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Dents are among the most encountered types of deformation of buried long-distance pipelines. This paper aims to determine the presence of turbulence flow within the dented spool using frequency domain analysis from acoustic emission response. This is a consideration based on the difficulties in extracting prominent information from acoustic emission signal during an existing dent inspection. The acoustic emission signal responses were obtained during the flow loop test from healthy, 5%, 15% and 30% dented spool to observe the turbulence effect on each dent region. The Fast Fourier Transform (FFT) analysis depicted an increasing trend along the increment of dent percentage with the highest value of 0.00025 mV for 30% dent spool. Moreover, the velocity streamline magnitude of computational fluid simulations was computed to obtain Reynolds number information to validate turbulence detection from acoustic emission responses. The analysis revealed a strong correlation between the FFT and the Reynolds number, as indicated by the coefficient of determination (R2) value of 0.80. Hence, this approach can provide critical information for existing dent detection.

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Detection of Turbulence Effect in Dented Pipeline by Acoustic Emission Response via Frequency Analysis

  • 会议论文

  • 发表日期：

    2026年

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  • Syed Muhamad Firdaus,
  • Mazian Mohammad,
  • Abdul Rahim Othman,
  • Mohd Faridz Mod Yunoh,
  • Naila Rusma Idris,
  • Nur Akmal Hakim Jasni,
  • Koi Swee Ling,
  • Nur Hafizatul Aqma Rusli

摘要

Dents are among the most encountered types of deformation of buried long-distance pipelines. This paper aims to determine the presence of turbulence flow within the dented spool using frequency domain analysis from acoustic emission response. This is a consideration based on the difficulties in extracting prominent information from acoustic emission signal during an existing dent inspection. The acoustic emission signal responses were obtained during the flow loop test from healthy, 5%, 15% and 30% dented spool to observe the turbulence effect on each dent region. The Fast Fourier Transform (FFT) analysis depicted an increasing trend along the increment of dent percentage with the highest value of 0.00025 mV for 30% dent spool. Moreover, the velocity streamline magnitude of computational fluid simulations was computed to obtain Reynolds number information to validate turbulence detection from acoustic emission responses. The analysis revealed a strong correlation between the FFT and the Reynolds number, as indicated by the coefficient of determination (R2) value of 0.80. Hence, this approach can provide critical information for existing dent detection.