Effects of transmission shaft flexibility on rolling element bearing tribodynamics in a high-performance transmission

2021 ◽  
Vol 165 ◽  
pp. 104440
Author(s):  
Brett Friskney ◽  
Mahdi Mohammadpour ◽  
Stephanos Theodossiades ◽  
Christopher Craig ◽  
Greg Rapson
Author(s):  
Wenbing Tu ◽  
Jinwen Yang ◽  
Wennian Yu ◽  
Ya Luo

The vibration response of rolling element bearing has a close relation with its fault. An accurate evaluation of the bearing vibration response is essential to the bearing fault diagnosis. At present, most bearing dynamics models are built based on rigid assumptions, which may not faithfully reveal the dynamic characteristics of bearing in the presence of fault. Moreover, previous similar works mainly focus on the fault with a specified size without considering the varying contact characteristics as the fault evolves. This paper developed an explicit dynamics finite element model for the bearing with three types of raceway faults considering the flexibility of each bearing component in order to accurately study the contact characteristic and vibration mechanism of defective bearings in the process of fault evolution. The developed model is validated by comparing its simulation results with both analytical and experimental results. The dynamic contact patterns between the rolling elements and the fault, the additional displacement due to the fault and the faulty characteristics within the bearing vibration signal during the fault evolution process are investigated. The analysis results from this work can provide practitioners an in-depth understanding towards the internal contact characteristics with the existence of raceway fault and theoretical basis for rolling bearing fault diagnosis.


2014 ◽  
Vol 889-890 ◽  
pp. 666-670
Author(s):  
Zong Tao Li ◽  
Yan Gao ◽  
Xiang Zhou ◽  
Yu Guo

The cepstrum edit scheme for the vibration feature extraction of the faulty rolling element bearing (REB) is studied in this paper. By combined the time synchronous average (TSA) and the real cepstrum to localize and edit the cepstral lines of the original vibration, the unwanted discrete frequency components can be removed. Then, a corresponding inverse procedure is designed, in which the edited cepstrum and the original phase spectrum are employed to reconstruct the edited vibration for the REB feature extraction. Simulation verified the scheme positively.


2005 ◽  
Vol 2005 (1) ◽  
pp. 53-59 ◽  
Author(s):  
David P. Fleming ◽  
J. V. Poplawski

Rolling-element bearing forces vary nonlinearly with bearing deflection. Thus, an accurate rotordynamic analysis requires that bearing forces corresponding to the actual bearing deflection be utilized. For this work, bearing forces were calculated by COBRA-AHS, a recently developed rolling-element bearing analysis code. Bearing stiffness was found to be a strong function of bearing deflection, with higher deflection producing markedly higher stiffness. Curves fitted to the bearing data for a range of speeds and loads were supplied to a flexible rotor unbalance response analysis. The rotordynamic analysis showed that vibration response varied nonlinearly with the amount of rotor imbalance. Moreover, the increase in stiffness as critical speeds were approached caused a large increase in rotor and bearing vibration amplitude over part of the speed range compared to the case of constant-stiffness bearings. Regions of bistable operation were possible, in which the amplitude at a given speed was much larger during rotor acceleration than during deceleration. A moderate amount of damping will eliminate the bistable region, but this damping is not inherent in ball bearings.


Author(s):  
W B Xiao ◽  
J Chen ◽  
G M Dong ◽  
Y Zhou ◽  
Z Y Wang

This paper presents a novel multichannel fusion approach based on coupled hidden Markov models (CHMMs) for rolling element bearing fault diagnosis. Different from a hidden Markov model (HMM), a CHMM contains multiple state sequences and observation sequences, and hence has powerful potential for multichannel fusion. In this study, a two-chain CHMM is employed to integrate the two-channel vibration signals collected from bearings, i.e. the horizontal and vertical vibration signals. Efficient probabilistic inference and parameter estimation algorithms are developed for the model. An experiment was carried out to validate the proposed approach. Normalized wavelet packet energy and wavelet packet energy entropy are extracted as features for classification respectively. Then, the results of the proposed approach are compared with those of the currently used approach based on HMMs and one-channel signals. The results show that the proposed approach is feasible and effective to improve the classification rate.


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