Abstract
Calibrated identification of volatile organics by electronic sensors needs development of data collection and data processing methods that can efficiently generate vapor identity features and some quantitative measure of its concentration simultaneously. In this paper, we present a simulation study on this based on surface acoustic wave (SAW) chemical sensors functionalized by polymer coating. The analysis utilizes transient responses of SAW sensors exposed to seven volatile organic compounds at various concentrations. The feature extraction is done by discrete wavelet decomposition using Daubechies-2 basis. A fuzzy c-means clustering method based Sugeno-type fuzzy inference system was then roped in for simultaneous identification and concentration estimation. The performance of the method has been analyzed for various conditions of polymer film thickness. It is concluded that there exists an optimum region for film thickness over which the present method yields nearly 100% correct classification with less than 1% concentration error.
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References
Persaud, K., Dodd, G.: Analysis of Discrimination Mechanisms in the Mammalian Olfactory System Using a Model Nose. Nature 299, 352–355 (1982)
Rogers, E.K.: Handbook of Biosensors and Electronic Noses: Medicine, Food and Environment. CRC Press (1997)
Gardner, J.W., Bartlett, P.N.: Electronic Noses: Principles and Applications. Oxford University Press, New York (1999)
James, D., Simon, M.S., Ali, Z., William, T.H.: Chemical Sensors for Electronic Nose Systems. Microchim. Acta 149, 1–17 (2005)
Rock, F., Barsan, N., Weimar, U.: Electronic Nose: Current Status and Future Trends. Chem. Rev. 108, 705–725 (2008)
Alphus, D.W., Baietto, M.: Applications and Advances in Electronic-Nose Technologies. Sensors 9, 5099–5148 (2009)
Singh, P., Yadava, R.D.S.: Effect of Film Thickness and Viscoelasticity on Separability of Vapour Classes by Wavelet and Principal Component Analyses of Polymer-Coated Surface Acoustic Wave Sensor Transients. Meas. Sci. Technol. 22, 025202, 15 (2011)
Singh, P., Yadava, R.D.S.: Feature Extraction by Wavelet Decomposition of Surface Acoustic Wave Sensor Array Transients. Def. Sci. J. 60, 377–386 (2010)
Martin, S.J., Frye, G.C., Senturia, S.D.: Dynamics and Response of Polymer-Coated Surface Acoustic Wave Devices: Effect of Viscoelastic Properties and Film Resonance. Anal. Chem. 66, 2201–2219 (1994)
Yadava, R.D.S., Chaudhary, R.: Solvation, Transduction and Independent Component Analysis for Pattern Recognition in SAW Electronic Nose. Sens. Actuat. B 113, 1–21 (2006)
Yadava, R.D.S., Kshetrimayum, R., Khaneja, M.: Multifrequency Characterization of Viscoelastic Polymers and Vapor Sensing Based on SAW Oscillators. Ultrasonics 49, 638–645 (2009)
Crank, J.: The Mathematics of Diffusion. Clarendon, Oxford, sec. 4.3 eq. 4.18 (1986)
Singh, P., Yadava, R.D.S.: Using Parametric Nonlinearity in SAW Sensor Transients and Information Fusion for Improving Electronic Nose Intelligence. Int. J. Computational Intelligence Research 6, 919–927 (2010) (Special Conf. Issue ICCI 2010)
Singh, P., Yadava, R.D.S.: A Fusion Approach to Feature Extraction by Wavelet Decomposition and Principal Component Analysis in Transient Signal Processing of SAW Odor Sensor Array. Sensors & Transducers J. 126, 64–73 (2011)
Burrus, C.S., Gopinath, R.A., Guo, H.: Introduction to Wavelets and Wavelet Transforms: A Primer. Prentice-Hall, Englewood Cliffs (1998)
Mallat, S.: A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Pattern Anal. and Machine Intell. 11, 674–693 (1989)
Bezdek, J.C., Ehrlich, R., Full, W.: FCM: The Fuzzy c-Means Clustering Algorithm. Computers & Geosciences 10, 191–203 (1984)
Nascimento, S., Mirkin, B., Pires, F.: A Fuzzy Clustering Model of Data and Fuzzy c-Means. In: The Ninth IEEE International Conference on Fuzzy Systems, vol. 1, pp. 302–307 (2000)
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Singh, P., Yadava, R.D.S. (2011). Wavelet Based Fuzzy Inference System for Simultaneous Identification and Quantitation of Volatile Organic Compounds Using SAW Sensor Transients. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_37
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DOI: https://doi.org/10.1007/978-3-642-27242-4_37
Publisher Name: Springer, Berlin, Heidelberg
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