. Most importantly, multi-source heterogeneous data such as macroscopic experience, physical data, microscopic images, and elemental spectra are isolated and cannot be effectively integrated and intelligently interpreted based on a core knowledge framework. This leads to low identification efficiency, opaque conclusion formation, difficulty in dealing with high-quality counterfeits, and ultimately weakens the authority and credibility of identification conclusions in serious scenarios such as scientific research, collection, and the judiciary. In summary, due to inherent deficiencies in core standards, process integration, and data fusion, existing technologies are no longer sufficient to meet the industry's demand for efficient, accurate, and authoritative identification of all types of meteorites.

[0004] Therefore, there is an urgent need in this field to develop a highly integrated and reliable identification method for all types of meteorites. Summary of the Invention

[0005] To improve existing methods and systems, firstly, this application provides an intelligent identification method based on a meteorite authentication system, including: S1: Based on the meteorite certification system, perform quantitative testing on meteorite samples based on physical indicators to generate physical indicator test results; compare the physical indicator test results with the meteorite certification system to generate preliminary screening results for the samples; S2: Based on the preliminary screening results, perform at least one precision test on the meteorite samples that have passed the preliminary screening, and output the precision test data corresponding to the precision test type; S3: Combining preliminary screening results, precise testing data, and meteorite certification system, with the meteorite certification system as the core criterion, the preliminary screening results and precise testing data are integrated and processed to output the final identification result based on the meteorite sample.

[0006] In some embodiments, in step S1, the quantitative detection of physical indicators includes the detection of the specific gravity, hardness, and magnetism of the meteorite sample.

[0007] In some embodiments, The criterion for specific gravity testing is: 7.0 to 8.0 g / cm³ for iron meteorites. 3 Rare earth meteorites have a density of 3.0 to 3.8 g / cm³. 3 The density of stony meteorites ranges from 2.9 to 3.8 g / cm³. 3 Tektites have a density of 2.2 to 2.8 g / cm³. 3 Ultralight meteorites have a density of less than or equal to 2.2 g / cm³. 3 ; Hardness determination standard: The Mohs hardness of natural meteorites is 5~7; Magnetic determination criteria: Iron meteorites are strongly magnetic, stony meteorites are weakly magnetic, and nickel-free meteorites, tektites, and ultralight meteorites are non-magnetic or extremely weakly magnetic.

[0008] In some embodiments, in step S2, the precision detection includes at least one of the following detection types: microstructure detection, elemental composition detection, quantum physical property detection, and isotope tracing detection.

[0009] In some embodiments, the threshold for element composition detection includes: For nickel-bearing meteorites, the mass percentage of nickel should be greater than or equal to 5%; For nickel-free meteorites, the mass percentage of nickel should be less than 0.1%; For glassy meteorites, the mass percentage of silicon dioxide should be greater than or equal to 70% and the mass percentage of nickel should be less than 0.1%. For rare earth meteorites, the content of at least one rare earth element in a rare earth meteorite is greater than or equal to three times the average content of at least one rare earth element in terrestrial rocks.

[0010] In some embodiments, the detection of quantum physical properties includes at least one of the following techniques: Quantum magnetic detection based on diamond nitrogen-vacancy color centers; Quantum gravity detection based on cold atom interferometry; Quantum coherent Raman spectroscopy detection.

[0011] In some embodiments, isotope tracing detection includes oxygen isotope and cosmogenic nuclide detection of meteorite samples.

[0012] In some embodiments, the microstructure detection is performed using an electron microscope, and the detection parameters used include: accelerating voltage, magnification, and working distance.

[0013] In some embodiments, the fusion process is performed using a weighted decision model, wherein the meteorite authentication system has a higher weight than the preliminary screening results and the detailed testing data of the samples.

[0014] Secondly, this application provides an intelligent identification system based on a meteorite authentication system, used to implement the method in any of the above embodiments, including: The database module is configured to store and provide relevant data for the meteorite authentication system; The physical index detection and screening module, connected to the database module, is configured to perform quantitative detection of physical indexes on meteorite samples to generate physical index detection results, and compare the physical index detection results with the specifications of the meteorite certification system to generate preliminary screening results for the samples. The precision detection module, connected to the physical index detection and screening module, is configured to perform at least one precision detection on meteorite samples that have passed the preliminary screening based on the sample preliminary screening results, and generate sample precision detection data. The intelligent judgment module, connected to the database module, physical index detection and screening module, and precision detection module, is configured to obtain the conclusions of the meteorite certification system, and receive the preliminary screening results and precision detection data of the sample for fusion processing and output the final identification result of the sample.

[0015] The technical solution of this invention is an intelligent identification method centered on an authoritative meteorite certification system. This method first performs standardized quantitative testing and preliminary screening of physical indicators such as specific gravity, hardness, and magnetism on the sample. Then, for samples that pass the screening, a systematic and precise test is performed on at least one of the following: microstructure, elemental composition, quantum physical properties, and isotope tracing, acquiring multidimensional data. Finally, using the expert conclusions of the meteorite certification system as the core judgment basis, an intelligent algorithm fuses and analyzes the preliminary screening results with the various precise test data to output the final identification result. This method integrates authoritative experience and knowledge, standardized physical testing, cutting-edge precision instruments, and intelligent interpretation, forming a closed-loop standardized process. Its beneficial effects are significant: First, with an authoritative system at its core, it greatly enhances the industry recognition and authority of the identification conclusions, applicable to multiple scenarios such as scientific research, transactions, and the judiciary. Second, through physical quantification, multimodal precise testing, and intelligent fusion, it achieves accurate identification of all categories, including nickel-bearing meteorites, nickel-free meteorites, ultralight meteorites, rare earth meteorites, and various types of tektites, with high accuracy and the ability to effectively distinguish high-quality counterfeits. Finally, the entire process has been standardized and made replicable, significantly reducing human subjective error and improving identification efficiency and consistency. Attached Figure Description

[0016] Figure 1 This is a flowchart of the intelligent identification method based on the meteorite authentication system proposed in this invention; Figure 2 This is a system architecture diagram of the intelligent identification method based on meteorite authentication proposed in this invention.

[0017] In the diagram: 1. Database module; 2. Physical index detection and screening module; 3. Precision detection module; 4. Intelligent judgment module. Detailed Implementation

[0018] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0019] Firstly, this application provides an intelligent identification method based on a meteorite authentication system, such as... Figure 1 As shown, it includes: S1: Based on the meteorite certification system, perform quantitative testing on meteorite samples based on physical indicators to generate physical indicator test results; compare the physical indicator test results with the meteorite certification system to generate preliminary screening results for the samples; S2: Based on the preliminary screening results, perform at least one precision test on the meteorite samples that have passed the preliminary screening, and output the precision test data corresponding to the precision test type; S3: Combining preliminary screening results, precise testing data, and meteorite certification system, with the meteorite certification system as the core criterion, the preliminary screening results and precise testing data are integrated and processed to output the final identification result based on the meteorite sample.

[0020] Meteorite identification is a crucial foundation of astromineralogy and planetary science. Its primary purpose is to accurately identify and scientifically classify fragments from extraterrestrial bodies. This work is not only vital for studying cutting-edge scientific questions such as the origin of the solar system and planetary evolution, but also has practical significance for meteorite collection, trading, and conservation. Because meteorites resemble certain terrestrial rocks or man-made objects, and imitations exist on the market, establishing systematic and reliable identification methods is essential. Based on their chemical composition, internal structure, and origin, meteorites can be mainly divided into three categories: stony meteorites (primarily composed of silicate minerals, the most common and accounting for the vast majority of discovered meteorites, further subdivided into chondrites and achondrites), iron meteorites (mainly composed of iron-nickel alloys, with high density and strong magnetism), and stony-iron meteorites (with silicates and metals roughly equal in proportion, relatively rare). In addition, there are some special types, such as tektites (mainly composed of silica glass) formed from meteorite impact events, and newly defined types that have attracted scientific attention, such as rare earth meteorites and ultralight meteorites.

[0021] The technical solution of this invention is specifically implemented through a process-oriented system with an industry-recognized meteorite authentication system as its absolute core and decision-making guideline. For example... Figure 1 As shown, the starting point of this method (step S1) is to screen samples strictly according to the standardized and quantifiable physical indicators within the system. This is not a simple data measurement, but rather an active diagnosis guided by the system. Specifically, the examiners first conduct visual verification based on the standardized descriptions of macroscopic features such as fusion crust, regmaglypts, and flow lines in the system to rule out obvious signs of artificial forgery. Subsequently, a systematic quantitative test of specific gravity, Mohs hardness, and magnetism is performed, and the measured data are compared with pre-set threshold standards within the system for different meteorite types (such as iron meteorites, stony meteorites, tektites, ultralight meteorites, and rare earth meteorites). For example, if a sample density ≤ 2.2 g / cm³ is detected... 3 Furthermore, the absence of magnetism initially points to the possibility of an ultralight meteorite. The reason for this step is that it uses standardized and repeatable physical measurements to objectify and quantify the traditional macroscopic identification process that relies on subjective experience. This efficiently filters out a large amount of terrestrial material that clearly does not conform to the basic physical characteristics of meteorites, allowing for more costly and precise subsequent testing to focus on genuine candidate samples, thereby improving the efficiency and economy of the overall identification process.

[0022] After initial screening, the method proceeds to step S2, which triggers one or more precision detection modules based on the initially identified meteorite type. The core of this step lies in its selective use of advanced technologies—not a fixed or random combination of techniques, but rather a targeted selection of the most effective technologies to verify or refine the initial assessment, guided by the logic of the certification system. For example, for samples suspected of being rare-earth meteorites, the "Full Spectrum Non-Destructive Testing of 80 Known Earth Elements" module can be invoked. This module uses handheld XRF and LIBS integrated equipment to acquire ppm-level elemental data from magnesium to uranium, focusing on verifying whether rare-earth elements (such as La, Ce, and Nd) are significantly enriched. Simultaneously, "Quantum Resonance Fingerprint Detection" can be used to match the spectral characteristics with a standard meteorite quantum database. For samples with unique structures, field emission scanning electron microscopy is used to observe their microscopic melting structure, mineral phases, or interface bonding characteristics under specific parameters. Furthermore, to confirm the origin of the celestial body, secondary ion mass spectrometry can be used for oxygen isotope analysis. The purpose of these precision testing modules is to obtain in-depth, high-precision objective data from multiple cross-verifying dimensions such as elemental composition, microstructure, physical properties, and isotopic "fingerprints" to compensate for the shortcomings of macroscopic physical screening and provide solid scientific data support for the final judgment, especially for identifying highly realistic artificial artifacts or confirming rare meteorite types.

[0023] Finally, in step S3, this method integrates data and knowledge from all levels through an intelligent weighted fusion judgment model. The key to this step lies in its processing logic: it doesn't treat all data equally, but explicitly uses the meteorite authentication system as the core judgment criterion. At the algorithm level, this is reflected in setting the expert experience and rules embedded in the authentication system as the highest weight, with preliminary screening results and various precise test data serving as input variables and supporting evidence. The model then performs comprehensive analysis, cross-validation, and conflict resolution. For example, when elemental analysis shows extremely low nickel content (not meeting traditional iron meteorite standards), but quantum magnetic detection shows a unique micro-domain magnetic distribution, and oxygen isotope analysis indicates an extraterrestrial origin, the model, guided by the authentication system's rule regarding the existence of nickel-free meteorite types, will comprehensively consider the microscopically observed impact characteristics and ultimately determine it as a nickel-free meteorite rather than a terrestrial rock. The reason for this fusion processing mechanism is to solve the problems of isolated data and conclusions relying on subjective expert synthesis in traditional identification methods. It dynamically combines core knowledge systems with multi-source heterogeneous data through algorithms, and outputs a standardized and structured conclusion that includes the authenticity of meteorites, their specific type, the origin of the celestial body, and the confidence level of the identification. This makes the identification process traceable and reproducible, and the conclusion more objective and authoritative.

[0024] This technical solution constructs a complete closed loop of "core knowledge system-driven, multi-level testing and verification, and intelligent data fusion." Its beneficial effects are systematic and progressive: First, through the standardization of physical indicators and preliminary screening, efficient filtering and standardization of the front end of the process are achieved. Second, through configurable precision testing combinations, full coverage and high-precision characterization of the deep characteristics of all types of meteorites (from conventional to ultralight, rare earth, and other special types) are achieved. Finally, through intelligent fusion judgment centered on an authoritative system, a leap from fragmented data to highly credible conclusions is achieved, ensuring a significant improvement in the scientific rigor, authority, and consistency of the identification conclusions, thereby effectively serving high-standard application scenarios such as scientific research, collectible authentication, and forensic identification.

[0025] In some embodiments, in step S1, the quantitative detection of physical indicators includes the detection of the specific gravity, hardness, and magnetism of the meteorite sample.

[0026] In this embodiment, the specific technical implementation of step S1 involves transforming the qualitative experience regarding macroscopic physical characteristics in the meteorite authentication system into a standardized testing process that allows for precise measurement and threshold determination. This step is the fundamental filtering stage of the entire method. Its core purpose is to efficiently screen out a large number of terrestrial rocks or artificial artifacts that clearly do not conform to the basic characteristics of meteorites through rapid and non-destructive physical measurements, thereby concentrating limited precision testing resources on high-probability samples. In practice, the appraisers first conduct a standardized visual inspection of macroscopic morphology such as fusion crust and regmaglypts according to the authentication system. Subsequently, the quantitative testing of three core physical indicators begins: First is the specific gravity test, which typically uses the Archimedes displacement method, employing a precision electronic balance to measure the mass difference of the sample in air and water, thereby calculating its density. The result is then compared with a preset threshold within the system; for example, a density of 2.0 g / cm³ is measured. 3 The sample will be affected because its value is less than or equal to 2.2 g / cm³. 3 The initial screening process points to "ultralight meteorites." The next step is hardness testing, using a standard Mohs hardness tester to scratch different parts of the sample. Natural meteorites generally have a Mohs hardness between 5 and 7, while tektites are further narrowed to a narrower range of 5.5 to 6.5. A sample with a hardness of 4 might be questioned at this stage. Finally, magnetic testing is performed using a strong neodymium magnet or a high-sensitivity magnetometer. The results serve as an important basis for classification; for example, a strongly magnetic sample might indicate the possibility of an iron meteorite, while non-magnetic or very weakly magnetic samples might be associated with nickel-free meteorites, tektites, or ultralight meteorites. The entire S1 step essentially encodes the expert knowledge of the certification system into a series of "if-then" judgment logics, such as "if the sample specific gravity is ≤2.2 g / cm³..." 3If it is non-magnetic, the preliminary screening result is "suspected ultralight meteorite", thus generating a structured preliminary screening result and providing a clear decision-making basis for the selection of detection paths in subsequent steps.

[0027] The design of step S1 brings several significant benefits. Its most direct effect is a substantial improvement in the efficiency and objectivity of the initial identification process. By transforming the subjective, "intuitive" macroscopic feel and perception, which rely on personal experience, into three quantifiable and repeatable physical parameters—specific gravity, hardness, and magnetism—with clearly defined numerical thresholds, it fundamentally reduces subjective arbitrariness and human error in the initial identification stage. This makes the screening process standardized and uniform, allowing any trained operator to follow the standard procedure and obtain consistent results. Secondly, this step acts as a highly efficient "pre-filter," quickly eliminating samples whose basic physical properties differ significantly from meteorites. For example, a sample with a density far below 2.2 g / cm³... 3 Rocks with a hardness far below 5 can almost immediately be identified as non-meteorites, eliminating the need for costly and time-consuming electron microscopy or isotope mass spectrometry analysis, thus saving overall identification costs and time. More importantly, the preliminary screening result is not a simple "yes / no" conclusion, but rather structured data with type-specific characteristics. For example, a preliminary determination of "suspected rare earth meteorite" directly triggers subsequent precise testing procedures focusing on full-spectrum analysis of rare earth elements and observation of microscopic mineral inclusions. This preliminary triage mechanism based on physical indicators transforms the entire multi-step identification method from a "production line" where all samples must undergo all tests into a dynamic process with intelligent guidance and optimized resource allocation, laying a solid foundation for ultimately achieving rapid and accurate identification of all categories.

[0028] In some embodiments, The criterion for specific gravity testing is: 7.0 to 8.0 g / cm³ for iron meteorites. 3 Rare earth meteorites have a density of 3.0 to 3.8 g / cm³. 3 The density of stony meteorites ranges from 2.9 to 3.8 g / cm³. 3 Tektites have a density of 2.2 to 2.8 g / cm³. 3 Ultralight meteorites have a density of less than or equal to 2.2 g / cm³. 3 ; Hardness determination standard: The Mohs hardness of natural meteorites is 5~7; Magnetic determination criteria: Iron meteorites are strongly magnetic, stony meteorites are weakly magnetic, and nickel-free meteorites, tektites, and ultralight meteorites are non-magnetic or extremely weakly magnetic.

[0029] In the specific technical implementation of this embodiment, the core of the physical index quantification detection relied upon in step S1 lies in transforming the knowledge of the physical characteristics of various meteorites in the meteorite certification system into a set of standardized detection operations with clear numerical thresholds that can be objectively executed. This transformation turns the originally fuzzy judgment based on experience into a scientific measurement that can be repeatedly verified step by step. In practice, each test corresponds to a specific instrument and method. For example, specific gravity testing usually uses the classic Archimedes' displacement method, using an analytical balance with an accuracy of 0.001 grams to measure the mass of the meteorite sample in air and when it is completely immersed in distilled water, and calculates its density value. Directly comparing this measured density with the judgment standard specified in the claims is the basis for subsequent logical judgment: if the measured value is 7.5 g / cm³... 3 If so, its weight in an iron meteorite is 7.0 to 8.0 g / cm³. 3 The range becomes a strong indicator of evidence; if the measured value is 2.1 g / cm³. 3 Then it meets the requirement of being an ultralight meteorite (≤2.2 g / cm³). 3 The criteria for determining the hardness of a sample are established to guide the identification process towards subsequent analysis specific to that type. Hardness testing is performed using a Mohs hardness tester. A standard mineral is used to scratch multiple different surfaces of the sample (such as the fusion crust and fracture surface), and the presence of scratches is observed to determine its Mohs hardness value. The criterion "5-7 for natural meteorites" plays a crucial screening and verification role here; a sample with a hardness of 4 will be seriously questioned because it is significantly below this lower limit. Magnetic testing is more intuitive but also requires standardization, typically using strong neodymium magnets or high-sensitivity gaussmeters. During the operation, it is necessary not only to observe whether the magnet is attracted but also to assess the magnitude and range of the attraction to distinguish between "strong magnetism" (such as iron meteorites, which are firmly attracted by magnets), "weak magnetism" (such as ordinary stony meteorites, which only have a slight attraction), and "non-magnetic or extremely weak magnetism" (such as tektites, which show no reaction to magnets). These three tests together form a rapid, non-destructive preliminary screening triangle. Any significant deviation of any indicator from the certification system standards may lead to the sample being prematurely excluded or marked as requiring special attention.

[0030] Implementing this standardized physical testing method based on clearly defined numerical thresholds has yielded several significant benefits. The primary benefit is the objectification and de-empiricalization of the initial stage of the identification process. Subjective descriptions such as "feels heavy," "feels hard," and "slightly magnetic" are precisely translated into "7.5 g / cm³". 3The quantitative screening process utilizes recordable and verifiable data such as "Mohs hardness 6" and "strong magnetism," which are compared against publicly available and standardized criteria. This significantly reduces subjective biases introduced by differences in personal experience among different appraisers, ensuring the consistency and impartiality of the screening basis. Secondly, this quantitative screening greatly improves the overall efficiency and economy of the identification process. Specific gravity, hardness, and magnetism tests can all be completed quickly and at extremely low cost. As a highly efficient filter, they can rapidly eliminate common terrestrial rocks or artificial materials whose basic physical properties are significantly inconsistent with the common characteristics of meteorites. This avoids sending all samples indiscriminately to expensive and time-consuming precision testing procedures such as electron microscopy and mass spectrometry, thus saving considerable time and money. Cost. Finally, this set of physical indicators is not only used for "filtering," but also for "preliminary classification" and "guidance." The combination of numerical results obtained from the preliminary screening can generate a structured preliminary conclusion, such as "high density, strong magnetism" pointing to iron meteorites, and "low density, non-magnetic" pointing to ultralight or tektites. This preliminary conclusion will serve as a key input, intelligently guiding the subsequent step S2 to select the most targeted combination of precision testing (for example, prioritizing full-spectrum elemental analysis for suspected rare earth meteorites), thus shifting the entire identification process from initial "general screening" to subsequent "precision testing," forming a logically coherent and resource-optimized intelligent identification path. This lays a solid and reliable data foundation and process framework for ultimately achieving high-precision and high-efficiency identification of all types of meteorites.

[0031] In some embodiments, in step S2, the precision detection includes at least one of the following detection types: microstructure detection, elemental composition detection, quantum physical property detection, and isotope tracing detection.

[0032] The specific technical implementation of step S2 in this embodiment is reflected in the intelligent invocation of one or more high-precision detection modules from a multimodal precision detection "toolbox" based on the suspected type indicated by the preliminary screening results, to perform deeper characterization and analysis of the sample. This design allows the identification process to naturally transition from rapid physical screening at the front end to confirmatory precision analysis at the back end, forming a progressive technical chain from "surface" to "point," from "macroscopic speculation" to "microscopic evidence." In practical implementation, each detection type corresponds to specific cutting-edge instruments and analytical methods. For example, for a sample that the preliminary screening suggests may be a "rare earth meteorite," the system will prioritize calling the "elemental composition detection" module. This module is not ordinary elemental analysis, but uses a customized full-spectrum detector that integrates handheld X-ray fluorescence spectroscopy, laser-induced breakdown spectroscopy, and Raman spectroscopy. It can simultaneously acquire the content data of 80 terrestrial elements, from magnesium to uranium, without damaging the sample, with a detection accuracy of up to ppm level. The operator points the probe at a typical area of ​​the sample, and the device can quickly generate a full-element spectrum. By analyzing the characteristic peaks and intensities of rare earth elements such as lanthanum, cerium, and neodymium in the spectrum and comparing them with the average background values ​​of terrestrial rocks, it is possible to accurately verify whether rare earth elements are abnormally enriched, thus providing core elemental chemical evidence for the identification of "rare earth meteorites".

[0033] Another example is for samples with unique structures, such as suspected "Xinjiang sighted colored glass meteorites" or samples with questionable internal structures, in which the "microstructure detection" module is activated. This module mainly relies on a high-resolution field emission scanning electron microscope (FESEM). During operation, the sample needs to be prepared into a suitable observation area and placed in the electron microscope sample chamber. Under specific accelerating voltages and working distances, the magnification is adjusted to thousands or even tens of thousands of times, allowing clear observation of the microscopic morphology of the sample surface. Identifiers can use this to verify the presence of the dense fusion crust and transition layer unique to natural meteorites, formed by high-temperature melting, observe whether the interior is a homogeneous glass structure or contains incompletely melted mineral fragments, and check whether the inner walls of the regmaglypts are covered with natural melting and cooling textures rather than artificial polishing marks. This direct observation at the microscale provides irrefutable morphological evidence for determining whether it has undergone a high-temperature melting process in space. Furthermore, for cases requiring extreme precision to distinguish between naturally formed and top-quality imitations, or to detect hidden internal defects, the "quantum physical property detection" module can be activated. For example, quantum magnetometers based on diamond nitrogen-vacancy color centers can achieve sensitivity at the femtotes level, enabling them to map extremely weak magnetic domain distributions on the sample surface at the micrometer scale. Natural iron meteorites, due to their unique Widmanstätten structure, exhibit a distinctive and uniform pattern of magnetic domain distribution, while artificially smelted iron blocks or forgeries display a chaotic distribution. By comparing the detected quantum magnetic signals with a standard meteorite database, an extremely sensitive "identity fingerprint" can be provided at the level of the material's most fundamental physical properties—a capability that traditional detection methods struggle to achieve.

[0034] Implementing this flexible and configurable precision testing scheme, triggered by preliminary screening results, has yielded rich and robust beneficial effects. Its primary effect is a significant improvement in the depth, accuracy, and confirmability of identification. While preliminary physical screening is efficient, it only provides directional clues and cannot offer a final conclusion. The precision testing in step S2, however, delves deeper into verifying these clues. Whether it's the "chemical identity card" provided by elemental full-spectrum analysis, the "structural formation history" revealed by microscopic electron microscopy, the "physical intrinsic fingerprint" detected by quantum sensing, or the "cosmic birth certificate" traced by isotope analysis, they all provide solid and objective data support for determining the authenticity and type of meteorites from different, independent, yet mutually corroborating scientific dimensions. This frees the identification conclusion from dependence on a single indicator, establishing it on a solid foundation of cross-verification through multiple evidence chains, thus greatly enhancing its authority. Secondly, this design achieves optimal allocation of identification resources and intelligent guidance of the process. Not every sample needs to undergo all four precision tests; that would be time-consuming and expensive. Based on the preliminary screening results, such as "suspected iron meteorite" or "suspected tektite," the system intelligently selects the most relevant and effective combination of tests for in-depth verification. For example, for a suspected iron meteorite, quantum magnetic detection and nickel content analysis may be prioritized; for a suspected lunar meteorite, isotope tracing testing must be initiated. This "testing according to the sample" model significantly improves the efficiency of high-end testing equipment, shortens the overall identification cycle of a single sample, and achieves the best balance between cost and benefit while ensuring the accuracy of the conclusions. Ultimately, the "precise sample detection data" generated in step S2 and the "preliminary screening results" in step S1 together constitute a multi-level, multi-modal evidence system, providing comprehensive and high-quality input for the intelligent fusion judgment in step S3, thus jointly ensuring that the final identification results have both high scientific rigor and practical feasibility.

[0035] In some embodiments, the threshold for element composition detection includes: For nickel-bearing meteorites, the mass percentage of nickel should be greater than or equal to 5%; For nickel-free meteorites, the mass percentage of nickel should be less than 0.1%; For glassy meteorites, the mass percentage of silicon dioxide should be greater than or equal to 70% and the mass percentage of nickel should be less than 0.1%. For rare earth meteorites, the content of at least one rare earth element in a rare earth meteorite is greater than or equal to three times the average content of at least one rare earth element in terrestrial rocks.

[0036] In this embodiment, the specific implementation of elemental composition detection relies on a highly integrated "full spectrum analyzer for 80 known Earth elements." This device typically integrates three technologies: handheld X-ray fluorescence spectroscopy, laser-induced breakdown spectroscopy, and Raman spectroscopy. Its core advantage lies in its ability to perform rapid, simultaneous, and non-destructive screening of 80 elements, from magnesium to uranium, without damaging the sample, achieving a detection accuracy at the ppm level. In practice, the examiner aligns the instrument's probe with a clean, typical area of ​​the meteorite sample (such as a fresh fracture surface or fusion crust). After initiating the detection, the device generates a full spectrum containing the characteristic peaks and intensities of all elements within a short time. At this point, the clearly defined thresholds set in the claims become the core criteria for the automated analysis software to perform preliminary classification. For example, when the software automatically calculates that the mass percentage of nickel is 7%, since this value is greater than or equal to the 5% threshold, the system will immediately mark it as "meeting the characteristics of nickel-bearing meteorites" and may further verify auxiliary parameters such as its nickel-cobalt ratio. Conversely, if the measured nickel content is only 0.05% (less than 0.1%), it meets the threshold of "nickel-free meteorites," which will guide the analysis program to focus on examining the ratios of other elements such as silicon-aluminum ratio and magnesium-iron ratio to determine whether it may belong to a lunar or Martian meteorite. For samples with special appearances, the system will simultaneously evaluate the content of silicon and nickel. If the silicon dioxide content is as high as 75% and the nickel content is close to zero, it simultaneously meets the dual thresholds of glassy meteorites, and is further corroborated by the spectral peaks of characteristic trace elements such as titanium and zirconium. The identification of rare earth meteorites is even more precise. The analysis software calls on the built-in crustal element abundance database to compare the content of each rare earth element, such as lanthanum, cerium, and neodymium, with the corresponding crustal average in real time. If the measured content of any rare earth element reaches three times or more of the crustal average, it will trigger an alert of "abnormal enrichment of rare earth elements", providing key chemical composition basis for the identification of rare earth meteorites.

[0037] Setting and applying this precise set of elemental composition detection thresholds has brought about fundamental and multi-layered beneficial effects. Its most direct effect is the objectification, quantification, and standardization of meteorite chemical composition determination, completely changing the one-sided approach of traditional identification that overly relies on the single indicator of "nickel content." By establishing differentiated and quantifiable elemental thresholds for different types of meteorites, such as nickel-containing, nickel-free, glassy, ​​and rare-earth-containing meteorites, elemental analysis has been transformed from a general "detection" tool into a precise "determination" system. For example, a 5% nickel threshold clearly distinguishes typical iron meteorites from low-nickel terrestrial rocks, while the combination of a 0.1% nickel threshold and a 70% silica threshold provides a clear and operable chemical benchmark for accurately identifying nickel-free stony meteorites and glassy meteorites. Secondly, this determination system based on multi-element thresholds greatly expands the coverage and accuracy of identification. This system not only upholds the traditional standards for identifying nickel-bearing meteorites, but more importantly, by formally recognizing "nickel content less than 0.1%" as a legitimate type (nickel-free meteorites) and establishing an independent standard of "rare earth element content several times higher than the Earth's crust average," it scientifically accepts and standardizes rare meteorite categories previously excluded by older standards. This allows identification techniques to keep pace with the times and encompass the latest scientific discoveries. Finally, these thresholds act as a precise "chemical filter" and "classifier," providing structured, machine-readable key input data for the entire intelligent identification process. Initial screening may point to "suspected rare earth meteorites," while the elemental analysis, with its threshold comparison showing "rare earth element levels exceeding the standard by three times," constitutes strong confirmatory evidence. This evidence will be corroborated by subsequent microscopic analysis of rare earth mineral inclusions, and together input into the final intelligent fusion judgment model. This ensures that the final identification conclusion is based on a cross-dimensional, verifiable chain of quantitative evidence, significantly enhancing the scientific rigor, authority, and repeatability of the identification work.

[0038] In some embodiments, the detection of quantum physical properties includes at least one of the following techniques: Quantum magnetic detection based on diamond nitrogen-vacancy color centers; Quantum gravity detection based on cold atom interferometry; Quantum coherent Raman spectroscopy detection.

[0039] In this embodiment, the specific implementation of quantum physical property detection technology represents a leap forward in meteorite identification, moving beyond traditional composition and morphology analysis to the detection of intrinsic physical properties of matter. This type of detection does not directly measure elemental content or observe structure, but rather obtains intrinsic information, like a "physical fingerprint," by sensing the unique response of matter at the quantum scale. Among these, quantum magnetic detection based on diamond nitrogen-vacancy color centers relies on an artificial diamond sensor embedded with an NV color center (nitrogen-vacancy defect). When a laser illuminates and reads the quantum spin state of this color center, its state is extremely sensitive to extremely weak magnetic fields. During detection, scanning the meteorite sample surface with micrometer-level precision using the diamond sensor can create a microscopic magnetic domain distribution map with a sensitivity reaching femtotes. The unique Widmanstätten structure within natural iron meteorites forms regular, continuous magnetic domain patterns, while artificially smelted or pieced-together forgeries exhibit chaotic or abruptly defined magnetic domain distributions. Quantum coherent Raman spectroscopy is another technique based on a completely different principle. It utilizes two precisely phase-locked picosecond laser pulses to coherently excite the vibrations of sample molecules through quantum interference. This technique can greatly enhance the typically extremely weak Raman scattering signal and has extremely high temporal resolution. For meteorite samples, it can clearly resolve the specific chemical bond vibration frequencies of silicates, oxides, and other minerals, and even detect crystal defect characteristics caused by the extreme environment of space (such as rapid cooling and impact pressure). These spectral "fingerprints" are fundamentally different from those of terrestrial rocks or artificial glass. Furthermore, quantum gravity detection based on cold atom interference typically involves an ultra-high vacuum chamber where rubidium or cesium atomic clouds are cooled to near absolute zero using laser cooling technology, forming "cold atoms." When these cold atoms fall freely in a gravitational field, their matter waves undergo interference phase shifts due to local gravitational field changes caused by minute density differences within the sample. By measuring this phase shift, it is possible to detect the vibrations of meteorite samples at 10⁻⁶ ppm. -8 The astonishing precision of g allows for non-contact inversion of the mass distribution inside meteorite samples, accurately detecting hidden cavities, fissures, or areas of uneven density. This is crucial for distinguishing artificially injected, filled, or synthetic imitations.

[0040] The introduction of such cutting-edge quantum physical property detection brings revolutionary and beneficial effects to this method, unattainable by traditional techniques. Its core value lies in providing near-ultimate physical evidence for identification. First, the feta-tesla-level microscopic magnetic domain map provided by quantum magnetic detection acts like an unforgeable "magnetic identity card." No matter how realistic a high-quality imitation iron meteorite may be, its internal crystal structure cannot perfectly replicate the Widmanstätten structure formed by the slow cooling of the natural universe, thus revealing its true nature under the detection of a quantum magnetometer. This solves the problem of verifying the authenticity of internal structures that traditional magnetic detection (which only distinguishes between presence and absence or strength) cannot address. Second, cold atom quantum gravity detection achieves a kind of "non-destructive internal vision." Without cutting or destroying the sample, it can perceive its internal density uniformity with extremely high precision, directly revealing those seemingly perfect samples that have been artificially pieced together or filled to correct weight or hide flaws—a feat that X-rays or CT scans cannot match in terms of precision or principle. Finally, the information on chemical bonds and crystal defects provided by quantum coherent Raman spectroscopy reveals the "origins" of matter at the atomic and molecular vibration level. The unique space environment experienced by meteorites leaves distinctive "scars" (defects) in their mineral lattices. This information is encoded in the peak positions, shapes, and widths of Raman spectra, providing direct physicochemical evidence for determining their natural origin. By fusing and comparing this data with macroscopic physical indicators, microscopic morphology, and elemental composition data, a multidimensional, three-dimensional, and interconnected evidence network is constructed, encompassing macroscopic to microscopic levels, composition to structure, and intrinsic physical properties. This allows the final identification conclusion to go beyond simply identifying "what it is" (elements) and "what it looks like" (structure), delving deeper into "its physical nature." This significantly reduces the technical space for counterfeiters, fundamentally elevating the authority, anti-counterfeiting capabilities, and scientific rigor of the identification results to a new level. It is sufficient to withstand the most sophisticated counterfeiting challenges and meet the ultimate requirements for evidentiary conclusiveness in forensic identification and cutting-edge scientific research.

[0041] In some embodiments, isotope tracing detection includes oxygen isotope and cosmogenic nuclide detection of meteorite samples.

[0042] In this embodiment, the implementation of specific isotope tracing detection technology represents a decisive step in meteorite identification, moving from material composition analysis to tracing its origin and history. This detection aims to answer two core scientific questions: From which specific celestial body in the solar system did the sample originate? And how long did it travel in space and when did it fall to Earth? Its implementation relies on two highly precise mass spectrometry techniques. For determining the celestial body's origin, secondary ion mass spectrometry (SIMS) is primarily used for oxygen isotope analysis. In practice, a micron-scale thin slice is cut, ground, and polished from the meteorite sample and placed in the ultra-high vacuum sample chamber of the SIMS instrument. The instrument bombards specific mineral micro-areas (such as olivine or pyroxene) on the sample surface with a focused primary ion beam (such as cesium ions), sputtering secondary ions. These secondary ions are then precisely measured using a high-resolution mass analyzer to determine the ratios of the three stable isotopes: oxygen-16, oxygen-17, and oxygen-18. The ratios are calculated using Δ... 17 O (i.e. δ 17 O and 0.52×δ 18 The deviation value of O can yield a "fingerprint" that is almost unaffected by geochemical processes. For example, the Δ value of a nickel-free meteorite sample can be measured. 17 The O value is approximately +2.5‰, which is significantly higher than that of Earth rocks (approximately 0‰) and falls precisely within the known oxygen isotope data range for lunar meteorites, thus providing conclusive, laboratory-level evidence for their lunar origin.

[0043] To reveal the "history" of meteorites, cosmogenic nuclides are required, which is typically performed using an accelerator mass spectrometer. Cosmogenic nuclides (such as...) 10 Be、 26 Al、 36 Cl, etc., are rare isotopes formed when the atomic nuclei inside a meteorite parent body are bombarded by high-energy galactic cosmic rays during its exposure in space. The procedure is more complex. First, a certain amount of meteorite sample (usually in the gram range) needs to be dissolved, separated, and purified through a rigorous chemical process to extract the extremely low abundance of the target nuclide. Then, the prepared sample ion source is sent to an atomizing filter (AMS). In the AMS, ions are accelerated to millions of electron volts, and then screened by a combination of magnetic and electrostatic analyzers. Finally, a highly sensitive detector detects the extremely low abundance of the target nuclide (such as Cl, ... 10 The counting is performed by determining the current concentration of these radionuclides and utilizing their known half-lives (e.g., Be). 26 By calculating using Al's half-life of 717,000 years, we can deduce the time the meteorite was independently exposed to cosmic rays in interstellar space after separating from its parent body ("space exposure age"), and the time it was buried on Earth after falling to Earth ("terrestrial burial age"). For example, a specific concentration of Al was detected in an ordinary chondrite. 26 Al and10 Based on model calculations, it can be inferred that Be drifted in space for about 5 million years and crashed into the Sahara Desert 20,000 years ago.

[0044] Integrating this isotope tracing detection into the identification process brings irreplaceable and definitive benefits. Its primary contribution lies in providing the most authoritative "birth certificate" for the celestial origin of meteorites. Traditional identification methods rely on elemental and mineralogical characteristics, which sometimes have multiple interpretations, while oxygen isotope ratios (especially Δ...)... 17 O isotope (O) is an original, tamper-proof imprint left over from the accretion process of different planetesimals in the solar system. It can clearly distinguish meteorites from those from Mars, the Moon, Vesta, and different asteroid groups, thus providing crucial source region information for scientific research and ensuring that the identification conclusions meet the evidentiary standards required for publishing high-level academic papers. Secondly, the "age" information determined by cosmogenic nuclide detection constitutes the ultimate temporal benchmark for verifying its naturalness. A forgery may be able to imitate appearance, composition, and even microstructure perfectly, but it is impossible to artificially replicate the combination of multiple cosmogenic nuclide concentrations that precisely match a long history of cosmic ray exposure. Therefore, this detection is the "ultimate judge" for identifying top-quality forgeries and confirming the cosmogenic origin of samples. Finally, these isotope data, together with the aforementioned physical indicators, elemental composition, quantum properties, and other evidence, form a closed chain of evidence in both the temporal (age) and spatial (origin) dimensions. For example, for a nickel-free meteorite that is initially suspected and matches the elemental characteristics, the final oxygen isotope data definitively confirms its Martian or lunar origin; while the cosmic exposure age it carries becomes a key parameter for assessing its scientific rarity and value. This means that the conclusions output by this identification method not only answer the questions of "what it is" and "whether it's real," but also delve deeper into the scientific questions of "where it came from" and "what its history is," elevating the authority, depth, and core value of meteorite identification in serving scientific research to a whole new level.

[0045] In some embodiments, the microstructure detection is performed using an electron microscope, and the detection parameters used include: accelerating voltage, magnification, and working distance.

[0046] In this embodiment, the core of the microstructure detection technology lies in the standardized setting of electron microscope operating parameters according to the meteorite authentication system, in order to achieve repeatable and high-precision observation of the unique formation traces of meteorites. This detection is typically performed using a field emission scanning electron microscope or a high-resolution transmission electron microscope. Its implementation is not based on arbitrary instrument adjustments, but strictly adheres to a set of preset technical parameters: the accelerating voltage is typically set between 5 and 30 kV; lower voltages are suitable for observing non-conductive areas sensitive to the electron beam, such as the surface fusion crust, to prevent charge accumulation, while higher voltages are used for penetrating observation of internal mineral phases; the magnification covers a wide range from 50x to 10,000x, allowing the examiner to quickly scan the entire sample at low magnification, locate typical regmaglypts or flow lines, and then focus on observing the microscopic details of that area at high magnification of several thousandx; the working distance is typically controlled between 8 and 15 mm. This optimized distance range ensures a good geometric relationship between the electron beam and the signal detector, thereby obtaining high-resolution secondary electron or backscattered electron images. For example, when identifying a suspected "Xinjiang witnessed colored tektite," the operator first sets the working distance to 10 millimeters and searches for incompletely melted stony meteorite fragments that may be embedded in the glass matrix at 1000x magnification. After finding the target, the magnification is increased to 5000x, and the accelerating voltage is adjusted appropriately to obtain a clearer compositional contrast image, allowing for detailed observation of whether the interface between the fragment and the surrounding glass matrix is ​​naturally melted and infiltrated or contains artificially attached gaps. For ultralight meteorites, a systematic scan is performed at medium magnification to confirm whether they possess the porous, lightweight structure and natural distribution characteristics of pores described in the certification system.

[0047] The standardization and refinement of electron microscopy parameters have brought crucial and irreplaceable benefits to this method. Its fundamental value lies in transforming qualitative microscopic morphological observation, which relies on expert experience, into an objective, quantifiable, and reproducible scientific testing procedure. Uniform accelerating voltage, magnification, and working distance parameters ensure a high degree of consistency and comparability in observations of similar areas of the same sample by different operators at different times, greatly eliminating observational biases caused by arbitrary instrument settings. This allows the conclusion that "microscopic features conform to meteorite certification standards" to be based on standardized experimental data. Secondly, this parameterized, multi-level observation strategy enables identification to seamlessly penetrate from millimeter-level macroscopic morphology to the microscopic world at the micrometer and even nanometer levels, capturing decisive causal evidence. Whether it's the three-layered structure of the fusion crust—the dense fused layer, the transitional diffusion layer, and the original matrix—or the directional arrangement of molten mineral particles in the parallel flow lines of space under a microscopic level, or the fingerprint-like condensation textures on the inner wall of the regmaglypts, these features, which can only be clearly revealed under specific magnification and imaging conditions, are "ironclad evidence" of the meteorite's unique processes of high-speed, high-temperature melting and airflow etching in space. They are natural archives that are extremely difficult to replicate with any terrestrial rock or artificial artifact. Therefore, microscopic structure detection provides a set of intuitive, high-resolution image evidence chains, which complement elemental data (answering "what is the composition") and physical data (answering "what are the macroscopic properties") to form a multi-dimensional and comprehensive verification system. Ultimately, these standardized electron microscopic images and observational descriptions, as structured "precise sample detection data," are input into the subsequent intelligent fusion judgment model, ensuring that the final identification conclusion not only has the support of chemical composition but also direct proof of morphological origin, significantly improving the scientific rigor, objectivity, and the solidity of the evidence in the identification work.

[0048] In some embodiments, the fusion process is performed using a weighted decision model, wherein the meteorite authentication system has a higher weight than the preliminary screening results and the detailed testing data of the samples.

[0049] This integrated processing mechanism, which assigns the highest weight to the meteorite authentication system, brings fundamental and crucial benefits. Its primary and most direct effect is the complete resolution of the pain point in traditional authentication—"rich data but conflicting conclusions"—ensuring the authority and industry acceptance of the authentication results. By setting the industry-recognized expert system knowledge as the core of decision-making, the output of the intelligent model is essentially consistent with the logical judgment of authoritative experts. This ensures that the final authentication report is not a cold, impersonal data compilation, but a professional judgment with substance and evidence, directly applicable to scenarios with extremely high authority requirements, such as scientific research endorsement, high-end transactions, and forensic authentication. Secondly, this weighting allocation model achieves a highly efficient, knowledge-based "data management" capability. Faced with massive amounts of multi-source, heterogeneous, and even potentially conflicting testing data (such as physical, chemical, microscopic, and isotopic data), the model does not get lost in the data. Instead, it uses the knowledge framework of the authentication system as a "navigation map" to intelligently prioritize and correlate different pieces of evidence. The high-weighted system rules guide the model to grasp the main contradictions and essential characteristics (such as the unique Westerland structure), while placing secondary and unconventional data features (such as slightly lower nickel content) in a subordinate position that requires reasonable explanation. This simulates the thought process of human experts "grasping key evidence and reasonably interpreting anomalies," but is implemented in a standardized and reproducible algorithm, greatly improving the accuracy and efficiency of judgment in complex situations. Finally, this mechanism ensures the logical rigor and closed loop of the entire intelligent identification method. All data generated from steps S1 and S2 ultimately converge in step S3, where a final judgment is made in a unified court based on the highest professional standards (certification system). This not only makes the entire technical solution form a complete closed loop from data collection and verification to intelligent judgment, but also ensures that the final identification results have a high degree of objectivity, consistency, and interpretability, because any conclusion can be traced back to which core rule it was based on and which specific data was weighted and integrated, thereby elevating the practicality, reliability, and authority of this invention to a whole new level.

[0050] Secondly, this application provides an intelligent identification system based on a meteorite authentication system, used to implement the method in any of the above embodiments, such as... Figure 2 As shown, it includes: Database module 1 is configured to store and provide relevant data for the meteorite authentication system; The physical index detection and screening module 2, connected to the database module 1, is configured to perform quantitative detection of physical indexes on meteorite samples to generate physical index detection results, and compare the physical index detection results with the specifications of the meteorite certification system to generate preliminary screening results for the samples. The precision detection module 3, connected to the physical index detection and screening module 2, is configured to perform at least one precision detection on the meteorite samples that have passed the preliminary screening based on the preliminary screening results, and generate sample precision detection data. The intelligent judgment module 4 is connected to the database module 1, the physical index detection and screening module 2, and the precision detection module 3. It is configured to obtain the conclusions of the meteorite certification system, and receive the preliminary screening results and precision detection data of the samples for fusion processing and output the final identification results of the samples.

[0051] The intelligent identification system based on meteorite authentication provided in this application is specifically implemented in a hardware and software integrated architecture consisting of four core modules, with clearly oriented data and instruction flows. For example... Figure 2 As shown, the entire system is based on and centers on database module 1. This module is not simply a data warehouse, but an expert system storing a structured knowledge base of the "Meteorite Authentication System." It contains standardized data such as macroscopic characteristic descriptions of various meteorites, quantitative physical index thresholds (e.g., specific gravity, hardness range), standard microscopic spectra, elemental abundance patterns, and even quantum fingerprint characteristics. When the identification process is initiated, physical index detection and screening module 2 is activated first. This module integrates instruments such as a high-precision electronic balance (used for Archimedes' displacement method to measure specific gravity), a standard Mohs hardness tester, and a digital magnetometer. When the operator places the meteorite sample in this module, the system automatically executes the standardized measurement process. For example, when measuring a sample, the module automatically controls the balance to complete the mass and displacement volume measurement, calculating the density to be 3.5 g / cm³. 3 Simultaneously, the hardness tester reported a Mohs hardness of 6, and the magnetometer detected a weak magnetic signal. Subsequently, the processor inside module 2 immediately sends a query and comparison request to database module 1, displaying the measured value of "3.5 g / cm³". 3 The data set "hardness 6, weak magnetism" is matched against the specifications in the knowledge base. Through rapid comparison, database module 1 returns a matching conclusion: the physical characteristics of this set of physical characteristics conform to the specifications of the "stony meteorite" category. Based on this, module 2 generates a structured "preliminary screening result of the sample" -- for example, "Preliminary judgment: conforms to the physical characteristics of stony meteorites, elemental and microscopic analysis is recommended".

[0052] Following this, the preliminary screening result is sent as an instruction to the precision detection module 3. This module is a highly integrated, flexible detection platform, which may be equipped with various instruments such as a scanning electron microscope, a multi-technology fusion elemental analyzer, and a quantum magnetic sensing unit. The intelligence of module 3 lies in its ability to dynamically call upon the most relevant detection unit based on the received instruction. Continuing with the previous example, for the preliminary determination of a "stony meteorite," module 3 may prioritize scheduling its elemental analysis unit (such as a spectrometer integrating XRF and LIBS) to perform non-destructive scanning of the sample and quickly obtain its main elemental composition; simultaneously, it may schedule the scanning electron microscope to automatically image the fusion crust region of the sample according to the standard parameters provided by database module 1 (such as 15kV accelerating voltage, 2000x magnification). These detections are all completed automatically or semi-automatically under program control, and the generated data (such as "Ni=1.2wt%", "microscopic image shows clear three-layer structure of fusion crust") is packaged into "sample precision detection data." Finally, all data streams and initial instructions converge in the intelligent determination module 4. The core of this module is a fusion processing algorithm engine. It retrieves the complete judgment rules and weight settings for stony meteorites, especially those with potential subcategories (such as ordinary chondrites), from the "Meteorite Authentication System" in database module 1. Then, it receives preliminary screening results from module 2 and detailed testing data from module 3. Internally, the algorithm uses the authentication system rules as the highest-weighted decision framework to perform weighted analysis and conflict checking on all input data. For example, although elemental data shows that the nickel content (1.2 wt%) does not meet the typical high-iron meteorite standard, the rule for "ordinary chondrite" in the authentication system knowledge base has a higher weight, and this rule includes acceptance of this nickel content range. The algorithm comprehensively considers factors such as the microstructure confirming a natural fusion crust and the perfect match of physical indicators, calculates the confidence level, and finally outputs a structured "final identification result," such as "Identified as: Ordinary chondrite (H group), confidence level 98.7%," and automatically generates an identification report containing the key evidence chain.

[0053] The system's beneficial effects stem from its highly integrated, streamlined, and intelligent modular design. First, the database module 1 solidifies scattered and implicit expert knowledge into centralized, readily accessible digital standards, ensuring absolute consistency and authority of the identification criteria from beginning to end—something difficult to maintain consistently through any manual process. Second, the physical index detection and screening module 2 fully proceduralizes and objectifies the preliminary screening process, entrusting steps prone to human error to standardized instruments and algorithms. This not only significantly improves efficiency but also provides high-quality, structured trigger signals for subsequent steps. Third, the flexible integration and intelligent scheduling of the precision detection module 3 achieves optimal allocation of detection resources. It performs "on-demand detection" based on preliminary conclusions, avoiding the resource waste and time delays caused by blind or fixed-set detection in traditional processes, making targeted, in-depth analysis of rare or special meteorites possible. Finally, the fusion processing of the intelligent judgment module 4 is the value loop point of the entire system. Through its algorithm, it faithfully executes the principle of "authentication system as the core," transforming multi-source heterogeneous data into a clear, traceable, and highly confident identification conclusion. This fundamentally solves the problems of authority and consistency caused by the disconnect between data and conclusions and the reliance on individual judgments in traditional methods. In summary, this system transforms the methodology into a stable, reliable, and repeatable physical tool, bringing the standardization, efficiency, and high authority of meteorite identification from the theoretical level to the technical implementation level.

[0054] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0055] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0056] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent identification method based on a meteorite authentication system, characterized in that, The method includes the following steps: S1: Based on the meteorite certification system, perform quantitative testing on the meteorite sample based on physical indicators to generate physical indicator testing results; compare the physical indicator testing results with the meteorite certification system to generate preliminary screening results for the sample; S2: Based on the preliminary screening results of the samples, perform at least one precision test on the meteorite samples that have passed the preliminary screening, and output the sample precision test data corresponding to the precision test type; S3: Combining the preliminary screening results of the sample, the precise testing data of the sample, and the meteorite authentication system, with the meteorite authentication system as the core judgment basis, the preliminary screening results of the sample and the precise testing data of the sample are fused and processed to output the final identification result based on the meteorite sample.

2. The method according to claim 1, characterized in that, In step S1, the quantitative detection of the physical indicators includes the detection of the specific gravity, hardness, and magnetism of the meteorite sample.

3. The method according to claim 2, characterized in that, The specific gravity test criteria are as follows: for iron meteorites, it is 7.0 to 8.0 g / cm³. 3 Rare earth meteorites have a density of 3.0 to 3.8 g / cm³. 3 The density of stony meteorites ranges from 2.9 to 3.8 g / cm³. 3 Tektites have a density of 2.2 to 2.8 g / cm³. 3 Ultralight meteorites have a density of less than or equal to 2.2 g / cm³. 3 ; Hardness determination standard: The Mohs hardness of natural meteorites is 5~7; Magnetic determination criteria: Iron meteorites are strongly magnetic, stony meteorites are weakly magnetic, and nickel-free meteorites, tektites, and ultralight meteorites are non-magnetic or extremely weakly magnetic.

4. The method according to claim 1, characterized in that, In step S2, the precision detection includes at least one of the following detection types: microstructure detection, elemental composition detection, quantum physical property detection, and isotope tracing detection.

5. The method according to claim 4, characterized in that, The threshold values ​​for elemental composition detection include: For nickel-bearing meteorites, the mass percentage of nickel should be greater than or equal to 5%; For nickel-free meteorites, the mass percentage of nickel should be less than 0.1%; For glassy meteorites, the mass percentage of silicon dioxide should be greater than or equal to 70% and the mass percentage of nickel should be less than 0.1%. For rare earth meteorites, the content of at least one rare earth element in the meteorite is greater than or equal to three times the average content of at least one rare earth element in terrestrial rocks.

6. The method according to claim 5, characterized in that, The detection of quantum physical properties includes at least one of the following techniques: Quantum magnetic detection based on diamond nitrogen-vacancy color centers; Quantum gravity detection based on cold atom interferometry; Quantum coherent Raman spectroscopy detection.

7. The method according to claim 6, characterized in that, The isotope tracing detection includes oxygen isotope and cosmogenic nuclide detection of the meteorite sample.

8. The method according to claim 7, characterized in that, The microstructure detection is performed using an electron microscope, and the detection parameters used include: accelerating voltage, magnification, and working distance.

9. The method according to claim 8, characterized in that, The fusion process is performed using a weighted decision model, wherein the weight of the meteorite authentication system is higher than the weight of the preliminary screening results of the sample and the precise detection data of the sample.

10. An intelligent identification system based on a meteorite authentication system, used to implement the method described in any one of claims 1-9, characterized in that, The system includes: Database module (1) is configured to store and provide relevant data for the meteorite authentication system; The physical index detection and screening module (2) is connected to the database module (1) and is configured to perform quantitative detection of physical indexes on the meteorite sample to generate physical index detection results, and compare the physical index detection results with the specifications of the meteorite certification system to generate preliminary screening results of the sample. The precision detection module (3), connected to the physical index detection and screening module (2), is configured to perform at least one precision detection on the meteorite sample that has passed the preliminary screening based on the sample, and generate sample precision detection data; The intelligent judgment module (4), connected to the database module (1), the physical index detection and screening module (2), and the precision detection module (3), is configured to obtain the conclusion of the meteorite certification system, and receive the preliminary screening results of the sample and the precision detection data of the sample, so as to perform fusion processing and output the final identification result of the sample.

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