356 results about "Water pollutants" patented technology

The invention discloses a method for inverting key parameters in an underground water pollutant biodegradation numerical model based on a neural network algorithm. Carrying out preprocessing and refined dimension reduction on the data, and processing high-dimensional multi-scale data; building a multilayer neural network architecture under a physical information neural network framework, embedding a related reaction equation of a pollutant natural attenuation process, and coupling a biochemical reaction mechanism and a data driving model; a neural network model is trained, errors in the training process are calculated, and the accuracy of an inversion result is improved by using a sub-when optimization algorithm; integrating observation data and a model prediction result, determining final parameter setting of a numerical model, and carrying out underground water damage real object quantification; comparative verification of a neural network parameter inversion model is carried out, and feasibility and accuracy of the parameter inversion method are ensured. According to the method, the problem that the key parameters of the biodegradation numerical model are difficult to accurately invert in the real object quantification process of underground water pollution under complex geological conditions is solved.

The invention discloses an intelligent monitoring and early warning system and method for agricultural non-point source pollution, and relates to the technical field of environmental monitoring, accurate prediction of water pollutant concentration is realized through multi-source heterogeneous data acquisition and fusion, a dynamic attention mechanism and a PINN-Transformer coupling model, the system extracts data spatial and temporal characteristics by using an optimized Transformer model, and the method is applied to the intelligent monitoring and early warning of agricultural non-point source pollution. A water pollution diffusion physical constraint is embedded, it is ensured that a prediction result conforms to an actual hydrodynamic law, and based on high-precision spatial-temporal distribution data, an intelligent algorithm is adopted to track a pollution diffusion path and rapidly lock a pollution source; meanwhile, the cellular automaton model simulates pollution risk dynamic diffusion and assists regional risk assessment, the system also combines a block chain technology to carry out credible evidence storage on key monitoring data, and real-time data processing and early warning pushing are realized through a cloud edge collaborative architecture. And an efficient and reliable technical solution is provided for agricultural water environment management and pollution prevention and control.

The invention relates to the technical field of water quality detection, and discloses a water quality pollutant detection method, system and equipment based on spectral analysis, and the method comprises the following steps: carrying out real-time spectral data acquisition on a water body sample in a vehicle driving process through a multispectral sensor array in a vehicle-mounted water quality detection device; obtaining a water body spectrum three-dimensional data cube; carrying out anti-vibration wavelength calibration and ambient light source interference elimination processing to obtain a preprocessed spectrum data set; performing standard multivariate decomposition processing and horizontal local constraint optimization of a pollutant target wave band on the preprocessed spectrum data set to obtain enhanced feature fingerprint spectrums for different types of water quality pollutants; and inputting the enhanced feature fingerprint spectrum into a deep belief network model to perform pollutant feature matching analysis to obtain various pollutant types and corresponding concentration values in the water body sample, thereby effectively eliminating ambient light changes and other background interferences, not only determining the pollutant types, but also accurately quantifying the concentration values.

The invention belongs to the technical field of water pollutant traceability, and particularly discloses a water quality fingerprint database analysis method based on feature recognition, which relates to the field of water pollutant traceability, and comprises the following steps: cross-comparing feature curved surface information of different upstream and downstream under feature peak whole database data and sorting to obtain pollutant features under different intensities; the pollution source type is identified according to the pollutant difference; sorting the characteristic curved surface information of the water body samples reflecting different nodes, calling a chemical characteristic analysis result, outputting a chemical characteristic sequence, and selecting a first sequence sampling point position of the chemical characteristic sequence corresponding to the spectral characteristics of the identified pollution source type as a pollution source; according to the method, whether the identification result is met or not is analyzed according to the biological characteristics of the pollution source, efficient source tracing is carried out on water pollutants, an accurate pollutant transmission path is output, meanwhile, the corresponding pollutant type is evaluated, the corresponding pollutant diffusion trend is given, and powerful data is provided for follow-up pollutant treatment.

The invention discloses an intelligent detection method for water pollutants, which comprises the following steps of: transmitting a signal of a specific frequency band to a water body through an electromagnetic wave transmitting module, acquiring reflected and refracted signals by using a multi-channel receiver, extracting the characteristics of dielectric constant, refractive index and the like of the water body, and analyzing the types and the concentration range of the pollutants by adopting a pattern recognition algorithm; the method comprises the following steps: selecting a micro-fluidic chip and an electrochemical unit, selecting a corresponding biosensor for targeted detection, processing detection data through the micro-fluidic chip and the electrochemical unit, predicting the concentration, spatial distribution and trend of pollutants through a data analysis module, setting a dynamic self-adaptive threshold by the system, realizing pollution early warning, and uploading data to a cloud platform through a remote communication module. And remote monitoring is supported. The method can be widely applied to the fields of water quality monitoring, environmental protection and pollution control, and the detection precision, the real-time performance and the intelligent level are improved.

The invention provides an underground water pollutant concentration prediction method and system based on machine learning, and relates to the technical field of underground water pollutant concentration prediction.The method comprises the steps that historical data, hydrogeological parameters, meteorological data, human activity data and geochemical parameters of underground water pollutant concentration of a target area are preprocessed; dividing a training set, a verification set and a test set; constructing a preset resolution feature set based on a geochemical mechanism; selecting an adaptive machine learning model according to data characteristics and coupling a physical mechanism; performing hyper-parameter tuning by adopting Bayesian optimization, and supplementing small sample data in combination with transfer learning to complete model training; predicting the underground water pollutant concentration of the target area by using the trained model, and outputting a pollutant concentration prediction result with an uncertainty interval; the invention provides a technical scheme for predicting the concentration of underground water pollutants, which is efficient, accurate and high in adaptability.

The invention relates to the technical field of water quality detection, and discloses a water quality detection method and device based on an electrochemical sensor. The method comprises the following steps: deploying a multi-depth electrochemical sensor array in a target water body according to different water depth positions and carrying out real-time monitoring to obtain electrochemical response signal data; performing electrochemical fingerprint feature recognition on the electrochemical response signal data to obtain electrochemical feature vectors of water sample pollutants at different water depth positions; carrying out pollutant analysis through a hierarchical electrochemical transfer-attention network model to obtain types and concentrations of heavy metal ions and organic pollutants in water samples at different water depth positions; and executing Kriging space interpolation and environmental factor correction to generate a three-dimensional pollutant distribution dynamic map of the target water body. According to the method, high-precision identification of low-concentration multi-component coexisting pollutants is realized, and visual analysis of spatial distribution characteristics and migration rules of water pollutants is realized.

The invention discloses an industrial park groundwater pollutant screening and identification method, which comprises the following steps: firstly, scoring the source strength, toxicity and path of pollutants through a comprehensive scoring method, and carrying out preliminary screening according to the scoring result to determine preliminarily concerned pollutants, thereby being beneficial to narrowing the screening range and reducing unnecessary evaluation work; the evaluation efficiency is improved. Meanwhile, the ITD index model constructed based on the three dimensions of source intensity, toxicity and path can more comprehensively consider the potential risk of the pollutants, and a scientific basis is provided for an evaluation result. The toxicity test result is introduced, so that the evaluation result is more accurate, and experimental data support is provided for the evaluation result. The method can provide scientific basis and technical support for underground water pollution prevention and control in industrial parks. According to the comprehensive evaluation result, corresponding risk prevention and control measures are provided for the optimal control pollutants in the list, the underground water pollution risk of the industrial park is reduced, and the environment and human health are protected.

The invention discloses a simulation-optimization method for a pollution site groundwater pumping-injection-treatment pollution remediation system based on a multiform evolution search normal form. The method comprises the following steps: constructing a groundwater flow model and a pollutant solute transport model; the method comprises the following steps: determining a management objective function and constraint conditions of hydraulic control of an underground water pollution range, establishing an underground water pollutant treatment model, optimizing underground water pumping and injection treatment of a pollution site by adopting BLMFO, solving the problem of interdependence between an upper-layer global target and a lower-layer local target through nested optimization, and constructing an auxiliary task by utilizing MFO; state variables are updated through the groundwater flow model and the pollutant solute transport model, a management objective function value of the groundwater pollutant treatment model is calculated, and whether constraint conditions are met or not is judged; meanwhile, decision variables are selected by optimizing the groundwater pollutant treatment model, and state variables are updated by returning to the groundwater flow model and the pollutant solute transport model.

The invention provides a method for rapidly detecting wastewater pollutants by atomic fluorescence spectrometry, and belongs to the technical field of wastewater treatment.The method comprises the steps that atomic fluorescence spectrum data of a wastewater sample are collected to establish a spectrum interference matrix to characterize the spectral line overlapping condition between elements; abnormal values are recognized through statistical analysis, a spectrum outlier matrix is built, abnormal fluorescence intensity distribution is recorded, sample matrix non-characteristic fluorescence signals are measured, a background fluorescence interference matrix is built, background interference intensity is quantized, system signal change rules are continuously monitored and detected, and a signal drift tendency matrix is built to predict the signal drift tendency. A spectrum interference matrix and a background fluorescence interference matrix are processed through a spectrum analytic function, compensation factors are calculated, spectrum overlapping and background interference influences are corrected, system drift is corrected in real time, and a final wastewater pollutant concentration detection result is output, so that the technical problem of unstable detection precision caused by coupling of multiple interference factors is solved.

The invention relates to an electric flocculation reactor and an electric flocculation treatment method. The electric flocculation reactor is provided with a biochemical treatment unit and a pretreatment unit located in the front of the biochemical treatment unit, and an electrode assembly with adjustable electrode spacing is arranged in the pretreatment unit. According to the electric flocculation treatment method, the electric flocculation reactor is adopted for removing pollutants in water, the distance between electrode plates in the electrode assembly is set or adjusted according to the water flow of inlet water or the pollutant flow, the biochemical treatment unit comprises an aerobic tank, the electrode assembly is arranged in the aerobic tank, iron ions are released through the electrode assembly, and the water quality is improved. And an iron ion environment beneficial to growth and metabolism of aerobic microorganisms is formed. According to the invention, the electrode spacing of the electric flocculation reaction can be adjusted, and the electric flocculation reaction device can better adapt to actual requirements.

The invention provides a sewage treatment multi-objective optimization method and device and a storage medium, and relates to the field of sewage data analysis and processing.The method comprises the steps that firstly, multiple types of sewage data are collected in a time sequence mode at a specified sewage data station and preprocessed to form a data set, then a sewage prediction model is constructed based on a deep learning model, and a sewage prediction result is obtained; and inputting the data set for training, and predicting the energy consumption of the sewage treatment equipment and the effluent pollutant concentration. Then, a multi-objective optimization function is constructed, so that the total energy consumption is minimized, and the effluent pollutant concentration reaches the standard; and finally, solving the function by using a multi-objective particle swarm optimization algorithm to obtain an optimal solution set, and screening out an optimal operation parameter from the optimal solution set. According to the method, two important targets of energy consumption minimization and effluent pollutant concentration standard reaching can be considered at the same time, the relation between energy consumption and water quality can be balanced, the optimal operation parameters are screened out from the optimal solution set, and the overall performance of sewage treatment equipment is improved.

The invention discloses a high-valued graded utilization method of marine shells, and belongs to the technical field of comprehensive utilization of biological resources and preparation of functional materials. The method comprises the following steps: cleaning, air-drying and superfine grinding marine shell wastes such as abalone shells, and extracting water-soluble organic components in the marine shell wastes by adopting mild water extraction, so that the obtained extract is rich in protein, polysaccharide or small molecule peptide, has good biological activity, and can be used for preparing functional materials such as biomimetic mineralization, tissue repair and the like; extracted shell powder residues are subjected to heat treatment or chemical activation treatment and then compounded with natural polymer materials such as chitosan and sodium alginate, and the composite adsorbent which is loose in structure and large in specific surface area is prepared and can be used for removing dye, heavy metal, antibiotics and other water pollutants. According to the invention, separate utilization of organic components and inorganic framework materials in the marine shells is realized, and the method has the characteristics of environmental protection, efficient resource conversion and multifunctional application, and has a good industrial popularization prospect.

The invention relates to the technical field of water pollutant concentration detection, and discloses a water pollutant concentration detection system and method based on big data analysis, and the water pollutant concentration detection method based on big data analysis comprises the following steps: constructing a multi-level sensing network, the multi-layer sensing network comprises a fixed monitoring station layer, a water surface unmanned ship layer and an underwater robot layer; carrying out multi-modal data fusion by utilizing a knowledge constraint data assimilation algorithm to generate consistent water quality parameter estimation; a double-layer cognitive structure combining a knowledge graph and a causal model is constructed, and water pollutant propagation understanding and tracing are achieved; continuous optimization of system configuration is realized through a multi-objective reinforcement learning framework; through collaborative optimization of a multi-layer sensing network, the system realizes three-dimensional monitoring of a water body, the monitoring coverage range is expanded, and meanwhile, the high-precision detection capability is kept.

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 provides a rapid detection method for water pollutants, which comprises the following steps: removing large-particle impurities and suspended solids in a water sample to be detected to obtain a target water sample; the method comprises the following steps: synchronously detecting multiple pollutant indexes of a target water sample through a multi-source sensor array to generate an initial detection data set; performing noise filtering and baseline correction on the initial detection data set to generate a target detection data set; performing space-time dimension dynamic fusion and feature decoupling on the target detection data set to generate water quality pollutant data and dynamic risk assessment indexes; and constructing a multi-dimensional risk assessment report by adopting the water quality pollutant data and the dynamic risk assessment indexes. By adopting a dynamic gradient filtering technology, impurity interference is effectively removed, dynamic risk assessment of a time dimension is realized, the accuracy and reliability of detection in a complex water quality environment are remarkably improved, and rapid and accurate water quality pollutant detection and risk assessment are realized.

The invention relates to the technical field of water pollutant removal, in particular to a UiO-66 / sodium carboxymethyl cellulose / polyvinyl alcohol / melamine sponge composite material and a preparation method and application thereof.The preparation method comprises the steps that zirconium chloride and terephthalic acid are dissolved in an organic solvent to obtain a mixed solution, the mixed solution is transferred into a reaction kettle, and through solvothermal reaction, the UiO-66 / sodium carboxymethyl cellulose / polyvinyl alcohol / melamine sponge composite material is obtained; the preparation method comprises the following steps: preparing UiO-66 powder; putting UiO-66 powder into the sodium carboxymethyl cellulose solution, and uniformly stirring the UiO-66 powder and the sodium carboxymethyl cellulose solution to obtain a UiO-66 / CMC mixed solution; placing the UiO-66 / CMC mixed solution in a polyvinyl alcohol solution, and uniformly stirring the UiO-66 / CMC / PVA mixed solution to obtain a UiO-66 / CMC / PVA mixed solution; the preparation method comprises the following steps: dipping a melamine sponge in a UiO-66 / CMC / PVA mixed solution to obtain an adsorption saturated melamine sponge; the UiO-66 / CMC / PVA / coated MS composite material is obtained by repeatedly freezing and thawing the adsorption saturated melamine sponge for multiple times and then freeze-drying, the composite material can be used for rapidly, efficiently and selectively removing phosphate or fluorine ions and the like in water and is convenient to separate and recycle, and a new thought is provided for development of efficient water treatment adsorbent materials.

The invention relates to the technical field of pollution treatment of livestock and poultry breeding, in particular to a pollutant emission prediction and management system for a livestock and poultry farm, which comprises a data acquisition and storage unit, a data processing unit, a data processing unit and a data processing unit, and is characterized in that the data acquisition and storage unit is used for acquiring multi-source data of the farm in real time; the influence factor calculation unit obtains key influence factors influencing water quality change and malodorous gas based on production data and facility operation data of the farm; the model prediction analysis unit generates a predicted value of pollutant emission by using a dynamic multi-dimensional pollutant emission prediction model, and key influence factors are introduced in the prediction process for correction; and the management decision-making unit judges the early warning level and generates a control instruction according to the early warning level. According to the system, accurate prediction of emission of malodorous gas and water pollutants is realized by constructing a dynamic multi-dimensional pollutant emission prediction model, and meanwhile, the system not only prevents excessive emission of pollutants in advance, but also is deeply integrated with aquaculture production management to guide actual aquaculture operation.

The invention belongs to the field of high-salt organic wastewater treatment, and particularly relates to a shale gas development high-salt organic wastewater co-treatment method, which comprises treatment units such as coagulation and precipitation integration, electrochemical catalytic oxidation complex breaking, two-stage reverse osmosis gradient desalination, low-temperature MVR evaporation-crystal form regulation and control and the like. The method provided by the invention can realize optimized coupling of process parameters of each treatment unit and high-efficiency collaboration of material flow / energy flow, and realizes low-carbon, economic and high-efficiency standard treatment of shale gas high-salt organic wastewater and resource comprehensive utilization of crystalline salt; and the quality of the treated effluent meets the direct emission limit value requirement in table 1 in Discharge Standard of Water Pollutants for Shale Gas Exploitation in Sichuan Province (DB51 / 3203-2024). The method is also suitable for treating shale gas production wastewater with similar water quality characteristics, and has good popularization and application prospects.

The invention discloses a pollution risk assessment method, a pollution risk assessment device, pollution risk assessment equipment and a computer readable storage medium for an underground water environment, and the method can accurately simulate the migration and diffusion of pollutants in underground water through a constructed underground water pollutant migration model. And calculating exposure by combining sensitive receptor distribution, calculating risk indexes and probabilities according to toxicological parameters, and finally determining risk levels. Through application of the series of models, the accuracy and scientificity of risk assessment are greatly improved, a reliable basis is provided for groundwater pollution prevention, control and treatment, and potential environmental risks are effectively reduced.

The invention discloses a method for preparing a porous carbon material by recycling coal gasification slag and semi-coke wastewater, which comprises the following steps: by taking coal gasification fine slag as a carrier and semi-coke wastewater as a phenol source, carrying out flotation-acid leaching modification on the fine slag to purify a carbon-rich component and optimize the surface adsorption activity of the carbon-rich component; then fully adsorbing phenolic substances in the wastewater by utilizing the modified slag body; introducing a composite aldehyde cross-linking agent, and initiating an in-situ phenolic aldehyde polymerization reaction to generate a composite precursor; the precursor is subjected to high-temperature carbonization and alkali activation pore forming, and finally the porous carbon material with the characteristics of high specific surface area, rich graded pores and low ash content is prepared. According to the process, full-amount collaborative recycling of the two wastes is achieved, and the process is green and free of secondary pollution. The obtained material is high in carbon content and rich in defect structure and surface functional groups, shows excellent adsorption capacity and catalytic carrier performance, can be widely applied to the fields of deep purification of water pollutants, adsorption of volatile organic compounds, energy catalysis and the like, and has remarkable environmental protection benefits and resource economic values.

The invention discloses a sewage treatment method and a sewage treatment system.The sewage treatment method comprises the steps that at each moment, a segmented affine exogenous autoregression model predicts the effluent pollutant concentration and energy consumption based on past sewage treatment parameters; the balance among the pollutant removal amount, the energy consumption cost and the emission cost is adjusted based on economic model predictive control; and selecting the optimal control input at the current moment. Therefore, the sewage treatment system is divided into a plurality of linear subsystems through the segmented affine exogenous autoregression model, each linear subsystem is a typical working condition, one linear subsystem corresponds to one sub-model in the segmented affine exogenous autoregression model, the working conditions are judged according to relevant parameters, detected in real time, of sewage treatment, and the working conditions are judged according to the relevant parameters, detected in real time, of the sewage treatment. And then selectively and dynamically activating the sub-model corresponding to the working condition, predicting the pollutant concentration and the energy consumption, and on this basis, predicting and generating the optimal control input at the current moment based on an economic model.

The invention discloses a water pollutant adsorbent. The water pollutant adsorbent is characterized by comprising a chelate prepared by reacting manganese dioxide with an EDTA-2Na (Ethylene Diamine Tetraacetic Acid-2Na) solution. The invention also discloses a preparation method and a production system of the water pollutant adsorbent. The preparation method of the water pollutant adsorbent comprises the following steps: 1, crushing and grinding electrolytic manganese anode mud; 2, removing impurities in the electrolytic manganese anode slime to obtain filter residues; 3, cleaning the filter residues, and carrying out solid-liquid separation to obtain an intermediate product; and 4, chelating modification. The water pollutant adsorbent production system comprises a reaction kettle. According to the technical scheme, the manganese dioxide raw material can be effectively utilized to prepare the pollutant adsorption and treatment material, and high-valued treatment of the electrolytic manganese anode mud solid waste is effectively achieved.

The invention relates to the technical field of water body pollution monitoring, in particular to a multispectral image fused water body pollutant accurate recognition system, which comprises a data acquisition module, a cloud processing module, a boundary processing module, a pollution recognition module, a diffusion prediction module and a visualization module, the system constructs sub-pixel representation of a water pollutant boundary by using a differential geometry manifold theory, and realizes high-precision pollutant boundary description through a multi-scale analysis and curvature flow optimization technology; enhancing pollutant characteristic expression by adopting multispectral image fusion and an optimal wave band selection technology; using a support vector machine model to accurately identify various pollutant types such as oil films, oil spots, algae blooms and the like; based on a boundary fine description result and a pollutant type identification result, the diffusion trend of pollutants is accurately predicted in combination with historical flow, wind direction and wind speed data, and the system improves the water pollutant boundary identification precision and enhances the identification capability of complex boundary forms and low-contrast regions.

The invention discloses a magnetic foaming freeze-dried modified chitosan material as well as a preparation method and application thereof, and belongs to the field of underground water treatment in coal mine areas. The magnetic foaming freeze-drying modified chitosan material is obtained by combining ferroferric oxide modification, sodium dodecyl sulfate foaming modification and instant freezing modification, and the magnetic foaming freeze-drying modified chitosan material is of a modified chitosan microsphere structure suitable for adsorption of mine water pollutants. And the adsorbent can stably exist in neutral, alkaline and high-salt mine water solutions, and has relatively good removal capability on metal ions such as iron, manganese and calcium in the mine water.

The invention discloses a pre-training model and multi-source coding feature fusion-based water pollutant molecular property prediction method and system, and relates to the technical field of environmental science and artificial intelligence crossing. Comprising the steps of collecting pollutant data; the collected pollutant data is preprocessed; taking SMILES as a molecular input basis, and extracting molecular features; according to the molecular features, feature vectors are obtained from an encoder and then input to a vector interaction module for feature fusion; and embedding the comprehensive molecules obtained after feature fusion into an expert mixed structure module to obtain comprehensive representation of an expert mechanism, inputting the comprehensive representation of the expert mechanism into a preset prediction head, and completing prediction of molecular properties through the prediction head. According to the method, the molecular language model features, the molecular graph neural network features and the molecular descriptor features are integrated, and feature fusion is carried out by utilizing an attention mechanism and residual connection, so that high-precision prediction of the molecular properties of pollutants is realized.

The invention discloses a heterojunction composite material and a preparation method and application thereof, and belongs to the technical field of catalysts, and the preparation method comprises the following steps: dispersing LaFeO3 and g-C3N4 in water, adding CuCl2, uniformly stirring, adding a sodium citrate aqueous solution, continuously stirring for 12-24 hours, centrifuging, washing and drying to obtain the heterojunction composite material; the mass ratio of the LaFeO3 to the g-C3N4 to the CuCl2 is (10 to 30) to (70 to 90) to (10 to 30). According to the invention, two narrow-band gap semiconductors (LaFeO3 and Cu2O) and a wide-band gap semiconductor (g-C3N4) are compounded to form the composite material with the double-heterojunction structure. As a photocatalyst, the material can be effectively applied to pollution control, and has excellent capabilities of removing organic water pollutants and air pollutants and sterilizing.

The invention relates to a water pollutant collection technology, and aims to provide a device for filtering and screening micro-plastics in a water body in a multi-stage manner. Comprising an inlet water pre-separation unit, a multi-stage filtering and screening unit, an automatic membrane changing unit and a control unit, the multi-stage filtering and screening unit comprises a plurality of filtering and screening assemblies which are connected in sequence and are of the same structure, an elastic corrugated pipe and a second water suction pump. The automatic film changing unit comprises a plurality of film changing assemblies which are the same in structure and are sequentially connected through a central rotating shaft, and a second stepping motor is arranged at the tail end of the central rotating shaft; and the membrane exchange assemblies and the filtering and screening assemblies are arranged in a one-to-one correspondence manner. According to the invention, the functions of automatic film changing control, multi-stage screening and self-cleaning are integrated, and the problem of filter screen blockage can be effectively solved; while the collection efficiency is improved, precise separation and continuous treatment of micro-plastics with different particle sizes are realized; through the control unit, mutual cooperation of the rotary membrane replacing assembly and the telescopic filtering and screening assembly is achieved, and automatic replacement of the filter membrane assembly is achieved.

A water pollutant detection method based on absorption-electrochemical characteristic fusion belongs to the technical field of environmental monitoring, and comprises the following steps: respectively acquiring absorption spectrum data and current-potential data through a spectrometer and an electrochemical workstation, highlighting key peak position characteristics by using an attention mechanism, and inhibiting redundancy and noise interference; extracting local and global features of the two types of signals by using a convolutional neural network, and splicing the local and global features to obtain joint representation; and cross-modal feature fusion is realized through a dynamic routing mechanism of the capsule network, and a spatial relationship and a hierarchical structure between features are captured. And finally, constructing a classification and regression double-branch output structure to realize pollutant type identification and concentration prediction. Compared with an existing single detection technology, the detection sensitivity of the low-concentration pollutants can be remarkably improved, the distinguishing problem of peak value overlapping is effectively solved, the selectivity and robustness of the system are enhanced, and therefore high-precision integrated detection of the water pollutants is achieved.

The invention discloses a preparation method of a zero-valent iron reduction material with micro-nano size and water stability, and belongs to the field of underground water pollutant degradation materials. The method comprises the following steps: 1) uniformly mixing micron-sized zero-valent iron powder and hexadecyl trimethoxy silane, and carrying out mechanical ball milling; and 2) cleaning the material with a cleaning agent, and drying to obtain the zero-valent iron reduction material with micro-nano size and water stability. According to the preparation method, a mechanical ball milling method and a hexadecyl trimethoxy silane surface modification method are utilized to cooperate, so that micro-nano size and surface hydrophobicity of the zero-valent iron are stabilized, agglomeration and passivation of the zero-valent iron in water are inhibited, and the reduction activity and water stability of the zero-valent iron material are improved; the reducing capacity of the material on pollutants such as halogenated hydrocarbon and heavy metal in water is remarkably improved, the material can be kept stable in water for a long time, the technical problems that the micro-nano zero-valent iron reducing material is prone to inactivation and difficult to store are solved, and waste of material resources can be reduced.