An algebraic observer for leak detection and isolation in plastic pipelines

In the continuation of authors' studies on leak diagnosis in pipelines, a new model-based Leak Detection and Isolation (LDI) algorithm is designed. This system only uses measures of flow and pressure coming from sensors placed at the ends of a pipeline. The present approach is based on a finite nonlinear pipeline model, and extended with variables related to the leak. On this basis, the purpose here is to investigate the use of a so-called algebraic observer to estimate the leak position and its magnitude. The corresponding observer design is thus presented, and its performances are illustrated both with simulation results, and experimental ones, with data taken from a real pipeline prototype.Consejo Nacional de Ciencia y TecnologíaInstitut Universitaire de FranceUniversidad Nacional de Colombi

Real time leak detection and isolation in pipelines: a comparison between Sliding Mode Observer and algebraic steady state method

The purpose of this paper is to compare two different algorithms used to detect and isolate water leaks in a pipeline. One method is based on a Sliding Mode Observer and the second method is an Algebraic method obtained from the pipeline model in steady state. Because of the simplicity of both methods, they can be easily implemented. The methods were tested offline with real time data and the Algebraic method was also implemented online. Satisfactory results are shown through some experiments.Consejo Nacional de Ciencia y Tecnologí

Kalman filters for leak diagnosis in pipelines: brief history and future research

The purpose of this paper is to provide a structural review of the progress made on the detection and localization of leaks in pipelines by using approaches based on the Kalman filter. To the best of the author’s knowledge, this is the first review on the topic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, the paper gathers the results from different research groups such that these are presented in a unified fashion. For this reason, a classification of the current approaches based on the Kalman filter is proposed. For each of the existing approaches within this classification, the basic concepts, theoretical results, and relations with the other procedures are discussed in detail. The review starts with a short summary of essential ideas about state observers. Then, a brief history of the use of the Kalman filter for diagnosing leaks is described by mentioning the most outstanding approaches. At last, brief discussions of some emerging research problems, such as the leak detection in pipelines transporting heavy oils; the main challenges; and some open issues are addressed

Real Time Leak Isolation in Pipelines Based on a Time Delay Neural Network

In this paper, the one leak isolation problem in a water pipeline is tackled using a Time Delay Neural Network. This scheme comes as an alternative to achieve better computing performance since the classical model-based methods usually have high workloads due to the pipe mathematical model complexity compared with the leak dynamics speed. The Neural Network structure could have better time performance exploiting the parallel architecture of some electronics devices like an FPGA. The authors propose a scheme where, due to the difficulty in obtaining training data from a real pipeline, a mathematical model is used to generate synthetic training data. Such training data is obtained using different leak magnitudes and leak positions and it is also corrupted by random noise in order to emulate real data pipe. Finally, to show the potentiality of this method, some results are presented by using real-noisy databases coming from a pipeline prototype.Following the classical leak diagnosis hypothesis, only flow and pressure sensor at both ends of the aqueducts are used for the treatment.ITESO, A.C

Liquid Transport Pipeline Monitoring Architecture Based on State Estimators for Leak Detection and Location

This research presents the implementation of optimization algorithms to build auxiliary signals that can be injected as inputs into a pipeline in order to estimate —by using state observers—physical parameters such as the friction or the velocity of sound in the fluid. For the state estimator design, the parameters to be estimated are incorporated into the state vector of a Liénard-type model of a pipeline such that the observer is constructed from the augmented model. A prescribed observability degree of the augmented model is guaranteed by optimization algorithms by building an optimal input for the identification. The minimization of the input energy is used to define the optimality of the input, whereas the observability Gramian is used to verify the observability. Besides optimization algorithms, a novel method, based on a Liénard-type model, to diagnose single and sequential leaks in pipelines is proposed. In this case, the Liénard-type model that describes the fluid behavior in a pipeline is given only in terms of the flow rate. This method was conceived to be applied in pipelines solely instrumented with flowmeters or in conjunction with pressure sensors that are temporarily out of service. The design approach starts with the discretization of the Liénard-type model spatial domain into a prescribed number of sections. Such discretization is performed to obtain a lumped model capable of providing a solution (an internal flow rate) for every section. From this lumped model, a set of algebraic equations (known as residuals) are deduced as the difference between the internal discrete flows and the nominal flow (the mean of the flow rate calculated prior to the leak). The residual closest to zero will indicate the section where a leak is occurring. The main contribution of our method is that it only requires flow measurements at the pipeline ends, which leads to cost reductions. Some simulation-based tes

Real-time leak diagnosis in water distribution systems based on a bank of observers and a genetic algorithm

The main contribution of this paper is to present a novel solution for the leak diagnosis problem in branched pipeline systems considering the availability of pressure head and flow rate sensors on the upstream (unobstructed) side and the downstream (constricted) side. This approach is based on a bank of Kalman filters as state observers designed on the basis of the classical water hammer equations and a related genetic algorithm (GA) which includes a fitness function based on an integral error that helps obtaining a good estimation despite the presence of noise. For solving the leak diagnosis problem, three stages are considered: (a) the leak detection is performed through a mass balance; (b) the region where the leak is occurring is identified by implementing a reduced bank of Kalman filters which localize the leak by sweeping all regions of the branching pipeline through a GA that reduces the computational effort; (c) the leak position is computed through an algebraic equation derived from the water hammer equations in steady-state. To assess this methodology, experimental results are presented by using a test bed built at the Tuxtla Gutiérrez Institute of Technology, Tecnológico Nacional de México (TecNM). The obtained results are then compared with those obtained using a classic extended Kalman filter which is widely used in solving leak diagnosis problems and it is highlighted that the GA approach outperforms the EKF in two cases whereas the EKF is better in one case.Peer ReviewedPostprint (published version

Online leak diagnosis in pipelines using an EKF-based and steady-state mixed approach

This paper proposes a methodology for leak detection and isolation (LDI) in pipelines based on data fusion from two approaches: a steady-state estimation and an Extended Kalman Filter (EKF). The proposed method considers only pressure head and flow rate measurements at the pipeline ends, which contain intrinsic sensor and process noise. The LDI system is tested in real-time by using an USB data acquisition device that is implemented in MATLAB environment. The effectiveness of the method is analyzed by considering: online detection, location as well as quantification of non-concurrent leaks at different positions. The leak estimation error average is less than 1% of the flow rate and less than 3% in the leakage position. Furthermore, the incorporation of a steady-state estimation shows that the solution of the LDI problem has improved significantly with respect to the one that only considers the EKF estimation. An experimental analysis was also performed on the effectiveness of the proposed approach for different sampling rates and for different leakage positionsPeer ReviewedPostprint (author's final draft

Leak detection using instantaneous frequency analysis

Leaking pipes are a primary concern for water utilities around the globe as they compose a major portion of losses. Contemporary interest surrounding leaks is well documented and there is a proliferation of leak detection techniques. Although the reasons for these leaks are well known, some of the current methods for leak detection and location are either complicated, inaccurate and most of them are time consuming. Transient analyses offer a plausible route towards leak detection due to their robustness and simplicity. These approaches use the change of pressure response of the fluid in a pipeline to identify features. The method used in the current study employ a single pressure transducer to obtain the time domain signal of the pressure transient response caused by a sudden opening and closing of a solenoid valve. The device used is fitted onto a standard UK hydrant and both cause a pressure wave and acquire the pressure history. The work described here shows that the analysis using Hilbert transform (HT), Hilbert Huang transform (HIHT) and EMD based method is a promising tool for leak detection and location in the pipeline network. In the first part of the work, the analysis of instantaneous characteristics of transient pressure signal has been calculated using HT and HHT for both simulated and experimental data. These instantaneous properties of the signals are shown to be capable of detecting the reflection from the features of the pipe such as leakages and outlet. When tested with leak different locations, the processed results still show the existing of the features in the system. In the second part of the work, the study is based on newly method of analysing nonstationary data called empirical mode decomposition (EMD) for instantaneous frequency calculation for leak detection. First, the pressure signals were filtered in order to remove the noise using EMD. Then the instantaneous frequency was calculated and compared using different methods. With this method, it is possible to identify the leaks and also the features in the pipeline network. These were tested at different locations of a real water distribution system in the Yorkshire Water region

Leakage Characterisation in Bulk Pipes using Pressure Tests

The supply of water is becoming increasingly strained as the demand for this essential and limited resource continues to increase. A significant amount of this resource is, however, lost through leakage. Not only does this result in a waste of a precious resource, but it also leads to a direct loss of revenue, especially considering that value has been added to the leaking water through collection, storing, purifying and pumping. A great deal of research has been done on reducing water leakages in distribution networks, however, leakage in bulk pipelines has received comparatively little attention thus far. In this study, bulk pipelines in the field were tested with a pressure testing device developed by the University of Cape Town. With this device, a range of pressures were applied to various pipeline sections and the corresponding leakages were measured, resulting in characteristic pressure-leakage relationships. The Fixed and Variable Area Discharge (FAVAD) and the empirical N1 leakage models were then applied to interpret the pressure-leakage relationships. Thirteen tests were attempted on pipeline sections ranging from 300 mm to 600 mm in diameter, and pressure tests were successfully performed on eight of the thirteen sections. Even though the effectiveness of the testing technique is dependent on the sealing capability of the isolation valves, it was found that most valves sealed effectively, with only two pipelines sections failing to isolate. The high elevation differences along the length of the pipelines were found to have a dominating effect on the characteristics of the leak, which made it possible to roughly estimate the most likely leak locations by comparing the observed leak characteristics to those found in literature for similar conditions. The dependence of the leak characteristics on the location means that both have to be determined simultaneously. This can benefit the analysis, as some locations may be excluded based on their unrealistic leakage characteristics. However, it also means that there will be uncertainty with regards to the true location and leakage characteristics for sections of the pipe where the leakage characteristics are realistic. Nonetheless, the measured leakage rate together with the estimated leak characteristics provided valuable information on the pipeline conditions, making it possible to rank the pipelines according to the severity of their conditions, for optimal allocation of maintenance resources. Through practical tests, the study shows that pressure testing is an effective, simple and low cost technique to assess leakage in bulk pipelines. It causes minimal interference to the pipe operation, requires little downtime and the data can be processed in minimal time

Localization Techniques for Water Pipeline Leakages: A Review

Pipeline leakages in water distribution network (WDN) is one of the prominent issues that has gain an interest among researchers in the past few years. Time and accuracy play an important role in leak localization as it has huge impact to the human population and economic point of view. The complexity of WDN has prompt numerous techniques and methods been introduced focusing on the accuracy and efficacy. In general, localization techniques can be divided into two broad categories; external and internal systems. This paper reviews some of the techniques that has been explored and proposed including the limitations of each techniques. Â