Investigation of data augmentation techniques for ultrasonic acoustic fiber sensing signals in guided wave-based pipeline damage detection

Pengdi Zhang; Khurram Naeem; Enrico Sarcinelli; Abhishek Venketeswaran; Sandeep R. Bukka; Nageswara Lalam; Ruishu F. Wright; Paul R. Ohodnicki

doi:10.1117/12.3013996

10 June 2024 Investigation of data augmentation techniques for ultrasonic acoustic fiber sensing signals in guided wave-based pipeline damage detection

Pengdi Zhang, Khurram Naeem, Enrico Sarcinelli, Abhishek Venketeswaran, Sandeep R. Bukka, Nageswara Lalam, Ruishu F. Wright, Paul R. Ohodnicki

Author Affiliations +

Proceedings Volume 13044, Optical Waveguide and Laser Sensors III; 130440J (2024) https://doi.org/10.1117/12.3013996
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

This paper examines the efficacy of quasi-distributed acoustic sensors (q-DAS) in identifying damage within pipeline structures, placing a substantial emphasis on generating synthetic q-DAS measurements in active ultrasonic testing setting and bridging the gap between synthetic and real q-DAS measurements. Our research utilizes simulation software to model the ultrasonic guided wave propagation and its interaction with pipeline defects. The pipeline structural health monitoring setup is based on the pulse-echo method utilizing a torsional symmetric mode T(0,1) at 32kHz, with an aim to identify corrosion and weld irregularities over extensive pipeline lengths. We have prioritized the calibration of simulation models against experimental data, fine-tuning the simulation processes to reflect actual conditions with higher fidelity. The study specifically highlights the simulation’s accuracy in capturing the distinct signatures of critical pipeline features and the subsequent detection capabilities within an operational context. By focusing on the experimental validation, we have advanced the understanding and application of structural health monitoring for essential infrastructure, ensuring the simulations' predictive strength aligns closely with real-world sensor data and observed phenomena.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Pengdi Zhang, Khurram Naeem, Enrico Sarcinelli, Abhishek Venketeswaran, Sandeep R. Bukka, Nageswara Lalam, Ruishu F. Wright, and Paul R. Ohodnicki "Investigation of data augmentation techniques for ultrasonic acoustic fiber sensing signals in guided wave-based pipeline damage detection", Proc. SPIE 13044, Optical Waveguide and Laser Sensors III, 130440J (10 June 2024); https://doi.org/10.1117/12.3013996

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