Neural Networks as a Tool to Characterise Oil State After Porous Bearings Prolonged Tests
Keywords:oxidation of lubricants, porous bearings characteristics, neural networks
The paper presents the results of research of durability tests of porous sleeves under differed conditions (600, 1000 and 1400 rpm, duration of the tests: 100, 200 and 1000 hours, temperature 60, 80 and 130˚C) of one oil. During the tests
a temperature of the bearing and a moment of friction were measured. After each durability test oil samples were extracted from the bearings and some chosen properties were carried out (FTIR spectrums and total acid number).
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