153 results about "Peak intensity" patented technology

The invention relates to the field of Raman spectrums, and discloses a Raman spectrum nonlinear generation method driven by mixed machine learning, which is used for meeting the requirements of a modern Raman spectrum analysis technology on mixture spectrum data with wide coverage, complete types and reliable quality. Comprising the following steps: performing weighted linear combination on pure component spectrums based on a concentration ratio to generate a primary mixture spectrum; the data diversity is enhanced; generating a prediction spectrum; generator parameters are optimized through multi-level feature comparison and adversarial training of the discriminator; matching and deleting false peaks, and reconstructing physical reasonable characteristic peaks; and dynamically adjusting the intensity of the characteristic peak, and outputting high-fidelity spectrum data. According to the method, by fusing physical constraint and deep learning, the peak position precision, intensity consistency and noise robustness of the generated spectrum are remarkably improved, quantitative analysis of a complex mixture in a wide concentration range is supported, and an efficient solution is provided for Raman spectrum database construction and chemical detection.

The invention discloses a metabonomics data batch correction method based on multi-kernel learning, and belongs to the cross technical field of bioinformatics and analytical chemistry. According to the method, the multi-kernel learning technology is utilized, the advantages of different kernel functions are fused in a self-adaptive mode, a model conforming to data reality is constructed, complex drift characteristics of metabolite signals are accurately captured, and efficient and accurate normalization processing of metabonomics data is achieved. Compared with traditional data standardization methods such as SVR and LOESS, the method has the advantages that the performance is excellent in the aspect of reducing the metabolite peak intensity variability, and the data stability is remarkably improved. In the subsequent multivariate statistical analysis, the classification accuracy is greatly improved, the comparability among different batches of data is also remarkably enhanced, reliable data support can be provided for discovery of disease biomarkers, and the method plays a key role in large-scale metabonomics research.

The invention provides a method for carrying out corn quality seed selection by using a hyperspectral imaging technology, and belongs to the technical field of corn quality seed selection. Corn kernels are subjected to spectrum scanning in a wavelength range of 400nm to 2500nm, spectrum data are preprocessed through a continuous wavelet transform algorithm, baseline drift and noise interference are removed, and a high-quality seed selection result is obtained. And accurately extracting spectral characteristic peaks of protein, starch, grease and moisture. And establishing a characteristic peak distribution matrix to record peak intensity distribution, and calculating a characteristic peak intensity weight coefficient and a position offset. And constructing a characteristic peak quality incidence matrix, establishing a numerical mapping relationship between the spectral characteristics and the quality parameters, and obtaining a peak width parameter and a spectral noise level. The spectral quality fusion function is adopted to process the multi-dimensional characteristic parameters, and the comprehensive quality evaluation index and the single quality evaluation index are calculated, so that the technical problem that the multi-dimensional quality characteristics of the corn kernels cannot be accurately identified and accurately graded is solved.

To provide a composition for chemical mechanical polishing and a polishing method that can effectively suppress contamination of foreign matters during manufacturing and can polish the surface of a semiconductor substrate to a flat surface.SOLUTION: The composition for chemical mechanical polishing according to the present invention contains (A) abrasive grains including silica and (B) a liquid medium, in the (A) component, when the peak intensity of 490 cm-1 derived from a 4-membered ring measured by Raman spectroscopy is x and the peak intensity of 800 cm-1 derived from a multi-membered ring measured by Raman spectroscopy is y, x / y is 4.5 to 6.0, and the (A) component has at least one functional group selected from those represented by the following general formulae (1) to (4), -SO3-M+ (1), -COO-M+ (2), -NR1R2 (3), -N+R1R2R3M- (4).SELECTED DRAWING: None

The invention provides a raman peak intensity information-based genuine medicinal material structured feature selection method and system. The method comprises the following steps: scanning medicinal material slices to generate two-dimensional distribution data of chemical components; a three-dimensional feature is constructed by using dual-wavelength laser irradiation and combining Raman peak intensity difference. And identifying a plurality of concentration regions and boundary cross points thereof through spatial topology analysis, establishing a spatial correlation model, analyzing a distribution rule, and finally forming component arrangement graph structure data. Key information is screened based on genuine medicinal material features, and after a discrimination model is input, a result is output in combination with spatial and spectral features, so that accurate discrimination is realized. And selecting the structured characteristics of the genuine medicinal materials based on Raman peak intensity information. According to the method, the spatial topology and the chemical component distribution characteristics of the Raman spectrum are fused to construct the graph structured identification model, so that the accuracy and the interpretability of genuine medicinal material identification are remarkably improved.

The invention relates to the field of biological cells, and particularly discloses a method for quantitatively analyzing metabolites in biological cells based on a Raman spectrum technology, and the method comprises the following steps: S1, collecting a Raman spectrum data set; s2, metabolite with uniform distribution and metabolite with stable content in the cells to be compared are selected as internal standards; s3, extracting the Raman characteristic peak area of the target object, and performing Raman distribution imaging in the cells according to the Raman characteristic peak area of the target object to obtain Raman imaging pictures of a plurality of substances; s4, performing Raman imaging normalization on the target object; s5, converting the normalized Raman peak intensity of the target object into a thermal image, and presenting Raman signals with different intensities in different colors to obtain an intracellular distribution diagram of each component of the intracellular metabolite; and S6, spatial distribution and quantitative analysis of intracellular metabolites. The method disclosed by the invention has the advantages of in-situ, nondestructive, high speed, quick effect, capability of simultaneously and quantitatively analyzing various metabolites on the subcellular scale and the like.

The invention provides a method for detecting PFAS based on a three-dimensional Ag / NiFe-LDHs surface enhanced Raman scattering substrate and ion pair extraction, and belongs to the technical field of PFAS detection.The method comprises the steps that firstly, the three-dimensional Ag / NiFe-LDHs SERS substrate is prepared, then ion pair extraction-dissociation treatment is conducted on a water sample to be detected, a detection solution is obtained, finally, the substrate is immersed in the detection solution for adsorption, and finally the detection solution is obtained. A spectrum is collected through a Raman spectrometer, and semi-quantitative detection of PFAS in a water sample is achieved according to the linear relation between the characteristic peak intensity and the PFAS molar concentration logarithm. According to the method, collaborative application of the three-dimensional Ag / NiFe-LDHs SERS substrate and an ion pair extraction technology and indirect detection of PFAS are realized, the detection difficulty that PFAS Raman signals are weak and are difficult to enrich is improved, the detection sensitivity and adaptability of PFAS in a water sample are improved, and an application foundation is laid for rapid monitoring of PFAS pollution of an environmental water body.

The invention discloses a real-time dynamic monitoring method for a new energy carbon-based material purification process, and relates to the field of material processing monitoring, and the real-time dynamic monitoring method comprises the following steps: collecting pulse voltage signals, stripping current density and electrolyte conductivity data in a graphene powder purification process, and monitoring the change of functional groups on the surface of graphene on line through an infrared spectrometer; obtaining characteristic absorption peak intensity data; according to the method, multi-source data in the purification process is subjected to collaborative analysis and intelligent regulation and control, an electrochemical parameter and material structure evolution correlation model is established, the process stability is improved through parameter self-adaptive adjustment, a closed loop integrating data acquisition, feature analysis and dynamic control is constructed, and the purification efficiency and purity of the graphene powder are effectively improved.

The invention relates to the technical field of analytical chemistry and information processing, in particular to a weighted characteristic peak quality accuracy-based forward and reverse mass spectrogram similarity matching method, which is suitable for high-throughput screening of risk substances in food safety detection, and comprises the following steps: acquiring mass spectrogram data to be queried and standard mass spectrogram data in a database; fragment ions with the peak intensity ranked in the first 7 or larger than or equal to 10 in the mass spectrum to be inquired and the standard mass spectrum are selected; judging whether the m / z difference value of fragment ions in the mass spectrum to be queried and the standard mass spectrum is less than or equal to 5ppm or not; calculating a forward matching degree score of the to-be-queried mass spectrum and the standard mass spectrum, and a reverse matching degree score of the standard mass spectrum and the to-be-queried mass spectrum; calculating a mean value according to the forward matching degree score and the reverse matching degree score; the average value is output as the similarity score of the mass spectrum to be queried and the standard mass spectrum, and the possibility that the screening result shows false negative is greatly reduced by considering the quality accuracy of fragment ions.

Provided is a separator having an intensity ratio of peaks corresponding to a (020) plane and a (110) plane in an X-ray diffraction (XRD) analysis graph of 2.6 to 5.7. The separator according to an embodiment has excellent stability at high temperature by satisfying the peak intensity ratio of the XRD analysis graph.

The invention relates to a method for measuring thermodynamic parameters of a corrosion product under zinc injection, which comprises the following steps: detecting the characteristic peak position of the corrosion product through Raman spectrum, comparing with a standard Raman spectrum database to obtain the chemical structure of the corrosion product, calibrating the peak intensity of a standard sample, and obtaining the concentration of the corrosion product according to the relationship between the peak intensity and the concentration of the standard sample. The conductivity of the coolant containing the corrosion product is detected through alternating current conductivity, and the ionization constant of the corrosion product is obtained in combination with concentration information provided by the Raman spectrum. According to the invention, the thermodynamic parameters of the corrosion product under the chemical condition of zinc injection water can be measured in situ, including the chemical structure, concentration and equilibrium constant of the corrosion product, and the problem of lack of the thermodynamic parameters of the corrosion product under the current chemical condition of zinc injection water is solved; and a foundation is laid for accurate prediction of the corrosion product deposition law and model development under the zinc injection water chemical condition.

The invention relates to the technical field of analytical chemistry, in particular to a method for quantitatively analyzing BSA (Bovine Serum Albumin) through SERS (Surface Enhanced Raman Scattering) based on an AgNR-coated MIP probe and a nano-silver sol substrate. Comprising the following steps: (1) preparing a BSA standard working solution system; (2) preparing a blank control solution system; (3) respectively determining the surface-enhanced Raman scattering peak intensity value I at 1621.8 cm <-1 > of the BSA standard working solution system and the blank control solution system in a portable Raman spectrometer, simultaneously determining the surface-enhanced Raman scattering peak intensity value I0 of the blank control solution system, and calculating delta I = I-I0; (4) drawing a working curve according to the relationship between the delta I and the concentration of the BSA; (5) preparing a sample solution according to the method in the step (1), determining the surface enhanced Raman scattering peak intensity value of the sample solution as Isample, and calculating delta Isample = Isample minus I0; and (6) calculating the BSA content of the sample solution according to the working curve. The determination method adopts an SERS (Surface Enhanced Raman Scattering) method in which AgNR-coated MIP is specifically combined with BSA (Bovine Serum Albumin), and is simple, convenient, rapid and high in sensitivity.

The invention discloses a fruit and vegetable pesticide residue rapid screening method based on an enzyme inhibition ratio method, and relates to the technical field of pesticide detection.The method comprises the following steps that S100, visible light, near-infrared and hyperspectral data of fruit and vegetable samples are synchronously collected through a multispectral sensing module, and a pH adjusting module is dynamically triggered based on spectral characteristic peak intensity; s200, executing dynamic pH regulation and enzyme reaction monitoring based on the output of the step S100; s300, based on the output of the S200, fusing the multispectral data and the dynamic curve through an intelligent analysis platform, outputting a pH sensitivity response curved surface through a transfer learning module, and dynamically updating proportional-integral control parameters; and S400, establishing a feedback verification closed loop based on a feedback module, automatically generating a unique identification code and triggering a GC-MS laboratory for confirmation when a positive sample of which the inhibition ratio is greater than a preset value is detected, and finally, synchronously and reversely calibrating the spectrum fusion weight in S300 and the pH adjustment parameter in S200 based on the deviation value.

Provided is a film-attached article 10 comprising a substrate 1 and a film 2 containing a silicon oxide on the substrate 1, wherein the film-attached article satisfies any one of the following (a) to (c). (a) Film thickness: less than or equal to 150 nm; Si–OH ratio: between 0.03 and 0.2, inclusive (b) Film thickness: greater than 150 nm and less than or equal to 400 nm; Si–OH ratio: between 0.07 and 0.3, inclusive (c) Film thickness: greater than 400 nm and less than or equal to 700 nm; an Si–OH ratio: between 0.15 and 0.5, inclusive The Si-OH ratio is the ratio of the peak intensity near 950 cm-1 attributed to a silanol group to the peak intensity near 1100 cm-1 attributed to a siloxane bond in Fourier transform infrared spectroscopy of the film.

The diamond member has a rake face and a flank. The ridge between the rake face and the flank forms a cutting edge. The arithmetic mean roughness of the rake face is 0.1 μm or more and 1.0 μm or less. The diamond member is measured for energy loss associated with the excitation of K-shell electrons of carbon by electron energy loss spectroscopy using a transmission electron microscope. The energy loss is used to measure the π bond originating from the carbon π bond in the graphite phase. * The intensity of the peaks and the σ due to the σ bond of carbon in the graphite phase and the diamond phase are * The peak intensity is calculated. * The peak intensity is σ * Divide the value by the peak intensity to obtain I π* / I σ* When the diamond material on the surface of the rake face is π* / I σ* is between 0.2 and 2.

The invention discloses a method for rapidly detecting the type and content of bacteria in gas based on a Raman spectrum technology, and relates to the technical field of microbiological detection.The method comprises the steps that a gas sample is collected, dried and dewatered, and the sampling volume is determined; the method comprises the following steps: pre-filtering a gas sample, guiding the pre-filtered gas sample to a low-background filter membrane to enrich bacteria, and irradiating the enriched bacteria on the low-background filter membrane by adopting near-infrared laser to generate a scattered Raman signal; raman signals are collected, and only light in a bacteria Raman characteristic peak interval is allowed to pass through in cooperation with a narrow-band optical filter; performing feature extraction and pattern recognition on the Raman signals, classifying to judge the types of bacteria, comparing the intensity of the Raman signals with a calibration curve of bacteria with known concentration, and calculating the concentration of the bacteria in the gas in combination with the sampling volume. Through exclusive gas sampling pretreatment and surface enhanced Raman scattering and fusion of representative Raman peak intensity, rapid bacteria detection with strong interference resistance, stability, reliability, low detection limit, high quantitative accuracy and cross-batch comparability is realized.

A method for cooling at least one ion (8) within a capture potential of an ion trap (2), comprising: - capturing the at least one ion (8) in the capture potential, wherein the at least one ion (8) oscillates about a potential minimum of the capture potential between a first inflection point region (13) and a second inflection point region (14), - illuminating the at least one ion (8) with a laser beam in the first inflection point region (13) and / or the second inflection point region (14) for cooling the at least one ion, wherein the laser beam has a beam center characteristic of a peak intensity and the beam center is spaced from the potential minimum, and - decreasing a distance of the beam center from the potential minimum until the beam center overlaps with the potential minimum, for further cooling of the at least one ion. Furthermore, a system (1) is specified.

This invention provides a method for preparing and testing powder diffraction standards for determining internal residual stress, belonging to the field of residual stress detection. The powder standards prepared by this invention possess shape retention capabilities, meeting the requirements of the transmission diffraction optical path in non-destructive diffraction determination of internal residual stress. The powder, after being bonded with an adhesive, forms a blocky solid form, and standards of different sizes can be prepared according to the penetration depth of different diffraction sources on different substrate materials. Furthermore, the ratio of powder to adhesive can be adjusted to obtain different diffraction volume ratios. By testing the uniformity of diffraction peak intensity distribution in translational and rotational degrees of freedom, the uniformity of the internal lattice distribution and orientation of the standard sample can be determined, thereby testing and judging the uniformity of the standard sample.

The invention relates to the technical field of composite insulator detection, and particularly discloses a Raman spectrum-based method for detecting an abnormal heating area of a composite insulator, which is suitable for a composite insulator with a silicone rubber sheath dyed by using ferric oxide as a pigment. The method comprises the following steps: firstly, selecting a to-be-detected sample, and performing spectrum acquisition on a to-be-detected area on the surface of the silicone rubber sheath by using a Raman spectrometer without applying operating voltage; then processing the spectral data, respectively extracting the characteristic peak intensities of ferric oxide in Raman shift ranges at 223 + / -8cm and 292 + / -12cm, and calculating the ratio of the two characteristic peak intensities; the obtained ratio is compared with a preset threshold value, whether an abnormal heating history exists in the to-be-detected area in the network hanging operation period or not is judged, and the preset threshold value is determined through establishment of a standard sample library and statistical analysis. The detection result is objective and is not interfered by electric field and environmental factors.

Provided is a plated member having, on an outer surface, a plated film composed mainly of chromium formed by using a trivalent chromium bath containing at least chromium, carbon, and oxygen, the plated film containing 60 at% or more of chromium and 1 at% to 30 at% of carbon, and having, on the outer surface, an indentation hardness of 11.1 GPa or more, and a degree of crystallinity calculated from a ratio of the integrated peak intensity of a measured value of an X-ray diffraction measurement and the following expression (1) is 5% or more. Degree of crystallinity (ratio of integrated peak intensity) = {(crystalline) / (crystalline + amorphous)} × 100% Here, the indentation hardness refers to a value obtained by instrumented indentation hardness measurement using a nanoindentation method (ISO 14577), and the integrated intensity ratio in expression (1) refers to a value determined in X-ray diffraction (XRD) analysis under conditions of 2θ: 30° to 60°, a half-width of crystalline: < 3, and a half-width of amorphous: ≥ 3.

The application discloses a multi-peak decomposition time-resolved Raman spectrum thermal map interactive analysis method and system, and belongs to the field of spectrum analysis. The method comprises the following steps: continuously or time-divisionally collecting a to-be-measured sample to obtain Raman spectrum data corresponding to different time points; preprocessing the original Raman spectrum data; extracting spectral characteristic peaks by using an adaptive peak value recognition algorithm, and performing characteristic peak integral calculation; obtaining time contribution coefficients of different chemical components or characteristic signals in the time dimension by using a multi-peak decomposition algorithm; generating a Raman thermal map in the time dimension according to the characteristic peak intensity and / or the time contribution coefficients; establishing an index mapping relationship between the position of the Raman thermal map and the corresponding time Raman spectrum data; and responding to the interactive operation of the user on the thermal map and displaying the Raman spectrum curve at the corresponding time point in real time. The application can realize visual display, dynamic monitoring and interactive analysis of time sequence data of Raman spectrum, and improves the efficiency and accuracy of Raman signal analysis of dynamic samples.

The application provides a kind of gold plating and K gold sample identification method and system, through X-ray detector, the energy spectrum of the sample to be measured is collected, the original X-ray spectrum of the sample to be measured is obtained, the original X-ray spectrum is smoothed, the target X-ray spectrum of the sample to be measured is obtained, the initial simulation spectrum of the sample to be measured is generated according to the target X-ray spectrum, the initial simulation spectrum is corrected by iterative algorithm, until the deviation of the characteristic peak intensity of each element in the target simulation spectrum obtained after correction and the corresponding element in the target X-ray spectrum meets the preset convergence condition, whether the sample to be measured is gold-plated sample is judged according to the target simulation spectrum, in the above manner, it is favorable to improve the accuracy of detection result, reduce the misjudgment rate in the scene such as thick plating layer misjudgment, similar component confusion.

The present invention relates to a sulfur-containing material comprising a sulfur-modifying compound, in which the sulfur-modifying compound is modified in the presence of a photoelectron spectroscopy analysis of the S1s orbital of the sulfur-containing material using hard X-ray photoelectron spectroscopy. The ratio (A / B) of the peak intensity area (A) of the peak corresponding to the S-S bond to the peak intensity area (B) of the peak corresponding to the C-S bond confirmed by waveform separation of the S1s orbital peak in the range of 2460 eV to 2475 eV is 2.5 to 4.0 (2.5 < = A / B < = 4.0).

A plated steel sheet according to the present invention includes on at least a part of a surface of a steel sheet, a plating layer having a chemical composition containing, by mass %, Al: 0.50 to 4.50 or less, Mg: 0.50 to less than 3.00%, Fe: 0.01 to 15.00%, and selectively containing one or more selected from the group consisting of following element group A, element group B, element group C, element group D, element group E, element group F, and element group G with a balance composed of 5.00 mass % or more of Zn and impurities, wherein in a measured result obtained by measuring the plating layer by an X-ray diffraction method, a peak intensity ratio I100 / I002 of an intensity I100 of a peak corresponding to a (100) plane of a MgZn2 phase to an intensity I002 of a peak corresponding to a (002) plane is 2.50 or more.

The application provides a SERS substrate and a detection method for epirubicin blood drug concentration, and belongs to the technical field of detection. ‑1 The characteristic peak intensity is determined. By establishing a quantitative curve of the epirubicin concentration in serum and the peak intensity, rapid quantitative detection of clinical samples is realized. The method has simple sample processing, high detection sensitivity, good repeatability, is consistent with the LC-MS / MS result, and is suitable for bedside treatment drug monitoring.

The invention provides a precious metal analyzer coating detection method and system based on an X fluorescence spectrum. The method comprises the following steps: on the basis of curvature data of each curved surface detection point in three-dimensional shape space data, adjusting a cooperative pose of an X-ray source and a dual-laser positioning device so as to control an X-ray beam to vertically enter each curved surface detection point; when the X-ray beam is vertically incident to the curved surface detection point, the precious metal sample is excited to generate an X fluorescence spectrum signal; according to the curvature data, correcting geometric attenuation factors in the X fluorescence spectrum intensity attenuation model by using a preset curved surface distance correction algorithm; and extracting the characteristic peak intensity value of the noble metal element, inputting the characteristic peak intensity value of the noble metal element into the fluorescence spectrum intensity attenuation model after geometric attenuation factor correction, and analyzing and outputting the thickness value of the noble metal coating. According to the technical scheme provided by the invention, high-precision and lossless online detection on the thickness of the precious metal coating on the complex curved surface is realized through a dynamic cooperative positioning and curved surface correction algorithm.

This invention belongs to the field of daily chemical product testing and analysis technology. It discloses an intelligent screening method, device, equipment, and storage medium for sulfur / sulfonate surfactants. The method involves pretreatment of the sample and high-resolution mass spectrometry (UHPLC-MS / MS) scanning, converting the sample into an mzXML file. All secondary mass spectrometry peaks in the file are screened to identify target secondary mass spectrometry peaks containing characteristic ions. The mass and peak intensity of all corresponding precursor ions are extracted. If the mass difference between two precursor ions is within the range of sulfur isotope mass difference and the peak intensity ratio is within a specified range, the precursor ion with the lower mass is selected as the quasi-molecular ion. A predicted molecular formula is generated, and matching structural information is retrieved from a database. Simulated fragmentation is used to obtain a simulated secondary mass spectrum, which is compared with the actual secondary mass spectrum to determine the predicted structure and identify sulfur / sulfonate surfactants. This intelligent processing of high-resolution mass spectrometry data improves data processing efficiency, sensitivity, and accuracy.

A release film includes a release layer and a substrate layer, the release layer includes two or more polymers, and satisfies at least one of the following (1) to (4). (1) The release layer has a plurality of different regions with different component ratios, and in a case in which Raman spectroscopy is performed on the different regions, at least a part of the different regions exhibits different peak intensities. (2) A surface of the release layer has a convex portion and a concave portion, and in a case in which Raman spectroscopy is performed on the convex portion and the concave portion, at least a part of the convex portion and at least a part of the concave portion exhibits different peak intensities. (3) A difference in SP value between at least two of the polymers is 0.3 or more. (4) At least one of the polymers is a nitrile group-containing (meth)acrylic polymer.

The invention provides a water antibiotic pollution detection method and system based on spectral characteristics, and belongs to the technical field of water environment monitoring, analysis and detection.The method comprises the steps that firstly, a surface enhanced Raman spectrogram and oxidation-reduction potential time sequence data of a to-be-detected water sample are synchronously obtained; then, extracting a ratio of the characteristic peak intensity of the target antibiotic from the spectrogram to generate a first characteristic set, and meanwhile, performing wavelet packet decomposition on the potential data and calculating an energy entropy to construct a second characteristic set; then, splicing the two feature sets, and screening out a target feature subset highly related to the concentration through a mutual information maximization algorithm; finally, a support vector projection regression model trained based on a structural risk minimization mechanism is utilized, and accurate detection of the concentration of the target antibiotics in the water sample to be detected is achieved through kernel function mapping and hyperplane projection operation. According to the method, the anti-interference capability and the quantitative precision of antibiotic detection under the complex water body background are improved.

The present application provides a method and system for selecting structured features of authentic medicinal materials based on Raman peak intensity information. Among them, the method generates two-dimensional distribution data of chemical components by scanning medicinal material slices; uses dual-wavelength laser irradiation, and constructs three-dimensional features in combination with Raman peak intensity differences. Through spatial topology analysis, multiple concentration regions and their boundary intersections are identified, a spatial correlation model is established and the distribution law is analyzed, and finally a graph structure data of the component arrangement is formed. Key information is screened based on the characteristics of authentic medicinal materials, and the results are output in combination with spatial and spectral features after input into the discrimination model to achieve accurate identification. Structural feature selection of authentic medicinal materials based on Raman peak intensity information. The present application constructs a graph-structured identification model by integrating the spatial topology and chemical component distribution characteristics of Raman spectra, which significantly improves the accuracy and interpretability of authentic medicinal material discrimination.