Classification of chemical compounds using a multisensory system (electronic nose), developed on a hardware device (FPGA)
DOI:
https://doi.org/10.38017/2390058X.119Keywords:
multisensory systems, neural networks, gas sensors, VHDL, FPGAAbstract
In multisensory systems specifically for the operation of the current electronic noses, the computer is the most widely used for the processing and classification of data from an array of chemical gas sensors. The main objective of this study is to replace the usual computer by using a hardware device, in order to obtain a system that is more portable and provides results in real time through the acquisition, processing and samples classification. In developing the system, the design of an algorithm in VHDL (Very High Speed Integrated Circuit - Hardware Description Language) to be implemented in a FPGA (Field Programmable Gate Array) Spartan 3E was performed. The results were as expected, since the module developed different experimental tests on both a computer and the FPGA is performed, obtaining a classification rate of 100% success.
Author Biographies
Oscar Eduardo Gualdrón Guerrero, Universidad de Pamplona
Cristhian Manuel Durán Acevedo, Universidad de Pamplona
José Antonio Araque Gallardo, Universidad de Pamplona
Jesús Eduardo Ortiz Sandoval, Universidad de Pamplona
References
[1] M. Holmberg, F. Winquist, I. Lundström, F. Davide, C. DiNatale, A. D’Amico, "Drift counteraction for an electronic nose", Sensors and Actuators B: Chemical, vol. 36, no. 1-3, pp. 528-535, octubre de 1996. doi: https://doi.org/10.1016/S0925-4005(97)80124-4
[2] J. Rodríguez and C. Durán, "Sistema de olfato electrónico para la detección de compuestos volátiles", Revista Colombiana de Tecnologías de Avanzada. vol. 2, no. 12, 2008, pp. 20-26. [En línea]. Disponible en: https://www.unipamplona.edu.co/unipamplona/portalIG/home_40/recursos/02_v07_12/revista_12/16112011/v12_04.pdf
[3] C. Durán. O. Gualdrón and L. Rojas, "Sistema de olfato electrónico de bajo costo para la detección de diferentes compuestos químicos contaminantes", Revista Colombiana de Tecnologías de Avanzada, Vol. 1, No. 17, 2011, pp. 121-126. [En línea]. Disponible en: https://www.unipamplona.edu.co/unipamplona/portalIG/home_40/recursos/03_v13_18/revista_17/03122011/18.pdf
[4] M. Basualdo, D. Matich and C. Ruiz, Redes neuronales artificiales y sus aplicaciones, Universidad Tecnológica Nacional, Facultad Regional Rosario, Departamento de Ingeniería Química, 2001, marzo, pp. 55. [En línea]. Disponible en: https://www.frro.utn.edu.ar/repositorio/catedras/quimica/5_anio/orientadora1/monograias/matich-redesneuronales.pdf
[5] J.W. Gardner, P. Bartlett, "Performance definition and standardization of electronic noses", Sensors and Actuators B: Chemical, vol. 33, no. 1–3, 1996, pp. 60-67, julio de 1996. doi: https://doi.org/10.1016/0925-4005(96)01819-9
[6] V. Pedroni, Circuit Design with VHDL, MIT Press, ed. 2nd, 2004, pp. 17-19. [En línea]. Disponible en http://www.pld.ttu.ee/~alsu/Pedroni_2010_Circuit%20Design%20and%20Simulation%20with%20VHDL.pdf
[7] R. Khalil and S. A. Kazzaz, Digital Hardware Implementation of Artificial Neuron Model Using FPGA, Department of Electrical Engineering, University of Mosul, Mosul, Iraq, 2008, diciembre, pp. 12-24. [En línea]. Disponible en https://rengj.mosuljournals.com/pdf_38764_d3b8e5f57cd6fd55752d5cee3b7be404.html.
How to Cite
Downloads
Downloads
Published
Issue
Section
License
Copyright (c) 2013 Ciencia, Innovación y Tecnología
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
