In this work, a representative mathematical model has been developed, which reliably describes the heating and cooling of a journal bearing as a result of its malfunctioning, and the model has been further confirmed on a test bench. The bearing model was validated by using analytical modeling methods, i. e. the experimental results were compared to the data obtained by analytical calculations. The regression and variance analysis techniques were applied to process the recorded data, to test the mathematical model and to define mathematical functions for the heating/cooling of the journal bearing. This investigation shows that a representative model may reliably indicate the change in the thermal field, which may be a consequence of journal bearing damage.

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Sliding bearings are widely used machine elements from which the correct operation depends on the availability of many technical systems and great attention is paid to the study of the prediction method for sliding bearings. Problems that occur with sliding bearings lead to high levels of vibration and noise. One of the important parameters in the diagnosis and prediction of the failure of sliding bearings is the thermal analysis. In addition to these parameters, frequent vibration spectrum analysis, oil film thickness and other relevant parameters are often used. Using advanced technologies, it is possible to significantly reduce the duration of measurement, and on the other hand increase the accuracy of diagnostic methods. Phase logic is a mathematically formalized mode of representation modeling uncertainty. In this paper, a selection of damage in the operation of a sliding bearing has been made and the way of diagnosing these problems is shown. Methods that integrate several diagnostic parameters into one show reliable methods of early detection of slip bearing damage.