11 results about "Water aging" patented technology

The invention discloses a water quality degradation early warning method and system for a water supply pipe network in a low-pressure area. The method comprises the following steps: S1, collecting topological structure data and pressure, flow, residual chlorine concentration and turbidity data of an urban water supply pipe network, and preprocessing the topological structure data and the pressure, flow, residual chlorine concentration and turbidity data; s2, constructing an initial node feature matrix, a pipe network node graph model, an adjacent matrix and a low-pressure area identification matrix; sequentially extracting a first pipe network spatial feature, a second pipe network spatial feature and a water flow stagnation time sequence feature, and fusing to obtain a space-time coupling feature; s3, extracting space-time coupling characteristics of the low-voltage area, and calculating to obtain a water age distribution matrix of each node of the low-voltage area; s4, residual chlorine attenuation characteristics are constructed, and then a low-pressure area residual chlorine concentration prediction sequence and a low-pressure area water quality degradation risk matrix are calculated; and S5, performing graded early warning. According to the method, the problems of inaccurate water age distribution inversion and inaccurate water quality risk prediction caused by residual chlorine attenuation prediction of the low-pressure area of the water supply network in a traditional method can be solved.

The invention discloses a lake ecological water transfer water age-carbon emission multi-objective optimization method based on an agent model. The method comprises the following steps: constructing a lake basin hydrological model based on an SCS-CN model and an impervious area method; an EFDC hydrodynamic model is constructed; estimating the average water age of the lake based on a Lagrangian particle tracking method, and estimating ecological water transfer carbon emission according to the lake inlet flow of the water transfer project; training based on a random forest regression model to obtain an agent model which takes the ecological water transfer control parameters and the basin confluence into lake flow as input and takes the average water age of the lake and the ecological water transfer carbon emission as output; constructing a multi-target collaborative optimization model for minimizing the average water age of the lake and minimizing the carbon emission of ecological water transfer according to the agent model; and solving the multi-objective collaborative optimization model. According to the method, combined optimization scheduling of water age improvement and carbon emission minimization of the urban lake area is realized, the ecological stability and low-carbon operation capability of the urban lake area are enhanced, and the method can be applied to the technical field of ecological regulation and control.

The present application relates to the technical field of secondary water supply control, and particularly relates to a water tank water age monitoring and early warning method and system based on the Internet of Things, which can comprehensively acquire water tank water quality and user water consumption information through multi-modal data acquisition and fusion; can master water tank water age changes in real time, discover potential problem areas in time, and guarantee water tank water quality safety by constructing a dynamic model and identifying abnormal areas; can provide a benchmark for comparative analysis of abnormal conditions by determining normal flow areas, so that early warning processing is more targeted; can accurately evaluate the severity of abnormalities by quantifying the spectral shift distance of the coupling oscillation mode of abnormal and normal areas; can start adaptive sampling according to the spectral shift distance, dynamically improve the monitoring accuracy of abnormal areas, capture details of water age changes in time, and provide reliable data for prediction and early warning; and can predict water age mutations and generate graded early warning instructions by training a neural network, so as to facilitate relevant personnel to respond in time and reduce water tank water quality risks.

The invention provides a multi-source energy supply water tank water age self-adaptive control method and device and electronic equipment, and relates to the technical field of water supply system monitoring control, and the method comprises the steps: calculating the water age of a to-be-controlled multi-source energy supply water tank based on an initial high liquid level threshold value, an initial low liquid level threshold value, the bottom area of the to-be-controlled multi-source energy supply water tank, and the average water flow calculated according to the historical water outlet flow; estimating the theoretical average water age under the current operation parameters; and based on the adjustment decision, updating a high liquid level threshold value and / or a low liquid level threshold value obtained by comparing the current liquid level value with the initial low liquid level threshold value and the initial high liquid level threshold value, so that the average water age of the to-be-controlled multi-source energy supply water tank in actual operation dynamically and stably approaches the target water age. Energy is supplied to the system through solar energy and a lithium battery, the water quality can be evaluated in real time, and on this basis, the high and low liquid level set values are dynamically adjusted, and the average water age of the water tank is actively controlled within a preset safety range.

The application discloses an ultrahigh anti-aging polypropylene composite material and a preparation method and application thereof. The composite material comprises the following components in parts by weight: 95-100 parts of polypropylene, 5-15 parts of ethylene-octene copolymer, 0.1-2 parts of an anti-aging compound, 2-5 parts of terpene resin, 2-5 parts of naphthenic oil, 0.5-5 parts of stearic acid and 0.5-5 parts of zinc stearate. The anti-aging compound comprises the following components in a weight ratio: 10-30% of modified graphene oxide / hydrotalcite, 10-30% of modified triazine charring agent, 20-40% of antioxidant and 20-40% of light stabilizer. The polypropylene composite material provided by the application has remarkably improved anti-aging properties, including heat-oxygen aging resistance, hot water aging resistance, light aging resistance and the like, and has good flowability and dispersibility, water resistance, yellowing resistance, good processing performance and mechanical properties and excellent comprehensive performance.

The application relates to the technical field of pipe network water quality monitoring, in particular to a water supply pipe network water quality intelligent monitoring system. The system comprises a spatial feature analysis module, which is used for collecting the water age of each monitoring point in the water supply pipe network and various water quality parameters at each time; the spatial consistency index of a target monitoring point at the same time is obtained by using the numerical change range of various water quality parameters of the target monitoring point and adjacent monitoring points upstream and downstream of the target monitoring point; a flow velocity adjustment factor acquisition module is used for acquiring the flow velocity adjustment factor of the target monitoring point at one time; a real anomaly index acquisition module is used for acquiring the real anomaly index of the target monitoring point at one time; and an anomaly score correction module is used for correcting the initial anomaly score of the target monitoring point at one time by using the flow velocity adjustment factor and the real anomaly index of the target monitoring point at one time to obtain a corrected anomaly score. The application can accurately monitor the water quality of the water supply pipe network.

The invention relates to a swimming pool water circulation filtration and energy consumption optimization control method and system, and belongs to the field of energy consumption control. The method comprises the following steps: acquiring swimming pool data, and constructing a three-dimensional water age field by establishing a water age field control equation; carrying out coupling transmission prediction based on the three-dimensional water age field, and outputting a pollutant concentration prediction map and a disinfectant concentration prediction map; a directional circulation strategy is generated based on the three-dimensional water age field, and optimized circulation system control parameters are obtained; on the basis of a directional circulation strategy, a pollutant concentration prediction map and a disinfectant concentration prediction map are combined, a disinfectant adding and water supplementing strategy is further optimized, and a comprehensive control instruction is output; and executing the comprehensive control instruction and carrying out real-time adaptive correction and learning optimization. According to the intelligent control method based on three-dimensional water age field modeling, coupling transmission prediction and multi-objective optimization, accurate, efficient and self-adaptive regulation and control of swimming pool water circulation and water quality management are achieved.

This invention provides a multi-tank peak-shaving and water storage system and method, relating to the field of water tank storage technology. The system includes: collecting water tank data and real-time pipeline flow rate, and processing this data to obtain the peak water usage period, real-time water age, and predicted water consumption for future periods for each water tank; processing the real-time pipeline flow rate under each storage area, the predicted water consumption of each water tank, the peak water usage period, the real-time liquid level, and the real-time water age to obtain the storage high liquid level for each water tank during peak water usage periods, the off-peak high liquid level during off-peak water usage periods, and the valve-opening water intake period; controlling the corresponding water tank to fill to the storage high liquid level when the real-time liquid level reaches a preset minimum liquid level during the valve-opening water intake period or during peak water usage periods, and controlling the corresponding water tank to fill to the off-peak high liquid level when the real-time liquid level does not reach the preset minimum liquid level during the valve-opening water intake period or during off-peak water usage periods. The beneficial effect is to prevent artificially created peak periods caused by scheduling based solely on the data characteristics of a single water tank.

The invention discloses a high-toughness waterproof epoxy adhesive and a preparation method thereof, and belongs to the technical field of adhesives. The high-toughness water-resistant epoxy adhesive is prepared from a component A and a component B, the component A is prepared from the following raw materials in parts by weight: 50 to 80 parts of bisphenol A type epoxy resin, 10 to 25 parts of carboxyl-terminated liquid nitrile rubber, 3 to 10 parts of nano montmorillonite and 1 to 5 parts of silane coupling agent; and the component B comprises the following raw materials in parts by weight: 30-50 parts of a modified alicyclic amine curing agent and 10-30 parts of silica powder. The high-toughness water-resistant epoxy adhesive disclosed by the invention is excellent in water aging resistance while keeping high peel strength and impact toughness, and is particularly suitable for bonding metal and composite material structures in ships, underwater facilities, outdoor buildings and humid environments.

The invention discloses a water supply pipe network optimization scheduling method considering a water age nonlinear target, and the method comprises the steps: removing pipelines with small influence on water age, namely pipelines with small pipe diameter, small water flow and low water age sensitivity before iterative optimization, improving the iterative optimization efficiency of subsequent training, and efficiently obtaining a scheduling scheme of a water supply pipe network. According to the method, the upper limit and the lower limit of the set water age and the upper limit and the lower limit of the pressure are used for constructing an optimization objective function, so that an optimization result is prevented from deviating to a minimum or maximum water age node in a model training process, and the average water age and the water age deviation of the whole network can be remarkably reduced.

The invention belongs to the technical field of reservoir water environment prediction, and discloses a reservoir outlet water temperature rapid prediction method integrated with hydraulic connection. The problems that in an existing reservoir outlet water temperature prediction scheme, numerical simulation efficiency is low, and a machine learning model lacks physical process support of hydraulic connection and a time lag effect, so that robustness and applicability are poor are solved. The method comprises the following steps: collecting reservoir related data and scheduling data; establishing a numerical model to calculate the dam front water body water ages of typical years such as a wet water year, a flat water year and a low water year, screening water age abnormal values by adopting a Raida criterion, and determining the maximum reasonable water age; taking the maximum reasonable water age as a time sequence length of an input feature, and establishing a time sequence prediction model of historical boundary data and ex-warehouse water temperature based on an LSTM algorithm; in practical application, boundary data of the maximum reasonable water age length before a to-be-predicted time period is input into the trained LSTM time sequence prediction model, and a reservoir outlet water temperature prediction result is output.