Source Direction Detection based on Stationary Electronic Nose System
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Source Direction Detection based on Stationary Electronic Nose System

Authors: Jie Cai, David C. Levy

Abstract:

Electronic nose (array of chemical sensors) are widely used in food industry and pollution control. Also it could be used to locate or detect the direction of the source of emission odors. Usually this task is performed by electronic nose (ENose) cooperated with mobile vehicles, but when a source is instantaneous or surrounding is hard for vehicles to reach, problem occurs. Thus a method for stationary ENose to detect the direction of the source and locate the source will be required. A novel method which uses the ratio between the responses of different sensors as a discriminant to determine the direction of source in natural wind surroundings is presented in this paper. The result shows that the method is accurate and easily to be implemented. This method could be also used in movably, as an optimized algorithm for robot tracking source location.

Keywords: Electronic nose, Nature wind situation, Source direction detection.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1062484

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[1] F. J. Acevedo, S. Maldonado, E. Dominguez, A. Narvaez, and F. Lopez, "Probabilistic support vector machines for multi-class alcohol identification," Sensors and Actuators B: Chemical, vol. In Press, Corrected Proof.
[2] H. Yu and J. Wang, "Discrimination of LongJing green-tea grade by electronic nose," Sensors and Actuators B: Chemical, vol. In Press, Corrected Proof.
[3] G. A. Bell and A. J. Watson, Tastes & Aromas, the chemical senses in science and industry. Sydney: University of New South Wales Press, 1999.
[4] Y. Peng, P. Min, C. Yuquan, and L. Guang, "The recognition of Chinese spirits using electronic nose with dynamic method," presented at Engineering in Medicine and Biology Society. Proceedings of the 23rd Annual International Conference of the IEEE, 2001.
[5] K. Brudzewski, S. Osowski, T. Markiewicz, and J. Ulaczyk, "Classification of gasoline with supplement of bio-products by means of an electronic nose and SVM neural network," Sensors and Actuators B: Chemical, vol. 113, pp. 135-141, 2006.
[6] T. Sobanski, A. Szczurek, K. Nitsch, B. W. Licznerski, and W. Radwan, "Electronic nose applied to automotive fuel qualification," Sensors and Actuators B: Chemical, vol. 116, pp. 207-212, 2006.
[7] E. Scorsone, A. M. Pisanelli, and K. C. Persaud, "Development of an electronic nose for fire detection," Sensors and Actuators B: Chemical, vol. 116, pp. 55-61, 2006.
[8] S. Ampuero and J. O. Bosset, "The electronic nose applied to dairy products: a review," Sensors and Actuators B: Chemical, vol. 94, pp. 1- 12, 2003.
[9] L. Carmel, "Electronic nose signal restoration--beyond the dynamic range limit," Sensors and Actuators B: Chemical, vol. 106, pp. 95-100, 2005.
[10] L. Carmel, N. Sever, D. Lancet, and D. Harel, "An eNose algorithm for identifying chemicals and determining their concentration," Sensors and Actuators B: Chemical, vol. 93, pp. 77-83, 2003.
[11] R. Haddad, L. Carmel, and D. Harel, "A feature extraction algorithm for multi-peak signals in electronic noses," Sensors and Actuators B: Chemical, vol. In Press, Corrected Proof.
[12] L. Carmel, S. Levy, D. Lancet, and D. Harel, "A feature extraction method for chemical sensors in electronic noses," Sensors and Actuators B: Chemical, vol. 93, pp. 67-76, 2003.
[13] M. Padilla, I. Montoliu, A. Pardo, A. Perera, and S. Marco, "Feature extraction on three way enose signals," Sensors and Actuators B: Chemical, vol. 116, pp. 145-150, 2006.
[14] C. Hong, R. A. Goubran, and T. Mussivand, "Improving the classification accuracy in electronic noses using multi-dimensional combining (MDC)," presented at Sensors. Proceedings of IEEE, 2004.
[15] S. J. Qin and Z. J. Wu, "A new approach to analyzing gas mixtures," Sensors and Actuators B: Chemical, vol. 80, pp. 85-88, 2001.
[16] J. Matthes, L. Groll, and H. B. Keller, "Source localization by spatially distributed electronic noses for advection and diffusion," Signal Processing, IEEE Transactions on
[see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol. 53, pp. 1711-1719, 2005.
[17] A. Loutfi and S. Coradeschi, "Relying on an electronic nose for odor localization," presented at Virtual and Intelligent Measurement Systems. VIMS '02. 2002 IEEE International Symposium on, 2002.
[18] L. Marques and A. T. De Almeida, "Electronic nose-based odour source localization," presented at Advanced Motion Control. Proceedings. 6th International Workshop on, 2000.
[19] W. Jatmiko, Y. Ikemoto, T. Matsuno, T. Fukuda, and K. Sekiyama, "Distributed odor source localization in dynamic environment," presented at Sensors, IEEE, 2005.