%0 Journal Article
%T An approach of classification and parameters estimation, using neural network, for lubricant degradation diagnosis
%A Gavril Grebeni£żan
%A Nazzal Salem
%A and Sanda Bogdan
%J ANNALS OF THE UNIVERSITY OF ORADEA. Fascicle of Management and Technological Engineering
%P 1-6
%D 2018
%R 10.1051/matecconf/201818403009
%X This paper addresses a delicate problem, namely the diagnosis of the state of the oils in the industrial systems, namely the machine tools. Based on measurements (the data set contains over five million records), within a Machine Intelligence for Diagnosis Automation (MIDA) project funded by the National Program PN II, ERA MANUNET: NR 13081221 / 13.08.2013, several applications of MATLAB toolbars are being developed in the field of artificial intelligence, specifically using the Support Vector Machine algorithms and neural networks. The tests were carried out on several distinct situations, followed by validation and verification tests on the devices designed and developed within the project (MIDA, Monitoil).
%K machine intelligence
%K condition monitoring
%K parameterized analysis
%K support vector machine
%K neural networks
%U https://imt.uoradea.ro/auo.fmte/files-2018-v2/Gavril%20Grebeni%C5%9Fan,%20Nazzal%20Salem,%20and%20Sanda%20Bogdan-An%20approach%20of%20classification%20and%20parameters%20estimation,%20using%20neural%20network,%20for%20lubricant%20degradation%20diagnosis.pdf