The envelope spectrum analysis on vibration signals has been demonstrated for many years as a powerful technique to extract effective indicators (features) for condition monitoring of rolling element bearings under stationary operating conditions. As will be shown in this paper, applying these diagnostic features without a care to rotating machines subject to varying operating conditions may lead to unreliable bearing fault diagnostics. Hence, the applicability of the diagnostic features is rather limited. To extend the applicability of the diagnostic features, number of researchers/research institutes have developed new features/methods to deal with variation of operating conditions. However, the methods proposed in the literature mainly focuses on shaft speed variations. In practice, both shaft speed and load can vary in time simultaneously so there might be an interaction effect on the diagnostic features responses. Moreover, the bearing temperature, being an operational parameter, may also vary significantly in some applications. Because the temperature affects the film thickness formed between the rolling elements and the raceways of bearings, which in turn contributes to the damping and contact stiffness of bearings, it is believed that the bearing temperature might also play an important role on the diagnostic features responses. To improve our understanding on how the three operational parameters variations, namely speed, load and temperature, affect the diagnostic feature responses, a set of experiments has been designed to investigate the effects using an in-house developed test setup. The main effects of the operational parameters on the diagnostic features are presented and discussed in this paper. Qualitative models describing the relationships between the diagnostic features and the operational parameters are deduced and discussed in the paper. It is believed that these qualitative models can be useful to inspire us in the future to develop methods/strategies for bearing fault diagnostics under varying rotational speed, load and temperature.
How to Cite
bearing fault monitoring, operating condition variations, realistic spall bearing fault generations
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