DocumentCode
2566206
Title
Remaining useful life prediction of automotive engine oils using MEMS technologies
Author
Jagannathan, S. ; Raju, G.V.S.
Author_Institution
Intelligent Syst. Lab., Texas Univ., San Antonio, TX, USA
Volume
5
fYear
2000
fDate
2000
Firstpage
3511
Abstract
This paper proposes a novel adaptive methodology where both micro-sensors and models are used in conjunction with neural network/fuzzy classification algorithm to predict the quality of engine oils. The condition of the engine oil is defined as a single variable and trended. Advanced prognostic algorithms are then applied on the oil condition trends to predict the remaining useful life of engine oils. Experimental results are given
Keywords
adaptive systems; condition monitoring; fault diagnosis; fuzzy set theory; internal combustion engines; mechanical engineering computing; microsensors; neural nets; adaptive system; automotive engine oils; condition monitoring; fuzzy classification; microsensors; neural network; useful life prediction; Automotive engineering; Costs; Degradation; Electronics packaging; Engines; Micromechanical devices; Oils; Petroleum; Pollution measurement; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2000. Proceedings of the 2000
Conference_Location
Chicago, IL
ISSN
0743-1619
Print_ISBN
0-7803-5519-9
Type
conf
DOI
10.1109/ACC.2000.879222
Filename
879222
Link To Document