1373 results about "Analytical technique" patented technology

A method and a system for reconstructing aerosol chemical components based on CNN-BiLSTM-BO, including collecting multi-source environmental observation data through observation equipment, preprocessing and extracting key characteristic variables. The pre-treated multi-source environmental observation data are input into the CNN-BILSTM model for feature analysis, and the CNN-BiLSTM hyperparameters are adjusted by Bayesian optimization algorithm to generate a reconstructed model of aerosol chemical components. After verifying the performance and stability of the reconstructed model, the predicted results of the chemical components of the aerosol are output. On the basis of not relying on traditional chemical analysis technology, the invention can accurately reconstruct various aerosol chemical components, greatly reduce the cost and time of chemical analysis, effectively solve the problems of variable inconsistency, data missing, and spatio-temporal mismatch in multi-source observation data, and automatically adjust hyperparameters through Bayesian optimization algorithm to ensure that the output prediction results are more accurate.

The invention discloses a pollution space analysis method and system based on atmospheric pollution concentration data, and particularly relates to the technical field of data analysis. A high-precision pollutant concentration spatial distribution model is constructed by combining pollutant diffusion characteristics and geographic information, and regional pollution differences are revealed; identifying a pollution source emission mode and analyzing the evolution trends of pollutants in different time and space ranges by matching spatial and temporal change analysis with a pollution source emission list; the influence of real-time meteorological data on pollution diffusion is analyzed, and a pollutant spatial distribution model is adjusted, so that the prediction precision is improved; pollution concentration distribution, pollution source emission and meteorological influence are combined, pollution hot spot areas are accurately identified, future pollution evolution conditions are analyzed and predicted based on historical trends, scientific and reasonable pollution treatment suggestions are provided, the limitation of traditional interpolation and statistical regression models is broken through, dynamic and accurate modeling of pollutant concentration is achieved, and the method is suitable for large-scale popularization and application. And the scientificity of pollution source tracing and treatment decision making is improved.

The invention relates to the technical field of process parameter analysis, and discloses a process parameter analysis method and system for a foaming material forming process and a storage medium, and the method comprises the following steps: carrying out parameter collection and data statistics on an MPPO material under a 160 DEG C standard process condition to obtain process parameter reference data; carrying out a load pressure parameter orthogonal test on the material to obtain a load pressure process parameter database; forming temperature gradient analysis is carried out, sampling testing is carried out at the interval of 5 DEG C from 160 DEG C to 190 DEG C, and a temperature control curve is obtained; performing coupling analysis and pressure dynamic compensation to obtain a forming process parameter combination; carrying out wet weight, dry weight and size detection on a product produced under the forming process parameter combination, and carrying out multi-dimensional parameter calculation to obtain a quality control index; and performing association verification and parameter correction on the quality control index and the forming process parameter combination, and outputting target process specification data. The method improves the control precision of the process parameters.

The invention discloses a soil micro-plastic pollution monitoring analysis method based on big data analysis, and relates to the technical field of monitoring analysis. Comprising the following steps: arranging a sensor and sampling equipment, and collecting micro-plastic data; the method comprises the following steps: researching migration and diffusion laws of micro-plastic data in soil in different time periods by utilizing a time sequence analysis method, and constructing a dynamic migration model of micro-plastic in combination with meteorological conditions and geographical conditions; the method comprises the following steps: performing spatial analysis on micro-plastic concentration data of a monitoring area, identifying a high-risk area of micro-plastic pollution, and preliminarily determining a gathering area and a pollution source of pollutants; and comparing the position of the pollution source with a historical pollution source record, verifying the accuracy of the pollution source, and generating early warning information of a potential pollution source. According to the invention, meteorological and topographic factors are combined to identify the trend and path of pollutant diffusion, so that the positioning of the pollution risk area is more accurate, and comprehensive monitoring and deep analysis of micro-plastic pollution are realized.

The invention relates to the technical field of soil pollution component analysis, and discloses an agricultural soil pollution prediction method. The method comprises the following steps: carrying out soil physicochemical property detection through layered gridding sampling, determining the heavy metal content, the organic matter content and the enzyme activity, and obtaining a pollution characteristic data set; monitoring diffusion characteristics of pollutants by adopting an electrochemical sensing detection array, and generating a migration rule model; a multi-parameter monitoring system is used for detecting the pH value, the oxidation-reduction potential and the ion activity, and a dynamic change sequence is formed; establishing a colloid interface action response matrix, and constructing a pollutant accumulation model; determining the occurrence form and the ion concentration of the pollutants, and generating an interaction map; and finally, constructing an early warning system, and outputting a prevention and control scheme. According to the invention, through cooperative application of multiple analysis and test means, and in combination with interface action mechanism research of pollutants in soil, whole-process intelligent monitoring of soil pollution prediction is realized.

The invention discloses a method for comprehensively identifying PFAS in an environment by combining targeted analysis, suspicious screening and non-targeted identification. The method comprises the following steps: S1, carrying out liquid chromatography-high resolution mass spectrometry fullscan / DDA / DIA analysis on an environmental sample; s2, carrying out liquid chromatography-high resolution mass spectrometry analysis on the plurality of PFAS standard substances; s3, according to a public chemical database and literature, collecting names and molecular formulas of a plurality of PFASs, calculating an accurate mass number, and jointly establishing a suspicious screening database in combination with an open-source MS2 spectrogram library; s4, establishing a non-targeted identification work flow by combining the mass number characteristics of the PFAS, the characteristic MS2 fragments, the characteristic neutral loss and the homolog characteristics; and S5, integrating the targeted analysis compound, the candidate compound subjected to suspicious screening and the candidate compound subjected to non-targeted identification, and comprehensively identifying the PFAS in the environmental sample. According to the method disclosed by the invention, the known and unknown perfluoroalkyl / polyfluoroalkyl compounds are fully identified through three complementary analysis technologies.

The invention relates to the technical field of cross-modal data fusion analysis of soil component detection and improvement agent preparation, in particular to a preparation method of a soil improvement agent based on component detection, which comprises the following steps: acquiring soil component data through a near infrared spectrometer, a high performance liquid chromatograph and an inductively coupled plasma mass spectrometer; an incremental principal component analysis algorithm is combined with an oscillation suppression function to update a covariance matrix in real time, a dynamic defect factor priority list is generated, a multi-objective optimization model improved based on NSGA-II is guided to integrate the soil pH value, humidity and organic matter content to construct a dose response curved surface, and a Pareto optimal solution set is solved. A sensor array collects environment feedback data, drives a transfer learning algorithm to calibrate parameters, a dynamic incidence matrix attenuation rate and optimal weight adaptive adjustment, iteratively outputs a modifier synergistic effect solution set through a closed-loop control mechanism, and solves the problems of difficult data fusion, principal component weight offset and component synergistic deviation. And the proportioning accuracy and stability are improved.

The invention discloses a method for predicting the content of heavy metals in different occurrence forms in soil based on machine learning, and relates to the technical field of soil component content analysis, and the method comprises the following steps: (1) collecting soil physicochemical properties, the total amount of soil heavy metals, the types of the heavy metals in the soil and the content of the heavy metals in different occurrence forms in the soil from a literature library, constructing a sample database; (2) preprocessing the sample database to obtain a preprocessed sample database; (3) for each kind of heavy metal, extracting corresponding sample data from the preprocessing sample database, dividing the sample data into a training set and a test set, selecting a machine learning algorithm, establishing a prediction model training model of different occurrence form contents of the heavy metal in the soil, and optimizing hyper-parameters in the training process; and (4) predicting the content of heavy metals in different occurrence forms in the soil to be detected by using the optimized prediction model. The method has a good application prospect in the aspects of heavy metal pollution risk evaluation and the like.

The present invention relates to the technical field of molecular interaction analysis, and specifically provides a method for analyzing intermolecular interactions. The method comprises the following steps: using a rare earth material with a ligand molecule modified on its surface as an upconversion material, contacting the upconversion material with a target molecule in a solution system, irradiating the solution system with excitation light that matches the rare earth material, and continuously changing the intensity of the excitation light actually received by the upconversion material as the target molecule continuously binds and dissociates with the ligand molecule of the upconversion material in a dynamic process, thereby changing the intensity of the emitted light. By recording the curve of the emission light intensity changing with time, the molecular interaction kinetic constants, such as the binding rate constant (K on ), dissociation rate constant (K off ) and affinity (K D ), etc., which solves the technical problems of low accuracy of existing BLI technology and high cost of SPR technology. Based on the above principles, the present invention has also developed a series of experimental consumables, kits, sensors and analytical devices for molecular interaction analysis.

The invention relates to the technical field of drug data analysis, in particular to a drug stability test and evaluation method and device, which are used for collecting drug component data, analyzing the distribution and aggregation trend of drug components, evaluating the stability characteristics of the drug components under multiple conditions and generating a fractal dimension calculation result. According to the invention, by collecting and updating the drug component data in real time and evaluating the stability characteristics of the drug under variable environmental conditions, the environmental change can be reflected in time, and the timeliness and accuracy of the prediction result can be significantly improved. According to the method, the function of adaptively adjusting model parameters is achieved, and real-time environment data is combined, so that the prediction model can more accurately simulate behaviors of drugs under different environment conditions, and therefore, the testing flexibility is improved, and the processing capacity for complex data is enhanced. In addition, by analyzing the specific influence of environmental factors on the drug stability, the setting accuracy of drug storage and transportation conditions is further improved.

The invention relates to the technical field of water quality data analysis, and discloses a river water quality pollution assessment method and system based on big data analysis, and the method comprises the steps: building a water quality parameter set; obtaining a preprocessed water quality data set; obtaining a global statistical analysis result through descriptive statistical analysis; carrying out hierarchical multi-time evaluation analysis to obtain a hierarchical evaluation result; obtaining a deviation value between the current water quality data and standard water quality data of a laboratory; reliable water quality characteristic data are obtained; a difference trend analysis result is obtained; performing relevance verification on the river water quality distribution map and the time change map of the target area according to the difference trend analysis result to form a comprehensive analysis result; and finally generating a comprehensive water quality pollution assessment report containing water quality traceability information and a comprehensive analysis result. According to the invention, a multi-parameter sensing technology and intelligent data processing are organically combined, so that the water quality of the river is efficiently, accurately and carefully analyzed, and the pollution degree is evaluated.

The invention relates to the technical field of sample analysis, and discloses a petroleum fractionating tower product analysis method and system based on a near infrared technology. Performing near infrared spectrum scanning on different batches of samples to obtain near infrared spectrum data of the different batches of samples, and preprocessing the near infrared spectrum data; and calculating optimal correction values of different batches of samples according to the preprocessed measured spectral intensity, obtaining key spectral characteristics of the different batches of samples, combining the measured spectral intensity corresponding to the key spectral characteristics and the optimal correction values into an input vector, and inputting the input vector into a pre-trained calibration model to obtain chemical property information of the different batches of samples. The chemical property information of the sample can be analyzed based on the change of the measured spectral intensity, the optimal correction value serves as a correction factor of an analysis result and is used for compensating the deviation in the analysis process, and the optimal correction value is added to the analysis result to offset the analysis deviation.

The invention discloses a sample analysis method and system based on a multi-dimensional gas chromatograph data fusion algorithm, and belongs to the technical field of sample analys.The method comprises the steps that 1, information of a multi-dimensional gas chromatograph is collected, and the data fusion algorithm is set according to the information of the multi-dimensional gas chromatograph; 2, identifying the detection sample, and detecting the detection sample through a multi-dimensional gas chromatograph to obtain corresponding sample detection data; 3, determining debugging parameters of a data fusion algorithm according to the sample detection data, and debugging the data fusion algorithm according to the debugging parameters; 4, performing fusion processing on the sample detection data through a debugged data fusion algorithm to obtain fused detection data; and 5, obtaining a sample analysis target of the user, and processing the fusion detection data according to the sample analysis target to obtain a sample analysis result.

A sequence of polymer units in a polymer (3), eg. DNA, is estimated from at least one series of measurements related to the polymer, eg. ion current as a function of translocation through a nanopore (1), wherein the value of each measurement is dependent on a k-mer being a group of k polymer units (4). A probabilistic model, especially a hidden Markov model (HMM), is provided, comprising, for a set of possible k-mers: transition weightings representing the chances of transitions from origin k-mers to destination k-mers; and emission weightings in respect of each k-mer that represent the chances of observing given values of measurements for that k-mer. The series of measurements is analysed using an analytical technique, eg. Viterbi decoding, that refers to the model and estimates at least one estimated sequence of polymer units in the polymer based on the likelihood predicted by the model of the series of measurements being produced by sequences of polymer units. In a further embodiment, different voltages are applied across the nanopore during translocation in order to improve the resolution of polymer units.

The present invention discloses a three-dimensional fluorescence portable water quality analyzer for pollution component determination and source tracing, and relates to the technical field of water quality analysis, the analyzer comprises the following components: a sample collection and processing module for collecting a water sample from a to-be-detected water body, filtering to remove impurities, and diluting the water sample according to a self-adaptive dilution multiple algorithm; fluorescence intensity information of a water sample under different excitation wavelengths and emission wavelengths is obtained through the three-dimensional fluorescence detection module, rich three-dimensional fluorescence spectrum data is formed, the real-time fluorescence lifetime imaging module is introduced, and by measuring the fluorescence lifetime of a fluorescent substance and utilizing the principle that different fluorescent substances have different fluorescence lifetime characteristics, the real-time fluorescence lifetime of the water sample is obtained. Various pollution components in the water sample are further distinguished and recognized, the pollution components can be accurately distinguished through fluorescence lifetime measurement and imaging, the accuracy of pollution component judgment is greatly improved, and a reliable basis is provided for accurate treatment of water quality pollution.

A sequence of polymer units in a polymer (3), eg. DNA, is estimated from at least one series of measurements related to the polymer, eg. ion current as a function of translocation through a nanopore (1), wherein the value of each measurement is dependent on a k-mer being a group of k polymer units (4). A probabilistic model, especially a hidden Markov model (HMM), is provided, comprising, for a set of possible k-mers: transition weightings representing the chances of transitions from origin k-mers to destination k-mers; and emission weightings in respect of each k-mer that represent the chances of observing given values of measurements for that k-mer. The series of measurements is analysed using an analytical technique, eg. Viterbi decoding, that refers to the model and estimates at least one estimated sequence of polymer units in the polymer based on the likelihood predicted by the model of the series of measurements being produced by sequences of polymer units. In a further embodiment, different voltages are applied across the nanopore during translocation in order to improve the resolution of polymer units.

The invention belongs to the technical field of quartz raw ore process mineralogy analysis, and particularly relates to a quartz raw ore process mineralogy analysis method which is a method for judging whether quartz raw ore can be used as high-purity quartz raw ore or not. The quartz raw ore is subjected to sample preparation, wherein a sample preparation method of a powder sample comprises the steps of crushing, wet grinding, filtering concentration and drying in sequence; carrying out chemical component analysis, phase component analysis and crystal structure analysis on the obtained powder sample; and carrying out electron probe microcell analysis, laser Raman spectrum analysis, lithofacies microscopic analysis and inclusion microscopic analysis on the obtained optical sheet. According to the quartz raw ore process mineralogy analysis method, the preparation method of the powder sample is simple, low in energy consumption and environmentally friendly, meanwhile, the obtained powder sample is slightly polluted by the outside, the obtained quartz raw ore process mineralogy analysis result can be closer to a true value, meanwhile, stable production of high-purity quartz sand can be ensured, and the production cost is reduced. And the loss of manpower, financial resources and material resources is reduced.

The invention relates to the technical field of fertilization scheme analysis, and discloses a polyglutamic acid and compound fertilizer combined analysis method and equipment and a storage medium, and the method comprises the following steps: determining crops needing to be analyzed; determining a growth cycle and a critical period of the crops needing to be analyzed; determining environment conditions and nutrient absorption characteristics of crop growth, and selecting proper fertilizer types and fertilization modes; according to the selected fertilizer types and fertilization modes, combined fertilization schemes of different growth periods and different key periods are generated, and a plurality of combined fertilization schemes are generated in each growth period and key period; evaluating the advantages and disadvantages of the combined fertilization schemes, and determining the optimal combined fertilization scheme of each growth cycle and key period; and verifying the optimal combined fertilization scheme to obtain a verification analysis result. According to the invention, the optimal polyglutamic acid and compound fertilizer combined fertilization scheme can be automatically calculated according to the set target formula and crop requirements, and detailed formula proportion and cost estimation are given.

The invention relates to the technical field of acidic wastewater titrimetric analysis, and discloses an automatic sampling titrimetric analysis method based on a copper smelting acidic wastewater treatment link, which comprises the following steps: collecting waste acid to obtain a waste acid sample; carrying out titration treatment on the waste acid sample to obtain a waste acid sample image after the titration reaction is finished, and carrying out sediment outline extraction on the waste acid sample image to generate sediment coagulation complexity; according to the method, automatic sampling titration is combined with image analysis, precipitation coagulation complexity and arsenic specific hue separation degree are extracted, a precipitation effectiveness index and an arsenic residue risk coefficient are generated through dynamic fusion, arsenic precipitates and other precipitates in similar forms are accurately distinguished by utilizing precipitate contour features and arsenic specific hue in an HSV color space, and the arsenic content is accurately determined. The method has the advantages that spectral signal superposition interference is avoided, and the arsenic residual state can be accurately reflected, so that whether arsenic removal is qualified or not is reliably judged, the accuracy and safety of waste acid treatment are improved, and the quality of water reuse is guaranteed.

The invention belongs to the technical field of honey analysis, and particularly relates to a method for analyzing characteristic chemical components of Qinling Mountain medium-peak honey. The analysis method comprises the following steps: obtaining different extraction layers, and carrying out mass spectrometry on each layer of sample; constructing a molecular network by mass spectrum data through a GNPS platform, and comparing the mass spectrum data with a database to obtain primary identification; unmatched nodes predict the skeleton by using an NAP tool to obtain a secondary result; then fractions are separated, and an unknown structure is deduced by combining an SMART technology with nuclear magnetism; and finally, synthesizing the three types of results to determine the characteristic chemical components of the honey. Compared with a single chromatography-mass spectrometry technology, the analysis method provided by the invention not only realizes data visualization, but also reduces the dependence of chemical component identification on a database to a certain extent, and provides reference for rapid characterization of chemical components in a honey crude extract or fraction.

The invention provides an analysis method for high-throughput evaluation of tobacco nicotine synthesis capability, and belongs to the technical field of nicotine synthesis capability analys.The analysis method comprises the steps that tobacco seeds are disinfected, germinated and cultured for 14 days to obtain seedlings, the seedlings are transferred to a control medium and an induction medium added with 3 [mu] M of methyl jasmonate to be cultured for 15 days, and the seedlings are obtained; the method comprises the following steps: removing water from an overground part for 15 minutes at 105 DEG C, drying at 65 DEG C until the weight is constant, grinding the overground part into powder, adding a NaOH solution and ethyl acetate containing an internal standard, carrying out vortex mixing uniformly, carrying out ultrasonication for 15 minutes, taking supernate, filtering to obtain sample extract liquor, inputting peak area data into an intelligent prediction model based on a hierarchical weight mechanism, and processing to obtain prediction correction data, the nicotine concentration of a sample is calculated by combining gas chromatography detection with a standard curve, the concentration is corrected by utilizing predicted correction data, finally, nicotine content data is calculated according to the corrected concentration and the dry weight of the sample, and high-precision evaluation of the tobacco nicotine synthesis capability is realized.

The invention discloses a gas analysis method and system for a gas source purification process, and relates to the technical field of gas detection and analysis. The method comprises the following steps: synchronously acquiring optical, electrochemical and conductivity detection signals in a gas source purification pipeline, and combining environmental parameters such as temperature, humidity and flow; carrying out filtering, anomaly elimination and normalization processing on the detection signal, constructing a multi-dimensional feature vector, and carrying out dimensionality reduction to obtain a principal component feature; and dynamically distributing weights through a self-adaptive weighted fusion model, and calculating a gas purification characteristic value. Establishing a drift prediction model based on historical data, inputting environmental parameters and operation duration to calculate a predicted drift amount, and correcting a gas purification characteristic value; when the drift distance exceeds a threshold value or reaches a calibration period, standard gas is introduced to detect the average response value of the drift distance, a calibration coefficient is calculated according to the concentration of the standard gas, the calibration coefficient is fed back and updated to the weighted fusion model and the drift prediction model, and self-correction and high-precision analysis of the gas purification process are achieved.

The invention discloses a sample adjusting device for a microbiological detection analyzer, and relates to the technical field of microbiological detection analysis, the sample adjusting device comprises a device main body, an inner cavity of the device main body is fixedly connected with a fixing plate, the fixing plate is fixedly connected with a servo motor, an output shaft of the servo motor is fixedly connected with a rotating disc, and the rotating disc is fixedly connected with a rotating shaft of the rotating disc. A crank is rotationally connected to the rotating disc, a loading table is rotationally connected to the end, away from the rotating disc, of the crank, a guide rail is fixedly connected to an inner cavity of the device body, and a first sample tube and a second sample tube are arranged on the loading table; in the process that the test tube moves to the position below the first sample tube and the second sample tube, a piston rod of a piston barrel moves, detection liquid in a liquid storage barrel is dropped into the test tube, meanwhile, the dropping quantity of the detection liquid can be adjusted and controlled, errors caused by different persons in manual operation are avoided, and the detection accuracy is improved. In addition, direct contact between operators and reagents and samples is reduced in the automatic process, and the risks of cross contamination and environmental pollution are avoided.

The utility model discloses an automatic cleaning device for a water quality analyzer, which comprises a mounting plate, a transverse plate is arranged on one side of the mounting plate, an analyzer body is arranged on the transverse plate, the bottom of the analyzer body is connected with a probe through a lead, a lifting plate is mounted on the lower wall of the transverse plate through a telescopic rod, the probe is fixedly connected with the lifting plate, and the probe is fixedly connected with the lifting plate. The device relates to the technical field of water quality analysis and is compact in structure, the sleeve drives the lifting plate to move downwards by rotating the screw rod, the probe extends into a water body for monitoring and analysis, the motor drives the driving gear to rotate, the rotating ring is arranged in the rotating ring in a sliding mode, and the rotating ring is arranged in the rotating ring in a sliding mode. The rotating ring drives the pair of rotating drums to rotate synchronously, brushes arranged on the outer sides of the rotating drums can clean the surface of a probe, impurities are prevented from being accumulated and attached to the surface of the probe to affect analysis and detection precision, a transmission gear is matched with a second gear ring, the rotating drums can drive the brushes to rotate, the cleaning effect is improved, and convenience is brought to use of people.

The invention relates to a near-infrared coal quality quantitative analysis model construction method, and belongs to the technical field of coal quality analysis. In order to solve the problems that a traditional coal quality analysis method is tedious in operation, time-consuming, destructive and difficult to meet rapid nondestructive detection requirements, the invention aims to realize rapid, accurate and quantitative detection and analysis of moisture, ash and volatile components in coal by combining a near infrared spectrum analysis technology with a deep learning algorithm. The method comprises the following specific steps: collecting and preparing a coal sample according to the national standard, and measuring moisture, ash and volatile components; the method comprises the following steps: acquiring spectral data by using a near infrared spectrometer, marking the spectral data, performing smoothing, multiplicative scatter correction and normalization processing, and dividing a training set and a test set according to a Kennard-Stone algorithm; and constructing a cascaded integrated deep learning prediction model of CNN-LSTM, and performing training, evaluation and optimization to predict coal quality indexes. According to the method, data are obtained based on a strict national standard experiment method, the accuracy of quantitative analysis of coal quality and the robustness of the model are improved by combining the near infrared spectrum technology with the deep learning model, and powerful support is provided for quality control and reasonable utilization of resources in the coal industry.

The invention belongs to the technical field of chemical analysis of metallurgical standard samples, and discloses a super duplex stainless steel spectrum standard sample with high quality, high uniformity, high stability and accurate fixed value and a development method thereof. The method comprises the following steps: component design and raw material proportioning, smelting and casting, forging and homogenization treatment, primary inspection of uniformity and sample processing, uniformity inspection, constant value analysis and mathematical statistics, determination of characteristic values of standard samples, stability analysis of the standard samples after long-term storage, and traceability guarantee measures. The super duplex stainless steel spectrum standard sample comprises the following components in percentage by mass: 25%-26% of Cr, 6.50%-7.50% of Ni, 3.50%-4.50% of Mo, 0.23%-0.27% of N, 0.5%-1.0% of Cu, 0.5%-1.0% of W, and the balance of iron and inevitable impurities, and the content of trace elements including sulfur, aluminum and boron is controlled in a specific ppm level range.

The invention relates to the technical field of section analysis of printed circuit boards, in particular to a section analysis method for PCB positioning cutting, a target abnormal area is positioned on a PCB through an optical microscope, the optical microscope not only can observe the morphology of the surface layer of a sample, but also can observe the morphology within a certain range below the surface layer, and the accuracy of section analysis is improved. And meanwhile, the optical microscope is very sensitive and accurate in color identification, so that compared with the prior art in which the target abnormal area is positioned on the PCB through a scanning electron microscope, the target abnormal area can be more effectively positioned on the PCB, and the purpose of reducing the positioning difficulty of the target abnormal area is achieved. Besides, the positioning layer and the protection layer are deposited in the target abnormal area, so that the cross section sample can be prevented from being physically and chemically damaged in the cutting process on the basis of improving the cutting precision of the cross section sample, and the failure analysis precision of the PCB is improved.

The invention relates to the technical field of liquid chromatography, and discloses a mixed product liquid chromatography comprehensive analysis method which comprises the following steps: S1, mixing products: respectively mixing aldehyde compounds and ketone compounds with different mobile phases, and then injecting into an injection chromatographic system; s2, liquid chromatographic analysis: separating and analyzing a mixed product by using a liquid chromatograph; s3, performing qualitative analysis; on the basis of liquid chromatographic analysis, each peak in a chromatogram is identified. The method aims at qualitative and quantitative analysis of main substances (groups) in an organic reaction mixed product system; the method is suitable for analyzing the relative percentage content of products related to organic chemical reactions such as raw materials (nonylphenol) related to a core production process, nonylphenol formylation reaction, nonylphenol esterification reaction, phenolic ester Fris rearrangement reaction and the like, and samples in a refining process; the influence of absorption peaks and chromatographic line oscillation of other non-target substances on the content analysis result can be effectively avoided.

The invention relates to the technical field of mineralogy, and provides a prediction method for mineral flotation yield. According to the method, the content and dissociation degree of the target minerals under different size fractions are accurately obtained through the technologies of ore grinding, system screening and automatic mineralogy analysis, the yield prediction method based on the mineral selectability physical model is established, the crossing from elements to minerals and from the whole to the size fractions can be achieved, and the yield prediction accuracy is improved. And a brand-new, scientific and reliable technical reference is provided for precise prediction and process optimization of the sulfide ore flotation yield.

The invention discloses a natural gas calorific value test result correction method, system, equipment and medium, and relates to the technical field of natural gas analys.The method comprises the steps that according to the initial calorific value, the carbon dioxide content and the relative density obtained through testing and pressure data and temperature data of a test point, the first nitrogen content is obtained through calculation based on an S-GERG88 state equation; calculating a first calorific value by using the first nitrogen content and the initial calorific value, and performing iterative calculation according to the first calorific value to obtain a second nitrogen content until the absolute value of the difference between the second nitrogen content and the first nitrogen content is smaller than a preset value; determining the first calorific value corresponding to the obtained second nitrogen content as a target calorific value; through an iterative algorithm, the accuracy of a natural gas calorific value test result and a natural gas working condition compression factor calculation result through the laser absorption spectrometry can be greatly improved, and then the path reliability and applicability of natural gas energy metering through the laser absorption spectrometry are improved.