TY - GEN
T1 - Leakage detection and location of compressible flow in a pipeline
AU - Adair, Desmond
AU - Emara-Shabaik, Hosam E.
AU - Jaeger, Martin
PY - 2014/1/1
Y1 - 2014/1/1
N2 - A methodology for pipeline leakage detection, together with isolating the size of the leak and the leakage location, using an evidential reasoning based approach is presented. Leakage in pipes produces two major effects, a change in the difference between inlet flow and outlet flow, and, an average pressure change over time. Each of these changes, although in reality coupled, can be thought of as providing two independent bodies of evidence (typically incomplete and non-specific) which can give hints of the occurance of a leak. Inference using traditional Bayesian analysis involves assumptions in cases of incomplete information and partial ignorance. Evidential reasoning, also called the Dempster-Shafer (DS) theory, has proved very useful for such situations and has the ability to incorporate both aleatory and epistemic uncertainities in the inference mechanism. The bodies of evidence from the changes mentioned above are mapped over a 'frame of discernment' of risk of leakage and subsequently the DS rule of combination is applied to make an inference on the occurence, size and location of a leak. What is described below is a novel methodology as to how a system based on the evidential reasoning approach may be trained to detect and locate leaks in compressible flow in a pipeline. The evidential reasoning based approach is trained off-line with the results encouraging.
AB - A methodology for pipeline leakage detection, together with isolating the size of the leak and the leakage location, using an evidential reasoning based approach is presented. Leakage in pipes produces two major effects, a change in the difference between inlet flow and outlet flow, and, an average pressure change over time. Each of these changes, although in reality coupled, can be thought of as providing two independent bodies of evidence (typically incomplete and non-specific) which can give hints of the occurance of a leak. Inference using traditional Bayesian analysis involves assumptions in cases of incomplete information and partial ignorance. Evidential reasoning, also called the Dempster-Shafer (DS) theory, has proved very useful for such situations and has the ability to incorporate both aleatory and epistemic uncertainities in the inference mechanism. The bodies of evidence from the changes mentioned above are mapped over a 'frame of discernment' of risk of leakage and subsequently the DS rule of combination is applied to make an inference on the occurence, size and location of a leak. What is described below is a novel methodology as to how a system based on the evidential reasoning approach may be trained to detect and locate leaks in compressible flow in a pipeline. The evidential reasoning based approach is trained off-line with the results encouraging.
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U2 - 10.1115/IPC201433026
DO - 10.1115/IPC201433026
M3 - Conference contribution
AN - SCOPUS:84918572332
T3 - Proceedings of the Biennial International Pipeline Conference, IPC
BT - Design and Construction; Environment; Pipeline Automation and Measurement
PB - American Society of Mechanical Engineers (ASME)
T2 - 2014 10th International Pipeline Conference, IPC 2014
Y2 - 29 September 2014 through 3 October 2014
ER -