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A model-based approach to detect and isolate non-concurrent multiple leaks in a pipeline is proposed, only using pressure and flow sensors placed at the pipeline ends. The approach relies on a nonlinear modeling derived from Water–Hammer equations, and related Extended Kalman Filters used to estimate leak coefficients. This extends former results d...
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We develop a novel jet engine health monitoring method using a high-fidelity, physics-based simulation model. In jet engine health monitoring, fault detection with a state estimation is frequently carried out. However, a challenge for a filtering-based health monitoring method with a high-fidelity model is the difficulty to analytically obtain the...
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... Regarding fault diagnosis [2][3][4], this stage deals with abnormal behaviors (faults) by detecting, locating, and identifying them. The output of this stage can either alert human operators, or be used by a fault-tolerant system with the aim of removing hazardous situations. ...
This study focuses on generating reliable signals from measured noisy signals through an enhanced sensor fusion method. The main contribution of this research is the development of a novel sensor fusion architecture that creates virtual sensors, improving the system’s redundancy. This architecture utilizes an input observer to estimate the system input, then it is introduced to the system model, the output of which is the virtual sensor. Then, this virtual sensor includes two filtering stages, both derived from the system’s dynamics—the input observer and the system model—which effectively diminish noise in the virtual sensors. Afterwards, the same architecture includes a classical sensor fusion scheme and a voter to merge the virtual sensors with the real measured signals, enhancing the signal reliability. The effectiveness of this method is shown by applying merged signals to two distinct diagnosers: one utilizes a high-order sliding mode observer, while the other employs an innovative extension of a predefined-time observer. The findings indicate that the proposed architecture improves diagnostic results. Moreover, a three-wheeled omnidirectional mobile robot equipped with noisy sensors serves as a case study, confirming the approach’s efficacy in an actual noisy setting and highlighting its principal characteristics. Importantly, the diagnostic systems can manage several simultaneous actuator faults.
... Both single and multiple leak scenarios have been resolved for individual pipelines. Some recent works for the single leak case are [6]- [10] whereas for the multi leak case [11]- [14], to mention a few recent works. The reference [15] provides a complete review of LDI methods. ...
The current study addresses the problem of leak detection and isolation (LDI) in a branched pipeline system. The detection process employs a mass balance approach following mass conservation principles. The leak isolation algorithm is activated upon detecting a leak, comprising a bank of
m
observers corresponding to the number of pipeline branches in the system. The state-space representation of the branched pipe, derived from a classical dynamic representation of a pipeline system, incorporates two variables defining the leak: its position and magnitude. The observability condition for each observer is fulfilled, ensuring the complete reconstruction of the state. To enhance robustness, a super-twisting algorithm (STA), functioning as an exact differentiator, is introduced to estimate the time derivatives of inputs and outputs. Consequently, the complete state is reconstructed using a set of algebraic equations dependent solely on inputs, outputs, and their time derivatives. The analysis considers only the flow rates and pressure head measurements at the inlets and outlets of the pipeline system. For illustrative purposes, experimental results of five leak scenarios are presented, utilizing databases generated from a test bed plant with two branchings constructed at the Tuxtla Gutiérrez Institute of Technology.
... 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. ...
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.
... Some studies have attempted to address multi-leak detection, yet challenges remain. Studies such as [17] describe a multileak detection strategy with adaptation strategies for each new leak occurrence, but parameter deviations often result in increased estimation errors. Similarly, relying solely on sensors at pipeline ends and steady flow can lead to inaccurate leak location in multi-leak scenarios [18]. ...
... Dynamic models of two-leak equivalent to one-leak can be explained using Eqs. (17) and (16) with unknown parameters p and z 2 . As described in [23], the authors propose creating a parameterized dynamic model for two simultaneous leak scenarios. ...
This study proposes a model-based fault detection method for identifying and pinpointing simultaneous leaks in a pipeline, utilizing flow and pressure sensors positioned at the ends of the pipeline. Nonlinear system equations were derived using continuity and momentum principles. It explores a scheme that involves online residual generation for detecting and localizing multiple leaks. This approach incorporates a two-stage decision-making algorithm integrating leak localization with real-time friction parameter identification, which is essential for estimating new simultaneous leaks in the pipeline. A nonlinear observer continuously identifies friction parameters, which is necessary due to oil's non-Newtonian behavior at all temperatures. Additionally, it constructs a dynamic model considering equivalence in the steady state of a leak's position with two simultaneous leaks. An identification process is proposed for estimating the specific parameters of the equivalence model by minimizing the quadratic error between pipeline data and steady-state class members. Compared to existing methods, its main innovation is to update oil pipeline friction functions in real time for all simultaneous leak scenarios. OLGA software simulates oil pipeline realistic operation. Results of the leak detector with different scenarios offered estimation errors of less than 0.5% in all the cases for an oil pipeline of 50 [km]. The effectiveness of the proposed method is confirmed by the convergence of system state and precision in the localization of various simultaneous leak scenarios.
... Double leakages, owing to their timing (occurrence), are classified into concurrent or non-concurrent. Internal methods for diagnosing multiple (double) leaks are reviewed in several papers [1,[5][6][7], with references to both non-simultaneous [8,9] and simultaneous leak cases [10][11][12][13]. ...
... On the whole, software-based detection and localization of multiple leaks, even in the two-leak case, remains a challenge [9,14]. As regards the difficulty, non-simultaneous leaks are easier to diagnose than simultaneous or almost simultaneous leaks in which transient states caused by their occurrence overlap in time. ...
... Therefore, more advanced solutions are applied, which often use the models of flow dynamics [1,[8][9][10][11][12][13][14]17]. When a two-leak case is perceived from the perspective of dynamic models in steady-state conditions, its general symptoms are consistent with a case of a single leak [1]. ...
The article deals with a diagnosis of multiple leaks from liquid transmission pipelines using analytical methods. Such solutions, based on advanced mathematical models of pipeline flow dynamics, usually turn out to be very complex and time-consuming. However, under certain operating conditions, a simpler approach may also be useful. Such an idea is presented in this paper, proposing two simplified methods for diagnosing double leakages. In principle, these methods apply to both simultaneous and non-simultaneous leaks. The first one uses a static model of a pipeline involving two leaks and takes advantage of the minimization of the objective function defined as the squared deviation of the modeled pressures from the pressures measured on the pipeline. The second method uses a pipeline flow model of a static type in combination with a gradient indicator aimed at detecting leaks and employing algorithms assigned to determining the location and size of leaks. The results of methods’ validation, based on tests carried out with the use of measurement data obtained from an experimental water pipeline, were also presented. The outcomes of the performed tests proved the methods’ effectiveness in terms of detection, isolation, localization, and intensity estimation of both simultaneous and non-simultaneous double leakages.
... The observer uses pressure or flow rate measurement, and no more sensors or equipment are required. In [3], the high-pressure gas pipeline was modeled as a linear parameter varying (LPV) system, and the differential Kalman filter was used as the observer to estimate the leaks. In [4], a nonlinear model derived from the water hammer equation (WHE), and the EKF observer is employed to evaluate multi leaks in pipelines. ...
The high-pressure gas cylinder is the pressure source for liquid propellant engine valve control. Leakage is a significant cause of pressure loss in gas cylinders, leading to engine control failure and serious flight accidents. In this paper, a model-based approach to estimate the leakage area and remaining useful life (RUL) of gas cylinders is proposed. To estimate the leakage area, a state space representation of the cylinder system is developed based on the nonlinear model derived from momentum, energy, and continuity equations. Leakage is defined as a system state, and an extended Kalman filter (EKF) as a state observer is implemented to estimate the leakage area. Internal pressure measurements of the gas cylinder are required as output parameters in the estimation process. Then, the estimated states are fed into the nonlinear model to iteratively calculate the RUL of the cylinder. To evaluate the effectiveness of the proposed method, scaling leakage test data, computational fluid dynamics (CFD) simulation results, and liquid rocket engine (LREs) hot test data are used. Calibration results have proved the validity and universality of the method, with the mean absolute error (MAE) for the remaining 80% useful life prediction results being less than 0.02, 0.04, and 1.10. This study can provide technical support for fault tolerance control and orbital replanning in case of control gas cylinder leaks.
... Research progress has been achieved in developing various kinds of pipeline leakage detection and localization approaches. Model-based approach such as hydraulic gradient approach (Carrera et al., 2015;Lopezlena and Sadovnychiy, 2019;Rojas and Verde, 2020;Torres et al., 2021), Kalman filter approach (Delgado-Aguiñaga et al., 2016, Fisher Discriminant Analysis approach (Romero-Tapia et al., 2018) etc., has been developed by discovering hidden fluid mechanics with mathematical complexity. Its accuracy of leakage detection and localization for different pipeline networks has been widely accepted as well. ...
... Research progress has been achieved in developing various kinds of pipeline leakage detection and localization approaches. Model-based approach such as hydraulic gradient approach (Carrera et al., 2015;Lopezlena and Sadovnychiy, 2019;Rojas and Verde, 2020;Torres et al., 2021), Kalman filter approach (Delgado-Aguiñaga et al., 2016, Fisher Discriminant Analysis approach (Romero-Tapia et al., 2018) etc., has been developed by discovering hidden fluid mechanics with mathematical complexity. Its accuracy of leakage detection and localization for different pipeline networks has been widely accepted as well. ...
Natural gas release from oil and gas facilities contributes significantly to the greenhouse effect and reduces the benefit of displacing heavy fossil fuels with natural gas. Real-time concentration spatiotemporal evolution forecasting of natural gas release is essential to predetermine atmospheric carbon trajectory and devise timely strategy to mitigate the expected impact on the environment. Deep learning approaches have recently been applied for spatiotemporal forecast tasks, but they still exhibit poor performance pertaining to uncertainty and boundary estimations. This study proposes an advanced Hybrid-Physics Guided-Variational Bayesian Spatial-Temporal neural network. Experimental study based on a benchmark experimental and simulation dataset was conducted. The results demonstrated that the additional uncertainty information estimated contributes to reducing the harmful ‘over confidence’ of the point-estimation models at the plume area. Also, the proposed normalized uncertainty and physical inconsistency constraint term ensured the accuracy at the plume boundary. By adopting the Monte Carlo sampling number m = 100, penalty factor λ = 0.1, and drop probability p = 0.1, the model achieves a real-time capacity of an inference time less than 1s and a competitive accuracy of R² = 0.988. Overall, our proposed model could provide reliable support to maximize the environmental benefits of natural gas energy usage and contribute to the carbon peak and neutrality target.
... In a pioneering work, Verde (2001) utilized a set of Kalman filters for localizing more than one leak in a steady-flow hydraulic pipeline with end sensors. Using data of pressure and flow at the ends of a pipeline, research for detecting and localizing multiple pipeline leaks has focused on developing schemes with various types of filters and optimization methods (Delgado-Aguiñaga et al. 2016;Keramat and Duan 2021;Kim 2020;Lang and Yuan 2020;Li et al. 2020;Rojas and Verde 2020;Torres et al. 2012;Verde 2005;Verde et al. 2014;Wang and Ghidaoui 2020). Sophisticated signal processing is applied to pressure and flow measurements at the pipeline's inlet and outlet, leading to reasonably reliable detection of multiple leaks. ...
ecause leaks tend to form at joints or welds at the intersection of modular pipes, the occurrence of multiple leaks in a long pipeline is possible. In this study, a multiple-leak detection methodology using an acoustic method was adopted. A mathematical model based on using the transfer matrix method for calculating the sound transmission loss in a pipeline with multiple leaks is presented. It was found that one can clearly differentiate the transmission loss spectrum of multiple leaks from that of a single leak. It was also established that one can distinguish the transmission loss spectra of pipes having two or three concurrent leaks. The transmission loss curves further appear to provide useful indications on the level of leaking severity.
... Some studies have attempted to address multi-leak detection, yet challenges remain. Studies such as [17] describe a multileak detection strategy with adaptation strategies for each new leak occurrence, but parameter deviations often result in increased estimation errors. Similarly, relying solely on sensors at pipeline ends and steady flow can lead to inaccurate leak location in multi-leak scenarios [18]. ...
... Dynamic models of two-leak equivalent to one-leak can be explained using Eqs. (17) and (16) with unknown parameters p and z 2 . As described in [23], the authors propose creating a parameterized dynamic model for two simultaneous leak scenarios. ...
