Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/8753
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Perera Lluna, Alexandre | - |
dc.contributor.author | Papamichail, Niko | - |
dc.contributor.author | Barsan, Nicolae | - |
dc.contributor.author | Weimar, Udo | - |
dc.contributor.author | Marco Colás, Santiago | - |
dc.date.accessioned | 2009-06-19T08:04:51Z | - |
dc.date.available | 2009-06-19T08:04:51Z | - |
dc.date.issued | 2003 | cat |
dc.identifier.issn | 1530-437X | - |
dc.identifier.uri | http://hdl.handle.net/2445/8753 | - |
dc.description.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. | ca |
dc.format.extent | 6 p. | cat |
dc.format.mimetype | application/pdf | eng |
dc.language.iso | eng | eng |
dc.publisher | IEEE | cat |
dc.relation.isformatof | Reproducció del document publicat a http://dx.doi.org/10.1109/ICSENS.2003.1279065 | cat |
dc.relation.ispartof | IEEE Sensors Journal, 2003, vol. 2, núm. 22-24, p. 860-865. | cat |
dc.relation.uri | http://dx.doi.org/10.1109/ICSENS.2003.1279065 | - |
dc.rights | (c) IEEE, 2003 | cat |
dc.source | Articles publicats en revistes (Enginyeria Electrònica i Biomèdica) | - |
dc.subject.classification | Detectors de gasos | cat |
dc.subject.other | Gas detectors | eng |
dc.subject.other | Electronic noise | eng |
dc.title | On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions | eng |
dc.type | info:eu-repo/semantics/article | eng |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 529790 | cat |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Enginyeria Electrònica i Biomèdica) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
529790.pdf | 466.29 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.