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
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;
Conference_Titel :
American Control Conference, 2000. Proceedings of the 2000
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-5519-9
DOI :
10.1109/ACC.2000.879222
