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Neural-Network-Based Sensor Data Fusion for Multi-Hole Fluid Velocity Probes

Ghosh, Anindya, Birch, David and Marxen, Olaf (2020) Neural-Network-Based Sensor Data Fusion for Multi-Hole Fluid Velocity Probes IEEE Sensors Journal, 20 (10). pp. 5398-5405.

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For measuring three components of velocity in unknown flow fields, multi-hole pressure probes possess a significant advantage. Unlike methods such as hot-wire anemometry, laser-Doppler velocimetry and particle-image velocimetry, multi-hole pressure probes can provide not only the three components of local velocity, but also static and stagnation pressures. However, multi-hole probes do require exhaustive calibration. The traditional technique for calibrating these probes is based on either look-up tables or polynomial curve fitting, but with the low cost and easy availability of powerful computing resources, neural networks are increasingly being used. Here, we explore the possibility to further reduce measurement uncertainty by implementing neural-network-based methods that have not been previously used for probe calibration, including supervised and unsupervised learning neural networks, regression models and elastic-map methods. We demonstrate that calibrating probes in this way can reduce the uncertainty in flow angularity by as much as 50% compared to conventional techniques.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
Ghosh, Anindya
Date : 15 May 2020
DOI : 10.1109/JSEN.2020.2969286
Copyright Disclaimer : © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Sensor fusion; Fluid flow measurement; Calibration; Probes; Temperature sensors; Temperature measurement; Temperature distribution
Depositing User : James Marshall
Date Deposited : 05 Mar 2020 14:34
Last Modified : 01 Jun 2020 13:19

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