Abstract
The paper deals with the problem of monitoring the complicated hydromechanical system of a rotary machine with fluid-film bearings. The prospect of accurate recognition of changes in the lubrication system, which are expressed in the appearance of air bubbles in the lubricant, is investigated. The monitoring of the state is carried out by means of high-speed measurements of shaft vibrations, lubricant pressure supply and other parameters. Measurement data are transmitted for analysis to an artificial neural network to recognize the state of the system. The developed neural network has demonstrated high recognition accuracy of more than 98 %. Some recommendations on the measurement results processing and the neural network settings are represented in the paper.
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