Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks

This research presents a data-driven structural health monitoring (SHM) approach for pipeline systems that leverages frequency response function (FRF) signals and artificial neural network (ANN) algorithms to accurately identify and classify diverse pipeline fault conditions. The study focuses on th...

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Bibliographic Details

Main Authors:	Hussein, Hussein A. M, Abdul Rahim, Sharafiz, Mustapha, Faizal B., Krishnan, Prajindra S., Abdul Jalil, Nawal Aswan
Format:	Article
Language:	en
Published:	KeAi Communications 2025
Online Access:	http://psasir.upm.edu.my/id/eprint/121594/1/121594.pdf http://psasir.upm.edu.my/id/eprint/121594/ https://www.sciencedirect.com/science/article/pii/S2667143324000507?via%3Dihub
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