Paper
13 May 2010 Visible/NIR on-line sensor for marine engine oil condition monitoring applying chemometric methods
A. Villar, E. Gorritxategi, S. Fernandez, D. Otaduy, A. Arnaiz, J. I. Ciria, Luis A. Fernandez
Author Affiliations +
Abstract
Marine engine oils are used for years without an oil change. During this long period of time the oil gets contaminated, not only by water and fuel but also by solid contaminants due to oxidation of the base oil, overreacted additives soot and other products of Heavy Fuel Oil combustion. This paper shows the design, development and assembly of a visible-near infrared (400-1100 nm) sensor that monitors several characteristics corresponding to in-use marine engine oil condition. Also, chemometric techniques (PLS) are applied for determining TBN, %insoluble in pentane, soot and water from visible-near infrared spectra, having in mind the low resolution capability of the extracted on-line sensor signal. Different prediction models for each oil parameter were obtained. These prediction models were developed by partial least squares regression from the VIS/NIR spectra. Finally, the sensor has been tested at low-speed crosshead engine (two stroke engine). So that, reference values for TBN, %insoluble in pentane, soot and water were obtained in the laboratory for every sample. During the validation test, the models showed: a) a correlation higher than or equal to 0.85; b) the slope for the regression model tends to one; c) low bias; and d) the root mean square error of prediction (RMSEP) and the standard error of performance (SEP) were similar and close to the laboratory's estimated error.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Villar, E. Gorritxategi, S. Fernandez, D. Otaduy, A. Arnaiz, J. I. Ciria, and Luis A. Fernandez "Visible/NIR on-line sensor for marine engine oil condition monitoring applying chemometric methods", Proc. SPIE 7726, Optical Sensing and Detection, 77262F (13 May 2010); https://doi.org/10.1117/12.862642
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Cited by 3 scholarly publications.
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KEYWORDS
Sensors

Water

Infrared sensors

Oceanography

Statistical modeling

Coastal modeling

Chemometrics

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