The use of acoustic emission information to distinguish between dry and lubricated rolling element bearings in low-speed rotating machines
Bearings are known as the vital parts of machines, and their condition is often critical to the success of an operation or process. Presence of a film of lubricant such as grease between the bearing surfaces minimizes the friction and surface wear. Contaminated grease or lack of lubricant may lead to an ineffective bearing performance or malfunction of the machinery parts. Therefore, in order to avoid unexpected breakdowns, reliable and robust bearing condition monitoring techniques are demanded. According to previous studies, acoustic emission (AE) signals contain valuable information that can be used for bearing condition monitoring and fault detection. The main objective of this study is to evaluate the effectiveness of AE signal parameters to distinguish between lubricated and dry bearings under similar operating conditions. To this end, a low-speed rotating test rig is manufactured and used. Eight levels of rotational speeds and four levels of radial loads were applied to the test rig shaft end, which is connected to the testing bearing. In each test, seven time domain AE parameters were computed. The statistical tools were also used to present the dominant experimental variables on AE signal parameters. According to experimental results, it was found that four AE parameters can be used to distinguish between dry and lubricated bearings.
KeywordAcoustic emission Rolling element bearing Condition monitoring Lubrication Signal processing
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