Simulation and experimental measurement of acoustic wave reflectometry for leak detection in pipes

Mustapha Abdullahi; S. Olutunde Oyadiji

doi:10.1117/12.2528686

1 April 2019 Simulation and experimental measurement of acoustic wave reflectometry for leak detection in pipes

Proceedings Volume 10972, Health Monitoring of Structural and Biological Systems XIII; 109721S (2019) https://doi.org/10.1117/12.2528686
Event: SPIE Smart Structures + Nondestructive Evaluation, 2019, Denver, Colorado, United States

Abstract

Leakage of oil and gas pipe systems, water pipes and other pipe networks can cause serious environmental, health and economic problems. In order to minimise the damages brought to the environment, human health and the economic issues, rapid non-destructive detection of pipeline leakage is imperative. In recent works, number of non-destructive testing (NDT) methods was used in detecting this defect in pipeline systems such ultrasonic, magnetic particle inspection, pressure transient and acoustic wave methods. In this study, the acoustic wave method and a modal frequency technique are used to detect leakage in pipeline system. Finite element analysis (FEA) was employed to simulate acoustic wave propagation in fluid-filled pipes with leakage. Furthermore, experimental testing was conducted to validate some of the numerical results. The experiment performed consisted of the measurement of acoustic wave propagation in a straight fluid-filled pipe. The FEA analysis of fluidfilled pipe can be used to simulate the acoustic wave propagation and acoustic wave reflectometry of a fluid-filled pipe with leakage of different using the ACAX element in order for accurate predictions. Also, the measured signal of acoustic wave propagation in pipeline from the experiment can be decomposed and de-noised to identify and locate leakages of different sizes.

Citation Download Citation

Mustapha Abdullahi and S. Olutunde Oyadiji "Simulation and experimental measurement of acoustic wave reflectometry for leak detection in pipes", Proc. SPIE 10972, Health Monitoring of Structural and Biological Systems XIII, 109721S (1 April 2019); https://doi.org/10.1117/12.2528686

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