Abstract
The health status of these bearings efficiently and effectively can be monitor using the spectrum analysis. The rolling element bearings are of two types rolling and sliding rolling element bearings, and these Sliding rolling bearings are of two types, linear and journal rolling bearings. The combination of both roller and ball can be referred to as rolling element bearings and can be widely used in many applications. The usage can be wide a range because of the permit rotary motion of shafts, starting from aircraft gas turbines, power transmissions, electric motors, bicycles, roller skates and many more. As the rolling element bearings have many advantages, compared with other types of bearings. As they are commonly referred to as antifriction bearings because the amount of lubrication required is less. In this paper, a new dimension is added for the spectrum analysis of rolling element bearing faults detection, analysis and diagnosis. Her the rolling element bearing faults are studied in comparison with three major factors like the time domain, frequency domain and spectrum plot obtained for the rolling element faults. The spectrum obtained from the normal and inner, outer race faults are consider mapping the spectrum analysis in more effective way.
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