Leak detection and location based on improved pipe model and nonlinear observer

Guillén, Marcos; Dulhoste, Jean-François; Besançon, Gildas; Scola, Ignácio Rubio; Duby, Georges

doi:10.1109/ecc.2014.6862388

Cited by 19 publications

(18 citation statements)

References 13 publications

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“…As we know, the maximum magnitude of the pressure fluctuation appears at the resonances of the pipeline system while the minimum comes at the anti-resonances. Similarly, resonances of the reservoir-pipe-valve system have been studied in detail in the past [13,17,19,22,24,26], to depress the damages from the steep rise of pressure head or to detect leakages and blockages in the pipeline system. However, little work takes care of the influence of the parameters of pipeline structure and fluid on the behavior of resonance and anti-resonance.…”

Section: Stma Modelmentioning

confidence: 99%

“…Thus, the approximation errors verified a remarkable accuracy of the extremums prediction, and the unsteady friction model has more complicated influences on the frequency response than the steady friction model. Detailed impacts of the VSI conditions with the steady friction model on the extremums of pressure fluctuations amplitudes (Equations (19)(20)(21)(22)(23)(24)(25)) are shown in Figure 9. When the VSI is increasing from γ 1 = 0.1 to γ 1 = 10, the pressure fluctuations amplitudes at frequencies ω = (n − 1 2 ) πa L , n = 1, 2 • • • decline sharply at both the upstream side and downstream side, whereas those at frequencies ω = nπa L , n = 1, 2, • • • fall after a rise at the upstream side and fall after holding at the downstream side.…”

Section: κ =mentioning

confidence: 99%

“…The transfer matrix equations were proposed to detect the leakage in a single pipe with the relative size of resonance peaks at certain odd harmonic frequencies [13][14][15][16][17]. Verde [18] reconstructed two leaks in a pipeline, while Guillen [19] provided a model to obtain system frequency response with two observers at the inlet and outlet, respectively. On the other hand, the detection of the blockage in the pipeline was also developed.…”

Section: Introductionmentioning

confidence: 99%

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Model Analysis and System Parameters Investigation for Transient Wave in a Pump–Pipe–Valve System

Zu-bin

Pan

et al. 2020

Water

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The frequency responses of the transient wave propagating in a pump–pipe–valve system are studied with the system transfer matrix analysis (STMA) method. Being different to that in the reservoir–pipe–valve system, the transient wave is used as a long-distance communication technology in the pump–pipe–valve system, and very few works have been done on the model analysis and strategies to control the behavior of the oscillation signal of the pipe pressure. The theoretic solutions are studied with three internal friction models: frictionless, steady friction, and unsteady friction. The dimensionless parameter of the valve signal intensity (VSI) is proposed, and it is found to be a key factor affecting the quality of the wave propagation in the pipe. A larger pressure oscillation at the upstream side results when the VSI is smaller than one, whereas a more uniform amplitude for the resonances and anti-resonances is obtained when VSI approaches one. Some feasible suggestions are provided to obtain high quality wave signals.

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Section: Stma Modelmentioning

confidence: 99%

Section: κ =mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Model Analysis and System Parameters Investigation for Transient Wave in a Pump–Pipe–Valve System

Zu-bin

Pan

et al. 2020

Water

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“…The simplest possible late-lumping observer design utilizing the feedback structure in (13) is to consider boundary correction via the feedback gain k l only and to set k = 0. This choice is particularly interesting since the resulting PDEs of the observer model (13) are exactly the same as for the plant model (10), whereas only the enforced boundary conditions change. This has the advantage of a rather fast and computationally efficient implementation once a simulation model for the plant is available.…”

Section: Lyapunov-based Observer Designmentioning

confidence: 99%

“…In terms of early-lumping designs, the method of choice is some sort of Kalman filter or extended Kalman filter (EKF). Herein, finite-difference methods (FDMs [9][10][11] ), finite-element methods, 12 or spectral methods (SMs 13,14 ) are used to spatially discretize the governing PDEs. The resulting system of ordinary differential equations is then used for the observer design.…”

mentioning

confidence: 99%

Early‐ and late‐lumping observer designs for long hydraulic pipelines: Application to pumped‐storage power plants

Marko

Mennemann

Jadachowski

et al. 2018

Intl J Robust & Nonlinear

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Pumped-storage power plants typically feature very long hydraulic pipelines, which can be modeled by a set of partial differential equations. The estimation of the pressure and volumetric flow along the pipes is an important task for the operation of such a plant. Therefore, this work compares different earlyand late-lumping-based observer designs for this system. Two late-lumping observers, ie, a Lyapunov-based design and an observer using the backstepping design method, are examined. The Lyapunov-based approach uses a simple boundary correction to stabilize the estimation error dynamics. In contrast, the backstepping-based approach allows utilizing additional in-domain correction to obtain a faster rate of convergence. For the implementation of these distributed-parameter observers, the spectral element method as a flexible and computationally efficient discretization method is introduced. It is shown that, compared with that of the Lyapunov-based design, the discretization of the backstepping-based design requires additional spatial grid points for the accurate approximation of its feedback gains. For the early-lumping approach, the spectral element method is used to approximate the model equations by a system of differential equations. Based on this approximation, an extended Kalman filter is designed. All observer designs are validated and compared for a representative test case. KEYWORDS distributed-parameter system, hydraulic pipeline, late lumping, spectral element method, state estimation INTRODUCTIONNowadays, the amount of electrical energy produced by renewable sources like wind turbines or solar panels is steadily increasing. Despite all their positive properties, most of these energy sources have the major drawback of being highly volatile in comparison to conventional sources like coal or gas. In order to compensate for the differences between generation and load and, thus, to ensure grid stability, large-scale energy storage capabilities like pumped-storage power plants are necessary. 1,2 A typical pumped-storage power plant comprises several turbines (Francis or Pelton type), which are connected to an upper and a lower reservoir by long hydraulic pipelines. The control of pumped-storage power plants, with the aim to react as fast as possible to load fluctuations in the electric grid while respecting the physical limits of the system at Int J Robust Nonlinear Control. 2018;28:2759-2779.wileyonlinelibrary.com/journal/rnc

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Long range pipeline leak detection and localization using discrete observer and support vector machine

Xie

Dubljević

2019

AIChE Journal

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A realistic pipeline modeled by a nonlinear coupled first‐order hyperbolic partial differential equations (PDEs) system is studied for the long transportation pipeline leak detection and localization. Based on the so‐called water hammer equation, a linear distributed parameter system is obtained by linearization. The structure and energy preserving time discretization scheme (Cayley–Tustin) is used to realize a discrete infinite‐dimensional hyperbolic PDEs system without spatial approximation or model order reduction. In order to reconstruct pressure and mass flow velocity evolution with limited measurements, a discrete‐time Luenberger observer is designed by solving the operator Riccati equation. Based on this distributed observer system, data on different normal and leakage conditions (various leak amounts and positions) are generated and fed to train a support vector machine model for leak detection, amount, and position estimation. Finally, the leak detection, amount estimation, and localization effectiveness of the developed method are proved by a set of simulations. © 2019 American Institute of Chemical Engineers AIChE J, 65: e16532 2019

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Leak detection and location based on improved pipe model and nonlinear observer

Cited by 19 publications

References 13 publications

Model Analysis and System Parameters Investigation for Transient Wave in a Pump–Pipe–Valve System

Model Analysis and System Parameters Investigation for Transient Wave in a Pump–Pipe–Valve System

Early‐ and late‐lumping observer designs for long hydraulic pipelines: Application to pumped‐storage power plants

Long range pipeline leak detection and localization using discrete observer and support vector machine

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