A NEW METHOD TO OPTIMIZE GEOMETRIC DESIGN OF ELECTROSTATIC SENSOR ELECTRODES USING PARTICLE SWARM OPTIMIZATION

Authors

  • Mozhde Heydarianasl Department of Control and Mechatronics Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Mohd Fua’ad Rahmat Department of Control and Mechatronics Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v78.9423

Keywords:

Electrostatic sensors, spatial sensitivity, velocity measurement, particle swarm optimization, electrode design

Abstract

Optimization of electrostatic sensor electrodes plays a significant role to achieve more homogenous spatial sensitivity. Particle swarm optimization (PSO) is a simple method that has attracted many attentions in recent years. In this paper, the physical sizes of several electrodes for electrostatic sensors are optimized using the PSO technique. Spatial sensitivity of electrode is considered as objective function in this method. Additionally, the thickness and length of electrode are described as physical characteristics of electrode, which need to be optimized. In order to verify this optimization method, different electrodes are applied in laboratory. The optimal value of thickness and length of electrode according to the optimization and experimentation are 5mm and 6mm, respectively. As a result, there is a great agreement between the optimization and experimental results.

References

Krabicka, J. and Y. Yan. 2007 Finite Element Modelling Of Intrusive Electrostatic Sensors For The Measurement Of Pulverised Fuel Flows. In Instrumentation and Measurement Technology Conference Proceedings, 2007. IMTC 2007. IEEE. 2007. IEEE.

Yan, Y. 1996. Mass Flow Measurement of Bulk Solids in Pneumatic Pipelines. Measurement Science and Technology. 7(12): 1687.

Shao, J., J. Krabicka, and Y. Yan. 2010. Velocity Measurement of Pneumatically Conveyed Particles using Intrusive Electrostatic Sensors. Instrumentation and Measurement, IEEE Transactions on. 59(5): 1477-1484.

Zhang, J., H. Hu, J. Dong, Y. Yan. 2012. Concentration Measurement of Biomass/Coal/Air Three-Phase Flow by Integrating Electrostatic and Capacitive Sensors. Flow Measurement and Instrumentation. 24: 43-49.

Xu, C., G. Tang, B. Zhou, and Sh. Wang. 2009. The Spatial Filtering Method for Solid Particle Velocity Measurement Based on an Electrostatic Sensor. Measurement Science and Technology. 20(4): 045404.

Kennedy, J. and R.C. Eberhart. 1997. A Discrete Binary Version of the Particle Swarm Algorithm. in Systems, Man, and Cybernetics. Computational Cybernetics and Simulation., 1997 IEEE International Conference on. 1997. IEEE.

Kennedy, J. and R. Mendes. 2002. Population Structure And Particle Swarm Performance. Proceedings of the Congress on Evolutionary Computation 2002. IEEE.

Kennedy, J. 2010. Particle Swarm Optimization. Encyclopedia of Machine Learning. Springer. 760-766.

Ishaque, K., Z. Salam, M. Amjad, and S. Mekhilef. 2012. An improved Particle Swarm Optimization (PSO)–based MPPT for PV With Reduced Steady-State Oscillation. Power Electronics, IEEE Transactions on, 2012. 27(8): 3627-3638.

Qian, X., X. Cheng, L. Zhang, and M. Cao. 2011. The Sensitivity Analysis and Optimization Design of the Electrostatic Inductive Measuring Device for Weak Charge Measurement of Coal Mine Dust. Computer Science for Environmental Engineering and EcoInformatics. Springer. 83-90.

Xu, C., Sh. Wang, G. Tang, D. Yang, and B. Zhou. 2007. Sensing Characteristics of Electrostatic Inductive Sensor for Flow Parameters Measurement of Pneumatically Conveyed Particles. Journal of Electrostatics. 65(9): 582-592.

Xu, C., S. Wang, and Y. Yan. 2013. Spatial Selectivity of Linear Electrostatic Sensor Arrays For Particle Velocity Measurement. Instrumentation and Measurement, IEEE Transactions on, 2013. 62(1): 167-176.

Krabicka, J. and Y. Yan. 2009. Optimised Design of Intrusive Electrostatic Sensors for the Velocity Measurement of Pneumatically Conveyed Particles. in Instrumentation and Measurement Technology Conference, 2009. I2MTC'09. IEEE. 2009. IEEE.

Krabicka, J. and Y. Yan. 2009. Finite-Element Modeling of Electrostatic Sensors for the Flow Measurement of Particles In Pneumatic Pipelines. Instrumentation and Measurement, IEEE Transactions on, 2009. 58(8): 2730-2736.

Heydarianasl, M. and M. F. A. Rahmat. 2014. The Effects of Distance on Velocity Measurement for Different Shapes of Electrostatic Sensor Electrodes. Jurnal Teknologi. 69(8).

Heydarianasl, M. and M. F. A. Rahmat. 2015. Modelling and Simulation of Different Electrode Size for Electrostatic Sensors. Control Conference (ASCC), 2015 10th Asian. 2015. IEEE.

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Published

2016-07-24

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Section

Science and Engineering

How to Cite

A NEW METHOD TO OPTIMIZE GEOMETRIC DESIGN OF ELECTROSTATIC SENSOR ELECTRODES USING PARTICLE SWARM OPTIMIZATION. (2016). Jurnal Teknologi (Sciences & Engineering), 78(7-4). https://doi.org/10.11113/jt.v78.9423