Neural Network Observer Based Leak Detection and Localization System for Oil Transporting Pipelines
Abdelelah Kidher Mahmood1, Mohammed Mahmood Abdulaal2
1Abdelelah Kidher Mahmood, Electrical Engineering Dept, University of Mosul, College of Engineering, Mosul, Iraq.
2Mohammed Mahmood Abdulaal, Electrical Engineering Dept, University of Mosul, College of Engineering, Saladin, Iraq.
Manuscript received on September 26, 2013. | Revised Manuscript received on October 10, 2013. | Manuscript published on October 30, 2013. | PP: 221-224 | Volume-3, Issue-1, October 2013. | Retrieval Number : A2222103113/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper considered with the design of two leak detection and localization systems in oil transporting pipeline. The first one based on mass balance principles and second one based on pressure gradient intersection. The main distinction of the both methods, thy have an intelligent observer structured by artificial neural network. Every system has been tested individually, and satisfactory results have been obtained with accurate and good performance. These methods collected together to work in parallel implementing a combined system, this system gives better performance and reduce the false alarm level.
Keywords: Intelligent observer, LDS, Leak detection and localization, Leakage classifier, Neural network observer, Oil transporting pipeline.