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Sensors and actuators. B, Chemical v.259, 2018년, pp.420 - 427   SCI SCIE SCOPUS
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Dual-channel mid-infrared sensor based on tunable Fabry-PErot filters for fluid monitoring applications

Rauscher, Markus S. (Corresponding author. ) ; Schardt, Michael ; Köhler, Michael H. ; Koch, Alexander W. ;
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    Abstract In this article, the design and application of an optical sensor for fluid monitoring based on two tunable Fabry-PErot filters is presented. The sensor enables fluid transmission measurements in the spectral ranges from 1818 cm −1 to 1250 cm −1 and from 1250 cm −1 to 952 cm −1 at wavenumber-dependent resolutions between approximately 20 cm −1 and 33 cm −1 . A novel method is proposed to ensure a correct wavenumber representation of the obtained spectra, correcting for an oblique light path in the optical system. The sensor shows high linearity and a low noise level for absorbance measurements. As an example for a fluid monitoring application, the transmission spectra of deteriorated automotive engine oil samples were measured and compared to spectra obtained with a Fourier-transform infrared spectrometer. We used partial least squares (PLS) regression to construct calibration models for the prediction of significant oil condition parameters, like oxidation, sulfation, water content and viscosity, from the obtained spectra. The values predicted from the absorption spectra show high correlation with reference values of the oil condition parameters determined in a laboratory according to appropriate standards. These results indicate that the sensor can be a useful supplementary tool for fast and cost-effective engine oil condition monitoring. Highlights The development of a mid-infrared spectroscopic fluid sensor is presented. The sensor is based on two miniaturized tunable Fabry-PErot filters. Spectra of deteriorated engine oil samples are measured and compared. The wavenumber shift of the spectra is algorithmically corrected. Multivariate methods enable an accurate prediction of oil condition parameters.


  • 주제어

    Optical sensor .   Fabry-Pérot filter .   Automotive engine oil condition monitoring .   Infrared sensing .   Multivariate data analysis.  

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