543 results about "Pollution prevention" patented technology

The invention relates to the technical field of environment monitoring, and discloses a water ecological pollution diffusion prediction method and system based on big data, and the method comprises the steps: constructing a sensing network of a water environment, obtaining real-time water environment data, carrying out the preprocessing of the data through an edge calculation node, and synchronously transmitting the data to a central platform; based on historical data and real-time water body environment data, establishing a dynamic prediction model of pollutant boundary condition parameters; according to the dynamic boundary condition parameters, constructing a pollutant propagation atlas, analyzing the spatial and temporal distribution trend of pollutant concentration and identifying the position of a pollution source; and according to a pollution source position identification result, executing aging prediction, and triggering a pollution early warning response in combination with a set threshold value. The space coverage rate and timeliness of pollution monitoring are improved, the intelligence and credibility of pollution tracking are enhanced, and the intelligent and scientific level of water ecological environment pollution prevention and control is improved.

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 belongs to the field of pollution prevention and control data processing, and particularly relates to a laboratory instrument data automatic acquisition and quality tracing system and a laboratory instrument data automatic acquisition and quality tracing method. A distributed search traceability mapping space is constructed through the storage mapping module to realize space-time-semantic composite indexing and classification detection of data, and a causal reasoning model of the quality judgment module is used for performing anomaly judgment; a reverse Hash traceability mechanism is innovatively designed, an index-traceability node graph and a segmented Hash heterogeneous node anchoring strategy are combined, Hash head, body and tail fragments are stored in three types of nodes of acquisition, storage and detection, and tamper-proof traceability of abnormal data and dynamic optimization of acquisition parameters are realized through cross-node aggregation verification; according to the invention, the problems of low data credibility and poor abnormal traceability efficiency in ecological environment monitoring are solved, and full-chain closed-loop management of data acquisition-analysis-traceability-acquisition configuration adjustment is supported.

The invention discloses a reservoir water regimen analysis method and system based on artificial intelligence, and the method comprises the steps: collecting original signals from multi-source monitoring indexes, such as water level, flow, rainfall and water quality, carrying out the standardized conversion through employing distributed calculation nodes, and forming a unified multi-source data set; based on this, using a feature extraction network to fuse upstream rainfall and reservoir flow, extracting space-time correlation features, and determining a short-term water level change trend; historical water quality abnormal data are integrated through a sequence prediction network, a time sequence is modeled, and potential pollution risks are judged; when the risk exceeds a threshold value, dynamically adjusting the weight of the prediction model, and generating an optimized water regimen simulation scene; finally, resource scheduling logic is fused, multi-scene risks are evaluated, and an optimization management strategy is output. Through deep fusion of spatial-temporal feature extraction and dynamic prediction, accurate water regimen prediction and flood control water supply decision support are realized, and the water resource management efficiency and the pollution prevention and control capability are improved.

The invention relates to the technical field of environmental pollutant detection, in particular to a straw open-air incineration pollutant emission quantitative method based on multi-source data fusion, which comprises the following steps: based on air pollutant monitoring data, calling a sensor network to obtain PM2.5, CO and NOX concentrations, analyzing fire point heat radiation intensity, collecting meteorological data, and calculating the concentration of PM2.5, CO and NOX; and obtaining a pollution source data set by combining the time sequence change of the fire points and the meteorological parameters. By integrating an environment monitoring sensor, satellite remote sensing and ground meteorological data, the comprehensiveness and accuracy of pollution source monitoring are improved, the combination of fire point intensity and pollutant concentration time sequence data is optimized, the evaluation of fire point and pollution hot spot areas and the comprehensive analysis of wind directions and meteorological conditions are optimized, the accuracy of a pollutant diffusion model is improved, and the pollution source diffusion efficiency is improved. The pollutant release amount is dynamically adjusted, and the diffusion model is corrected by using a geographic information system, so that the scientificity of pollution prediction and emission intensity evaluation is enhanced, and more accurate pollution prevention and control decision support is provided.

The invention belongs to the technical field of farmland tail water pollution load analysis and evaluation, particularly relates to a farmland tail water pollution load analysis and evaluation method, and aims to overcome the obvious defects of an existing monitoring and evaluation method in the aspects of monitoring point layout, index coverage, data processing, analysis depth and the like. In order to solve the problems that farmland tail water pollution load analysis and evaluation cannot meet accurate and dynamic farmland tail water pollution load analysis and evaluation requirements and pollution prevention and control decisions are difficult to effectively support in the prior art, the invention provides the following scheme: the method comprises the following steps: S1, carrying out multi-source acquisition on farmland information data, and carrying out fusion processing; s2, setting a fixed sampling unit and a movable sampling unit according to farmland information setting; according to the method, multi-source data such as farmland basic information, agricultural production activity data, meteorological data and water quality monitoring data are comprehensively considered, and comprehensive and accurate quantification and evaluation of farmland tail water pollution load are realized through a data preprocessing and fusion technology.

The invention discloses a construction site dust fall and pollution prevention and control method and system based on multi-modal perception, and relates to the technical field of construction management, and the method comprises the steps: collecting PM data at a boundary in real time through a boundary monitoring device preset at the boundary of a construction site, and meanwhile, using an unmanned plane carrying the monitoring device to monitor the PM data at the boundary; performing flight monitoring on the interior of the construction site according to a preset route, and collecting PM data of different areas of the site; performing preliminary analysis on the multi-modal sensing data in real time by using an edge calculation module, and identifying dust abnormal conditions; and the data processing center analyzes a current pollution scene of the construction site, matches an optimal dust falling strategy for the current pollution scene, controls surrounding dust falling equipment to perform dust falling operation, constructs a self-organizing communication network among the dust falling equipment, and adjusts a dust falling operation plan by using dust falling feedback information. According to the invention, real-time data collected by the boundary monitoring equipment and the unmanned aerial vehicle are fused, and environment parameters and construction working conditions are combined, so that precise regulation and control of the dust falling equipment are realized.

The invention relates to the technical field of environment monitoring, in particular to an underground water monitoring and early warning method and system based on multi-source data fusion, and the method comprises the following steps: obtaining water quality, flow velocity, temperature and pH value data, adjusting the collection frequency, verifying the state of a sensor, forming a water quality and geologic feature data set, analyzing rainfall, air temperature, permeability and water flow dynamic state, and obtaining a water quality and geologic feature data set. And generating a seepage trend, identifying a pollutant diffusion path, range and main path, evaluating a diffusion rate and influence, and generating a pollution diffusion early warning level in combination with permeability and risk standards. According to the invention, through fusion analysis of multi-source data, determination of the correlation between an underground water flowing mode and water quality change, timely capturing of the influence of meteorological change on underground water, accurate evaluation of pollutant diffusion path, rate and influence range, improvement of timeliness and accuracy of pollution early warning, and improvement of monitoring response speed through automatic data processing. And timely and accurate decision support is provided for groundwater resource management and pollution control.

The invention relates to the technical field of atmospheric dust pollution prevention and environmental protection, and discloses a multi-objective optimization layout method for dust monitoring points of a bulk cargo port, which comprises the following steps: processing historical meteorological data and port geographic information, and calculating the comprehensive evaluation concentration of each candidate grid point in combination with a pollutant diffusion model; constructing a multi-target nonlinear mixed integer programming model taking maximization of environment sensitive point coverage and minimization of concentration interpolation deviation as target functions, wherein the model comprehensively considers multiple reality constraints; solving the model by adopting an improved genetic algorithm to obtain an optimal solution set capable of forming tradeoff among different targets; and carrying out quantitative evaluation on the solution set through preset monitoring area coverage rate and monitoring accuracy indexes, and determining an optimal monitoring point position layout scheme. According to the invention, a scientific and quantitative optimized layout scheme can be provided for bulk cargo port dust monitoring, and the reliability and spatial representativeness of a monitoring network are improved.

The invention belongs to the technical field of tool magazines, particularly relates to a disc type tool magazine with a chain type radial servo chain, and provides the following scheme aiming at the problems that when a tool sleeve is replaced, cuttings and cooling liquid can be carried to enter movable parts such as a locking mechanism in the tool sleeve, so that the mechanism is inflexible in action and blocked, and normal grabbing, releasing and locking of the tool are influenced. Comprising a base body, one side of the base body is fixedly connected with a disc, an index plate is arranged on the base body, and an assembly part is arranged on one side of the base body; and the driving circular pipe is arranged on one side of the assembly part. According to the disc type tool magazine with the chain type radial servo chain, the problem of mechanism clamping stagnation caused by invasion of cuttings and cooling liquid is fundamentally solved through the pre-cleaning module and the positioning auxiliary module, pollution prevention is deeply integrated into the tool changing process, the high tool changing efficiency is maintained while the cleaning effect is ensured, and the tool changing efficiency is improved. And the reliability and the service life of the tool magazine in high-speed machining are remarkably improved.

The invention discloses a dust suppression method and system for railway track dry bulk cargo loading. The method comprises the steps that if it is detected that loading operation is started on an iron road trunk line, an area to be subjected to dust suppression is determined based on loading operation field data; acquiring environment information corresponding to the region to be subjected to dust suppression, wherein the environment information comprises wind direction information; determining a to-be-loaded article based on the loading field operation data, and determining the moisture content corresponding to the to-be-loaded article; and a control strategy corresponding to the spraying system is determined based on the wind direction information, the water content and the area corresponding to the area to be subjected to dust suppression, and operation parameters corresponding to the spraying system are adjusted based on the control strategy so as to perform dust suppression treatment on the loading operation process. According to the invention, accurate treatment of railway track loading flying dust pollution is realized, limitation of traditional fixed dust suppression is broken through, and pollution prevention and control efficiency and resource utilization efficiency are remarkably improved.

The invention relates to the field of water environment pollution detection and analysis, in particular to a water environment pollution detection and analysis system and method based on the Internet of Things, and solves the problems of sampling redundancy, missing detection, high-dimensional data over-fitting, difficulty in traceability and early warning lag in traditional detection. The system comprises a monitoring acquisition module, a water quality anomaly detection module, a pollution tracing module, a pollution early warning module and a database. The monitoring acquisition module adopts chaotic adaptive sampling to adjust sensor frequency, and entropy optimization water quality data is obtained by combining permutation entropy and collaborative filtering denoising; the water quality anomaly detection comprises the following steps: standardizing data into high-dimensional point clouds, calculating a Betti number and a non-equilibrium state entropy, and fusing to generate a comprehensive pollution topological entropy index; according to pollution traceability, a dynamic graph and a diffusion kernel matrix are constructed by using GNN, and the optimal source intensity is solved through quantum annealing; the range is predicted through a diffusion equation for early warning, and information is integrated to generate a report to be pushed to users. The method corresponds to a module flow and provides support for pollution prevention and control.

The invention discloses a microplastic transportation path prediction method, device and equipment based on a complex hydrodynamic environment and a medium, and relates to the technical field of environment monitoring and water pollution governance, and the method comprises the steps: integrating a watershed digital elevation model, a river channel vector diagram, microplastic attributes and real-time hydrological data; a dynamic adjacency matrix is used for capturing water flow direction changes, multi-modal feature fusion is combined for modeling micro-plastic physical attributes and topographic resistance, the problem of monitoring data scarcity is solved through a cross-basin transfer learning strategy, a micro-plastic transfer path is accurately predicted, high-precision simulation of micro-plastic transfer in a complex hydrodynamic environment is achieved, and high-precision simulation of micro-plastic transfer in a complex hydrodynamic environment is achieved. The pollution prevention and control efficiency is improved.

The invention relates to the technical field of wastewater treatment in the water treatment technology, in particular to a wastewater treatment multistage dynamic quantification control system based on result feedback, which comprises a storage module, an identification module, a quantification module and an execution module, the storage module stores a causal chain in a reaction process, the identification module identifies a matching state of a current operation parameter and the causal chain and enables the quantification module to determine a risk index, and the execution module performs control optimization to execute corresponding measures based on the determined risk index. Tracking intervention from a pollution source to a derivation phenomenon is realized, a pollution migration problem implied in wastewater treatment is converted into an identification item of quantitative operation, and limitation of traditional single-point identification control is broken through through sequential logic verification and a multi-dimensional matching degree fusion mechanism. The accuracy of membrane pollution prevention and control and the resource utilization efficiency are improved while the process continuity is guaranteed, and a closed-loop control normal form of traceability pre-judgment dynamic quantification grading interception is formed.

The invention discloses a flood season river pollution early warning system and method, and relates to the technical field of environmental monitoring, the system comprises a microbial electrochemical sensor module, a current monitoring and data analysis module, a multistage early warning trigger module, a chemical detection auxiliary module, and a data transmission and storage module, through the microbial electrochemical sensor network, water samples on the surface layer, the middle layer and the bottom layer of a river can be collected at the same time, the toxicity index of composite pollutants is analyzed in real time by means of metabolic activity changes of electroactive flora, the comprehensiveness of monitoring of the river pollution condition is greatly improved, meanwhile, the current pulse frequency is monitored in real time, and the toxicity index is rapidly analyzed; and by matching with a preset accurate threshold value of the early warning trigger module, an early warning mechanism can be quickly triggered once the pollution condition reaches an early warning standard, so that the early warning timeliness is greatly improved, the time interval from pollution occurrence to early warning sending is shortened, and precious time is won for taking pollution prevention and control measures in time.

The utility model provides a dust removal cleaning device for preventing and treating atmospheric environmental pollution, and relates to the field of atmospheric environmental pollution prevention and treatment. The dust removal cleaning device for atmospheric environmental pollution prevention and control comprises a filter bin, an air inlet is formed in the front end of the filter bin, an air suction port is formed in the rear end of the filter bin, the bottom of the filter bin is in through connection with a liquid drainage bin, and a fixing frame is rotationally connected to the center position in the filter bin. When the dust removal and cleaning device for atmospheric environmental pollution prevention and control is used, a filter bin filters air through an air inlet and an air suction port, filtered impurities are attached to the surface of the front end of a filter plate, at the moment, a servo motor drives a power wheel to rotate by a circle, the power wheel drives an adjusting wheel to rotate by 90 degrees, and the adjusting wheel drives a fixing frame to rotate; the fixing frame drives the filter plate to rotate, the side, attached with impurities, of the filter plate faces downwards, at the moment, the filter plate is in a horizontal state, meanwhile, the fixing frame drives the baffle to block the air inlet and the air suction port of the filter bin, and the waste gas blocking device has the advantage of blocking waste gas.

The invention discloses a soil pollution diffusion prediction method based on differential evolution, and relates to the technical field of soil pollution control, and the method comprises the steps of collecting soil sensing data in real time, and uploading the soil sensing data to a data center. Real-time sensing data are compared and calibrated, sensing data errors caused by environmental factors are effectively reduced, data input into a model are more accurate and reliable, meanwhile, model parameters are optimized and solved by combining differential evolution and a particle swarm optimization algorithm, the differential evolution is used for global optimization to find a proper parameter combination, and the accuracy of the model parameters is improved. Particle swarm optimization performs local fine adjustment based on a differential evolution result, and the two are alternately performed, so that the accuracy of soil pollution diffusion prediction is greatly improved, the diffusion trend of pollutants in soil can be more accurately grasped, and a more reliable basis is provided for ecological environment management and human health protection.

The invention provides a fusion method of ground station monitoring and satellite remote sensing inversion PM2.5 data, and relates to the technical field of PM2.5 pollution prevention and control. Ground station data and satellite remote sensing data are subjected to time matching and space matching and then are fused by using a universal Kriging method to obtain a high-precision and large-area coverage PM2.5 product. The PM2.5 data spatial correlation is considered, so that the fusion result is closer to reality, the calculation complexity is reduced, and meanwhile, the reliability of the fusion result can be judged by giving an error after data fusion. According to the method, the limitations of insufficient spatial consideration and high calculation complexity of a traditional method are made up, and the PM2.5 product can be used for pollution process analysis, climate change and other researches.

The invention relates to the technical field of test numerical simulation, and particularly discloses a numerical simulation detection system based on an underground water hydrogeological test and a cloud platform, and the system comprises a multi-data fusion module which fuses multi-source data through a space-time registration algorithm, and constructs a three-dimensional geological model; the coupling simulation module performs non-Darcy seepage, solute transport and heat transfer coupling analysis on the model to obtain a coupling simulation factor matrix; the diffusion reasoning module determines the current pollution plume distribution and reasones the dynamic diffusion data of the current pollution plume distribution in combination with the model and the matrix; the seepage analysis module determines a multi-scale seepage structure and predicts multi-medium layer water volume dynamic exchange data; the model building module generates a hydrogeological simulation dynamic model based on the data; the prediction decision module combines an AI algorithm and a model to obtain a hydrogeological evolution prediction decision result; groundwater geology research, pollution prevention and control and water resource management are assisted, and intelligent prediction decision support is provided.

The invention belongs to the technical field of crop pollution prevention, and particularly relates to a rice heavy metal adsorption and isolation method based on iron agent regulation and control. According to the method, the iron agent is applied to the polluted rice field soil to induce the soil-rhizosphere interface to form an iron film, heavy metals (such as As, Cu, Pb and Cd) are fixed by virtue of adsorption and complexing effects of the iron agent, and migration of the heavy metals to rice roots is reduced, so that accumulation of the heavy metals at edible parts (leaves and ears) of the rice is reduced; the tolerance of the rice in a polluted environment is enhanced; and the risk of heavy metals in a food chain is reduced. Experiments show; through treatment of an iron film formed by a certain iron-based concentration, accumulation of the heavy metals in the rice leaves can be remarkably reduced, and the accumulation amount of the heavy metals in the rice leaves is far lower than the accumulation amount (1 / 40-1 / 120) of the heavy metals in rice roots. The invention provides an effective solution for farmland soil remediation and crop safety production.

The utility model provides a self-service tableware distribution device which comprises a housing and at least one set of stock bin mechanism arranged in the housing, the stock bin mechanism comprises a tableware containing bin and a tableware blanking bin, the tableware containing bin is used for stacking and storing tableware, and the tableware blanking bin is sequentially provided with an upper mold, a middle mold and a lower mold. The three parts are respectively provided with channels for controlling the sequential falling of tableware; in the initial state, the middle mold is aligned with the upper mold and staggered with the lower mold, and when a user presses a switch or pulls tableware, channels between the molds are in linkage alignment, and a single piece of tableware is released to a taking position; the tableware head triggers the linkage assembly in the taking process, the middle mold is driven to reset, and preparation of the next piece of tableware is achieved. The device provided by the utility model is reasonable in structure, does not need to be electrically driven, completes tableware distribution by means of mechanical linkage, has the advantages of automatic control, single-support taking, sequential supply, pollution prevention and the like, and is suitable for cafeteria, shared kitchens, enterprise canteens and other scenes.

The invention relates to the field of atmospheric dust pollution prevention and environmental protection, and discloses a wharf dust emission monitoring grid clustering point distribution method based on uncertainty quantization, which comprises the following steps of: a, performing dust diffusion simulation by utilizing a pollutant diffusion model, and determining a dust comprehensive evaluation concentration; b, performing comprehensive evaluation and preliminary screening based on fuzzy evaluation to obtain candidate point distribution grids; c, the candidate point distribution grids are clustered, and the candidate point distribution grids are merged into categories; and step d, determining a final dust emission monitoring point according to the category. According to the method, the objective dust comprehensive evaluation concentration is calculated by introducing the GAUSSION diffusion model based on various meteorological scenes and occurrence probabilities, and subjective judgment depending on historical experience is replaced; and a fuzzy evaluation technology and an entropy weight method are utilized to carry out mathematical quantification on various uncertain factors, so that interference of human factors can be eliminated fundamentally, and a point distribution result is more reliable and representative.

The invention relates to the technical field of water supply network pollution monitoring, in particular to a water supply network water pollution rapid detection method. The method comprises the following steps: acquiring water supply pipe network operation data, extracting pipe network structure information, detecting a water flow direction, and constructing a water supply pipe network topological graph; on the basis of the topological graph and the operation demand data, the negative pressure overload condition of the pipe network is judged, the pipeline damage condition is estimated, then the conditions of external pollutant invasion and hydraulic unbalance are analyzed, and the pollutant backflow trend and the water flow retention area are determined; the conditions of microorganism breeding and internal water quality deterioration are evaluated by combining a water flow retention area and a pollutant backflow trend, and tracing and positioning of a pollution source are carried out; pipe network structure adjustment, water flow regulation and control and pollution prevention and control measures are implemented according to the pollution source tracing result, and optimization treatment of the water supply pipe network is achieved; optimization treatment of the water supply pipe network is achieved through pollution monitoring of the water supply pipe network.

The invention provides a method for estimating atmospheric heavy metal environmental capacity. The method comprises the following steps: acquiring basic topographic and meteorological data of a to-be-estimated target area; determining an atmospheric heavy metal emission scheme; obtaining the day-by-day grid-by-grid heavy metal concentration of the target area in the simulation year by adopting an air quality model; and calculating to obtain a non-carcinogenic risk quotient value and a carcinogenic risk quotient value, comparing with 1 to judge whether an atmospheric heavy metal emission scheme needs to be adjusted, and obtaining the atmospheric heavy metal environmental capacity of the emission source arrangement position until the non-carcinogenic risk quotient value or the carcinogenic risk quotient value is less than 1. According to the method, pollutant types are expanded from fine particulate matters and precursors thereof to atmospheric heavy metals, constraint based on pollutant concentration is promoted to constraint of crowd health, and a reasonable environmental capacity result is obtained by utilizing iterative calculation. According to the invention, the goal of atmospheric environmental pollution prevention and control work is improved from improvement of air quality to reduction of crowd health risks, and technical support is provided for cooperative emission reduction work of various pollutants.

The invention discloses a secondary pollution prevention structure for powder bagging, and relates to the technical field of packaging equipment, the secondary pollution prevention structure comprises a discharging transfer bin, a conical bin, a dust recovery assembly and an air bag pressing assembly; the conical stock bin is fixed to the lower end of the discharging transfer bin, a discharging pipe is arranged at the output end of the conical stock bin, the dust recycling assembly comprises a shell, an exhaust pipeline and a dust suction machine, the shell is fixed to the outer walls of the conical stock bin and the discharging pipe, an air exhaust cavity is formed by the shell and the outer walls of the conical stock bin and the discharging pipe, and the dust suction machine is arranged in the air exhaust cavity. The air exhaust pipeline is communicated with the air exhaust cavity, the dust collector is connected with the end, away from the shell, of the air exhaust pipeline, the air bag pressing assembly comprises a fixing plate and an air bag, the fixing plate is arranged on the outer wall of the conical stock bin, and the air bag is fixedly arranged on one edge of the fixing plate or the outer wall of the discharging pipe. The powder bagging device can prevent powder from overflowing from a bag opening to pollute the environment during bagging.

The invention discloses a high-precision pollution tracing method based on a watershed water quality fingerprint database. Belongs to the technical field of water pollution traceability. The method comprises the steps of establishing a watershed water quality fingerprint database, establishing an enterprise sewage fingerprint database and tracing pollutants. According to the method, aiming at the characteristics of a water body environment and main characteristic pollutants thereof, the physicochemical properties of the water body environment and the main characteristic pollutants are analyzed, the main source type of the characteristic pollutants is accurately identified, the contribution degree of the characteristic pollutants is determined, a sound water body pollution source analysis technical system is established, and technical support is provided for water environment quality evaluation, water environment risk evaluation and pollutant reduction. Meanwhile, a pollution tracing result can effectively guide water pollution prevention and control work, the pertinence, scientificity and rationality of pollution prevention and control are improved, and the method is an important basis for formulating a water pollution prevention and control plan and a regional industry and energy structure adjustment scheme.

The invention provides a dangerous waste landfill leakage emergency shield blocking and co-processing method and system, and relates to the technical field of underground pollution prevention and control and environment emergency treatment. On-site monitoring data are collected under the unified space-time reference, a pollution feather envelope line and shield curtain geometry are determined based on rapid inversion, a shield tunneling machine is driven to form a waterproof curtain, functional pipe pieces are arranged, an inward flow field is established in the curtain, and the water level difference and the negative pressure level are controlled in real time. The control terminal calculates a risk evaluation and dosage flow velocity instruction set according to the monitoring data and the extraction parameter set, and issues the risk evaluation and dosage flow velocity instruction set to the grouting, extraction and agent injection system to realize synchronous operation of curtain reinforcement and in-situ chemical repair; when the risk and repair indexes reach the standard, load reduction and plugging are carried out, and long-term monitoring is carried out. According to the method, rapid sealing control, dynamic repairing and intelligent decision making of the hazardous waste leakage area are achieved, and the accuracy of emergency disposal is improved.

The utility model discloses a sewage treatment sedimentation tank for preventing and controlling environmental pollution, relates to the technical field of sewage treatment, aims to solve the technical problem that suspended solids and impurities settled at the bottom of the tank are inconvenient to clean, and comprises a tank body, a cleaning mechanism arranged in the tank body and a collecting mechanism arranged on the cleaning mechanism, a second lead screw is arranged between the mounting plates, a second motor for driving the second lead screw is arranged at the side end of each mounting plate, the cleaning mechanism comprises a cleaning box, the cleaning box is located at the bottom of the pool body, impurity inlets are formed in the two side ends of the cleaning box, and scraper buckets are installed at the positions, located at the impurity inlets, of the two side ends of the cleaning box. And a first filtering mechanism and a second filtering mechanism are symmetrically arranged in the cleaning box. The sewage treatment sedimentation tank has the advantages that a novel tank bottom cleaning structure is provided, impurities at the bottom of the tank can be filtered and intercepted in the cleaning box in the moving process of the cleaning box, and the impurities at the bottom of the sewage treatment sedimentation tank can be conveniently cleaned.

An indoor pollution prevention system includes a plurality of gas detection modules, one or more intelligent control-driving processing devices, one or more gas-exchange processing devices, and one or more indoor cleaning and filtration devices. The gas-exchange processing device includes one or more flow-guiding component and a cleaning and filtration assembly. The intelligent control-driving processing device controls the operation of the indoor cleaning and filtration device in real-time under a surveillance condition, therefore the air pollution source in the indoor space passes through the indoor cleaning and filtration device, allowing the air pollution source in the indoor space to be filtered and exchanged to become a clean air.

The invention discloses a carbon emission prediction method and device based on iTransform, and the method comprises the steps: constructing an improved data preprocessing network based on data features, and carrying out the preprocessing of carbon emission data through the data preprocessing network; on the basis of the data preprocessing network, in combination with multivariable and non-stationary data features of the data preprocessing network, selecting an adaptive converter architecture, integrating a wavelet convolution module for capturing multi-scale features of data, and introducing a frequency enhancement channel attention mechanism to serve as an improved iTransform prediction network; inputting the preprocessed carbon emission data into an improved iTransform prediction network, and outputting a carbon emission prediction value at a future moment; pollution prevention and control are assisted based on the carbon emission prediction value, and environmental pollution is reduced. The device comprises a processor and a memory. According to the method, the accuracy of carbon emission content prediction in the future and the precise CO2 emission prediction capability are guaranteed, early warning and regulation prompts can be provided for related industries, emission reduction of each industry is supported, pollution prevention and control are assisted, then environment improvement is promoted, and the pressure of carbon emission on an ecological system is relieved.