Rolling element bearing is a vital component in rotating machinery, such as a wind turbine (WT) system. By accurately monitoring its health condition, the faults can be detected at an early stage, providing sufficient lead time to perform maintenance and hence reducing accidents and economic losses. Bearing usually suffers from various wears and tears, which result in a gradual increase in clearance through its lifetime. Insufficient understanding of vibration characteristics under different clearances brings difficulties for bearing condition monitoring. Thus, this paper presents a nonlinear bearing vibration model with six degrees of freedom (DOF) to investigate the vibration characteristics under different radial clearances and load conditions. Then, a dedicated bearing test is established to verify the reasonability and effectiveness of the vibration model. Furthermore, a comprehensive simulation analysis is conducted to study the vibration characteristics over an extended range of the internal radial clearance and external load. Results show that the dynamic force on each ball presents an impulse whose magnitudes increases whereas the pulse width reduces with clearance increases. Ball pass frequency of outer race (BPFO) is the dominant modulation component and the frequency is in accordance with the number of dynamic force impulses. Two indicators, i.e., root mean square (RMS) value and spectral centroid, are proposed to indicate clearance changes. In general, they show an uptrend with the increase in clearance, which is in line with the dynamic force increasing with clearance, especially the spectral centroid of the low frequency band. However, it should be noted that the RMS value and spectral centroid exhibit a fluctuating behavior due to nonlinear vibration responses. For the first time, this study shows the details of vibration characteristics with clearance variations and provides a foundation for monitoring the bearing conditions before any obvious local defects on raceways.

Gearbox is a key component in mechanical transmission and faults on gears will lead to breakdowns and unscheduled downtime. Health condition monitoring and remaining useful life (RUL) prediction can provide sufficient leading time for gearbox timely maintenance. To some degree, the RUL prediction accuracy relies on the performance of the diagnostic features on reflecting the degradation of gears during its lifetime. However, most current commonly used features fail to reveal the fault mechanism hidden behind vibration signal and hold poor capability on noise cancellation. In this paper, modulation signal bispectrum (MSB) is proposed to reveal the signal modulation mechanism and monitor the health condition of gears. Then, an improved relevance vector machine (IMRVM) is introduced to realize the process of RUL prediction. Last, a run-to-failure test rig is designed to verify the effectiveness the MSB features for RUL prediction. Results show that MSB possesses better performance on denoising and capturing the weak variation due to modulation in gear system. The optimal MSB features after selection show better performance on reflecting the degradation of the gear and have higher prediction accuracy for gear RUL prediction comparing with RMS, kurtosis and so on. These findings provided more useful and practical information for gear RUL prediction and gearbox maintenance.

Bearings are key components in rotating machinery, which is widely used in many fields, such as CNC machines, wind turbines and induction machines. The increasingly harsh operation environment can lead to wear and tear on raceways and reduce the precision and reliability of bearing or even machinery. Lubrication could relieve the wear to some degree, which is benefit to prolong the bearing’s life. Thus, investigation on the vibration responses under the influence of oil film is of great significance. However, for mechanism analysis, how to include the oil film into the bearing dynamic model affects the result and efficiency of solution. To address this problem, this study proposed a fast algorithm through load distribution and interpolation when calculating oil film stiffness and thickness during the solution of bearing vibration model. Analysis of oil film on vibration is carried out and a bearing test rig is designed to verify the proposed model. Numerical simulation result shows that rotational speed and load have vital effect on oil film and vibration, and oil film can play a role of shock absorption. The experimental result is consistent with the simulation, which shows that the proposed model has a better performance on modeling bearing vibration and the method of considering oil film is reasonable.