International Journal of Advances in Scientific Research and Engineering-IJASRE

On-Line non-intrusive Monitoring of Particulate Solid Materials in Gas Flowlines Using Acoustic Sensor and ML Techniques

Article Category: Engineering Technology

DOI: 10.31695/IJASRE.2019.33670

Pages: 185-192

Author: Kuda Tijjani Aminu ,Don McGlinchey

Abstract: This paper describes initial steps towards developing a real-time quantitative particulate solids’ (sand) monitoring system for Multiphase flowlines based on acoustic monitoring and machine learning techniques. The concentration and the velocity of the solids were varied during experimental trials. A conventional contact microphone mounted externally to a production flowline bend was used for recording the emitted acoustic signal. Features extracted from the signal were used as input to Time Delay Neural Network (TDNN) with solids concentration and velocity label to a training set. The TDNN achieved low values of normalized root mean square error (NRMSE) for all the models compared to the classical neural network.

Keyword: Multiphase flow, Acoustic Monitoring, Machine Learning, Signal processing, Condition Monitoring.

This work is licensed under a Creative Commons Attribution 4.0 (International) Licence. (CC BY-NC 4.0)
Copyright © 2018 IJASRE All Rights Reserved

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