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Drift correction for gas sensors using multivariate methods
Author(s) -
Artursson Tom,
Eklöv Tomas,
Lundström Ingemar,
Mårtensson Per,
Sjöström Michael,
Holmberg Martin
Publication year - 2000
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/1099-128x(200009/12)14:5/6<711::aid-cem607>3.0.co;2-4
Subject(s) - constant (computer programming) , sample (material) , component (thermodynamics) , set (abstract data type) , principal component analysis , factorial experiment , concept drift , simple (philosophy) , computer science , analytical chemistry (journal) , statistics , mathematics , chemistry , physics , thermodynamics , chromatography , data stream , philosophy , epistemology , programming language
Drift is one of the most serious impairments afflicting gas sensors. It can be seen as a gradual change in the sensor response over a long period of time when the external conditions are constant. This paper presents a new simple drift counteraction method based on PCA and PLS. The basic idea is to remove the drift direction component from the measurements. The direction of the drift, p , is calculated from measurements for a reference gas. Projecting the sample gas measurements on this vector gives the score vector t . The drift component tp T can then be removed from the sample gas data, which we call component correction (CC). The method is tested on a data set based on a reduced factorial design with four gases and a concentration gradient of hydrogen. It is found that the method works efficiently for both cases. Copyright © 2000 John Wiley & Sons, Ltd.