Leak Detection in Pipelines by the use of State and Parameter Estimation
MasteroppgaveStudent thesisAlternative title
Leak Detection in Pipelines by the use of State and Parameter Estimation (English)
A model based estimation process is implemented in simulation of a transmission
line for the purpose of leak detection. The model has one inlet, one branch and two
outlets. The objective of this thesis is aimed at determining, through simulation results,
the effectiveness of the Kalman Filter for leak detection in a pipeline network.
Water distribution systems often contain a large amount of unknown losses. The
magnitude of the water loss range from 10 to over 50 percent of the total water
pumped. Water leaks and losses lead to an unnecessary increase in energy used
to pump water to users, which means higher costs for the providers and thus the
customers. Our increasing population and the necessity and limited availability of
water will, and are already causing problems, so it is obvious that more control
efforts need to be implemented on these systems. Moreover, leaks that are not considered
to be major faults tend to go unnoticed, which in total add up to a lot of
The work done in this thesis may also be relevant for the petroleum industry, as
transportation of oil and gas also face many of the same problems as the water
distribution industry. One should also note that the environmental impact of leaks
in oil pipes are bigger than those in water pipes.
The leak detection process used in this thesis is model based. A model of a transmission
line with a branch and two outlets is derived from two basic partial differential
equations describing mass and momentum balances for a hydraulic transmission line.
Simulations are run , and when the system is in its steady state, a leak is introduced.
Flow and pressure at all three extremes are used as inputs to the Kalman Filter.
The likelyhood of two leaks occuring simultaneously is low, so only one leak will be
expected at a time.
Localization of the leaks are not studied, only the detecton and the magnitude.
It is shown that a Kalman Filter can be used as a detection method in this system
to a certain degree. The changes caused by the pressure change is noticable when a
leak occurs in a large scale system, even if the leak is very small. The speed of the
Kalman Filter proved to be a problem area, as some of the estimated states used
a long time to reach its final value. More satisfying results may be found through
more rigorous testing, improvements in the model itself, and changes to the tuning
parameters in the Kalman Filter.
Place, publisher, year, edition, pages
Institutt for teknisk kybernetikk , 2014. , 60 p.
ntnudaim:10325, MTTK teknisk kybernetikk og robotikk
IdentifiersURN: urn:nbn:no:ntnu:diva-24457Local ID: ntnudaim:10325OAI: oai:DiVA.org:ntnu-24457DiVA: diva2:710737
Aamo, Ole Morten, Professor