Pipeline Parameter Identification and Leak Localization Using Experimental Data

2014 ◽  
Author(s):  
Kamal Moustafa ◽  
Yousef Haik
Keyword(s):  
Parameter Identification ◽  
Real Life ◽  
Pressure Head ◽  
Leak Location ◽  
Localization Scheme ◽  
Pipeline Systems ◽  
Leak Localization ◽  
Points Of View ◽  
Detection And Localization ◽  
Minimum Objective Function

Pipeline systems are important in many fields of real life to distribute fluids from one location to another. Leakage from such pipeline systems poses serious problems from the technical, environmental and economic points of view. Early leak detection and localization is, therefore, important for real life applications. In this paper, an experimental study is conducted to collect the pressure head measurements at a number of nodes along a pipeline carrying oil for both the healthy and leaky cases. The experimentally measured data are utilized to identify the leak factor and coefficient of friction of the considered pipeline. The identified parameters are utilized by the propose localization scheme to determine the leak location. The identification is implemented by a window marching technique that uses the collected pressure head measurements and seeking the minimum objective function that represents the mismatch between the measured and numerically modeled pipeline variables. Monte Carlo simulation results are reported to demonstrate the effectiveness of the proposed parameter identification and leak localization techniques.

Leak detection and localization for pipelines using multivariable fuzzy learning backstepping

2021 ◽  
pp. 1-12
Author(s):  
Farzin Piltan ◽  
Jong-Myon Kim
Keyword(s):  
Transmission Lines ◽  
Leak Detection ◽  
Support Vector ◽  
Robust Learning ◽  
Regression Techniques ◽  
Space Formulation ◽  
Points Of View ◽  
Detection And Localization ◽  
Fuzzy Learning ◽  
Backstepping Algorithm

Pipelines are a nonlinear and complex component to transfer fluid or gas from one place to another. From economic and environmental points of view, the safety of transmission lines is incredibly important. Furthermore, condition monitoring and effective data analysis are important to leak detection and localization in pipelines. Thus, an effective technique for leak detection and localization is presented in this study. The proposed scheme has four main steps. First, the learning autoregressive technique is selected to approximate the flow signal under normal conditions and extract the mathematical state-space formulation with uncertainty estimations using a combination of robust autoregressive and support vector regression techniques. In the next step, the intelligence-based learning observer is designed using a combination of the robust learning backstepping method and a fuzzy-based technique. The learning backstepping algorithm is the main part of the algorithm that determines the leak estimation. After estimating the signals, in the third step, their classification is performed by the support vector machine algorithm. Finally, to find the size and position of the leak, the multivariable backstepping algorithm is recommended. The effectiveness of the proposed learning control algorithm is analyzed using both experimental and simulation setups.

New Leak Location Approaches for Gas Pipelines Using Acoustic Waves

2018 ◽  
Author(s):  
Cuiwei Liu ◽  
Yuxing Li ◽  
Qihui Hu ◽  
Wuchang Wang ◽  
Yazhen Wang ◽  
...  
Keyword(s):  
Natural Gas ◽  
Acoustic Waves ◽  
Economic Loss ◽  
Transportation Systems ◽  
Gas Pipelines ◽  
Natural Gas Pipelines ◽  
New Methods ◽  
Leak Location ◽  
Localization Errors ◽  
Leak Localization

Natural gas is a vital energy carrier which can serve as an energy source, which is extremely vulnerable to leakages from pipeline transportation systems. The required ignition energy is low. Although the safety of natural gas pipelines has been improved, the average economic loss of natural gas accidents, including leaks, is large. To solve these problems, an acoustic leak localization system is designed and researched for gas pipelines using experiments with methods proposed according to different application situations. The traditional method with two sensors installed at both ends can be improved by a newly proposed combined signal-processing method, which is applied for the case that it is necessary to calculate the time differences with data synchronicity. When the time differences cannot be calculated accurately, a new method based on the amplitude attenuation model is proposed. Using these methods, the system can be applied to most situations. Next, an experimental facility at the laboratory scale is established, and experiments are carried out. Finally, the methods are verified and applied for leak localization. The results show that this research can provide a foundation for the proposed methods. The maximum experimental leak localization errors for the methods are −0.592%, and −7.62%. It is concluded that the system with the new methods can be applied to protect and monitor natural gas pipelines.

scholarly journals Vibration Based Damage Detection of Rotating Beams

2018 ◽  
Vol 148 ◽  
pp. 14008 ◽  
Author(s):  
Stanislav Stoykov ◽  
Emil Manoach ◽  
Maosen Cao
Keyword(s):  
Damage Detection ◽  
Selection Criteria ◽  
Excitation Frequency ◽  
Real Life ◽  
Equation Of Motion ◽  
Damage Localization ◽  
Rotating Beam ◽  
Free Boundary Conditions ◽  
Wide Range ◽  
Detection And Localization

The early detection and localization of damages is essential for operation, maintenance and cost of the structures. Because the frequency of vibration cannot be controlled in real-life structures, the methods for damage detection should work for wide range of frequencies. In the current work, the equation of motion of rotating beam is derived and presented and the damage is modelled by reduced thickness. Vibration based methods which use Poincaré maps are implemented for damage localization. It is shown that for clamped-free boundary conditions these methods are not always reliable and their success depends on the excitation frequency. The shapes of vibration of damaged and undamaged beams are shown and it is concluded that appropriate selection criteria should be defined for successful detection and localization of damages.

scholarly journals Compressed sensing based optimal sensor placement for leak localization in water distribution networks

2017 ◽  
Vol 20 (6) ◽  
pp. 1286-1295 ◽  
Author(s):  
Xiang Xie ◽  
Quan Zhou ◽  
Dibo Hou ◽  
Hongjian Zhang
Keyword(s):  
Compressed Sensing ◽  
Knapsack Problem ◽  
Water Distribution ◽  
Sensor Placement ◽  
Real Life ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Mutual Coherence ◽  
Optimal Sensor Placement ◽  
Leak Localization

Abstract The performance of model-based leak detection and localization techniques heavily depends on the configuration of a limited number of sensors. This paper presents a sensor placement optimization strategy that guarantees sufficient diagnosability while satisfying the budget constraint. Based on the theory of compressed sensing, the leak localization problem could be transformed into acquiring the sparse leak-induced demands from the available measurements, and the average mutual coherence is devised as a diagnosability criterion for evaluating whether the measurements contain enough information for identifying the potential leaks. The optimal sensor placement problem is then reformulated as a {0, 1} quadratic knapsack problem, seeking an optimal sensor placement scheme by minimizing the average mutual coherence to maximize the degree of diagnosability. To effectively handle the complicated real-life water distribution networks, a validated binary version of artificial bee colony algorithm enhanced by genetic operators, including crossover and swap, is introduced to solve the binary knapsack problem. The proposed strategy is illustrated and validated through a real-life water distribution network with synthetically generated field data.

scholarly journals LINGUISTIC ASPECTS OF «UNNATURAL» NARRATOLOGY: THE IMAGE OF A NON-EXISTENT TEXT AUTHOR

2019 ◽  
pp. 17-30
Author(s):  
Florij Batsevych
Keyword(s):  
Real Life ◽  
The Body ◽  
Narrative Strategies ◽  
Story Telling ◽  
Narrative Approaches ◽  
Linguistic Pragmatics ◽  
Unnatural Narratology ◽  
Speech Genre ◽  
Points Of View ◽  
Special Points

The article tries to implement the methods of the so-called «unnatural» narratology to analyse the texts of the collection of short stories «Absolute Emptiness» («Doskonała prόżnia»), which is a set of reviews on non-existent texts. In story-telling structures of this kind, an author usually forms and a reader usually cognitively processes: (a) new types of these structures (schemes), which are not generated in non-estranged texts; (b) new narrative strategies, in particular, the reference part of the textual story may contain actors impossible to be met in «usual» texts; (c) narrative approaches to the formation and evaluation of story-telling structures where there are objects, persons, etc. absent in the real life; (d) means of «restoring» the images of the non-existent authors in the «body» of other texts (in particular, paratexts similar to reviews). The article proves that literary narratives that reflect the non-existent texts demand additional cognitive efforts from an addressee to perceive the communicative senses generated in them. The most important source of such senses creation is a specific logic of the world perception and its reflection, which is non-characteristic to the «classical» speech genre of a review. In view of linguistic pragmatics, these texts actualize special points of view, empathy, and means of their focus. The author’s standpoint about the non-existent text and its reconstruction in paratexts form a shifted focus of empathy, and, what is more, generate non-usual communicative senses, the perception of which demands additional cognitive and psychological efforts from the addressee (a reader, a listener).

On the Estimation of Failure Rates of Multiple Pipeline Systems

2006 ◽  
Author(s):  
F. Caleyo ◽  
L. Alfonso ◽  
J. A. Alca´ntara ◽  
J. M. Hallen ◽  
F. Ferna´ndez Lagos ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Oil And Gas ◽  
Statistical Tests ◽  
Real Life ◽  
Intensity Function ◽  
Model Parameters ◽  
Repairable Systems ◽  
Failure Data ◽  
Pipeline Systems ◽  
Failure Intensity

In this work, the statistical methods for the reliability of repairable systems have been used to produce a methodology capable to estimate the annualized failure rate of a pipeline population from the historical failure data of multiple pipelines systems. The proposed methodology provides point and interval estimators of the parameters of the failure intensity function for two of the most commonly applied stochastic models; the homogeneous Poisson process and the power law process. It also provides statistical tests to assess the adequacy of the stochastic model assumed for each system and to test whether all systems have the same model parameters. In this way, the failure data of multiple pipeline systems are only pooled to produce a generic failure intensity function when all systems follow the same stochastic model. This allows addressing both statistical and tolerance uncertainty adequately. The proposed methodology is outlined and illustrated using real life failure data of multiple oil and gas pipeline systems.

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