3424results about "Treatment control/steering" patented technology

The invention relates to the technical field of sewage treatment, and particularly discloses a sewage and wastewater treatment control system and method based on an intelligent optimization algorithm. Water quality data are collected through a data acquisition module, and a water quality characteristic matrix is generated through preprocessing. And the prediction module analyzes the feature matrix by using the trained water quality dynamic prediction model to obtain a water quality prediction result. And processing the prediction result by using a multi-objective optimization algorithm to obtain an initial control parameter. And the parameter optimization module calculates a water load fluctuation ratio, a model confidence coefficient and an equipment state according to the sewage and wastewater treatment data, inputs the water load fluctuation ratio, the model confidence coefficient and the equipment state into the adaptive fuzzy network and generates a multi-target parameter optimization suggestion. And the dynamic optimization module adjusts the multi-objective optimization algorithm parameters according to the parameters, and processes the prediction result again to obtain optimization control parameters. And the control module regulates and controls sewage and wastewater treatment according to the optimized parameters. The system realizes closed-loop management from data acquisition, prediction and optimization to control, can dynamically adapt to water quality change, and operates stably and efficiently.

The invention relates to the field of wastewater treatment, and provides an industrial wastewater membrane process intelligent optimization method and system based on multi-dimensional data modeling. The method comprises the following steps: acquiring wastewater quality parameters of a target scene and a production line equipment state in real time through a multi-dimensional sensor network, and constructing a digital twinborn model of a wastewater treatment system in the target scene; the membrane surface pollution type of each node in the wastewater treatment system is identified through a digital twin model, and the inner membrane pollution evolution condition in the future preset duration is predicted; a multi-strategy evolutionary reinforcement learning algorithm is adopted, the wastewater quality parameters, the production line equipment state and the membrane pollution prediction result are combined, multi-target dynamic optimization is conducted on a wastewater treatment system through a multi-agent collaborative decision-making algorithm, an optimization strategy is generated based on the multi-target dynamic optimization result, and membrane process operation parameters and production control parameters are dynamically adjusted. According to the method, real-time intelligent adjustment of membrane process operation can be realized, the stability of membrane process operation is guaranteed, and the treatment efficiency of membrane process operation is improved.

The present invention relates to the technical field of the control of wastewater treatment devices. Disclosed is an intelligent control method for wastewater treatment devices at a dry bulk cargo terminal, which is used for solving the problem of poor control of wastewater treatment devices at a terminal. The method comprises the following steps: installing a plurality of types of sensors at key locations of a dry bulk cargo terminal, and using edge computing nodes to perform real-time data collection and preprocessing; on the basis of historical features and temporal features, using a machine learning model to perform wastewater type classification, thereby realizing efficient dynamic adjustment of operating parameters of wastewater treatment devices; then, by means of weighted voting and confidence evaluation, integrating a plurality of classification results to ensure an optimal treatment effect; and analyzing actual wastewater treatment conditions to continuously optimize device control, thereby preventing faults, extending the service life of devices, and improving the wastewater treatment effect.

The disclosure relates to an intelligent dosing control method, device and system for softening and removing hardness. Based on calculation by the intelligent dosing control method or device for softening and removing hardness of the disclosure, a softening agent dosing scheme can be intelligently recommended, while allowing the dosage adjustment in real time, thereby realizing the real-time and precise dosing of agents throughout the process. The intelligent dosing control system for softening and removing hardness of the disclosure automatic monitors the inlet water quality, and the dosing device can be controlled to perform precise dosing of agents through the calculation by the intelligent dosing control method or device for softening and removing hardness. Based on the monitoring feedback of outlet water quality and then calculation by the intelligent dosing control method and / or device for softening and removing hardness, the agent dosage can be automatically readjusted.

The invention discloses a precise phosphorus removal control method for a high-efficiency sedimentation tank based on a magnetic medium, and relates to the technical field of sewage phosphorus removal. The method comprises the following four steps: carrying out real-time water inlet parameter acquisition on a magnetic powder feeding tank, a mixing tank, a flocculation tank and an efficient sedimentation tank, carrying out multivariable dynamic modeling to cooperatively calculate the agent feeding amount, and carrying out agent feeding and water outlet parameter feedback regulation. The method comprises the following steps: monitoring the flow of inlet water, the total phosphorus concentration and the suspended matter concentration in real time, establishing a quadratic polynomial model of the total phosphorus removal rate by combining the interaction formed by sequentially mixing magnetic powder, a flocculating agent and a coagulant aid with sewage to react, and dynamically calculating the theoretical dosage of the three agents; monitoring and feeding back the total phosphorus concentration and the suspended matter concentration of effluent at a water outlet end, and dynamically adjusting the dosage of the medicament according to the total phosphorus concentration and the suspended matter concentration; precise adding of a dephosphorization agent is achieved, the dephosphorization effect is improved, the operation cost is reduced, and the automation level is improved. The problems that in an existing sewage precipitation phosphorus removal process, the agent adding amount is difficult to accurately control, and the automation degree is low are solved.

The invention discloses an intelligent monitoring system for sewage treatment in the coal chemical industry, and relates to the technical field of sewage treatment.The intelligent monitoring system is characterized in that a water quality monitoring unit is used for collecting parameters such as COD, turbidity, pH and heavy metal ion concentration in real time, the change trend of water quality in a short time is predicted through a long-short term memory (LSTM) network, and then adding parameters of a flocculating agent are dynamically calculated; the defects of a fixed adding curve or artificial experience adjustment are overcome, so that the adding amount, the type and the speed of the flocculating agent can be adaptively adjusted to be matched with the change of sewage components; the addition optimization unit is combined with a CNN-LSTM model to analyze the rheological characteristics of the sludge, so that the addition of the flocculating agent adapts to the rheological change of the sludge, the flocculation effect is optimized, and the sludge settling performance is improved; meanwhile, the stirring control unit adjusts the stirring strength and time in real time based on ultrasonic online monitoring data, so that the flocculating agent is fully dispersed, the particle distribution state is optimized, the flocculation reaction is more uniform, and the subsequent precipitation separation efficiency is improved.

The invention provides a zero-discharge treatment process for recycling production wastewater, and relates to the technical field of water treatment and recycling, and the zero-discharge treatment process comprises the following steps: S1, oxidizing and degrading COD through ozone and a Fenton reagent, and generating a flocculatable intermediate; s2, intercepting suspended matters by using a gradient aperture filter bed in a grading manner, and monitoring a dynamic membrane resistance coefficient delta Rm in real time to automatically trigger backwashing; s3, coupling an ultrafiltration reverse osmosis membrane to realize that the organic matter rejection rate eta is greater than or equal to 98%, and synchronously regulating and controlling flux and operation pressure by an online spectrometry; s4, regulating and controlling the current density by adopting a rotational flow electric flocculation reactor for directional crystallization to produce industrial salt with Cl <-> less than or equal to 50mg / L; and S5, based on the total dissolved solid recovery rate TR and the comprehensive energy consumption, establishing a multi-target optimization model for real-time parameter adjustment. According to the method, a membrane pollution early warning and backwashing dynamic response mechanism is constructed through cross-scale cooperative regulation and control of delta Rm and the retention rate eta, and a catalytic oxidation effect strengthening and electric crystallization parameter self-tuning technology is combined, so that the problem of cooperative optimization of high-salinity wastewater salt gradient separation and pollutant deep removal is solved.

The invention discloses a dosing system for pre-oxidation enhanced coagulation in a water plant and an intelligent regulation and control method, and relates to the technical field of pre-oxidation enhanced coagulation water treatment. The system comprises a raw water pump, a mixing tank, a tubular static mixer, a flocculation tank, a sedimentation tank, an industrial personal computer and multiple online detection instruments which are sequentially connected in series, so as to monitor the flow, conductivity, pH value, temperature, turbidity, ultraviolet absorbance and organic matter concentration of raw water. Key water quality indexes are monitored in real time through data collection and a pre-oxidation enhanced coagulation regulation and control system based on machine learning of an industrial personal computer, and intelligent and accurate prediction of the dosage of oxidants (potassium permanganate, permanganate composite agents and potassium ferrate) and coagulants is achieved; the effluent turbidity, the effluent ultraviolet absorbance and the effluent organic matter concentration of the sedimentation tank are fed back in real time, the adding amount of the oxidizing agent and the coagulant is dynamically adjusted through a regulation and control algorithm, the effluent quality is guaranteed, and medicine consumption is reduced.

The invention belongs to the technical field of sewage treatment, and discloses a catalyst monitoring system based on sensing linkage and a control method.The system comprises a mixing pool, a settling pool and a backflow pool which are circularly arranged through pipelines, and further comprises a strong oxidant adding device, a powder catalyst adding device and a controller. According to the technical scheme, through combined use of the sensor, the flow meter and the valve, the problem of high loss rate of the powder type catalyst is solved, the service life of the catalytic reactor is prolonged, and the risk of environmental pollution is reduced. Meanwhile, the invention further discloses a powder type catalyst loss monitoring and controlling method based on the sensor and automatic control, in the method, hierarchical control is adopted on a controller control framework: a bottom-layer MPC is combined with a top-layer PINN prediction model to form a double-layer framework of network prediction and classical control, accurate monitoring and control are achieved, and the reliability of the controller is improved. Therefore, the purposes of reducing the loss rate of the catalyst, improving the stability of the catalytic reactor and prolonging the service life are achieved.

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 relates to an intelligent decision-making method, system, equipment and medium for sewage medicament addition, and the method comprises the following steps: detecting and preprocessing sewage water quality parameters, extracting feature vectors, and carrying out clustering analysis to obtain water quality categories. Historical dosing data is retrieved and subjected to statistical analysis, and an initial dosing scheme is generated; a water quality change curve is obtained by simulating the scheme, and then the optimal dosing scheme is obtained through optimization. And finally, generating and issuing an agent adding control instruction, and executing treatment, so that the technical problems that the traditional agent adding mode mostly depends on artificial experience or simple automatic control, and is difficult to cope with the complex working condition of dynamic change of water quality and water quantity, so that the agent adding is inaccurate, and the agent waste is possibly caused are solved.

The invention belongs to the technical field of water treatment, and particularly relates to a whole-process three-stage linkage control intelligent flocculation dosing method, which comprises the following steps: collection: collecting water quality and water quantity parameters of inlet water and outlet water in real time in the water treatment process; collecting a floc image in the reaction process, analyzing the particle size distribution and the breakage rate of the floc image, and collecting a torque parameter of a stirring device at the same time; according to the invention, multiple types of sensors are deployed in the water inlet area of the flocculation tank, the reaction area and the water outlet area of the sedimentation tank, water quality, water quantity and reaction process parameters are collected in real time, and edge calculation and cloud optimization technologies are combined, so that full-flow intelligent control from agent pre-feeding, reaction process regulation and control to water outlet effect refinement is realized; the method is suitable for scenes such as municipal sewage treatment plants and industrial wastewater treatment stations requiring precise control of flocculant addition, and is especially suitable for water treatment processes with frequent water quality fluctuation and sensitive agent cost, so that the treatment efficiency can be remarkably improved, and the operation cost can be reduced.

The present disclosure provides a cleaning device. The cleaning device includes a cleaning device body, a drive mechanism, a filtering mechanism, a liquid inlet portion, a liquid outlet portion, and a mode switching member. The drive mechanism and the filtering mechanism are disposed on the cleaning device body. The liquid inlet portion includes at least a first water inlet. The first water inlet is provided on the cleaning device body. The liquid outlet portion includes at least a first water outlet. The first water outlet is provided on the cleaning device body. The first water inlet, the filtering mechanism, the drive mechanism, and the first water outlet sequentially communicate to form a first water path. The mode switching member is configured for the cleaning device to be switched between a position on a liquid surface and a position under the liquid surface.

The invention discloses an intelligent purification and circulation method and system for waste water of a motor home, and belongs to the technical field of waste water treatment and reuse. Generating a matrix containing key pollution characteristics based on the parameters; executing multi-stage membrane treatment according to the matrix decision to obtain graded water quality; based on a water quality matching reuse standard, a scheduling scheme is generated by combining requirements and environment adjustment priorities; the scheme and the water network state are combined to optimize water volume allocation, and efficient recycling of recycled water is controlled. According to the invention, dual-mode sensing fusion analysis, dynamic pollution characteristic identification, multi-stage membrane intelligent cooperative processing and a water network balance optimization scheduling strategy are adopted, efficient deep purification, safe grading recycling and intelligent management of motor home wastewater can be realized, and the utilization rate of water resources, the intelligent level of system operation and the user experience are remarkably improved.

The invention discloses an intelligent supervision and regulation system for steam recompression mother liquor wastewater treatment, which relates to the technical field of production monitoring and is characterized in that a plurality of water quality parameters are monitored and analyzed in real time by integrating a water quality monitoring module, a data fusion module, a flow monitoring module, a control center, an automatic regulation module and a feedback control module; the data fusion module uses a machine learning algorithm to train historical data and performs abnormity prediction and water quality fluctuation identification based on real-time data, the control center combines flow and water quality prediction data to calculate the adjustment demand of the wastewater treatment equipment and generate an adjustment instruction, and the automatic adjustment module dynamically optimizes the operation state of the equipment according to the instruction. The feedback control module compares the real-time water quality data with the adjusted water quality, generates a feedback signal and further optimizes an adjustment instruction, so that the accuracy and stability of equipment adjustment in the wastewater treatment process are ensured, deposition or volatilization of heavy metals or organic compounds is effectively prevented, the water quality is ensured to reach the standard, and the environmental influence is reduced.

The invention relates to the technical field of sewage treatment, in particular to a sewage treatment control process based on dynamic regulation and control of aeration and carbon source addition, which comprises the following steps: acquiring microbial metabolism heat change data in real time; biochemical treatment: monitoring the dielectric constant of a water body and the Reynolds number of sewage flow in real time, and constructing a multi-parameter coupling regulation and control model and dynamically regulating and controlling the aeration rate in combination with microbial metabolism heat change data obtained in the pretreatment step; accurately adding the carbon source according to a calculation result of the carbon source demand prediction model; sewage subjected to biochemical treatment is subjected to ultrafiltration through a nanofiber membrane and then subjected to combined disinfection treatment through ultraviolet rays and ozone, treatment parameters are regulated and controlled in real time according to the membrane flux attenuation trend in the treatment process, and dynamic and accurate control over sewage treatment is achieved. According to the method, the problem of energy consumption waste caused by excessive aeration or low degradation efficiency caused by insufficient aeration in a traditional process is solved, and accurate matching of dissolved oxygen supply and microbial requirements is realized.

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 relates to the technical field of industrial wastewater treatment, in particular to an intelligent operation and maintenance system for industrial wastewater treatment, which comprises a wastewater data acquisition module, a wastewater data preprocessing module, a wastewater complex component identification and classification module and a wastewater treatment process scheduling and optimization module, the wastewater data acquisition module acquires water quality monitoring data in wastewater in real time; the wastewater data preprocessing module is used for preprocessing the collected water quality monitoring data; the wastewater complex component identification and classification module realizes optimized classification of wastewater complex components; and the wastewater treatment process scheduling and optimizing module selects a wastewater treatment process, automatically adjusts parameters of the wastewater treatment process and optimizes an operation strategy of wastewater treatment. According to the invention, different pollutant components in the wastewater and dynamic change trends thereof are accurately identified, and the efficiency and precision of wastewater component analysis are significantly improved.

The invention relates to the technical field of circulating water treatment, and discloses a circulating water treatment closed-loop optimization method and system based on water quality prediction.The circulating water treatment closed-loop optimization method based on water quality prediction.The circulating water treatment closed-loop optimization method based on water quality predictioncomprises the steps that a time sequence knowledge graph supporting the time dimension is constructed and used for representing water quality parameters and time sequence evolution characteristics of the relation of the water quality parameters; constructing a multi-time scale prediction engine to predict a future water quality state; developing a predictive constraint generator, and converting future water quality prediction into current decision constraints; a space-time sensitive multi-objective optimization algorithm is introduced, and a medicament proportioning strategy is optimized; a multi-time-scale collaborative optimization system is realized, so that short-term response and long-term stability are further balanced; an environment adaptation active evolution system is constructed, and automatic adjustment of the system along with environment changes is achieved; according to the invention, the fundamental transformation of a circulating water treatment control mode is realized, and a brand new closed-loop optimization normal form is provided for a circulating water treatment system.

The invention discloses a high-pressure soft water medium treatment and supply system, which belongs to the technical field of seawater desalination treatment, and comprises a multi-dimensional ion detection module for detecting the concentration distribution characteristics of target inhibition ions in original seawater to generate a corresponding coating material selection instruction; the electric field dynamic coupling module captures a termination signal according to the coating material selection instruction; the shock wave generation module starts a main pump to generate fluid shock waves to execute sediment breaking action according to the termination signal; the monitoring module is used for monitoring the finally output softened water ion concentration and reversely calculating the pollution index of the coating surface; and the heat cycle feedback device is used for starting a self-cleaning mode according to the pollution index and transmitting waste heat in the cleaning process to the pump set. The electric field dynamic coupling adsorption and fluid shock wave cooperative treatment technology is adopted, high-efficiency ion capture, dynamic sediment removal and waste heat recycling can be achieved, energy consumption is remarkably reduced, and continuous and stable operation of the system is guaranteed.

The invention belongs to the field of oil and gas field high-salinity wastewater treatment, and particularly relates to a shale gas high-salinity wastewater electrochemical catalysis coupling membrane separation low-carbon treatment method which comprises the treatment steps of pretreatment, electrocatalytic oxidation, membrane separation, salt recycling and product recovery, intelligent management and control, energy coupling and the like. The dissolved air flotation unit generates micro-nano bubbles through a venturi-rotational flow coupling device and cooperates with PAC / PAM to realize efficient flotation; softening agents are added into the multi-stage sedimentation tank by stages, closed-loop control is carried out, and soluble barium, boron, fluoride and hardness are removed; the electrochemical oxidation unit strengthens mass transfer through ultrasonic waves and degrades organic matters difficult to treat; the membrane treatment realizes up-to-standard discharge of wastewater through a hollow fiber membrane bioreactor-roll type ultrafiltration membrane-anti-pollution type reverse osmosis membrane integrated system; the magnetic control evaporation crystallizer utilizes the magnetic field gradient and the temperature gradient to cooperatively regulate and control the crystallization process, the membrane separation strong brine is subjected to quality separation treatment, and high-purity salt products are produced. The method provided by the invention can effectively realize up-to-standard discharge treatment of shale gas fracturing flowback wastewater and resource utilization of evaporative crystallization salt, is also suitable for treating shale gas recovery wastewater with similar water quality characteristics, and has good popularization and application prospects.

The invention discloses an intelligent industrial wastewater treatment method based on edge calculation and multi-modal data fusion, which comprises the following steps: synchronously acquiring various data of an industrial wastewater treatment site through edge nodes, automatically adjusting and aligning the generation time of each data, and ensuring that the time error of different data is less than a set threshold value; organically fusing the image features, the chemical parameters and the component analysis report to generate pollutant description features; constructing a simplified simulation model on the edge equipment, and predicting the diffusion trend of the wastewater pollutants by using the simulation model based on the pollutant description characteristics; and when the network is interrupted, the edge equipment is automatically switched to a local mode, and the operation is continued by using the stored model and the wastewater data acquired in real time. According to the method, the simulation model is deployed through the edge equipment, so that the calculation amount can be greatly reduced, the diffusion trend of wastewater pollutants can be accurately predicted, effective treatment measures can be taken in time, and the stability and reliability of an industrial wastewater treatment system are improved.

The invention relates to the technical field of swimming pool cleaning equipment control, and provides a cleaning mode switching method and device for a multifunctional swimming pool cleaning robot. According to the method, water quality data corresponding to a swimming pool, stain distribution images of pool walls and pool bottoms, swimming pool structure size data and stain type data are collected in real time; dividing a cleaning area according to the swimming pool structure size data, generating a stain area marking result in the cleaning area in combination with the stain distribution image and the stain type data, and judging the pollution level of the whole swimming pool according to the water quality data so as to retrieve a corresponding cleaning mode from a preset cleaning mode library, the preset cleaning mode library comprises a global coverage mode, a key enhancement mode, a corner fitting mode and a water quality maintenance mode; and according to the called cleaning mode, a corresponding cleaning path plan and execution instruction is generated, and the driving module, the scrubbing module and the purification module are controlled to work cooperatively. According to the method, accurate analysis of the swimming pool environment is achieved, and blind cleaning of a traditional fixed mode is avoided.

The invention provides a chemical sewage advanced treatment system and method based on multistage membrane separation, and relates to the technical field of chemical sewage treatment.The method comprises the steps that pollution load data under preset membrane flux is collected, and the cascade reflux amount in the current membrane separation process is determined through the pollution load data and a real-time pressure index during membrane separation filtration; according to the separation interference deviation, the steady-state filtering period of the membrane separation filtering grade in the constant flux change is predicted, the steady-state filtering period is synchronously screened, and the full-flow separation limit of the multistage membrane separation unit in different pollution loads is obtained; and generating a separation regulation and control index when the equivalent flux generates peak offset according to the cascade reflux quantity and the full-flow separation limit, and performing starting point triggering on the treatment flow of the multistage membrane separation sewage and dirt. Under the dynamic working condition of operation of the multistage membrane separation system, balance adjustment can be carried out on the advanced treatment process trigger of the chemical sewage, so that the standard-reaching rate of membrane separation chemical sewage advanced treatment is increased.

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 provides a low-carbon high-efficiency biochemical system control method and system. The system comprises an internal reflux control module, a carbon source adding module and a precise aeration module, the internal reflux control module is used for refluxing nitrate nitrogen required to be denitrified to the anoxic tank for denitrification, so that the effect of removing total nitrogen is achieved; the carbon source adding module is used for providing the current required dosage through online nitrate nitrogen instruments arranged in an anoxic tank and an aeration tank according to dynamic nitrate nitrogen value comparison and variation trend comparison at the tail end of the anoxic tank, so that the carbon source adding amount is accurately controlled; and the accurate aeration module reads the real-time numerical value of ammonia nitrogen at the tail end of the aeration tank, performs mean value calculation on the numerical value in each period, performs difference value calculation on the average value of ammonia nitrogen in the current period and the average value of ammonia nitrogen in the last period, and reaches the numerical value of dissolved oxygen through frequency adjustment of an aeration fan to run in a required operation interval. The control method of the low-carbon high-efficiency biochemical system aims to realize low-carbon high-efficiency accurate control of the biochemical system, aeration as required, addition of an external carbon source and control of internal reflux.

The invention discloses an intelligent control method and system for muddy water treatment of a muddy water shield tunnel, and relates to the technical field of muddy water treatment.The method comprises the steps that physical characteristic data and chemical characteristic data of muddy water are collected in real time, preliminary treatment is conducted through edge computing nodes, and standardized muddy water characteristic data flow is output; carrying out preliminary screening operation on muddy water according to an intelligent separation strategy, and screening out medium-particle impurities; through self-adaptive dynamic vortex regulation and control, the muddy water rotational flow speed and the muddy water pressure are regulated, and medium particle impurities are subjected to rotational flow separation; carrying out deep separation treatment on medium-particle impurities subjected to cyclone separation, and outputting clear water and deposited mud cakes; clear water flows back to the shield tunneling machine through pumping equipment to be recycled, and deposited mud cakes are subjected to dehydration treatment. According to the invention, medium particle impurities are accurately separated according to the change of muddy water characteristics by utilizing a regulation and control method of dynamically adjusting the rotational flow speed and pressure, so that the muddy water separation efficiency is effectively improved, and the energy consumption is reduced.

The invention discloses a real-time sewage treatment method and system based on sewage data monitoring, and relates to the technical field of sewage treatment.The method comprises the steps that historical sewage data and sewage data are obtained through a sensor and preprocessed; constructing a change trend prediction model based on the historical sewage data, and analyzing the sewage data; predicting the pollutant concentration value of the specific pollutant concentration in a period of time in the future; according to the predicted pollutant concentration value, calculating the type and the accurate proportion of the medicament needing to be treated; and training and optimizing the model according to a processing effect evaluation result, and adjusting model parameters. According to the method, the defect that chemicals are put according to experience in traditional sewage treatment is overcome, the accurate dosage of the oxidizing agent can be calculated according to the accurate concentration of the organic pollutants when sewage containing the organic pollutants is treated, effective removal of the organic pollutants is guaranteed, waste of the chemicals is avoided, and the treatment efficiency and stability are improved.

The invention provides a method and a system for intelligently interactively controlling water production equipment. Wherein heavy metal ion concentration data is collected in real time through a multi-node sensing array, concentration difference fluctuation of adjacent monitoring points is analyzed, and a pollutant diffusion track is deduced; when the monitoring data exceeds the standard, switching of a standby water source is triggered based on a diffusion trajectory analysis result, and a reverse cleaning instruction is generated in combination with the dynamic ratio of the concentration gradient change rate to the diffusion speed; dynamically correcting the concentration deviation by utilizing fluid mechanics parameters in a high-pressure impact process in cooperation with multi-dimensional sensor data, and generating environmental response type pollution grade parameters; finally, a pollutant migration path in the three-dimensional diffusion model is matched according to the pollution level, a decision signal containing emergency water source coordinates and the cleaning priority is output, and full-process closed-loop intelligent control from pollution monitoring to emergency decision is achieved. According to the technical scheme provided by the invention, the response speed and the disposal accuracy of the water quality sudden pollution event are improved.

The invention discloses a sewage treatment method, system and device based on a neural network model and a medium, and relates to the technical field of sewage treatment.By monitoring water quality parameters such as inflow total phosphorus concentration in real time, neural network model input data are preset to always reflect the current actual working condition instead of prediction based on outdated or fixed data, and the accuracy of sewage treatment is improved. The timeliness and accuracy of dosing amount prediction are ensured, and the hysteresis of traditional off-line detection is eliminated to realize real-time regulation and control. A plurality of treatment schemes are obtained by generating different combinations of dissolved gas amount and hydraulic retention time, each treatment scheme corresponds to different minimum dosage, and on the premise of ensuring that the sewage treatment effect meets the effluent total phosphorus concentration limit value, the treatment scheme corresponding to the minimum sewage treatment cost is taken as a target scheme, so that the sewage treatment efficiency is improved. According to the decision-making mode based on cost optimization, the most economical operation scheme can be selected from a plurality of feasible schemes, so that the sewage treatment cost is effectively reduced on the premise that the total phosphorus concentration requirement of effluent is met.