5830 results about "Water use" patented technology

The invention relates to the technical field of agricultural intelligent irrigation, and discloses a meteorological data fused water-saving irrigation control method, device and equipment and a medium. According to the method, a historical meteorological data set is constructed through multi-source meteorological data fusion, a dynamic water demand table is generated in combination with a crop water demand characteristic database, and a crop water demand model is established based on soil moisture content data. A grid irrigation unit division and growth period coupling soil moisture content response matrix construction technology is adopted, a cooperative constraint is established between a water demand threshold value and a water saving benefit through a multi-objective optimization learning algorithm, and a personalized irrigation scheme is generated. A soil moisture content dynamic evaluation matrix containing a dynamic time warping operator is designed, and dynamic matching of the soil layered soil moisture content and a standard template is achieved. The contradiction between meteorological response lag and low water resource utilization rate in traditional irrigation is effectively solved, accurate irrigation decision is realized through multi-dimensional data fusion and an intelligent optimization algorithm, and the water-saving benefit and the agricultural water resource utilization efficiency are improved.

The invention provides a water resource scheduling optimization method and system based on artificial intelligence. The method comprises the following steps: acquiring water resource multi-source heterogeneous data of a target area, generating a dynamic balance strategy according to a precipitation gradient change trend of precipitation distribution characteristic data and a consumption rate association relationship in user side water demand fluctuation mode data, and determining the water demand fluctuation mode of the user side on the basis of node pressure distribution characteristics of dynamic load data of a water delivery pipe network. Outputting a multi-target water delivery path optimization scheme in combination with a priority weight in a dynamic balance strategy, and converting the multi-target water delivery path optimization scheme into a scheduling instruction set for controlling a pump station valve in the geographic space topology; according to the technical scheme provided by the invention, the defects of non-uniform resource allocation, poor real-time response capability and the like of a traditional static scheduling strategy are overcome, the utilization rate of water resources is also improved, and the flexibility and the response speed of a water supply system are enhanced.

The invention discloses a modeling analysis method for optimizing an urban water supply pipe network, and belongs to the technical field of intelligent water affairs, and the method comprises the steps: building a comprehensive pipe network database, collecting hydraulic parameters through Internet of Things equipment, and fusing the hydraulic parameters with GIS topological data; constructing a dynamic hydraulic simulation model, coupling real-time data of a pressure sensor with an EPANET model, and correcting a friction resistance coefficient of a pipe section; a hybrid optimization algorithm architecture is designed, a double-target genetic algorithm is adopted for old pipe network transformation, and a constrained particle swarm algorithm is adopted for new pipe network planning; executing multi-stage optimization calculation, generating a pipe diameter feasible solution space in combination with geographical constraints, and iteratively outputting a scheme meeting a pressure threshold value; and generating a pipe network optimal configuration scheme, and outputting an engineering implementation list through spatial overlay analysis and valve regulation logic. According to the method, the problem of modeling distortion caused by a multi-source data island is solved, the defect that a static model is difficult to adapt to dynamic water demands is overcome, and the economical efficiency and the engineering implementability of a pipe network optimization scheme are remarkably improved.

The invention discloses a flexible load multi-target collaborative scheduling system and method, and relates to the technical field of collaborative optimization of power systems. The method is used for solving the problem of lack of accurate prediction and multi-target coordination of agricultural electricity and water utilization regulation and control. Firstly, based on meteorological data, soil moisture content and crop growth characteristics, an irrigation demand prediction model is constructed, irrigation water demand is predicted, and a water pump load power baseline is generated; then, a dynamic baseline constraint condition is generated in combination with historical behavior data and water pump start-stop logic; establishing a power grid side objective function, a user side objective function and a water affair side objective function, and introducing an underground water and carbon emission punishment mechanism; thirdly, dividing the power distribution network into sub-regions, adopting an alternating direction multiplier method to solve a region regulation and control strategy in parallel, coordinating water resource distribution conflicts through virtual interactive variables, and outputting a global scheduling instruction; and finally, collecting real-time response data and correcting the prediction model on line to realize closed-loop adaptive optimization.

The invention relates to the technical field of water pump control, and provides a water supply and drainage pump set assembly and a digital control system, which realize self-adaptive control under a complex working condition by fusing multi-source data such as pressure, flow and temperature, break through the dependence of traditional control on a single parameter, and improve the response capability of the control system to water fluctuation and equipment state change. Based on a long-short-term memory network trained by historical multi-source data, a control system can predict a pressure set value in advance, the pressure set value is solved through a particle swarm algorithm, and weight fusion is performed according to the predicted pressure set value and the solved pressure set value to generate an adjustment instruction, so that the starting and stopping times of equipment and mechanical wear are reduced, and the service life of the equipment is prolonged. The maintenance cost is reduced, and water resource waste is avoided through accurate control; and meanwhile, through a redundancy design and a fault-tolerant mechanism, the control system can still operate stably under the scenes of sensor faults, equipment abnormity and the like.

The invention relates to the technical field of water resource scheduling, and provides an urban inland river system intelligent resource scheduling management system and method based on dynamic data collaboration, and the method comprises the following steps: S1, collecting river hydrological data, water quality indexes, urban water demands and water transfer facility state data in real time, and carrying out the time-space alignment and abnormal value filtering; s2, a hydrodynamic force-water quality coupling model of multiple water sources is established, a multi-objective optimization model is established in combination with constraint conditions of ecological base flow and an engineering upper limit, and the multiple water sources include but not limited to river water, underground water, reservoir water, reclaimed water, rainwater and desalinated seawater; and S3, carrying out global dynamic optimization on the water transfer proportion and the water transfer facility parameters by adopting a model algorithm, and minimizing the water transfer cost and the ecological influence. By quantifying the maximum flow upper limit and the ecological base flow threshold value of each water source and optimizing the water transfer proportion and facility parameters, the water resource utilization efficiency is improved, and it is guaranteed that the water transfer cost and the ecological influence are balanced in the urban river water dispatching process.

The invention discloses a multi-target water supply scheduling method and system based on big data driving, and the method comprises the steps: collecting the multi-source data of a plurality of water supply targets, and enabling the scheme to obtain more reliable data support in the scheduling planning of the water supply targets; based on multi-source data serving as input features, the scheme combines the multi-source data with a graph space-time prediction model, a season statistical model and a gradient lifting regression model to obtain water consumption predicted by the three models respectively, prediction results of the three models are integrated through error adaptive weighting, more reliable predicted water consumption requirements are obtained, and the prediction efficiency is improved. And after the linear distribution model of the water source and the water supply targets is solved, initial water supply distribution schemes in one-to-one correspondence with the multiple water supply targets are obtained, the water supply accuracy of the water supply targets can be improved, multiple costs are used as targets to be minimized, and after multi-constraint combined solving, the water supply accuracy of the water supply targets can be improved. Therefore, the scheduling cost optimization is considered under the condition that the multi-target water supply scheduling meets flexibility and reliability.

The invention discloses a regional water supply emergency scheduling method and system. The method comprises the following steps: fusing GIS and IoT data to construct a dynamic three-dimensional topology model; historical water consumption and meteorological data are decomposed through wavelet multi-scale decomposition, and a prediction model is input to obtain a water consumption prediction value of a scheduling day period; on the basis of reservoir water storage, flow, water quality, rainfall and pollution source data collected in real time, a flow-water quality coupling model is used for predicting the reservoir inflow and water quality of a dispatching day; the method comprises the following steps: establishing a multi-objective function by combining water consumption prediction, storage prediction and current water storage, embedding a water quality constrained multi-objective optimization model, and solving by adopting an NSGA-II algorithm to obtain a Pareto optimal scheduling scheme set; and finally, a scheme is selected to be issued and executed. According to the method, data-physical collaborative intelligent scheduling decision is realized, the water supply demand is met under the condition that the water supply quality is stable, the condition of water shortage of the user terminal is avoided, and the water quality of the user terminal can continuously reach the standard.

The invention provides an intelligent water affair scheduling method based on LSTM and multi-objective optimization, and belongs to the technical field of intelligent water affair management and urban water supply system optimization. Comprising the following steps: based on water consumption data, performing analysis through a long short term memory neural network to obtain water consumption demand prediction; based on the water consumption demand prediction, combining pipeline information and pipe network layout data, performing pipe network pressure partition optimization, and obtaining a pipe network layout optimization result; and based on the pipe network layout optimization result, combining the historical operation data of the equipment and the water demand prediction, carrying out efficiency analysis on the pump station equipment to obtain an operation combination scheme of the equipment.

An intelligent fertilization and water supply method and system. The method comprises the following steps: step a, comprehensive soil monitoring, involving: comprehensively monitoring various soil indexes by means of a plurality of sensors, so as to obtain real-time data of the soil indexes; b, consideration of crop-specific requirements, involving: for the varieties and growth stages of different crops, thoroughly studying the unique moisture and nutrient requirements of the crops, so as to ensure the rationality and accuracy of a fertilization amount; c, comprehensive consideration of environmental factors, involving: collecting data of surrounding environmental factors; d, utilization of an intelligent irrigation mode, involving: by using a cyclic irrigation mode, an intermittent irrigation mode, etc., in combination with the water requirement pattern of each crop and a change in soil moisture, realizing efficient water utilization; e, implementation of a dynamic fertilization plan, involving: on the basis of a change in a crop growth condition and in soil fertility, dynamically adjusting fertilization time, frequency and dosage, so as to ensure that the nutrient supply matches the requirements of each crop; and f, implementation of a precise fertilization technique, involving: precisely delivering fertilizer to an absorption part of each crop, so as to improve the efficiency of nutrient utilization.

The invention discloses an intelligent precise farmland irrigation direction control system based on the Internet of Things, and relates to the technical field related to intelligent irrigation. Comprising a data acquisition module, a data processing and analyzing module, a data labeling and classifying unit, a three-dimensional coordinate model building module, a nozzle angle adjusting device, a nozzle water quantity adjusting unit and a control instruction execution unit. According to the invention, the distance between the nearest nozzle and the water-requiring position is calculated, so that irrigation water can reach the water-requiring area more efficiently, the distance is accurately calculated to ensure that water can be quickly and accurately conveyed to the required area, water loss and energy waste caused by long-distance water conveying are avoided, the water spraying direction is adjusted in combination with the wind direction and the wind speed, and the water spraying efficiency is improved. The device can effectively cope with the influence of natural wind on irrigation, and by monitoring wind direction and wind speed information in real time and combining the wind direction and wind speed information with water spraying parameters of the spray head, the system accurately calculates horizontal and vertical angle adjustment values of the spray head, so that sprayed water flow can accurately reach a water needing position.

The invention discloses an urban resident water consumption behavior classification method based on an intelligent water meter, and relates to the technical field of intelligent water affairs. The method is used for improving water consumption behavior recognition and anomaly detection precision. The method comprises the steps that firstly, a water flow change direction sequence is generated in real time through an intelligent water meter, and flow gradient and timestamp density characteristics are captured and extracted based on a stable persistence trigger event; then, eliminating water hammer noise by adopting an adaptive filtering mode, extracting a key turning point in combination with curvature analysis, comparing the key turning point with a behavior pattern library topology, and generating a dual-channel behavior feature vector; further, metering grids are divided according to valve distribution in the building water supply system, distribution clustering is executed in combination with the pressure gradient, and a cross-grid abnormal feature conduction path is constructed; and finally, tracing an abnormal diffusion path by means of a multilayer graph convolutional network, positioning a water pressure abrupt change inflection point, mapping the water pressure abrupt change inflection point to a building component, and outputting a leakage point identifier and a behavior mode label, thereby realizing high-precision classification and abnormal identification of residential water consumption behaviors.

The invention provides an intelligent management method and system for reducing pollution and carbon of rural domestic sewage. According to the method, sewage flow velocity, COD concentration, ammonia nitrogen content data, user water use time and detergent use amount are collected, and a database is constructed. And weighting the flow velocity and COD to generate a pollution load evaluation value, and calculating an organic matter pollution influence value in combination with ammonia nitrogen and detergent data. A porous ceramic medium is arranged in the biological treatment device, and the dissolved oxygen concentration is adjusted according to the pollution load. A correlation curve of a COD concentration peak value and water consumption time is established, a prediction model is constructed in combination with dissolved oxygen parameters, the gas injection and reflux ratio is adjusted through graded pressure instructions, and the critical value of dissolved oxygen is maintained. The day and night temperature difference is fused to correct the degradation rate, and the optical detection data is combined to optimize the critical range and the instruction priority, so that the cooperative control of sewage treatment and carbon emission reduction is realized. According to the invention, self-adaptive adjustment of dissolved oxygen in sewage treatment is realized, and the sewage reduction and carbon reduction management efficiency of domestic sewage is improved.

The invention discloses a unit area irrigation water consumption estimation method and system based on multi-source data fusion, and relates to the field of irrigation water consumption estimation. Multi-source heterogeneous data such as remote sensing images, meteorological data, soil humidity and crop growth information are fused, and observation and model errors are reduced through data assimilation; estimating crop evapotranspiration under an energy balance principle; estimating daily-scale irrigation water consumption by adopting a water balance method; a crop actual irrigation area identification model based on deep learning is introduced, actual irrigation areas of different crop types are effectively distinguished, and the influence of temporal and spatial changes on irrigation efficiency is dynamically reflected. According to the method, high-precision and rapid estimation of the comprehensive unit area irrigation water consumption of a single crop and multiple crops on different regional scales can be realized, the timeliness and accuracy of irrigation water quota evaluation are remarkably improved, and the method has strong adaptability to climate change, soil difference and crop diversity and is suitable for popularization and application. Powerful technical support is provided for precise irrigation and intelligent water conservancy management.

The invention relates to an inter-basin water saving amount transaction and scheduling optimization method, which comprises the following steps of: performing dynamic contrast analysis on water saving behaviors and water resource response on the basis of historical water consumption behaviors, resource regulation and control records and meteorological basic data, judging the autonomy and continuity of the water saving behaviors, and obtaining the right-confirmable water saving amount; according to the watershed water resource tension degree, the water ecology sensitivity and the water transfer cost, a cross-watershed conversion rule is adopted, a conversion scale factor is set, and resource value transverse butt joint of water saving behaviors of different areas is achieved; calculating the flow attenuation, the regional bearing threshold and the water quality compatibility in the allocation path based on the water-saving amount obtained by the water-saving transaction, and determining the available transmission range and the sustainable allocation amount of the water-saving amount; and according to the distribution of the water-saving quotas and the corresponding value grades, carrying out combined screening according to the use priority, the basin compensation relationship and the space-time adaptation requirements, outputting a resource allocation scheme, and forming a cross-basin water-saving-quantity-driven water resource optimal allocation structure.

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 discloses a time-phased intelligent pressure regulation management method and system for secondary water supply, and belongs to the technical field of water supply management, and the method specifically comprises the steps: dividing a day into a water consumption peak period and a water consumption low period based on historical water consumption flow data, and determining the starting and ending time nodes of each time period; through hydraulic calculation and actual water supply pressure monitoring, a pressure control point at the tail end of the water supply system is locked, and water supply pressure data of the point are collected in real time; in the water consumption peak period, a peak pressurization control strategy is executed; in the water consumption low-peak period, analysis is conducted according to historical water supply pressure data of a tail end pressure control point, and a low-peak period pressure safety threshold value is set; a pressure instruction is sent to a control system according to the threshold value, and water supply equipment is controlled to output pressure according to the threshold value; the water supply pressure of a tail end pressure control point is monitored in real time, and when the pressure is lower than a low-peak-period pressure safety threshold value, pre-alarm is triggered, and pressure changes are continuously recorded; and if the pre-alarm state is not finished continuously, switching to a peak-period peak pressurization control strategy.

The invention discloses a fire hydrant pressure adaptive regulation and control system based on Internet of Things data, and relates to the technical field of urban water supply pipe network fire hydrant pressure control, and the system comprises a multi-source data collection module which is used for collecting fire hydrant pressure time sequence data in real time from a plurality of Internet of Things nodes deployed in an urban water supply pipe network, and historical pressure data, pipeline topological structure data and user water consumption mode data of the water supply network are obtained from a historical database. Real-time and historical data are integrated through the multi-source data acquisition module, a comprehensive basis is provided for pressure regulation and control in combination with a pipe network topology and a user water consumption mode, and the integrity of data support is improved; the pipe network state prediction module is used for extracting multi-dimensional features and predicting pressure changes by means of an LSTM model, the pressure abnormal risk can be recognized in advance, and hysteresis of traditional regulation and control is avoided.

The invention belongs to the technical field of water supply network adjustment, and particularly relates to a water supply network pressure and flow adjusting method. The method comprises the following steps: firstly, collecting pressure, flow and water temperature data of a monitoring node at present and in a preset time period, wherein the preset time period is set according to a water consumption period; preprocessing flow data through a sliding window method and fitting a curve, and marking an instantaneous disturbance time period; the dynamic response coefficient of each disturbance time period is calculated, and water temperature correction is needed; combining the flow standard score, the dynamic response coefficient and the real-time deviation coefficient to obtain a flow dynamic regulation index; a pressure stability index is obtained through pressure and water temperature trend feature vector matching; the two are subjected to weighted fusion to form a pipe network comprehensive regulation factor, and the valve opening and the water pump power are regulated accordingly. The method can accurately identify instantaneous disturbance, improve the adjustment precision and response speed, and guarantee stable water supply.

The invention discloses an intelligent water meter operation monitoring method and system based on the Internet of Things, and relates to the technical field of intelligent water meters. According to the method, a disturbance consistency scoring index Ipd and a behavior map variation score Simv are constructed, and a multi-parameter coupling backtracking risk grade scoring function Rtrace is introduced; the disturbance sudden change intensity, the period stability, the flow direction consistency and the historical behavior deviation degree can be comprehensively considered, and the recognition precision of the unnatural disturbance water flow and the potential abnormal water consumption behavior is effectively improved. Particularly, under the condition that disturbance abnormity and behavior map abnormity are coupled, secondary comparison evaluation is carried out on a backtracking risk grade scoring function Rtrace and a risk interval threshold value, so that risk judgment and risk grade division with higher distinction can be realized, illegal water taking, backflow and backward flow and other abnormal water consumption behaviors can be accurately locked under the condition of a low misjudgment rate, and the accuracy and the reliability of the system are improved. And the intelligent sensing capability and the behavior modeling reliability of the urban water supply system are enhanced.

The invention provides an intelligent irrigation district management method and system based on the Internet of Things, and the method comprises the steps: obtaining the real-time irrigation water amount and water pump energy consumption data of each water conveyance channel in a target irrigation district; according to the real-time irrigation water amount and the water pump energy consumption data, generating a dynamic water resource supply and demand relation graph; determining a target water delivery channel corresponding to the water resource transaction request of the water consumption terminal of each irrigation area from a target irrigation area, and if any target water delivery channel has a condition that a water pump is overloaded or a deposition diffusion coefficient value is greater than a preset diffusion coefficient threshold value, determining the water resource transaction request of the water consumption terminal of each irrigation area based on a dynamic water price adjustment rule and a dynamic water resource supply and demand relationship graph, generating a water resource transaction price of the target water conveyance channel; and according to the water resource transaction prices of all the target water conveyance channels and the node states in the dynamic water resource supply and demand relationship graph, generating target water conveyance optimization parameters of each target water conveyance channel. The water resource allocation efficiency of the irrigation area and the operation stability of the water conveying system are improved.

The invention discloses a staged design flood estimation method under the influence of climate change and reservoir regulation and storage. The method comprises the following steps: acquiring meteorological and hydrological data, human water consumption data and global climate mode output data of a reservoir; a reduced natural reservoir runoff series is obtained based on a water balance method, a GR4J-9 hydrological model is calibrated to achieve natural reservoir runoff simulation, and a long-short-term memory model is constructed to simulate the influence of human activities such as reservoir regulation and storage on runoff; based on a global climate mode set and a quantile deviation correction method, driving a GR4J-9 hydrological model and a long-short term memory model to obtain a reservoir runoff series under climate change and performing flood season staging; establishing a staging design flood calculation model of a future scene based on a Copula function, and deducing the most probable staging design flood; and constructing an emergence constraint model based on the dew point temperature so as to obtain a corrected stage design flood result. According to the method, the comprehensive influence of climate change and reservoir regulation and storage is considered, and a reference basis is provided for deducing stage design flood.

The invention relates to the technical field of greening irrigation equipment, in particular to urban greening green plant irrigation equipment which comprises a supporting plate, a water inlet pipe is fixedly connected to the center of the supporting plate, a grounding support is rotatably mounted on the lower end face of the supporting plate, and a uniform sprinkling irrigation assembly is fixedly mounted at the upper position of the peripheral wall of the water inlet pipe; the uniform sprinkling irrigation assembly comprises two sealing bearings fixedly installed on the peripheral wall of the water inlet pipe, and the outer rings of the two sealing bearings are fixedly connected with an irrigation frame. The spray pipe can perform vertical reciprocating swing spray irrigation during forward and reverse rotation, the irrigation range is greatly widened, the comprehensiveness and sufficiency of the green plant irrigation effect are improved, meanwhile, the rotary spray irrigation rate and the irrigation water flow can be adaptively adjusted according to the air humidity, the green plant irrigation effect is further improved, and the green plant irrigation efficiency is improved. More accurate irrigation operation can be carried out on the green plants, and the water waste condition of the irrigation operation of the green plants can be reduced.

The invention provides an irrigation district water resource scheduling optimization method based on cloud computing, and the method comprises the following steps: collecting irrigation district multi-source data in real time through a space-air-ground integrated sensing network, and uploading the data to a cloud platform after preprocessing; the method comprises the following steps: constructing digital twin bodies of an irrigation area in a cloud platform, dividing the irrigation area into a plurality of sub-areas according to water consumption attributes, and integrating hydraulics and hydrological agriculture models; real-time data and future weather information are fused, and a water demand prediction value is generated through a water demand prediction model by taking the sub-region as a unit; a scheduling scheme is generated by adopting a multi-objective optimization algorithm based on the predicted value, and the minimum economic benefit, water resource utilization rate and energy consumption are taken as optimization objectives; and performing simulation evaluation on the scheme by using the digital twinborn body, outputting a performance index aided decision, and finally determining an optimal scheduling scheme. According to the method, accurate prediction, dynamic optimization and intelligent scheduling of the water resources in the irrigation area are realized, and the utilization efficiency of the water resources and the irrigation management level are improved.

The invention discloses a hydrological data model fusion analysis method based on water resource scheduling decision support, and relates to the field of water resource scheduling, and the method comprises the steps: loading an HMM-BP noise detection model, obtaining a multi-source data fusion model, and outputting a space-time grid data cube; constructing a water consumption behavior prediction unit through a TPB decision tree model, adding a water right transaction engine, and outputting a water consumption prediction value, a behavior of an intelligent contract protocol and a transaction cooperation model; an incremental method is adopted to generate N combined scene matrixes of rainfall and temperature rise correlation adjustment, an ecological stability evaluator is combined, a climate and ecological coupling model is constructed, and a scene and risk mapping table and a resource re-allocation weight are output; and constructing an intelligent rule base platform to obtain an executable decision logic tree. The system has the advantage that full-chain intelligentization of water resource scheduling is realized through modular integration. Therefore, social and market collaborative prediction, climate and ecological risk quantification and adaptive decision support are achieved.

The invention discloses a method for recycling and treating production wastewater of a concrete mixing plant, belongs to the technical field of solid-containing wastewater recovery, and aims to solve the technical problems that the recyclable consumption of the wastewater of the concrete mixing plant in the concrete processing process is low and fine aggregates and gel materials in the wastewater are not effectively recovered in the prior art. The method specifically comprises the following steps: adding the wastewater generated by the mixing plant into a settling tank, standing and settling for 1-3 days, and separating liquid to obtain settled slag and settled liquid. Solid impurities in the wastewater of the concrete mixing plant are regenerated and recycled and then are combined with fly ash to reinforce concrete; according to the present invention, the plasticizing performance and the pumpability of the concrete material are effectively improved, the compressive strength and the chloride ion permeation resistance of the concrete material are improved, and the prepared reuse water can be directly used for concrete production and processing, and is not affected by the addition amount.

The invention discloses an intelligent faucet, and relates to the technical field of kitchen and bath intelligent water equipment, the faucet comprises a data acquisition module, a flow matching module, a delay determination module and an MCU; the data acquisition module acquires hand data through double infrared sensors, and transmits the hand data to the MCU after background reference value calibration, gesture state marking and abnormity filtering; the traffic matching module constructs a time sequence track matrix, extracts features and normalizes the features to match corresponding traffic; and the delay judgment module generates a standard matrix template based on the scene, and adjusts the water outlet delay through cosine similarity comparison. According to the invention, while the sensing reliability of the faucet is improved, accurate flow adaptation and delay optimization are realized.

The invention discloses a control method of a gas water heater, the gas water heater and a storage medium. The method comprises the steps that the gas water heater is controlled to be shut down; a fan in the gas water heater is controlled to execute post-cleaning operation, and whether a water using signal of the gas water heater exists or not is detected; when the water consumption signal is detected, the fan is controlled to stop executing post-cleaning operation, and the gas water heater is controlled to execute ignition operation; and when the water consumption signal is not detected, the fan is controlled to maintain execution of post-cleaning operation until the operation duration of the post-cleaning operation is longer than the target duration. The invention aims to effectively shorten the restarting time of the gas water heater after the gas water heater is shut down and ensure the use safety of equipment at the same time.

The invention discloses multi-pump collaborative variable-frequency energy-saving water supply equipment and a control method, belongs to the technical field of intelligent control of water supply equipment, and aims to solve the problems of high energy consumption and poor adaptability of traditional water supply equipment. The method comprises the following steps: collecting water consumption data, extracting features through a sliding window, screening parameters through principal component analysis to construct a feature parameter set, dividing feature clustering groups in combination with time attribute clustering, and associating water consumption time periods and demand intensity grades to construct a typical water consumption mode; according to the water pump performance curve and the attenuation index, constructing an updated dynamic capability matrix; matching a target water consumption mode, screening water pumps to construct an execution pump set, decomposing a flow demand and distributing a load to generate a regulation and control instruction; and executing the instruction and counting the deviation accumulated duration, and judging whether to update the instruction. Dynamic adaptation of the water pump set and the water demand is achieved, and the water supply stability and the energy saving performance are improved.

The invention relates to a method for calculating the slag entrapment amount of continuous casting covering slag based on computational fluid mechanics, which adopts a large eddy simulation (LES) turbulence model, a multiphase flow model (VOF) and a discrete phase model (DPM) in CFD calculation, and combines a grid self-adaptive coarsening and refining mechanism and a VOF-to-DPM conversion mechanism. The method is used for numerical simulation and control of the slag entrapment amount of the continuous casting covering slag under the argon blowing condition, a slag entrapment mode calculation result is verified through a water model experiment, and a numerical simulation calculation result obtained through the method is well matched with a water model experiment result. Compared with the prior art, the method has the advantages that the slag entrapment amount of the continuous casting covering slag can be effectively calculated, and a basis is provided for controlling the slag entrapment amount of the covering slag.