6689results about "Water aeration" 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 present invention relates to the field of environmental protection technology, and discloses a sewage treatment system based on intelligent perception and dynamic control, including: a multi-parameter detection module, which monitors the treatment process in real time by collecting and transmitting real-time data; an AI data processing engine module, which analyzes through data processing algorithms and generates process control schemes; a 5G communication module, which is used for data transmission between modules; an intelligent control platform module, which performs automatic adjustment of process parameters; a cloud storage service module, which is used to store system data in the cloud; an equipment automatic maintenance module, which monitors the equipment status through sensor data; an energy and resource recovery module, which is used to recover the heat and gas resources generated during the treatment process for reuse. In the present invention, the AI ​​engine adjusts the aeration amount, dosage and other parameters in the treatment system in real time through comprehensive analysis of historical data and real-time data, realizes fully automatic dynamic control, and greatly improves the efficiency of sewage treatment.

The invention relates to the technical field of sewage treatment, in particular to a liftable aeration device and a sewage treatment system.The system comprises a data acquisition module for acquiring dissolved oxygen concentration, gas flow and air pressure at multiple moments before each moment in the sewage treatment process and recording the dissolved oxygen concentration, the gas flow and the air pressure as historical data sets of each moment; the feature analysis module is used for determining the gas supply stability at each moment; determining a first trend degree, a second trend degree, a first collaborative factor and a second collaborative factor of each fluctuation moment in the historical data set of each moment; determining a relative collaboration degree and a forward feedback index at each moment; the aeration control module is used for determining a proportionality coefficient and an integral parameter of a PID controller at each moment; and in combination with a PID (Proportion Integration Differentiation) controller, obtaining a gas flow control value at each moment, and controlling the concentration of the dissolved oxygen in the sewage. The gas flow can be more accurately adjusted, the control accuracy of the concentration of dissolved oxygen in sewage is improved, and the sewage treatment efficiency is improved.

The invention provides a multi-source data fusion modeling method and system in an aeration process, and is applied to the field of intelligent aeration control in sewage treatment. The method comprises the steps that multi-source time sequence data such as dissolved oxygen, turbidity, flow, temperature, power and pool bottom pressure pulsation signals are collected, dissolved oxygen response lag is calculated through cross-correlation analysis with power change as the reference, time sequence alignment is carried out, and a dissolved oxygen reference interval is predicted by utilizing calibration data in combination with a physical constraint LSTM model; performing spectral analysis on the pressure pulsation signal to extract a gas-liquid coupling characteristic value, and generating a cooperative regulation instruction of the frequency of the blower and the rotating speed of the stirrer based on the information; by means of the scheme, control oscillation caused by lag of the dissolved oxygen sensor can be effectively overcome, online monitoring of bubble form distribution is achieved, the gas-liquid mass transfer efficiency is improved, invalid aeration is avoided, and system energy consumption is remarkably reduced on the premise that stable effluent quality is guaranteed.

The invention provides a sewage treatment system and method based on a large language model and multi-agent collaboration, and the system comprises a sensor network which is used for collecting the water quality parameters of sewage in real time; the monitoring agent is used for performing data verification on the water quality parameters; the at least one edge computing node is used for performing data preprocessing on the water quality parameters; the cloud decision intelligent agent is used for generating a sewage treatment strategy according to the preprocessed water quality parameters based on a large language model; the execution agent is used for executing the sewage treatment strategy and treating the sewage; the evaluation agent is used for analyzing and evaluating the sewage treatment effect and feeding back the sewage treatment effect to the cloud decision agent so as to optimize the sewage treatment strategy; by constructing an intelligent and dynamic treatment system, real-time monitoring, intelligent analysis and self-adaptive treatment of the mariculture sewage are realized, so that the sewage treatment stability and environmental protection benefits are improved, and the sustainable development of the mariculture industry is promoted.

The invention relates to the technical field of sewage treatment, in particular to a sewage treatment aeration control method and system.The method comprises the steps that according to collected historical data, abnormal values are removed through intelligent calculation in combination with optimization and correction, an accurate sample data set is obtained and then classified through a clustering model, and all classifications are subjected to training and verification testing; a trained BP neural network model is obtained, a follow-up controller outputs accurate aeration quantity through the BP neural network model according to latest data to control each aeration device, and the increase / decrease of the air quantity of the biochemical pool is automatically adjusted; the blast volume of the biochemical pool is controlled and the air volume matching working condition is controlled according to the inlet water quality and the water volume, so that the control precision of the aeration rate in the sewage treatment process can be effectively improved, the energy consumption waste is reduced, the process control efficiency is improved, the air volume of the biochemical pool under different working conditions is ensured to be at the optimal value, the outlet water quality stability and the standard-reaching rate are ensured, and the power consumption cost is reduced; the method is suitable for sewage treatment plants of various types and scales, and has a wide market application prospect.

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 provides an intelligent aeration optimization control method and system for a sewage plant, and relates to the technical field of sewage treatment.The method comprises the steps that water quality, water quantity and aeration quantity data are collected in real time; analyzing and processing the data of the water quality, the water quantity and the aeration quantity to form a sewage treatment process data set which comprises the change rate of a water quality index, the fluctuation condition of the water quantity and aeration efficiency information; and according to the sewage treatment process data set, establishing and training a dynamic mathematical model in the sewage treatment process to reflect the relationship among the water quality, the water quantity and the aeration quantity. Real-time monitoring, model prediction and intelligent adjustment technologies are integrated, the aeration control strategy is effectively optimized, the sewage treatment efficiency is improved, the stability of water quality is ensured, and energy conservation and environmental protection are promoted.

The invention discloses a gas self-excitation modulation device, an enhanced pollution aeration treatment system and an application method of the enhanced pollution aeration treatment system, through the arrangement of the gas self-excitation modulation device, intermittent modulation airflow matched with an orifice bubble generation process is formed, the instantaneous pulse acting force for upward separation of bubbles is increased, the bubble generation time is shortened, and the aeration bubble size is reduced; and the mass transfer rate of the gas-liquid interface is further improved. According to the invention, the existing laid aerator does not need to be replaced, the aerator material does not need to be modified, and the method is widely applicable to microporous aerators in any form; a water phase does not need to be driven to flow, so that energy consumption is greatly reduced, and adverse disturbance to a target water body is avoided; compared with a gas dissolving method and a jet flow air entraining method, the technology only drives a gas phase to enter a liquid phase, energy is saved, and meanwhile full-amount treatment of target liquid can be achieved. In addition, through sectional arrangement of the oscillation cavity self-excitation unit and the outflow unit, batch application can be carried out.

The invention discloses an intelligent dosing system and method based on machine learning, and the method comprises the steps: S1, collecting fluidized bed operation parameters and water quality characteristic data in real time, including water flow dynamic parameters, water quality index parameters and particle morphology parameters, and constructing a time sequence characteristic database; s2, constructing a dynamic dosing model based on the fluidized bed by using data in the time sequence characteristic database, and performing joint prediction on the medicament type, the dosing amount and the operation parameters; s3, according to a prediction result output by the model, controlling the agent dosage, the agent concentration, the water flow speed and the aeration intensity; and S4, monitoring the fluidized bed and dosing control parameters in real time, and dynamically correcting the fluidized bed parameters in combination with the effluent turbidity of the fluidized bed and the particle sedimentation efficiency, so as to solve the problems that the sewage treatment effect in the prior art is poor, and medicament waste, substandard treatment and secondary environmental pollution are possibly caused.

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.

The invention provides a sewage AI intelligent management and control system based on a neural network algorithm, which comprises multi-source data acquisition units, an algorithm processing unit and an execution feedback unit, and is characterized in that the multi-source data acquisition units are deployed at a water inlet and a water outlet of a sewage treatment assembly line and in a biological reaction tank; comprising a fast parameter detection array composed of a pH sensor, a conductivity sensor, a dissolved oxygen sensor, a turbidity sensor, a temperature sensor and an ORP sensor. The process state monitoring group consists of an aeration equipment rotating speed sensor, a reflux pump flowmeter and a sludge concentration meter; the fast parameter detection array and the process state detection group are connected with the edge computing node through an industrial bus, perform sliding window mean filtering preprocessing on original data, generate regulation and control instructions of aeration rate, reflux ratio and sludge discharge frequency through model calculation, and send the regulation and control instructions to the execution unit; the complete refined AI intelligent control sewage treatment system based on the neural network algorithm is realized.

The invention relates to the technical field of sewage treatment, in particular to aerobic granular sludge integrated sewage treatment equipment which comprises an aerobic tank, and the aerobic tank comprises an outer tank body and an inner tank body; a turntable is rotationally mounted on the inner bottom surface of the inner tank body, and a plurality of groups of aeration mechanisms are also fixedly mounted on the turntable; the aeration mechanism comprises an aeration assembly, a dredging assembly is arranged on the aeration assembly, and a pressing assembly used in cooperation with the dredging assembly is arranged on the inner wall of the inner tank body; a driving mechanism is fixedly mounted on the top surface of the inner tank body and is in transmission connection with the periphery of the hollow shaft; a transmission assembly is arranged on the periphery of the hollow shaft and is in transmission connection with a plurality of floating foam cleaning assemblies. According to the sewage treatment device, the floating foam cleaning step can be transferred into the settling zone in the sewage treatment process, and cleaning is relatively easy. The dredging assembly is sequentially and periodically pressed by the pressing assembly, so that the aeration assembly is periodically and automatically dredged.

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 invention relates to the technical field of sewage treatment, in particular to a dissolved oxygen control method and system applied to an aeration system, and the method comprises the following steps: based on a preset data acquisition frequency, obtaining water quality parameter information of inlet water and the inside of an aeration tank, and arranging at least two groups of water quality parameter information according to a time sequence to obtain a time sequence water quality characteristic set; performing dynamic aerobic evaluation on the time sequence water quality characteristic set to obtain a dynamic dissolved oxygen range; dividing a plurality of time windows according to the initial sewage treatment regulation and control instruction, and determining a target dissolved oxygen range and an aeration energy consumption constraint in each time window; calculating a dissolved oxygen real-time gap between the dynamic dissolved oxygen range and a target dissolved oxygen range in the corresponding time window; carrying out constraint coupling analysis on the dissolved oxygen real-time notch and the aeration energy consumption to obtain real-time aeration control parameters, and adjusting an aeration system according to the real-time aeration control parameters; the problem of underexposure or overexposure caused by lagging adjustment can be avoided, and meanwhile energy waste caused by frequent overshoot is reduced.

The invention relates to the technical field of sewage treatment control, in particular to a sewage treatment control system based on data analysis. The system comprises a data acquisition module, a water quality prediction module, a dynamic adjustment module and an energy-saving feedback module. The data acquisition module acquires water quality historical data, environmental factor data and sewage flow data, the water quality prediction module is used for establishing a long-short term memory network model for predicting the water quality change trend, and the dynamic adjustment module is used for analyzing the relationship between water quality indexes and equipment operation parameters by using a Pearson's correlation coefficient analysis method. An energy-saving feedback module is adopted; a genetic algorithm is adopted to find an optimal operation combination among the devices; feedback adjustment is performed on the aeration rate, the water pump flow rate and the stirring speed parameters of the dynamic adjustment module, so that when the water quality changes, the operation parameters of the devices are adjusted in time, and the sewage treatment effect is ensured; and energy consumption is reduced.

The invention discloses a self-adaptive intelligent device system for water ecological restoration and water quality improvement, and particularly relates to the field of water ecological restoration, the self-adaptive intelligent device system comprises a monitoring module, a control module, a restoration module, an energy supply module and a remote communication module, and the modules are connected through signals; the monitoring module is used for monitoring the temperature, the pH value, the dissolved oxygen, the turbidity and the nutritive salt content of the water body in real time as well as the water level change, the water flow speed and the meteorological conditions; the control module analyzes and processes the monitoring data, automatically generates a control instruction according to a preset target and rule, and adjusts the operation parameters and the working state of the repair module; the restoration module is used for restoring the water body; the energy supply module is used for providing stable and reliable energy supply for the whole device system. The change trend of the water quality parameters can be predicted in advance, so that the system can take measures in advance, manual intervention is reduced, and the automation degree and the operation efficiency of the system are improved.

The invention provides a sewage treatment progress monitoring method and system, and the method comprises the steps: collecting and processing a first water quality parameter value of a key node of a sewage treatment facility in a historical time period, constructing a dynamic model of a sewage treatment process through a deep neural network, and introducing a genetic algorithm to optimize the structure and parameters of the dynamic model. An optimized dynamic model is obtained, the optimized dynamic model is used for predicting the sewage treatment effect, and a prediction result and operation data of the sewage treatment facility are obtained; using a fuzzy logic control algorithm to adjust the operation parameter setting value of the sewage treatment system, and using a support vector machine algorithm to classify and identify the fault mode of the sewage treatment system to obtain a fault classification result; based on the prediction result, the operation data, the optimized operation parameter setting value and the fault classification result, a comprehensive monitoring management system based on the cloud platform is constructed; according to the invention, comprehensive monitoring and fault identification of the sewage treatment process are realized, and efficient, stable and reliable operation of sewage treatment is ensured.

The invention discloses a sewage filtering device for river regulation and a treatment method, and relates to the technical field of sewage filtration, the sewage filtering device comprises an outer box body, a filtering part, a collecting part and a medicine treatment part, the filtering part comprises a filtering belt, the collecting part comprises a collecting box, and a plurality of connecting pipes are arranged at the bottom end of the collecting box; a switching mechanism is arranged in the outer box body, the medicine treatment component comprises a water pump, a first liquid box, a second liquid box and a medicine liquid box, a first control mechanism is arranged in the second liquid box, and a second control mechanism is arranged in the first liquid box. The multiple collecting boxes are arranged on the mounting rotating shaft, the collecting boxes can be conveniently and automatically switched, solid impurities in the collecting boxes can be conveniently extruded and dewatered in the switching process, chemicals can be conveniently and automatically added into the second liquid box by arranging the chemical adding assembly, and through an aerator, the chemical can be conveniently and rapidly added into the second liquid box. The sewage and the medicament can be conveniently and fully mixed.

The invention relates to the technical field of sewage treatment, in particular to a coupling control system and method for deep denitrification of sewage, and the system comprises a real-time water quality monitoring module, a microorganism twinborn modeling module, a real-time prediction module, an intelligent decision module, an execution mechanism module and a prediction regulation and control module. Compared with the prior art that a passive feedback control strategy based on an effluent quality index is generally adopted, the hysteresis quality is high, and violent fluctuation of an inflow load cannot be coped with; according to the method, a digital twinborn body capable of reflecting the functional state of a microbial community in real time is constructed, and a control target is improved from a traditional process parameter set point to direct optimization of microbial ecological functions; according to the invention, the method achieves the fundamental crossing from the control of technological parameters to the regulation and control of microbial ecology, can carry out intervention from the root of the reaction process, enables the system to have the active health management capability, and remarkably improves the stability of the treatment efficiency and the intelligent level of coping with complex working conditions.

The invention discloses a sewage treatment plant greenhouse gas optimization control method and device and a storage medium, and relates to the technical field of environmental protection, and the method comprises the steps: discretizing a sewage treatment process of an aeration tank into a plurality of complete mixing reactors connected in series, and constructing a sewage treatment process mechanism model based on an activated sludge model; optimizing parameters of the sewage treatment process mechanism model according to the target greenhouse gas concentration spatial distribution data, the target greenhouse gas emission flux and the water quality spatial distribution data to obtain a digital twinborn model; based on a digital twinborn model, a dissolved oxygen set value of each complete mixing reactor partition in an aeration tank is used as a decision variable, a multi-objective evolutionary algorithm is adopted for solving, a Pareto optimal control strategy is generated, and the technical problem that in the prior art, an optimal control strategy of greenhouse gas is not accurate is solved. And precise quantification and collaborative optimization control of greenhouse gas emission are realized.

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 relates to the technical field of sewage treatment, in particular to an aerobic aeration treatment system for plateau domestic sewage treatment, which comprises a pretreatment unit, a biological treatment unit, an advanced treatment unit and a recycling unit which are connected in sequence, the system further comprises a data acquisition module, an aerobic aeration intelligent regulation and control module, a biochemical environment constant-temperature maintenance module, a carbon-nitrogen proportion and backflow dynamic regulation and control module, a digital twinning and sludge characteristic simulation module and an energy collaborative scheduling module. Compared with the prior art which adopts a standard aeration strategy and cannot adapt to the special environment of low air pressure and low oxygen partial pressure of the plateau, the system can accurately adapt to the plateau environment by integrating real-time atmospheric pressure and water temperature monitoring, dynamically calculating the oxygen saturation solubility and correcting the aeration control target according to the oxygen saturation solubility, so that the aeration control target is optimized. Stable supply of dissolved oxygen required by biochemical reaction is ensured, and the technical bottleneck of low efficiency of traditional sewage treatment in plateau regions is fundamentally overcome.

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 discloses wastewater treatment equipment and method used in a starch sugar production process, and belongs to the technical field of starch sugar production wastewater treatment. The shell comprises an inner shell and an outer shell, the bottom of the outer shell is fixedly provided with a drainage valve, the top of the inner shell is fixedly connected with a fixing frame, the fixing frame is fixedly provided with a power mechanism, the outer wall of the top of the inner shell is provided with a scum collecting mechanism, the bottom of the inner shell is fixedly provided with a cleaning cavity, and the side wall of the cleaning cavity extends outwards to form a blow-off pipe; a cleaning mechanism is fixedly arranged on the cleaning cavity, a filter cavity is fixedly arranged at the upper part of the cleaning cavity, a rotary filter screen is rotationally connected in the filter cavity, and an aeration disc is fixedly arranged at the top of the filter cavity. By arranging the power mechanism, when the driving motor rotates forwards and rapidly, rapid and efficient mixing of wastewater and a flocculating agent is promoted, and when the driving motor rotates backwards and rotates slowly, aeration operation is carried out in cooperation with the aeration disc, and soluble organic substances in the wastewater are removed. The method is mainly used for treating the starch sugar production wastewater.

The invention discloses a precise sewage aeration method, and relates to the field of water, wastewater, sewage or sludge treatment, the method comprises a feed-forward model and a feedback model, the feed-forward model collects historical data of aeration tank operation parameters, environmental parameters and oxygen demand, and a decision tree is iteratively generated to correct errors and determine a target dissolved oxygen value; the feedback model corrects the target dissolved oxygen value according to the aeration tank dissolved oxygen concentration and the mixed liquid suspended solid concentration; and controlling the power of the aeration equipment according to the target dissolved oxygen value. Through common coordination of the feedforward model and the feedback model, accurate aeration of sewage treatment is realized.

The invention discloses a sequencing batch aerobic granular sludge reactor, and relates to the technical field of sewage treatment, the sequencing batch aerobic granular sludge reactor comprises a reaction tank, the interior of the reaction tank is divided into an upper aerobic granular sludge reaction cavity and a lower anoxic standing cavity through a partition plate; the sequencing batch water supply mechanism comprises a water feeding barrel, a sliding sleeve is fixedly connected to the middle of a partition plate, the inner side of the sliding sleeve is vertically and slidably connected with the water feeding barrel, and the water feeding barrel is fixedly connected with the sliding sleeve; the bottom end of the water feeding cylinder is fixedly connected with the middle part of a piston circular plate; the peripheral side of the piston circular plate is in sliding connection with the inner wall of the anoxic standing cavity; according to the sequencing batch type aerobic granular sludge reactor, a sequencing batch type sewage treatment process is adopted, sewage treatment steps are compact, when clear water is discharged, the situation that sewage entering the bottom of the aerobic granular sludge reaction cavity is mixed with clear water on the upper layer due to the fact that a mud filtering layer is scattered can be avoided, and the sewage treatment effect can be ensured.

The invention discloses a method for reducing saline-alkali water into modern seawater suitable for culturing various seafoods by using microorganisms, a special fish fertilizer for the method and application of a preparation method of the special fish fertilizer, and the method comprises the following specific steps: 1, pretreating the saline-alkali water: pumping saline-alkali with the salinity of 15-30% o into a culture pond, compressing, mixing and precipitating until the pH value is 7.3-7.5; 2, performing microbial culture: performing multi-stage enrichment on halobacterium violaceum and selecting dominant colonies; the method comprises the following steps: mixing underground saline-alkali water with the salinity of 10-20% o, saline-alkali water of a salt lake with the salinity of 180-200% o and high saline-alkali soil containing part of organic matters, cooking and sealing at the temperature of 200-210 DEG C, inoculating selected mixed halobacterium purple, pumping air, culturing with sunlight, and propagating for later use, wherein the pH value is 8.3-8.5; 3, reduction reaction: carrying out reduction reaction in a static water environment, when the water body is red brown or dark brown, inoculating a heterotrophic photosynthetic bacteria liquid and an autotrophic photosynthetic bacteria liquid with concentration, inoculating yeast powder, carrying out common reaction, then inoculating a special aquaculture fish fertilizer preparation, carrying out oxygenation reaction, and adjusting the pH value to 8.5-8.8; real seafood can be cultured in saline-alkali water in deserts and gobi deserts, zero pollution and zero emission can be achieved, the cost of development, implementation and popularization is low, and the cost of 10,000 cubic meters of water is only 675 yuan.

The invention relates to the technical field of rural sewage treatment, and discloses a rural sewage intelligent monitoring and aeration regulation and control system based on Internet of Things. The system comprises a pollution parameter sensing layer, a pollution index analysis layer, an aeration path generation layer, a process parameter matching layer, a dynamic monitoring focusing layer, a cross-modal mapping layer, an equipment scheduling decision-making layer and an aeration parameter generation layer. Wherein the pollution parameter sensing layer collects operation parameters in real time by means of a multi-source sensing terminal; the pollution index analysis layer divides pollution parameter intervals and calculates a distribution coefficient; the aeration path generation layer generates an aeration intensity grading path in sequence; the process parameter matching layer outputs a process deviation parameter set; dynamically monitoring a focusing layer to adjust the density of monitoring points; the cross-modal mapping layer establishes space-time correlation mapping of water quality parameters and aeration intensity; the equipment scheduling decision-making layer sorts the calling sequence of the aeration equipment; and the aeration parameter generation layer converts the parameters into executable regulation and control parameters. The system realizes intelligent monitoring of rural sewage and accurate aeration regulation and control.