Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/8753
Title: On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions
Author: Perera Lluna, Alexandre
Papamichail, Niko
Barsan, Nicolae
Weimar, Udo
Marco Colás, Santiago
Keywords: Detectors de gasos
Gas detectors
Electronic nose
Issue Date: 2003
Publisher: IEEE
Abstract: Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.
Note: Reproducció del document publicat a http://dx.doi.org/10.1109/ICSENS.2003.1279065
It is part of: IEEE Sensors Journal, 2003, vol. 2, núm. 22-24, p. 860-865.
URI: http://hdl.handle.net/2445/8753
ISSN: 1530-437X
Appears in Collections:Articles publicats en revistes (Electrònica)

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