321 results about "Fluorescence spectrometer" patented technology

The invention discloses a TSFS sample generation method based on an improved generative adversarial network. The TSFS sample generation method comprises the following steps: step 1, acquiring TSFS data of a sample by using a three-dimensional fluorescence spectrometer; step 2, constructing a CA-WGAN-GP optimization model with a convolution attention mechanism, and performing data enhancement on an original TSFS sample; step 3, in a model training stage, storing generated data once after epoch training for a certain number of times, and enabling a generated sample coverage to have higher diversity by utilizing generator models of a plurality of training stages; 4, extracting enhanced sample features by using a pre-trained CNN model, projecting the sample features by using linear discriminant analysis LDA, and preliminarily screening samples according to a Mahalanobis distance and a set threshold value; and 5, performing secondary screening by using a K-means algorithm to obtain a final training sample set. According to the method, the time-consuming and labor-consuming problem of TSFS sample acquisition is effectively solved, the model over-fitting phenomenon is reduced, and the robustness of unknown data is improved.

The invention provides an intelligent sorting method and system for radioactive substances. The method comprises the following steps: synchronously detecting surface element composition and radiation intensity of a radioactive substance through an X-ray fluorescence spectrometer, and constructing a spatial difference matrix of element abundance distribution and a radiation gradient topological graph; the three-dimensional coordinates, the pressure threshold value and the shape adaptation parameters of the target grabbing position are determined on the basis, the curvature radius of the clamping jaw deformation contour is dynamically adjusted, and the error of the dynamic geometric envelope and the contour template is converged to be within the threshold value; finally, when the clamping jaw reaches a target position, the area of the heat shrinkage material is activated to be heated according to the radiation intensity abrupt change boundary coordinates, a sealed isolation layer synchronously expanded with the dynamic geometric envelope is generated, and safe grabbing and sealed isolation of radioactive substances are achieved. According to the technical scheme, accurate grabbing of radioactive substances, error self-adaptive compensation and synchronous isolation of radiation leakage can be achieved, and the sorting safety and efficiency are improved.

The invention belongs to the technical field of pesticide residue detection, and particularly relates to a DebNet intelligent classification algorithm based on fluorescence method pesticide residue detection, which comprises the following steps: detecting a pesticide sample by using a fluorescence spectrometer to obtain one-dimensional spectral data of the pesticide sample; preprocessing the spectral data; performing data enhancement on the preprocessed spectral data, wherein an enhancement mode comprises linear interpolation, noise injection, spectrum translation and spectrum cutting; building a hybrid neural network model comprising an input layer, a convolutional layer, a pooling layer, an LSTM layer, a self-attention module, a full connection layer and an output layer, namely a DebNet model; training a DebNet model based on the enhanced spectral data, wherein the training process comprises forward propagation and back propagation; and utilizing the trained DebNet model to classify and identify the spectral data of a to-be-detected sample. The method can improve the classification accuracy, reduce the sample requirements, simplify the data processing flow, and reduce the detection cost.

The invention relates to the technical field of municipal engineering, and provides a sewage pipeline low-pollution water inflow and infiltration diagnosis method based on a fluorescence spectrum image, and the method comprises the steps: collecting different types of sewage and different types of low-pollution water in a sewage pipeline troubleshooting region, and according to the mixing condition of the sewage and the low-pollution water in the sewage pipeline troubleshooting region, determining whether the sewage and the low-pollution water are mixed or not; the collected different types of sewage and different types of low-pollution water are mixed according to different proportions, a three-dimensional fluorescence spectrophotometer is used for detecting a mixed water sample, a fluorescence spectrum image corresponding to the mixed water sample is obtained, and according to the fluorescence spectrum image corresponding to the mixed water sample, the sewage type and proportion and the low-pollution water type and proportion, the low-pollution water is detected. And training the water sample type diagnosis model and the water sample type proportion diagnosis model, and performing low-pollution water inflow and infiltration diagnosis on the sewage pipeline to be diagnosed based on the models. In this way, low-pollution water inflow and infiltration diagnosis can be achieved when multiple types of sewage coexist in a sewage pipeline.

The invention relates to the technical field of mineral processing data processing, in particular to a preparation method of a high-calcium fluorite and barite paragenic ore combined inhibitor, which comprises the following steps: collecting multi-source process mineralogy data output by an X-ray fluorescence spectrometer, an automatic mineral analyzer and the like, converting the multi-source process mineralogy data into a structured format, and constructing a process mineralogy database; based on historical data of a database, a random forest algorithm is adopted to train a correlation model, the correlation rule of mineral characteristics such as calcite content, fluorite particle size distribution and barite monomer dissociation degree and the inhibitor ratio is learned, and parameters of the optimization model are fed back through a flotation test. The combined inhibitor solves the problem of selective separation caused by similar surface properties through a synergistic effect of covering active sites of fluorite calcium by modified water glass, regulating active sites of barite barium by citric acid and assisting in enhancing inhibition by modified starch, and solves the problem of low efficiency of multi-source data integration through structured data processing and model closed-loop optimization; the flotation separation efficiency and the concentrate grade are improved.

The invention relates to the technical field of grading gangue selection of coal gangue, in particular to a grading gangue selection method of coal gangue, which comprises the following steps: acquiring mineral texture data through a multispectral imaging device, analyzing the spatial distribution of aluminum and silicon elements in combination with an X-ray diffractometer, and generating a three-dimensional component map through spatial registration and fusion with infrared heat value data; impurities are dynamically removed through sulfur element spectrum detection, and the air pressure and the material flow of winnowing equipment are adjusted by matching roasting process parameters; components of the sorted waste are analyzed through an X-ray fluorescence spectrometer, particle size data are obtained through a laser particle analyzer, a genetic algorithm is input to iteratively optimize detection channel combination and sampling density, a resource distribution instruction is generated, and equipment parameter correction is fed back. According to the method, aluminum-silicon ratio critical value accurate identification, sorting parameter dynamic adaptation and waste recycling path optimization are realized, and the problem of overburning caused by insufficient quantitative analysis of element distribution in the prior art is solved.

The invention discloses an intelligent carbon anode quality detection system, particularly relates to the field of electrolytic aluminum, and comprises a data acquisition module, a data preprocessing module, a data analysis module and a comprehensive judgment module. According to the method, a full-process data acquisition system covering raw materials, forming, roasting and appearance is constructed, accurate acquisition of multi-source data is realized by using equipment such as an X-ray fluorescence spectrometer and a hydraulic sensor, the problem of dispersion of traditional detection data is solved, and the detection accuracy of the multi-source data is improved through multi-stage pretreatment methods such as outlier elimination, sliding window filtering, temperature compensation and wavelet noise reduction. Dimension difference and sensor noise interference are effectively eliminated, and data reliability is improved. A multi-level evaluation model composed of a raw material comprehensive index, forming energy density, roasting maturity and appearance integrity is innovatively established, and intelligent comprehensive evaluation and accurate grading management and control of the carbon anode quality are achieved in combination with a dynamic weighting comprehensive quality index formula and a four-level grading mechanism.

The invention discloses magnetron sputtering coating equipment integrated with an X fluorescence spectrometer and a working method of the magnetron sputtering coating equipment, and relates to the technical field of thin film deposition. The magnetron sputtering coating equipment comprises a sample injection cavity, a sample placing cavity, an isolating valve and a process cavity which are sequentially distributed in the linear direction; a transmission manipulator is mounted in the sample injection cavity and is used for driving a wafer to be transmitted and moved in the lofting cavity and the process cavity; an X fluorescence spectrophotometer for dynamically detecting the thickness of a wafer film is mounted on the sample injection cavity; the lofting cavity is matched with the transmission manipulator and is used for storing wafers; a liftable sample table, an angle-adjustable cathode target head and a flexible mechanical structure are arranged, the difference between the thickness data and the target thickness is judged at the first time of obtaining the thickness data of the spectrograph, so that the angle of the cathode target head is automatically adjusted, and the target thickness is corrected; the whole equipment is high in automation degree, and the working efficiency is improved.

The invention relates to the technical field of monitoring and tracing of sewage, in particular to an online sewage monitoring method based on a three-dimensional fluorescence spectrum. The method comprises the following steps: step 1, sampling sewage in the whole area; 2, measuring COD, ammonia nitrogen and TOC values of the sewage sample; 3, scanning the sewage sample by adopting a three-dimensional fluorescence spectrometer to obtain three-dimensional fluorescence spectrum data; 4, analyzing the obtained three-dimensional fluorescence spectrum data by adopting a parallel factor analysis method to obtain fluorescence components of the sewage sample; 5, establishing a fluorescence database; and 6, establishing a sewage identification model. According to the invention, rapid source tracing of the sewage is realized, and the sewage incoming condition can be rapidly monitored.

The invention relates to the technical field of photoelectric detection, and discloses a wavelength dispersion X-ray fluorescence spectrometer detector bias correction method, which comprises the following steps: preparing a bias correction sample containing various elements; loading the bias correction sample into a wavelength dispersion X-ray fluorescence spectrophotometer, adjusting excitation conditions of each element to obtain preset signal intensity, adjusting detector bias to enable spectral peaks of each element to be located at a specific channel position, recording detector bias corresponding to characteristic line wavelengths of each element, and determining the spectral peaks of each element according to the detector bias. Establishing a numerical relationship between the detector bias voltage and the element characteristic line wavelength; and automatically matching and setting a corresponding detector bias voltage according to the characteristic line wavelength of the to-be-detected element in the to-be-detected sample and the established numerical relationship. The method is simple and easy to operate, the detector bias value corresponding to the wavelength of the to-be-detected element can be rapidly and accurately determined through self-made powder tabletting, the operation process is simplified, the element coverage range is expanded, and the calibration precision is improved.

The invention discloses a multi-element information acquisition and analysis system based on telemetering drifting buoys, and relates to the technical field of marine environment monitoring. A three-dimensional fluorescence spectrometer, a temperature-salinity-depth sensor, a positioning module and a miniature water sampler are carried on each telemetering drifting buoy; the system is used for collecting algae fluorescence spectrums, water quality parameters and position data in real time, inputting the data into a trained random forest model to output the red tide occurrence probability, triggering multi-level early warning in combination with a preset expert rule engine, linking air and shore-based equipment and a data storage system, and utilizing laboratory true value data obtained by a miniature water sampler to determine the red tide occurrence probability. And performing incremental training on the random forest model every day, thereby dynamically optimizing internal structure parameters of the model. The method effectively improves the prediction probability of the red tide.

The invention discloses a multifunctional micro-spectrum test system with adjustable test temperature and pressure, and belongs to the technical field of spectrum detection. Functions of an absorption spectrograph, a fluorescence spectrograph, a Raman spectrograph and a photoluminescence excitation spectrograph are integrated into one set of equipment, so that samples are not required to be transferred for multiple times at the same position, only the positions of part of parts in a test system need to be finely adjusted, and related test parameters are set; the Raman spectrum, the reflection / absorption spectrum, the fluorescence spectrum and the photoluminescence excitation spectrum of the sample can be obtained. Furthermore, through a test environment control subsystem, the temperature and the pressure of the test environment can be continuously and accurately adjusted, and the gas atmosphere can be changed according to requirements, so that not only can the sample be protected from denaturation in the test process, but also different samples can be ensured to be tested in the same test environment, and the test efficiency is improved. And the surface of the sample is not frozen in the low-temperature testing process, so that the testing result is more accurate and reliable.

The invention relates to the technical field of heavy metal detection, in particular to a method for detecting heavy metal in water by combining membrane evaporation drying and a monochromatic aggregation X-ray fluorescence spectrophotometer, which comprises the following steps: (1) taking a certain volume of water sample, and adding an internal standard; (2) placing a polyamide membrane at the pretreatment position, and carrying out evaporation drying treatment, so that heavy metal elements in the water sample are enriched on the polyamide membrane in the form of solid residues; (3) taking out the polyamide membrane, performing X-ray radiation on solid residues on the polyamide membrane, and collecting fluorescence signals of heavy metal elements; and (4) carrying out qualitative and quantitative analysis on the heavy metals in the water sample by combining an internal standard algorithm with a fluorescence signal. According to the method disclosed by the invention, the heavy metals in the water are detected by combining membrane evaporation drying and a monochromatic gathering X-ray fluorescence spectrometer, and the 0.1 ppb-level analysis level of the heavy metals in the water sample can be realized by combining a membrane enrichment method.

The invention relates to the technical field of handheld spectrometers, in particular to a portable handheld X fluorescence spectrometer. Comprising a handle, the handle is fixedly connected with a shell, the shell is provided with a detection part and a display screen, the detection part is used for detecting a detected object, a sliding groove is formed in the side, away from the shell, of the handle, a sliding block is slidably connected into the sliding groove of the handle, and an anti-falling rope is wound around the sliding block. A first tension spring is fixedly connected between the sliding block and the handle, and a protection assembly is arranged on the shell and used for reducing damage to the detection part when the shell slides down. In the process that the spectrograph is shaken, the sliding block is driven by the anti-falling rope to slide, the sliding block pulls the first tension spring, and the hard tension between the anti-falling rope and the sliding block is changed, so that the probability that the joint between the anti-falling rope and the sliding block is broken is reduced, and the probability that the detection part is damaged is reduced.

The invention provides a cultural relic age determination method and system, and relates to the technical field of cultural relic age determination, the method comprises the following steps: collecting a sample from a to-be-tested cultural relic, and cleaning, drying and crushing the sample to obtain a treated sample; performing elemental composition analysis on the sample through an energy dispersion X-ray fluorescence spectrophotometer to obtain the types and content ratios of main elements and trace elements in the sample; collecting similar cultural relic samples of known years, performing elemental composition analysis, and establishing a standard sample ratio of the known years; comparing the ratio of the types and contents of the main elements and the trace elements in the sample with the ratio of a standard sample of a known age, and fitting a calibration curve through a least square method according to a comparison data set; and optimizing the calibration curve, and calculating an absolute age estimation value of the cultural relic according to the optimized calibration curve. According to the method, interference of single element variation is reduced through multi-element correlation analysis, and historical relic age determination is carried out.

The invention relates to the technical field of geological exploration, in particular to an X-ray fluorescence spectrometer and geological radar combined gold vein rapid positioning method, which comprises the following steps: S1, arranging an exploration survey line in a pre-selected exploration area; s2, along the same measuring line, measuring the content of the gold mineralization indication element in the earth surface or the shallow medium by using an X-ray fluorescence spectrometer, synchronously recording the position information of a measuring point, and generating element content spatial distribution data; the gold mineralization indicating element comprises at least one of arsenic As, antimony Sb and mercury Hg; s3, carrying out detection by using a geological radar along the same measuring line, obtaining a reflected wave signal of an underground medium, synchronously recording position information of a detection point, identifying fault zone and joint zone geological structure anomalous bodies through data processing, and generating geological radar space distribution data; through XRF and GPR data fusion, a CAI quantitative model is established to precisely delineate an ore prospecting target area, a hidden ore body is effectively identified, the exploration precision and efficiency are greatly improved, and the exploration cost is reduced.

The invention relates to an on-line steel component automatic analysis method based on an X-ray fluorescence spectrometer, and the method comprises the following steps: M1, carrying out on-line detection on steel, obtaining data information of the temperature of the steel in real time based on an infrared thermometer, and obtaining data information of element analysis of the steel in real time based on the X-ray fluorescence spectrometer; the data information of the measurement position of the X-ray fluorescence spectrophotometer is obtained in real time based on a laser sensor, the content of each element in the steel is predicted through an improved whale optimization lightweight gradient elevator classification prediction algorithm, and the predicted data information of the content of each element in the steel is obtained. According to the invention, component analysis operation is automatically and standardly carried out, the use is simple and convenient, online component automatic detection of steel is realized, the working efficiency is improved, the labor cost is reduced, and the operation safety is improved.

Provided is an X-ray fluorescence spectrometer that achieves a uniform state on a back side of a thin sheet-shaped sample so as to prevent a difference in a measurement condition depending on a measurement position. The X-ray fluorescence spectrometer includes: a sample stage; a background correction cover, which is arranged adjacent to an outer side of the sample stage so that a surface of the background correction cover is substantially flush with a surface of the sample stage; and a moving mechanism. The moving mechanism moves the background correction cover based on movement of the sample stage and, when the sample stage is absent on a back side of the sample at a measurement position, moves the background correction cover so that the background correction cover is located on the back side of the sample at the measurement position.

The present invention relates to the technical field of the preparation of Cr3+-doped fluorescent materials. Disclosed are the preparation of a Cr3+-doped fluorescent material and the use thereof in a plant light supplement lamp. The preparation comprises the following steps: weighing a matrix raw material and a Cr3+-containing raw material according to the stoichiometric ratio, and respectively grinding and then storing same in a dryer; placing the raw materials into a ball milling tank, and subjecting same to planetary ball milling for 3-6 hours; transferring same to an alumina crucible, and pre-sintering same for 2-5 hours; after secondary ball milling, adding a fluxing agent thereto; placing same in a high-temperature furnace and sintering same for 6-10 hours, and furnace cooling same or cooling same under the protection of an inert gas; and firstly coarsely crushing same, then grinding same to 10-30 μm, alternately cleaning same with deionized water and ethanol, drying same in an air dry oven, detecting and screening the product by using a fluorescence spectrophotometer, an X-ray diffractometer and a scanning electron microscope, and remanufacturing unqualified products after adjusting process parameters according to detection results. The present invention has a high light-emitting efficiency, and the spectrum thereof is suitable for plant photosynthetic absorption. When being applied to a light-supplementing lamp, plant growth can be promoted, the plant height and the chlorophyll content are significantly increased, and the natural spectrum is simulated, such that the material is suitable for multiple cultivation scenarios.

The invention relates to the field of ecological environment, in particular to a method for characterizing the influence of PPCPs on the toxicity of an activated sludge system by using a viable and dead bacteria staining method, which comprises the following steps of: improving an SYTO 9 dye and PI dye cell staining method, namely quantitatively detecting the fluorescence intensity corresponding to dead bacteria and viable bacteria by using a three-dimensional fluorescence spectrophotometer; a quantitative detection technology of flora activity is established, and a set of method capable of rapidly and accurately quantifying the ratio of dead bacteria to viable bacteria in a sample is constructed; according to the invention, degradation conditions of PPCPs and organic matters in water with different concentrations and different PPCPs under the same operation condition and a change rule of water toxicity are explored, the influence of PPCPs on the toxicity of an activated sludge system is represented by using a viable bacteria and dead bacteria staining method, and the influence degree of PPCPs on a sewage treatment system can be rapidly analyzed through relative fluorescence intensity. Therefore, a rapid and effective detection method is provided for monitoring the influence of the PPCPs in the inlet water of the sewage plant on the treatment process of the water plant, and the method has a wide application prospect.

The invention relates to the technical field of elemental analysis, in particular to an all-elemental analysis method for unknown waste. The all-element analysis instrument provided by the invention comprises an inductively coupled plasma emission spectrometer (ICP-OES), an inductively coupled plasma mass spectrometer (ICP-MS), an X-ray fluorescence spectrometer (XRF), an energy dispersive X-ray spectrometer (EDS), an infrared carbon-sulfur analyzer, an oxygen-nitrogen-hydrogen analyzer, an elemental analyzer (EA), a chemical method, a spark direct-reading spectrometer and an ion chromatograph (IC). The all-element analysis can accurately determine the contents of components and elements in the product, and can provide high-quality and comprehensive data, thereby helping researchers to better understand the interaction and influence among the elements. All-element analysis of the unknown waste is of great significance to improvement of waste resource utilization efficiency, optimization of waste treatment process, promotion of green low-carbon technical progress and formulation of effective resource utilization measures.

The invention discloses a method, a system, equipment and a medium for determining impurity components in graphite ore, and relates to the technical field of component determination. The method comprises the following steps: preparing a standardized sample; respectively measuring a to-be-measured sample and the standardized sample by using an X-ray fluorescence spectrophotometer, and determining the elemental analysis line intensity of the to-be-measured sample and the elemental analysis line intensity of the standardized sample; performing regression analysis on the elemental analysis line intensity of the standardized sample by using a mathematical correction mode, and determining related parameters; the related parameters comprise a calibration curve constant and a spectral line overlapping interference correction coefficient; and content calculation is carried out based on the elemental analysis line strength of the sample piece to be detected and the related parameters, and the impurity components in the target graphite ore are obtained. The method provided by the invention can improve the determination precision of impurity components in graphite ore.

The invention discloses an atmospheric microparticulate monitoring device and method based on multi-mode sensing, and relates to the technical field of ecological environment monitoring. The device comprises a data acquisition system used for carrying out real-time sample acquisition and signal conversion on conventional pollution factors and meteorological parameters in air; the data analysis system is used for carrying out concentration analysis and early warning on the signals converted by the data acquisition system; the error evaluation system is used for performing error evaluation on the key indexes of the data acquisition system according to the acquired samples; and the data transmission system is used for carrying out cross-regional transmission on the sample acquired by the data acquisition system and the analysis result according to a sensitivity quantity algorithm based on an anonymous model. Real-time monitoring of atmospheric micro-particles with high accuracy and strong applicability is realized based on atmospheric monitoring standards independent of a meteorological monitoring framework, and reasonable adjustment of device parameters is realized by cooperation of the atomic fluorescence spectrometer and the enrichment sampling and pretreatment unit.

The invention discloses a novel method for detecting the thickness of a diamond and diamond-like carbon coating layer based on X-rays, which adopts X-ray nondestructive detection and adds an optimization algorithm, can solve the influence of residues on a detection result by an algorithm for single-ray mutual interference of the same element, and can improve the detection accuracy. The optimization algorithm and the method can be applied to the thickness of diamond grown in the surface physical modification direction of chip products, diamond-like carbon (DLC) coatings on the surfaces of hard alloys such as tool steel and structural materials, CVD (chemical vapor deposition) diamond coatings and the like. The method is also applicable to other element thicknesses of which the surfaces are not detected by the energy dispersion X-ray fluorescence spectrometer, such as nitrogen N layers and oxygen O layers, and also comprises cicada wing membranes or biological bionic membranes in the biological direction. In the aspect of chemical industry, the method is suitable for PE polyethylene and epoxy resin.

The invention discloses a method and device for detecting the state of a filter screen of air purification equipment, and relates to the technical field of filter screen state monitoring, and the method comprises the following steps: selecting a quantum dot material and an intelligent response type indicator material, respectively coating and weaving the materials on the filter screen, and measuring the original fluorescence intensity of the new filter screen by using a fluorescence spectrometer; calculating a comprehensive evaluation function according to the change of the fluorescence intensity, the color change of the pH sensitive dye and the influence of the coating thickness, and performing acoustic resonance frequency measurement by using the data of the initial state to obtain a resonance frequency characteristic curve when the pH sensitive dye is not polluted and a resonance frequency characteristic curve when the pH sensitive dye is not polluted; comparing the difference between the current fluorescence intensity and the initial fluorescence intensity, comparing the change of the resonance frequency characteristic curve with the resonance frequency characteristic curve without pollution, and comparing the color of the current pH sensitive dye with the initial high-quality picture; and judging whether the intelligent response type indicator material is abnormal or not by combining all comparison results.

The invention belongs to the technical field of environmental monitoring, and particularly relates to a water pollution source identification method based on adaptive three-dimensional fluorescence spectrum (3D-EEM) analysis and a multi-scale convolutional neural network (ACNN-MS). Specifically, the invention provides a method combining a self-adaptive three-dimensional fluorescence spectrum analysis technology and a multi-scale convolutional neural network (MS-CNN), 3D-EEM data are obtained through an improved high-sensitivity three-dimensional fluorescence spectrometer, residual connection is introduced in model construction to avoid the gradient disappearance problem, and the method has the advantages that the method is simple and easy to implement, and the real-time performance of the 3D-EEM data is improved. And a new adaptive wavelength selection algorithm (AWSSA) is utilized to screen the most representative wavelength interval for high-precision calculation, so that the defects of high detection limit, low precision, need of opening a black box and difficulty in traceability positioning of a traditional spectrum and algorithm are overcome. According to the method, the pollution source can be efficiently positioned, the early warning information can be provided, and the quick response capability of the water body pollution event is remarkably improved.

The invention provides a performance testing method and system for a loess foundation solidified by an industrial solid waste green cementing material, and relates to the technical field of foundation performance testing. The method comprises the steps that sampling points are evenly distributed on a solidified loess foundation, and solidified soil samples are collected in a layered mode according to the depth; detecting the solidified soil sample through an X-ray fluorescence spectrophotometer to obtain the content of solid waste components; the uniformity score of the solidified loess foundation is determined; obtaining the wet density and the moisture content of the solidified soil sample; the compactness score of the solidified loess foundation is determined; obtaining the mixing amount of a cementing material and the number of maintenance days of the solidified loess foundation; inputting the mixing amount of the cementing material and the number of maintenance days into a trained compressive strength prediction model to obtain predicted compressive strength of the solidified loess foundation; determining a compressive strength score of the solidified loess foundation; and determining the performance score of the solidified loess foundation. According to the invention, the performance of the solidified loess foundation can be comprehensively tested according to the uniformity, compactness and compressive strength of the solidified loess foundation.

The invention discloses a method for detecting perfluorinated compounds by using a sensor array composed of dyes, comprising the following steps: S1, preparing a fluorescent dye solution: preparing a fluorescein diluent, a coumarin 7 diluent, and a cyanine diluent; S2, preparing a pollutant solution: preparing diluted PFBA solution, PFOA solution, PFDA solution, PFUdA solution, and PFDoA solution; S3, constructing a fluorescent sensor array and detecting perfluorinated compounds: placing a sample in a fluorescence spectrometer for detection. The dyes used in the detection method of the invention are easy to obtain and have strong fluorescence stability. The sensor array can detect perfluorinated compounds with similar structures, and the operation is simple.

An article with a surface layer, that is excellent in fingerprint stain removability, friction resistance, and adhesion to a protective film of the surface layer. The article includes a base material and a surface layer provided on the surface of the base material. The surface layer contains groups having —O— between carbon-carbon atoms of a fluoroalkyl group with two or more carbon atoms and has a normalized F intensity in a range of 0.38 to 0.53, where the normalized F intensity is obtained by preparing a glass containing 4.96 mass % of fluorine atoms as a standard sample, measuring, by an X-ray fluorescence spectrometer, the fluorine atom intensity in the surface layer and the fluorine atom intensity in the standard sample, respectively, and dividing the fluorine atom intensity in the surface layer by the fluorine atom intensity in the standard sample.

The present invention belongs to the technical field of pesticide residue detection, and specifically relates to a DebNet intelligent classification method based on fluorescence pesticide residue detection, comprising the steps of detecting pesticide samples using a fluorescence spectrometer to obtain one-dimensional spectral data of the pesticide samples; preprocessing the spectral data; performing data enhancement on the preprocessed spectral data, wherein the enhancement methods include linear interpolation, noise injection, spectral shifting, and spectrum clipping; building a hybrid neural network model including an input layer, a convolutional layer, a pooling layer, an LSTM layer, a self-attention module, a fully connected layer, and an output layer, namely a DebNet model; training the DebNet model based on the enhanced spectral data, wherein the training process includes forward propagation and backpropagation; and utilizing the trained DebNet model to classify and identify the spectral data of the sample to be tested. The present invention can improve classification accuracy, reduce sample requirements, simplify data processing procedures, and reduce detection costs.