Development of Multiple Leakage Detection Method for a Reservoir Pipeline Valve System

The detection of multiple leakages in pipeline systems has been one of the challenging issues for the control of water loss in water distribution systems. Inverse transient analysis can be a useful principle for predicting leakage through the calibration of location and leakage quantity, based on the pressure reflection that originates from an abnormal boundary condition. In this study, an innovative leakage detection method is proposed to address unknown conditions on multiple leakage dimensions through introduction of revised leakage expressions based on a frequency domain approximation. A multiple leakage function was modified for an efficient representation of multiple abnormalities at a reservoir pipeline valve system. An iterative metaheuristic scheme (IMS) was designed to handle an optimization scheme for multiple leakages using a pressure response for a discharge impulse introduced through value manipulation. In order to address unsteady friction in hydraulic transients combined with multiple leakages, both one-dimensional and two-dimensional models were used to derive leakage expressions for turbulent and laminar flow conditions. An isolated multiple leakage function (IMLF) was proposed to exclusively encapsulate the impact of leakages and unsteady fiction. Considering uncertainties in the hydraulic transient propagation, data noise, and multiple local optima issues in large parameter calibrations, three advanced schemes were modularized to improve detectability of IMS. Several hypothetical examples were presented to show the potential of IMS, validity of three advanced schemes, and robustness in multiple leakage prediction compared to existing approaches.     

Diagnosis of Pipe Systems by means of a Stochastic Successive Linear Estimator

Environmental concerns and legislation of the water industry have recently drawn the attention of many researchers to the management, calibration and power cost reduction of water pipeline systems. Effective water system management rests upon the knowledge of the current state of a water pipeline system. For example, leakages, unknown status of in-line valves, and partial blockages are often a source of management costs. These anomalies must be detected and corrected as early as possible. In this paper a diagnosis tool is presented able to detect leaks, partially closed in-line valves and partial blockages by means of transient head measurements. The algorithm introduced is a Stochastic successive Linear Estimator [SLE] (Yeh et al. Water Resour Res 32: 2757–2766, 1996a) which provides statistically best unbiased estimate of these anomalies and quantifies the uncertainty associated with these estimates via assimilation of available information. Therefore, the information from common diagnosis techniques e.g., inspection methods, and head measurements available at different locations of the system, obtained by different transient tests are fused to provide the most accurate and reliable diagnosis.     

A Selective Literature Review on Leak Management Techniques for Water Distribution System

Water Distribution System suffers from leakages causing social and economic costs. There is need of platform to manage water distribution system more efficiently by detecting, localizing and controlling the leakages even before or as soon as they occur, ensuring quality water services to the consumers. Since last two decades, high efforts have been made by researchers for the development of efficient leakage management techniques for reduction of water losses in distribution system. This paper provides a comprehensive analysis on leakage management techniques covering three aspects: leakage assessment, leakage detection and leakage control, with an objective to identify present challenges and future scope in their respected field. Role of smart water technologies for efficient leakages management in pipeline network is also examined and discussed. Conclusion is drawn regarding current leakage management techniques and proposals for future work and existing challenges are also outlined.     

Time and Energy Savings in Leak Detection in WSN-Based Water Pipelines: A Novel Parametric Optimization-Based Approach

This paper presents a novel optimization algorithm for monitoring a complex water pipeline using Wireless Sensor Networks (WSN), in order to solve the trade-off between a timely and accurate detection of a leak, and an efficient utilization of the energy at the WSN’s nodes aimed at prolonging the WSN’s lifetime. The scheme relies on using vibration sensors of different sensitivities to detect vibrations due to a leak, and on exploiting duty-cycling, hierarchical adaptive sampling and wavelet-based signal compression, in order to reduce sensing, computation and communication energies. Given the constraints of a maximum allowable sensor energy, a limited time to detect a leak after it occurs, and an acceptable percentage of signal distortion due to compression, a new optimization-based backtracking learning algorithm is developed here that solves for the values of various monitoring parameters such that it satisfies all the given constraints. Developing such an optimization algorithm has also required performing a sensitivity analysis, i.e. investigating the effect of changing the key monitoring parameters on the performance of leak detection and energy consumption. Simulation results for various cases successfully demonstrate the effectiveness of the algorithm while supporting the prediction of the sensitivity analysis.

     

Impedance Method for Abnormality Detection of a Branched Pipeline System

In this paper, an integrated detection scheme is developed to simultaneously address a leakage, a partial blockage and unknown branched pipeline elements. Expressions for the pressure head and discharge for a branched pipeline system having both a leakage and a blockage are derived in frequency domain. Boundary conditions for a reservoir and a branched dead-end allow the development of impedance formulations. The condition for a pipeline junction can be addressed using either a common condition for the pressure head combined with a continuity condition of discharge or a connectivity condition for impedance. In order to consider the unsteady friction’s impact, the impedance development process studied both the impact resulting from velocity profiles with two-dimensional distributions and the impact resulting from local and convective accelerations. Impedance expressions are derived for two distinct branched pipeline systems at different abnormality conditions. Based on drived formulations describing these systems, response functions were derived in the frequency domain and their corresponding time domain representations were integrated into a meta-heuristic calibration scheme for inverse transient analysis. Using an objective function for minimization of root-mean-square-errors between the observed and computed pressures, the calibration based one impulse response can simultaneously predict locations and magnitudes of abnormalities as well as parameters for a branched pipeline. The strength of the impedance-based approach for inverse transient analysis arises mainly from its feasibility to address different conservation conditions for pressure and discharge and for combining these conditions into a unified impedance connectivity condition.     

NONLINEAR HYDRODYNAMIC RESPONSE OF MARINE CABLE -BODY SYSTEM UNDER RANDOM DYNAMIC EXCITATIONS

Three-dimensional motion equations of a marine Tethered Remotely Operated Vehicle (TROV) system with large elastic deformation and snap loads are formulated using the lumped parameter model. This formulation is simple and quite general in solving a wide range of offshore-related cable and pipeline problems using only three degrees of translational freedom for each computational nodes. The model is convenient in dealing with non-uniform features of the cable with low or even zero tension. The snap load that would damaged the sling is predicted by computing the dynamic tension and the instant configuration of the cable. This investigation may help avoid resonance, extend the cable life, reduce the test expense and avoid operating accidents.     

A Life Cycle Oriented Multi‑objective Optimal Maintenance of Water Distribution: Model and Application

Aiming at trading off several conflicting criteria in practical maintenance in a deteriorating water distribution network, a life cycle oriented multi-objective optimization model of water distribution network maintenance is developed, which is composed of seven interrelated sub-models with different functions. This model can provide decision support for preventive maintenance decision, including identifying the pipeline that needs to be maintained, judging the time point for maintenance, determining the type of maintenance technology, calculating the economic cost of maintenance, and presenting the impact under different maintenance strategies. Based on the life cycle of each pipeline, multiple effects in the water distribution can be dynamically evaluated, such as pipeline age, failure rate, hydraulic reliability health level etc. Based on special design of chromosome gene encoding, the algorithm of elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) is incorporated to achieve multi-objective optimization solution effectively. With application of a county in Zhejiang province in China, three strategies including empirical decision single-objective optimization decision and multi-objective optimization decision are evaluated and compared to the baseline systematically. Although the annual maintenance cost of strategy III is not the lowest among those three strategies, the pipeline age, failure rate, hydraulic reliability, and health level of the water distribution network under the strategy are at the best level. With multiple objectives considered simultaneously, the results of strategy III are recommended as the optimal maintenance implementation arrangements. This model can promote to find an optimal maintenance strategy, and provide a technical support for the planning, design and implementation of maintenance arrangements of water distribution network in a long-term period.

     

Valve Maneuver Prediction in Simple and Complicated Pipeline Systems

The pressure and flow variations in pipeline systems are extremely sensitive to dynamic operations of the valves. Valve control and propagation of pressure waves along pipelines and their interactions with different pipeline elements introduce pressure transients in pipeline systems. The time series of the pressure head at any designated position depends on boundary conditions such as valve maneuver as well as geometrical and material characteristics of the pipeline system. An innovative method is proposed to calibrate the valve trajectory using pressure head records. The impedance method and particle swarm optimization were integrated with decomposition of convolution between the pressure response function and time series of the valve maneuver. To validate the applicability of this study, the developed method was tested in three hypothetical pipeline systems: a simple reservoir pipeline valve, multiple reservoir pipeline valves, and a complicated pipe network. Decomposition of the transfer function in the time domain and its convolution contributed toward improving the efficiency of the developed method. The successful calibrations of valve actions demonstrate the potential of the proposed scheme as an alternative to conventional flow meters for high-resolution flow rate evaluation.

     

基于多尺度卷积神经网络的管道泄漏检测模型研究

如何有效检测管道泄漏是节水型社会建设迫切需要解决的关键和热点问题之一。近年来基于深度学习的管道泄漏检测方法发展迅速,本文针对传统单尺度卷积神经网络对泄漏特征提取不充分的问题,提出一种基于多尺度一维卷积神经网络(MS1DCNN)的管道系统泄漏检测模型。该方法利用多个不同卷积尺度的卷积通路并行提取管道泄漏的特征并进行泄漏信息的分类预测。基于经典的管道系统布置,利用瞬变流模型生成管道泄漏工况下的三个水压数据集对模型进行验证,三个数据集分别用于预测管道的泄漏位置、泄漏量和非恒定摩阻系数,对应样本数为39601、3980、4900,并将预测结果与其他深度学习方法和传统的机器学习方法进行对比分析。结果表明：MS1DCNN模型对数据集样本下泄漏位置、泄漏量、非恒定摩阻系数的分类准确率达到99.96%、98.48%、100%,三者平均预测精度比传统一维卷积神经网络(1DCNN)、BP神经网络、支持向量机(SVM)和k近邻算法(KNN)提高0.31%、2%、1.27%、22.8%;MS1DCNN在信噪比为-4～12 dB的噪声环境下各数据集的平均F₁分数分别为99.2%、97.02...     

IFTSQP: An Inexact Optimization Model for Water Resources Management under Uncertainty

Abstract

An interval-fuzzy two-stage quadratic programming (IFTSQP) method is developed for water resources management under uncertainty. The methodincorporates techniques of interval-parameter programming, two-stage stochastic programming, and fuzzy quadratic programming within a general optimization framework to tackle multiple uncertainties presented as intervals, fuzzy sets and probability distributions. In the model formulation, multiple control variables are adopted to handle independent uncertainties in the model's right-hand sides; fuzzy quadratic terms are used in the objective function to minimize the variation in satisfaction degrees among the constraints. Moreover, the method can support the analysis of policy scenarios that are associated with economic penalties when the promised targets are violated. The developed method is then applied to a case study of water resources management planning. The results indicate that reasonable solutions have been obtained. They can help provide bases for identifying desired water-allocation plans with a maximized system benefit and a minimized constraint-violation risk.     

Control-Oriented Impedance Matrix and Alternative Transient Control for Pipe Network Systems

In this study, a transient control method is proposed through the generation of an alternative transient in pipe network systems. A control-oriented transient analysis is performed to achieve transient control in the context of linear independence. The relationship between pressure head and discharge are incorporated into a control-oriented impedance matrix and the response function is formulated from either the discharge or pressure head impulse to either a point-scale or integrated section pressure response, or their combination. A surge control scheme is proposed by integrating a metaheuristic algorithm into the superposition platform of the response functions. Application examples demonstrate that the proposed method is a potential platform for a centralized pressure management system in a pipe network. The effectiveness of the proposed scheme in an actual system is confirmed by the method’s feasible multi-objective formulation, efficient computational cost for real-time operation, and robustness against pressure noise in commercially available sensors.

     

管道系统漏损控制技术进展

为了提高供水效率和运行管理水平,针对国内外关于供水管道系统漏损控制方面的现状,从管网故障监测技术及设备、泄漏定位模型方法、信号辨识与算法寻优、健康维护和智能管理等视角梳理了管道系统泄漏监测与漏损控制技术的进展及存在的主要问题,分析了各检测方法用于管网泄漏问题的适用性。在此基础上,从实用角度提出了管网漏损控制值得解决的关键问题和方向如下:(1)针对漏损的监测和预警,应研究面向漏损监控的管网网络组建优化布置及快速预警技术;(2)针对小泄漏的定位模型,应研究管网漏损区域辨识与基于水力反问题分析的主动检测理论和方法;(3)针对检测设备研制,应重点研发基于探地雷达、光纤传感和内窥机器人等新技术的关键设备;(4)针对管网健康维护和智能管理,应研究复杂管网独立计量区域划分方法及管网健康评价和优化维护技术。     

A Parallel Multi-objective Optimization Algorithm Based on Coarse-to-Fine Decomposition for Real-time Large-scale Reservoir Flood Control Operation

Reservoir flood control operation (RFCO) is a multi-objective optimization problem with a long sequence of correlated decision variables. It brings big challenges to large-scale multi-objective optimizers which were generally developed based on the divide-and-conquer strategy. For solving large-scale RFCO problem, a novel coarse-to-fine decomposition method is developed and combined with the algorithmic framework of multi-objective evolutionary algorithm based on decomposition (MOEA/D), giving rise to the proposed pCFD-MOEA/D algorithm. The pCFD-MOEA/D algorithm first divides the original RFCO problem into a sequence of sub-problems from coarse to fine scale with different scheduling time intervals. Then all sub-problems are optimized simultaneously and communicate at set intervals. Experimental results on three typical floods at Ankang reservoir have demonstrated that the proposed pCFD-MOEA/D can successfully obtain the elaborate hourly schedule schemes in real time and outperforms the compared algorithms.

     

Robust Water Supply Chain Network Design under Uncertainty in Capacity

This paper focuses on the capacity uncertainty in water supply chains that occurs when facilities face disruption. A combination of scenario-based two-stage stochastic programming with the min-max robust optimization approach is proposed to optimize the water supply chain network design problem. In the first stage, the decisions are made on locations and capacities of reservoirs and water-treatment plants while recourse decisions including amount of water extraction, amount of water refinement, and consequently amount of water held in reservoirs are made at the second stage. The proposed robust two-stage stochastic programming model can help decision makers consider the impacts of uncertainties and analyze trade-offs between system cost and stability. The literature reveals that most exact methods are not able to tackle the computational complexity of mixed integer non-linear two-stage stochastic problems at large scale. Another contribution of this study is to propose two metaheuristics - a particle swarm optimization (PSO) and a bat algorithm (BA) - to solve the proposed model in large-scale networks efficiently in a reasonable time. The developed model is applied to several hypothetical cases of water resources management systems to evaluate the effectiveness of the model formulation and solution algorithms. Sensitivity analyses are also carried out to analyze the behavior of the model and the robustness approach under parameters variations.

     

改进遗传算法的研究现状分析

遗传算法是全局优化自适应概率搜索算法,它有智能寻优、鲁棒性等优点,但也存在早收敛、结果不精确等不足。因此许多学者提出了一些改进措施来弥补遗传算法的缺点。本文对近些年来出现的改进遗传算法进行了简要介绍,并对其优缺点进行了评述。     

The influence of non-uniform blockages on transient wave behavior and blockage detection in pressurized water pipelines

Blockages in piping systems are formed from potentially complex combinations of bio-film build up, corrosion by-products, and sediment deposition. Transient-based methods seek to detect blockages by analyzing the evolution of small amplitude pressure waves. In theory, such methods can be efficient, nearly non-intrusive and economical but, thus far, studies have only considered symmetrical blockages, uniform in both the radial and longitudinal directions. Laboratory experiments are described here that involve pipe blockages with various levels of irregularity and severity; the way the transient response is affected by a non-uniform blockage is investigated. The differences between uniform and non-uniform blockages are quantified in terms of the rate that wave envelopes attenuate and the degree that phases are shifted. Two different methods for modeling these impacts are compared, namely through an increase in pipe roughness and through a wave scattering model. Wave scattering is shown to play a dominant role in explaining both wave envelope attenuation and phase shift. The accuracy of existing transient-based methods of blockage detection in the frequency domain is also examined, and is found that the predictions of rough blockage locations and sizes by current method are in good agreement with data, with relatively larger discrepancies for rough blockage lengths.     

基于D8算法和Dinf算法的水系提取研究

目前基于DEM提取水系研究较多,采用的方法不同,但对于对比不同方法的研究较少。以福建省为实验样区,采用SRTM DEM高程数据,对比分析了单流向算法(D8算法)与多流向算法(Dinf算法)提取水系结果。结果表明:Dinf算法提取的水系质量优于D8算法,但其计算过程较D8算法复杂;在平坦区域和大河流区域中,Dinf算法改善了D8算法容易产生的"平行伪河道"问题,生成的河网会比较圆滑、自然。     

Optimal and Adaptive Operation of a Hydropower System with Unit Commitment and Water Quality Constraints

Management of water resources has become more complex in recent years as a result of changing attitudes towards sustainability and the attribution of greater attention to environmental issues, especially under a scenario of water scarcity risk introduced by climate changes and anthropogenic pressures. This study addresses the optimal short-term operation of a multi-purpose hydropower system under an environment where objectives are conflicting. New optimization models using mixed integer nonlinear programming (MINLP) with binary variables adopted for incorporating unit commitment constraints and adaptive real-time operations are developed and applied to a real life hydropower reservoir in Brazil, utilizing evolutionary algorithms. These formulations address water quality concerns downstream of the reservoir and optimal operations for power generation in an integrated manner and deal with uncertain future flows due to climate change. Results obtained using genetic algorithm (GA) solvers were superior to gradient based methods, converging to superior optimal solutions especially due to computational intractability problems associated with combinatorial domain of integer variables in the unit commitment formulation. The adaptive operation formulation in conjunction with the solution of turbine unit commitment problem yielded more reliable solutions, reducing forecasting uncertainty and providing more flexible operational rules.     

基于奇异值分解及波数滤波的三维地质雷达噪声抑制技术研究

针对城市地下管线探测中三维地质雷达数据出现强噪声干扰问题,提出基于奇异值分解（SVD）和波数滤波（Wavenumber filtering）相结合的处理方法,并给出了选取奇异值数目阈值的定量判据。研究表明：通过选择合适的奇异值,SVD 方法能准确划分地质雷达数据中的目标信号和噪声信号;基于高斯低通的波数域滤波可有效压制杂波及噪声;将上述SVD 方法与波数滤波方法结合应用,发现可有效提高三维雷达深度切片信号的信噪比,使有效反射信号更加清晰并保证地下目标信息完整性。该方法可提升三维地质雷达对目标反射信号识别的效率与精度,使其更适用于城市地下管线探测。     

Leakage Identification in Water Distribution Networks with Error Tolerance Capability

Leakages in water distribution networks have caused considerable waste of water resources. Thus, this study proposes a novel method for hydraulically monitoring and identifying regions where leakages occur in near-real time. A large network is first divided into several identification regions. To exploit a strong constructive and discriminative power, sparse coding is used, thereby adaptively coding the information embedded in observed pressures efficiently and succinctly. And a linear classifier is trained to determine the most likely leakage regions. A benchmark case is presented in this study to demonstrate the effectiveness of the proposed method. Results indicate that the proposed method can identify leakage events with enhanced tolerance capability for measurement errors. The method is also partially effective for identifying two simultaneous leakages. Certain practical advice in balancing the number of sensors and regions is also discussed to enhance the application potential of this method.