Proposing a New Acoustic Emission Parameter for Bearing Condition Monitoring in Rotating Machines

Bearings are important machine parts and their condition is often critical to success of an operation or process, hence there is a great need for periodic knowledge of their performance. According to reported research works in the past several years, it is believed that the extracted information from acoustic emission (AE) signals can be used for bearing condition monitoring. In this work, a novel parameter based on using the ratio of AE mean (μ) and AE standard deviation (σ ), formulated as μ/σ is proposed to distinguish between lubricated and dry bearings. A heavy duty test rig was used in experimental work. Various levels of radial loads and rotational speed (ω) were applied to rotating shaft, which is connected to rolling element bearings. It was found that, except few cases, regardless of various levels of radial loads used, at higher levels of rotational speed, dry and lubricated bearings can be clearly distinguished when using proposed parameter.