Water Control System Research Articles

Water Pollution Prevention and Control System Based on Cluster Analysis

Water Pollution Prevention and Control System Based on Cluster Analysis

Optimal Control of Chilled Water System Based on Improved Sparrow Search Algorithm

Chilled water systems have large time delays and large inertia, and the traditional PID controller has a poor control effect. In this paper, an improved sparrow search algorithm is proposed to optimize the control of chilled water systems. Firstly, the random walk strategy was used to randomly perturb the sparrows to improve the searching ability of the sparrows. Then, a Gauss mutation was added in the iteration process of sparrows to enhance the local search ability. Finally, the values of the PID parameters as obtained by the above methods were substituted into the controller for simulation. The simulation results show that the method proposed in this paper improves the search accuracy of the sparrow search algorithm and effectively solves the problems of large time delays and large inertia in the chilled water system. The method in this paper took the least amount of time for the system to reach the steady state at only 12.75 s. The control effect of the proposed method was also better than that of the improved ant colony optimization algorithm. The rise time was 2.713 s, and the adjustment time was 4.95 s.

Legionnaires disease: history of the discovery, the main stages of the study pathogen and infection

The article discusses main directions and stages of the 45 years of Legionnaires disease study. Analysis of epidemiology and laboratory diagnostics of infection show as unknown until 1976 microorganism occupied a notable niche in the etiology of severe pneumonia. Control and monitoring of potential dangerous water systems, generating water aerosol containing Legionella in high concentration, plays a major role in the prevention of Legionnaires disease.

PERANCANGAN SISTEM MONITORING DAN KONTROL KUALITAS AIR SERTA PEMBERIAN PAKAN OTOMATIS PADA BUDIDAYA LELE BIOFLOK BERBASIS INTERNET OF THINGS

Cultivation with a biofloc system has several advantages and disadvantages. Biofloccatfish cultivation technology is a technique to balance carbon and nitrogen levels in water toimprove pond water quality. However, cultivators must make observations in the cultivationpond water more often and carefully in order to prevent the increase in nitrogen levels. So,referring to this, a monitoring and control system for water quality and automatic feeding onbiofloc catfish cultivation was designed. The research was conducted by applying theexperimental method, in which the system is divided into three subsystems, namely waterquality monitoring, automatic water replacement, and automatic feeding. The results obtainedfrom conducting this research are in the form of tool trial data which will then be compared withdata from the program that has been made, as well as performance data from the automaticwater replacement subsystem and automatic feeding subsystem which were carried out for 5consecutive days. The conclusion of this research is that the design of a water qualitymonitoring and control system and automatic feeding on biofloc catfish cultivation based on theInternet of Things has been successfully made. In the automatic water replacement subsystem,the average relative error is 2.75%. In the automatic feeding subsystem, the average differencein feeding time is 14.5 seconds and the average relative error is 3.3%.

Plant Water Stress Monitoring and Control System

Plant Water Stress Monitoring and Control System

Application of ITC cucumber fertilizer and water control system

In order to optimize the environmental factors for cucumber growth, a fertilizer and water control system was designed based on the Internet of Things (IoT) system. The IoT system monitors environmental factors such as temperature, light and soil Ec value, and uses image processing to obtain four growth indicators such as cucumber stem height, stem diameter size, number of leaves and number of fruit set to establish a single growth indicator model for temperature, light, soil Ec value and growth stage, and the four growth indicators were fused to obtain the comprehensive growth indicator Ic for cucumber, and calculates its deviation to determine the cucumber growth status. Based on the integrated growth index Ic of cucumber, a soil Ec control model was established to provide the optimal environment and fertilizer ration for cucumber at different growth stages to achieve stable and high yield of cucumber.

The added water control system based on neural network model and double parameter corrected for loosening and conditioning cylinder

In order to improve the stability of outlet moisture in the of loosening and conditioning cylinder, we concentrate on loosening and conditioning cylinder, and design the prediction model of the added water volume based on neural network technology and the double parameter corrected control system of material balance and moisture deviation for loosening and conditioning cylinder by using historical production data. Taking the set value of inlet and outlet moisture of the loosening and conditioning cylinder as the input factor and the added water volume as the output factor, the prediction model of the added water volume was to predict the total volume of the added water. When there was a big deviation between the actual value and the set value of outlet moisture, the double parameter corrected control system of material balance and moisture deviation was used to correct the deviation, so as to improve the outlet moisture stability and the control accuracy of the added water volume. Using Cigarette brand “diamond (hard-case Yingbin)” produced by Zhangjiakou cigarette factory to built model and analysis, the results showed that after the improvement, the standard deviation of output moisture of loosening and conditioning cylinder reduced by 0.27%, and the control stability and the control level of production process were improved.

PERANCANGAN SISTEM MONITORING DAN KONTROLING POMPA AIR BERBASIS ANDROID

Water is a necessity that is so important for every creature in the world, and the estimate of water must always be available or it is in homes, offices, public places or industry. This causes the water storage tank to play an important role in ensuring the availability of air is always there and under control. In this research, it is based on an Android-based Water Pump Monitoring and Control system with the support of IoT (Internet of Things) technology so that it makes it easier for users to monitor the amount of water in the storage tank and control the water pump to fill water into the tank, the system built is supported by the NodeMCU module. esp8266, Relay and Ultrasonic Sensor and connected to the Blynk application which functions as an application interface in monitoring and controlling the water pump. If the air has determined the specified distance, a notification will appear to immediately turn off the water pump, thus it is hoped that this system can help users see the condition of the water pump and water tank even though they are not at home

Precise control of water and wastewater treatment systems with non-ideal heterogeneous mixing models and high-fidelity sensing

Non-ideal heterogeneous mixing models are developed and incorporated within advanced closed-loop control strategies utilizing high-resolution sensing to maximize the resiliency and minimize the energy consumption of water treatment processes with intelligent model-based decision-making approaches. The proposed non-ideal heterogeneous mixing models capture continuity (heat and mass conservation), yet are extremely simple with few parameters, so they lend themselves to fast online prediction (with extrapolation capabilities) and regular recalibration. Further, they are more accurate than computational fluid dynamics (CFD) (60% less error) and symbolic regression data-driven models (73% less error). Real-time high-resolution sensor data are collected for observing spatiotemporal responses of state variables (conductivity, pH, and temperature) to transient influent shocks. Deterministic global dynamic optimization is used for training and recalibration of the non-ideal heterogeneous mixing models to guarantee the best-possible fits to the sensor data. The models are then deployed within standard model-predictive control and two economic model-predictive control strategies to demonstrate model-based decision-making for disturbance rejection and optimal operation of aeration in a continuous flow nitrification system utilizing high-resolution sensor data from several spatial positions. The new technology platform, consisting of high-resolution sensors, non-ideal heterogeneous mixing modeling, deterministic global dynamic optimization, and model-predictive control, offers superior performance over current approaches in water and wastewater treatment processes.

Development of laboratory scale model of field automatic water control system with sheetpipe technology

In this study, a 2mx2mx0.5m box is modeled, filled with soil having a thickness of 40 cm rice fields and sheet pipe subsurface drainage installed 30 cm below the surface. The sheet pipe is connected to the air duct and reservoir upstream and the drainage outlet pipe downstream. Automation of the water level control in the reservoir is done utilizing a digital controller which has been programmed and connected to a water level sensor and a solenoid valve. If the water level is detected falls below the minimum threshold, the controller will open the solenoid valve and flow water to the reservoir until the specified level. This system is connected to the server via wireless internet, data monitoring and control settings can be done by the user via a dashboard in an internet browser. The test was carried out for approximately 3 months with rice planting and un-inundated irrigation. The test results show that the system has been able to function in remote monitoring and regulation of the controller, automatic irrigation operations, and water supply in the land as needed in the rice planting experiment with the control error of 2.6 cm.

Smart Irrigation System Based on the Internet of Things and the Cloud

A water system is a technique for giving water to plants to grow and create. Water in plants or water systems is not a cutting-edge idea; it has been followed and applied from one century to another or decade to decade. Advances have developed in lockstep with time. At the point when we compare the 1980s and 2021, we see a sensational distinction in advances just as in the water system strategy. During the 1980s, the water system was accomplished utilizing furrows and wrinkles. A water system is a technique for providing water to the root zone at the ideal opportunity. Plants draw water from wet soil, and by the component of evapotranspiration (ET), plants come to pass water into the air while drawing supplements accessible in soil with water for root zone improvement. At the point when the stockpile of water in the root zone falls under a specific edge, plants can't draw supplements and water for sustenance. Thus, supply great water to the root zone before as far as possible is reached. This cutoff is controlled by the types of plants, soil, and environment. Since the edge cap changes relying upon the sort of plant. Logical booking requires the utilization of the proper volume of water at the fitting time frame and area inside the office. This requires consistent checking of soil dampness content at the root zone and the commencement of the water system as per a pre-modified timetable base on wear the idea of the plant, its turn of events, soil type, and environment. Accordingly, for logical water system booking, sensors should be planted close to the root zone in the dirt to get to the agent's dampness status. The signs created and recognized by soil dampness sensors should be prepared in a microcontroller for water system planning by predefined programming. The microcontroller ought to likewise be intended to hand off the sign to a far-off area where the siphoning and well framework for water system control is found. Also, the criticism of these sensors ought to be examined by the microcontroller as indicated by a foreordained program to end the water system relying upon the plant, its the degree of improvement, soil, and environment. This paper presents a cloud-based and web of things-based water system framework. This framework utilizes sensors to gather continuous water system information, stores information into the cloud, proprietor of information provides the order and suitable move is made on dependent on the outcome created.

Chaotic Particle Swarm Optimization in Water Pollution Prevention and Control System Planning

Chaotic Particle Swarm Optimization in Water Pollution Prevention and Control System Planning

System Control Scheme and Design Idea of Soft Sensing Model for Heavy Metal Ion Concentration

This paper combines ion exchange technology and soft sensor technology to design and improve a series of integrated automatic control and module distributed combination of new ion exchange system. At the same time, a visual water management and control system for industrial heavy metal wastewater treatment is developed based on the industrial IoT platform of eForceControl. Through information collection and data integration of heavy metal pollutants with different characteristics in the process flow, a variety of ion exchange materials in the distribution module are optimized. Combined with big data analysis and ion sensing, it realizes online monitoring and treatment of water pollution factors, optimizes production capacity management of industrial system, and is committed to solving problems such as low efficiency of traditional heavy metal wastewater treatment, single data analysis mode and chaotic operation and control.

Research progress and prospect of Ordovician carbonate rocks in Tahe oilfield: karst feature

Inspired by structural geology, karstology, geomorphology, as well as petroleum geology, coupling excellent documented research works and the field investigation, the status and prospect for the studies on karst feature of Tahe oilfield are discussed comprehensively. Results indicate: (a) the majority of research works have appeared since 2000 and can be classified as three categories and 12 subclasses, in which caves, fracture cave systems and fault-karst reservoirs are considered as the main research topics, (b) existed studies can be divided into four stages, and fault-karst reservoir analysis is a hot spot recently, focusing on the scale of the formed reservoir. It is the common sense that faults control both fractures and caves. Originally, there exist close relationships among karst phenomena whether they're on the ground or underground. Revealing these relationships mentioned above is the important direction for the studies of Tahe oilfield in the future. As for the areas where faults are widely distributed in karst, there exist hierarchical properties in karstology: (1) fault controls topography and landform, (2) fault, topography and landform control the water system and (3) fault, topography, landform and water system control karst. These hierarchical properties are the basic connotation of the laws for karst evolution, and the vital goals of the karst study of Tahe oilfield as well. Applications of methods and techniques and field-karst investigation are the solid guarantees to achieve these goals.

Monitoring the state of flowing water in purification and water supply systems

The article substantiates the need to control water at various stages of its purification before consumption. Several stages of water purification in the city of St. Petersburg are considered. The advantages and disadvantages of the used water control system are noted. Various options for monitoring the state of water in the pipeline between cleaning cycles are considered. The advantages of using a refractometer for monitoring the purity (quality) of water are shown.

Geospatial approach for developing an integrated water resource management plan in Rajshahi, Bangladesh

The integrated water resource management (IWRM) plan plays a substantial role in addressing institutional problems and capacity building for the use, control, preservation, and sustainability of water systems, especially for developing countries like Bangladesh. Bangladesh is undergoing dramatic changes in land cover/land use (LC/LU) change, primarily due to rapid urbanization. Urbanization converts the natural resources (water bodies) into impervious surfaces (urban areas and roads). Rajshahi is one of the largest metropolitan cities in Bangladesh, and its urban sustainability is affected by the demolishment of water bodies influenced by rapid LC/LU change. Satellite images at different spatial resolutions are extensively used for extracting water body information at various periods. Using multi-temporal Landsat TM/OLI satellite images, the study aimed to estimate the spatiotemporal LC/LU change and identify the most influential LC/LU parameters that contributed to the reduction of surface water body from 1989 to 2019. The support vector machine, matrix union, and image difference algorithms were applied to estimate LC/LU classification, conversion of LC/LU, and water body to other LC/LU classes. Results revealed that a massive increase in the built-up area (16%) and infrastructural development were the primary cause for water body reduction, and loss of water bodies was estimated at around 8% in the last 30 years. Key informant's interviews were conducted to identify the effective management and technical strategies for developing a sustainable IWRM plan utilizing modern technology. The estimated hydro-geomorphological (modeling flow direction, stream network, flow accumulation, and surface water potential zones) information would be beneficial to any developing country.. This study will contribute to the development of effective strategies for conserving existing water bodies and ensuring ecological and environmental sustainability by increasing plant biodiversity and mitigating the effects of heatwaves.

Optimal control of chilled water systems based on collaboration of the equipment's near-optimal performance maps

The model-based strategies have been widely used for optimization of energy consumptions of chilled water systems. The strategies usually establish the system’s energy consumption models, and use optimization algorithms to search the optimal setpoints. However, the models of these strategies may be inaccurate, and the nonlinearity of the models will cause a large amount of computational load. In order to solve the problems, this paper set up the near-optimal performance maps of system equipment instead of models based on operation data. Each map indicates the highest or near-highest operation efficiency of a kind of equipment under the different operation conditions. A novel control strategy for optimization of chilled water systems is developed based on collaborating those maps. An airport chilled water system which is located in the south of China is used for validation. The proposed strategy is compared with two conventional strategies on the chilled water system. Results show that the proposed strategy can not only significantly save the energy consumption of the system, but also has a lower computation time, so the proposed strategy can be better applied to online optimization control.

A Study Into the Use of Milliflex Quantum as Rapid Microbial Detection Method for Microorganisms in Pharmaceutical...

Control of pharmaceutical water systems represents an essential part of Good Manufacturing Practice and embedded within this is the quality control testing of water systems for viable microorganisms, and subjecting the data obtained to trend analysis. This has traditionally been achieved by membrane filtration and the use of a culture medium. While such test methodologies can recover a level of the bioburden present, the incubation times are lengthy. To address the problem of time-to-result, rapid microbiological methods offer an alternative approach. One such example is the Milliflex Quantum, which is the focus of this article.

New Functionalized Macroparticles for Environmentally Sustainable Biofilm Control in Water Systems.

Reverse osmosis (RO) depends on biocidal agents to control the operating costs associated to biofouling, although this implies the discharge of undesired chemicals into the aquatic environment. Therefore, a system providing pre-treated water free of biocides arises as an interesting solution to minimize the discharge of chemicals while enhancing RO filtration performance by inactivating bacteria that could form biofilms on the membrane system. This work proposes a pretreatment approach based on the immobilization of an industrially used antimicrobial agent (benzalkonium chloride—BAC) into millimetric aluminum oxide particles with prior surface activation with DA—dopamine. The antimicrobial efficacy of the functionalized particles was assessed against Escherichia coli planktonic cells through culturability and cell membrane integrity analysis. The results showed total inactivation of bacterial cells within five min for the highest particle concentration and 100% of cell membrane damage after 15 min for all concentrations. When reusing the same particles, a higher contact time was needed to reach the total inactivation, possibly due to partial blocking of immobilized biocide by dead bacteria adhering to the particles and to the residual leaching of biocide. The overall results support the use of Al2O3-DA-BAC particles as antimicrobial agents for sustainable biocidal applications in continuous water treatment systems.

A data-driven electric water heater scheduling and control system

Domestic hot water (DHW) heating accounts for up to 30% of average household energy use. Compared to gas fired water heaters, electric water heaters (EWH) can be powered by renewable generation resources, thus making it a potential renewable heating option. Furthermore, with the growing need for energy storage, incorporation of renewable resources, and initiatives worldwide, the electrification of DHW heating is expected to continue the rapid growth. However, many commercial EWH products with monitoring and alerting functionalities lack the intelligence to optimize and perform predictive control with data; on the other hand, research studies with refined models and simulations come short in incorporating real-time data and providing robust optimal controls under uncertainties in real-world settings. This paper presents a EWH Smart Scheduling and Control System using data-driven disturbance forecasts in a robust Model Predictive Control (MPC) to accomplish various demand side management objectives. Testing with a real-world EWH dataset and a two-state EWH model, robust MPC simulations are conducted on a central EWH supplying DHW for a multi-unit apartment building with quantified prediction uncertainty. Results show that the proposed system is capable of anticipating DHW demand with an uncertainty interval covering up to 97% of the actual demand during the test days and reducing electricity cost up to 33.2% as well as maintaining a desired DHW temperature without affecting user comfort. Further, the flexibility of the system to alter load profiles under different Demand Response (DR) programs is demonstrated. Reductions in both power and water consumption can be accomplished. The proposed system can create an implementable solution of forecasting DHW usage and optimizing controls as a part of a robust and reliable building energy management and control system in real-world settings.