2009 results about "Standard curve" patented technology

The invention provides a method for determining hydrocarbon components in mixed aromatic hydrocarbons by using comprehensive two-dimensional gas chromatography-mass spectrometry. The method comprises the following steps: optimizing a target function to make a chromatographic peak signal obtained by a separation model accord with a chromatographic separation process mechanism, fully utilizing complementary information of chromatography and mass spectrometry, improving separation precision, and guiding analysis of complex aliasing peaks; analyzing overlapped chromatographic peaks determined by principal component analysis by adopting the established separation model to obtain a chromatographic peak signal representing a single component after separation, and matching the chromatographic peak signal with a corresponding mass spectrum; in combination with a single chromatographic peak signal and a mass spectrum obtained through separation, according to characteristic fragments and chromatographic retention time in the mass spectrum, component types corresponding to chromatographic peaks are judged, and characterization of the composition of the mixed aromatic hydrocarbon is achieved; a separated single chromatographic peak is subjected to quantitative analysis, the content of each component is calculated by adopting an external standard method in contrast with a standard curve, a quantitative result of the mixed aromatic hydrocarbon sample is obtained, and the measurement precision of the mass fraction of each hydrocarbon component is improved.

The invention provides an HCG and LH test paper identification method and system based on optical characteristics and a storage medium. The method comprises the following steps: firstly, collecting and generating a reflectivity curve of a test paper detection area and a quality control area; secondly, extracting a reflection characteristic value of a curve in a detection area for test paper validity verification, and entering a core identification stage if the test paper is qualified; preliminary judgment is carried out by calculating a similarity deviation value of a quality control area curve and an HCG / LH standard curve, when the deviation is significant, a preliminary recognition result is generated and enters a cross validation link, and a result is confirmed by comparing a reflection characteristic value with a dynamic threshold range; when the similarity deviation is not obvious or the cross validation is not passed, starting a pre-trained discrimination model to perform final arbitration; by constructing a quadruple judgment mechanism of validity verification, preliminary recognition, cross validation and model arbitration, the operation complexity and misjudgment risk of manual test paper type selection are overcome, and the automation degree of the detection process and the accuracy and reliability of the recognition result are improved.

The invention discloses a liquid chromatography-tandem mass spectrometry detection method and system, and the method comprises the steps: designing a multi-dimensional gradient elution program according to the physicochemical properties of a target compound, and obtaining a chromatographic separation spectrogram; performing efficient ionization on the target compound according to the chromatographic separation spectrogram to obtain an ionization signal; according to the ionization signal, fragmenting the target ions, and obtaining a fragment ion spectrogram through fragment ion screening; according to the fragment ion spectrogram, a multivariable data analysis algorithm based on machine learning is adopted, a standard curve of a target compound and an interferent database are combined, quantitative analysis is carried out, and a quantitative result is generated through a dynamic interference correction technology in combination with principal component analysis and a partial least square method. By utilizing the embodiment of the invention, the sensitivity, the accuracy and the real-time performance of detection can be improved through multi-dimensional gradient elution, dynamic ionization and fragmentation parameter optimization in combination with an analysis means of machine learning.

The invention relates to the field of test and detection of building materials, in particular to a method for detecting the residual equivalent weight of a flocculating agent in washed fine aggregate, which comprises the following steps: preparing standard samples containing flocculating agents with different concentrations, detecting to obtain a first standard fluidity and drawing a standard curve; a clear soaking solution obtained by fully soaking the washed fine aggregate replaces a flocculant solution to prepare a detection sample, first detection fluidity is obtained through detection, and the residual equivalent of the flocculant in the washed fine aggregate is obtained by combining the standard curve. According to the method, the influence of the difference of the sand on the fluidity is eliminated, the accurate residual equivalent of the flocculating agent is obtained, and the method has high universality.

The invention relates to the technical field of sewage traceability positioning, and discloses a sewage traceability positioning method and device for carbon nitrogen ratio imbalance. The method comprises the following steps: performing carbon-nitrogen ratio standard curve deviation calculation and data dimension reduction processing on carbon-nitrogen space-time attenuation data to obtain carbon-nitrogen imbalance feature vector data; performing pipe network connectivity calculation and transmission path analysis on the coordinate data of the multi-level sewage system to obtain migration trajectory data of carbon and nitrogen pollutants; performing multi-dimensional data fusion on the carbon-nitrogen imbalance feature vector data and the carbon-nitrogen pollutant migration trajectory data to obtain spatial distribution data of the carbon-nitrogen imbalance pipe section; and carrying out pollution contribution calculation and region boundary identification on the spatial distribution data to obtain position region data of a carbon-nitrogen ratio abnormal source. According to the method, correlation analysis of the carbon and nitrogen space-time attenuation characteristics and the pipe network connectivity is established, and data dimension reduction and space analysis technologies are combined, so that the problem region range can be quickly reduced, and a more accurate tracing positioning result can be provided.

The invention relates to a method for detecting pyridine in air, a test paper sheet is placed in an air environment to be detected, the color change of the test paper sheet is observed, the pyridine concentration is qualitatively judged or quantitatively judged according to the color change of the test paper sheet, and the test paper sheet is made of a filter paper sheet and a zinc-based organic-inorganic hybrid halide material. According to the method, qualitative or semi-quantitative judgment of the pyridine concentration in the air can be performed by adopting a test paper sheet and a color card or a linear correlation model standard curve graph, so that whether the pyridine content in the air exceeds the standard or not or the exceeding amplitude can be monitored, and the method has the advantages of convenience in operation and more convenience in detection.

The invention relates to the technical field of sewage treatment optimization, in particular to an intelligent sewage plant full-process management and control method based on digital twinning, which comprises the following steps: acquiring concentration data to calculate rate clustering fluctuation, setting a threshold value mark stable section to analyze sedimentation association, constructing dynamic threshold value output control information, and adjusting stirring to generate a sludge discharge instruction set. According to the method, through the time sequence clustering of the concentration change rate, the stable section in the sludge sedimentation process is identified, the concentration fluctuation identification precision is improved, the sedimentation hysteresis is judged based on the time difference between the sedimentation track and the standard curve, the particle layering identification capability is improved, and the dynamic threshold matrix is constructed by using the correlation degree and the particle size data; the concentration range, the settling velocity deviation and the particle size distribution dispersion are fused, the multidimensional property of a regulation and control basis is enhanced, the interface position movement trend is combined, the concentration range is matched, a stirring intervention instruction is output, real-time regulation and accurate control of the layered settling process are achieved, and the treatment stability and the reaction time efficiency are improved.

The invention relates to the technical field of total phosphorus detection, in particular to a method for determining total phosphorus in water, which comprises the following steps: 1) digestion treatment: adding an oxidant into a water sample to be detected, and then performing microwave digestion treatment to obtain digested water; a molybdate reagent is added into the digested water, then an improved ascorbic acid solution is added, a chromogenic reaction is completed at the set temperature, and the improved ascorbic acid solution is obtained by mixing an ascorbic acid solution and sodium ethylene diamine tetracetate; measuring the concentration: measuring the absorbance value of the obtained color development product by using a spectrophotometer and a long-optical-path cuvette; and drawing a standard curve: using a phosphorus standard solution as a quality control sample, adding a plurality of calibration points in a low-concentration interval of 0.0-0.1 mg / L, carrying out colorimetric determination, and establishing quadratic equation fitting according to absorbance and concentration so as to determine the total phosphorus content of the water sample to be detected, and the method has the advantages of high sensitivity and good accuracy in total phosphorus testing.

The invention discloses a non-derivatization quantitative detection method for amino acid in a high-concentration protein preparation, which comprises the following steps: separating by using a graphitized carbon chromatographic column, adding an ion pair reagent trifluoroacetic acid into a mobile phase, and detecting by using an electric fog detector (CAD); the method comprises the following steps: preparing a plurality of groups of amino acid standard substance solutions with different concentration groups, wherein the concentration range is 1mmol / L-20mmol / L; drawing a quadratic equation standard curve of the amino acid standard product concentration and the peak area as a detection equation for detecting the amino acid concentration; the method comprises the following steps: diluting a test sample by using ultrapure water for multiple times, carrying out ultrafiltration centrifugal treatment, removing protein, introducing the sample, obtaining a corresponding peak area according to the spectrum integral of the test sample, and substituting the peak area into the detection equation to obtain the concentration of amino acid in the test sample. The method has the advantages of high detection precision, high detection efficiency and simple operation, and greatly reduces the adverse effect of high-concentration protein on the chromatographic column.

The invention discloses a hyperspectral satellite target rock and mineral identification method and system based on spectral characteristic parameters. The method comprises the following steps: S1, collecting and preprocessing a standard rock and mineral reflection spectrum curve; s2, collecting a regional hyperspectral satellite image and carrying out image preprocessing; s3, identifying diagnostic spectral reflection and absorption characteristics of the target rock mine based on the standard curve; s4, screening and extracting a diagnostic spectral range of the hyperspectral satellite image; s5, calculating diagnostic spectral characteristic parameters of the hyperspectral image target rock mine; and S6, on the basis of the S5, processing the spectral characteristic parameters obtained by calculation, and realizing target rock and mine identification based on multi-dimensional diagnosis spectral characteristics. According to the method, the application potential of the hyperspectral satellite image in the field of remote sensing geology is effectively improved and the scientificity and the accuracy of the hyperspectral satellite image in large-range rock and ore recognition drawing application are improved through the target rock and ore standard spectral curve characteristic analysis, hyperspectral satellite image processing and spectral characteristic parameter estimation methods.

The invention discloses a model method for predicting cheese preference degree based on GC-MS combined with machine learning, and belongs to the technical field of cheese evaluation. The method comprises the following steps: firstly, determining the cheese preference of Chinese consumers by adopting a method for checking all suitable items, determining the nature of volatile flavor compounds by combining headspace-arrow type solid-phase microextraction and gas chromatography-mass spectrometry, and quantifying by adopting an internal standard curve method. Secondly, the correlation between the sensory attributes and the compounds is established through quantitative description analysis and Pearson correlation coefficients, and the characteristic flavor compound of each sensory attribute is obtained; and finally, establishing a cheese consumer preference degree identification method by using a machine learning algorithm, and predicting the Chinese consumer preference degree of unknown cheese by using the model. According to the method, the cheese preference degree of Chinese consumers can be accurately recognized only by means of data obtained through instrument analysis and the classification model, a set of more objective and rapid cheese consumer preference degree prediction method is established, and more accurate prediction is achieved along with the increase of sample libraries.

The invention discloses a sample concentration detection method, a standard curve group establishment method, a matrix specificity standard curve optimization method, a standard curve group establishment device and an immunity analyzer, and belongs to the field of diagnostic analysis. Acquiring matrix information of a to-be-detected sample; selecting a matrix specificity standard curve corresponding to the matrix of the sample to be detected; and detecting the sample and calculating the concentration of the analyte in the sample to be detected by using a matrix specificity standard curve selected from a plurality of standard curve groups of which the specificity corresponds to different matrixes. The corresponding substrate specificity standard curves are configured for various types of substrates in advance, and when a detection task is carried out, the corresponding substrate specificity standard curves can be selected and called, so that the detection is more targeted, the substrate effect caused by using a general standard curve can be avoided, the substrate effect can be reduced, the implementation operation is simpler, and the detection efficiency is improved. And the working time of detection personnel can be remarkably saved, and the detection cost is effectively reduced.

The invention discloses a method for measuring calcium and magnesium in an environmental water body by using a smart phone graphic colorimetric method, which belongs to the technical field of environmental monitoring and comprises the following steps: measuring a calcium and magnesium total amount standard curve, measuring a magnesium content standard curve and measuring the total amount of calcium and magnesium in an actual water sample. On the basis of a smart phone colorimetric method, water collection sampling, mixed reaction and photographing measurement are performed, and the test time of one sample can be controlled to be 10 min. The method is rapid, accurate and high in sensitivity, can be used for real-time field in-situ determination, and meets the requirements of rapid in-situ quantitative analysis and determination of an environmental water sample.

The invention provides an aviation nacelle part waviness automatic detection and evaluation method, and belongs to the field of product production detection, and the method comprises the steps: carrying out the protocol scanning of part surface contour features, and obtaining the undistorted coordinate point discrete point cloud data of the actual surface contour; filtering the point cloud data; obtaining a piece of flattened deviation value discrete point cloud data; obtaining a flattened deviation value continuous curve by adopting a general standard curve reduction method; extracting waviness components, and obtaining a curve center line; obtaining a crest value and a trough value participating in calculation; and calculating the maximum wave amplitude, the waviness and the slope for evaluating the waviness by using the wave peak value and the wave trough value. According to the method, the relation between the minimum cut-off wavelength of the waviness and the sampling interval is stipulated, the undistorted reduction of the surface profile curve is ensured, the influence of non-waviness profile components in the digital evaluation of the waviness is eliminated through a combined calculation method, and the evaluation accuracy of the waviness of the aviation nacelle part is improved.

The invention belongs to the technical field of analysis and detection, and discloses a method for detecting perfluorinated and polyfluoroalkyl substances in cosmetics, which comprises the following steps: (1) mixing a perfluorinated and polyfluoroalkyl substance standard solution and an isotope internal standard solution to obtain a mixed standard solution; detecting the mixed standard solution by adopting a liquid chromatograph-mass spectrometer, drawing a standard curve, and calculating to obtain a linear equation; (2) mixing a cosmetic sample with the isotope internal standard solution, adding an extracting solution, extracting, and filtering to obtain a mixed solution to be detected; detecting the mixed to-be-detected solution by adopting the liquid chromatograph-mass spectrometer to obtain a detection result, and substituting the detection result into the linear equation to obtain the content of the perfluoro and polyfluoroalkyl substances in the mixed to-be-detected solution, the perfluoro and polyfluoroalkyl substances comprise perfluorocarboxylic acid, perfluorosulfonic acid, a fluorine polymer, perfluoroalkyl ether sulfonic acid, saturated fluorine telomere acid and perfluoroether carboxylic acid.

The invention relates to the technical field of new material detection, in particular to a copper foil coating content detection method. The method comprises the following steps: preparing a plurality of mixed standard solutions; the mixed standard solution comprises copper ions and at least one to-be-detected element ion; in the plurality of mixed standard solutions, the copper ion concentrations are the same and are first preset concentration values; measuring a plurality of mixed standard solutions, and establishing a standard curve between a theoretical value and a measured value of the ion concentration of each to-be-measured element; dissolving a plating layer on the surface of the to-be-detected copper foil by using nitric acid, and filtering to obtain a to-be-detected sample solution; adding copper salt into the to-be-detected sample solution to obtain a to-be-detected analysis solution; measuring the to-be-measured analysis solution to obtain the measurement concentration of each to-be-measured element ion; according to the measured concentration of each to-be-measured element ion and the corresponding standard curve, the corrected content of each to-be-measured element ion is obtained. The problem that an existing copper foil coating content detection method is low in detection accuracy is solved.

A triple droplet type digital PCR (ddPCR) detection method for the severe fever with thrombocytopenia syndrome virus (SFTSV), spotted heat group rickettsia (SFGR) and tsutsugamushi Ot is established. According to the method, specific primers and probes are designed based on an SFTSV L gene, an SFGR 17Kd gene and an Ot 47Kd htrA gene, the reaction temperature and the concentration of the primers and probes are optimized to establish an SFTSV, SFGR and Ot triple ddPCR reaction system, and the specificity, sensitivity and repeatability of the triple ddPCR reaction system are analyzed. According to results, the optimal primer concentration and probe concentration of triple digital PCR are 600nmol / L and 250nmol / L respectively, and the optimal annealing temperature is 60 DEG C; the correlation coefficients of the triple ddPCR SFTSV, the triple ddPCR SFGR and the triple ddPCR Ot standard curve are 0.98, 0.99 and 0.98 respectively, and the lowest detection lower limits are 0.59 copies / mu L, 0.46 copies / mu L and 0.36 copies / mu L respectively. According to the invention, the SFTSV, SFGR and Ot triple digital PCR detection method is established, the sensitivity is high, the specificity is strong, and quantitative detection of three pathogens in SFTS suspected cases can be realized.

The invention discloses an all-solid-state calibration-free ion concentration detection method. The method comprises the following steps: constructing a plurality of traditional three-electrode detection systems; in each traditional three-electrode detection system, current and impedance signals are synchronously acquired through a step potential electrochemical spectrum and an electrochemical impedance spectrum, and interface kinetic parameters are analyzed; on the basis of a traditional three-electrode detection system, an original reference electrode is removed, a counter electrode is reserved, all glassy carbon electrodes with gradient membrane volumes are connected in series one by one to obtain a new three-electrode detection system, the new three-electrode detection system is immersed in a to-be-detected solution, a preset potential is applied, and through transient current response in combination with calibrated kinetic parameters, the gradient membrane volumes of the glassy carbon electrodes are detected. And performing inversion to obtain the ion concentration of the to-be-detected solution. According to the method, automatic calibration is realized by analyzing interface process kinetic parameters of different-volume film ion selective electrodes and calculating the slope to generate a built-in standard curve. According to the method, interface process parameters are obtained through transient current, and dependence of a traditional detection system on the stable potential of a reference electrode is eliminated.

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 relates to a method for detecting activity of gamma-polyglutamic acid hydrolase and application. The method comprises the following steps: (1) preparing an enzymolysis reaction solution and a blank reaction solution; (2) preparing an NAC / OPA mixed solution; (3) adding an NAC / OPA mixed solution into the enzymatic hydrolysis reaction solution to obtain a reaction solution to be detected; (4) drawing a standard curve by taking L-glutamic acid as a standard substance; and (5) detecting the fluorescence intensity of the blank reaction solution and the reaction solution to be detected by using a microplate reader, and then calculating the activity of the gamma-polyglutamic acid hydrolase according to the fluorescence intensity and the standard curve. The method for detecting the activity of the gamma-polyglutamic acid hydrolase is high in detection speed, detection of a single sample can be completed within 25 min, and nearly real-time process monitoring is achieved. And the method has the advantages of reliable detection result and high accuracy, can be used for monitoring the enzyme activity of the gamma-polyglutamic acid hydrolase in the gamma-polyglutamic acid preparation process in real time and guiding the optimization of the fermentation process, and has extremely high industrial application value.

The invention provides a primer group for qualitative and quantitative detection of three types of fish toxicity karenia, a detection method and application, and belongs to the technical field of marine aquaculture guarantee. The primers as shown in SEQ ID NO.1-6 provided by the invention can be used for respectively identifying the species of the Karenia saddle, the Karenia longgroove and the Karenia butterfly; a plasmid standard curve and a cell standard curve are established in combination with an SYBR Green I fluorescent quantitative PCR technology, and specific identification and quantity determination of the three types of fish-toxic karenia are further realized. The method has the advantages of high specificity, high sensitivity, simplicity in operation, short time consumption and the like, can overcome the limitation of traditional morphological identification, can realize rapid and accurate qualitative identification and quantitative detection of a large number of samples, is time-saving and labor-saving, is relatively low in price, and can become an effective technical means for prediction, early warning and large-area monitoring of the Karenia red tide.

The invention relates to the technical field of water quality detection, and discloses a water quality monitoring method and system based on a full spectrum, light absorption value II detection at different heights is carried out on each index of water quality in a water body through the full spectrum, normalization processing is carried out on the light absorption value II and a light absorption value I in pure water to obtain an absorbance uniformity value # imgabs0 #, and the absorbance uniformity value # imgabs0 # is calculated. Correlating and weighting the light absorption value II # imgabs1 # and the absorbance uniform value # imgabs2 # at any height, establishing a multiple linear regression model, estimating a regression coefficient # imgabs3 # through a least square method, obtaining a predicted value # imgabs4 #, substituting the predicted value # imgabs4 # into a standard curve regression equation of each index, obtaining a final concentration value of each index, reducing the difference of the light absorption values at different heights during detection, and determining the concentration value of each index. The on-site water quality detection accuracy is improved.

The invention relates to the technical field of electric power marketing, in particular to an electric power marketing business online auditing all-in-one machine digital inspection system, which comprises a data acquisition and classification module, a curve modeling and feature extraction module, a dynamic threshold generation module, a database management module and an anomaly detection and alarm module. According to the method, curve modeling is carried out by combining historical normal data, standardization processing is carried out through multiple curve modeling, a new standard curve is established, the curvature between points on the curve is used as a reference voucher, a threshold range is established, and the power consumption curve is automatically produced by monitoring existing power consumption data. And the calculated curvature is compared with a threshold value, so that electricity consumption abnormity can be judged, and inspection is facilitated.

The invention discloses a digital children growth and development predictive guidance method, particularly relates to the field of children growth and development evaluation, solves the problems of individual growth trajectory matching and specificity recognition, and comprises the following steps: segmenting a normal growth curve into local reference windows and constructing a long-term standard curve; generating a target growth curve in combination with a dynamic time warping method, and capturing the growth characteristic difference between short-term fluctuation and global trend of a target individual; by extracting a relative curvature unbalance factor and a cross-section extension entropy difference value, dynamic deviation of a target growth curve in local and global ranges is quantitatively described; performing time domain division dynamic evaluation by using a short-term mutation deviation index and a long-term gradual deviation index, generating an explanation credibility coefficient of a normal target growth trajectory, dividing individual growth characteristic grades, and determining an explanation capability range of a normal growth curve to the target trajectory, thereby being beneficial to distinguishing the matching degree of a target and a normal growth mode, and improving the target growth accuracy. And the growth specificity is recognized.

The invention relates to the technical field of optical property testing, in particular to a method for measuring and analyzing imaging illumination distribution, which comprises the following steps of: shooting uniform diffuse reflection white screens one by one by using an imaging tester, controlling exposure parameters and focal length to ensure that images are clear, gradually adjusting a shooting angle to cover the whole imaging area, collecting imaging data of each angle to generate a multi-angle imaging data set; comparing the image gray value in the multi-angle imaging data set with a preset gray reflectivity curve, adjusting the gray value matching standard curve pixel by pixel, and calculating the reflectivity for each pixel to obtain a pixel reflectivity matrix. According to the method, the accuracy of illumination effect evaluation is improved, the adaptability and the real-time adjustment capability of a complex illumination system are enhanced, and the practicability and the economical efficiency of illumination design are promoted.

The invention discloses a method and equipment for rapidly detecting the content of progesterone in cow and sheep milk, and the method comprises the following steps: respectively collecting an optical signal, an electrochemical signal and current and voltage data of a sample in the cow and sheep milk through an optical detection module, an electrochemical detection module and a current and voltage detection module; the physical and chemical characteristics of the sample in the cow and sheep milk can be comprehensively analyzed from multiple dimensions. The detection data can be quickly and accurately processed and transmitted by combining a signal processing system and equipment, a reliable guarantee is provided for subsequent analysis, and in addition, a progesterone mathematical model embedded into the signal processing system realizes high-precision calculation of the concentration of progesterone in milk of cattle and sheep by combining a detection signal and a standard curve. The model not only improves the accuracy of a detection result, but also remarkably shortens the analysis time, and practically meets the urgent requirements for rapid detection and efficient output in practical application.

The invention relates to the field of detection methods, and particularly discloses a method for determining the silicon content in silicon steel through inductively coupled plasma emission spectrometry. The determination method comprises the following steps: preparing a to-be-tested solution: weighing 0.10-0.20 g of a silicon steel sample, adding 10-15mL of nitric acid (1 + 2), heating and dissolving at a low temperature, boiling for 10-60s, cooling to room temperature, keeping the temperature of the solution to be less than or equal to 80 DEG C, dropwise adding 3-5mL of hydrofluoric acid, and fixing the volume to obtain the to-be-tested solution; 0.095-0.19 g of metal iron is weighed and put into a polytetrafluoroethylene beaker, and the metal iron is dissolved according to the sample dissolving method in the prepared to-be-tested solution to obtain the Fe reference solution; making a standard curve: mixing the Si reference solution and the Fe reference solution with different volumes to prepare a standard solution in an analysis gradient range, and detecting and drawing the standard curve; and detecting the to-be-detected sample, and combining the standard curve to obtain the silicon content in the silicon steel sample. The method has the advantages of high accuracy, simplicity, convenience, rapidness and short detection period.

The invention discloses a steady-state boundary convection-dispersion model parameter acquisition method based on a variable separation method, and the method comprises the steps: constructing a convection-dispersion mathematical model under a one-dimensional finite-scale steady-state boundary condition, and carrying out the dimensionless processing of an original mathematical model through a dimensionless factor; secondly, analyzing and solving the new mathematical model after nondimensionalization by adopting a separation variable method, systematically deriving an analytical solution expression of a one-dimensional steady-state boundary convection-dispersion model in combination with a groundwater dynamic theory and a solute transport mechanism, and constructing a standard curve capable of reflecting different permeability parameters and solute transport related parameters; an indoor one-dimensional convection-dispersion test is carried out, water level and solute concentration measured data at different observation points are obtained, and permeability parameters and solute transport related parameters of a test medium are efficiently obtained through wiring. According to the method, the accuracy and adaptability of the convection-dispersion model in the aspect of parameter identification under the limited scale condition are enhanced; and operation is simple, parameter identification quantity is large, and precision is high.

The invention discloses a cast-in-place pile integrity detection method based on a heat conduction model, and relates to the technical field of cast-in-place pile detection. The method comprises the following steps: firstly, constructing a cast-in-place pile heat conduction characteristic template library comprising standard heat conduction curves corresponding to various integrity states, wherein each standard curve comprises a plurality of key temperature nodes; generating a comprehensive heat conduction curve by fusing the standard curves of the same type of integrity states; acquiring actual temperature monitoring data of the to-be-detected cast-in-place pile, selecting a corresponding comprehensive heat conduction curve, and extracting a reference heat conduction curve; marking abnormal conduction nodes in the reference conduction curve to obtain a corrected conduction curve; and establishing a heat conduction anomaly analysis model to verify and correct key temperature nodes of the conduction curve, determining defect nodes, generating an integrity report containing position information of the defect nodes, and completing detection. Various quality conditions of the cast-in-place pile can be covered, advantages and characteristics of curves are integrated, and detection errors and unnecessary links are reduced.

The invention discloses a method for quantitatively detecting viable bacteria of lactobacillus reuteri, lactobacillus rhamnosus, lactobacillus paracasei and lactobacillus acidophilus. The novel molecular detection target disclosed by the invention has high specificity on target bacteria. The disclosed PMA-qPCR method comprises the steps of target detection, qPCR primer and probe design, qPCR detection system, PMA treatment condition and viable bacteria quantitative standard curve. After qPCR amplification, if a Cq value appears, the dissolution peak is single and the dissolution temperature is consistent with that of a positive sample (only aiming at a dye method), the lactic acid bacteria are identified as target lactic acid bacteria, and the number of viable bacteria can be calculated according to a corresponding standard curve. The method can effectively detect and count viable bacteria of Lactobacillus reuteri, Lactobacillus rhamnosus, Lactobacillus paracasei and Lactobacillus acidophilus, has the advantages of rapidness, accuracy, simple operation and the like, and is convenient for food enterprises and inspection institutions to use.