412 results about "Material analysis" patented technology

The invention provides a double-space fatigue electron microscope test system, which is applied to the technical field of material analysis, and comprises an electron microscope module, a fatigue loading module and a vacuum isolation damping module, the vacuum isolation damping module controls two spaces of the electron microscope module and the fatigue loading module to be communicated or independent; the fatigue loading module comprises a hydraulic loading actuator, an electromechanical loading actuator, a loading rod and a fixing clamp, the fixing clamp is used for clamping a to-be-tested sample, and the loading rod is used for stretching or extruding the to-be-tested sample; and the fatigue loading module is driven by the moving mechanism to reciprocate along the X axis to adjust the position of the to-be-tested sample or rotate along the X axis to realize switching of different stations. According to the double-space fatigue electron microscope test system, combined use or independent use of the electron microscope module and the fatigue loading module is realized, and adverse factors such as vibration and pulse generated by the fatigue loading module during electron microscope observation are improved; in-situ compensation is achieved by means of cooperation of loading force and displacement of the fatigue loading module, and the observation effect of the electron microscope is improved.

The invention discloses a path planning method for a palletizing robot based on a multi-path convolutional neural network, and relates to the technical field of convolutional neural networks, and the method comprises the steps: employing the three-source data of a quality inspection report image, a damaged video and a microscopic image, extracting features through a parallel convolutional neural network, generating a dynamic maximum curvature constraint value after the fusion, and obtaining the path planning of the palletizing robot. And self-adaptive path planning of material characteristics is realized. And nodes conforming to curvature constraint are screened based on a probability route map (PRM) to generate a track, and the vibration spectrum energy of the mechanical arm is monitored in real time. When vibration exceeds a dynamic safety threshold value, subsequent path constraint is tightened in real time through a curvature penalty factor, and the damage risk is reduced by 90%; a closed loop of material analysis, path generation, vibration feedback and parameter correction is established, and balance of safety and efficiency is achieved in a high-speed stacking scene.

The invention relates to a double-spectrum target detection method based on physical prior constraints, and belongs to the technical field of computer vision and deep learning. The method comprises the following steps: acquiring an RGB image and an IR image after registration, and extracting RGB and IR global feature vectors; constructing a double-spectrum target detection model by adopting a double-branch convolutional neural network; carrying out physical constraint fusion on the RGB and IR features to construct a bimodal fusion feature vector and training a model; wherein the model comprises a double-branch backbone network, a physical prior constraint module, a physical fusion module, a physical enhancement UNet module and a multi-scale detection head; the thermal physical constraint module establishes temperature-radiation relation constraint based on Stefan-Boltzmann law, the material analysis module identifies 12 materials and establishes physical attribute mapping, and the physical consistency verification module performs sub-pixel level registration and multi-level consistency detection; a to-be-detected image is collected and input into the trained model to obtain a detection result. According to the invention, high-precision rapid nondestructive detection of a target in a complex environment is realized.

The invention provides a method and system for calculating the ultra-high cycle fatigue life of a wind power blade in a complex environment, and relates to the technical field of material analysis and evaluation.The method comprises the steps that a wind power blade sample is collected, environmental parameters such as humidity, wind speed and salt mist concentration are set, and the influence of the marine environment on the wind power blade is simulated; performing a simulation test, establishing a relationship among the humidity, the wind speed, the salt mist concentration and the salt mist corrosion load, and calculating corresponding influence coefficients and influence constants; and applying different salt spray corrosion loads to the wind power blade sample by utilizing finite element analysis, respectively obtaining time-stress relation curves under different environmental parameters, measuring limit stress, and taking the time for reaching the limit stress as the fatigue life. And finally, comprehensive fatigue life evaluation of the wind power blade in the complex marine environment is generated by integrating the fatigue life under the influence of each environmental parameter.

The invention relates to the technical field of advertisement putting methods, in particular to an information flow advertisement module putting method, which specifically comprises the following steps of: 1, constructing a user portrait, collecting and analyzing behavior data of a user on various platforms, and constructing the user portrait; 2, analyzing and classifying advertisement materials; step 3, selecting and evaluating a delivery platform, namely selecting a corresponding delivery platform and evaluating the delivery platform; step 4, making a putting strategy, and making a specific putting strategy according to a user portrait, advertisement material classification and a putting platform evaluation result; 5, real-time monitoring and data collection: in the advertisement putting process, monitoring the advertisement putting effect in real time and collecting related data; according to the method and the device, the advertisement putting accuracy can be improved, an advertiser can accurately reach a target customer group, and the click rate and the conversion rate are improved.

The invention relates to the technical field of material analysis, and discloses an intelligent raw material composition screening method and system based on a sound insulation material, and the method comprises the steps: collecting acoustic characteristic test data, microstructure data and chemical composition data of a candidate sound insulation material; performing frequency response curve decomposition on the acoustic characteristic test data to obtain a characteristic frequency band sound absorption coefficient, and constructing an acoustic impedance tensor of the sound insulation material to analyze the sound wave dissipation performance of the candidate sound insulation material; calculating the pore distribution entropy and connectivity index of the candidate sound insulation material to analyze the sound wave propagation retardation efficiency of the candidate sound insulation material; analyzing the molecular chain flexibility and interfacial compatibility of the candidate sound insulation material to evaluate the acoustic performance stability of the candidate sound insulation material for multi-component compounding; and screening a target material from the candidate sound insulation materials by using sound wave dissipation performance, sound wave propagation retardation efficiency and acoustic performance stability. The performance matching degree of the raw materials screened out of the sound insulation material in actual composite use can be improved.

The invention relates to the technical field of material analysis, in particular to a crystal plasticity finite element modeling method, a crystal plasticity finite element modeling device, a storage medium and electronic equipment. The crystal plasticity finite element modeling method comprises the following steps: collecting grain information of a given material sample; performing crystal grain division based on the crystal grain information to obtain a crystal grain data file, and determining grid parameters based on a crystal grain with a minimum crystal grain morphology area in the crystal grain information; creating a grain geometric model according to the grain data file, creating a grid model according to the grid parameters, and mapping the grain geometric model to the grid model to obtain a crystal plasticity finite element grid model; and endowing a boundary condition and a constitutive relation to the crystal plasticity finite element mesh model so as to realize crystal plasticity finite element simulation. According to the crystal plasticity finite element modeling method provided by the invention, the modeling calculation efficiency can be improved while the model precision is ensured.

In one aspect, the present disclosure relates to a material analysis method which may comprise the steps of: (a) preparing a specimen for structure analysis; (b) training an artificial intelligence model with a training image labelled with a structure aspect of an arbitrary specimen; (c) analyzing a plurality of analysis images not labelled with a structure aspect of a specimen using the trained artificial intelligence model, and removing analysis images classified into preset noise structure aspects; and (d) analyzing, by using the trained artificial intelligence model, the analysis images from which the analysis images classified into the noise structure aspects have been removed, and classifying the analysis images into at least one target structure aspect.

The invention relates to the technical field of material analysis, in particular to a method for evaluating a pore structure of a refractory material by using industrial CT, which comprises the following steps: selecting an X-ray source parameter, a detector parameter, a focal length and the like of the industrial CT to be matched with a refractory material with different thicknesses, selecting a filter to avoid image noise, identifying an internal structure of the refractory material, and evaluating the pore structure of the refractory material. And obtaining a two-dimensional projection image of the internal structure. According to the method, the image noise is reduced through the filtering technology, the internal structure of the refractory material can be identified more accurately, the data integrity is ensured, a more accurate three-dimensional model can be generated, the analysis of the pore structure is more detailed and accurate, and by quantitatively analyzing the pore size, shape and distribution of the refractory material, the analysis accuracy of the refractory material is improved. The performance change of the material can be effectively monitored, the prediction capability of the refractory material in practical application is improved, and the application safety and reliability of the refractory material in an extreme environment are enhanced.

The invention relates to the technical field of medicinal liquor stability enhancement, and discloses a long-noded pit viper medicinal liquor stability enhancement system. Comprising a raw material monitoring module, a substance analysis module, a stability prediction module, a phase change correction module and a dispersion spectrum optimization module. The raw material monitoring module collects data through preprocessing nodes and a dynamic proportioning network and constructs a multi-stage raw material fusion topology; the substance analysis module analyzes components and inhibits precipitation by using a spectrum analysis unit and a precipitation inhibition unit; the stability prediction module generates a stability strategy through a turbidity modeling node and a colloid optimization unit, and optimizes a dispersion state; the phase change correction module corrects a phase state and calibrates parameters by means of a temperature isolation unit and an oscillation compensation unit; and the dispersion spectrum optimization module constructs an evaluation network to monitor the settlement rate and feeds back and adjusts the settlement rate. According to the system, real-time monitoring, dynamic analysis and accurate regulation and control of the stability of long-noded pit viper medicinal liquor are realized, the component balance of the medicinal liquor is improved, the generation of precipitates is inhibited, the environmental adaptability is enhanced, and the stable product quality is guaranteed.

The invention relates to the technical field of material analysis, and particularly discloses an ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry)-based automatic quantitative analysis method for primary and secondary elements in a high-temperature alloy, which comprises the following steps: dissolving a to-be-analyzed high-temperature alloy sample in a mixed acid of sulfuric acid and nitric acid to obtain a to-be-detected sample solution; feeding the sample solution to be detected into an atomizing chamber through a peristaltic pump, and collecting emission spectrum data of each element; establishing a standard curve of the concentration and emission intensity of each element by using a standard solution with known concentration; pre-processing the received emission spectrum data through a control system and a data processing module of the instrument; the data processing module compares the preprocessed emission spectrum data with a standard curve through a multiple linear regression method; and generating a detailed analysis report, and transmitting the generated analysis report to terminal equipment of a user through a printer or a network. Through an optimized sample dissolving method, a data preprocessing technology and a real-time correction algorithm, the accuracy and the stability of an analysis result can be effectively improved.

The invention relates to the technical field of hydraulic building material analysis, in particular to a material performance analysis method based on dam material physical properties and a related product, and the method comprises the following steps: applying multi-physical field composite loading including water pressure and temperature change to a sample of a dam material, collecting multiple performance data of the test sample in the composite loading process; key indexes are extracted according to the performance data; a comprehensive performance evaluation model is constructed based on the key indexes, an evaluation value representing the comprehensive performance of the dam material is obtained through calculation, and quantitative comprehensive analysis on the performance of the dam material is completed; according to the method, the performance comprehensive evaluation model integrating the core indexes is constructed, a principal component analysis and self-learning mechanism is introduced, and automatic extraction of main factors, reasonable weight distribution and dynamic adaptation of the regional environment are realized on the basis of original performance data; and the problems of single-point data isolation, weak coupling capability, poor structure specificity and the like in a traditional evaluation method are obviously solved.

The invention relates to the technical field of material analysis, in particular to an intelligent inspection device and method for bridge structure diseases, and the method comprises the steps: determining a plurality of disease suspected regions through obtaining a plurality of frames of unmanned aerial vehicle images of a bridge structure, carrying out the feature analysis of each disease suspected region, and determining the feature value of each disease suspected region; according to different candidate time interval lengths and characteristic values, determining interval change fluctuation degrees representing the possibility of rain and sewage flow marks corresponding to different candidate time intervals in each disease suspected area, and carrying out feature distinguishing on the rain and sewage flow marks and crack diseases; according to the interval change fluctuation degree, determining interval division fitness, comprehensive identification capability and timeliness of different candidate time intervals; according to the interval division fitness, the target interval change fluctuation degree corresponding to each disease suspected area is determined, so that the crack disease area is determined for intelligent inspection, the recognition accuracy is improved, and the intelligent inspection effect is ensured.

The invention relates to the technical field of material analysis, in particular to a rare earth element online detection device and method based on laser-induced breakdown spectroscopy. According to the invention, the laminar flow lining plate is arranged, and the to-be-detected liquid is conveyed to the laminar flow lining plate through the liquid conveying device, so that the laminar flow of the to-be-detected liquid is formed on the laminar flow lining plate. Then, an LIBS signal of the to-be-detected liquid laminar flow is collected through an LIBS signal collection device, and the to-be-detected liquid laminar flow can reduce laser energy consumed by solvent evaporation, so that the signal intensity is improved; and the to-be-detected liquid laminar flow can also reduce the fluctuation of the liquid level, so that the signal stability is improved. In addition, the acoustic signal of the liquid laminar flow to be detected is acquired through the acoustic signal acquisition device, and the LIBS signal and the acoustic signal are jointly analyzed, so that the accuracy of rare earth element detection can be improved.

The invention relates to the technical field of material analysis, in particular to a light microscope-field emission electron microscope combined shale rock slice analysis and identification method, which comprises the following steps of: firstly, combining a brightness distribution condition represented by a bright field image of a shale rock slice and a birefringence deviation condition represented by a cross polarization image from an optical angle; determining a mineral discrimination index representing an atomic number agent; applying offsets of different sizes based on the distribution condition of mineral discrimination indexes and the surface fluctuation condition of shale rock slices, and determining a position offset vector by combining gray scale gradient distribution on the basis; and finally, determining the cross-scale positioning and more accurate electron microscope objective table coordinates corresponding to each pixel point in combination with a position offset vector in a pixel coordinate conversion process based on an image physical distance scale and rotation translation processing, so that the cross-scale positioning accuracy of the optical microscope and the field emission scanning electron microscope is higher. The reliability of analyzing and identifying the shale rock slice is obviously improved.

The invention discloses a testing device and an analysis method for gas adsorption and desorption behaviors of a porous material. The testing device comprises an infrared spectrometer; a gas adsorption instrument; the temperature controller is connected with the infrared spectrometer; the nitrogen generator is connected with the infrared spectrometer; the cooling-water machine is connected with the infrared spectrometer; the liquid nitrogen tank is connected with the infrared spectrometer; the two ends of the connecting pipe are connected to the infrared spectrometer and the gas adsorption instrument respectively, and a second gas inlet valve is arranged on the connecting pipe and used for controlling on-off; and the connecting pipe is coated with a heating belt. The gas molecular state and the dynamic behavior can be detected and analyzed through the infrared spectrometer, the gas temperature can be controlled through the temperature controller, the cooling-water machine, the liquid nitrogen tank and the heating belt, nitrogen is output through the nitrogen generator to maintain the internal gas environment of the infrared spectrometer, and environmental interference is reduced. The invention relates to the technical field of porous material analysis equipment.

The invention discloses a metal JC constitutive model parameter optimization method for metal material analysis, which comprises the following steps of: rearranging and combining experimental data from different sources according to different quantities to describe the influence of the experimental quantity on the uncertainty of JC constitutive model parameters, and wrapping all possible JC constitutive model parameters; according to the method, the uncertainty range of model parameters can be completely described, the uncertainty representation of the current JC constitutive model parameters is obtained by calculating the basic inference allocation, namely, the BBA value, of each interval, the complete JC constitutive model parameter uncertainty representation can be obtained by fusing the JC constitutive model parameters of multiple data sources, and a model with the JC constitutive model parameters as input and the BBA value as output is established. According to the method, a JC constitutive model uncertainty transfer method is established by taking the response of the metal structure as an output proxy model, the calculation amount required by parameter updating is reduced, and the updating of the parameters of the JC constitutive model is completed through the real response of the metal structure in an experiment.

The invention relates to the technical field of material table robots, in particular to an intelligent material table robot system based on an AI vision technology, which is provided with a material table control module, a feature acquisition module, a material analysis module, a material identification module and a grabbing regulation and control module, a material analysis module determines the gray fluctuation condition of to-be-sorted materials according to gray characterization parameters in a grabbed recognition area at different illumination angles so as to mark the feature grabbed recognition area, a material recognition module determines a shielding trend sub-area, a shielding trend sub-vector is constructed, and the shielding trend sub-vector is calculated. And a grabbing compensation mode of the to-be-sorted materials is determined through a grabbing regulation and control module according to the comparison condition of the conveying direction vector and the shielding trend vector. According to the method, the grabbing recognition area with shielding interference is marked according to the gray features of the materials, the grabbing compensation mode is adaptively adjusted based on the change trend of dynamic shielding, and the efficiency and reliability of an intelligent material table robot system are improved.

The invention discloses a method for preparing a section sample of a new energy automobile battery powder material, and relates to the technical field of battery material analysis, and the method comprises the following steps: uniformly mixing a battery powder material with a liquid conductive adhesive solution; pouring the mixture into a mold for curing, and demolding to obtain a conductive sample block with a regular shape; directly loading the conductive sample block in an ion beam cutting system for ion cutting to obtain a flat sample section; and surface metal spraying treatment is not needed, and electron microscope observation and analysis are directly carried out. According to the preparation method, the conductive adhesive solution is adopted for inlaying and is combined with mold forming, so that time-consuming mechanical grinding and polishing procedures in a traditional method are omitted, and the preparation period is greatly shortened; and meanwhile, an in-situ conductive network formed after the glue solution is cured is utilized to effectively inhibit the charge effect, so that direct observation without metal spraying is realized, sample preparation damage and plating interference are avoided, and the authenticity and accuracy of an analysis result are ensured. The method is simple and convenient to operate and good in repeatability.

The invention discloses a security check image recognition and early warning system based on a terahertz imaging technology, relates to the technical field of security check image recognition and early warning, and solves the technical problems that in the prior art, linear change processing cannot be carried out on a terahertz image, the availability of the image cannot be ensured, and consequently the subsequent article comparison efficiency is reduced. The terahertz imaging control unit is used for carrying out region division according to a real-time security check execution region and carrying out terahertz imaging mode control according to the divided region; the material analysis unit is used for performing material analysis on the object detected in real time in the terahertz image, and determining the material of the corresponding detected object in the terahertz image by combining terahertz image analysis with wavelength transmission process analysis of an imaging technology in an actual scene; and the terahertz image processing unit is used for carrying out linear change processing on the terahertz image, adjusting the gray level distribution condition of the image by establishing gray level mapping, and improving the definition of the image.

The invention discloses a salt spray test device for simulating a salt spray environment, and relates to the technical field of material analysis equipment. The device comprises a main box body, a box cover, an ultrasonic salt mist generating device, an axial flow fan, an airflow distributor, an airflow guide device, a salt mist metering device, a control device panel and the like, wherein the main box body is provided with an inner cavity and a top sealing water tank; an auxiliary box body is arranged on one side of the main box body, and the auxiliary box body is provided with an inner cavity and is communicated with the inner cavity of the main box body; the upper end of the auxiliary box body is provided with a sunken saline water tank for storing saline water; the bottom of the ultrasonic salt mist generating device is communicated with the salt water tank through a conduit. Through the innovative structure, many problems of a traditional test are solved, salt mist distribution is optimized, and uniformity is ensured; temperature and humidity are accurately controlled, and simulation is more real; an ultraviolet light source is introduced, the illumination period is precisely regulated and controlled, and the device fits the natural environment; the corrosion resistance of the material can be comprehensively and accurately evaluated, reliable test support is provided for research, development and application of the material, and product quality and reliability are improved.

The invention discloses a method and system for constructing a universal digital twin asset data model for multi-source heterogeneous data exchange and sharing, and belongs to the technical field of digital twin. The method comprises the following steps: obtaining three-dimensional data structures and three-dimensional data indexes of different geometric forms in a digital twin model, the spatial topological relation between the three-dimensional data structures is identified; converting texture map information of the three-dimensional data structure into a unified format, normalizing coordinates of the texture map information, and unifying vertex coloring information of the three-dimensional data structure to a standard color space; and performing material analysis and description on different material characteristics of the digital twin model, dynamically calling node objects corresponding to the different material characteristics to obtain real material information, and finally dynamically outputting to obtain a general three-dimensional data model. According to the invention, the problem that a unified digital twin floor scene is difficult to generate due to different sources and structures of current model data can be solved.

The invention discloses a spectral data correction method, a substance analysis device and a digital twin system of the substance analysis device, and belongs to the technical field of lunar surface exploration. The device integrates multiple functions of element acquisition, spectral analysis, temperature compensation, weight measurement, high-definition image acquisition, three-dimensional shape reconstruction and the like, and by designing a special darkroom structure and a temperature control module, the influence of the extreme temperature of the lunar surface and stray light on the measurement precision is effectively avoided. The device adopts a Raman spectrum sensor and an infrared spectrum sensor to realize substance component detection, and corrects measurement errors caused by temperature fluctuation in real time through multispectral data preprocessing and a nonlinear temperature compensation model. Meanwhile, the multi-view image acquisition and high-density morphology reconstruction technology ensures the accurate restoration of the surface morphology and color information of the sample; the digital twin subsystem realizes remote monitoring and dynamic optimization through real-time data synchronization and virtual simulation, and improves the detection efficiency and decision precision.

The invention relates to the technical field of display process materials, in particular to a display process material characteristic analysis system and method. Comprising a central control unit used for setting a plurality of monitoring points according to the technological process of a display material; the monitoring unit comprises a plurality of monitoring sub-modules, and the monitoring sub-modules are used for collecting characteristic data packets of all monitoring points; the monitoring sub-module is also used for collecting auxiliary data packets of each monitoring point; the analysis unit is used for constructing a characteristic analysis model of the preprocessing model; a plurality of monitoring points are set according to the technological process of a display material, abnormal analysis is carried out on abnormal characteristic data in time by constructing an early warning sub-module corresponding to each monitoring point, and when it is judged that the characteristic data of a single monitoring point is abnormal, a corresponding abnormal data packet is generated by collecting corresponding technology monitoring data; and according to the material analysis model, process parameters causing characteristic index fluctuation are analyzed in time, a process optimization strategy is output, and the production quality and the production efficiency of the display material are improved.

The invention relates to the technical field of electric power, in particular to a cable nondestructive testing method which comprises the following steps: acquiring corresponding calibration parameters from a database according to the model of a to-be-tested cable, and calculating the total length and fault position of the to-be-tested cable at the near end of the to-be-tested cable by adopting a time domain reflection method; at the tail end of the cable to be detected, at the tail end, at least two core wires are short-circuited, a four-wire detection method is adopted to measure the direct-current resistance of a core wire loop at the near end, and standard temperature correction is conducted on the direct-current resistance of a single core wire; the resistivity to be measured is calculated by using the total length of the cable to be measured, the actual cross sectional area of the core wire and the direct current resistance of the single core wire at the standard temperature, and whether the actual core wire material of the cable to be measured is qualified is analyzed according to the resistivity to be measured and a resistivity threshold value set based on the calibrated core wire material. And early warning is carried out based on a core wire material analysis result and a fault position. According to the method, the cable length, the fault position and the core wire material qualification can be quickly, nondestructively and accurately detected on site.

The invention relates to a synthetic standard sample suitable for in-situ pyrrhotite Fe-S isotope analysis and a preparation method and application thereof, and belongs to the technical field of geological analysis and material analysis. The particle size of the synthesized standard sample is 100-150 microns, and the interior of the particle is compact and free of holes; delta 34S is equal to-1.16 + / -0.22 per mill, and delta 56Fe is equal to 0.39 + / -0.03 per mill; the delta 34S in the synthesized standard sample is detected by SIMS, and the standard deviation 2SD of the delta 34S is 0.53%. The delta 56Fe in the synthesized standard sample is detected by LA-MC-ICPMS, and the standard deviation 2SD of the delta 56Fe is equal to 0.47 per mill. The method has the advantages that the pyrrhotite is synthesized in a laboratory, the reproducibility of the synthesized standard sample is realized, and the problems that the original in-situ pyrrhotite Fe-S isotope standard sample is natural in source, very few in available quantity and non-reproducible are solved.

The invention relates to the technical field of semiconductor manufacturing, in particular to a novel material analysis method which comprises the following specific steps: step (1) multi-source data acquisition and quantum enhancement simulation; (2) carrying out adaptive feature fusion; (3) intelligent prediction and interpretation driven by the knowledge graph; and (4) closed-loop feedback and preparation optimization. According to the novel material analysis method, through deep fusion of quantum calculation, a knowledge graph, an adaptive algorithm and a closed-loop system, the bottleneck is comprehensively broken through, a full-process solution from atomic-scale analysis to macroscopic performance optimization is provided for efficient research and development of the novel material, and the method has the advantages of being high in practicability and wide in application range. And the technical blank of interdisciplinary intelligent material analysis is filled.

The invention discloses a multi-information synchronous measurement device and method for a whole space, and belongs to the technical field of spectral measurement and analysis. The device comprises a double-pulse laser excitation module, a multi-angle spectrum acquisition module, a transient imaging module, a backlight shadow imaging module and a synchronous control module. The measurement method comprises the steps of sample positioning pretreatment, double-pulse plasma excitation, multi-angle spectrum synchronous acquisition, plasma transient imaging, shock wave backlight shadow imaging, detection post-treatment and the like, and synchronous acquisition of multi-dimensional data is realized through accurate time sequence control. Omnibearing synchronous measurement of plasma spectrum, form and shock wave propagation is realized, and the device has the advantages of high data time consistency, comprehensive information acquisition, high measurement precision and high experiment efficiency, can be widely applied to the fields of material analysis, environment monitoring, plasma physical research and the like, and has wide application prospect. And the method has good adaptability in LIBS (Laser-induced Breakdown Spectroscopy) technology expansion scenes such as double pulses and magnetic confinement.

The invention discloses an intelligent auxiliary auditing method and system for a special equipment detection report based on a multi-modal large model. The method comprises the following steps: acquiring structured inspection data; checking the structured inspection data through a preset database of the special equipment so as to obtain the checked structured inspection data; performing multi-source report consistency comparison and regulation-driven inspection item verification on the audited structured inspection data to obtain a multi-source report consistency comparison result and an inspection item compliance verification result; and generating a structured pre-auditing report according to a multi-source report consistency comparison result and an inspection item compliance checking result. According to the intelligent auxiliary auditing method for the special equipment detection report based on the multi-modal large model, through fusion of the semantic comprehension ability of OCR, image analysis, a term knowledge base and the fine-tuning large model, full-process automatic auxiliary auditing from data analysis, multi-source consistency checking to conclusion logic checking is achieved.

This invention discloses a pretreatment method for detecting trace perfluorinated and polyfluoroalkyl substances (PFAS) in complex matrix textiles, belonging to the field of materials analysis technology. The method involves placing the textile in an alkaline solvent containing an alkyl sulfonate displacing agent. Under heating conditions, the displacing agent utilizes its competitive adsorption mechanism to forcibly occupy matrix adsorption sites and displace the target analytes into the solvent. Subsequently, the temperature is rapidly lowered to the phase separation induction temperature, inducing supersaturation precipitation of the displacing agent, which then encapsulates impurities in situ and co-precipitates, forming a solid-liquid stratified system. Finally, the supernatant is collected for analysis. This invention utilizes the dual properties of the displacing agent—high-temperature solubilization and low-temperature phase change removal—to effectively break the strong adsorption equilibrium of aged textiles without using a solid-phase extraction column. This solves the contradiction between low extraction rate and significant matrix interference, significantly improving the recovery rate of PFAS. It offers advantages such as low cost, simple operation, and high accuracy.