Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification
Author:
Zhang Pengdi1ORCID, Venketeswaran Abhishek1, Wright Ruishu F.2, Lalam Nageswara2, Sarcinelli Enrico1, Ohodnicki Paul R.13ORCID
Affiliation:
1. Mechanical Engineering and Materials Science, University of Pittsburgh, 3700 O’Hara Street, Pittsburgh, PA 15261, USA 2. National Energy Technology Laboratory, 626 Cochrans Mill Road, Pittsburgh, PA 15236, USA 3. Electrical and Computer Engineering, University of Pittsburgh, 3700 O’Hara Street, Pittsburgh, PA 15261, USA
Abstract
This study presents a framework for detecting mechanical damage in pipelines, focusing on generating simulated data and sampling to emulate distributed acoustic sensing (DAS) system responses. The workflow transforms simulated ultrasonic guided wave (UGW) responses into DAS or quasi-DAS system responses to create a physically robust dataset for pipeline event classification, including welds, clips, and corrosion defects. This investigation examines the effects of sensing systems and noise on classification performance, emphasizing the importance of selecting the appropriate sensing system for a specific application. The framework shows the robustness of different sensor number deployments to experimentally relevant noise levels, demonstrating its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage to pipelines by emphasizing the generation and utilization of simulated DAS system responses for pipeline classification efforts. The results on the effects of sensing systems and noise on classification performance further enhance the robustness and reliability of the framework.
Funder
United States Department of Energy Office Advanced Research Projects Agency-Energy (ARPA-E) REPAIR project Nuclear Energy University Program (NEUP) project
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
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