JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Step-wise Elimination Method Based on Euclidean Distance for Performance Optimization Regarding to Chemical Sensor Array
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Step-wise Elimination Method Based on Euclidean Distance for Performance Optimization Regarding to Chemical Sensor Array
Lim, Hea-Jin; Choi, Jang-Sik; Jeon, Jin-Young; Byu, Hyung-Gi;
  PDF(new window)
 Abstract
In order to prevent drink-driving by detecting concentration of alcohol from driver`s exhale breath, twenty chemical sensors fabricated. The one of purposes for sensor array which consists of those sensors is to discriminate between target gas(alcohol) and interference gases(, CO, NOx, Toluene, and Xylene). Wilks`s lambda was presented to achieve above purpose and optimal sensors were selected using the method. In this paper, step-wise sensor elimination based on Euclidean distance was investigated for selecting optimal sensors and compared with a result of Wilks`s lambda method. The selectivity and sensitivity of sensor array were used for comparing performance of sensor array as a result of two methods. The data acquired from selected sensor were analyzed by pattern analysis methods, principal component analysis and Sammon`s mapping to analyze cluster tendency in the low space (2D). The sensor array by stepwise sensor elimination method had a better sensitivity and selectivity compared to a result of Wilks`s lambda method.
 Keywords
Step-wise sensor elimination;Array optimization;Wilks`s lambda;
 Language
Korean
 Cited by
1.
Investigation of Chemical Sensor Array Optimization Methods for DADSS, Journal of Sensor Science and Technology, 2016, 25, 1, 13  crossref(new windwow)
 References
1.
https://en.wikipedia.org/wiki/Ignition_interlock_device (modified on 7 July 2015)

2.
B. Y. Kim, C. S, Lee, J. S. Park, and J. H. Lee, "Preparation of Pt-, Ni- and Cr-Decorated $SnO_2$ tubular nanofibers and their gas sensing properties", Journal of Sensor Science and Technology, Vol. 23, No. 3, pp. 211-215, 2014. crossref(new window)

3.
Jin-Young Jeon, Jeong-Suk Shin, Joon-Boo Yu, and Hyung- Gi Byun, "Chemical sensors array optimization based on wilks lamda technique", Journal of Sensor Science and Technology, Vol. 23, No. 5, pp. 299-304, 2014. crossref(new window)

4.
Chaudry, A. N., T. M. Hawkins, and P. J. Travers, "A method for selecting an optimum sensor array", Sensors and Actuators B: Chemical, Vol. 69, No. 3, pp. 236-242, 2000. crossref(new window)

5.
Hyung-Gi Byun and Jang-Sik Choi, "Real-time visualization techniques for sensor array patterns using PCA and sammon mapping analysis", Journal of Sensor Science and Technology, Vol. 23, No. 2, pp. 99-104, 2014. crossref(new window)

6.
Sammon Jr. J. W., "A nonlinear mapping for data structure analysis", IEEE Trans. on computers, Vol. c-18, No. 5, pp. 401-409, 1969. crossref(new window)

7.
http://en.wikipedia.org/wiki/Feature_selection(modified on 16 April 2015)