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

In this contribution the stability properties and regulation of a class of convective systems described by first order hyperbolic partial differential equations are studied. The systems' setting is consistent with the first and second laws of thermodynamics, allowing to use the entropy functional as a storage function and the internal entropy production as the dissipation in an analogue context to Hamiltonian systems. It is found that the difference of the entropy evaluated at the boundaries is directly proportional to the supply rate, fulfilling the dissipation inequality. Furthermore, the dynamics of the entropy balance allows to define a saturated Proportional-Integral controller with variable parameters, whose design is achieved through a cascade structure. The inner loop tracks an entropy reference, while the outer loop tracks a process variable. The main advantage of the regulation design is that only a lumped actuator is needed with continuous measurements at the boundaries. The controller is designed for an adiabatic plug flow reactor with a recycle of the output stream into the input stream, where the recycle rate is used as the control variable. Finally, the controller is tested to track a set point under several disturbances.

show abstract

“…In addition, the dissipation function defines a variable χ (t) := Ẇ , such that Ẅ in (21) together with the uncertain terms in (22) become…”

Section: A Boundary Controlmentioning

confidence: 99%

Dissipative Boundary Control for an Adiabatic Plug Flow Reactor With Mass Recycle

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Data for training may be acquired through supervisory control and data acquisition (SCADA) system (physical sensors) or from the mathematical models of the pipelines (virtual sensors) [19]. In this study, OLGA simulator is used to generate pipeline data which is based on transient mathematical models and used by several studies [24,40,41].…”

Section: Case Study For Data Generationmentioning

confidence: 99%

“…Pipeline leak detection techniques can be mainly classified into hardware-based and software-based methods [7][8][9]. Hardware-based methods require the installation of external sensors Various software-based techniques like fuzzy systems [17] support vector machine [18][19][20][21], neural networks [22][23][24][25], statistical [26][27][28] and, transient models [29][30][31], etc. are applied in faults detection studies.…”

Section: Introductionmentioning

confidence: 99%

Leak Detection in Gas Mixture Pipelines under Transient Conditions Using Hammerstein Model and Adaptive Thresholds

et al. 2020

View full text Add to dashboard Cite

Conventional leak detection techniques require improvements to detect small leakage (<10%) in gas mixture pipelines under transient conditions. The current study is aimed to detect leakage in gas mixture pipelines under pseudo-random boundary conditions with a zero percent false alarm rate (FAR). Pressure and mass flow rate signals at the pipeline inlet were used to estimate mass flow rate at the outlet under leak free conditions using Hammerstein model. These signals were further used to define adaptive thresholds to separate leakage from normal conditions. Unlike past studies, this work successfully detected leakage under transient conditions in an 80-km pipeline. The leakage detection performance of the proposed methodology was evaluated for several leak locations, varying leak sizes and, various signal to noise ratios (SNR). Leakage of 0.15 kg/s—3% of the nominal flow—was successfully detected under transient boundary conditions with a F-score of 99.7%. Hence, it can be concluded that the proposed methodology possesses a high potential to avoid false alarms and detect small leaks under transient conditions. In the future, the current methodology may be extended to locate and estimate the leakage point and size.

show abstract

“…To determine the associated discrete operators, the resolvent operator is solved in a closed analytical form. Based on that, a discrete water hammer system is obtained in the discrete-time setting, and it is augmented with the measurement and state noise signals, which is amenable for discrete Kalman filter design [76].…”

Section: Single-phase Pipeline Hydraulic Modelmentioning

confidence: 99%

Discrete-Time Kalman Filter Design for Linear Infinite-Dimensional Systems

Xie

Dubljević

2019

Processes

Self Cite

View full text Add to dashboard Cite

As the optimal linear filter and estimator, the Kalman filter has been extensively utilized for state estimation and prediction in the realm of lumped parameter systems. However, the dynamics of complex industrial systems often vary in both spatial and temporal domains, which take the forms of partial differential equations (PDEs) and/or delay equations. State estimation for these systems is quite challenging due to the mathematical complexity. This work addresses discrete-time Kalman filter design and realization for linear distributed parameter systems. In particular, the structural- and energy-preserving Crank–Nicolson framework is applied for model time discretization without spatial approximation or model order reduction. In order to ensure the time instance consistency in Kalman filter design, a new discrete model configuration is derived. To verify the feasibility of the proposed design, two widely-used PDEs models are considered, i.e., a pipeline hydraulic model and a 1D boundary damped wave equation.

show abstract

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

Cited by 37 publications

References 25 publications

Dissipative Boundary Control for an Adiabatic Plug Flow Reactor With Mass Recycle

Dissipative Boundary Control for an Adiabatic Plug Flow Reactor With Mass Recycle

Leak Detection in Gas Mixture Pipelines under Transient Conditions Using Hammerstein Model and Adaptive Thresholds

Discrete-Time Kalman Filter Design for Linear Infinite-Dimensional Systems

Contact Info

Product

Resources

About