Universiti Teknologi Malaysia Institutional Repository

Design optimisation of electrostatic sensor electrodes via MOPSO

Heydarianasl, M. and Rahmat, M. F. (2020) Design optimisation of electrostatic sensor electrodes via MOPSO. Measurement: Journal of the International Measurement Confederation, 152 . ISSN 0263-2241

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Official URL: http://dx.doi.org/10.1016/j.measurement.2019.10728...

Abstract

An ideal electrostatic sensor with optimized electrodes is required for solid particles (SPs) velocity determination. The simplicity and reliability of the multi-objective particle swarm optimization (MOPSO) imparted further impetus to the accurate determination of SPs velocity using electrostatic sensors. This paper reports a new design of electrostatic sensors via MOPSO, where the sensors geometry is determined using response surface methodology (RSM). Besides, electrode sensing factors including spatial sensitivity and statistical error of electrostatic sensors are considered for the optimization. Parameters such as electrode dimensions, velocity, and distribution of particles in the pipeline are found to greatly influence the electrodes sensing performance. Electrodes with different physical sizes were applied to find their optimal value to attain minimum statistical error and maximum spatial sensitivity, which were optimization targets. Following RSM and MOPSO methods, an electrode's optimum length of 0.6 cm and thickness of 0.5 cm has been achieved. It is established that the electrodes spatial sensitivity distribution appears uniform due to their size optimization. Furthermore, very thin electrodes with short length are determined to be prerequisite for sensitivity enhancement. Present study finds a theoretical basis for the electrostatic electrodes optimal design.

Item Type:Article
Uncontrolled Keywords:design optimization, electrodes, electrostatic sensor
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:93699
Deposited By: Narimah Nawil
Deposited On:31 Dec 2021 08:28
Last Modified:31 Dec 2021 08:28

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