17070results about "Sustainable biological treatment" patented technology

The invention provides an intelligent sewage treatment process optimization method and system. The method comprises the following steps: continuously collecting the flux attenuation rate, transmembrane pressure difference and pollutant spectrum data of a ceramic membrane, carrying out time sequence analysis, constructing a pollution accumulation dynamic model, and predicting a critical threshold value; when a threshold value is reached, triggering an ultrasonic cavitation device, adjusting high-frequency vibration to generate a microbubble group, stripping pollutants by utilizing shock waves, and calculating membrane flux recovery data; fusing the spectral data and the recovery data to extract an actual pollution stripping efficiency value, and comparing a theoretical value to obtain a difference proportion; if the actual value is lower than the theoretical value, the cleaning period is shortened, the fluid pressure is increased to strengthen the stripping effect, and meanwhile, dynamic model parameters are reversely corrected based on the pressure adjustment amplitude to form closed-loop regulation and control. According to the invention, intelligent prediction, self-adaptive cleaning and closed-loop optimization of ceramic membrane pollution are realized, the sewage filtering efficiency is improved, and the energy consumption and cleaning cost are reduced.

The invention discloses an intelligent regulation and control method and system for sewage treatment and a program product, and relates to the technical field of sewage treatment.The method comprises the steps that a multi-modal water quality sensing network is constructed, and sewage quality parameter information and overall treatment target numerical value information are obtained; according to the equipment operation state and the overall treatment target numerical value information, sewage treatment process parameters are generated, and treatment units in the sewage treatment system are distributed in a plurality of areas; triggering a process regulation and control instruction according to the sewage treatment process parameters and the overall treatment target numerical value information; obtaining partition processing effect detection information, and comparing the partition processing effect detection information with the corresponding index value to obtain a partition difference value; if the partition difference value exceeds a preset change threshold range, triggering a partition self-adaptive regulation and control updating instruction; obtaining partition adjustment parameter information according to the partition self-adaptive regulation and control updating instruction; and triggering an adjustment instruction. The invention provides an intelligent regulation and control method based on multi-dimensional perception and adaptive decision.

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 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 discloses a low-temperature-resistant heterotrophic nitrification-aerobic denitrification pseudomonas and application thereof, and belongs to the technical field of microorganisms, the strain of the pseudomonas is pseudomonas JL-1 (Pseudomonas silesiensis JL-1), the pseudomonas silesiensis is preserved in China General Microbiological Culture Collection Center on August 23, 2024, and the preservation number is CGMCC NO: 31730. The invention further discloses a preparation method of the low-temperature-resistant heterotrophic nitrification-aerobic denitrification pseudomonas and an application of the low-temperature-resistant heterotrophic nitrification-aerobic denitrification pseudomonas for the low-temperature-resistant heterotrophic nitrification-aerobic denitrification pseudomonas for the low-temperature-resistant heterotrophic nitrification-aerobic denitrification pseudomonas for the low-temperature-resistant heterotrophic nitrification-aerobic denitrification pseudomonas. The JL-1 strain can still effectively carry out nitrification and denitrification processes at the temperature as low as 5 DEG C, the JL-1 strain is especially suitable for sewage treatment in cold regions due to the efficient denitrification characteristic in the cold environment, and the problem that a traditional sewage treatment strain is insufficient in denitrification efficiency under the low-temperature condition is solved. Under different temperatures and conditions, the JL-1 can significantly remove nitrate nitrogen and ammonia nitrogen in a water body, the nitrogen removal rates exceed 90% under the conditions of 5 DEG C and 10 DEG C, and extremely high nitrogen removal efficiency is shown.

A sewage treatment system based on aerobic granular sludge is disclosed, which includes a sewage treatment tank (1), a water distribution and aeration integrated mechanism and a water distribution and aeration switching control mechanism. The sewage treatment tank (1) includes a tank body (11), a top cover (13) is fixedly connected to a top opening of the tank body (11), and a clear water overflow port is arranged at a top side of the tank body (11). The water distribution and aeration integrated mechanism includes a first slip ring (21), a limit water retaining sleeve (220) is fixedly connected to an inner bottom of the tank body (11) through a water retaining sleeve mounting assembly, and a mixing section (212) of a water distributor body is vertically and slidably connected in the limit water retaining sleeve (220).

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 relates to the technical field of data processing, and discloses a heterogeneous data regularization method for multi-source information fusion, which comprises the following steps of: arranging distributed sensors in a plurality of processing stages in a sewage treatment process, and synchronously acquiring detection data of all the distributed sensors through an access protocol and a time sequence; performing semantic analysis on the detection data, performing label normalization on the detection data, and completing semantic label standardization; processing the detection data after semantic standardization to obtain metadata; constructing a data cross-layer representation model based on transfer learning, and performing feature extraction and semantic embedding on metadata to obtain uniform vectorization expression; and according to the vectorization expression, constructing an information knowledge graph oriented to the whole flow of sewage treatment. Unified vectorization expression of time sequence, semantics and structural features among different data sources is achieved, and the fusibility, interpretability and usability of data are improved.

The invention discloses a short-cut denitrification-anaerobic ammonia oxidation system and an intelligent regulation and control method thereof, and belongs to the technical field of intelligent regulation and control of sewage treatment. Comprising the following steps: constructing and processing a machine learning data set to obtain a training set and a test set; based on the training set, a prediction model is established through a machine learning method, and prediction performance is evaluated to select an optimal prediction model; performing importance analysis on the data in the data set as feature data, and identifying key features; and taking the key features as optimization regulation and control parameters, and constructing an optimal control strategy through a particle swarm optimization algorithm. Compared with the prior art, the method has the beneficial effects that a system denitrification performance prediction model is constructed and optimized by utilizing a machine learning method by utilizing a large number of system operation parameters, microbial community structures and other multi-dimensional data, the operation characteristics of the system are fully reflected, and a unique optimal control strategy is designed and formed aiming at a specific scene; and the adaptability of the strategy is improved.

The invention relates to the technical field of microorganisms, and provides a low-temperature-resistant heterotrophic nitrification-aerobic denitrification pseudomonas and application thereof, the strain is pseudomonas (Pseudomonas sp.) SW1, and the preservation number is CCTCC (China Center for Type Culture Collection) NO: M 20221797. The low-temperature-resistant heterotrophic nitrification-aerobic denitrification bacterium Pseudomonas sp. SW1 has the characteristic of low temperature resistance, can well grow at 4-10 DEG C, and has relatively strong heterotrophic nitrification-aerobic denitrification nitrogen removal capability, and the enrichment culture of the strain is carried out in a relatively low nitrogen source, and the condition is extremely consistent with the application scene of the strain in domestic sewage.

The air supply type jet aerator comprises a water inlet pipe, one end of the water inlet pipe is connected with an air inlet unit through a first connecting pipe, and the end, away from the first connecting pipe, of the air inlet unit is connected with a second-stage mixing pipe through a second connecting pipe; the end, away from the second connecting pipe, of the second-stage mixing pipe is connected with a third-stage mixing pipe through a third connecting pipe, the end, away from the third connecting pipe, of the third-stage mixing pipe is connected with a spray head through a fourth connecting pipe, the inner wall of the water inlet pipe is connected with a loop assembly, and the inner wall of the second-stage mixing pipe is connected with a contraction unit. And the inner wall of the third-stage mixing pipe is connected with a turnover crushing mechanism. The invention also discloses a jet aeration method of the air supply type jet aerator with porous air inlet and compression circulation. The air supply type jet aerator solves the problem that the existing air supply type jet aerator is easy to cause sludge bulking.

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, 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 sewage denitrification dosing method and system based on machine learning and a storage medium, and belongs to the technical field of sewage treatment.The method includes the steps that data are collected and preprocessed, and variable data influencing biochemical pool carbon source dosing behaviors are obtained; and lagging influence of carbon source input on the denitrification amount index is analyzed, and the duration time range of the drug effect is determined. And adopting the trained prediction model, and based on the denitrification amount index and the prediction variable of the future t + X period, obtaining the dosage of the (t + 1) th period. Through a correlation analysis method, the correlation rule of nitrogen conversion in the future X period after the carbon source is added is analyzed, the duration time of the drug effect is determined, the lag effect is accurately quantified, and the problem of mismatching of regulation and control opportunities is avoided. The hysteresis effect is captured and subjected to multi-factor coupling analysis based on the prediction model, the carbon source adding amount and time are optimized, system load fluctuation caused by excessive carbon sources or incomplete nitrogen removal caused by insufficient carbon sources are avoided, and the stability of an original sewage ecological system is gradually improved.

The invention discloses a dosing device for sewage treatment, which relates to the technical field of sewage treatment, and comprises a box body and a sewage pipe mounted at the top of the box body, and also comprises an isolating and mixing mechanism, the device comprises a plurality of mixing cylinders arranged in a box body, sealing rings mounted in the mixing cylinders, stirrers rotationally connected to the interiors of the sealing rings, a lifting assembly for driving the stirrers to lift in sections, and a transmission assembly for driving the stirrers to rotate; the layered dosing mechanism comprises a plurality of quantitative cylinders arranged in the box body, pistons mounted in the quantitative cylinders and a linkage assembly used for driving the pistons to move; according to the dosing device for sewage treatment, a flocculating agent is put into sewage in a sectional manner, and the sewage is separated from a flocculating precipitate in a sectional manner, so that the sewage flocculation treatment sufficiency is effectively improved, and the problem that the flocculating agent is dispersed into the precipitate, so that the sewage is difficult to sufficiently flocculate and precipitate is solved.

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 provides a sewage treatment carbon source adding control method, and relates to the technical field of sewage treatment, and the method comprises the following steps: obtaining water inlet parameters of a water inlet end of sewage to be treated and process parameters of a treatment section, the water inlet parameters comprising chemical oxygen demand, total nitrogen, total phosphorus and flow; the process parameters comprise the phosphate concentration at the tail end of an anaerobic tank, the nitrate concentration at the tail end of an anoxic tank, and the total nitrogen and chemical oxygen demand of inlet water of a denitrification filter tank; dynamically calculating a predicted carbon-nitrogen ratio and a predicted carbon-phosphorus ratio in real time according to water inlet parameters and the process parameters; based on the predicted carbon-nitrogen ratio, the predicted carbon-phosphorus ratio and a preset effluent quality standard, a carbon source adding point and a first carbon source adding amount are determined, and the carbon source adding point comprises at least one of an anaerobic tank, an anoxic tank and a denitrification filter tank; according to the carbon source feeding point and the first carbon source feeding amount, the carbon source feeding device is controlled to execute corresponding feeding operation, through segmented feeding and closed-loop control, COD standard exceeding caused by excessive carbon sources is avoided, and secondary pollution is effectively inhibited.

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 purification device for aquaculture wastewater, and relates to the technical field of wastewater purification. Comprising a box body as well as a physical filter tank and a biochemical bacterium culture tank which are arranged in the box body, and further comprises a microfiltration assembly arranged in the physical filter tank, the microfiltration assembly comprises a filter cartridge rotationally connected to the interior of the physical filter tank, a backwashing pipe is fixedly connected to the interior of the physical filter tank, and a sewage collecting tank is arranged in the filter cartridge; a cleaning assembly matched with backwashing to improve the cleaning effect of the filter cartridge is arranged in the filter cartridge, the cleaning assembly comprises a floating plate arranged in the filter cartridge, a connecting rod slidably penetrates through the floating plate, and the upper end of the connecting rod penetrates through the dirt collecting tank and is fixedly connected with a first cleaning brush; stubborn attachments such as mycoderm and caustic soda attached to the inner wall of the filter cartridge can be brushed off by utilizing the first cleaning brush, and the cleaning effect on the filter cartridge can be improved by matching with backwashing, so that the attachments on the inner wall of the filter cartridge can be massively washed off, the backwashing period is shortened, and the blockage probability of the filter cartridge is reduced.

The invention discloses a method for denitrifying wastewater by using a low-temperature-resistant heterotrophic nitrification and aerobic denitrification bacterium, and relates to a method for denitrifying wastewater by using a biological bacterium, the bacterium is Pseudomonas putida, is named as Pseudomonas umsongensis BK17, belongs to Pseudomonas, and is preserved in the China Center for Type Culture Collection (CCTCC), the preservation number is CCTCC M 20242924, and the preservation date is December 27, 2024. The strain is a heterotrophic nitrification-aerobic denitrification bacterium, can efficiently remove inorganic nitrogen pollution in a water body, still has good denitrification performance under low-temperature stress, and is high in low-temperature tolerance. The strain can efficiently treat nitrogen-containing wastewater under the condition of 10 DEG C, and the removal efficiency can reach 99% or above. The method has great potential in the application of inorganic nitrogen pollution treatment of domestic sewage and other water bodies in cold regions in China.

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

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

The invention relates to the technical field of sewage control, in particular to a control method and system of sewage treatment equipment and a medium. The method comprises the following steps: arranging a buffer cavity made of a flexible material at the water inlet end of sewage treatment equipment; the volume of the buffer cavity is adjusted in real time according to the original water inlet flow, and a flexible buffer cavity volume dynamic adjustment strategy is obtained; if the flexible buffer volume dynamic adjustment strategy executes the volume adjustment of the buffer cavity, evaluating the water outlet stability degree of the buffer cavity to obtain buffer effect evaluation data; a miniature electromagnetic valve is used for controlling the inlet opening degree of a reactor unit in the sewage treatment equipment, and the water inlet flow of the reactor unit is controlled to be balanced; and adjusting the porosity of the reactor unit partition plate to realize dynamic control and adjustment of sludge sedimentation. By dynamically adjusting the volume of the buffer cavity, water inlet flow fluctuation is effectively buffered, fine control over sludge sedimentation is achieved, and the impact resistance and operation stability of sewage treatment equipment are remarkably improved.

The invention relates to the technical field of water resource monitoring, in particular to a combined type automatic backwashing filter which comprises a tank body, a separation disc, a backwashing mechanism and a filter element, an inlet pipe, an outlet pipe and a discharge filter pipe are arranged on the outer wall of the tank body, the separation disc is fixed to the inner wall of the tank body, and the backwashing mechanism comprises a physical cleaning assembly and a chemical cleaning assembly. The physical cleaning assembly intermittently moves along the circumference, the chemical cleaning assembly quantitatively feeds chemicals in a segmented mode in the vertical direction, and the multiple filter elements are arranged at the top end of the separation disc in a circumferential array mode and matched with the through holes. Through the synergistic effect of circumferential intermittent movement of the physical cleaning assembly and vertical sectional quantitative dosing of the chemical cleaning assembly, physical washing and chemical treatment are synchronously achieved in the back washing process, viscous pollutants and microbial films are effectively removed, the risk of secondary pollution is reduced, meanwhile, energy consumption is reduced, the service life of a filter element is prolonged, and the service life of the filter element is prolonged. The device has the advantages of efficient cleaning, reliable operation and good economical efficiency.

The invention relates to the technical field of automatic control, and discloses a water affair treatment process optimization control method, system and equipment and a medium. The method comprises the steps of performing state judgment on sensor detection data through a multi-parameter state recognition algorithm to obtain a processing stage switching instruction; modeling a microbial activity change rule according to the switching instruction to obtain a staged prediction model; optimizing the prediction model through a switching model prediction control algorithm to obtain a multi-target control strategy; performing coordinated calculation on the set value according to the control strategy to obtain a distributed control instruction; and performing driving control on the equipment by using the control instruction through the field bus to obtain a coordinated operation state. According to the invention, the control precision and the multi-target coordination optimization capability of the water affair treatment process are improved.