5552 results about "Effluent" patented technology

The invention provides a sewage treatment carbon source intelligent adding method, which comprises the following steps: collecting multi-parameter feed-forward and feedback signals of water inlet and an anoxic tank, constructing a dynamic model containing feed-forward compensation, model prediction control and feedback compensation, calculating the theoretical adding amount of a carbon source, inputting a predicted value and feedback parameters into an LSTM network for correction, and optimizing a network structure by a genetic algorithm. The adding amount is controlled in a closed-loop mode through a variable frequency pump, the LSTM weight is updated on the basis that the error is larger than 5%, and finally a control strategy is optimized by using an NSGA-II algorithm and integrating carbon source consumption, effluent total nitrogen and energy consumption. The dynamic self-adaptive carbon source adding method is constructed by fusing feedforward perception, LSTM prediction, feedback regulation and multi-objective optimization, so that quick response and accurate control on water quality fluctuation are realized, the denitrification efficiency and the carbon source utilization rate are improved, and the method has excellent engineering adaptability and popularization value.

The invention provides a sewage treatment plant terminal effluent carbon source quality detection and evaluation method, which realizes full-flow dynamic evaluation and regulation of carbon source quality through on-line monitoring and intelligent algorithm fusion. According to the method, an online water quality full-spectrum detector is used for collecting original spectrum data flow, and after preprocessing such as variational mode decomposition denoising and mutual information feature selection, organic matter content quantification, variation trend analysis and anomaly detection are completed in combination with algorithms such as a support vector machine and an autoregressive moving average model. An entropy weight method is introduced to dynamically adjust the weight of the evaluation model, model parameters are optimized based on a gradient descent algorithm, a process adjustment instruction is generated through reinforcement learning and fuzzy logic, and an automatic system is linked to execute regulation and control. According to the method, the problems of hysteresis and singleness of traditional offline analysis are solved, multi-dimensional real-time evaluation, abnormal quick response and process dynamic optimization of the quality of the carbon source are realized, the sewage treatment efficiency and the effluent quality stability are improved, and a technical support is provided for continuous standard reaching of the quality of the carbon source.

The invention discloses a sewage plant accurate dosing method based on multi-mode automatic machine learning, and belongs to the technical field of sewage treatment. The method comprises the following steps: acquiring historical sensing data and image data of a sewage plant; extracting key features in the image by using a YOLO visual model, fusing the key features with sensor data, and constructing a multi-modal sample data set; carrying out modeling training on the fused data by adopting an automatic machine learning framework, and constructing a'water inlet-dosing-water outlet 'prediction model; generating a reference sample data set according to an existing dosing rule; inputting the sample data into the trained prediction model to obtain predicted effluent quality data, and adjusting the dosage until the predicted effluent quality of all samples meets a water quality standard condition; and finally outputting an optimized dosing sample data set. According to the invention, precision and real-time dosing of the sewage plant can be realized, chemical waste can be effectively reduced, the treatment efficiency is improved, the cost is saved, and the water quality is ensured to stably reach the standard.

The invention discloses a system and a method for degrading organic wastewater through cooperation of hydrodynamic cavitation and plasma. The system comprises a liquid storage tank, an aeration device and a plasma rotary cavitation reactor, the plasma rotary cavitation reactor comprises a reactor shell, and the reactor shell is provided with an organic wastewater inlet and an organic wastewater outlet; the aeration device is communicated with the organic wastewater inlet; and the liquid storage tank is communicated with the aeration device. The plasma discharge technology and the hydrodynamic cavitation technology are fused, active substances such as ozone and hydroxyl radicals are generated through dielectric barrier plasma discharge, degradation of organic wastewater is enhanced in cooperation with the hydrodynamic cavitation technology, and the degradation effect of the wastewater is improved; an upper row of teeth and a lower row of teeth with opposite tooth inclination angles are arranged on the rotor, so that fluid is triggered to circularly flow between a cavitation area and a discharge area, and the gas-liquid mass transfer efficiency is further improved; by arranging the upper jet flow cavitation channel and the lower jet flow cavitation channel which are variable in inner diameter and opposite in direction, the pressure drop value when fluid flows through the channels is changed, and the cavitation effect is enhanced.

Disclosed in the present invention is a process for deeply removing fluorine from wastewater by means of an induced crystallization method in sludge backflow. The process comprises the following steps: step 1. placing lime powder and deionized water in a seed crystal reactor to prepare lime milk and at the same time putting a calcite seed crystal into the seed crystal reactor; step 2. introducing high-concentration fluorine-containing acidic wastewater into a reactor; and step 3. introducing the lime milk obtained in step 1 into the reactor in step 2 to undergo a reaction, wherein during the reaction, the pH value of the mixed solution is controlled to remain neutral. The present invention is based on a high-density sludge method (HDS process). By utilizing the HDS process, the advantages of effectively improving the sludge density, reducing the lime consumption, facilitating the operation, and enabling the water quality of an effluent to be more stable are realized. In conjunction with induced crystallization technology, an induced crystallization process in a high-density sludge backflow is formed to promote precipitation and crystallization and allow sedimentation to proceed quickly, thereby shortening the process time and overcoming the defects of traditional lime precipitation methods.

The invention discloses a stepped treatment process for multi-path recycling of oil and gas field drilling mud, which comprises the following steps: oxidizing and breaking gel of the drilling mud to scatter the mud structure, and then granulating and coagulating; then, carrying out the following gradient treatment: step 1, filtering the outlet water of granulation and coagulation, and taking the filtrate as reinjection water; step 2, carrying out nucleation granulation reaction on the filtrate obtained in the step 1, using effluent for preparing drilling fluid, and carrying out solid waste treatment on solid-phase crystal seeds and solid-phase mud cakes subjected to granulation and coagulation; and step 3, carrying out ozone flotation reaction on the effluent obtained in the step 2, wherein the effluent is used for preparing the guanidine gum fracturing fluid. According to the method, resource recycling of the waste drilling mud is achieved, the usage amount of a gel breaker in a traditional gel breaking and filter pressing technology is reduced, a filter pressing plate is omitted, the treatment efficiency in the mud recycling treatment process is improved, the treatment cost of the waste water-based drilling mud is reduced, different recycling ways can be met, and the method is suitable for popularization and application. And specific operation is flexible and changeable.

The invention provides a low-concentration chemical-physical coupling intelligent continuous porous carbon production method and system. The method comprises the following steps: pretreatment: crushing a carbon source to obtain a carbon precursor; carbonizing: heating and carbonizing the carbon precursor in a fluidized bed reactor to obtain a carbonized product; chemical activation: dipping the carbonized product in a chemical activator solution to obtain a chemical activated product, and drying the chemical activated product; physical activation: mixing a reaction gas and an inert gas as an activation gas, placing the chemical activation product in the activation gas, and performing gas activation at a preset temperature to obtain a physical activation product; and post-processing. By coupling chemical activation with physical activation, the concentration of a chemical activation reagent can be reduced, and the wastewater amount and the pollutant concentration after reaction are reduced by reducing the dosage of the reagent, so that the wastewater treatment process is simplified, the treatment agent and energy consumption is reduced, and the treatment cost is reduced.

The invention discloses a process and system for recovering phosphorus and fluorine from ardealite leachate, which comprises the following steps: feeding the ardealite leachate into an induced crystallization reactor for induced crystallization, discharging generated large-particle fluorapatite crystals from a crystal discharge port at the bottom of the induced crystallization reactor, and collecting and recycling; aluminum hydroxide flocs and fine-particle fluorapatite crystals enter a cyclone separator along with the effluent, the fine-particle fluorapatite crystals are separated and then flow back to the induced crystallization reactor, the aluminum hydroxide flocs form precipitates in the flocculation sedimentation tank through flocculation to be removed, and the effluent of the flocculation sedimentation tank enters a multi-stage treatment system. According to the method disclosed by the invention, fluorine and phosphorus in the phosphogypsum leachate are recovered together, the recovered fluorapatite finished product is high in purity and can be recycled, and the amount of chemical sludge is also greatly reduced, so that the treatment cost of the sludge is reduced.

The invention discloses a perchlorate wastewater treatment method which comprises the following steps: discharging perchlorate wastewater into an adjusting tank, and adjusting and buffering water quality in the adjusting tank; discharging the adjusted wastewater into a coagulating basin, and adding a coagulant to react with suspended solids in the wastewater; feeding the wastewater subjected to the coagulation reaction into a sedimentation tank, and completing solid-liquid separation in the sedimentation tank; discharging the precipitate, and enabling the treated wastewater to enter a microbial catalysis tank; perchlorate in the treated wastewater is subjected to biodegradation in a microbial catalysis tank; carrying out MBR (Membrane Biological Reactor) treatment on the wastewater subjected to biodegradation, intercepting microorganisms in the wastewater in a biological catalysis tank, and discharging the wastewater which does not contain the microorganisms and is subjected to biodegradation into an RO (Reverse Osmosis) membrane treatment device; the wastewater is subjected to reverse osmosis treatment at the RO membrane treatment device, reverse osmosis concentrated water is conveyed to the biological catalysis tank, and reverse osmosis fresh water is conveyed back to the water purification tank. The biological enzyme catalysis and membrane separation method is adopted, so that the perchlorate wastewater can be discharged after reaching the standard, and the treatment process is efficient, convenient and low in cost.

The invention relates to the technical field of ammonia-nitrogen wastewater degradation, in particular to a deamination reactor optimization method based on CFD and BP neural networks. The method comprises the following steps: performing three-dimensional modeling according to geometric parameters of a deamination reactor, and obtaining a sample set; training a neural network through the sample set; and predicting the cavitation volume fraction and length in the deamination reactor by using a neural network. According to the deamination reactor optimization method based on the CFD and the BP neural network, the cavitation intensity of the deamination reactor is predicted based on a CFD numerical simulation result in combination with the neural network. CFD numerical simulation has the defects of low simulation speed, tedious operation steps and large workload, the cavitation intensity in the device with different parameters is calculated by constructing a neural network model, the amount of information to be processed is large, the calculation speed is high, complex problems can be rapidly processed, and the calculation efficiency is improved.

The invention discloses a dynamic optimization setting method and system for process parameters of a biological reaction tank of a sewage treatment plant based on machine learning. The method comprises the following steps: S1, data acquisition; s2, data integration and preprocessing; s3, establishing an effluent quality and concentration simulation prediction matrix; s4, carrying out model fusion; and S5, carrying out dynamic optimization setting on the technological parameters of the biological reaction tank based on the effluent quality simulation prediction model matrix established in the steps S1 to S4. The method comprises the following steps: firstly, establishing an outlet water quality high-precision simulation prediction model matrix, performing setting optimization on process parameters of a green pool and a reverse pool by adopting a particle swarm algorithm according to the model matrix, and finally obtaining process parameter set values of a future operation period; the advanced data analysis technology is fully utilized, the operation efficiency and effect of the sewage treatment plant are improved through the steps of collecting, processing, predicting, optimizing and the like, and energy conservation and consumption reduction are achieved on the premise that it is guaranteed that the effluent of the sewage treatment plant stably reaches the standard.

The invention discloses a gradient optimization control method for an aeration system of a sewage plant. The gradient optimization control method comprises the following steps: S1, acquiring key monitoring multi-source data of the aeration system of the sewage plant in real time through an online sensor; s2, setting a security threshold value of each monitoring data to form a security constraint condition; s3, taking unit nitrogen removal energy consumption minimization as an optimization target, and constructing a comprehensive loss function fusing an energy consumption item and a water quality deviation item; s4, iteratively updating the air volume of the aeration system by adopting a self-adaptive gradient algorithm; s5, the optimized and updated air volume is issued to the aeration equipment to be executed, and water quality data and energy consumption data after execution are collected in real time, a control effect is calculated, an award signal is generated, and the award signal serves as feedback to be input into an optimization module; and S6, dynamically adjusting key parameters including the learning rate and the gradient threshold according to a feedback result. According to the invention, the energy consumption can be effectively reduced and the control precision can be improved while ensuring that the effluent stably reaches the standard, and the stable operation of the aeration system of the sewage plant under a complex working condition is ensured.

The invention discloses a sewage plant total phosphorus concentration prediction method based on multiple machine learning models and a control system, and belongs to the field of environmental monitoring and treatment. The method comprises the following steps: automatically collecting detection data of a sewage plant, and generating a time sequence data set through intelligent preprocessing; according to the method, a total phosphorus concentration prediction model is constructed by adopting multiple machine learning algorithms, a reference prediction model is automatically selected through evaluation indexes, hyper-parameter tuning is performed by utilizing a swarm intelligence optimization method, and an optimized high-performance prediction model is obtained. The model is deployed to a real-time monitoring system, and through integration with a PLC and monitoring hardware, high-frequency prediction and dynamic regulation and control closed loop are realized; and continuously optimizing model parameters and a regulation and control strategy by returning deviation information to form a'prediction-control-optimization 'closed loop. According to the method, the effluent total phosphorus concentration prediction precision and regulation efficiency are remarkably improved, the agent adding cost is reduced, and the intelligent level of a sewage treatment system is improved.

The invention belongs to the technical field of cutting fluid wastewater treatment supervision, and particularly relates to a cutting fluid wastewater treatment system for machine tool accessory processing, which comprises a wastewater step-by-step treatment unit, an in-out online monitoring unit, a pollution analysis unit, a wastewater treatment management and control analysis unit and an intelligent management end, various pollutants in cutting fluid wastewater are removed by integrating various treatment technologies through the wastewater step-by-step treatment unit, and the in-out online monitoring unit samples the cutting fluid wastewater before treatment and purified water after treatment and collects monitoring data of various pollution parameters in corresponding sampled liquid. The pollution analysis unit judges the pollution condition based on the monitoring data of each pollution parameter in the corresponding sampling liquid, and the wastewater treatment management and control analysis unit judges whether wastewater treatment is abnormal or not through analysis and accurately evaluates the treatment management and control performance for cutting fluid wastewater treatment. The treatment efficiency and the treatment effect of the cutting fluid wastewater can be guaranteed, and the intelligent and automatic levels are high.

The invention provides an iron and steel enterprise high-salt wastewater and high-salt solid waste collaborative resource utilization system which is characterized in that firstly, non-magnetic fly ash in sintering machine head fly ash is screened out through a pretreatment module; carrying out multi-stage washing and filter pressing treatment on slurry obtained by mixing the non-magnetic dedusting ash, the blast furnace gas condensate water and the strong brine of the desalting water station through a multi-stage washing and filter pressing module to obtain multi-stage washing ash and multi-stage ash washing brine; finally, carrying out purification and separation treatment on the multi-stage ash washing brine through a purification and separation module to obtain industrial-grade NaCl, industrial-grade KCl and devitrification mother liquor; according to the method, non-magnetic fly ash, blast furnace gas condensate water and strong brine of a desalting water station are used as raw materials, the problem of enrichment of alkali metal and chloride ions in a sintering machine system is solved through a series of co-processing technologies, and meanwhile industrial-grade NaCl and industrial-grade KCl are extracted from the blast furnace gas condensate water and the strong brine of the desalting water station. Therefore, the resource utilization rate is improved, and benefits are increased for iron and steel enterprises.

The invention relates to a cooling tower device for recovering heat from waste steam, which adopts three layers of transversely arranged heat exchange tube groups, realizes cascade recovery of heat energy of waste steam through communication of an air inlet and an air outlet, and is additionally provided with fins on the surfaces of heat exchange tubes to enhance the gas-liquid mass transfer efficiency. The core innovation lies in that a built-in mechanical cleaning mechanism is arranged, a driving assembly is in linkage with multiple sets of bidirectional adapters through a rotating shaft, brush rods distributed in the circumferential direction are driven to conduct high-frequency physical scraping on heat exchange pipes and fins, scale deposition is effectively restrained, and compared with traditional chemical cleaning, the shutdown maintenance time is shortened; the steam latent heat recovery rate can be increased, meanwhile, secondary pollution is avoided through a full-mechanical cleaning scheme, modular layout is adopted in structural design, interlayer fluid distribution of the heat exchange pipe set is achieved through a U-shaped pipe and a straight pipe, it is ensured that the resistance coefficient of the system is lower than that of similar equipment, and the device has remarkable energy-saving benefits in industrial scenes such as chemical engineering and metallurgy.

The invention provides an iron phosphate wastewater treatment method and system, and belongs to the field of wastewater treatment.The iron phosphate wastewater treatment method comprises the steps that ammonium sulfate in wastewater is separated out through an MVR evaporation device, and then primary precipitation is conducted by adjusting the pH value to remove heavy metal impurities; then adding ammonia water for secondary precipitation and filtration to further remove phosphate radical impurities; then adding lime to carry out three-stage precipitation filtration to remove fluorine element; and finally, carrying out ammonia removal treatment on the obtained tail liquid, returning to the first step of working procedure, and carrying out repeated treatment again. Wherein the generated ammonia gas is used for secondary precipitation filtration; the mode of directly recovering resources in the iron phosphate wastewater through the cooperation of a high-temperature treatment method and a fractional precipitation method is beneficial to avoiding heat value waste, and the energy consumption cost for subsequent treatment of the tail liquid and the use cost of the reagent dosage in a tail gas recovery system are reduced.

A pressure-regulating buoyant hydrodynamic pump is disclosed that floats adjacent to a surface of a body of water over which waves tend to pass. In response to wave-induced movements of the device, water is drawn into a mouth at a lower end of an injection tube, and water is ejected from a mouth at an upper end of the injection tube. The ejected water is deposited into an interior of the hollow buoy thereby augmenting a water reservoir therein. And water flows from the water reservoir to and through a water turbine, thereby energizing a generator, power electronics, and an electrical load. A novel water-turbine effluent buffering tube, or chamber, smooths pressure variations felt across the water turbine.

The invention discloses an oxidation-reduction free radical synergistic electrochemical wastewater treatment method and system. The method comprises the following steps: collecting pollutant concentration in wastewater and electrochemical reactor state parameters in real time through a sensor array; analyzing a pollutant change trend based on the data, and determining an optimization target value of an active substance generation proportion in combination with historical data; the trained classification model is used for classifying the water body state, and whether dynamic adjustment is needed or not is judged; if necessary, calculating the state parameter correction according to the deviation between the target value and the actual value, and adjusting the operation of the reactor; and monitoring the adjusted active substance proportion and degradation efficiency, and dynamically updating the optimization target according to the adjusted active substance proportion and degradation efficiency and the pollutant trend to realize continuous self-adaptive regulation and control. The intelligent closed-loop control of the reaction parameters is realized, the stability of the treatment efficiency is obviously improved, and the energy consumption and the risk of secondary pollution are effectively reduced.

The invention discloses a treatment process for acid mine wastewater and a combined reactor thereof, and relates to the technical field of water treatment. The method specifically comprises the following steps: oxidizing the mine acid wastewater through an aerobic reactor; adjusting the pH value to 2.8 by using KOH in a first neutralization reactor, and further adjusting the pH value to 4.5 by using KOH in a second neutralization reactor; the wastewater enters a pretreatment reactor, H2S is introduced for treatment, and the treated wastewater continuously enters two anaerobic reactors for reaction. According to the method, an aerobic-anaerobic combined reactor containing iron oxidizing bacteria and sulfate reducing bacteria is adopted for treating the mine acid wastewater, on one hand, AMD can be effectively treated, on the other hand, heavy metal can be selectively precipitated, and Schwertmannite and metal sulfide with utilization value are obtained. The method not only realizes the economic value of effectively utilizing the wastewater, but also realizes the target of environmental treatment, and has better economic value.

The invention belongs to the technical field of sewage treatment and artificial intelligence, and particularly relates to an effluent ammonia nitrogen concentration measurement method based on a neural network and Bayesian optimization, which comprises the following steps: step 1, constructing a basic model, collecting a characteristic variable x, preprocessing x, and normalizing x; 2, inputting x into a basic model for feature extraction and reinforcement; 3, extracting long-term time sequence features of a feature sequence from the x after feature extraction and enhancement through a bidirectional long-short-term memory neural network, dynamically adjusting an input step length, capturing a bidirectional time dependency relationship in the sequence, and outputting a predicted value; and step 4, performing parallel Bayesian optimization algorithm, dynamically adjusting the acquisition function, simultaneously evaluating a plurality of candidate points, performing parallel adaptive acquisition function, and outputting a measurement value. According to the scheme, the acquisition function can be dynamically adjusted according to different stages of the optimization process, the parameter space coverage rate is improved, multiple candidate points are evaluated at the same time, the exploration speed of the parameter space is increased, and the generalization ability of the model is enhanced.

The utility model discloses a multifunctional industrial wastewater treatment device, and the utility model relates to the technical field of multifunctional industrial wastewater treatment devices. A second water inlet pipe is provided inside the centrifugal cylinder, a water outlet groove is provided at the bottom of the second water inlet pipe, a guide plate is fixedly connected to the inner wall of the centrifugal cylinder, a slag discharge groove is provided at the bottom of the centrifugal cylinder, and a plurality of oil outlet holes are provided above the centrifugal cylinder. The centrifugal force after the centrifugal cylinder rotates to full speed separates the wastewater with heavy weight from the residue and grease. Due to its own light weight, the grease is thrown into the inner cavity of the treatment cylinder through the oil outlet hole, and the heavy residue is deposited downward. When the set slag discharge cycle is reached, the slag discharge starts, and the scraper scrapes the grease adhered to the inner wall of the treatment cylinder and discharges it through the second slag discharge pipe. The sealing ring opens the slag discharge groove upward, so that the residue inside the centrifugal cylinder is discharged to the outside of the device through the slag discharge pipe, so as to avoid the grease adhering to the inner wall of the treatment cylinder and affecting the treatment efficiency of the wastewater.

The invention relates to the technical field of sewage treatment, in particular to a distributed rural sewage treatment station intelligent optimization method and system. According to the method, firstly, the water quality parameters and the operation parameter data are collected and cleaned, the preprocessed feature data are input into the prediction model to obtain the prediction result, the prediction result is compared with the real-time operation data to obtain the deviation data, and the model parameters are dynamically optimized and issued according to the deviation data, so that the blindness of parameter setting in a traditional method is reduced; the control strategy can be adjusted in real time according to the actual operation condition, the operation cost is remarkably reduced while the effluent reaches the standard, and the treatment efficiency is improved.

The utility model provides a petroleum wastewater oil-water separation device which is connected with a discharge port of a mixer, the mixer is used for mixing and reacting oil dirt in petroleum wastewater with air and a flocculating agent to form scum, the device comprises an air floatation tank, one end of the air floatation tank is connected with the discharge port of the mixer through a conveying pipeline, and the other end of the air floatation tank is provided with a receiving hopper; a scum scraping mechanism is arranged at the top of the air floatation tank; the dredging mechanism comprises a push block, a connecting plate and a reciprocating mechanism, the connecting plate is connected with the push block, the connecting plate is slidably connected in a vertically arranged sliding sleeve, the sliding sleeve is fixed in the receiving hopper through a transverse plate, the reciprocating mechanism is arranged at the other end of the air floatation tank, and when the connecting plate moves downwards to the maximum limit, the push block enters a slag discharging opening of the receiving hopper, and the slag discharging opening is opened. When the connecting plate moves upwards to the maximum limit, a preset distance is reserved between the push block and the slag discharging opening. The device can dredge the material receiving port in time through the dredging mechanism, so that a large amount of scum is prevented from being accumulated in the receiving hopper to influence the scraping of the scum in the air floatation tank.

The invention discloses a special phosphorus removal agent for deep phosphorus removal and a preparation method and application thereof, and relates to the field of phosphorus removal agents and preparation methods thereof.The phosphorus removal agent is prepared from a porous precursor, an activating agent and a dispersing agent, and the porous precursor comprises at least one of aluminum oxide, iron oxide, calcium oxide and magnesium oxide; the activating agent comprises at least one of lanthanum salt, cerium salt, zircon salt, magnesium salt and ferric salt. By optimizing the composition of the porous precursor and activating treatment, the phosphorus adsorption capacity is remarkably improved, the phosphorus removal agent also plays a role in micro-flocculation in the process of mixed adsorption with sewage, a wet adding mode is adopted, the adding amount can be flexibly adjusted according to the phosphorus concentration condition of inlet water and outlet water, and the phosphorus removal efficiency is improved. The phosphorus removal agent can reduce the total phosphorus concentration in tail water of a sewage treatment plant to 0.5 mg / L or below.

The invention relates to the field of water treatment and video treatment, and discloses a water plant coagulating sedimentation effect estimation method, system, medium and equipment based on alumen ustum target tracking, and the method comprises the following steps: collecting alumen ustum video images, and aligning online flow water quality instrument data with the alumen ustum video images; inputting the aligned online flow water quality instrument data and alumen ustum video images into a video target tracking large model, tracking each alumen ustum target, and constructing the form and motion characteristics of alumen ustum to obtain alumen ustum characteristic data; based on alumen ustum characteristic data and online flow water quality instrument data, a sedimentation tank effluent turbidity estimation model is trained; reading alumen ustum video streams and online instrument data on line, inputting the alumen ustum video streams and the online instrument data into the large video target tracking model, and estimating the effluent turbidity of the sedimentation tank through the effluent turbidity estimation model of the sedimentation tank. The risk that the adding amount of the coagulant is not adjusted in time can be reduced, the water quality stability of effluent of the sedimentation tank is improved, and the backwashing frequency and economic cost of the filter tank are reduced.

The invention relates to the technical field of waste incineration, in particular to a waste incineration fly ash reduction and recycling harmless system and a working method. The system comprises a dioxin mechanical detoxification subsystem, a multi-stage countercurrent water washing subsystem, a quaternary system evaporation salt separation subsystem and a heavy metal pickling recovery subsystem, and according to the working method of the system, low-temperature mechanical detoxification, multi-stage countercurrent fly ash water washing, heavy metal pickling recovery and low-cost quaternary system evaporation salt separation are organically combined; the low-cost reduction, harmless and resourceful treatment of the fly ash is realized, the treated fly ash can be directly used for preparing materials such as building materials, and the method has a wide application prospect. In addition, no flue gas is generated, a flue gas treatment system is not needed, secondary fly ash and wastewater discharge is avoided, and near-zero discharge can be realized.

The invention provides a sewage treatment method and treatment system utilizing effective distribution before and after combination of AOA and a carbon source. Belongs to the technical field of sewage treatment. The method comprises the following steps: sequentially carrying out denitrification, first anaerobic phosphorus release, first nitrification, second nitrification and second anaerobic phosphorus release on sewage to obtain a first nitrification solution; part of the first nitrification liquid flows back to the denitrification process, the remaining first nitrification liquid is precipitated, and purified water and sludge are obtained; or sequentially carrying out denitrification, first anaerobic phosphorus release, first nitrification and second nitrification on the sewage to obtain second nitrification liquid; part of the second nitrification liquid is refluxed into the denitrification process, the remaining second nitrification liquid is sequentially subjected to second anaerobic phosphorus release and precipitation to obtain purified water and sludge, the nitrification liquid is refluxed, nitrate which is not subjected to denitrification is refluxed to be further denitrified, and therefore the concentration of nitrate in treated effluent and the concentration of total nitrogen in the effluent are reduced. The sewage treatment effect is improved.

The invention discloses an effluent total phosphorus prediction model construction method based on a pigeon flock optimization echo state network, and the method comprises the steps: obtaining sewage treatment data, and carrying out the data preprocessing; determining an auxiliary variable set and a prediction variable according to the preprocessed sewage treatment data; wherein the predictive variable is effluent total phosphorus; determining the number of input nodes and the number of output nodes of the echo state network according to the auxiliary variable set and the prediction variable; and determining optimal parameters of an echo state network reserve pool layer based on a self-adaptive improved pigeon inspired optimization algorithm in combination with a tabu search algorithm. According to the method, the global search capability of the pigeon inspired optimization algorithm and the local search capability of the tabu search algorithm are utilized, the optimization capability of the algorithm is further improved by improving an operator updating formula in the pigeon inspired optimization algorithm, and the parameters and the structure of the echo state network are optimized by applying a self-adaptive adjustment mechanism. The original algorithm gets rid of a local optimal solution, and the model prediction precision can be improved.

The invention provides an autonomous adjustment method and system for a thermal power plant desulfurization wastewater dosing device, and the method comprises the steps: collecting multiple parameters such as flow, pH value, heavy metal ion and suspended matter concentration in real time through on-line monitoring instruments arranged at a water inlet end, a reaction unit and a water outlet end; constructing and continuously updating a dynamic mathematical model based on historical data and a reaction mechanism; a control system integrating intelligent algorithms such as a neural network and fuzzy control is utilized, and optimal dosing parameters are calculated in combination with the model and real-time data; a dosing pump or a valve is driven to execute precise dosing; and finally, closed-loop optimization is formed through effluent quality feedback. According to the invention, automatic, accurate and self-adaptive adjustment of the dosing device is realized, the defects that a traditional mode depends on manpower and response lags behind are overcome, stable and standard discharge of desulfurization wastewater is effectively guaranteed, meanwhile, medicament consumption and operation cost are remarkably reduced, and the automation level and the capability of coping with working condition fluctuation of the system are improved.