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dc.contributor.authorPerera Lluna, Alexandre-
dc.contributor.authorPapamichail, Niko-
dc.contributor.authorBarsan, Nicolae-
dc.contributor.authorWeimar, Udo-
dc.contributor.authorMarco Colás, Santiago-
dc.description.abstractLeakage 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
dc.relation.isformatofReproducció del document publicat a
dc.relation.ispartofIEEE Sensors Journal, 2003, vol. 2, núm. 22-24, p.
dc.rights(c) IEEE, 2003cat
dc.sourceArticles publicats en revistes (Enginyeria Electrònica i Biomèdica)-
dc.subject.classificationDetectors de gasoscat
dc.subject.otherGas detectorseng
dc.subject.otherElectronic noiseeng
dc.titleOn-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditionseng
Appears in Collections:Articles publicats en revistes (Enginyeria Electrònica i Biomèdica)

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