2670results 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 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 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 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 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 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 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 relates to the technical field of intelligent control of filters, and discloses an intelligent control method for a self-cleaning filter based on sensing of the Internet of Things. The method comprises the following steps: collecting multi-source sensing data such as inlet and outlet water pressure difference, flow fluctuation frequency, turbidity change rate and vibration spectrum characteristics when the filter runs; performing hierarchical clustering on the data according to a preset blockage level threshold value, and generating a blockage feature matrix with a timestamp; the matrix dynamic state is monitored in real time, and when the turbidity change rate and the covariance of the vibration spectrum characteristics exceed a dynamic threshold value, self-adaptive cleaning strategy switching is triggered; in combination with the time-space matching degree of a historical cleaning period and a current matrix, decomposing sub-feature sets of high-frequency blockage and low-frequency deposition modes, and correcting the weight of the high-frequency sub-feature sets through cross validation of fluid dynamics and mechanical wear parameters; and finally, a preferential cleaning area is reversely positioned along the structural topological graph of the filter, a three-dimensional cleaning path instruction is generated, and the opening degree of a blow-down valve is synchronously adjusted, so that the control and operation performance of the filter is optimized.

The invention relates to the field of intelligent manufacturing, and provides a bio-pharmaceutical wastewater cooperative treatment method and system based on a graph neural network. The method comprises the following steps: monitoring a biopharmaceutical process in real time; performing dynamic aggregation on the real-time monitoring data to obtain molecular structure information, microbial community network information and a topological relation among process links in a pharmaceutical process to obtain a dynamic heterogeneous knowledge graph; analyzing interaction rules of different node types in the dynamic heterogeneous knowledge graph by adopting a hierarchical learning mechanism through a multi-modal graph neural network, and predicting migration paths of pollutants and / or pollutant detection indexes in the biopharmaceutical process according to the interaction rules; based on the key index change trend in the migration path, multi-objective optimization decision making is carried out, an optimization control strategy for the biopharmaceutical process is generated, intelligent source tracing and optimization treatment of biopharmaceutical wastewater are achieved, the wastewater treatment efficiency is improved, and the wastewater treatment effect is improved.

The invention discloses a water supply energy-saving safe scheduling and purification intelligent control system, and relates to the field of water supply energy-saving purification, and the system comprises a sensing module, a calculation module, an acquisition terminal, a scheduling module and a purification module.A final water demand prediction value is obtained by constructing a time-sequence-dependent water use feature set and performing prediction and error correction on an LSTM model; performing water supply energy-saving safety scheduling analysis, generating a water supply pipeline equipment control parameter combination, performing pipeline state abnormity and pipeline fluid pressure analysis, calculating a pipeline state abnormity value, performing pressure loss state change analysis when the pipeline fluid flows to obtain a pipeline fluid pressure loss value, and performing image construction to obtain a water pipeline pressure difference value; the electronic valve works according to the adjusted valve opening value through the scheduling module, and the calculation module receives the water quality data obtained by the sensing module and performs corresponding valve control and purification treatment, so that responsibility complaints of users are greatly reduced, and resource waste is reduced.

The invention relates to the technical field of water resource purification, in particular to a control method and equipment of a reverse osmosis water purification system.The control method comprises the steps that firstly, on the fluctuation dimension of the pre-membrane pressure, the adjusting requirement of the frequency of a high-pressure pump is preliminarily determined on the dimension of the pre-membrane pressure according to an obtained pressure fluctuation index; determining a membrane resistance increase factor representing the pollution state of the reverse osmosis membrane on the basis of the transmembrane pressure difference on the dimension of separation function failure of the reverse osmosis membrane; finally, a membrane separation abnormal value is comprehensively represented by combining a pressure fluctuation index and a membrane resistance increase factor, and a purified water recovery rate is introduced to a membrane separation result end, so that the finally obtained frequency reduction demand degree is more accurate, and the control effect of the reverse osmosis water purification system is improved; therefore, the stable, efficient and sustainable operation of the reverse osmosis water purification system can be ensured while the membrane surface pollutant deposition driving force can be effectively reduced and the membrane pollution speed can be slowed down.

The invention discloses an integrated process for cooperative treatment and up-to-standard discharge of industrial wastewater and domestic wastewater of a power plant, and relates to the field of cooperative treatment of wastewater and sewage, and the integrated process comprises the following steps: configuring a raw water collection system, setting a raw water source, configuring a multi-stage filtration and heating pretreatment process, configuring an ultrafiltration membrane system, and setting a fine filtration path. A first-stage reverse osmosis system is configured, reverse osmosis parameters are set, a second-stage reverse osmosis system is configured, a low-conductivity water treatment path is set, a mixed ion exchanger is configured, a desalted water output path is set, a standby pool body is set, and the adjusting capacity is set. A raw water collecting system, a multi-stage filtering and heating pretreatment process, an ultrafiltration membrane system, a first-stage reverse osmosis system, a second-stage reverse osmosis system, a mixed ion exchanger and a standby pool body are sequentially arranged in the process. The problems of unstable effluent quality, insufficient deep desalination capability and poor emergency regulation capability in a traditional power plant wastewater treatment mode can be effectively solved.

The invention discloses a bimodal cooperative control-based intelligent chemical adding optimization method for a water supply project. The method comprises the following steps of: S1, acquiring effluent quality and quantity data of a water supply system and a monitoring index of a running state of the water supply system in a plurality of continuous control periods adjacent to a current control period; s2, judging whether the running state of the water supply system is in a stable state or not according to the monitoring indexes and the effluent quality and quantity data, if so, entering step S4, and otherwise, entering step S3; s3, calculating the dosing pump control quantity in the current control period by adopting a fuzzy self-tuning PID algorithm; s4, determining a dynamic prediction time domain adjustment rule, inputting effluent quality and quantity data in a time domain into the machine learning model, and adopting a model prediction control MPC algorithm to obtain a dosing pump control quantity; and S5, according to the control quantity of the dosing pump in the step S3 or the step S4, controlling the dosing pump to add a medicament into the clean water tank, and returning to the step S1 when the water supply system is in a running state and the current control period is completed.

The invention relates to a water quality parameter monitoring and intelligent dosing method and system based on the Internet of Things, and the method comprises the steps: obtaining water quality parameter data of a time sequence through a multi-point sensing device, and carrying out the data preprocessing of the water quality parameter data, and obtaining a first water quality data set; performing time sequence analysis on the first water quality data set to obtain a water quality trend feature set; inputting the water quality trend feature set into a preset water quality state prediction model to obtain a predicted water quality parameter value in a preset future time period; performing anomaly analysis on the predicted water quality parameter value and a preset parameter threshold range to obtain early warning data, the early warning data including a pollution risk area, an anomaly time interval and a risk category; and according to the early warning data and the historical governance data, performing optimization calculation on the dosing parameters through a tree model to determine a first dosing scheme. According to the application, the accuracy and timeliness of water pollution monitoring and treatment can be effectively improved, and an intelligent solution is provided for water environment management.

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 present disclosure provides a method for controlling a cleaning device and a cleaning device. The cleaning device includes a first distance sensor disposed at a bottom. The control method includes: in a process in which the cleaning device moves on a bottom of a pool, when the cleaning device approaches or collides with an obstacle, controlling the cleaning device to climb the obstacle; and in a process of climbing the obstacle, if the obstacle is determined as a step, controlling the cleaning device to move from a first surface of the step to a second surface of the step, where the step at least includes the approximately vertical first surface and the approximately horizontal second surface, where the obstacle is determined as the step at least based on a detection value of the first distance sensor.

The invention relates to the technical field of water treatment, and discloses a direct spraying type waste heat recovery acidic water treatment method. The method comprises the following steps: arranging a pH value difference sensor group and a conductivity sensor at a joint of a buried pipe cold storage system and a direct-spraying type waste heat recovery device, and monitoring the whole process of acid water treatment in real time to obtain water quality change data of the acid water; performing filtering treatment and working condition matching analysis on the acid water quality change data and the system operation parameters to obtain a cold storage-acid water treatment cooperation mode; performing thermochemical coupling analysis through the hyperboloid mapping network to obtain a corrosion risk assessment result; and executing the heat exchange efficiency and pH value adjustment dual-constraint optimization model according to a corrosion risk assessment result, and outputting an anti-corrosion control strategy. According to the method, the complex nonlinear relation between the pH value change and the temperature gradient can be accurately captured, the accuracy of corrosion risk prediction is greatly improved, and damage to equipment caused by corrosion is effectively avoided.

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 relates to the technical field of water treatment, in particular to a high-recovery-rate short-process salt-tolerant reverse osmosis system and treatment method.The system comprises a pretreatment unit, a sensor monitoring unit, a self-adaptive pressure-flow coupling control unit, an intelligent operation and maintenance unit and a gradient boosting reverse osmosis membrane set. According to the invention, ultrahigh recovery rate and desalination performance are realized, gradient boost membrane module design is combined with concentration polarization inhibition technology, membrane surface flow state distribution is optimized, osmotic pressure influence is significantly reduced, pressure-flow coupling control and concentrated water excess pressure energy recovery technology are integrated, energy dynamic cyclic utilization is realized, energy consumption is reduced, and the method is suitable for industrial production. By monitoring the membrane flux attenuation rate and the transmembrane pressure difference in real time and dynamically optimizing a pulse cleaning strategy, dynamic optimization of high-salinity wastewater treatment is realized, and the problems of low recovery rate, high energy consumption and quick membrane pollution in high-salinity wastewater treatment are solved.

The invention relates to the technical field of water quality monitoring, in particular to an aquaculture water quality monitoring and self-adaptive regulation and control platform and method.The aquaculture water quality monitoring and self-adaptive regulation and control platform comprises a data processing module used for obtaining water quality parameter data of aquaculture at multiple monitoring points and multiple time points and conducting preprocessing and time sequence serialization fitting on the water quality parameter data to obtain a data processing module; obtaining a water quality parameter time sequence; the feature extraction module is used for carrying out space-time semantic recognition and feature extraction on the water quality parameter time sequence and constructing a feature sequence of each water quality parameter; and the risk early warning module is used for carrying out inter-parameter space-time correlation calculation and dynamic risk threshold value adaptation according to the feature sequence to obtain water quality risk early warning features. By combining the water quality parameters and the culture organism state data, the system can accurately evaluate the risk level of the water quality, timely warn potential risk factors, help a culturist to take effective precautionary measures, and avoid the death or health problem of the culture organism.

A water filtration system is also disclosed. The water filtration system includes a regenerative media filter vessel, a filtrate line, a feed line, a recirculation line, a gas line, and at least one pump. A method of filtering water in a system comprising a regenerative media filter is disclosed. The method includes operating the system in a filtration mode, operating the system in a cleaning mode responsive to a differential pressure measurement across the regenerative media filter, operating the system in an aeration mode, operating the system in a pre-filtration mode after operating the system in the cleaning mode, operating the system in a drain mode, and operating the system in the filtration mode following the drain mode. A controller and non-transitory computer-readable medium having computer-readable signals stored thereon that define instructions that, as a result of being executed by the controller, instruct the controller to perform a method of operating a water filtration system are disclosed.

The invention relates to the technical field of industrial wastewater deep purification, and discloses an industrial wastewater deep purification system based on nano catalytic membrane separation, which comprises a pretreatment module, a catalytic degradation module, a membrane separation module, an intelligent control module and a regeneration maintenance module which are sequentially connected according to a treatment flow, the pretreatment module adjusts the water quality of inlet water to a range suitable for subsequent treatment through pH adjustment and suspended matter interception, that is, the pH is 2-11, and the turbidity is less than or equal to 50NTU; the catalytic degradation module is used for decomposing organic pollutants and mineralizing refractory substances under the excitation of ultraviolet / visible light by utilizing the photocatalytic characteristic of a nano catalytic membrane. The TiO2 / WO3 heterojunction nano catalytic membrane is adopted, so that deep oxidation of refractory pollutants such as phenol and sulfonamide antibiotics is realized, finally, the COD removal rate of 98.7% is achieved, and compared with a traditional photocatalytic process, the energy consumption is reduced by 54%.

The invention relates to the technical field of water treatment equipment, in particular to an ultrasonic water treatment equipment control method and system based on variable-frequency vibration waves. According to the method, based on preset fluid working condition parameters, ultrasonic frequency conversion vibration wave signals covering multiple frequency bands are dynamically generated, and a vibrator array is driven to generate a composite sound field; a cavitation effect and an activation effect are synchronously excited in a fluid medium through variable-frequency vibration wave signals, so that physical form depolymerization and surface charge distribution change of scale forming substances occur; a shearing effect is formed on a fluid-pipe wall boundary layer, an attached state biological membrane structure is stripped, and the microscopic binding force of a crystallized scale body is loosened; monitoring the dispersion degree of scale-forming substances in the fluid and the state of a boundary layer, and adjusting the frequency band combination and energy distribution of variable-frequency vibration waves to maintain scale inhibition; and continuously optimizing the frequency conversion strategy and the sound field intensity according to the feedback data of the scale inhibition maintenance state. Through intelligent multi-band frequency conversion control of the ultrasonic water treatment equipment, efficient and environment-friendly water treatment and scale prevention effects are realized.

The invention discloses an intelligent self-adaptive silt filtering system and method for a pumped storage power station, and belongs to the technical field of pumped storage power stations. The system comprises a multi-parameter water quality monitoring module, an intelligent self-adaptive filtering module, a hydraulic cyclone enhanced separation module, a self-cleaning and backwashing module and a central control and data processing module. According to the method, river sediment characteristics are monitored in real time, filtering parameters are dynamically adjusted through an artificial intelligence algorithm, efficient sediment interception is achieved by combining hydraulic cyclone separation and multi-stage filtering, the problem of filtering medium blockage is solved through a self-cleaning mechanism, and meanwhile the self-adaptive learning capacity is achieved so as to optimize system performance. The system can significantly improve the filtering efficiency, reduce energy consumption and operation and maintenance cost, adapt to complex water quality working conditions, and guarantee safe and stable operation of key equipment of the pumped storage power station.