4138results about "Water treatment parameter control" patented technology

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 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 relates to the technical field of environmental engineering water treatment automatic control, and discloses a landfill leachate treatment control method based on cooperative control. The method comprises the following steps: acquiring real-time monitored water quality parameter data streams including a pretreatment stage pH value, a main treatment stage COD concentration, a deep treatment stage membrane pressure difference and the like in a landfill leachate treatment system, inputting the data streams into a cooperative control framework, and dynamically correcting PID controller parameters through a nonlinear gain function to generate a primary adjustment instruction; evaluating and generating a strategy optimization instruction based on the reinforcement learning strategy network; inputting the two into a grey prediction model and outputting a cooperative control signal containing a feedforward compensation amount; and finally, dynamically adjusting the coagulant dosage, the aeration intensity and the working pressure of the membrane component according to the signal to form a closed-loop control loop. The method can master the water quality change in real time, accurately regulate and control the treatment process, improve the stability and reliability of the treatment system, and effectively improve the landfill leachate treatment effect.

The invention discloses a modularized ultrapure water preparation and on-line monitoring system, which comprises a pretreatment module, a purification module, a monitoring module and a control module, and is characterized in that a dynamic monitoring end is arranged, and when ultrapure water preparation is monitored in real time, a multi-parameter fusion detection mechanism and self-adaptive threshold analysis are integrated; meanwhile, the abnormal state of the water quality is dynamically judged based on the conductivity, TOC and particulate matter data collected in real time, the sudden change risk of the water quality output by the purification module can be recognized in real time, error accumulation caused by traditional single-point monitoring is avoided, and therefore the purity detection reliability of the ultrapure water is improved; and the reverse osmosis unit and the electrode deionization unit of the purification module can immediately respond to the effluent parameter change of the pretreatment module, so that the hidden dangers of membrane blockage and recovery rate reduction caused by water quality fluctuation are reduced, and the energy consumption redundancy is reduced while the water quality stability is ensured.

The invention belongs to the technical field of wastewater treatment, and provides a wastewater treatment equipment remote control system based on the Internet of Things, which aims at solving the problems that the traditional fixed DO concentration control cannot adapt to water inlet load fluctuation, the effluent is easy to be substandard or the aeration energy consumption is high, the monitoring data noise is large, and the time sequence is misplaced. According to the scheme, a multi-dimensional real-time sensing network is constructed, flow, COD, BOD, ammonia nitrogen, water temperature, distributed DO and sludge activity sensors are deployed, discrete wavelet transform is adopted for noise reduction, and a data time sequence is aligned; a three-layer load-DO-energy consumption dynamic correlation model is designed, a basic layer predicts a load trend through LSTM, a middle layer quantifies a DO demand through a microbial metabolism model, and an optimization layer outputs an optimal DO set value through a PPO algorithm; and developing a dynamic decision-making system, adaptively generating a DO interval according to a load state, and adjusting fan parameters and number in a linkage manner. According to the invention, load dynamic adaptation is realized, effluent ammonia nitrogen is guaranteed to reach the standard, aeration energy consumption is reduced, and remote control precision and equipment operation efficiency are improved.

The present invention discloses an intelligent control method for sewage treatment equipment at dry bulk cargo terminals, relating to the technical field of sewage treatment equipment control, and is used to address the problem of poor control of sewage treatment equipment at terminals. The method comprises following steps: installing multiple types of sensors at key locations on dry bulk cargo terminals, utilizing edge computing nodes for real-time data acquisition and preprocessing, combining historical and temporal features with machine learning models to classify sewage types, achieving efficient dynamic adjustment of sewage treatment equipment operation parameters, then using weighted voting and confidence assessment to integrate multiple classification results to ensure optimal treatment results, and analyzing the actual sewage treatment situation to optimize equipment control continuously, thereby preventing failures, extending equipment life, and improving sewage treatment effectiveness.

The invention provides a sewage treatment state monitoring method and system based on image feature analysis. The method comprises the following steps: acquiring a plurality of image frame data and a plurality of sensor time sequence data of a flocculation basin in a first time period; performing data splicing on the image frame data and the plurality of sensor time sequence data to obtain a plurality of multi-modal data at different moments; inputting each piece of multi-modal data into a preset floc detection model, so that the floc detection model performs feature fusion on each piece of data in the multi-modal data through an attention mechanism, and generates a frame-level floc feature vector corresponding to the multi-modal data according to a feature fusion result; and inputting each frame-level floc feature vector and the plurality of sensor time sequence data into a preset sewage treatment state evaluation model, so that the sewage treatment state evaluation model outputs the current sewage treatment state according to the input data, and the accuracy and real-time performance of sewage treatment state monitoring are improved.

Methods and systems for water quality assessment are disclosed. The method includes obtaining a first input data indicative of properties of a first liquid sample, the first input data including turbidity data and total suspended solids data for the first liquid sample, where the first liquid sample is acquired from a liquid source. The method further includes determining, using a computer processor and a machine learning model, a first predicted particle-size distribution of the first liquid sample based on the first input data, where particle-size distribution is controlled, at least in part, by a set of dosage parameters configurable by a water quality system. The method further includes determining, with an optimizer applied to the machine learning model, an optimal set of dosage parameters based on the first predicted particle-size distribution and adjusting the set of dosage parameters of the water quality system to the optimal set of dosage parameters.

The present disclosure relates to the technical field of water treatment, and provides a dosing control system in a water treatment process. The system comprises: a programmable logic controller configured to transmit current characteristic values of water inlet parameter characteristics and water outlet parameter characteristics collected by sensors to an edge gateway, and drive a camera to capture a floc image; the camera is configured to transmit the captured floc image to the edge gateway; the edge gateway is configured to obtain a dosing amount prediction value based on a preset dosing amount prediction model according to the water inlet parameter characteristics, the water outlet parameter characteristics and the floc image, and feed back the obtained dosing amount prediction value to the programmable logic controller; and the programmable logic controller is further configured to control the dosing pump to perform a dosing operation in the water treatment process according to the dosing amount prediction value. The present scheme can improve the dosing control efficiency of the water treatment process.

The invention discloses a seawater desalination treatment system and method based on a penetration method, and particularly relates to the technical field of seawater desalination treatment.The seawater desalination treatment system is provided with an online monitoring module, and various indexes in the seawater desalination treatment process are monitored through a multi-source sensor; a seawater pollution treatment module is arranged to remove suspended particles and pollutants in seawater; a seawater desalination treatment module is arranged for deep desalination; setting an equipment management module to judge whether equipment maintenance is needed or not based on the real-time operation data of the equipment; a semi-permeable membrane loss prediction module is arranged for semi-permeable membrane loss prediction; setting a semi-permeable membrane maintenance control module to automatically match a corresponding maintenance strategy according to the predicted membrane loss degree; a forward osmosis and reverse osmosis coupling process is combined, so that the desalination rate and the energy consumption efficiency ratio are improved, and the service life of the semipermeable membrane is effectively prolonged; an intelligent monitoring-prediction-control system is constructed, and the stability and reliability of the technological process are guaranteed.

The invention discloses an environment-friendly multi-purification device and method for sewage treatment, and relates to the technical field of sewage multi-stage treatment. Comprising a multi-stage filtering device, a permeation filtering piece is installed on the multi-stage filtering device, and a floating oil absorption piece is installed on the permeation filtering piece; the floating oil absorption piece is used for prolonging the service life of the permeation filtering piece; a pretreatment piece is mounted on the multi-stage filtering device; a sampling and mixing part is mounted in the pretreatment part; a sampling control piece is mounted on the pretreatment piece; the pretreatment part is adopted to facilitate pretreatment mixing work of sewage, the sampling control part can be used for automatically controlling accelerated mixing of water stored in the pretreatment part when a worker needs to sample, and the situation that sample sewage is not accurate enough when the sampling position is single can be avoided; the problems that an existing multi-purification device for sewage treatment is not convenient for floating oil removal and is not convenient for premixing and sampling when sewage enters are solved.

The invention discloses a sewage treatment dosing method and system based on machine learning, electronic equipment, a storage medium and a product. The method comprises the following steps: constructing a multi-parameter time sequence data set between historical operation data about a sewage treatment system and historical dosing amount data of time lag duration t corresponding to each group of historical operation data; a dosing prediction model is constructed based on a random forest network, and a multi-parameter time sequence data set is used for training; dynamically updating the lagging duration t; operating parameters of the sewage treatment system are collected in real time, and the trained dosing prediction model is used for predicting the dosing amount of the optimal dosing lagging duration. According to the method, the hysteresis of an existing dosing control mode is effectively compensated, meanwhile, the delay time is dynamically regulated and controlled, accurate prediction of the dosing amount is achieved, the fluctuation risk of the effluent quality is reduced, and the working condition generalization ability of a dosing system is improved.

The invention relates to the technical field of generator set mixed bed operation monitoring, and discloses an operation health degree monitoring method and system based on fine treatment mixed bed resin tracking, the monitoring system comprises a sampling tube, a sampling electric valve, a sampling isolation valve, a cation resin column, a conductivity meter, a mixed bed failure monitoring device and a resin regeneration system; the sampling pipe extends into the central axis of the fine treatment mixed bed; a plurality of sampling pipes are arranged along the height direction of the fine treatment mixed bed, are sequentially connected with a sampling electric valve and a sampling isolation valve, and then are connected in series to one end of a cation resin column; the other end of the cation resin column is connected with the conductivity meter; the mixed bed failure monitoring device is electrically connected with the sampling electric valve, the sampling isolation valve and the conductivity meter; and the resin regeneration system is connected with a water inlet pipeline and a water outlet pipeline of the fine treatment mixed bed through a fine treatment mixed bed resin inlet valve and a fine treatment mixed bed resin outlet valve respectively. Health degree monitoring is realized by establishing a layered monitoring system, and long-term stability of water quality of a power plant system is guaranteed.

The invention discloses a water purification method and system for urban and rural integrated water supply, and relates to the technical field of water treatment. The water purification method for urban and rural integrated water supply solves the problems that an existing system is poor in process adaptability, inaccurate in control and low in energy efficiency. Water quality and pipe network data are collected in real time through a sensor; an adjustable folded plate flocculation device is adopted, and the flocculation effect is optimized in combination with turbidity dynamic adjustment; constructing a multi-parameter dosing model, and dynamically dosing according to flow, turbidity and the like; the LSTM neural network is used for predicting the state of a filter layer, and air-water pulse backwashing is intelligently controlled; and adding a composite flocculant to enhance pollutant removal, and realizing water quality prediction and system collaborative optimization by virtue of a random forest algorithm and a digital twin platform. The flocculation efficiency is improved, dosing is accurately controlled, energy consumption and water resource waste are reduced, and an efficient and stable scheme is provided for urban and rural water supply.

The invention discloses a real-time sewage treatment method based on sewage data monitoring, particularly relates to the technical field of sewage treatment, and is used for solving the problem of how to realize real-time sewage treatment under the condition that quality problems such as sewage blockage, drifting and missing exist in online monitoring data under complex and fluctuating working conditions. The problem that real-time, stable and energy-saving self-adaptive regulation and control can still be conducted on the sewage treatment process based on sewage monitoring data is solved, and the problems that due to dirty data and sudden change of working conditions, outlet water exceeds the standard, and energy consumption / chemical consumption is abnormal are avoided. Key water quality soft measurement and multi-source difference checking are implemented under the constraint of working condition numbers by constructing a sewage working condition map and a data quality evaluation rule base and introducing sliding time window feature extraction, monitoring credibility grading and sewage state fingerprints. The control strategy can still generate reliable aeration control instructions, backflow control instructions and dosing control instructions when monitoring data distortion and working condition fluctuation, so that the effluent is ensured to stably reach the standard, and the risk of control deviation is reduced.

The invention relates to the field of direct drinking water of a fusion calculation model, and discloses a double-membrane mixing direct drinking water system and an operation method.The method comprises the steps that online data of a water supply end and a water quality monitoring end are collected for cleaning and time alignment, and a basic working condition data set is formed; the method comprises the following steps: establishing an operation characteristic model comprising water demand prediction, raw water quality prediction and membrane flux characteristic sub-models, calculating double-membrane target water yield and water quality indexes based on the model to generate a control parameter set, evaluating membrane pollution to generate an online cleaning task queue, performing joint simulation to generate a pressure stability control instruction set, and dynamically correcting the model. The conversion from passive response to active pre-judgment of the double-membrane mixing direct drinking water system is realized, and the operation stability, the water quality guarantee capability and the water-saving and energy-saving effects are improved.

A buoyant hydrodynamic pump is disclosed that can float on a surface of a body of water. Wave-driven oscillations result in periodic upward ejections of water inside a downwardly projecting tube that can be collected in a reservoir. Water within such a reservoir may return to the body of water via a turbine, thereby generating electrical power, or the device's pumping action can be used for other purposes such as water circulation, propulsion, dissolved minerals extraction, or cloud seeding.

The invention discloses a wastewater pretreatment system based on intelligent control, the wastewater pretreatment system comprises a coagulation precipitator, a pulse impurity remover and an ultrafiltration device which are connected in sequence, wastewater is subjected to precipitation treatment by adding a coagulant, a plurality of anode plates and cathode plates are arranged in the pulse impurity remover, the anode plates and the cathode plates are alternately arranged, and the ultrafiltration device is connected with the coagulation precipitator. The anode plate and the cathode plate provide dynamic pulse current through a pulse intelligent control system; the water quality monitoring system monitors wastewater quality data in real time, and the pulse controller adjusts operation parameters output by the pulse power supply according to the wastewater treatment effect; and the ultrafiltration is used for removing suspended matters in the wastewater output by the pulse impurity remover. When the pretreatment system is used for treating the wastewater, the treatment effect is fed back in real time through the water quality monitoring system, and the pulse intelligent control system can be used for dynamically adjusting operation parameters in real time, optimizing the operation parameters, improving the treatment efficiency, saving the energy consumption, reducing the dosage of chemicals in the front-end coagulation precipitator and reducing the operation cost.

The invention discloses a method and system for accurately controlling the concentration of dissolved oxygen (DO) of a sewage treatment aeration unit, and the method comprises the steps: constructing a prediction model, and obtaining a model prediction value of the DO concentration at a current moment or a future moment according to the prediction model; calculating a current confidence coefficient; taking the current confidence coefficient as a weight coefficient, and carrying out weighted fusion calculation on a DO concentration measured value at the current moment and a DO concentration model prediction value to obtain a DO concentration fusion variable; the aeration air volume is adjusted or controlled with the purpose of minimizing the error between the DO concentration fusion variable and the DO concentration target value; the problem of overshoot oscillation caused by DO response lag in traditional control is solved, and a dynamic and accurate control solution is provided for the DO concentration of the aeration unit of the sewage plant.

The invention relates to an intelligent aeration system and a control method, and belongs to the technical field of sewage treatment. The system comprises a clean water tank, an aeration tank, a data acquisition unit, a PLC control unit and an aeration unit. The system dynamically calculates the required DO set value by collecting the inlet water chemical oxygen demand, the clear water ammonia nitrogen concentration, the sludge concentration and the sewage temperature of sewage in real time, calculates the difference value between the actual DO value and the required DO set value, calculates the aeration amount needing to be adjusted, and finally adjusts the blast volume through the aeration unit. The problems that a traditional aeration system is high in energy consumption and low in control precision are solved, insufficient aeration or excessive aeration can be effectively avoided, and stable effluent quality is guaranteed.

A refillable dispensing device for measurably dispensing liquid chemical treatment into a body of water, including: a vessel having a wall; a vessel opening at one end and a vessel surface at a opposite end of the vessel; a removable closure for closing the vessel opening; a metered dosing device in communication with the vessel opening and the removable closure for metered dose dispensing of liquid chemical treatment into a body of water.

The invention discloses an enhanced metal-based composite water purifying agent and a preparation method thereof, belongs to the technical field of preparation of water purifying agents, and aims to solve the technical problem that the flocculation capacity and the stability of a composite water purifying agent in the prior art need to be further improved. The preparation method specifically comprises the following steps: preparing a water purifying agent skeleton dispersion liquid by using chitosan and sodium alginate; chitosan-sodium alginate is used as a porous framework, a polyphenol-multi-metal complex is loaded, a structure is enhanced through Ca < 2 + > crosslinking, then SiO2 is used for coating to improve acid and alkali resistance and stability, and finally PAC is introduced to realize rapid flocculation. In the preparation process, the organic framework, the metal complex and the inorganic coating layer are fully compounded through pH control and step-by-step dropwise adding, and the obtained composite water purifying agent can efficiently remove phosphorus, chromium and suspended solids in water and shows a remarkable synergistic purification effect and storage stability.

The invention provides an MMPC-based sedimentation tank intelligent dosing control system and method, and relates to the technical field of water treatment.The MMPC-based sedimentation tank intelligent dosing control system comprises a fixing frame and a sedimentation tank, and a water inlet pipe is fixedly installed at the top of the fixing frame; the left end of the water inlet pipe is fixedly connected with a flow instrument; the left end of the flow instrument is fixedly connected with a filter pipe; a water inlet detection pipe is slidably mounted on the left side of the filter pipe; and four mounting seats B are fixedly mounted at the top of the water inlet detection pipe. Based on a multi-model self-adaptive switching structure, the problem of mismatching of a traditional single model under variable working conditions is solved, when the inflow flow fluctuates or the turbidity changes suddenly, the system automatically calls a prediction model matched with the current working condition, the change of the effluent turbidity is predicted in advance, the dosage is adjusted in time, and the effluent turbidity is stably controlled within a target range, so that the stability of the system is improved. The safety of water consumption of residents is guaranteed, and the problem of out-of-control risk caused by time delay is solved.

The invention belongs to the technical field of sewage treatment, and particularly relates to an intelligent response filter material, a preparation method thereof and a denitrification deep-bed filter tank. The intelligent response filter material is of a three-layer composite structure and sequentially comprises a carbon source inner core, a transition layer and a wrapping layer from the inner layer to the outer layer; the carbon source core comprises aquatic plant powder, aggregate and reinforced fibers, the transition layer adopts a hydrophilic modified porous carrier, and the wrapping layer adopts a pH responsive polymer. According to the invention, the intelligent response type filter material prepared from aquatic plant straws is adopted, and the pH response type envelope can automatically adjust the release rate of a carbon source according to the pH change caused by the denitrification process, so that intelligent on-demand supply of the carbon source is realized, and the denitrification efficiency and the utilization rate of the carbon source are greatly improved.

The invention relates to the technical field of electrochemical water treatment, and discloses a high-salt waste liquid electric flocculation hardness removal and electrodialysis resourceful treatment method and a high-salt waste liquid electric flocculation hardness removal and electrodialysis resourceful treatment system. The method comprises the following steps: collecting water quality parameters of the high-salt waste liquid and initial electrochemical impedance spectroscopy parameters of a polar plate; calculating the initial current density according to the hardness and the conductivity, carrying out electric flocculation treatment, monitoring impedance spectrum change in real time, identifying the scaling type, and predicting the residual operation time of the polar plate; the current density is optimized according to the prediction time, and the residual hardness is calculated; and adjusting electrodialysis parameters by taking the residual hardness as a feedforward signal for concentration, and performing bipolar membrane electrodialysis on the concentrated solution to obtain acid-alkali liquor. The problems that in the electrochemical treatment process of the high-salt waste liquid, the state of a polar plate cannot be monitored in real time, consequently, operation parameters are adjusted blindly, and energy consumption is high and the recycling efficiency is low due to the fact that parameters of a pretreatment unit and parameters of a pretreatment unit are not linked are solved.

The invention discloses a sewage reuse system and method. The system comprises a sewage collection module, a pretreatment module, an advanced treatment module, a water quality monitoring module, an intelligent regulation and control module, a reuse distribution module, a sludge treatment module and a medicament management module, by arranging the sewage collection module, the pretreatment module, the advanced treatment module and the like, graded purification treatment of sewage is achieved, dynamic optimization of the treatment process is achieved in combination with the water quality monitoring module and the intelligent regulation and control module, and the sewage treatment efficiency and the water quality stability are improved. The reuse distribution module realizes multi-path reasonable utilization of standard sewage, the sludge treatment module realizes resource utilization of sludge, and the agent management module guarantees accurate addition and stable supply of agents.

The invention discloses an intelligent adding control platform for a water treatment process, and relates to the technical field of water treatment, and the intelligent adding control platform comprises a data processing module which is used for obtaining historical water treatment data of water treatment plants in different regions to obtain historical medicament use data; the feedforward control module is used for acquiring sewage data in the plant area to obtain basic dosing data; the prediction and supplement module is used for predicting a water quality change trend according to the basic dosing data to obtain a dosing effect, and performing medication adjustment to obtain supplementary dosing data; the dynamic adjustment module is used for obtaining a target quantification set of the plant area and carrying out weight distribution to obtain a dosing strategy; and the trust adjustment module is used for collecting the sensor state and sensor output data of each sensor to obtain the confidence coefficient of sewage treatment, and modifying the dosing strategy according to the confidence coefficient to obtain a target dosing strategy. The method has the effect of improving the accuracy and intelligence of automatic dosing on medicament control.

The invention discloses a device and process for treating pharmaceutical wastewater through an internal electrolysis method. The device comprises a pretreatment unit, an internal electrolysis reaction unit, a precipitation separation unit, a pH adjusting unit and a control system which are sequentially connected. The internal electrolytic reaction unit comprises a reaction tower body, the top of the reaction tower body is provided with a water inlet, and the bottom is provided with a water outlet; a supporting layer, an iron-carbon micro-electrolysis filler layer, a catalytic oxidation layer and a biological membrane layer are sequentially arranged in the reaction tower body from bottom to top, the iron-carbon micro-electrolysis filler layer comprises an iron-carbon composite filler, and the mass ratio of iron to carbon in the iron-carbon composite filler is (1: 1)-(3: 1). The internal electrolysis reaction unit with a multi-level filling structure is adopted, iron-carbon micro-electrolysis, catalytic oxidation and biodegradation are organically combined to form a synergistic effect, the removal efficiency of refractory organics in the pharmaceutical wastewater is remarkably improved, and the COD removal rate can reach 80% or above.

The invention discloses a dissolved oxygen closed-loop regulation and control method used in a sewage treatment process. The method comprises the following steps: acquiring real-time dissolved oxygen concentration in a reaction tank through a distributed sensor array, and performing temperature compensation; an online water quality analyzer is used for collecting water inlet flow, chemical oxygen demand, ammonia nitrogen and water temperature to construct a comprehensive input feature vector; establishing a nonlinear dynamic mapping model based on a deep neural network, and outputting a target dissolved oxygen set value changing along with working conditions; an aeration adjusting instruction is generated by adopting a feedforward-feedback composite adaptive fuzzy PID control algorithm; dynamically adjusting the air volume of an air blower and the opening density of a partition aeration disc to match the aerobic rate of microorganisms; and the control performance is evaluated regularly, and a model parameter online optimization mechanism is triggered to continuously improve the setting precision. According to the method disclosed by the invention, the dissolved oxygen can be accurately controlled, so that the aeration energy consumption is reduced by not less than 18%, the control precision is within + / -0.3 mg / L, and the robustness, the automation level and the low-carbon operation capability of the system are remarkably improved.

The invention provides a strong brine zero-discharge circulating cooling water high-salt operation method and system. The method comprises the following steps: S1, pretreating high-efficiency membrane softening produced water and controlling a shunting dynamic ratio; s2, variable parameter closed-loop control and energy consumption optimization of the water supplementing system; s3, multi-variable cooperative regulation and evaporation efficiency improvement of the circulating water system; s4, dynamically adding the high-salt scale and corrosion inhibitor and controlling the uniformity of a concentration field; s5, multi-dimensional data fusion and intelligent decision making of the online detection system; s6, carrying out dynamic flow regulation and energy recovery on the sewage discharge system; s7, carrying out self-adaptive backwashing and efficiency monitoring on the sewage filtering system; s8, double-circulation temperature difference matching and anti-scaling control of the closed cooling system are carried out; s9, simulating multi-working-condition corrosion monitoring and data inversion of the heat exchanger; s10, carrying out the digital twinborn modeling and parameter optimization of the whole system; the method has the advantages of remarkable water-saving effect, energy conservation, consumption reduction, stable operation and good economical efficiency.