Characterization of Motor Oil by Laser-Induced Fluorescence

Fandong Meng; Siying Chen; Yinchao Zhang; He Chen; Pan Guo; Taotao Mu; Xiaohua Liu

doi:10.1080/00032719.2015.1015073

Characterization of Motor Oil by Laser-Induced Fluorescence

Fandong Meng, Siying Chen^*, Yinchao Zhang, He Chen, Pan Guo, Taotao Mu, Xiaohua Liu

^*Corresponding author for this work

School of Optics and Photonics

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

A new laser-induced fluorescence method is presented to classify brands of motor oil. A 266-nanometer radiation was employed to collect sixty sets of fluorescence spectra for each brand. Cluster analysis and support vector machine were employed to distinguish motor oils with principal component analysis, which was applied to extract spectral characteristics. The recognition accuracy was up to 100 percent. The results demonstrate that laser-induced fluorescence offers rapid response, high recognition, and high sensitivity for the classification of motor oils.

Original language	English
Pages (from-to)	2090-2095
Number of pages	6
Journal	Analytical Letters
Volume	48
Issue number	13
DOIs	https://doi.org/10.1080/00032719.2015.1015073
Publication status	Published - 2 Sept 2015

Keywords

Cluster analysis
Laser-induced fluorescence
Motor oils
Principal component analysis
Support vector machine

Access to Document

10.1080/00032719.2015.1015073

Cite this

@article{fce1ea78190640b2aa40084a7bdb3e76,

title = "Characterization of Motor Oil by Laser-Induced Fluorescence",

abstract = "A new laser-induced fluorescence method is presented to classify brands of motor oil. A 266-nanometer radiation was employed to collect sixty sets of fluorescence spectra for each brand. Cluster analysis and support vector machine were employed to distinguish motor oils with principal component analysis, which was applied to extract spectral characteristics. The recognition accuracy was up to 100 percent. The results demonstrate that laser-induced fluorescence offers rapid response, high recognition, and high sensitivity for the classification of motor oils.",

keywords = "Cluster analysis, Laser-induced fluorescence, Motor oils, Principal component analysis, Support vector machine",

author = "Fandong Meng and Siying Chen and Yinchao Zhang and He Chen and Pan Guo and Taotao Mu and Xiaohua Liu",

note = "Publisher Copyright: {\textcopyright} 2015, Copyright {\textcopyright} Taylor & Francis Group, LLC.",

year = "2015",

month = sep,

day = "2",

doi = "10.1080/00032719.2015.1015073",

language = "English",

volume = "48",

pages = "2090--2095",

journal = "Analytical Letters",

issn = "0003-2719",

publisher = "Taylor and Francis Ltd.",

number = "13",

}

TY - JOUR

T1 - Characterization of Motor Oil by Laser-Induced Fluorescence

AU - Meng, Fandong

AU - Chen, Siying

AU - Zhang, Yinchao

AU - Chen, He

AU - Guo, Pan

AU - Mu, Taotao

AU - Liu, Xiaohua

PY - 2015/9/2

Y1 - 2015/9/2

N2 - A new laser-induced fluorescence method is presented to classify brands of motor oil. A 266-nanometer radiation was employed to collect sixty sets of fluorescence spectra for each brand. Cluster analysis and support vector machine were employed to distinguish motor oils with principal component analysis, which was applied to extract spectral characteristics. The recognition accuracy was up to 100 percent. The results demonstrate that laser-induced fluorescence offers rapid response, high recognition, and high sensitivity for the classification of motor oils.

AB - A new laser-induced fluorescence method is presented to classify brands of motor oil. A 266-nanometer radiation was employed to collect sixty sets of fluorescence spectra for each brand. Cluster analysis and support vector machine were employed to distinguish motor oils with principal component analysis, which was applied to extract spectral characteristics. The recognition accuracy was up to 100 percent. The results demonstrate that laser-induced fluorescence offers rapid response, high recognition, and high sensitivity for the classification of motor oils.

KW - Cluster analysis

KW - Laser-induced fluorescence

KW - Motor oils

KW - Principal component analysis

KW - Support vector machine

UR - http://www.scopus.com/inward/record.url?scp=84931028816&partnerID=8YFLogxK

U2 - 10.1080/00032719.2015.1015073

DO - 10.1080/00032719.2015.1015073

M3 - Article

AN - SCOPUS:84931028816

SN - 0003-2719

VL - 48

SP - 2090

EP - 2095

JO - Analytical Letters

JF - Analytical Letters

IS - 13

ER -

Characterization of Motor Oil by Laser-Induced Fluorescence

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this