49 results about "Sample composition" patented technology

The invention discloses an intelligent event studying and judging method based on machine learning, which comprises the following steps of: extracting features from multi-source event data, constructing an event fragment set with a uniform structure according to a preset time window, identifying fragments with stable features in the event fragment set as normal samples, constructing a reference model through an MCD algorithm, and analyzing the normal samples. The method comprises the following steps: extracting feature distribution in a normal state, comparing a to-be-analyzed event with a reference model, calculating feature offset, forming a behavior trajectory, determining an anomaly judgment range by adopting an elliptical envelope algorithm, and finally evaluating an event risk level and dynamically adjusting reference sample composition according to a continuous anomaly condition to realize intelligent identification and risk judgment of the event. According to the invention, dynamic perception and intelligent identification of complex events can be realized.

The invention belongs to the technical field of X-ray fluorescence spectrum analysis, and provides a WDXRF testing method based on polyester film pretreatment and application thereof.The method comprises the steps that a sample to be tested is placed in a sample cup, covered with a polyester film and pressed into a tablet through a hydraulic machine, the tablet is placed in a mold, and a WDXRF test is conducted; the parameters of the hydraulic machine comprise that the target pressure is 300-400 kn, and the pressure maintaining time is 5-20 s; the pressing time is 3-5 s; the sampling time is 5-7 s; the sample adding depth is 7-9 s. The method disclosed by the invention is simple, convenient and feasible, is low in cost, can be widely applied to WDXRF tests of various special samples, and has extremely high practical value. According to the method, the polyester film is used for treating the special sample, so that the test of the special sample which cannot be tested originally is realized, the change of sample components is avoided, the side effect is small, the accuracy is high, and the test method has an important application prospect.

The invention discloses a time-resolved LIBS (laser-induced breakdown spectroscopy) system and a sample component analysis method and product thereof, and relates to the field of laser-induced breakdown spectroscopy. After the sample is irradiated by the ablation laser, plasma is generated; in the plasma expansion and cooling process, excited state atoms and ions are subjected to energy level transition, and a characteristic radiation spectrum is released; the delay control module sets different delay time so as to control the working time interval of the laser generator and the spectrograph; the spectrograph receives the characteristic radiation spectrums at different delay times by using an optical fiber probe, stimulates the characteristic radiation spectrums at the integration time, and determines characteristic radiation spectral lines of different elements; and the computer analyzes the characteristic radiation spectral lines, determines spectral line intensities of different elements, and determines a component result of the sample in combination with the calibrated spectral line intensities and the element content function curve so as to improve the accuracy of the component result of the sample.

The invention relates to the field of material thermal expansion testing, and provides a thermal expansion measuring device and method for gradient materials, and the device comprises an array probe module, a machine vision system, a temperature control system, a driving mechanism, a control module and a housing. The probe array module comprises probes arranged at equal intervals, and the bottom ends of the probes are in direct contact with the surface of a sample; the driving mechanism drives the probe array to scan along a sample component gradient direction; the machine vision system is used for collecting a probe top end image and combining an image processing algorithm to achieve full-area analysis of gradient components. Compared with existing equipment, the thermal expansion behavior of samples such as component gradient materials and composite materials can be represented, the thermal expansion behavior characterization device is particularly suitable for thermal expansion behavior characterization of key components such as aerospace gradient coatings and nuclear reactor cladding materials, and a reliable testing means is provided for design optimization of functionally gradient materials.

A sensor device includes a sensor, which may include an acoustic wave resonator structure, having a surface to which analyte capture ligand is bound. The device also includes a crowding agent to reduce the ratio of binding of an analyte in a sample composition to the analyte capture ligand when the sample composition is flowed across the surface of the sensor.

To provide a method for accurately determining factor XIII activity values in finished products and intermediate products in which factor XIII is purified or concentrated compared to plasma, without being affected by sample composition while also improving the workability required to measure physical properties corresponding to factor XIII activity values by using the FXIII-GLDH method.SOLUTION: Provided is a method for determining an unknown factor XIII activity value contained in a test sample by comparing the physical properties of the test sample with those of a known reference sample. The physical properties correspond to the amount of change per unit time of NAD(P)H or NAD(P)H analogues consumed or NAD(P) or NAD(P) analogues produced in the FXIII-GLDH method. The reference sample and test sample contain fibrinogen at a concentration of 2.0 to 4.0 mg / mL.SELECTED DRAWING: Figure 1

One or more X-ray intensities for a sample may be approximated. Measured intensities are received from an X-ray detection system at one or more diffraction angles. A sample simulation module computes simulated sample intensities from an X-ray fluorescence sample model with initial sample model parameters indicating the sample composition and / or layer thickness of one or more sample layers. A correction module applies a triangular collimator correction to the simulated sample intensities and determines a mathematical distance between the corrected simulated sample intensities and corresponding measured intensities. The sample model parameters are adjusted and the correction steps are repeated until the distance change falls below a minimal distance change. The sample model parameters regarding sample composition and / or the layer thickness associated with the corrected simulated intensities are provided as approximated concentration values of respective components contained in the measured sample and / or the layer thickness of the measured sample.

The temperature field prediction method of a hypersonic wind tunnel, an electronic device and a storage medium belong to the technical field of wind tunnel measurement and control. In order to solve the problem that the temperature field control effect of the hypersonic wind tunnel is poor, the working condition data of the hypersonic wind tunnel is collected, the input samples in the original data sample set are reconstructed in phase space, the input samples and the output samples used for model training are obtained, the sample training data set and the sample test data set are composed, the Bayesian regression method, the support vector regression method and the BP neural network method are used to establish the outlet temperature prediction model of the temperature field of the hypersonic wind tunnel, the sample training data set is used to train the three outlet temperature prediction models of the temperature field of the hypersonic wind tunnel, the sample test data set is used to test the three outlet temperature prediction models of the temperature field of the hypersonic wind tunnel, and the optimal outlet temperature prediction model of the temperature field of the hypersonic wind tunnel is obtained. The present application is accurate in prediction.

The invention provides a layered ferroelectric material piezoelectric response measurement method and device capable of eliminating static artifacts, and relates to the technical field of advanced functional material characterization and testing. According to the specific implementation scheme, a CuxInyP2S6 single crystal is synthesized by adopting a chemical vapor transport method; a Raman spectrum and an energy dispersive spectrometer are used for testing, and whether a sample composition is a CuInP2S6-In4 / 3P2S6 bulk heterostructure or not is verified; if the verification result is yes, the influence of the CuInP2S6-In4 / 3P2S6 ferroelectric domain characterization result under the action of the static artifact is obtained through a PFM test; using a static blind spot method to counteract static artifacts, and performing comparative analysis to obtain a real amplitude value of a CuInP2S6-In4 / 3P2S6 surface ferroelectric domain; and corresponding data are extracted for calculation, so that the piezoelectric coefficient of CuInP2S6-In4 / 3P2S6 is obtained. By optimizing a bias voltage and laser positioning strategy, the interference of electrostatic interaction on a measurement signal is effectively eliminated.

The present invention relates to the technical field of image data processing, and more particularly to a method for detecting composition uniformity based on microscopic images of titanium alloy ingots, comprising the steps of obtaining a sample image, determining the grayscale level of each grain based on the number and grayscale value of pixels in each grain in the sample image, obtaining the principal component vectors of the grains, determining the phase structure attribution coefficient of the grains based on the number and modulus of the principal component vectors of the grains, the grayscale level and area of ​​the grains, further determining each phase structure grain in the sample image, determining the phase structure uniformity of the sample image based on the number of grains of each structural phase, obtaining the component uniformity of the sample image using the same method as for the phase structure uniformity, and determining the comprehensive uniformity of the sample image based on the component uniformity and phase structure uniformity of the sample image. The present invention combines the sample composition and grain morphology to comprehensively evaluate the composition uniformity of the sample, thereby improving the reliability of the sample composition uniformity detection.

A method and a system for self-regulating control of an internal chamber pressure of a mass spectrometer are provided. The method specifically includes: associating a first test mass spectrum set, a sample composition, a compositional ratio, and a chamber pressure regulation parameter to obtain a test data set; performing characteristic factor identification on a first real-time mass spectrum generated in real time to obtain a plurality of first real-time characteristic factors when a mass spectrometer is used for sample detection; matching the first real-time characteristic factors with different test data sets; and regulating an internal chamber pressure of the mass spectrometer according to the chamber pressure regulation parameter in the test data set when there exists a test data set with a matching degree greater than or equal to a preset value.

The application discloses a kind of liquid-solid interface frozen XPS characterization method.The method comprises the following steps: (1) with thin layer two-dimensional material as solid phase, solid phase is transferred to liquid phase sample, and solid phase is salvaged with aluminium oxide substrate, at this time, a layer of liquid film of liquid phase sample is formed between aluminium oxide substrate and solid phase, and liquid-solid interface sample is constructed;(2) liquid-solid interface sample is fixed on sample holder, placed in liquid nitrogen and frozen, after liquid phase sample is frozen and solidified, it is placed into sample cavity and vacuumized, then it is transferred to test cavity for testing, solid phase is etched using ion beam etching technology, until the liquid-solid interface of solid phase and liquid phase sample is detected, so as to realize the XPS characterization of liquid-solid interface.The liquid sample is frozen and solidified by using liquid nitrogen cooling mode, which can meet the vacuum requirement of XPS characterization, and realize the characterization of liquid sample composition, valence state and other information in ultra-high vacuum environment.

This invention provides a method for predicting the Tm value of a melting curve, relating to the field of biodetection technology. The method includes the following steps: constructing a Tm value labeling model and a Tm value prediction model; acquiring data information of the sample to be tested and inputting the data information into the Tm value labeling model; preprocessing the data information by the Tm value labeling model and labeling the sample to be tested with or without a Tm value; samples with Tm values ​​constitute a valid sample set; extracting several peaks from the original melting curve to obtain an original Tm value set; encoding the original Tm value set according to temperature intervals; wherein the temperature bits in the original binary vector are arranged according to temperature intervals; inputting the original melting curve from the valid sample set into the Tm value prediction model to obtain the predicted Tm value. Arranging the temperature bits according to temperature intervals allows the model to learn the correlation between adjacent temperatures, thereby more accurately capturing the influence of temperature changes on the Tm value, and thus improving the accuracy of Tm value prediction.

The invention relates to the technical field of separation and extraction of precious metals, in particular to a method and a system for analyzing and optimizing selected silver based on a fire assaying method. The method comprises the following steps: collecting sample component data in real time by using a sensor, and obtaining standardized sample component data through denoising and standardization treatment; classifying the samples by adopting a support vector machine, and dividing the samples into a high difference group and a low difference group based on component difference; for high-difference group samples, performing iterative search of a preliminary optimization parameter set by adopting a genetic algorithm; the influence of smelting atmosphere parameters on the separation efficiency is evaluated through a simulation method, the smelting atmosphere parameters are adjusted, and the stability of the smelting atmosphere parameters is verified; predicting a separation efficiency trend according to process feedback data, and updating an optimization parameter set based on the separation efficiency trend; and finally, the control system generates an equipment control instruction according to the updated parameter set to ensure that the production equipment executes the separation process according to the optimization condition. The efficient and stable separation process is achieved for precious metal gold and silver.

This invention belongs to the field of spectroscopic technology for sample composition and content analysis, specifically relating to a device and method for measuring the concentration of specific elements based on fiber Bragg gratings and LIBS. A solid-state Q-switched laser emits pulsed light that interacts with the substance through an optical path. The resulting plasma is transmitted to corresponding single-mode fibers, circulators, and corresponding gratings, then returns to the circulator and is fed into the corresponding detector. A timing controller controls the light intensity collected by the detector for integration calculation, and the result is returned to a computer. The wavelengths selected by the first and second fiber Bragg gratings correspond to the internal standard element and the analyte element in the sample, respectively. Using the ratio of the corresponding light intensities and the mathematical relationship established with the standard sample, the concentration of the analyte element in the unknown sample can be calculated. This invention eliminates the need for a complex spectrometer structure, resulting in a simple device structure, high resolution for single-element concentration measurement, and allows for control of the fiber Bragg grating wavelength within 100 pm using a temperature-controlled water bath, or the measurement of different element concentrations by replacing the fiber Bragg grating with different wavelengths.

The application discloses a kind of field geological sample intelligence airing equipment, it is related to soil sampling technical field, including: rack, airing platform, shed top, the airing platform is by several groups of sample clamps for fixing sample composition;The shed top includes several groups of support frame, the top of the support frame is detachably installed with guide rod, the lower side of any one end of the guide rod is equipped with cloth reel, the side of the rack away from cloth reel is detachably installed and is equipped with the winding mechanism for pulling rain cloth to cover the rack.The design scheme of the present application is designed by installing the airing platform that can be turned over on the rack, when airing soil sample, soil sample is fixed by sample clamp, according to the airing cycle, sample clamp will periodically automatically turn over 180 degrees, so that the front and back of soil sample can be evenly aired, to prevent soil sample from not being dried, while improving the airing efficiency, the work burden of researcher is reduced.

The present invention provides a mineral exploration method, a mineral exploration system and a mineral exploration robot, which are applied to the mineral exploration robot. The mineral exploration robot is provided with a visual perception device, an analysis device and a sampling tool, and is communicatively connected to an external host computer; the method includes: obtaining an exploration point image of a target exploration point through the visual perception device; inputting the exploration point image into a pre-trained geological type recognition model to output the actual geological type corresponding to the exploration point image; determining a target sampling tool corresponding to the actual geological type based on the actual geological type and the preset corresponding relationship between the geological type and the sampling tool, and collecting samples through the target sampling tool; and analyzing the collected samples in real time through the analysis device to obtain real-time exploration data of the target exploration point. In this way, the geological type can be automatically identified in complex terrains, a suitable sampling tool can be selected, and the sample composition can be analyzed in real time, thereby improving the safety and efficiency of exploration work.

The present application belongs to the technical field of metallurgical quality detection, and relates to a method for tracking steel sample detection time, comprising the following steps: S1, recording sample information in the sample detection process, including sample type, sample code, order arrival time, sample sending time and sample arrival time; S2, printing a sample label through a label printer and sticking the label on the sample; S3, sending the sample to a preparation station for sample preparation; S4, scanning a two-dimensional code at the sample code column of a direct-reading spectrometer to input the sample code; and S5, displaying sample composition data and sample analysis time. According to the present application, the detection time of each sample is dynamically and real-timely displayed in the detection and analysis system of the steel sample, so that the problem that the operation personnel cannot intuitively understand the detection time and cannot timely and accurately fill in the reason for exceeding the detection time is solved, thereby avoiding the situation that the detection result is affected by untimely information transmission and it is difficult to trace the failure reason.

A solution for approximately measuring one or more X-ray intensities of a sample by an X-ray detection system that includes at least one collimator having a given angular range, a monochromator, and an X-ray detector. Measurement intensities are received from the detection system at respective one or more diffraction angles. Simulated sample intensities are calculated from an X-ray fluorescence sample model having initial sample model parameters indicative of a sample composition and / or a layer thickness of one or more sample layers. Triangular collimator corrections are applied to the simulated sample intensities, and mathematical distances between the corrected simulated sample intensities and corresponding measured intensities are determined. The sample model parameters are adjusted and the correction step is repeated until the distance change falls below the minimum distance change. Sample model parameters associated with the corrected simulated intensities are provided as approximate concentration values of the respective components contained in the measured sample and / or a layer thickness of the measured sample.

To provide a method and system for determining sample composition from spectral data acquired by a charged particle microscopy system.SOLUTION: Chemical elements in a sample are identified by processing spectral data with a trained neural network (NN). If the identified chemical elements do not match a known elemental composition of the sample, the trained NN is retrained with the spectral data and the known elemental composition of the sample. The retrained NN can then be used to identify chemical elements within other samples.SELECTED DRAWING: Figure 1

This invention provides a method and system for determining sample composition based on spectral data. [Solution] A scientific instrument for performing spectral analysis comprises a memory for storing computer executable instructions and a processor for executing computer executable instructions, wherein the computer executable instructions perform a first operation using an encoder to compress one or more unknown spectra into one or more compressed unknown spectra in latent space, and a second operation to match one or more compressed unknown spectra with one or more compressed known spectra in order to obtain one or more candidate matches of a sample.

The application discloses a drilling leakage prediction model establishment method, a drilling leakage prediction method and a device. The drilling leakage prediction model establishment method comprises the following steps: for a drilled well with leakage mark data, extracting a seismic attribute value corresponding to each depth value of the leakage mark from each set seismic attribute body according to a synthetic record of the well, so as to obtain a sample containing the leakage mark corresponding to the depth value and each seismic attribute value; the leakage mark data comprises a plurality of depth values of the well and the leakage mark corresponding to each depth value; a plurality of samples are combined into a sample set, the sample set is used for training a set classification model, so as to obtain a classification model used for predicting drilling leakage, and the classification model comprises at least one sub-classification model. The drilling leakage can be reasonably predicted before drilling.

The invention is directed to compositions and methods for collecting, transporting, and storing, without refrigeration, biological materials, which may comprise samples of biological, clinical, forensic, and / or environmental origin. These compositions preserve the viability of the collected organisms and / or the RNA / DNA and proteins in the sample composition mixture and permit the long-term storage of samples. Compositions are compatible with subsequent manipulation of the sample, including propagation and culture of the collected microorganisms, or isolation, purification, detection, and characterization of proteins, nucleic acids, and other macromolecules. When the compositions containing microorganisms and any polynucleotides therein are further processed, such as by nucleic acid testing, there is an increased ability to detect, isolate, purify and / or characterize select microbes and their components, such as nucleic acids, when compared to conventional microbial transport media that contain interfering substances and RNA / DNA extraction is not required prior to PCR analysis. In particular, the compositions disclosed allow for the collection, transport and storage of biological samples for extended periods at ambient temperature, while maintaining the integrity of the macromolecules of the sample for subsequent extraction, identification, and quantitation.

The embodiment of the invention discloses a sample component analysis method, electronic equipment, a storage medium and a program product, and relates to the technical field of sample component analysis. The method comprises the following steps: acquiring a target sample, determining a target test condition, and analyzing the target sample based on the target test condition to obtain a first analysis result of the target sample; based on the first analysis result, determining at least two reference samples associated with the target sample and a blank sample; measuring the reference samples and the blank samples to obtain measurement data, and determining a quantitative analysis model based on the measurement data; and in response to a component analysis instruction of a to-be-detected sample, determining target components of the to-be-detected sample based on the quantitative analysis model. According to the scheme provided by the embodiment of the invention, the components of the sample and the content of each component can be quickly and accurately determined.

The application discloses a kind of geological sample component identification and abnormal detection system based on machine learning, it is related to geological sample component identification and detection technical field, first by the ratio of Compton and Rayleigh scattering intensity calculated by ray fluorescence energy spectrum, obtain effective atomic number and its uncertainty;Again, the continuum of short-wave infrared spectrum is removed, the depth of aluminum hydroxyl absorption band and band shape asymmetry are extracted, and the slope is used to represent the granularity, and the monotone spline is trained to obtain the clay proportion estimation;According to the end member set and atomic number table, the theoretical atomic number and uncertainty are obtained, and the measurement side is integrated into a unified scale to obtain the cross-modal inconsistency index.The state variable and the index are used as the target to adaptively optimize the collection and retest, and the consistency constraint is executed to solve the mixture and abnormality determination.The application can carry out high-precision identification and abnormality determination under complex working conditions.

This disclosure relates to a method for near-infrared spectral conversion of gasoline. Hydrocarbon compounds are used as standard samples, and their spectra are acquired on two spectrometers. A fitting algorithm is then used to obtain a fitting coefficient vector between the standard spectral matrix obtained from the first spectrometer and the spectrum of a typical gasoline sample. This fitting coefficient vector is then multiplied by the standard spectral matrices obtained from both spectrometers to obtain the gasoline fitted spectral matrix. A mathematical transformation is then performed on this resulting matrix to obtain the gasoline near-infrared spectral conversion coefficients between the first and second spectrometers. This method eliminates minor spectral differences between near-infrared spectra of gasoline samples measured by different spectrometers. In practical applications, it eliminates the need to collect gasoline standard samples, saving manpower and resources, while improving the accuracy of spectral conversion. It is suitable for rapid analysis of gasoline sample composition and properties.

This application discloses an elemental composition analysis method, apparatus, storage medium, and product, relating to the field of laser technology. It controls a galvanometer scanning optical path to guide a pulsed laser into an array of fiber optic bundles to excite plasmas at multiple spatial points on the sample surface. The compositional spectral signals generated by each plasma are collected, and spatial distribution information of the sample's elemental composition is generated based on these signals. The array of fiber optic bundles improves collection efficiency by collecting the emitted plasma light, and the combination of the fiber optic bundles and fiber optic probes enables spatial scanning of the sample surface, obtaining the elemental composition distribution of the sample within a spatial range, thus improving the accuracy of sample composition analysis.