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A Comparison of the Multivariate Calibration Methods with Feature Selection for Gas Sensors’ Long‐Term Drift Effect

Year 2019, Volume: 11 Issue: 3, 170 - 176, 30.12.2019

Abstract

In many electronic nose applications where gas sensors utilizing for a
long time, there is an undesirable drift effect on the sensors, which affects the
classification quality negatively. Although the sensor drift is inevitable, it is
possible to reduce this effect with the calibration transfer methods. This paper
presents a comparison study of various multivariate standardization methods to
facilitate an effective calibration way on a comprehensive dataset, which is
reachable on‐line. In this study, three methods applied: direct standardization (DS)
orthogonal signal correction (OSC) and piecewise direct standardization (PDS). In
addition, these three methods are applied data, which consisted of selected
features. The results have shown that the classification success has increased with
multivariate calibration technique applied to the selected features. The results also
demonstrate that using the best features in the signal processing part can play an
important role for the calibration

References

  • Artursson, T., Eklöv, T., Lundström, I., Martensson, P., Sjöström, M., and Holmberg, M. 2000. Drift correction for gas sensors using multivariate methods. J. Chemomet, vol. 14, pp. 711‐723.
  • Chandrashekar, G. and Sahin, F. 2014. A survey on feature selection methods, Computers and Electrical Engineering, vol. 40, pp. 16‐28.
  • Fernandez, L. Guney, S., Gutierrez‐Galvez, A. and Marco, S. 2016. Calibration transfer in temperature modulated gas sensor arrays, Sensors and Actuat. B, Chem., vol. 231, pp. 276‐284.
  • Feudale, R. N., Woody, N. A., Tan, H., Myles, A. J., Brown, S. D. and Ferre, J. 2002. Transfer of mulivariate calibration models: A review. Chemomet. Intell. Lab. Syst., vol. 64, pp. 181‐192.
  • Galvãoa, R. K. H., Soares, S. F. C., Martins, M. N., Pimentel, M. F. and Araújo, M. C. U. 2015. Calibration transfer employing univariate correction and robust regression, Anal. Chim. Acta., vol. 864, pp. 1‐8.
  • Haugen, J., Tomic, O., and Kvaal, K. 2000. A calibration method for handling the temporal drift of solid state gassensors, Anal. Chim. Acta, vol. 407, pp. 23‐39.
  • Malli, B., Birlutiu, A. and Natschläger, T. 2017. Standard‐free calibration transfer ‐ An evaluation of different techniques, Chemomet. Intell. Lab. Syst., vol. 161, pp. 49‐60.
  • Panchuk, V., Kirsanov, D., Oleneva, E., Semenov, V., Legin, A. 2017. Calibration transfer between different analytical methods, Talanta, vol. 170, pp. 457‐463.
  • Pearce, T. C., Schiffman, S. S., Nagle H. T., Gardner, J. W. 2002. Handbook of Machine Olfaction. 1st edition, WILEYVCH, Weinheim, p. 79.
  • Pereira, C. F., Pimentel, M. F., Galvão, R. K., Honorato, F. A., Stragevitch, L. and Martins, M. N. 2008. A comparative study of calibration transfer methods for determination of gasoline quality parametres in three different near infrared spectrometers. Anal. Chim. Acta, vol. 611, pp. 41‐47.
  • Tomic, O., Ulmer, H. and Haugen, J. 2002. Standardization methods for handling instrument related signal shift in gas‐sensor array measurement data. Anal. Chim. Acta, vol. 472, pp. 99‐111.
  • Vergara, A., Vembu, S., Ayhan, T., Ryan, M. A., Homer, M. L., Huerta, R. 2012. Chemical gas sensor drift compensation using classifier ensembles, Sensors and Actuat. B, Chem., vol. 166‐167, pp. 320‐329.
  • Wang, Y., Veltkamp, D. J., and Kowalski, B. R. 1991. Multivariate instrument standardization, Anal. Chem., vol. 63, pp. 2750–2756.
  • Wold, S., Antti, H., Lindgren, F., Öhman, J. 1998. Orthogonal signal correction of near‐infrared spectra, Chemomet. Intell. Lab. Syst., vol. 44, pp. 175‐185.
  • Zhang, F., Chen, W., Zhang, R., Ding, B., Yao, H., Ge, J., Ju, L., Yang, W. and Du, Y. 2017. Sampling error profile analysis for calibration transfer in multivariate calibration, Chemomet. Intell. Lab. Syst., vol. 171, pp. 234‐240.

A Comparison of the Multivariate Calibration Methods with Feature Selection for Gas Sensors’ Long‐Term Drift Effect

Year 2019, Volume: 11 Issue: 3, 170 - 176, 30.12.2019

Abstract

In many electronic nose applications where gas sensors utilizing for a long time, there is an undesirable drift effect on the sensors, which affects the classification quality negatively. Although the sensor drift is inevitable, it is possible to reduce this effect with the calibration transfer methods. This paper presents a comparison study of various multivariate standardization methods to facilitate an effective calibration way on a comprehensive dataset, which is reachable on‐line. In this study, three methods applied: direct standardization (DS) orthogonal signal correction (OSC) and piecewise direct standardization (PDS). In addition, these three methods are applied data, which consisted of selected features. The results have shown that the classification success has increased with multivariate calibration technique applied to the selected features. The results also demonstrate that using the best features in the signal processing part can play an important role for the calibration

References

  • Artursson, T., Eklöv, T., Lundström, I., Martensson, P., Sjöström, M., and Holmberg, M. 2000. Drift correction for gas sensors using multivariate methods. J. Chemomet, vol. 14, pp. 711‐723.
  • Chandrashekar, G. and Sahin, F. 2014. A survey on feature selection methods, Computers and Electrical Engineering, vol. 40, pp. 16‐28.
  • Fernandez, L. Guney, S., Gutierrez‐Galvez, A. and Marco, S. 2016. Calibration transfer in temperature modulated gas sensor arrays, Sensors and Actuat. B, Chem., vol. 231, pp. 276‐284.
  • Feudale, R. N., Woody, N. A., Tan, H., Myles, A. J., Brown, S. D. and Ferre, J. 2002. Transfer of mulivariate calibration models: A review. Chemomet. Intell. Lab. Syst., vol. 64, pp. 181‐192.
  • Galvãoa, R. K. H., Soares, S. F. C., Martins, M. N., Pimentel, M. F. and Araújo, M. C. U. 2015. Calibration transfer employing univariate correction and robust regression, Anal. Chim. Acta., vol. 864, pp. 1‐8.
  • Haugen, J., Tomic, O., and Kvaal, K. 2000. A calibration method for handling the temporal drift of solid state gassensors, Anal. Chim. Acta, vol. 407, pp. 23‐39.
  • Malli, B., Birlutiu, A. and Natschläger, T. 2017. Standard‐free calibration transfer ‐ An evaluation of different techniques, Chemomet. Intell. Lab. Syst., vol. 161, pp. 49‐60.
  • Panchuk, V., Kirsanov, D., Oleneva, E., Semenov, V., Legin, A. 2017. Calibration transfer between different analytical methods, Talanta, vol. 170, pp. 457‐463.
  • Pearce, T. C., Schiffman, S. S., Nagle H. T., Gardner, J. W. 2002. Handbook of Machine Olfaction. 1st edition, WILEYVCH, Weinheim, p. 79.
  • Pereira, C. F., Pimentel, M. F., Galvão, R. K., Honorato, F. A., Stragevitch, L. and Martins, M. N. 2008. A comparative study of calibration transfer methods for determination of gasoline quality parametres in three different near infrared spectrometers. Anal. Chim. Acta, vol. 611, pp. 41‐47.
  • Tomic, O., Ulmer, H. and Haugen, J. 2002. Standardization methods for handling instrument related signal shift in gas‐sensor array measurement data. Anal. Chim. Acta, vol. 472, pp. 99‐111.
  • Vergara, A., Vembu, S., Ayhan, T., Ryan, M. A., Homer, M. L., Huerta, R. 2012. Chemical gas sensor drift compensation using classifier ensembles, Sensors and Actuat. B, Chem., vol. 166‐167, pp. 320‐329.
  • Wang, Y., Veltkamp, D. J., and Kowalski, B. R. 1991. Multivariate instrument standardization, Anal. Chem., vol. 63, pp. 2750–2756.
  • Wold, S., Antti, H., Lindgren, F., Öhman, J. 1998. Orthogonal signal correction of near‐infrared spectra, Chemomet. Intell. Lab. Syst., vol. 44, pp. 175‐185.
  • Zhang, F., Chen, W., Zhang, R., Ding, B., Yao, H., Ge, J., Ju, L., Yang, W. and Du, Y. 2017. Sampling error profile analysis for calibration transfer in multivariate calibration, Chemomet. Intell. Lab. Syst., vol. 171, pp. 234‐240.
There are 15 citations in total.

Details

Primary Language English
Subjects Electrical Engineering
Journal Section Articles
Authors

Gülnur Begüm Ergün This is me

Selda Güney

Publication Date December 30, 2019
Published in Issue Year 2019 Volume: 11 Issue: 3

Cite

IEEE G. B. Ergün and S. Güney, “A Comparison of the Multivariate Calibration Methods with Feature Selection for Gas Sensors’ Long‐Term Drift Effect”, IJTS, vol. 11, no. 3, pp. 170–176, 2019.

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