Water Leak Diagnosis in Pressurized Pipelines: A Real Case Study

Delgado-Aguiñaga, J.A.; Begovich, O.

doi:10.1007/978-3-319-55944-5_12

Cited by 12 publications

(16 citation statements)

References 13 publications

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“…In 2017, Delgado et al described the successful localization of a leak in a pipeline of the water distribution network in Guadalajara, Mexico [30]. The localization was achieved by using a discrete-time extended Kalman filter (Appendix A.3), which was constructed by a lumped version of the WH equations.…”

Section: Brief Historymentioning

confidence: 99%

Kalman Filters for Leak Diagnosis in Pipelines: Brief History and Future Research

Torres

Jiménez-Cabas

González

et al. 2020

JMSE

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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.

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Section: Brief Historymentioning

confidence: 99%

Kalman Filters for Leak Diagnosis in Pipelines: Brief History and Future Research

Torres

Jiménez-Cabas

González

et al. 2020

JMSE

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“…Additionally, this table contains some works that propose methodologies based on the Kalman filter for addressing different problems associated with the pipeline operation monitoring, which do not exactly concern leak or fault detection. 1980-1990 [10], [11] 1990-2000 -2000-2010 [20], [14], [35], [36], [16], [15], [12], [37], [18], [23], [38], [39], [24] 2010-Up to the present [40], [25], [26], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [46], [52][28], [53], [54], [55], [29], [30], [31], [32], [33], [34] In Table 1, we present a taxonomy of CPM systems according mainly to the type of Kalman filter employed in the solution formulation of the leak detection and location. In addition, other parameters are highlighted, such as the fluid involved in the study, the type of leak, either single or multiple leaks, and also the type of validation (in a simulation, in a laboratory or in the field).…”

Section: Brief Historymentioning

confidence: 99%

“…Depending on the indication of the selector, one of the two Kalman filters can be used to estimate the position of the leak. The approach was numerically tested with synthetic and experimental data from a hydraulic test apparatus.In 2017, Delgado et al described the successful localization of a leak in a pipeline of the water distribution network in Guadalajara, Mexico[30]. The localization was achieved by using a discrete-time extended Kalman filter (Appendix A.3), which was constructed by a lumped version of the WH equations.…”

mentioning

confidence: 99%

Kalman Filter for Leak Diagnosis in Pipelines: Brief History and Future Research

Torres¹,

Jiménez-Cabas²,

González³

et al. 2019

Preprint

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The purpose of this paper is to provide a structural review of the progress made on detection and localization of leaks in pipelines by using approaches based on the Kalman filter. This is, to the best of our knowledge, the first review on the t opic. 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, we try to gather the results from different research groups and present them in a unified fashion. For this reason, we propose a classification of the current approaches based on the Kalman filter. For each of the existing approaches within this classification, the basic concepts, fundamental results, and relations with the other approaches are discussed in detail. The review starts from a short summary of basic concepts 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, we briefly discuss some emerging research problems, such as the leak detection in pipelines transporting heavy oils, and we discuss the main challenges and some open problems.

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“…The scientific community has paid attention to that problem and has proposed several methodologies for monitoring and supervision purposes in order to avoid losses and accidents (see, e.g, [2][3][4][5][6][7][8][9][10][11]). In particular, in Begovich et al [2], a LDI algorithm based on Billman and Isermann [3] has been implemented and tested with accurate results and based on steady-state conditions, which increase the convergence time in the leak parameter estimation process.…”

Section: Introductionmentioning

confidence: 99%

“…The technique uses a mathematical model derived from the equations of the water hammer together with the method of finite differences for its solution, providing a suitable location for the blockage. Besides, concerning the implementation problem, a recent algorithm based on the extended Kalman filter Delgado-Aguiñaga and Begovich [10] has successfully identified a leak in an aqueduct in Guadalajara, Mexico. A posterior study estimated that approximately 130 million liters of drinking water had been lost in this incident.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Observer Ensemble for Leak Diagnosis in Water Pipelines

et al. 2019

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This work deals with the Leak Detection and Isolation (LDI) problem in water pipelines based on some heuristic method and assuming only flow rate and pressure head measurements at both ends of the duct. By considering the single leak case at an interior node of the pipeline, it has been shown that observability is indeed satisfied in this case, which allows designing an observer for the unmeasurable state variables, i.e., the pressure head at leak position. Relying on the fact that the origin of the observation error is exponentially stable if all parameters (including the leak coefficients) are known and uniformly ultimately bounded otherwise, the authors propose a bank of observers as follows: taking into account that the physical pipeline parameters are well-known, and there is only uncertainty about leak coefficients (position and magnitude), a pair of such coefficients is taken from a search space and is assigned to an observer. Then, a Genetic Algorithm (GA) is exploited to minimize the integration of the square observation error. The minimum integral observation error will be reached in the observer where the estimated leak parameters match the real ones. Finally, some results are presented by using real-noisy databases coming from a test bed plant built at Cinvestav-Guadalajara, aiming to show the potentiality of this method.

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Water Leak Diagnosis in Pressurized Pipelines: A Real Case Study

Cited by 12 publications

References 13 publications

Kalman Filters for Leak Diagnosis in Pipelines: Brief History and Future Research

Kalman Filters for Leak Diagnosis in Pipelines: Brief History and Future Research

Kalman Filter for Leak Diagnosis in Pipelines: Brief History and Future Research

Evolutionary Observer Ensemble for Leak Diagnosis in Water Pipelines

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