A model-based estimation process is implemented in simulation of a water transmission line for the purpose of leak detection. The objective of this thesis is aimed at determining, through simulation results, the effectiveness of the Extended Kalman Filter for leak detection.
Water distribution systems often contain large amounts of unknown losses. The range in magnitude of losses varies from 10 to over 50 percent of the total volume of water pumped. The result is a loss of product, including water and the chemicals used to treat it, environmental damage, demand shortfalls, increased energy usage and unneeded pump capacity expansions. It is clear that more control efforts need to be implemented on these systems to reduce losses and increase energy efficiencies. The problems of demand shortfalls, resulting from lost product, are worsened by the limited availability of water resources and a growing population and economy. The repair of leakage zones as they occur is not a simple problem since the vast majority of leaks, not considered to be major faults, go undetected.
The leak detection process described in the work of this thesis is model based. A transient model of a transmission line is developed using the Method of Characteristics. This method provides the most accurate results of all finite-difference solutions to the two partial differential equations of continuity and momentum that describe pipe flow. Simulations are run with leakage within the system and small transients are added as random perturbations in the upstream reservoir head. The head measurements at the two pipe extremes are used as inputs into the filter estimation process.
The Extended Kalman Filter is used for state estimation of leakage within the transmission line. The filter model places two artificial leakage states within the system. The estimates of these fictitious leakage states are then used to locate the actual position and magnitude of leakage within the transmission line. This method is capable of locating one leak within the line.
The results of the Extended Kalman Filter (EKF) process show that it is capable of locating the position and magnitude of small leaks within the line. It was concluded that the EKF could be used for leak detection, but field tests need to be done to better quantify the ability of these methods. It is recommended that a multiple filtering method be implemented that may be able to locate the occurrence of multiple leakage.
| Identifer | oai:union.ndltd.org:USASK/oai:usask.ca:etd-03242005-110841 |
| Date | 04 April 2005 |
| Creators | Lesyshen, Ryan M |
| Contributors | Zhang, W. J. (Chris), Sumner, David, Putz, Gordon, Habibi, Saeid R., Burton, Richard T. |
| Publisher | University of Saskatchewan |
| Source Sets | University of Saskatchewan Library |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://library.usask.ca/theses/available/etd-03242005-110841/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Saskatchewan or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
Page generated in 0.0029 seconds