184 results about "Material analysis" patented technology

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 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 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 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 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 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.

The invention relates to the technical field of mobile robot environment perception and navigation, in particular to a storage environment depth map generation and processing method based on laser vision. Comprising the following steps: an original data acquisition and point cloud construction step: acquiring multi-dimensional original echo data including geometric distance, echo intensity and pulse width, and constructing an initial three-dimensional point cloud; a light-object interaction characteristic decoupling step: analyzing light intensity attenuation and pulse width broadening characteristics, and constructing an intensity distance material mapping model; a material analysis and confidence generation step: analyzing the data to identify high reflection, light absorption deficiency and semitransparent areas, and generating a pixel-level confidence tensor; a semantic enhancement depth map generation step: restoring abnormal pixels based on tensor and endowing physical trafficability semantics to generate a semantic enhancement depth map; according to the invention, the problem of visual deception is effectively solved, and the passing efficiency in a complex storage environment is improved.

The invention discloses an annular focus electron beam focusing device and method, and belongs to the field of energy, aerospace, material analysis and high-energy physics. The annular focus electron beam focusing device comprises a cathode assembly, a focusing electrode assembly and an anode target which are sequentially arranged in the electron beam propagation direction; the cathode assembly comprises a lamp filament; the focusing electrode assembly at least comprises a focusing electrode and a focusing cover, the focusing electrode is provided with a supporting part used for fixing a filament, the supporting part is movably connected with the focusing electrode, and then the assembling height of the filament is changed; the focusing cover covers the focusing electrode in a matched mode, and the focusing electrode is provided with a positioning part used for positioning the focusing cover in the axial direction. By replacing the lamp filaments with different ring diameters and / or adjusting the assembly height of the lamp filaments, the electron beams converge on the bombardment surface of the anode target to form the annular focus with the preset size, a basis is provided for adapting to the annular focuses with different sizes, and the flexibility and the application range of equipment are greatly improved.

The invention relates to the technical field of computer vision and automatic control, and discloses an automatic checking method for the number of stacked sheet materials, which comprises the following steps: identifying a standard number table image to obtain a platform standard identifier and a material standard number; performing visual identification processing on the field material image, identifying a platform identification target and all material targets corresponding to the platform identification target, and obtaining position information of the material targets; identifying the platform identification target to obtain a platform analysis identifier; and outlier elimination processing and gap filling processing are carried out on the material target according to the position information. And finally obtaining a platform analysis identifier and a material analysis quantity. And matching the platform analysis identifier with the platform standard identifier, comparing the material analysis quantity corresponding to the matched platform with the material standard quantity, and outputting a verification conclusion according to a comparison result. Through the arrangement, accurate detection of the material quantity is realized, and the accuracy, the efficiency and the automation level of warehouse checking work are improved.

A method is provided for generating and / or displaying a dynamic tooth chart In some cases, the method can include receiving dataset(s) associated with a patient. Each dataset comprises data corresponding to an imaging modality of a plurality of imaging modalities and provides information on a dentition of the patient. The datasets are processed to generate, for each dataset, one or more tooth portions. Each tooth portion comprises an image of one or more teeth of the patient. The one or more tooth portions are arranged into a dental chart. A visualization of the dental chart of the patient is generated and provided to a user device for presentation in a user interface. In some cases, a method can include determining one or more chart annotations can by performing a shape analysis, a teeth arrangement analysis, and / or a material analysis on 3D dental model(s) and / or 2D images of the patient's jaw.

Time-series data formed by acquiring values indicating amounts or states of a plurality of biological materials for each biological material at a plurality of time points is prepared, the plurality of biological materials are divided into a plurality of groups on the basis of temporal variations of time-series data of the respective biological materials, representative time-series data indicating a state of each group is generated on the basis of time-series data of at least one biological material included in each group, and dependencies between the groups are estimated on the basis of the representative time-series data of each group.

The application provides a method for measuring material ionization potential based on ultraviolet photoelectron yield spectrum, and relates to the technical field of material analysis, and comprises the following steps: monochromatic light in a vacuum ultraviolet band is divided into a main light path for transmission and a reference light path for reflection at a target wavelength; the number of incident photons of the reference light path at the target wavelength is measured, and the number of incident photons of the main light path at the target wavelength is measured; the light splitting ratio at the target wavelength is calculated according to the number of incident photons of the main light path and the number of incident photons of the reference light path at the target wavelength; the number of photoelectrons excited by the main light path from the surface of a sample to be measured at the target wavelength is measured; the ultraviolet photoelectron yield spectrum of the sample to be measured is determined according to the light splitting ratio, the number of incident photons of the main light path and the number of photoelectrons at multiple wavelengths, and the ionization potential of the sample to be measured is determined based on the ultraviolet photoelectron yield spectrum. The application not only simplifies the measurement process of the ionization potential, but also improves the accuracy and stability of the experiment.

The invention discloses a preparation method of an iron ore concentrate powder scanning electron microscope sample, and belongs to the field of material analysis and testing. The preparation method comprises the following steps: (1) adding iron ore concentrate powder to be detected into absolute ethyl alcohol, and fully and uniformly shaking to obtain a sample solution; (2) adding a dispersing agent into the sample solution, and uniformly oscillating by using an ultrasonic method to obtain a solution after ultrasonic oscillation; and (3) pouring the solution subjected to ultrasonic oscillation into a sprayer, uniformly spraying the solution to the surface of a conductive adhesive tape fixed on an objective table of a scanning electron microscope through the sprayer, and naturally drying to obtain the iron ore concentrate powder scanning electron microscope sample. The method is simple in sample preparation process, uniform in iron ore concentrate particle dispersion and easy to operate, the problem of iron ore concentrate powder agglomeration is solved, meanwhile, a scanning electron microscope sample chamber is not polluted, and the observation result is real and reliable.

The invention discloses a cast iron white sample preparation method for direct-reading spectrometry detection, a mold and a processing device thereof, and relates to the technical field of metal material analysis and detection, the cast iron white sample preparation method comprises the following steps: S1, under the protection of high-purity inert gas, rapidly melting a cast iron sample by using a high-frequency induction heating device; and S2, the completely-molten metal liquid is rapidly poured into a mold internally provided with a forced water cooling system. According to the preparation method of the cast iron white sample for direct-reading spectrometry detection and the mold, high-frequency rapid melting and ultra-rapid cooling of the water-cooling copper mold are combined, graphite precipitation is fundamentally inhibited, even for high-carbon-equivalent cast iron, it can be guaranteed that 100% of a full white structure is obtained, the problem that carbon and silicon elements are not detected accurately in spectral analysis is thoroughly solved, and the production efficiency is improved. The prepared sample is uniform and compact in structure, free of defects such as shrinkage porosity and pores and high in component representativeness, and the reproducibility and accuracy of direct-reading spectrum analysis are greatly improved.

The invention discloses a quantitative analysis method for ardealite leachate-carbonate rock fracture corrosion effect, and belongs to the technical field of material analysis. The quantitative analysis method for the ardealite leachate-carbonate rock fracture corrosion effect comprises the following steps: preparing a carbonate sample; preparing ardealite leachate; mounting the sample in a seepage device in a sealing manner, pouring the leachate into the seepage device, and carrying out a seepage test; performing CT scanning on the sample before and after corrosion to obtain a two-dimensional section slice image of the sample, and preprocessing the slice image based on a gray value and threshold segmentation method; and performing three-dimensional digital reconstruction on the preprocessed CT slice data, and calculating pore structure parameters, fracture structure parameters, fractal dimensions and permeability of the sample to complete quantitative analysis. By adopting the quantitative analysis method for the ardealite leachate-carbonate rock fracture corrosion effect, the problem of low analysis accuracy of the ardealite leachate corrosion effect by an existing analysis method can be solved.

The invention discloses a qualitative and quantitative detection method for graphene in a fiber fabric based on microwave assistance, and relates to the technical field of nano material analysis and detection. The qualitative and quantitative detection method comprises the following steps: adding a solvent and a dispersing agent into a fiber fabric sample, carrying out microwave-assisted dissolution treatment, adding the obtained mixture into a microwave-vortex ultrasonic-centrifugal integrated treatment system, and carrying out vortex dispersion, ultrasonic stripping and gradient centrifugal separation to obtain enriched graphene precipitate; the graphene precipitate is uniformly mixed with an internal standard substance silicon carbide, Raman spectroscopy is adopted for testing, qualitative analysis is carried out by analyzing the characteristics of a G peak and a 2D peak, and quantitative calculation is carried out on graphene according to the intensity ratio of a D peak to a silicon carbide characteristic peak. The method is efficient and accurate, and effectively solves the problems of low treatment efficiency, high cost, environmental pollution, easy damage of graphene structure and insufficient quantitative analysis precision of a traditional method.

This invention relates to the field of high-purity material analysis technology, and discloses a method for simultaneously separating and enriching copper, cadmium, nickel, cobalt, zinc, lead, and barium in lithium carbonate. The steps are as follows: dissolving a lithium carbonate sample in nitric acid to obtain an acidified sample solution; adjusting the acidified sample solution to an alkaline pH range of 9.5-10.5 using an ammonia-ammonium acetate alkaline buffer solution; passing the alkaline solution through a solid-phase extraction column filled with iminodiacetic acid-type chelating resin, where copper, cadmium, nickel, cobalt, zinc, lead, and barium ions are selectively adsorbed onto the resin; and eluting the adsorbed heavy metal ions with acid to achieve separation and enrichment. This invention effectively overcomes the inhibition and interference of the lithium carbonate matrix on the detection of trace heavy metals, and in particular significantly improves the adsorption and recovery rate of elements such as barium. It achieves efficient separation and enrichment of multiple heavy metals in complex matrices, providing a reliable pretreatment solution for high-sensitivity and high-accuracy quality control analysis of lithium carbonate products.

The present invention provides a resin material analysis method and a resin material analysis device, with which it is possible to nondestructively evaluate the degree of progress of hydrolysis for a resin material that contains a polymer having hydrolyzability.　Provided is a resin material analysis method in which a resin material that contains a polymer having hydrolyzability is subjected to: a reference measurement step for performing near-infrared spectroscopic measurement on a plurality of reference samples that are composed of the resin materials having different degrees of progress of hydrolysis so as to obtain a plurality of reference spectra; an objective measurement step for performing near-infrared spectroscopic measurement on an objective sample that is composed of the resin material having an unknown degree of progress of hydrolysis so as to obtain an objective spectrum; and an estimation step for estimating the degree of progress of hydrolysis in the objective sample by comparing the objective spectrum with the plurality of reference spectra in a wavelength range including contributions (A, B) of near-infrared absorption by a hydroxyl group.

The application provides a method and system for identifying molecular composition and predicting physical properties based on a graph, and belongs to the technical field of material analysis and testing. The method comprises: performing infrared spectrum detection and gas chromatography detection on the gasoline to be detected respectively to obtain infrared spectrum data and gas chromatography data; obtaining a first predicted molecular composition according to the infrared spectrum data; identifying a second predicted molecular composition based on the gas chromatography data; performing linear addition on the first predicted molecular composition and the second predicted molecular composition to obtain an overall predicted molecular composition; and taking the overall predicted molecular composition and predicted molecular attribute information as the molecular detection result of the gasoline to be detected. The application solves the technical problems of low accuracy of gasoline molecular composition identification, great limitation of a single detection method and inaccurate physical property prediction in the prior art, achieves the technical effect of improving the accuracy of molecular composition identification through double spectrum data fusion, and realizes reliable physical property prediction based on accurate molecular composition.

The present invention relates to a material analysis method, which may comprise the steps of: (a) preparing a sample for structural analysis; (b) training an artificial intelligence model by using a training image marked with structural characteristics of any sample; (c) analyzing a plurality of to-be-analyzed images with unlabeled sample structure characteristics by using the trained artificial intelligence model, and removing the to-be-analyzed images classified as preset noise structure characteristics; and (d) using the trained artificial intelligence model to analyze the remaining to-be-analyzed images after the to-be-analyzed images classified as the noise structure characteristics are removed, and classifying the remaining to-be-analyzed images as at least one target structure characteristic.

The present application belongs to the technical field of material analysis and detection, and particularly relates to a tungsten carbide powder detection method, which realizes the shaping of the tungsten carbide powder by mixing and sintering metal powder with tungsten carbide powder to form a large-volume tungsten carbide inlaid sample. The tungsten carbide metallographic sample is ground and polished to make the tungsten carbide grains appear, thereby reducing the difficulty of tungsten carbide sectioning and being conducive to the detection of various performance indicators of the tungsten carbide powder by using equipment, so as to effectively evaluate the quality of the tungsten carbide powder. The metal powder used in the present application can reduce the sintering temperature, prevent the tungsten carbide powder sample from appearing recovery recrystallization and defect elimination and being damaged at high temperature during the high-temperature sample preparation process, help to maintain the original morphology and structure of the tungsten carbide, and meet the industrial implementation.

The invention provides a diet data analysis method, system and device based on intelligent equipment, and aims to solve the problems that traditional diet analysis depends on manpower, recognition is single, dynamic states in meals are ignored, and food materials and cooking processes cannot be reversely deduced. Comprising the steps of pre-meal static multi-mode scanning, physical decoupling analysis, in-meal dynamic interaction analysis, cross-spatio-temporal data fusion and probability traceability. The system comprises the intelligent tableware integrated with multiple modules / sensors, a data processing unit for executing an algorithm and a result display unit for displaying a report. According to the method, the component identification precision and the nutrition estimation accuracy are improved, the whole-process accurate analysis of the diet data from before meal to during meal is realized, and reliable data support is provided for diet health management.

A fluid material analysis and detection device comprises a Brinell fluid detector body, and a calibration beryllium copper spring of the Brinell fluid detector body is sleeved with a corrugated pipe; auxiliary fixing structures are uniformly arranged in the middle of the stabilizing bracket; a positioning clamping block is arranged on the outer wall of a main shaft of the rotor, the rotor is one of a common rotor and a Newtonian fluid test rotor, and clamping grooves matched with the positioning clamping block are formed in the tops of the inner walls of the common rotor and the Newtonian fluid test rotor; and the positioning clamping block is fixedly connected with the clamping groove of the common rotor or the clamping groove of the Newtonian fluid test rotor through a vertically arranged fixing bolt. The problem that in the prior art, when a fluid material analysis and detection device is used for detecting non-Newtonian fluid, the detection error is large is solved.

The utility model relates to metal analysis and detection technical field, concretely relates to a kind of metal composite material analysis and detection instrument, including fixed plate, fixed column, displacement component, feeding plate and detection component, fixed plate side is equipped with fixed column, the fixed column and the fixed plate are all equipped with displacement component, the displacement component is used to control the position of feeding plate and detection component by displacement motor, and then analysis and detection can be better carried out;Feeding plate and detection component are installed on the displacement component, and the detection component is used to analyze and detect metal composite material.

The application discloses a kind of low temperature extremely cold environment under optical fiber coating detection equipment and method, belong to coating detection technical field, comprising: obtaining temperature cycle times, coating thickness, heating gradient and other detection condition data, and coating adhesion, shrinkage, cracking length and other performance data;Construct detection condition evaluation model output detection condition coefficient;Based on detection condition, coating performance analysis model is established to output performance evaluation coefficient;Combined with the content of silicon dioxide nanoparticles and polyether polyurethane data, material analysis model is output material analysis coefficient;If the coefficient exceeds the preset threshold, then determine that the coating is unqualified and generate target formulation parameters.The application solves the technical problems of coating performance quantification evaluation and formulation precise optimization under extreme environment, significantly improves detection efficiency and reliability.

The invention discloses an electromagnetic shielding new material component analysis device, and relates to the technical field of material analysis, a cover plate is opened, a worker places a material on a laser lens, the material is fixed through a positioning assembly to achieve a positioning effect, a handle is pulled to drive the cover plate to flip, the cover plate is supported through a hydraulic rod, and the material is placed on the laser lens. The surface of the working platform is rubbed through the wiping assembly, so that impurities on the surface of the part are cleaned, the impurities are prevented from covering the laser lens, the influence on the subsequent operation efficiency is avoided, heat or gas is prevented from being easily accumulated in the spectrometer shell, and the impurities in the spectrometer shell are absorbed and cleaned through the processing part; the accuracy and reliability of detection data are guaranteed, the gas in the spectrograph shell is absorbed and cleaned through the processing part, so that the interference of the gas on a detection signal is eliminated, the data accuracy is guaranteed, the core part of equipment is protected, and the service life is prolonged.

The present disclosure relates to a method for analyzing a grain boundary of a polycrystalline two-dimensional material including transferring a polycrystalline two-dimensional material onto a substrate for analysis including a single crystalline two-dimensional material formed on a substrate; analyzing the polycrystalline two-dimensional material; depositing a metal thin film on the polycrystalline two-dimensional material; and exfoliating the polycrystalline two-dimensional material.

This invention relates to the field of materials analysis technology, specifically to a method for analyzing and identifying shale thin sections using a combination of optical microscopy and field emission scanning electron microscopy. First, from an optical perspective, the method combines the brightness distribution of bright-field images of shale thin sections with the birefringence deviation of cross-polarized images to determine mineral discrimination indices representing atomic number proxies. Then, based on the distribution of the mineral discrimination indices and the surface undulations of the shale thin sections, different biases are applied, and the positional bias vector is determined by combining this with the gray-level gradient distribution. Finally, based on the physical distance scale of the image and the pixel coordinate transformation process involving rotation and translation, the positional bias vector is used to determine the electron microscope stage coordinates corresponding to each pixel point for more accurate cross-scale positioning. This improves the accuracy of cross-scale positioning using optical microscopy and field emission scanning electron microscopy, significantly enhancing the reliability of shale thin section analysis and identification.