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Revelando la dinámica del estrés inducida por la turbulencia en tuberías abolladas mediante emisión acústica y
Syed Muhamad Firdaus1, Mazian Mohammad1,2, Abdul Rahim Othman1,2
1Institute of Sustainable Energy & Resources (ISER), Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Abstract:
Dents are among the most common deformation defects in buried transmission pipelines, significantly influencing structural integrity and internal flow behaviour. This study examines the occurrence of turbulence in dented pipe sections using time-frequency analysis of acoustic emission (AE) responses. The approach aims to overcome the challenge of obtaining meaningful information from AE signals during conventional dent inspections. By correlating AE spectral characteristics with flow-induced turbulence, the study provides insights into how mechanical deformation influences AE signal behaviour, contributing to an improved assessment of pipeline integrity. In this study, AE signals were captured during flow loop tests on healthy, 5%, 15%, and 30% dented pipe sections to evaluate the influence of dent severity on turbulence behaviour. Time-frequency domain analysis using the Morlet wavelet transform on the starting, middle, and end segments of AE signals revealed a progressive increase in signal energy with increasing dent depth, reaching a maximum of 2.54 × 10-08 μE2/Hz - 2.54 × 10-08 μE2/Hz for the end segment of AE signals under the 30% dented pipe condition. Complementary computational fluid dynamics (CFD) simulations were performed to compute velocity streamlines and corresponding Reynolds numbers for validating the turbulence detection results. A strong correlation between the CWT coefficient energy and Reynolds number, with R2 values of 0.9633, 0.9007, and 0.9052 for the starting, middle, and end signal segments, respectively, was observed. These findings demonstrate that AE time-frequency analysis offers a reliable diagnostic approach for identifying and characterising dent-induced turbulence in pipeline systems.
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