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survey on gas leak detection and localization techniques,” Journal of Loss
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In this
paper, in order to guarantee a suitable water pipeline monitoring in this
project, we have implemented hybrid technique that combines the RTTM method for
real-time leak detection with the wave propagation method for leak
localization. To evaluate the localization method, a location error is
calculated to test the localization accuracy which depends on the distance from
the pipeline inlet. The obtained results are acceptable. However, in the next
work, we will enhance the location accuracy by combining the implemented
localization method with an intelligent algorithm allowing to reinforce its
results and to be certain about the leak position

IV. Conclusion


 The pressure near the valve undergoes a
pressure surge (?P1) as the dynamic pressure of the ?uid converts to
hydrostatic pressure. A positive pressure wave is generated, and travels
upstream along the pipeline. Arriving at the leak point, a sudden drop by ?
value occurs in the pressure. A negative pressure wave is produced and starts
to propagate downstream. A Pressure Recorder (PR) collects the pressure data.

B. Leak Localization approach


2: Water Distribution System



• Leak location: Once the leak is
identi?ed, the WPM is employed to locate the leak point..

 • Leak Detection: RTTM  method: The pressure-?ow pro?le of the
pipeline is calculated based on the measurements of the pipeline inlet and
outlet. Substituting the collected measurements into a mathematical model, the
predicted operating parameters can be evaluated by employing the Method of
Characteristics (MOC) . Preliminary leak detection is considered by comparing
the predicted modelled values to the measured values.

WSNi system is
Responsible for collecting monitored water pressure and ?ow rate parameters by
the use of autonomous sensors. Firstly, the segment i of pipeline is divided
into equal segments and sensor nodes are placed in each segment ends. Then,
hierarchical WSN architecture is implemented where sensors are grouped into
clusters. Each cluster head transmits the data to a Base Station (BSi) which
will be analysed by the RCC to recognize the presence of the leak and its
position. Hybrid method is implemented as following:

The global architecture is
shown in Fig. 1. It is divided into two sub-systems: WSN system and Remote
Control Centre (RCC). For each segment i of the pipeline,


global architecture




Thus, unless
the threshold values are adapted, high false alarm rates will be recorded
during transient periods of the pipeline. Moreover, unless a localization
technique is attached to the method, it cannot localize the actual location of
the leak on its own.

The mass balance method for leak
detection is straightforward (Burgmayer and Durham 2000; Martins and Seleghim
2010). It is based on the principle of mass conservation. The existence of leak
causes an unbalance between the output and input mass ?ow rate as well as the
line pack variable rate (Liou 1996; Parry et al. 1992). This is variable that
de?nes the actual amount of gas in a pipeline or distribution system. A leak
alarm is raised once the difference between the volume of ?uid entering a
section of the pipeline and the volume of the ?uid leaving the section exceeds
some pre-set threshold. (Liu 2008) presented a detailed theory and the
implementation issues that are encountered in this method. In their work, they
further pointed out that the volume or mass can be obtained by using readings
of commonly used process variables such as temperature, pressure and ?ow rate.
(Rougier 2005) presented a hybrid mass balance method, which incorporates
probabilistic method to the mass balance method. The main drawback of this
method is that the probabilistic method requires a substantial amount of
computational power. One of the advantages of the mass balance method however
is the ease with which it can be implemented on existing pipeline infrastructure.
It is also able to rely on existing instrumentation already available on the
pipeline; thus, resulting in low cost implementation (Murvay and Silea 2012;
Wan et al. 2011). However, its performance relies on the size of the leak,
frequency at which balance measurements are obtained as well as on the overall
accuracy of measuring instruments. Another limitation of the mass balance
method is its inability to detect small leak in real-time. Thus, resulting in
loss of signi?cant amount of ?uid before an alarm is raised. A further
limitation is that the mass balance method easily affected by random
disturbances around the pipeline as well as the pipe dynamics.

              This method depends on pipe ?ow
models developed to employing equations such as: conservation of momentum, mass
and energy as well as the equation of state of the ?uid. The presence of
leakage is determined by the estimated value and measured value of the ?ow.
Continuous monitoring noise levels and transient events minimize false alarm
rate. Billmann and Isermann (1987) designed an observer with friction
adaptation that in the event of leakage it generates a different output from
one obtained from measurements. Thus, from this difference leakage can be


Real time transient modelling


II .leak detection

combining the RTTM (Real Time
Monitoring System Method) 4 and the Wave Propagation Method (WPM)  for water leak monitoring and pipe modeling.
The rest of paper is organized as follows: section II reviews the previous
implemented hybrid pipeline leak detection methods. Section III details and
describes the water pipeline model. In section IV, we detail the PLDS
architecture. Section V illustrates the leak detection methodology. Finally,
section VII concludes this paper.

we focus on sensing the continuously
water parameters (pressure and ?ow rate) to detect the presence of the leak and
to locate its position. Thus, the originality of our contribution is to deploy
a hybrid method

distribution is generally installed through underground pipes. Monitoring the
underground water pipelines is more difficult than monitoring the water
pipelines located on the ground in open space. This situation will cause a
permanent loss if there is a disturbance in the pipeline such as leakage. Leaks
in pipes can be caused by several factors, such as the pipe’s age, improper
installation, and natural disasters. Therefore, a solution is required to
detect and to determine the location of the damage when there is a leak.
Wireless Sensor Network (WSN) is considered as a reliable solution for Pipeline
Leak Detection Systems (PLDS) to supervise pipeline and to detect and localize




Keywords—Wireless Sensor Network, Pipeline monitoring, Leak, Hybrid
technique, Detection, Localization,


Abstract— The
monitoring of leaks in pipelines is an important issue to be addressed by
researchers and the public. This is due the fact that they can have a great
impact both economically and environmentally. In recent years, the effect of
leakages of pipelines carrying oil, gas and nuclear ?uids have posed a threat
on humans as well as marine life. This paper provides a survey of recent
methods of detecting pipeline leaks with special focus on Real Time Transient
Modeling and Wave Propagation Method is implemented to detect and locate the
position of the leak in a water pipeline. A mathematical model is carried out
to solve the transient based leak detection model and different scenarios are
developed to estimate the relationship between the pressure ?uctuation and leak
position. The obtained results approve the potentiality of the proposed


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