3893 results about "Ammoniacal nitrogen" patented technology

The invention discloses an expressway service area sewage treatment system based on the Internet of Things, and relates to the technical field of sewage treatment.The expressway service area sewage treatment system is provided with a multi-modal sensor and an edge computing unit, real-time monitoring and data processing of sewage flow and water quality parameters are achieved, the water quality change trend and the parameter change rate are rapidly recognized, and the sewage treatment efficiency is improved. The sensing capacity of the system to load changes is remarkably improved, the system conducts real-time adjustment according to the water quality changes, fluctuation of the treatment effect and waste of energy consumption are avoided, an LSTM model is adopted for conducting dynamic prediction on water quality parameters, in combination with real-time monitoring data, the aeration strategy is optimized through intelligent self-adaptive adjustment and closed-loop fine control, and the aeration efficiency is improved. The LSTM model can predict the future sewage load and ammonia nitrogen concentration change, the aeration intensity and time are adjusted in advance, the fluctuation of the ammonia nitrogen concentration is quickly responded through PID control and closed-loop control of a feedback mechanism, and the ammonia nitrogen removal efficiency and the aeration accuracy are improved.

The invention relates to the technical field of process control, in particular to an intelligent environment monitoring and adjusting system for lip fish culture, which comprises an environment parameter monitoring module, a multivariable linkage calculation module, a self-adaptive adjusting module, a fuzzy logic control module and an abnormity emergency response module. According to the method, the trend value is formed through time-phased grouping analysis and relevance calculation of the water quality parameters, dynamic prediction of the breeding environment change is achieved, the cooperative adjustment capacity among the dissolved oxygen, the water temperature and the ammonia nitrogen concentration is optimized through analysis of the multi-parameter linkage relation, the accuracy of environment control is improved, and the method is suitable for large-scale popularization and application. The cooperation efficiency of oxygen pump frequency and temperature control equipment response is improved through real-time matching calculation of equipment operation parameters, the rapid adaptive capacity to water quality changes is enhanced, abnormal fluctuation monitoring is combined with equipment linkage adjustment, rapid response during water quality sudden change is ensured, and the adverse effect of environment fluctuation on fish growth is reduced.

The invention provides a sewage treatment aeration control system and method based on multi-parameter collaborative optimization. The method comprises the following steps: acquiring multi-sensor data of COD (Chemical Oxygen Demand), BOD5 (Biochemical Oxygen Demand), DO (Dissolved Oxygen Demand), ammonia nitrogen, ORP (Oxidation Reduction Potential), pH (Potential of Hydrogen), water inlet flow and sludge concentration of wastewater in an aeration tank by utilizing a multi-parameter sensor module; according to the dynamic correction oxygen mass transfer coefficient and the feedforward parameter, establishing a relationship between the water inlet load and aeration; calculating the air volume of an air blower and the fine adjustment value of the opening degree of a butterfly valve through a PID control algorithm and feedback parameters, and correcting the aeration quantity to obtain a total air volume target value; and adjusting the opening degree and the rotating speed of a guide vane of the air blower according to the self-adaptive PID control parameters and the corrected total air volume target value by utilizing a self-adaptive PID controller, and adjusting the opening degree of a butterfly valve according to a gradient butterfly valve adjusting strategy. The output of the air blower is optimized by adopting self-adaptive PID, and the opening degree of the butterfly valve of each biological tank is dynamically adjusted through a gradient valve adjusting strategy, so that the accurate control of the aeration rate is realized; the sewage treatment effect is ensured.

The invention relates to the field of sewage control, in particular to a nano zero-valent iron and zeolite molecular sieve synergistic composite material as well as a preparation method and application thereof. The nano zero-valent iron synergistic zeolite molecular sieve composite carrier (nZVI at Z-PU) is successfully prepared through an impregnation method, the preparation method is simple and controllable, and corresponding substances are introduced in the preparation process, so that the composite carrier has the structure and properties of being rough in surface, hydrophilic and carrying positive charges. Through modification, the ammonia nitrogen adsorption capacity of the nZVI-Z-PU is increased to 4-6.5 mg / g carrier, meanwhile, the initial adsorption capacity of the nZVI-Z-PU to microorganisms is remarkably improved and is 8.7 times that of a common polyurethane sponge carrier, and the initial adsorption capacity of the nZVI-Z-PU to the microorganisms is far superior to that of the common polyurethane sponge carrier. Therefore, after the zeolite molecular sieve and the nZVI are combined, the generation of NOB can be remarkably inhibited, and meanwhile, the activity of AnAOB is improved.

The invention discloses a culture method of anaerobic ammonia oxidation granular sludge with a polydopamine modified charcoal-loaded Fe-Cu sodium alginate microsphere kernel, which comprises the following steps: modifying charcoal by using polydopamine, then carrying out Fe-Cu ion loading, finally preparing sodium alginate microspheres, and taking the prepared sodium alginate microspheres as the kernel to prepare the anaerobic ammonia oxidation granular sludge with the polydopamine modified charcoal-loaded Fe-Cu sodium alginate microsphere kernel. And co-culturing the sodium alginate microspheres and activated bacillus DMF-4 in an oxygen-free environment, continuously culturing for 3 weeks, and collecting by using a gravity settling or centrifugal method to obtain the anaerobic ammonium oxidation granular sludge with the sodium alginate microsphere core. The sodium alginate microspheres serving as the core provide large density and good morphological support for sludge particles, the problem of sludge bulking is avoided, and the settling performance is improved. According to the present invention, the sludge anti-shearing performance is improved, the adsorption capacity of the slowly released and continuously slowly released iron ions on organic matters, ammonia nitrogen and heavy metals is enhanced, the sewage treatment effect is improved, and the iron ions are the biodegradable material so as not to cause secondary pollution in the use process.

The invention discloses an integrated water quality monitoring and processing system for aquaculture, and the system comprises a data collection module which is used for obtaining dissolved oxygen, ammonia nitrogen, pH value, temperature and flow data from a plurality of spatial distributed sensing nodes; the data preprocessing module is used for completing noise removal, correction and time sequence synchronization; the water quality state estimation module is used for outputting real-time multi-point water quality states based on a distributed unscented Kalman filtering algorithm; the space-time fluid modeling module is used for constructing a Lagrange model to extract a flow velocity field and a diffusion coefficient; the scheduling optimization module is used for generating an aeration and dosing scheme by adopting an improved multi-target Pareto optimization algorithm based on a space-time sensitive boundary; the execution module is used for controlling an air blower, an aeration pipe and a dosing pump to complete oxygenation and dosing operations; and the self-adaptive updating module is used for collecting feedback data to adjust filtering gain and optimizing parameters so as to realize closed-loop control of the system.

The present invention discloses a multi-dimensional intelligent control system for fluorine removal, which specifically relates to the field of sewage fluorine removal, including a water quality fluctuation monitoring module, a normal measurement judgment module, an abnormal stage judgment module, a deep learning prediction module, and a multi-task regression module; the water quality fluctuation monitoring module is used to obtain water quality fluctuation information of a water source that needs to be defluorinated in real time, establish pre-measurement condition 1 and pre-measurement condition 2 based on the water quality fluctuation information, and determine whether there are water quality influencing factors in the current water source through pre-measurement condition 1 and pre-measurement condition 2. The present invention realizes the management of fluorine concentration control by introducing multi-dimensional water quality fluctuation information and real-time monitoring mechanism, and performs real-time prediction based on water quality parameters such as water body chromaticity, conductivity, reflectivity and ammonia nitrogen concentration in combination with deep neural network, which is conducive to identifying water quality fluctuations and performing corresponding regulation, dynamically responding to water quality changes, and improving the convenience of water source control.

The invention relates to the technical field of environment assessment, in particular to a coastal zone culture area multi-dimensional environment assessment method and a cloud platform. The method comprises the following steps: continuously recording dissolved oxygen concentration, pH value, centigrade temperature, salinity unit, turbidity scattering unit, chlorophyll fluorescence intensity, ammonia nitrogen milligram per liter and nitrite milligram per liter, synchronously calling multi-source remote sensing images covering a culture area and an adjacent water area, extracting remote sensing reflectivity data through image correction and atmospheric correction, and calculating to obtain water color parameters. According to the method, the water quality sensor array is deployed at the key point of the culture area, continuous multi-parameter environmental data acquisition is carried out, multi-source remote sensing images are synchronously integrated, water color information is extracted in real time, and the timeliness and data accuracy of culture water area environmental monitoring are improved; trend decomposition and dynamic baseline construction are carried out based on the data sequence, so that the environmental fluctuation evaluation of the breeding area is more objective and accurate.

The invention discloses low-temperature-resistant and high-salt-resistant aerobic pseudomonas kirschner kirschner K2 as well as a preparation method and application thereof. The preparation method comprises the following steps: carrying out low-temperature and high-salt enrichment culture; screening and domesticating, and monitoring the concentration of ammonia nitrogen; and after 3-5 times of enrichment culture, diluting the enrichment culture, further culturing until a macroscopic bacterial colony is obtained, and then picking and carrying out plate streaking to separate a pure strain. The invention also relates to application of the strain in preparation or prevention of nitrification and denitrification nitrogen removal drugs in treatment of high-salt nitrogen-containing wastewater. The strain is low-temperature-resistant and high-salt-resistant heterotrophic-aerobic denitrifying bacteria, has the characteristic of low temperature resistance, grows well at low temperature and high salt salinity, has higher heterotrophic nitrification-aerobic denitrification nitrogen removal capacity, is suitable for nitrogen removal treatment of high-salt wastewater such as food processing wastewater and landfill leachate, and has wide application prospects. The superiority is particularly obvious under a low-temperature condition.

The invention discloses a river water ecological health monitoring method and a river water ecological health monitoring system, relates to the technical field of ecological health monitoring, and aims to solve the problem that a traditional water quality monitoring method mainly depends on water sample collection and laboratory analysis, and judges the water quality by measuring indexes such as dissolved oxygen, pH value, ammonia nitrogen, total phosphorus, heavy metal and dissolved organic matters in water; the river runoff is calculated from the precipitation and the drainage basin area, and the monitoring points are set in combination with the environmental information, so that an accurate data basis can be provided for subsequent water quality health assessment. The water quality condition is predicted by utilizing the water flow speed and the pollution point discharge amount and then compared with an actual monitoring result, so that potential problems can be found in time and a monitoring strategy can be optimized.

The invention relates to the technical field of water environment treatment, in particular to a water environment ecological treatment method and system based on a constructed wetland, and the method comprises the following steps: measuring the dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, water temperature and pH value of a root zone in the constructed wetland, and calculating the pollutant concentration distribution value and plant root system distribution density of each monitoring point; and obtaining a water quality root distribution characterization value. In an artificial wetland environment, the concentration of dissolved oxygen, the concentration of ammonia nitrogen, the concentration of total phosphorus, the water temperature and the pH value of a root zone are measured, the concentration distribution of pollutants is calculated, numerical calculation is carried out in combination with the distribution density of plant root systems, water quality root system distribution characterization is constructed, spatial heterogeneity analysis of wetland water quality is enhanced, and the targeting of pollutant degradation is optimized. Based on water quality root system distribution characterization, plant growth cycle parameters are calculated in combination with water quality parameters, association between water quality dynamic changes and plant growth states is constructed, and the adaptability of wetland ecological regulation and control is improved.

The invention discloses an intelligent control method for water treatment aeration. The intelligent control method comprises the following steps: S1, setting a preset condition; s2, measuring water quality data, wherein the data comprises chemical oxygen demand (COD), ammonia nitrogen amount, water temperature and water flow velocity; s3, an intelligent aeration algorithm is set, the intelligent aeration algorithm comprises an air inflow calculation model, the air supply amount of a fan and the opening degree of a valve are adjusted according to the result of the air inflow calculation model, and therefore the dissolved oxygen content, namely the DO value, is adjusted; s4, performing operation calculation according to the current water quality data through an intelligent aeration algorithm to obtain a suggested air volume of the intelligent aeration algorithm; intelligent aeration algorithm model training is carried out by collecting data of a fan, a regulating valve, dissolved oxygen, ammonia nitrogen and the like, dynamic response can be carried out on a training result biochemical pool aeration link according to the inlet water quality and water quantity of a sewage treatment plant and the water quality and water quantity of a water outlet of the sewage treatment plant, and stable process indexes are achieved through aeration according to needs.

The invention discloses a shallow lake water quality pollution treatment system and method, and relates to the technical field of water pollution, and the method comprises the steps: S1, building a disturbance intensity index DIX and ammonia nitrogen concentration change curve, achieving the quantitative recognition of bottom mud disturbance and pollution release behaviors, training a rebound risk prediction model according to the quantitative recognition, and outputting a rebound risk prediction coefficient Ft; and the capability of pre-judging the rebound trend of the ammonia nitrogen pollution is effectively improved. In the step S2, the adjusted aeration response frequency BAF is dynamically generated based on the rebound risk prediction coefficient Ft value, so that the aeration behavior is converted into a risk-driven system from a traditional timing system, the energy consumption and disturbance intensity are further reduced, and the treatment efficiency is improved. And S3, further introducing a governance residual coefficient GRC, constructing a complete feedback closed loop, and realizing accurate evaluation and secondary strategy optimization of the governance effect of each round, thereby avoiding the problem of effect back-off or excessive disturbance after governance.

The invention provides an intelligent aeration system and a control method, and the system comprises a multi-parameter monitoring module which collects parameters such as water depth, pressure, temperature, dissolved oxygen, inlet water ammonia nitrogen, chemical oxygen demand, and mixed liquid suspended solid concentration in real time; the data analysis and preprocessing module adopts a sliding window algorithm to carry out data cleaning and anomaly detection; the oxygen supply demand prediction module establishes an oxygen demand prediction model based on machine learning, and combines theoretical calculation and deep learning prediction; the multi-target intelligent control module adopts a reinforcement learning algorithm, establishes a Markov decision process model, and optimizes the processing effect and energy consumption at the same time; the execution control module is used for accurately adjusting the rotating speed of a fan, the opening degree of a valve and the running state of an aerator; and the system collaborative optimization module realizes linkage control of the aeration system and the carbon source adding system. The system has the functions of self-adaptive parameter adjustment, fault diagnosis and self-recovery, the DO control precision reaches 95% or above, the daily average electricity is saved by 9.7%, the NH4-N of effluent is reduced by 25%, and the annual comprehensive benefit exceeds 500,000 yuan.

The invention belongs to the technical field of microorganisms, and discloses a low-temperature-resistant aerobic denitrifying bacterium and application thereof. The low-temperature-resistant aerobic denitrifying bacterium is Enterobacter ludwigii CW-01, and the preservation number of the low-temperature-resistant aerobic denitrifying bacterium is CGMCC (China General Microbiological Culture Collection Center) No.27126. The low-temperature-resistant aerobic denitrifying bacterium can be used for preparing the The enterobacter lewis CW-01 strain disclosed by the invention can efficiently realize aerobic denitrification degradation of ammonia nitrogen, nitrate and nitrite within the temperature range of 4-35 DEG C, and is especially suitable for wastewater treatment in which the ammonia nitrogen, nitrate and nitrite are difficult to remove due to low temperature; the strain also has good salt resistance, and provides a good microbial material for biological nitrogen removal treatment of low-temperature, high-salt and high-ammonia nitrogen polluted water. The nitrogen is efficiently removed, meanwhile, the use amount of a carbon source is remarkably reduced, the enterprise cost is greatly reduced, and the method has a good application prospect in the field of sewage treatment.

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

The invention provides an intelligent management method and system for reducing pollution and carbon of rural domestic sewage. According to the method, sewage flow velocity, COD concentration, ammonia nitrogen content data, user water use time and detergent use amount are collected, and a database is constructed. And weighting the flow velocity and COD to generate a pollution load evaluation value, and calculating an organic matter pollution influence value in combination with ammonia nitrogen and detergent data. A porous ceramic medium is arranged in the biological treatment device, and the dissolved oxygen concentration is adjusted according to the pollution load. A correlation curve of a COD concentration peak value and water consumption time is established, a prediction model is constructed in combination with dissolved oxygen parameters, the gas injection and reflux ratio is adjusted through graded pressure instructions, and the critical value of dissolved oxygen is maintained. The day and night temperature difference is fused to correct the degradation rate, and the optical detection data is combined to optimize the critical range and the instruction priority, so that the cooperative control of sewage treatment and carbon emission reduction is realized. According to the invention, self-adaptive adjustment of dissolved oxygen in sewage treatment is realized, and the sewage reduction and carbon reduction management efficiency of domestic sewage is improved.

The invention discloses an internal coupling energy-saving atomization ammonia water recovery process for high-concentration ammonia-nitrogen wastewater, and particularly relates to the technical field of wastewater treatment. The process comprises the steps that firstly, ammonia gas and water vapor mixed gas generated after high-concentration ammonia-nitrogen wastewater is rectified through a deamination tower enters the absorption-condensation integrated ammonia recoverer through a pipeline, an internal coupling energy-saving atomization energy-saving device of the integrated ammonia recoverer can generate superfine water mist, and after being combined, ammonia-containing vapor and the superfine water mist are subjected to rapid heat exchange; meanwhile, due to the characteristic that ammonia is extremely easy to dissolve in water, ammonia gas molecules can be combined with liquefied water vapor water molecules, and dissolving heat of the water vapor water molecules can be quickly released to form ammonia water. The method is simple in technological process and small in equipment investment and occupied area, a multi-stage absorption tower and a large amount of absorbent can be saved, the ammonia water is recycled in one step, the ammonia water is high in purity and controllable in concentration, almost no noncondensable gas is generated, and meanwhile steam energy consumption in the high-concentration ammonia-nitrogen wastewater deamination process can be saved.

The invention provides a treatment method of ammonia-nitrogen-containing wastewater, and belongs to the technical field of wastewater treatment. The preparation process comprises the following steps: preparing the wastewater treatment agent; preparing an immobilized microbial compound; and treating the ammonia-nitrogen-containing wastewater. According to the immobilized microbial carrier prepared by the invention, a stable dual-network structure and proper pore channels are formed through the synergistic effect of the polyvinyl alcohol, the carboxymethyl chitosan and the polyurethane; secondary cross-linking significantly enhances the stability of the carrier, optimizes internal pore channels, and is beneficial to attachment and proliferation of microorganisms; after the corn straw biochar is modified by Ca / Al, the specific surface area and functional groups are increased, and the physicochemical adsorption of ammonia nitrogen is enhanced. The three are combined, and ammonia nitrogen in wastewater is efficiently removed through synergism of carrier adsorption and microbial metabolism.

The invention provides a preparation method and an application method of a gasified slag-based carbon-zeolite composite material, and belongs to the technical field of carbon-zeolite composite materials. The preparation method comprises the following steps: taking gasified slag as a raw material, mixing the gasified slag with alkali, a silicon source substance, a surfactant and water, and sequentially carrying out aging treatment and hydrothermal reaction to obtain the gasified slag-based carbon-zeolite composite material. The gasified slag-based carbon-zeolite composite functional material is prepared from the gasified slag, the process is simple, the preparation cost is low, meanwhile, high-added-value utilization of the gasified slag is achieved, the purpose of treating waste with waste is achieved, and economic benefits and environmental protection benefits are achieved. The gasified slag-based carbon-zeolite composite functional material prepared by the invention has a good removal effect on low-concentration ammonia nitrogen and organic matter wastewater, has regeneration performance, and still has good ammonia nitrogen adsorption and organic pollutant degradation performance after regeneration.

The invention belongs to the field of deep learning, and relates to a sewage treatment plant water quality prediction method based on an improved transformer deep learning model, which comprises the steps of collecting sewage water quality monitoring data including chemical nitrogen demand COD, ammonia nitrogen, pH, temperature and flow of a sewage treatment plant at different moments, performing data cleaning, and performing noise removal based on wavelet transform. The method comprises the following steps: preprocessing sewage water quality monitoring data to obtain processed sewage water quality monitoring data to establish a data set, constructing a water quality prediction model of a sewage treatment plant based on an improved transformer deep learning model, inputting parameters in the preprocessed sewage water quality monitoring data set training model, and predicting the water quality of the sewage treatment plant based on the trained improved transformer sewage water quality prediction model. According to the invention, through improving the transformer deep learning model, modeling is carried out on sewage quality monitoring data and other long time sequence data with strong time sequence characteristics based on the attention mechanism, the prediction precision of the sewage quality can be improved, intelligent water quality prediction of a sewage treatment plant is realized, and the water quality prediction cost is reduced.

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 invention relates to the technical field of municipal sludge treatment, in particular to a method for recycling nitrogen and phosphorus elements from municipal sludge. According to the method, the municipal sludge is subjected to hydrothermal carbonization treatment, the treated solid-phase product is dried and ground to a specific particle size, the solid-phase product is subjected to acid leaching under a specific condition to extract the phosphorus element, and then heavy metal and metal elements such as Al and Fe in the acid leaching liquid are removed by adopting strong-acid ion exchange resin and a chemical precipitant, so that the phosphorus element is obtained. And finally, mixing the struvite with a hydrolyzate which is subjected to hydrothermal carbonization treatment and is rich in ammonia nitrogen, and precipitating by adjusting the element proportion and the pH value to obtain a solid-phase product struvite crystal. According to the method, external nitrogen-containing substances do not need to be added, the content of heavy metal in the solid-phase product struvite can be effectively reduced, the recovery rate of phosphorus can reach 93% or above, the recovery rate of ammonia nitrogen can reach 63% or above, the recovery rate of nitrogen and phosphorus is high, energy consumption is low, and the treatment cost is low.

The invention provides a bioreactor aeration self-adaptive control method and system based on machine learning, and the method comprises the steps: collecting the water inlet flow, ammonia nitrogen concentration, dissolved oxygen concentration, water temperature and chemical oxygen demand data of a bioreactor in real time through a sensor, and carrying out the water balance verification and the Kalman filtering pretreatment containing a water temperature compensation item; generating an aeration instruction by adopting multi-model collaboration; outputting a reference aeration rate by a deep reinforcement learning DRL model; the self-adaptive PID controller dynamically adjusts the proportionality coefficient according to the dissolved oxygen deviation and calculates the correction amount; and the LSTM network generates a fusion weight, and combines the seasonal compensation factor and the safety coefficient to synthesize the final aeration rate. The system passes mutation rate constraint and nitrification efficiency verification, an ASM1 model is triggered to recheck when the deviation exceeds the standard, and after passing, an air blower with the precision of + / -2% executes an instruction and performs closed-loop feedback in a period smaller than or equal to 10 seconds. After the method is implemented, the aeration energy consumption is reduced to 0.38 kWh / m, the effluent ammonia nitrogen standard reaching rate is improved to 98.5%, the dissolved oxygen fluctuation range is reduced to + / -0.3 mg / L, and the impact load response time is shortened to be within 15 minutes.

The invention relates to a wastewater treatment optimization method based on electrochemical reaction. Comprising the following steps: monitoring the concentration of pollutants in wastewater in real time by configuring various sensors including a heavy metal sensor, a chemical oxygen demand sensor and an ammonia nitrogen sensor; sensor data is transmitted to the central control unit of the processing system through the wireless communication module; constructing a reaction kinetic model according to the type and concentration of pollutants in the wastewater and the properties of electrochemical reaction; an optimization target is set, the pollutant removal rate is calculated to be maximized, and energy consumption and consumables including abrasion of electrodes and use of chemical reagents are reduced; dynamically adjusting parameters of electrochemical reaction by adopting a self-adaptive optimization algorithm; the parameters comprise current density, voltage of an electrolytic cell, reaction time and temperature; in the wastewater treatment process, the sensor feeds back the pollutant concentration of the wastewater and the voltage and current density information in the electrolytic bath in real time; and the data is transmitted to a central unit of the control system through the data transmission module.

The invention relates to an intelligent breeding method for crayfish offspring seeds in a winter fallow field, and belongs to the technical field of aquaculture. In order to solve the problems of dissolved oxygen management lag, high ammonia nitrogen accumulation risk and overlarge energy consumption caused by low utilization rate of winter fallow fields and dependence of water quality regulation and control on artificial experience in the prior art, the method comprises the following steps: deploying a water quality dynamic monitoring system based on the Internet of Things to collect data of water temperature, dissolved oxygen, pH value, ammonia nitrogen and nitrite in real time; the power and the water level of the oxygenation equipment are dynamically adjusted after analysis of the edge calculation module; graded regulation and control are achieved by combining a three-level response mechanism, when the dissolved oxygen content is lower than 6 mg / L or the pH value is abnormal, the power of the nanometer oxygenation device is started to 50%, and when the dissolved oxygen content continuously deteriorates, the irrigation system is linked to inject the water body with the temperature being adjusted in advance. According to the method, through intelligent multi-parameter cooperative control and ecological bait design, the resource utilization rate of the winter fallow field is increased, the survival rate of the young crayfish is increased to 85% or above, and the method is suitable for large-scale and green efficient breeding of the young crayfish in a rice-shrimp rotation mode.

The invention provides an intelligent control system and method for aquaculture. The intelligent control system comprises a dissolved oxygen detector, a pH detector, an ammonia nitrogen detector, a redox potentiometer, a structured data front-end processor, an underwater binocular vision observation device, a camera, an unstructured data front-end processor, a cloud processor and front-end equipment. The cloud processor makes a decision according to the information of the structured data front-end processor and the unstructured data front-end processor, and controls the front-end equipment to adjust the operation of the culture pond. According to the aquaculture monitoring system, aquaculture water quality key parameters such as dissolved oxygen, pH value, ammonia nitrogen and oxidation-reduction potential are monitored, aquatic animals are monitored in real time in the aquaculture process, the aquaculture environment is dynamically regulated and controlled, and the intelligence of aquaculture is improved. The intelligent control system for aquaculture can be used as a minimum unit template, is efficient and stable in operation, and facilitates the realization of whole-course real-time monitoring, autonomous regulation and control, multi-link coordinated linkage control and intelligent decision-making of aquaculture through copying and popularization.

The invention discloses an aerobic granular sludge culture method based on a micro-nano aeration technology, and belongs to the technical field of water treatment. According to the invention, micro-nano aeration is used, so that the oxygen transfer rate in the aerobic granular sludge reactor is 2.1 times of that of a conventional aeration group, the generated hydroxyl radicals are 2.6 times of that of the conventional aeration group, the final removal efficiencies of ammonia nitrogen, total nitrogen and COD (Chemical Oxygen Demand) can respectively reach 98%, 85% and 97%, the denitrification performance is excellent, the treatment period is shortened by 1 hour, and the treatment cost is reduced. After the aeration time is shortened, 28% of aeration energy consumption is saved. Micro-nano aeration not only is beneficial to culture and domestication of aerobic granular sludge and promotes removal of pollutants, but also improves the energy utilization efficiency.

The invention discloses a Trichotoma sp. ZSL-NS2 strain capable of producing protein and application of the Trichotoma sp. ZSL-NS2 strain in wastewater treatment of a dairy farm. The Trichotoma sp. ZSL-NS2 strain named as the Trichotoma sp. ZSL-NS2 strain is preserved in the China Center for Type Culture Collection on November 7, 2024, and the preservation number is CCTCC NO.M20242469. The Trichotoma sp. ZSL-NS2 strain is named as the Trichotoma sp. ZSL-NS2 strain. The algal strain is separated from soil beside a wastewater storage pool of a dairy farm, is purified and enriched under a high-salt condition (the salinity is 2.0-5.0%), has relatively strong wastewater tolerance and pollutant purification capacity, has the removal rates of more than 70% of COD, 85% of ammonia nitrogen, 75% of TN and 95% of conventional pollutants respectively, and particularly has the most obvious removal effect on ammonia nitrogen and total phosphorus. In addition, the protein content of the conneronea is as high as 52%, and the conneronea can be used as a protein raw material for high-value application.