Cargando…
Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment
Optimization of the acoustic resonant sensor requires a clear understanding of how the output responses of the sensor are affected by the variation of different factors. During this work, output responses of a capacitive acoustic transducer, such as membrane displacement, quality factor, and capacit...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431226/ https://www.ncbi.nlm.nih.gov/pubmed/25894937 http://dx.doi.org/10.3390/s150408945 |
_version_ | 1782371302589333504 |
---|---|
author | Haque, Rubaiyet Iftekharul Loussert, Christophe Sergent, Michelle Benaben, Patrick Boddaert, Xavier |
author_facet | Haque, Rubaiyet Iftekharul Loussert, Christophe Sergent, Michelle Benaben, Patrick Boddaert, Xavier |
author_sort | Haque, Rubaiyet Iftekharul |
collection | PubMed |
description | Optimization of the acoustic resonant sensor requires a clear understanding of how the output responses of the sensor are affected by the variation of different factors. During this work, output responses of a capacitive acoustic transducer, such as membrane displacement, quality factor, and capacitance variation, are considered to evaluate the sensor design. The six device parameters taken into consideration are membrane radius, backplate radius, cavity height, air gap, membrane tension, and membrane thickness. The effects of factors on the output responses of the transducer are investigated using an integrated methodology that combines numerical simulation and design of experiments (DOE). A series of numerical experiments are conducted to obtain output responses for different combinations of device parameters using finite element methods (FEM). Response surface method is used to identify the significant factors and to develop the empirical models for the output responses. Finally, these results are utilized to calculate the optimum device parameters using multi-criteria optimization with desirability function. Thereafter, the validating experiments are designed and deployed using the numerical simulation to crosscheck the responses. |
format | Online Article Text |
id | pubmed-4431226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-44312262015-05-19 Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment Haque, Rubaiyet Iftekharul Loussert, Christophe Sergent, Michelle Benaben, Patrick Boddaert, Xavier Sensors (Basel) Article Optimization of the acoustic resonant sensor requires a clear understanding of how the output responses of the sensor are affected by the variation of different factors. During this work, output responses of a capacitive acoustic transducer, such as membrane displacement, quality factor, and capacitance variation, are considered to evaluate the sensor design. The six device parameters taken into consideration are membrane radius, backplate radius, cavity height, air gap, membrane tension, and membrane thickness. The effects of factors on the output responses of the transducer are investigated using an integrated methodology that combines numerical simulation and design of experiments (DOE). A series of numerical experiments are conducted to obtain output responses for different combinations of device parameters using finite element methods (FEM). Response surface method is used to identify the significant factors and to develop the empirical models for the output responses. Finally, these results are utilized to calculate the optimum device parameters using multi-criteria optimization with desirability function. Thereafter, the validating experiments are designed and deployed using the numerical simulation to crosscheck the responses. MDPI 2015-04-16 /pmc/articles/PMC4431226/ /pubmed/25894937 http://dx.doi.org/10.3390/s150408945 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Haque, Rubaiyet Iftekharul Loussert, Christophe Sergent, Michelle Benaben, Patrick Boddaert, Xavier Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment |
title | Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment |
title_full | Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment |
title_fullStr | Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment |
title_full_unstemmed | Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment |
title_short | Optimization of Capacitive Acoustic Resonant Sensor Using Numerical Simulation and Design of Experiment |
title_sort | optimization of capacitive acoustic resonant sensor using numerical simulation and design of experiment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431226/ https://www.ncbi.nlm.nih.gov/pubmed/25894937 http://dx.doi.org/10.3390/s150408945 |
work_keys_str_mv | AT haquerubaiyetiftekharul optimizationofcapacitiveacousticresonantsensorusingnumericalsimulationanddesignofexperiment AT loussertchristophe optimizationofcapacitiveacousticresonantsensorusingnumericalsimulationanddesignofexperiment AT sergentmichelle optimizationofcapacitiveacousticresonantsensorusingnumericalsimulationanddesignofexperiment AT benabenpatrick optimizationofcapacitiveacousticresonantsensorusingnumericalsimulationanddesignofexperiment AT boddaertxavier optimizationofcapacitiveacousticresonantsensorusingnumericalsimulationanddesignofexperiment |