109 results about "Peak intensity" patented technology

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 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 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 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 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.

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.

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 invention discloses a photovoltaic cell, a photovoltaic module and a processing method of the photovoltaic cell, the surface of the photovoltaic cell is provided with an antireflection layer, and the antireflection layer has a saturated bond; when the anti-reflection layer on the surface of the photovoltaic cell is characterized by adopting a Raman scattering spectrum analysis test, a Raman spectrum chart obtained by the anti-reflection layer has a characteristic peak A, and the ratio range of the peak intensity of the characteristic peak A to the half-peak width is 1-25. According to the photovoltaic cell, a Raman spectrum chart in the antireflection layer has a characteristic peak A at the position, the ratio range of peak intensity to half-peak width is 1-25, the characteristic peak A is relatively sharp, intermolecular acting force in a molecular structure of the characteristic peak A is high, chemical bonds are not prone to breakage, and therefore the characteristic peak A at the position is the characteristic peak corresponding to a saturated bond; therefore, a large number of saturated bonds exist in the antireflection layer, and only a small number of unsaturated bonds or dangling bonds exist in the antireflection layer, so that the stability and passivation effect of the antireflection layer are ensured, and the photovoltaic cell is further ensured to have relatively good power generation efficiency.

The application 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, and comprises the following steps: first, a three-dimensional Ag / NiFe-LDHs SERS substrate is prepared; then, ion pair extraction-dissociation treatment is performed on a water sample to be measured to obtain a detection solution; finally, the substrate is immersed in the detection solution for adsorption, a spectrum is collected by using a Raman spectrometer, and semi-quantitative detection of PFAS in the water sample is realized according to the linear relationship between the characteristic peak intensity and the logarithm of the molar concentration of PFAS. The application realizes the synergistic application of the three-dimensional Ag / NiFe-LDHs SERS substrate and the ion pair extraction technology and the indirect detection of PFAS, improves the detection difficulty of weak PFAS Raman signals and difficult enrichment, improves the detection sensitivity and adaptability of PFAS in the water sample, and lays an application foundation for rapid monitoring of PFAS pollution in environmental water.

The invention relates to the technical field of tobacco leaf detection, in particular to a tobacco leaf oil content quantitative characterization method. The method comprises the following steps: measuring state information of protons in a tobacco leaf sample by using low-field nuclear magnetic resonance to obtain a spin-spin relaxation time T2 spectrum and a spin-lattice relaxation time T1 spectrum, and generating a T1-T2 two-dimensional spectrogram; determining peak positions of low-activity protons and medium-activity protons in the T1-T2 two-dimensional spectrogram to obtain T2 values of the low-activity protons and the medium-activity protons, and solving an average T2 value of the low-activity protons and the medium-activity protons of the plurality of groups of tobacco leaf samples; on the spin-spin relaxation time T2 spectrum of the tobacco leaf sample to be detected, the low-activity proton peak intensity and the medium-activity proton peak intensity of the tobacco leaf sample to be detected at the average T2 value are obtained, and the ratio of the low-activity proton peak intensity to the medium-activity proton peak intensity serves as the oil content quantitative value of the tobacco leaf sample to be detected. According to the method, nondestructive testing of the tobacco leaf raw material oil content is realized by utilizing a low-field nuclear magnetic technology, and quantitative characterization of the tobacco leaf raw material oil content is realized by combining the T1-T2 two-dimensional spectrogram.

The invention provides an SERS (Surface Enhanced Raman Scattering) substrate and a detection method for the blood concentration of epirubicin, and belongs to the technical field of detection.The SERS substrate is prepared by the following steps: firstly, respectively preparing 40nm and 20nm gold nanoparticles through a sodium citrate reduction method, and constructing the SERS substrate on a silicon dioxide sheet through ABA sandwich dispensing; an epirubicin blood sample is pretreated through an acetonitrile precipitation method and then dropwise added to the substrate to be dried away from light, and the 1236 cm <-1 > characteristic peak intensity is detected through a 785 nm Raman spectrum. By establishing a quantitative curve of epirubicin concentration and peak intensity in serum, rapid quantitative detection of clinical samples is realized. The method is simple in sample treatment, high in detection sensitivity, good in repeatability, consistent with LC-MS / MS results, and suitable for bedside treatment drug monitoring.

This invention discloses a method for fabricating and applying a formaldehyde SERS sensor based on an Au@ZIF-8 core-shell nanostructure, belonging to the field of gas detection technology. Formaldehyde has an extremely small intrinsic Raman cross section, and ordinary SERS substrates lack the ability to capture it, resulting in weak detection signals at low concentrations. This sensor uses Au@ZIF-8 core-shell nanoparticles to assemble a two-layer thin film as the SERS substrate. The Au nanoparticles (AuNPs) serve as the electromagnetic enhancement core, while the ZIF-8 shell layer enriches and sieves formaldehyde molecules. A layer-to-layer deposition method is used to construct the double-layer thin film structure to obtain optimal SERS performance. This invention solves the problems of low sensitivity, poor specificity, insufficient stability, and difficulty in rapid on-site detection in existing formaldehyde detection technologies. The detection limit is as low as 0.16 ppt, and within a wide range from 0.01 ppb to 100 ppm, the characteristic peak intensity exhibits an excellent linear relationship with the logarithm of formaldehyde concentration (R² ≥ 0.995). It can specifically identify formaldehyde and exclude interference from other VOCs, making it suitable for rapid quantitative detection of formaldehyde in practical scenarios such as indoor environments and cigarette smoke.

The invention relates to the technical field of high-resolution mass spectrum determination, and discloses a complete 15N stable isotope labeled protein abundance determination method based on high-resolution mass spectrometry, which comprises the following steps: collecting and calculating a mass spectrum signal of a sample to be detected to obtain the actually measured relative isotope peak intensity of the sample at m / z = i; calculating to obtain predicted relative isotope peak intensity of m / z = i under different 15N isotope abundance; according to a formula 1, respectively calculating correlation coefficients r under different 15N isotope abundance; the correlation coefficients r calculated under different 15N isotope abundance are compared, and the r value closest to 1 is the 15N stable isotope labeled protein abundance value. The use amount of required samples is small, pretreatment such as derivatization is not needed, and operation is easy and convenient; the method is high in resolution, small in calculation workload, and good in stability and accuracy.

The invention discloses a polyester fiber analysis method and system based on infrared spectroscopy, and relates to the technical field, and the method comprises the following steps: obtaining a PET sample; carrying out sample analysis on the PET sample, and collecting infrared spectrum data; extracting peak intensity or area characteristic data of a plurality of characteristic peaks in the corresponding infrared spectrum data; and constructing a PET regeneration analysis model, and inputting the feature data into the PET regeneration analysis model to obtain qualitative and quantitative analysis results. Four key characteristic peaks highly related to the regeneration process in a PET spectrum are screened as a minimum characteristic set, and partial least squares discriminant analysis and partial least squares regression are combined, so that rapid identification and content quantification of regenerated PET are realized. The method does not need an expensive chemical analysis platform and complex sample pretreatment, is high in detection speed, is wide in applicable sample form, remarkably reduces the detection cost, improves the detection flux, and meets the requirements for regenerated PET proportion verification, tracing and quality control in spinning, packaging and supervision scenes.

A catalyst containing, as an essential component, molybdenum; bismuth; and cobalt, in which a sum (S) of ratios of peak intensities expressed by the following formula in an X-ray diffraction pattern obtained by using CuKα rays as an X-ray source is 42 or more and 113 or less. S={(peak intensity at 2θ=14.1°±0.1°)+(peak intensity at 2θ=25.4°±0.1°)+(peak intensity at 2θ=28.5°±0.1°)} / (peak intensity at 2θ=26.5°±0.1°)×100.

The invention discloses a rubber infrared spectrum detection method and device, electronic equipment and a storage medium, the method and the device are applied to the electronic equipment, and specifically, aperiodic modeling is performed based on a chemical structural formula of a to-be-detected rubber part to obtain a trial model; acquiring dot matrix data of peak intensity and peak position of the trial model; performing simplification processing and data arrangement on the dot matrix data to sequentially obtain simplified dot matrix data and a table view dot matrix; drawing based on the table viewpoint matrix to obtain a total spectrum; performing peak marking processing on the total spectrum to obtain a plurality of peak positions; correcting each peak position to obtain a plurality of corrected peak positions; and carrying out replacement processing on the corresponding peak positions in the total spectrum by utilizing the corrected peak positions to obtain an infrared spectrogram. According to the scheme, accurate and rapid infrared detection on the rubber failure part can be realized under the condition that the rubber failure part does not need to be damaged, and an infrared spectrum is relatively clean by virtue of an optimized treatment means, so that weak change of the content of functional groups can be distinguished.

This invention provides a method for predicting the weathering degree of open-pit mine slopes. In the field of dynamic weathering degree classification, the method includes: taking samples from the area to be evaluated to prepare multiple rock samples; conducting longitudinal wave velocity tests, uniaxial compression tests, and nitrogen adsorption specific surface area tests on the multiple rock samples; conducting XRD mineral diffraction tests on the multiple rock samples; obtaining a rock weathering degree classification standard based on the weathering grade of the rock samples under longitudinal wave velocity ratio conditions, the weathering grade of the rock samples under peak intensity ratio conditions, the rock porosity of the rock samples, and the rock alteration mineral content of the rock samples; and constructing a spatiotemporal evolution model of the weathering degree of open-pit mine slope rocks using the mining years as the target time series sample to predict the future weathering time and the weathering degree of rocks at the mining location.

The invention provides a Raman spectrum gas component quantitative analysis method based on an XGBoost algorithm and application of the Raman spectrum gas component quantitative analysis method, belongs to the technical field of spectrum analysis, and is particularly suitable for real-time gas monitoring in the olefin polymerization and cracking process. According to the method, Raman spectrum data of mixed gas and pure substances of all components are collected through a Raman spectrum enhancement cavity, after pretreatment, key characteristic peaks are extracted by adopting signal-to-noise ratio screening, correlation minimization or principal component analysis, and then an XGBoost model is trained with the intensity of the characteristic peaks and gas components are predicted. The problems that traditional Raman analysis is high in nonlinear interference and sensitive in noise and a traditional machine learning model is low in precision and poor in interference resistance are solved, the mean square error and the anti-interference capacity are remarkably optimized, and a high-precision and high-robustness gas component detection scheme is provided for a complex industrial environment.