Study on non-invasive classification of engine oil based on visible and short-wave near infrared spectroscopy

Author

Zi-Li, Zhou ; Yi-Fang, Zhang ; Di, Wu ; Yong, He ; Xiao-Li, Li ; Yong-Ni, Shao

Author_Institution

Comput. Eng. Dept., Zhejiang Inst. of Mech. & Electr. Eng., Hangzhou, China

fYear

2010

fDate

24-27 Aug. 2010

Firstpage

1089

Lastpage

1091

Abstract

Visible and short-wave near infrared (Vis-SwNIR) spectroscopy was used for the non-invasive classification of engine oil. A total of 150 oil samples from three brands were prepared. The calibration set contains 120 samples which were randomly selected. The remaining 30 samples were used for the prediction. After the spectra measurement, principal component analysis was calculated to cluster the samples. Discrete wavelet transform (DWT) was used to do the spectral mining. The obtained wavelet coefficients were inputted into artificial neural network (ANN) for the brand classification of engine oil. The correct classification rate of 100% was obtained by DWT-ANN model. The overall results show that Vis-SwNIR spectroscopy is a feasible technique for the brand classification of engine oil.

Keywords

calibration; data mining; discrete wavelet transforms; engines; infrared spectroscopy; mechanical engineering computing; neural nets; principal component analysis; artificial neural network; brand classification; calibration set; discrete wavelet transform; engine oil; noninvasive classification; principal component analysis; short-wave near infrared spectroscopy; spectra measurement; spectral mining; visible near infrared spectroscopy; wavelet coefficients; Artificial neural networks; Classification algorithms; Discrete wavelet transforms; Engines; Petroleum; Principal component analysis; Spectroscopy; Visible and short-wave near infrared (Vis-SwNIR) spectroscopy; Wavelet transform (WT); artificial neural network (ANN); engine oil; principal component analysis (PCA);

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Education (ICCSE), 2010 5th International Conference on

Conference_Location

Hefei

Print_ISBN

978-1-4244-6002-1

Type

conf

DOI

10.1109/ICCSE.2010.5593421

Filename

5593421