2445 results about "Water consumption" patented technology

The invention relates to the technical field of soil monitoring, in particular to a farmland irrigation management and control system based on the Internet of Things, and the system comprises a soil monitoring module, a crop water demand analysis module, an irrigation strategy making module, an irrigation execution control module, a water source management module, a fertilizer distribution module, an irrigation effect evaluation module and an adaptability adjustment module. According to the method, the crop water demand is analyzed by combining the decision tree, the water consumption is accurately calculated, the irrigation strategy optimizes the time and frequency based on the linear programming and simulated annealing method, the scheme adaptation degree is improved, the irrigation link adopts an automatic control and dynamic adjustment mechanism, the environment and crop demand changes are adapted in real time, and the irrigation efficiency is improved. Water source allocation ensures efficient distribution of multiple water sources on the basis of dynamic optimization, the type and quantity of fertilizer feeding are accurately controlled according to crop requirements, the irrigation effect is subjected to self-adaptive optimization of an irrigation plan after crop data evaluation, and accurate, flexible and efficient farmland resource management is integrally achieved.

The invention discloses an intelligent irrigation control method and system based on meteorological information, and relates to the technical field of irrigation control, an area to be irrigated is divided into a plurality of sub-areas, and future rainfall (first rainfall) is predicted through a preset meteorological early warning model; acquiring water absorption data of each sub-region, calculating a water absorption coefficient, and determining absorbable rainfall (second rainfall) in combination with the first rainfall; and judging the water consumption of each sub-region according to the crop growth data and the historical data, and comparing the water consumption with the second rainfall. If the water consumption is greater than the second rainfall, the sub-region needs to be irrigated; according to the method, the soil water content of each sub-region can be finely judged, and whether rainfall meets the water demand or not is evaluated, so that whether irrigation is needed or not is judged, excessive irrigation and water resource waste are avoided, meanwhile, it is ensured that crops obtain enough water, water resource management is optimized, and the crop growth effect and agricultural production efficiency are improved.

The invention discloses a dynamic load adjusting method and system for dish-washing machine energy efficiency and water efficiency test, and the method comprises the steps: setting a test set of different dirt degrees and types of tableware proportions, carrying out the transient performance analysis of each washing mode, predicting the fluid flow and temperature distribution in a cavity of a dish-washing machine, and recognizing an abnormal region; a first objective function based on the washing effect is constructed to optimize water pump parameters to improve a water flow path, a second objective function is constructed to adjust heating element parameters, energy efficiency and water efficiency testing is conducted to determine the optimal washing period, the water pump parameters and the heating element parameters as optimal operation parameters, and a decision tree algorithm is introduced; and learning a mapping relation between the test condition and the optimal operation parameters, and adjusting the operation parameters of the dish-washing machine in real time by means of a control algorithm according to the tableware dirt degree and proportion. According to the method, the energy efficiency and water efficiency balance of the dish washing machine under different load conditions can be effectively improved, the washing effect is enhanced, energy consumption and water consumption are reduced, and meanwhile good interpretability is achieved.

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 maintenance method and system for the wall of a squat silo, and the method comprises the steps: applying controllable environment parameters to a concrete test block group with the same proportion through an environment simulation device, and obtaining test block deformation data, moisture content data and stress data; performing time sequence correlation mapping on the test block deformation data, the moisture content data and the stress data and environmental parameters to obtain a maintenance decision data set; acquiring a real-time environment vector through a sensor network deployed on the site of the squat silo; inputting the real-time environment vector into a maintenance decision model, and generating a spraying control instruction by matching the maintenance decision data set; and driving a spraying system to execute operation according to the spraying control instruction, and dynamically correcting spraying parameters based on moisture monitoring data. According to the method, through data-driven intelligent maintenance decision and dynamic closed-loop control, the crack risk of the wall of the squat silo is remarkably reduced, meanwhile, water resource consumption is reduced, and double breakthrough of maintenance quality and resource efficiency is achieved.

The invention discloses a rural water supply pipe network pressure monitoring analysis method and device based on digital twinning. The method comprises the following steps: collecting historical basic data of a rural prediction area; flow and pressure sensors are arranged at nodes of a rural water supply network to obtain monitoring data; uploading the data to a server through a data stream processing framework, and preprocessing the data to obtain preprocessed data; constructing a relational database management system to perform batch processing on the preprocessed data to obtain historical basic data and monitoring data after batch processing; constructing a rural pipe network water pressure prediction model; constructing a pipe explosion detection and water pressure control model; according to the physical data, constructing a rural water supply pipe network geometric model based on ArcGIS; and constructing a rural water supply pipe network system data model and realizing visualization of the operation state of the water supply pipe network. Rural water supply characteristics and water consumption characteristics are fully considered, intelligent management and control of the rural water supply system are achieved, and reliability and safety of rural water supply are effectively guaranteed.

The invention discloses an agricultural water utilization right distribution and transaction management method suitable for a high-water area, and particularly relates to the technical field of agricultural water utilization right management. A self-adaptive water right scheduling model is constructed, the water surplus and shortage conditions in the future 2-24 hours are calculated, the agricultural water quota is dynamically adjusted through a regional water right redistribution mechanism, and meanwhile, a water right transaction is divided into a long-term contract transaction and a short-term instant transaction based on an intelligent contract system of a block chain, so that the water right transaction efficiency is improved. The peasant households are allowed to match and dispense water resources in real time through the intelligent water right transaction terminal, the water right transaction matching rule is further adjusted in combination with historical transaction data, a water transfer execution effect and peasant household water consumption behavior analysis, and a regional water resource scheduling strategy is adaptively adjusted; accurate irrigation, efficient water right circulation and intelligent scheduling are achieved, the utilization efficiency of agricultural water resources is effectively improved, stable production of farmlands is guaranteed, meanwhile, a water right market circulation mechanism is adjusted, and the flexibility and the intelligent level of water resource regulation and control are improved.

The invention discloses an irrigation area scale irrigation water consumption monitoring method based on physical constraint machine learning, and is applied to the technical field of irrigation water consumption monitoring. Comprising the following steps: constructing a space-time continuous sequence of irrigation response characteristics of an irrigation area by using a multi-source data integration and assimilation technology; the irrigation water amount balance equation and the earth surface energy conservation law are used as regularization terms of physical constraints to be embedded into the training process of the long and short term memory deep learning model, so that an irrigation water amount prediction model is established; and dynamically estimating the irrigation water consumption of the irrigation area based on the irrigation water consumption prediction model obtained by training. According to the method, the water balance equation and the energy conservation law are embedded into the machine learning model, so that the model prediction result follows the basic physical law, and water consumption estimation violating the physical common sense is avoided. The introduction of the physical constraint improves the robustness and generalization ability of the model under an unconventional climate condition or a limited training data condition, and enhances the credibility and interpretability of a result.

The invention discloses an agricultural and pastoral area water network regulation and storage project scale determination method and system. The method comprises the following steps: collecting historical data of an agricultural and pastoral area, dividing the agricultural and pastoral area into a plurality of secondary sub-areas, respectively calculating the water demand and available water consumption of each secondary sub-area, and identifying a water shortage time period and a water shortage area; constructing a regulation and storage project layout scheme set, and calculating the regulation and storage capacity and project parameters of each regulation and storage project; constructing a single-target optimization model, simulating a regulation and storage result of each regulation and storage project layout scheme, evaluating each regulation and storage project layout scheme, and screening out an optimal regulation and storage project layout scheme; and constructing an irrigation scheduling optimization model based on the optimal regulation and storage project layout scheme, solving the model to dynamically optimize and adjust the water storage time, the water discharge time and the water discharge amount of the regulation and storage project, and generating an agricultural and pastoral area water network regulation and storage project layout scheme. The water resource utilization efficiency of agricultural and pastoral areas is improved, the water resource supply and demand contradiction is relieved, and sustainable development of agriculture and animal husbandry and ecological environment improvement are promoted.

The invention discloses an intelligent water affair management method and system based on artificial intelligence, and relates to the technical field of intelligent water affair management, and the method comprises the steps: initializing a pipe network digital twinborn model, loading pre-stored pipe network GIS data, collecting pipeline pressure data, water quality parameters and user water consumption in real time, inputting a risk assessment model, calculating a real-time risk probability, and carrying out the real-time risk assessment. When the real-time risk probability exceeds an early warning threshold value, generating a high-risk early warning signal; based on the high-risk early warning signal, a differential order parameter and an integral gain parameter are calculated through a pipe state fractional order controller, a voltage stabilization control instruction is generated and executed, and meanwhile a control error signal in the voltage stabilization process is extracted; inputting the control error signal and the water source type label into the element reinforcement learning model, and dynamically optimizing the differential order parameter and the integral gain parameter to obtain a water source risk coefficient; according to the method, personalized modeling and dynamic updating of risk assessment are realized by outputting the dynamic response characteristic data.

The invention relates to the technical field of agriculture, in particular to a greenhouse energy-saving water consumption monitoring system which is used for solving the problems that in the prior art, historical data and real-time data cannot be combined to accurately predict irrigation water consumption, scientificity and rationality of an irrigation strategy cannot be guaranteed, and the irrigation cost is low. And different environmental conditions and crop growth stages cannot be dynamically adapted. Historical data and real-time data are combined through the irrigation water consumption adjusting module, the irrigation water consumption is accurately predicted through a machine learning model, automatic adjustment is achieved to improve efficiency, multiple factors are comprehensively considered, scientificity and reasonability of an irrigation strategy are guaranteed, different environment conditions and crop growth stages are dynamically adapted, water resource utilization is optimized, and the irrigation efficiency is improved. Cost is reduced, personal errors are reduced through automatic operation, and various crops and complex growth environments are supported.

The invention relates to the technical field of error verification, and particularly discloses an error verification method and system for an intelligent water meter, which adopts a neural network model based on deep learning to carry out fine-grained time sequence feature extraction on time sequence data of temperature and pressure of a water body flowing through a multifunctional intelligent water meter in a target time period; according to the method, the time sequence change mode of the water body temperature and the pressure in each local time domain is captured, time sequence integral coding is carried out on the time sequence change characteristics of the water body temperature and the pressure in each local time domain to understand the time sequence accumulation effect of the water body temperature and the pressure on the water consumption in the global time domain, and intelligent prediction of the water consumption is achieved. And error verification is carried out on the intelligent water meter according to the difference between the prediction result and the measured value of the water meter. In this way, the measuring error of the intelligent water meter can be reflected more accurately, and then the error checking precision and the intelligent level of water affair management are improved.

The invention relates to the technical field of computer data processing, and particularly provides an intelligent washing parameter optimization decision-making method based on multi-modal perception fusion, which comprises the following steps: acquiring stain characteristic parameters of a fabric to be cleaned in real time through a multi-source acquisition module; constructing a collaborative regulation model, determining the type and proportion of the detergent and mechanical force parameters based on the stain characteristic parameters, training the collaborative regulation model by taking the maximization of the stain removal rate as a target and taking the energy consumption and the water consumption as constraint conditions, and outputting an optimal washing strategy; controlling the washing device to execute corresponding operation according to the washing strategy; stain residues and energy consumption abnormal data in the washing process are monitored in real time, the washing rotating speed and the washing duration are dynamically corrected, and the detergent supplementing and putting amount is synchronously adjusted according to chemical component distribution. The limitation of the existing single-mode recognition technology on complex stain analysis is broken through, resource waste and fabric damage caused by traditional extensive washing are avoided, and the technical contradiction between the decontamination effect and resource consumption in the prior art is effectively solved.

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 outlet control method, system and device for an intelligent water valve, and relates to the technical field of water outlet control of water valves. The water outlet control method for the intelligent water valve comprises the following steps of water outlet prediction, intelligent water valve adjustment evaluation and water outlet control effect evaluation. The real-time water outlet data corresponding to each intelligent water valve control mode is collected, the water outlet prediction index is obtained in combination with the corresponding historical water outlet data so as to adjust the opening degree of the valve, then the intelligent water valve adjustment evaluation index is obtained according to the real-time water consumption data and the real-time water return data, and whether the intelligent water valve control mode is switched or not is judged. Finally, water outlet control adjustment measures are taken according to the water outlet control effect evaluation index, the effect of improving the water outlet control effectiveness of the intelligent water valve is achieved, and the problem that in the prior art, water outlet control of the intelligent water valve is not sufficiently associated with user requirements is solved.

The invention relates to the technical field of reservoir flood control dispatching, and discloses a dam hydraulic opening and closing control method, device and equipment and a storage medium. The method comprises the steps that multi-source hydrological data, weather forecast information and unit operation states of a current reservoir are collected; inputting the multi-source hydrological data and the weather forecast information into a preset hydrological prediction model, and outputting a hydrological prediction result; based on the hydrological prediction result and the real-time reservoir area water level and the unit operation state in the multi-source hydrological data, a gate opening control instruction is generated through a reservoir optimization scheduling model; and a hydraulic opening and closing system is adjusted according to the gate opening control instruction, and the current reservoir flood discharge gate opening is controlled. According to the method, data such as upstream incoming water, reservoir area water level and water consumption are utilized, weather forecast information is combined, a hydrological prediction model is constructed, a reservoir dispatching scheme is optimized according to a hydrological model prediction result, the reservoir area water level and unit operation conditions, and on the premise that flood prevention safety is guaranteed, reservoir dispatching is optimized, the reservoir area water level is automatically adjusted, and power generation benefits are improved.

The invention relates to the technical field of remote water meter abnormity early warning, and discloses a remote water meter abnormity early warning method and system based on historical water volume, and the method comprises the steps: dividing a user water meter into three classes A, B and C according to the installation time of the user water meter, and employing a differentiated abnormity detection strategy. For the A-type users, establishing a water consumption prediction model based on historical consumption data of the A-type users; for the B-type users, finding similar reference water meters from the A-type users by using a K-means clustering algorithm; and for the C-type users, monitoring whether the accumulated water consumption for continuous N days is completely equal or not after the C-type users are installed. After real-time usage data is obtained, usage deviations of various users are calculated respectively, if the deviations exceed a set threshold value, abnormal early warning is triggered, and the early warning level is dynamically adjusted according to the number of abnormal duration days. According to the method, technologies such as machine learning and clustering analysis are comprehensively utilized, a set of comprehensive, flexible and efficient water consumption abnormity early warning system is constructed, and the refinement and intelligence level of urban water supply management can be remarkably improved.

The invention relates to the technical field of water meter flow, in particular to an ultrasonic water meter flow curve fitting system, which is characterized in that an edge computing device is used for primarily processing original data at a data acquisition end, a mean filtering algorithm is used for removing noise data, and the data after acquisition is subjected to filtering, denoising, abnormal value elimination and normalization processing; a dynamic evaluation model is constructed by adopting a time sequence prediction algorithm, the model calculates and predicts various data of future ultrasonic water meter flow by continuously inputting real-time data, and the model is optimized according to a prediction result, so that errors of the model are continuously reduced in the training process, and the prediction accuracy of the model is improved; modeling and fitting are conducted on the flow curves, calculated by the neural network model, of the ultrasonic water meter in different working states through the fitting model, the fitted curves can serve as a basic data source of a user water consumption behavior and system load characteristic advanced analysis model, and energy-saving analysis and fault positioning are facilitated.

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 present invention relates to the technical field of ultrasonic therapy, and particularly to a water circuit arrangement structure of an ultrasonic therapy device and an ultrasonic therapy device. The water circuit arrangement structure of the ultrasonic therapy device includes an ultrasonic therapy head, a water supply pipeline, and a water receiving tray. The ultrasonic therapy head has a cavity for accommodating a breast and performing treatment, and the inner wall of the cavity is an arc surface. A first connection channel communicating with the water supply pipeline is provided at the bottom of the ultrasonic therapy head. During ultrasonic therapy, a water medium enters the cavity from the bottom of the ultrasonic therapy head and overflows from the top of the cavity of the ultrasonic therapy head. The water receiving tray is arranged outside the ultrasonic therapy head and is used for receiving the water medium overflowing from the cavity of the ultrasonic therapy head. The beneficial effects of the present invention are as follows: The ultrasonic therapy head directly serves as a carrier for holding water, reducing water consumption, and reducing pipeline settings, avoiding winding interference. The structure is simple and the layout is compact, and the treatment operation is simple, convenient, and flexible.

The invention provides an irrigation district water resource optimal configuration, scheduling and control system and software, the system comprises a water resource configuration module, a water volume optimal scheduling module and an operation control module, the water resource configuration module is used for realizing a water resource configuration process, and comprises three parts of objective function determination, model expression and model solution; and in the water volume optimization scheduling module, according to a water resource configuration model, time period parameters are substituted for solution to obtain the water distribution volume of each time period of each water consumption unit, and then water volume scheduling is carried out according to the water distribution volume. According to the invention, all-around and multi-layer configuration of water resources is realized; according to the method, a reasonable objective function is determined, for example, economic benefits, social benefits, natural resource balance and the like are considered, and a corresponding mathematical model is constructed to express a water resource allocation problem, so that a basis is provided for solution, and accurate management of water resources is realized. The objective function can reflect the demands of different benefit groups, and ensures the fairness and sustainability of water resource allocation.

The invention relates to the field of water resource monitoring and early warning, in particular to an intelligent water consumption monitoring and early warning method based on the Internet of Things. The method comprises the steps of obtaining water flow data and temperature data, and obtaining a water flow predicted value through a dynamic weighted sliding window prediction algorithm; calculating a water flow deviation value based on the water flow data and the water flow predicted value; calculating a temperature correction coefficient based on the temperature data, and calculating a comprehensive error value; and calculating a risk assessment value based on the comprehensive error value in combination with the temperature correction coefficient, and assessing an abnormal risk. The method solves the problems that a prediction algorithm adopted by a traditional water consumption monitoring mode is too simple, lacks dynamic adaptability to water flow fluctuation and is difficult to effectively cope with sudden water flow changes; the influence of external environment factors on the water flow is neglected, so that the prediction error is large; an adopted fixed threshold cannot adapt to different environment changes, and abnormal risks cannot be accurately detected in real time.

The invention discloses a rice field irrigation control method, and belongs to the field of rice field irrigation, and the method comprises the steps: obtaining soil humidity, water level and meteorological data from a rice field through a sensor network, storing the data in a pre-established distributed database, and obtaining a multi-source data set; according to the data set in the unified format, key features of soil humidity, water level and meteorological data are extracted by adopting a principal component analysis method, and a feature vector set is obtained; if the water consumption of the predicted irrigation scheme exceeds a preset threshold value, the scheme is optimized and adjusted through a linear programming algorithm, and an optimized irrigation scheme is obtained; according to the optimized irrigation scheme, the water consumption in the irrigation process is monitored in real time through flow meter equipment, and accurate measurement data are obtained; and the accurate measurement data is distributed through a quota management module, a regional water resource allocation scheme is generated by adopting a dynamic quota algorithm, and a quota management result is obtained.

Livestock may be managed by a variety of systems, processes, and techniques. In particular implementations, the properties of water may be monitored by automated techniques and treated water may be provided to animals. In certain implementations, sick, or potentially sick, livestock may be provided with treated water to improve their health. The automated techniques may include monitoring the movements and / or water consumption of the livestock and predicting which ones may be sick based on their movements and / or water consumption. In some implementations, a water trough may contain multiple segments. The water properties in the segments may be maintained at different states.

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 discloses an optimized dispatching water supply method for reclaimed water and conventional water under a drought condition, which comprises the following steps: evaluating a drought grade through meteorological data, precipitation prediction and reservoir level factors, dynamically adjusting the water supply amount of a conventional water source according to the drought grade, and preferentially guaranteeing life and ecological water; according to the production type and the water quality requirement of the enterprise, the reclaimed water demand and the water quality grade are evaluated and divided, and water sources are optimally distributed; the total water deficit and the water consumption cost are minimized by optimizing the scheduling model, and the reclaimed water and the conventional water are reasonably scheduled; and setting constraint conditions to ensure that the conventional water source water supply capacity, the reclaimed water treatment capacity and the pipe network distribution capacity are not in overload operation. Reasonable supply of a conventional water source and reclaimed water is ensured through accurate drought grade evaluation and water source dynamic adjustment; reclaimed water with matched water quality grades is provided according to different water quality requirements of enterprises, and excessive treatment and water quality waste are effectively reduced.

A combined dust suppression system for a metal ore unloading station, and a using method. The combined dust suppression system consists of an ore unloading station tunnel wall surface accumulated dust high-pressure water flushing device, an ore unloading station tunnel floor spraying, watering, and wetting device, and an ore unloading station ore train floor bidirectional high-pressure spray dust suppression device. The ore unloading station tunnel wall surface accumulated dust high-pressure water flushing device is used for performing manual flushing on a tunnel by means of high-pressure water in the travel direction of an ore unloading train, the ore unloading station tunnel floor spraying, watering, and wetting device is used for performing spraying, watering, and wetting on the tunnel, and the ore unloading station ore train floor bidirectional high-pressure spray dust suppression device isolates dust generated during ore unloading at the ore unloading station. The water consumption can be reduced, excessive water in an ore unloading pit that causes adhesion and blockage can be effectively avoided, the field applicability of high-pressure spray dust suppression measures is improved, and on-demand spray dust removal of a high-pressure spray device is achieved; high-pressure water is used for flushing accumulated dust on the tunnel wall surfaces of ore unloading stations, and the tunnel floors of ore unloading stations are sprayed, watered, and wetted, thereby achieving significant comprehensive dust suppression and dust control effects, and notable energy-saving effects.