Approximation of a multivariable sensor characteristic applied to the carbon monoxide sensor

Janiczek, J.

doi:10.1016/j.measurement.2010.04.009

“…A theoretical method for polynomial approximation of a multivariable sensor characteristic was proposed in [18]. In its practical application only the compensation of the impact of humidity, RH, on gas sensor characteristics is shown.…”

Section: Figurementioning

confidence: 99%

Compensation of the Impact of Disturbing Factors on Gas Sensor Characteristics

2013

APH

0

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Methods for gas control have been extensively developed for the monitoring of air quality, for gas leak control, for the development of 'electronic nose' systems, etc. Metal oxide gas sensors have been widely used in particular. However, apart from changes in the controlled gas concentration, changes in their parameters also depend on ambient conditions. The main impact comes from temperature and humidity. Therefore, the compensation of these disturbances is important for increasing the accuracy of concentration measurements of the controlled gases and the reliability of control. The present paper proposes a method for compensating the impact of temperature and humidity on gas sensor characteristics using artificial neural networks. This compensation method is applied to the control of methane concentration by gas sensors TGS813 and TGS2611. The results obtained confirm the applicability of this method.

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Gas Recognition Using Artificial Neural Networks

Nodirbek,

Shukhrat,

Ulugbek

et al. 2024

Lecture Notes in Networks and Systems

0

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Compensation of the Impact of Disturbing Factors on Gas Sensor Characteristics

Nenova¹,

Dimchev²

2013

ACTA POLYTECH HUNG

19

0

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Methods for gas control have been extensively developed for the monitoring of air quality, for gas leak control, for the development of 'electronic nose' systems, etc. Metal oxide gas sensors have been widely used in particular. However, apart from changes in the controlled gas concentration, changes in their parameters also depend on ambient conditions. The main impact comes from temperature and humidity. Therefore, the compensation of these disturbances is important for increasing the accuracy of concentration measurements of the controlled gases and the reliability of control. The present paper proposes a method for compensating the impact of temperature and humidity on gas sensor characteristics using artificial neural networks. This compensation method is applied to the control of methane concentration by gas sensors TGS813 and TGS2611. The results obtained confirm the applicability of this method.

show abstract

Approximation of a multivariable sensor characteristic applied to the carbon monoxide sensor

Cited by 3 publications

References 8 publications

Compensation of the Impact of Disturbing Factors on Gas Sensor Characteristics

Compensation of the Impact of Disturbing Factors on Gas Sensor Characteristics

Gas Recognition Using Artificial Neural Networks

Compensation of the Impact of Disturbing Factors on Gas Sensor Characteristics

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