Suppression of Strong Background Interference on E-Nose Sensors in an Open Country Environment
AbstractThe feature extraction technique for an electronic nose (e-nose) applied in tobacco smell detection in an open country/outdoor environment with periodic background strong interference is studied in this paper. Principal component analysis (PCA), Independent component analysis (ICA), re-filtering and a priori knowledge are combined to separate and suppress background interference on the e-nose. By the coefficient of multiple correlation (CMC), it can be verified that a better separation of environmental temperature, humidity, and atmospheric pressure variation related background interference factors can be obtained with ICA. By re-filtering according to the on-site interference characteristics a composite smell curve was obtained which is more related to true smell information based on the tobacco curer’s experience. View Full-Text
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Tian, F.; Zhang, J.; Yang, S.X.; Zhao, Z.; Liang, Z.; Liu, Y.; Wang, D. Suppression of Strong Background Interference on E-Nose Sensors in an Open Country Environment. Sensors 2016, 16, 233.
Tian F, Zhang J, Yang SX, Zhao Z, Liang Z, Liu Y, Wang D. Suppression of Strong Background Interference on E-Nose Sensors in an Open Country Environment. Sensors. 2016; 16(2):233.Chicago/Turabian Style
Tian, Fengchun; Zhang, Jian; Yang, Simon X.; Zhao, Zhenzhen; Liang, Zhifang; Liu, Yan; Wang, Di. 2016. "Suppression of Strong Background Interference on E-Nose Sensors in an Open Country Environment." Sensors 16, no. 2: 233.
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