152 results about "Three dimensional fluorescence" patented technology

The invention belongs to the technical field of river and lake water quality monitoring, and discloses a river and lake water quality intelligent traceability monitoring system and method.Dissolved organic matter fluorescent fingerprints are analyzed in real time through a three-dimensional fluorescent monitoring unit, pollution markers are detected, and parameters such as COD, ammonia nitrogen and total phosphorus are synchronously detected through a full-spectrum monitoring unit; the video monitoring unit is used for collecting section images / videos of rivers and lakes, other sensors are used for collecting real-time values of chlorophyll, pH, conductivity, turbidity and dissolved oxygen in a water body, then the data processing module is used for carrying out normalization processing on multi-source data, and the analysis and early warning module is used for analyzing water quality early warning scores, spectrum early warning scores and video early warning scores. All scores are synthesized to obtain a comprehensive early warning score, traceability is started when comprehensive early warning is larger than or equal to the grade II, pollution sources are recognized based on three-dimensional fluorescence spectrum comparison and upstream patrol, and a river and lake water body monitoring-early warning-traceability-verification closed loop is achieved.

The invention particularly relates to a water pollution intelligent traceability system based on a three-dimensional fluorescence spectrum, which relates to the technical field of environmental monitoring, and comprises a water sample collection and three-dimensional fluorescence data acquisition module, a data preprocessing and PARAFAC component decomposition module, a multi-source pollution characteristic fingerprint database module and an intelligent comparison and pollution source analysis module. According to the method, standard acquisition and preprocessing are adopted, and the original data quality is ensured by means of scattering rejection, instrument correction and the like; pure fluorescence components are decomposed through a PARAFAC algorithm, and feature extraction reliability is guaranteed through triple verification. In the comparison link, spectrum similarity, concentration proportion difference and space-time hydrological constraint multi-round screening are adopted, and irrelevant pollution sources are removed; and then the contribution proportion is quantified, and Monte Carlo simulation, water quality and specific pollutant cross validation are carried out, so that the crossing from suspected tracing to quantitative responsibility investigation is realized.

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.

The invention relates to the technical field of electronics, and discloses a drainage pipe network pollutant tracing method, device and equipment, a medium and a program product. According to the method, the map similarity between a first three-dimensional fluorescence spectrum map corresponding to a first water sample of a target node and a second three-dimensional fluorescence spectrum map corresponding to each upstream pipe network node is calculated; and determining at least one target upstream pipe network node in the plurality of upstream pipe network nodes based on the map similarity, and determining pollution source information of abnormal water in a target node according to first water quality data of the target upstream pipe network node and second water quality data on a sewage flowing path between the target upstream pipe network node and the target node, the advantages of high sensitivity, rapid detection and the like of the three-dimensional fluorescence spectrum technology are utilized in the pollutant traceability process, and efficient and accurate traceability of pipe network pollutants is achieved.

The invention discloses a water sample pollution traceability analysis method fusing absorption-three-dimensional fluorescence spectrum characteristics, and relates to the field of water sample spectrum analysis traceability. According to the method, high-precision prediction of pollutant indexes is realized by utilizing multi-dimensional information of a three-dimensional fluorescence spectrum and an absorption spectrum of a water sample, qualitative and quantitative traceability of main pollution components and potential emission sources in a water body is carried out based on correlation analysis of the prediction indexes, a pollutant feature library and an emission source database, and the method has the advantages of high accuracy and high accuracy. The integration of water quality monitoring and pollution source management is realized, and a systematic and real-time technical means is provided for pollution analysis of a complex water body.

The invention relates to the field of environmental monitoring, and particularly discloses a non-negative matrix factorization and adaptive peak recognition fluorescence feature extraction and traceability system, which comprises a spectral data preprocessing module, a spectral data non-negative matrix factorization module, a component number automatic selection module, an adaptive peak recognition module, a feature library construction module and a similarity comparison module. An improved non-negative matrix factorization model is adopted to decompose the three-dimensional fluorescence spectrum matrix of a single sample, and an optimal component number K is automatically determined through multiplicative update rule iterative optimization; the self-adaptive peak identification module carries out selective filtering, accurately extracts the position and intensity of a fluorescence peak through multiple mechanisms, and carries out peak position calibration in a neighborhood; the Hungary algorithm is adopted to carry out characteristic peak matching to calculate the comprehensive similarity between the samples, and rapid and accurate identification of the pollution source is realized. The method has the advantages of high resolution, strong anti-interference capability, low requirement on the number of samples, automation and the like, and is suitable for water quality fingerprint feature extraction of a water sample in a complex environment and real-time source tracing of sewage.

The invention provides an underground water environment monitoring system and method, and the method comprises the steps: carrying out the three-dimensional fluorescence spectrum full-wave band scanning of a known type of pollution source reference sample in a target monitoring region, and obtaining a three-dimensional fluorescence spectrum data set; performing characteristic analysis on the three-dimensional fluorescence spectrum data set to obtain fluorescence characteristic components, and determining a characteristic excitation wavelength corresponding to each fluorescence characteristic component; the classification contribution degree of each characteristic excitation wavelength is evaluated, and a characteristic excitation wavelength combination during source tracing of the pollution source is obtained through screening; performing fixed wavelength scanning on the to-be-detected underground water sample in the target monitoring area according to the characteristic excitation wavelength combination, and determining the initial type of the pollution source; and determining the relative contribution degree of the type of the pollution source of the to-be-detected underground water sample, simulating the migration trend of the pollution plume according to the underground water migration and diffusion model, and generating the position of the pollution source of the to-be-detected underground water sample. By adopting the scheme of the application, the pollution source of the underground water can be quickly identified and positioned at low cost.

The invention belongs to the technical field of water pollutant identification, and particularly relates to a water pollutant distinguishing method and system based on multi-source spectrum fusion. According to the method, ultraviolet visible spectrum data and three-dimensional fluorescence spectrum data are effectively integrated in a multi-source spectrum data fusion mode, so that the characteristic information of water pollutants is captured, stably appearing characteristic absorption wavebands can be positioned by utilizing the ultraviolet visible spectrum data, and the water pollutants can be accurately detected. The method comprises the following steps: identifying a characteristic sub-region capable of representing the fluorescence response characteristic of a pollutant through three-dimensional fluorescence spectrum data, in a characteristic extraction stage, performing first-order derivative operation on an ultraviolet visible spectrum to position an absorption peak position, calculating curvature distribution of a three-dimensional fluorescence spectrum to identify the characteristic sub-region, and when a fusion characteristic is generated, performing first-order derivative operation on the three-dimensional fluorescence spectrum to identify the characteristic sub-region; according to the method, the key operation parameters are subjected to grid search optimization, and the optimal key operation parameter combination is screened out by performing multiple rounds of iterative training and evaluation on a preset training set and a verification set, so that the recognition performance of the real-time collected water sample is improved.

The invention belongs to the technical field of environment monitoring, and particularly relates to a quantitative recognition method for contribution of autogenous source organic carbon of a surface water body. Based on the stable isotope ratio and the three-dimensional fluorescence spectrum, the water DOM source analysis method is constructed, the source and characteristics of DOM are comprehensively analyzed, and the characteristic information and contribution of autogenous source organic carbon are specifically recognized. The three-dimensional fluorescence spectrum has the advantages of being rapid in detection, small in sample use amount and the like, DOM sources can be rapidly and qualitatively identified, different DOM sources can be quantitatively calculated through stable isotope ratio analysis, and meanwhile the research area land utilization, hydrological water environment and water quality parameters are combined, so that the DOM sources can be rapidly and qualitatively identified. And the source and migration rule of the DOM in the water body can be determined more comprehensively. The quantitative identification method provided by the invention has the advantages of more comprehensive water DOM research, more complete identification system and more reliable traceability result.

A modality for compressed light field measurement to capture 3D fluorescent signals at kilohertz volume rate, is described. This modality, termed Squeezed Light field Microscopy (SQLFM), acquires the light field with an array of rotated 2D sub-aperture images. An anamorphic relay system applies anisotropic scaling, effectively "squeezing" the image along one axis. This allows the camera sensor to detect the light field with a letterbox-shaped region of interest (ROI). Each squeezed sub-aperture image is complementary to the others, facilitating successful 3D reconstruction from compressed measurement while preserving the nominal FOV and spatial resolution. SQLFM can achieve over a fivefold increase in acquisition rate compared to traditional LFM.

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 relates to a three-dimensional fluorescence spectrum image super-resolution reconstruction method for a water quality detection instrument, which is suitable for reconstructing a low-resolution and sparse three-dimensional fluorescence spectrum image collected by a portable water quality detection instrument into a high-resolution full spectrum. According to the method, an efficient super-resolution reconstruction network architecture composed of a feature extraction module, an up-sampling module and a trainable multi-Gaussian mixture point spread function is constructed. A joint loss function combining a reconstruction error and a degradation consistency error is designed, and a joint training strategy is adopted to synchronously optimize a network and PSF parameters, so that accurate reduction of a fluorescence peak shape structure and enhancement of spectrum authenticity are realized. The applicability and robustness of the portable water quality detection instrument based on the three-dimensional fluorescence spectrum in pollutant identification and analysis tasks are improved, and the portable water quality detection instrument is suitable for actual scenes such as intelligent water quality monitoring.

The invention relates to the technical field of fluorescence detection, in particular to a three-dimensional fluorescence detection correction method based on double light sources, and the correction method comprises the following steps: obtaining double light source optical parameters, sample cell geometric parameters and original fluorescence intensity data, the geometric parameters of the sample pool comprise the length, width, height, pool wall reflection coefficient and sample attenuation coefficient of the sample pool; and constructing a light intensity distribution model in a three-dimensional space of the sample cell based on the optical parameters of the double light sources and the geometric parameters of the sample cell. According to the invention, accurate characterization of the light intensity of any spatial point in the sample cell is realized, light intensity deviation caused by various factors is quantified from the source, personalized correction is carried out on each spatial point, the influence caused by optical path difference at different positions, light source fluctuation and element error is effectively offset, and the accuracy and accuracy of the detection result are improved. The consistency of detection values of standard substances with the same concentration in different areas of the sample pool is greatly improved, and the linearity of a standard curve is remarkably optimized.

The invention discloses a Maotai-flavor liquor process category and authenticity identification model construction method, an identification method, an identification device and equipment. The method comprises the following steps: acquiring data of liquor samples; preprocessing the sample data to obtain preprocessed sample data; the preprocessed sample data are input into an initial identification model constructed based on a graph neural network or a partial least square discrimination method, the initial identification model is trained, target identification models are obtained, and the target identification models comprise a gas chromatography identification model, an ion chromatography identification model and / or a three-dimensional fluorescence spectrum identification model. According to the method, multiple analysis technologies such as GC, IC and EEM and a chemometrics modeling analysis module are adopted, analysis results of different technologies are mutually verified, a target identification model with high prediction precision is constructed, and accurate identification of the process category and authenticity of the Maotai-flavor liquor is realized.

The invention discloses an activated sludge fluorescence online detection device based on a flow cell, and relates to the field of activated sludge biomass detection.The activated sludge fluorescence online detection device comprises a fluorescence spectrophotometer and a fluorescence spectrophotometer sample table arranged on the fluorescence spectrophotometer, and the fluorescence spectrophotometer is connected with a processor through a cable; the fluorescence spectrophotometer sample table is connected with a sample cup through a guide pipe, activated sludge is arranged in the sample cup, and a peristaltic pump is arranged on the guide pipe; the activated sludge continuously flows through the fluorescence spectrophotometer sample table through the guide pipe for three-dimensional fluorescence detection through the peristaltic pump, sludge sedimentation in a traditional cuvette is avoided, measurement is simple and convenient, and on-line real-time monitoring of the activated sludge biomass can be achieved.

The invention belongs to the technical field of fluorescence spectrum collection, and particularly relates to a quasi-three-dimensional fluorescence spectrum collection method and spectrograph based on a software phase locking technology, and the method comprises the following steps: respectively modulating coprime modulation frequencies of a plurality of laser light sources with different wavelengths, and synchronously exciting the laser light sources to the surface of a sample; a fluorescence signal generated on the surface of the sample is received and processed by a linear array CCD detector to obtain a multi-wavelength spectral signal simultaneously containing background light, scattered light and fluorescence components; inputting the multi-wavelength spectral signal into a software phase-locked amplification system, introducing a Costas ring to the software phase-locked amplification system for real-time tracking and correction, and generating a synchronous reference signal consistent with the laser modulation frequency; inputting the synchronous reference signal into a software lock-in amplifier, and extracting a plurality of pure fluorescence spectrum components excited by specific-frequency laser; and synthesizing the plurality of pure fluorescence spectrum components to finally form a quasi-three-dimensional fluorescence spectrum.

The invention provides an urban rainwater pipe network mixed connection tracing method based on a pollution source fluorescence spectrum library in combination with machine learning. The method relates to the fields of numerous pollution sources around a pipe network, complex mixing and connecting conditions and the like. The method comprises the following steps: sampling through an inspection well to obtain a water sample; extracting an organic matter multi-dimensional characteristic matrix from the water sample by adopting technologies such as three-dimensional fluorescence spectroscopy (EEM) and the like; and carrying out fluorescence data analysis on the multi-dimensional characteristic matrix by using an NPLSDA (N-Way Partial Least Squares Discriminant Analysis) model, carrying out comparative analysis and identification, and determining the source of the pollution source. According to the technology, the specific source of mixed connection sewage of the rainwater pipe network can be quickly diagnosed through mixed connection rainwater well sampling analysis, and efficient and convenient decision support is provided for mixed connection transformation and traceability investigation of the urban rainwater pipe network.

The application discloses a kind of municipal engineering technical field's multi-source data fusion's urban drainage pipe network evaluation method, for evaluating the drainage quality of drainage pipe network in target area, the method includes obtaining the water quantity data of each water treatment system in the first period of target area, water quality data, climate data, tidal data, water quantity corresponding permanent population data, pollution emission background value and low concentration external water three-dimensional fluorescence spectrum.The application is fused to multi-source data, and the water quality and quantity data of influent of sewage treatment plant or pump station are cleaned, the type of influent and seepage external water in sewage treatment plant is distinguished, the problem that current sewage treatment system quality improvement and efficiency evaluation method only focuses on external water quantity evaluation but external water type is not clear is solved, and then the improvement direction of drainage pipe network quality improvement and efficiency is clear, it is helpful to clear the priority of mixed error connection, damage and external water inflow problem in the quality improvement and efficiency range of drainage pipe network.

The invention relates to the technical field of leather wastewater treatment, and provides an ultraviolet-visible spectrum-based leather wastewater ozone dosage and COD (Chemical Oxygen Demand) prediction method. The method comprises the following steps: firstly, determining the types of organic matters in a tannery wastewater sample, and determining the distribution characteristics of the organic matters in different fluorescent regions through three-dimensional fluorescence spectrum analysis, so as to discriminate the types of organic pollutants; secondly, screening key wavelengths, and determining characteristic absorption wavelengths representing different organic matters through an ultraviolet-visible light spectrum; then carrying out an ozone oxidation experiment, and synchronously measuring a COD value and an ultraviolet absorption spectrum under different ozone addition amounts; based on experimental data, a multiple linear regression and exponential regression prediction model of ozone dosage and a COD prediction model based on partial least squares regression are established. According to the invention, accurate control of ozone dosage and real-time monitoring of COD are realized, the treatment efficiency is improved, the operation cost is reduced, the adaptability to water quality fluctuation is enhanced, and the method has a wide engineering application prospect.

The invention discloses a multi-source data fusion urban drainage pipe network evaluation method in the technical field of municipal engineering, which is used for evaluating the drainage quality of a drainage pipe network in a target area. The method comprises the following steps: acquiring inflow water quantity data, inflow water quality data, climate data, tide data, permanent population data corresponding to inflow water quantity, a pollution emission background value and a low-concentration external water three-dimensional fluorogram of each water treatment system in a target area in a first period; according to the invention, through multi-source data fusion, inlet water quality and quantity data of the sewage treatment plant or the pump station are cleaned, the types of the inlet water and the seepage water in the sewage treatment plant are distinguished, and the problem that the current quality and efficiency improvement evaluation method of the sewage treatment system only focuses on external water quantity evaluation, but the types of the external water are not clear is solved; therefore, the quality-improving and efficiency-improving transformation direction of the drainage pipe network is determined, and the priority of the problems of misconnection, damage and external water inflow in the quality-improving and efficiency-improving range of the drainage pipe network can be determined.

The invention relates to the technical field of oil-gas exploration, in particular to a method for measuring the oil content of an oil-based mud polluted rock core (rock debris). The method comprises the following steps: oil-based mud fluorescence quantification, sample pretreatment, ultrasonic oscillation extraction, extraction liquid fluorescence analysis, wellhead oil solvent fluorescence quantification and oil content calculation. The method comprises the following steps: collecting oil-based mud and wellhead oil on an exploration site, treating the oil-based mud and the wellhead oil with pesticide residue-grade dichloromethane, and determining respective fluorescence fingerprint spectrograms and characteristic peaks through three-dimensional fluorescence detection; the method comprises the following steps: grinding a rock core (rock debris) sample to 60-80 meshes, carrying out ultrasonic extraction to obtain an extract, detecting a spectrogram, identifying and deducting an oil-based mud pollution peak, and calculating the oil content by combining the correlation between the fluorescence intensity and concentration of wellhead oil. The method can effectively distinguish the oil-based mud from the oil content of the sample, realizes accurate detection of the oil content of the polluted sample, makes up for insufficient core data, is suitable for evaluation of conventional, unconventional, deep and ultra-deep oil and gas reservoirs, and provides reliable support for oil and gas exploration and the like.

The invention belongs to the field of soil dissolved organic matter analysis, and provides a multispectral-based DOM detection and reclamation influence evaluation method, which comprises the following steps: step 1, collecting dry farmland soil samples of different reclamation years, and obtaining soil column samples of a plough layer, a plow pan and subsoil; 2, extracting, centrifuging and filtering the soil sample to obtain a DOM solution; 3, detecting the DOM solution by adopting an ultraviolet-visible absorption spectrum; step 4, adopting a three-dimensional fluorescence spectrum and combining parallel factor analysis to obtain fluorescence components and source characteristics of the DOM solution; step 5, analyzing molecular composition and characteristic parameters of the DOM solution by adopting solid-phase extraction in combination with Fourier transform ion cyclotron resonance mass spectrometry; and step 6, based on the detection data in the steps 3-5, evaluating the influence of reclamation years on the composition, structure and degradation characteristics of the DOM. According to the method, multi-dimensional detection of soil DOM is realized through a multi-spectrum and mass spectrum combined technology, and DOM is comprehensively analyzed from a macrostructure to molecular composition.

The invention discloses a three-dimensional fluorescent nano printing method capable of being monitored in situ in real time, which comprises the following steps: (1) preparing a photoresist which comprises the following components: a two-step absorption photoinitiator, a small molecule polymerization monomer, aggregation-induced emission dye molecules and a photoresist auxiliary reagent; (2) a continuous laser beam acts on the photoresist through a three-dimensional scanning system, a double-step absorption photoinitiator generates an active factor through a double-step absorption process, a photopolymerization reaction of a small molecule polymerization monomer is initiated, and three-dimensional nano printing is achieved; in the photopolymerization region, the doped aggregation-induced emission dye molecules enable the printing structure to present strong fluorescence and the non-polymerization region to present weak fluorescence; and (3) rapidly scanning the three-dimensional nano printing area, obtaining the fluorescence intensity distribution of the three-dimensional nano printing structure in real time, and tracking and exploring the dynamic process and error correction of the three-dimensional nano printing. According to the invention, ultrahigh-precision fluorescent pattern three-dimensional nano printing and real-time in-situ detection can be realized.

The invention discloses a method, equipment, medium and product for predicting the year of Maotai-flavor liquor, and relates to the technical field of chromatography and spectrum, chemometrics and artificial intelligence analys.The method comprises the steps that a chromatographic separation technology is utilized, chromatographic data and spectrum data of a Maotai-flavor liquor sample to be detected are collected, the chromatographic data are preprocessed, and the year of the Maotai-flavor liquor sample to be detected is obtained; determining the preprocessed data; decomposing and processing the three-dimensional fluorescence spectrum data based on a high-order cyclic factor algorithm, and determining a decomposition result; taking the processed data as four trained Bayesian network models, and outputting four year prediction results of the Maotai-flavor liquor; and taking the median of the four year prediction results of the Maotai-flavor liquor as the final year prediction result of the Maotai-flavor liquor sample to be detected. According to the method, the year prediction accuracy and prediction efficiency of the Maotai-flavor liquor can be improved.

The application discloses a kind of aquaculture tail water solubility organic matter characteristic analysis method and system, specifically related to water quality monitoring and analysis technical field, for solving the problem that existing solubility organic matter characterization method is difficult to effectively associate and predict its actual degradation behavior in biological treatment process.Synchronously obtain the three-dimensional fluorescence spectrum data of the water sample to be measured and the liquid chromatography-organic carbon detection combined analysis data, obtain the hydrophilic-hydrophobic component ratio and the proportion of tyrosine-like and humus-like fluorescence components from the analysis, and then judge whether there is significant humus-like component.According to the judgment result, selectively start the deep analysis of the molecular aggregation state of humus-like component, and comprehensively consider the related proportion parameters and aggregation state information, finally realize the evaluation of the biological degradation potential trend of solubility organic matter, and provide key basis for the stability warning of biological treatment system.

A deep learning-based method and system for statistical analysis of fluorescence proportion information in microfluidic droplet arrays, belonging to the field of ddPCR detection technology, includes the following steps: S1 acquiring a three-dimensional fluorescence volume image of the droplets and performing preprocessing; S2 constructing a DropletSegNet model; S3 pre-training the DropletSegNet model constructed in S2; S4 using the three-dimensional fluorescence volume image to be tested as input to the DropletSegNet model, and transforming the original output of the DropletSegNet model into droplet analysis results with physical meaning and biological interpretability. A droplet stacking topology decoupling module is designed, modeling the adhesion decoupling as an edge classification problem on a graph structure, and using a graph neural network (GCN) for structured post-processing. This achieves accurate decoupling and segmentation even in cases of tight droplet stacking or adhesion, improving the accuracy of nucleic acid concentration calculation and positive proportion statistics.

The invention discloses a dishwasher cleaning performance detection method based on fluorescence imaging, which comprises the following steps: performing simulated washing on pollutants and polluted tableware based on temperature and time parameters of a to-be-tested dishwasher to obtain a washed product, the method comprises the following steps: acquiring a fluorescence image of washed tableware according to a three-dimensional fluorescence spectrum of washed pollutants and a fluorescence imaging system, modeling a pollution contact curved surface according to physical parameters of the washed tableware, and correcting a pollution area in the fluorescence image by using a curved surface model to obtain a corrected area; and extracting the total pixel area of the polluted area in the washed tableware based on the corrected area, and calculating to obtain a cleaning performance score. According to the method, the problem that pollutants are difficult to identify when being similar to the surface color of tableware is solved by utilizing a fluorescence technology, a cleaning performance score evaluation mode is given from a pixel level, and the intelligent development of the cleaning performance test of the dish washing machine is promoted.

The present application belongs to the technical field of three-dimensional fluorescence spectrum analysis, chemometrics and machine learning, and discloses a traditional Chinese medicine harvest period identification method, system and electronic equipment fusing three-dimensional fluorescence and machine learning, aiming at the problems of long time consumption of traditional Chinese medicine harvest period identification methods, insufficient precision of existing spectrum analysis and weak model generalization ability, comprising: obtaining three-dimensional fluorescence spectrum data of the traditional Chinese medicine to be identified; after background and scattering subtraction, extracting fluorescence intensity through a weight self-adaptive alternating trilinear decomposition algorithm; substituting the fluorescence intensity into an improved prediction model to output a harvest period prediction value. The present application combines the fast and efficient advantages of three-dimensional fluorescence spectrum with the precise analytical ability of high-order matrix decomposition and machine learning, realizes fast, accurate and stable identification of the harvest period of traditional Chinese medicine through feature weighting screening, batch difference correction and harvest period interval penalty optimization, adapts to batch detection requirements, reduces detection cost and provides technical support for quality control of traditional Chinese medicine.

A water pollution trend prediction method based on three-dimensional fluorescence spectrum image features comprises the steps that firstly, the three-dimensional fluorescence spectrum image features are extracted through a Krawtchouk moment and an HOG descriptor, and the Euclidean distance between a current measurement point and a normal water quality cluster center is calculated and used for representing feature space similarity; meanwhile, analyzing the similarity of the position relationship through a binarization template of a fluorescence spectrum contour curve; and finally, carrying out weighted fusion on the two similarities to realize anomaly detection. For trend prediction, the pollution development trend is judged by calculating the included angle between the to-be-detected point and each pollution type cluster center relative to the normal water quality cluster center. According to the method, high-precision anomaly detection is realized by fusing the feature space similarity and the position relation similarity, and the pollution trend is judged by using the included angle. The method not only can capture the subtle change of the position and shape of the fluorescence peak of the three-dimensional fluorescence spectrum, but also can improve the recognition and prediction capabilities.

The invention discloses a method for simulating phosphorus and chromium migration during farmland irrigation with acid mine wastewater, which comprises the following steps: mixing a plant-derived organic material with deionized water to obtain a soluble organic matter; h2O2 oxidizes Fe < 2 + > to prepare pure Schwertmannite, and the pure Schwertmannite is placed in a phosphate solution to obtain phosphorus-loaded Schwertmannite; mixing the phosphorus-loaded Schwertmannite and the soluble organic matter with a chromate solution, carrying out oscillation adsorption, carrying out solid-liquid separation after adsorption, carrying out CrO and POconcentration change test on filtrate, and carrying out mineral characterization on separated solids; a three-dimensional fluorescence spectrum is adopted to track composition conversion of the soluble organic matter in the reaction process; and analyzing the component change of the supernate before and after the reaction by adopting Fourier transform ion cyclotron resonance mass spectrometry. The influence mechanism of DOM on phosphorus and chromium fate in mineral / water interface molecular fractionation is disclosed from the molecular level, and a scientific basis is provided for collaborative migration risk assessment of phosphorus and heavy metal in acid mine wastewater irrigation area farmland.