多目标约束下给水管网水质传感器选址优化算法的研究

利用EPANET2模拟扩展周期非稳态水力水质条件下管网节点污染物浓度变化,根据各个节点被注入污染物后,在管网模拟结束时得到的选址目标值的大小来确定节点有可能作为污染物注入的节点,目标值越大,该节点被选择的可能性越大.另外,本文提出了基本粒子群算法与遗传算法交叉、变异算子相结合的整数编码的优化算法来求解水质传感器选址问题,并编制了相应的计算程序.文中结合算例,以经过归一化后的节点平均坐标作为衡量选址结果的指标,得到了不同污染物注入开始时刻、注入持续时问和质量注入速率条件下传感器选址节点平均坐标的累计分布函数图,为传感器的选址提供参考.     

Water Quality Sensor Placement: A Multi-Objective and Multi-Criteria Approach

To satisfy their main goal, namely providing quality water to consumers, water distribution networks (WDNs) need to be suitably monitored. Only well designed and reliable monitoring data enables WDN managers to make sound decisions on their systems. In this belief, water utilities worldwide have invested in monitoring and data acquisition systems. However, good monitoring needs optimal sensor placement and presents a multi-objective problem where cost and quality are conflicting objectives (among others). In this paper, we address the solution to this multi-objective problem by integrating quality simulations using EPANET-MSX, with two optimization techniques. First, multi-objective optimization is used to build a Pareto front of non-dominated solutions relating contamination detection time and detection probability with cost. To assist decision makers with the selection of an optimal solution that provides the best trade-off for their utility, a multi-criteria decision-making technique is then used with a twofold objective: 1) to cluster Pareto solutions according to network sensitivity and entropy as evaluation parameters; and 2) to rank the solutions within each cluster to provide deeper insight into the problem when considering the utility perspectives.The clustering process, which considers features related to water utility needs and available information, helps decision makers select reliable and useful solutions from the Pareto front. Thus, while several works on sensor placement stop at multi-objective optimization, this work goes a step further and provides a reduced and simplified Pareto front where optimal solutions are highlighted. The proposed methodology uses the NSGA-II algorithm to solve the optimization problem, and clustering is performed through ELECTRE TRI. The developed methodology is applied to a very well-known benchmarking WDN, for which the usefulness of the approach is shown. The final results, which correspond to four optimal solution clusters, are useful for decision makers during the planning and development of projects on networks of quality sensors. The obtained clusters exhibit distinctive features, opening ways for a final project to prioritize the most convenient solution, with the assurance of implementing a Pareto-optimal solution.

     

Localization of Contamination Sources in Drinking Water Distribution Systems: A Method Based on Successive Positive Readings of Sensors

This paper addresses the problem of the localization of contamination sources after deliberate contaminations in drinking water distribution systems (DWDS). The proposed methodology is based on the information given by successive positive readings of sensors. Thus, it is possible to estimate the localization of the contamination sources based on only the first sensor that detected a contamination, and then update the results when more information is available. From the tests performed on a real drinking water distribution system, it was possible to observe that as new sensors detect changes in contaminant concentration, other possible contaminations may be detected and the location of contamination sources may be more restricted. The results achieved for the two set of sensors considered in the study contained the correct locations and the instants of contaminations previously simulated. Two case studies were also analysed to study the effect of the occurrence of false positives. It was concluded that it is not always possible to verify the occurrence of those anomalies and when it is verified, it is not possible to distinguish between a false positive and a false negative. The occurrence of false positives did not affect also the results related with the real detections.     

Entropy-Based Sensor Placement Optimization for Waterloss Detection in Water Distribution Networks

The work presented herein addresses the problem of sensor placement optimization in urban water distribution networks by use of an entropy-based approach, for the purpose of efficient and economically viable waterloss incident detection. The proposed method is applicable to longitudinal rather than spatial sensing, thus to devices such as acoustic, pressure, or flow sensors acting on pipe segments. The method utilizes the maximality, subadditivity and equivocation properties of entropy, coupled with a statistical definition of the probability of sensing within a pipe segment, to assign an entropy metric to each pipe segment and subsequently optimize the location of sensors in the network based on maximizing the total entropy in the network. The method proposed is a greedy-search heuristic.     

Risk Probability Assessment of Sudden Water Pollution in the Plain River Network Based on Random Discharge from Multiple Risk Sources

Starting from the time variance and uncertainty of accidental discharge, this paper describes the probability of the occurrence of the “normal-accident” alternate state for a risk source using the Markov state transfer model, simulates the behaviour of pollutants in rivers using the hydrodynamic and water quality models for non-conservative substances, and tracks the transport path of pollutants in rivers using the water quality model for conservative substances. The above models are coupled with the Sequential Monte Carlo algorithm, and the risk probability analysis model for sudden water pollution in the plain river network is established and applied to the Yixing river network. The results show that (a) the risk probability of exceeding ammonia nitrogen standard (PES of ammonia nitrogen) is lower in the upper reaches and higher in the middle and lower reaches; (b) dynamic changes in pollutant concentration lead to different changes in the PES of ammonia nitrogen in each reach; (c) the differences in the simulated PES values between the sudden scheme and the stable scheme (NPES of ammonia nitrogen) in the upper and middle reaches show a patchy distribution of high and low values, which are related to the risk source location, the water movement direction and the concentration change in the reach after accepting pollutant loads from the risk sources; (d) the NPES of ammonia nitrogen in the lower reaches results from the coupling effect caused by accidental discharges from multiple risk sources; and (e) the different effects of the lower boundary hydrological conditions on the upstream water inflow lead to the different coupling effect on the water quality probability of sections in the downstream area.

     

Modularity-Based Procedure for Partitioning Water Distribution Systems into Independent Districts

A proper division of a Water Distribution System (WDS) into District Metered Areas (DMAs) provides important management benefits particularly with regard to leakage detection through water balances, control and optimization of pressure so as to reduce leakage, implementation of monitoring, warning and emergency acting systems against accidental or intentional water contamination. This paper presents a new methodology that combines a suitable modularity-based algorithm for the automated creation of DMA boundaries and convincing practical criteria for the DMA design. A further plus of the proposed methodology is its ability to identify many technically feasible solutions that can be subsequently economically assessed. The successful applications of the proposed methodology to a real case study, already tested by other authors, has proven its effectiveness for the DMA design in existing water distribution systems.     

Using CANARY event detection software for water quality analysis in the Milwaukee River

Urban water sources are susceptible to various contamination events as a result of natural, accidental, and human-induced occurrences. An early warning monitoring system provides timely information on changes in urban water quality. In this study, an analysis was made with CANARY event detection software (EDS) to monitor water quality parameters in river water and to identify the onset of anomalous water quality periods. Water quality signals including pH, conductivity, and turbidity from the Milwaukee River over specified periods during the summer season of 2018–2020 were employed as inputs to event detection algorithms in CANARY. The data analysis results show that CANARY can be useful as an early warning system for monitoring contamination in urban water sources and help to identify abnormal conditions quickly. The sensibility of the model relies on optimizing the configuration parameters, which involves selecting the ideal set of parameters for the event detection algorithm and adjusting the BED parameters to increase or decrease the probability of generating an alarm. The number of events reported between the Linear Prediction Correction Filter (LPCF) and Multivariate Nearest Neighbor (MVNN) algorithms varied as a result of different residual calculation mechanisms. Climate factors that contributed to the abnormal water quality events in the river were examined. The analysis of rainfall on water quality was carried out using a statistical method by determining whether there is a significant difference (p-value) between the seasonal mean water quality data and the mean value of water parameters during the sampling duration. Regression analysis was also performed to estimate the best model that describes the relationship between each of the water quality parameters and temperature.     

Identification of Critical Pipes for Water Distribution Network Rehabilitation

The water distribution network needs to be rehabilitated when the network is unable to perform the desired function. In this study, a methodology is developed to identify the critical pipes in the water distribution network for its rehabilitation by using four network reliability metrics: supply shortage, pressure decline, energy loss per unit length, and the hydraulic uniformity index. These metrics consider different aspects of reliability of the water distribution network using pressure-dependent analysis to calculate the overall criticality of the pipes. In contrast to the conventional reliability index, the present study uses both the normal and abnormal conditions at nodes (fire demand) and pipe (pipe failure) and thus, provides more balance reliability metrics for the network. The literature shows that the node and pipe level metrics have been used separately, whereas in this study both the node and pipe level metrics are combined to develop the present methodology. The methodology is applied to four different water distribution networks, including one typical realistic water distribution network, the data for which is adopted from literature. The results show that the methodology can identify the critical pipes successfully to prioritize the water distribution network rehabilitation and found to be simple in implementation for practicing professionals. The results further show that the critical pipes are found to be located from the source on the paths that do not have a loop or around the nodes of higher demand. The study might also be useful for the extension plan of a water distribution network along with strengthening the deficient nodes/ pipes of the network.

     

给水管网故障实时诊断方法

本文提出了城市给水管网故障实时诊断的一个快速、有效和实用方法。方法通过实时监测给水管网中3个位置的水压变化，利用人工神经网络技术来诊断故障位置、故障程度和故障影响范围。方法可适用于我国北方冬季严寒气候等常常导致的给水管网爆管事故及日常故障的实时诊断。作为给水管网故障诊断的重要内容之一，本文还建立了给水管网局部破坏状态下水力分析的方法。最后，本文以一小型给水管网为例对方法进行了验证，并就实际应用中的几个问题进行了讨论。     

基于贝叶斯理论的城市供水管网泄漏在线检测与定位

许多城市的供水管网都安装了SCADA(Supervisory Control And Data Acquisition)系统,基于SCADA系统监测到的数据可对管网泄漏进行检测。通过引进统计学概率论中一基本定理——贝叶斯定理来建立管网泄漏的在线检测与定位模型,一定程度上解决了水力模拟误差、测量误差、测点配置等因素导致的不确定性问题。模型通过实例考核取得较为满意的诊断结果。     

灌溉渠道远程数据采集平台设计

为促进灌区信息化建设,针对灌溉渠道数据信息有线监测系统面临的布线复杂、施工及维护成本高等问题,在分析灌溉渠道数据采集节点分布特点的基础上,结合Zig Bee近距离通信技术和GPRS远距离通信技术各自的优势,设计了一款数据测量终端和用于远程数据传输的遥测终端。测量终端以一定采样频率获取监测区域水位、流量、水质等信息,通过测量终端将传感器数据以无线信号形式向遥测终端传输,遥测终端完成Zig Bee网络数据收集并远程传输至监控中心。利用测量终端和遥测终端构建了渠道数据监测网络,可用于灌溉渠道水位、流量及其它重要参数信息的监测。现场实际测试运行效果表明,该平台采用无线传输方式,实现了渠道流量的数据采集、传输及显示功能,并能够实现渠道多数据信息的采集及远程数据传输。     

A Security-Oriented Manual Quality Sampling Methodology for Water Systems

The management and security of water resources will be a key challenge in the years ahead. This work investigates the water quality manual sampling scheduling problem in drinking water distribution networks. This work contributes to research by presenting a problem formulation based on the underlying substance propagation dynamics, coupled with the impact dynamics describing the ??damage?? caused by a contamination in a drinking water distribution network. The proposed solution methodology optimizes a risk-objective, in order to compute a manual sampling scheme comprised of sampling nodes and times, using evolutionary computation techniques. To illustrate the methodology, we present simulation results on a real water distribution network.     

A new online monitoring and management system for accidental pollution events developed for the regional water basin in Ningbo, China

Due to urgency of the accidental pollution events (APE) on one side and the variability in water quality data on the other side, a new online monitoring and management system (OMMS) was developed for the purpose of sustainable water quality management and human health protection as well. The Biological Early Warning System (BEWS) based on the behavioral responses (behavior strength) of medaka (Oryzias latipes) were built in combination with the physico-chemical factor monitoring system (PFMS) in OMMS. OMMS included a monitoring center and six monitoring stations. Communication between the center and the peripheral stations was conducted by the General Packet Radio Service (GPRS) network transmission complemented by a dial-up connection for use when GPRS was unavailable. OMMS could monitor water quality continuously for at least 30 days. Once APEs occurred, OMMS would promptly notify the administrator to make some follow up decisions based on the Emergency Treatment of APE. Meanwhile, complex behavioral data were analyzed by Self-Organizing Map to properly classify behavior response data before and after contamination. By utilizing BEWS, PFMS and the modern data transmission in combination, OMMS was efficient in monitoring the water quality more realistically.     

一种水雨情实时监测系统与设计

根据水雨情遥测实时监测要求,开展了一种水雨情实时监测系统与设计。通过雨量传感器、流速仪、视频采集传感器等多种传感器采集数据,然后采用4G无线通信技术手段将雨量、流量、水位等数据传输至监控中心,实现了水雨情数据的显示、查询以及网络共享,开发一种遥测与遥控的WEB水雨情实时监测与管理系统,该系统在很大程度上提高了监测水雨情的工作效率,具有良好的推广价值和经济效益。     

Pressure Zoning Approach for Leak Detection in Water Distribution Systems Based on a Multi Objective Ant Colony Optimization

Leakages result in considerable loss of water in water pipe networks. Therefore it is an important issue to detect leakage amount and its approximate location. Leakages in water distribution system are directly related to the operating pressure. In the current study, a new model is proposed for leakage amount and location detection and it is applied into two benchmark water distribution networks. In the proposed method, the water distribution networks are divided into three pressure zones in order to consider the leakage differences in different operating pressures. Then, nodal pressures and demands are calibrated using a new multi objective ant colony based optimization model. In this method, leaks are simulated as extra nodal demands. For determining the nodes where leakage happens, a probability based scheme is used. The leakage occurrence probability varies depending on the pressure zone that each node is located. The results illustrate the applicability of the proposed model for detecting the leakages in water distribution systems.     

A Simplified Methodology for Optimal Location and Setting of Valves to Improve Equity in Intermittent Water Distribution Systems

In this paper, a simplified methodology to increase the water distribution equity in existing intermittent water distribution systems (WDSs) is presented. The methodology assumes to install valves in the water distribution network with the objective to re-arrange the flow circulation, thus allowing an improved water distribution among the network users. Valve installation in the WDS is based on the use of algorithms of sequential addition (SA). Two optimization schemes based on SA were developed and tested. The first one allows identifying locations of gate valves in order to maximize the global distribution equity of the network, irrespectively of the local impact of the valves on the supply level of the single nodes. Conversely, the second scheme aims to maximize the global equity of the network by optimizing both location and setting (opening degree) of control valves, to include the impact of the new flow circulation on the supply level of each node. The two optimization schemes were applied to a case study network subject to water shortage conditions. The software EPA Storm Water Management Model (SWMM) was used for the simulations in the wake of previous successful applications for the analysis of intermittent water distribution systems. Results of the application of the SA algorithms were also compared with those from the literature and obtained by the use of the multi-objective Non-Dominated Sorted Genetic Algorithm II (NSGA II). The results show the high performance of SA algorithms in identifying optimal position and settings of the valves in the WDS. The comparison pointed out that SA algorithms are able to perform similarly to NSGA II and, at the same time, to reduce significantly the computational effort associated to the optimization process.

     

Key techniques for evaluation of safety monitoring sensors in water conservancy and hydropower engineering

For the evaluation of construction quality and the verification of the design of water conservancy and hydropower engineering projects, and especially for the control of dam safety operation behavior,safety monitoring sensors are employed in a majority of engineering projects. These sensors are used to monitor the project during the dam construction and operation periods, and play an important role in reservoir safety operation and producing benefits. With the changing of operating environments and run-time of projects, there are some factors affecting the operation and management of projects,such as a certain amount of damaged sensors and instability of the measured data. Therefore, it is urgent to evaluate existing safety monitoring sensors in water conservancy and hydropower engineering projects. However, there are neither standards nor evaluation guidelines at present. Based on engineering practice, this study examined some key techniques for the evaluation of safety monitoring sensors, including the evaluation process of the safety monitoring system, on-site detection methods of two typical pieces of equipment, the differential resistor sensor and vibrating wire sensor, the on-site detection methods of communication cable faults, and a validity test of the sensor measured data. These key techniques were applied in the Xiaolangdi Water Control Project and Xiaoxi Hydropower Project. The results show that the measured data of a majority of sensors are reliable and reasonable, and can reasonably reflect the structural change behavior in the project operating process, indicating that the availabilities of the safety monitoring sensors of the two projects are high.     

长距离输水工程综合水毁风险的估算方法及其应用

长距离输水工程沿途往往要跨越众多河系,极易受到洪水的冲击。现有的风险评价方法只能从水文要素的角度考察单个交叉建筑物的水毁风险或其综合水文风险。本文以可靠度理论为基础,提出通过计算Ditlevsen界限的方法,将求解n维分布函数的难题转化为求解二维分布函数,据此给出了串联系统引水工程交叉建筑物的综合水毁风险,解决了多维风险组合计算的问题。并以南水北调中线工程河北省北段为例,对该方法进行了应用。结果表明:南水北调中线工程河北省北段交叉建筑物系统综合水毁风险的上下界限分别为0.08052%和0.08050%,平均值为0.08051%,因水流冲刷失稳而水毁的风险是非常小的,输水安全是有保证的。     

城市暴雨道路积水监测技术及其应用进展

针对日益频发的极端暴雨事件使得城市道路积水的问题,为获得及时准确的积水数据,从道路积水监测技术层面,梳理了人工监测、传感器监测、遥感和视频影像监测的技术原理及相关改进,对比分析了不同传感器监测的优缺点。在此基础上,总结了道路积水监测技术的应用情况,并就未来发展趋势进行了展望。分析认为,道路积水监测需充分利用现有的视频设备、改进遥感水体识别技术、构建多源立体监测网以及基于海量监测数据的雨洪物理-数字耦合模型等方面开展研发和应用,全方位提高城市的雨洪预警水平和能力。     

基于多传感器数据融合的供水管网故障报警系统

针对传统的供水管网故障监控系统存在的误报次数多、抗干扰能力差、可信度低等缺点,研究利用多传感器监测供水过程的压力、电流、流速和液位等参数,采用基于D-S证据理论的多传感器数据融合技术,并对D-S证据理论进行了时间域和空间域融合方法的改进,以实现对供水管网故障的早期检测报警。结果表明:该方法可以有效避免监测数据的失误,解决了多传感器鲁棒性导致的证据冲突问题,提高了供水管网故障报警的可靠性。