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Dimensionality Reduction and Pattern Recognition of Flow Regime Using Acoustic Data

Vahabi, N; Selviah, DR; (2018) Dimensionality Reduction and Pattern Recognition of Flow Regime Using Acoustic Data. In: Arai, K and Kapoor, S and Bhatia, R, (eds.) Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2. (pp. pp. 880-891). Springer: Cham, Switzerland. Green open access

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Abstract

In this study we investigated the novel application of Principal Component Analysis (PCA) in order to reduce the dimensionality of acoustic data. The acoustic data are recorded by fibre optic distributed acoustic sensors which are attached along a 3500 m pipe with a sampling frequency of 10 kHz and for a duration of 24 hours. Data collected from distributed acoustic sensors are very large and we need to identify the part that contains the most informative signals. The algorithm is applied to water, oil and gas datasets. We aimed to form a smaller dataset which preserves the pattern of the original dataset which is more efficient for further analysis. The result of this study will lead to automation of multiphase flow pattern recognition for oil and gas industry applications.

Type: Proceedings paper
Title: Dimensionality Reduction and Pattern Recognition of Flow Regime Using Acoustic Data
Event: 2018 Intelligent Systems Conference (IntelliSys)
Location: London, Uk
Dates: 06 September 2018 - 07 September 2018
ISBN-13: 978-3-030-01056-0
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-01057-7_65
Publisher version: https://doi.org/10.1007/978-3-030-01057-7_65
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Feature extraction, Principle component analysis (PCA), Signal processing, Dimension reduction
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10043440
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