Articles producció científica> Enginyeria Electrònica, Elèctrica i Automàtica

A new approach to NO2 Gas sensing based on Pulsed UV light and FFT analysis using MOX sensors

  • Datos identificativos

    Identificador: imarina:5894946
    Handle: http://hdl.handle.net/20.500.11797/imarina5894946
  • Autores:

    Gonzalez E, Llobet E, Romero A, Vilanova X
  • Otros:

    Autor según el artículo: Gonzalez E, Llobet E, Romero A, Vilanova X
    Departamento: Enginyeria Electrònica, Elèctrica i Automàtica
    Autor/es de la URV: Gonzalez Fernandez, Ernesto / Llobet Valero, Eduard / Romero Nevado, Alfonso José / Vilanova Salas, Javier
    Palabras clave: Pulsed uv light Gas sensing Chemical sensor Calibration model
    Resumen: © 2001-2012 IEEE. Metal Oxide Semiconductor gas sensors have been recently temperature modulated, and UV light activated to improve their sensitivity and selectivity. In this work, we present the first known development of calibration models, using pulsed UV light modulation for WO 3 based gas sensing. Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR) methods have been developed using components from the FFT analysis of the DC resistance signal of the sensor. The use of pulsed UV light, combined with low-temperature activation allowed a significant reduction in power consumption as compared to the high operating temperature traditionally used with Metal Oxide non-MEMs-based sensors. The methodology proposed in this study allows diminishing the time necessary to determine the concentration, with the reduction of the pulsed UV light period, and the number of pulses used for this purpose, in respect to the use of resistance rate analysis, as proposed by other authors. The FFT analysis made before performing the linear regression methods allows the diminution of the prediction error from the models, as compared to the rate analysis. These advantages present a progress over the analysis of the rates from the resistance signal, recently presented by other authors. The correct performance of the presented procedure, working with NO 2 concentrations under harmful exposure limits, opens the opportunity of using this methodology in real air quality applications.
    Áreas temáticas: Química Physics, applied Nutrição Medicina veterinaria Medicina ii Materiais Matemática / probabilidade e estatística Interdisciplinar Instruments & instrumentation Instrumentation Engineering, electrical & electronic Engenharias iv Engenharias iii Engenharias ii Engenharias i Electrical and electronic engineering Ciências biológicas ii Ciências biológicas i Ciência da computação Biotecnología Astronomia / física
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1530-437X
    Direcció de correo del autor: alfonsojose.romero@urv.cat xavier.vilanova@urv.cat eduard.llobet@urv.cat
    Identificador del autor: 0000-0003-3502-0813 0000-0002-6245-7933 0000-0001-6164-4342
    Fecha de alta del registro: 2023-02-18
    Volumen de revista: 20
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://ieeexplore.ieee.org/document/8844733
    URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Ieee Sensors Journal. 20 (1): 397-404
    Referencia de l'ítem segons les normes APA: Gonzalez E, Llobet E, Romero A, Vilanova X (2020). A new approach to NO2 Gas sensing based on Pulsed UV light and FFT analysis using MOX sensors. Ieee Sensors Journal, 20(1), 397-404. DOI: 10.1109/JSEN.2019.2942490
    DOI del artículo: 10.1109/JSEN.2019.2942490
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2020
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Electrical and Electronic Engineering,Engineering, Electrical & Electronic,Instrumentation,Instruments & Instrumentation,Physics, Applied
    Pulsed uv light
    Gas sensing
    Chemical sensor
    Calibration model
    Química
    Physics, applied
    Nutrição
    Medicina veterinaria
    Medicina ii
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    Instruments & instrumentation
    Instrumentation
    Engineering, electrical & electronic
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Electrical and electronic engineering
    Ciências biológicas ii
    Ciências biológicas i
    Ciência da computação
    Biotecnología
    Astronomia / física
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