MATEC Web Conf.
Volume 184, 2018Annual Session of Scientific Papers IMT ORADEA 2018
|Number of page(s)||6|
|Section||Machines Engineering and Technologies|
|Published online||31 July 2018|
An approach of classification and parameters estimation, using neural network, for lubricant degradation diagnosis
University of Oradea, Faculty of Manag. and Technological Eng., Industrial Engineering Department, Universitatii 1, Romania
2 Zarqa University, Faculty of Engineering Technology, P.O. Box 132222 Zarqa 13132, Jordan
3 University of Oradea, Faculty of Manag. and Techn. Eng., Mechanical Eng. and Automotive Department, Universitatii 1, Romania
* Corresponding author : firstname.lastname@example.org
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).
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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