Non-linear dynamic behaviors of rolling element bearings due to surface waviness

2004 ◽  
Vol 272 (3-5) ◽  
pp. 557-580 ◽  
Author(s):  
S.P. Harsha ◽  
K. Sandeep ◽  
R. Prakash
Keyword(s):  
Rolling Element Bearings ◽  
Surface Waviness ◽  
Dynamic Behaviors ◽  
Linear Dynamic ◽  
Rolling Element ◽  
Non Linear

scholarly journals Influence of raceway waviness on the level of vibration in rolling-element bearings

2017 ◽  
Vol 65 (4) ◽  
pp. 541-551 ◽  
Author(s):  
S. Adamczak ◽  
P. Zmarzły
Keyword(s):  
Ball Bearing ◽  
Correlation Coefficients ◽  
Rolling Element Bearings ◽  
Test Results ◽  
Frequency Bandwidth ◽  
Surface Waviness ◽  
Medium Frequency ◽  
Method Of Calculation ◽  
Rolling Element ◽  
Bearing Vibration

AbstractThis paper provides a quantitative analysis of how raceway waviness (RONt) in 6304-type bearings affects their vibration. The waviness of bearing races was measured at the actual points of contact between the balls and the races. The measurements were conducted in the range of 16–50 undulations per revolution (UPR). The bearing vibration was analyzed in three bandwidths of frequency: low (LB) (50 ÷ 300 Hz), medium MB (300 ÷ 1800 Hz) and high HB (1800 ÷ 10 000 Hz), as well as in the full RMS bandwidth. The paper also presents the procedure used to determine the actual points of contact between the ball and each race to specify the point of waviness measurement. The method of calculation of the contact angle for a ball bearing is also discussed. The Pearson linear correlation coefficients were determined to analyze the relationships between the waviness parameters and the level of vibration. The test results show that an increase in the surface waviness on the inner and outer raceways causes an increase in the vibration level. The influence is most visible for the medium frequency bandwidth.

Sensitivity Analysis of an Information Maximization Approach to the Blind Separation of the Vibration Responses of Defective Rolling Element Bearings

2005 ◽  
Author(s):  
C. Yiakopoulos ◽  
I. Antoniadis
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Linear Function ◽  
Network Structure ◽  
Vibration Response ◽  
Rolling Element Bearings ◽  
Rolling Element ◽  
Non Linear ◽  
Vibration Responses ◽  
Neural Network Structure

Vibration response of rotating machines is typically mixed and corrupted by a variety of interfering sources and noise, leading to the necessity for the isolation of the useful signal components. A relevant frequently encountered industrial case is the need for the separation of the vibration responses of the same type of bearings inside the same machine. For this purpose, a Blind Source Separation procedure has been successfully applied, based on the maximization of the information transferred in a neural network structure. Thus, a key element for the success of the proposed procedure is the non-linear function used in this single layer Neural Network structure. However, since the vibration response of defective rolling element bearings is characterized by signals with super-Gaussian distributions, a sensitivity analysis of this non-linear function is necessary. First, this analysis is performed in a set of numerical experiments, based on dynamic models of defective bearings. Finally, the same analysis is applied in an experimental test rig.

scholarly journals Multi-Dimensional Harmonic Balance Applied to Rotor Dynamics

2007 ◽  
Author(s):  
Mikhail Guskov ◽  
Jean-Jacques Sinou ◽  
Fabrice Thouverez
Keyword(s):  
Harmonic Balance ◽  
Dynamical Behavior ◽  
Steady State Solution ◽  
Rotor Dynamics ◽  
Radial Clearance ◽  
Rolling Element Bearings ◽  
Arc Length ◽  
Test Rig ◽  
Rolling Element ◽  
Non Linear

A large number of technical systems feature multi-frequency dynamical behavior. Multiple shaft rotating machinery, subject to simultaneous unbalances spinning at different speeds is a particular case of such systems. Common methods of steady state solution are not valid when the addressed systems have non-linear properties. This study presents a generalized version of harmonic balance coupled with arc-length continuation, developed in order to treat the dynamics of a dual shaft test rig provided with an inter-shaft bearing. The non-linearities are brought about by the presence of rolling element bearings with radial clearance. Numerically, the non-linear terms are taken into account via an AFT (alternating frequency-time domain) procedure, involving multi-dimensional FFT. The numerical results show the presence of response peaks corresponding to the rig’s eigenmodes predicted by linear eigensolution and from experiments. The overall behavior is consistent with the counter-rotating character of the machine operation. Non-linear phenomena due to bearings are also observed, especially the stiffening shape of peaks and apparent pedestal anisotropy involving the presence of backward whirling components in the system’s motion.

Experimental investigation on time-domain features in the diagnosis of rolling element bearings by acoustic emission

2021 ◽  
pp. 107754632110161
Author(s):  
Aref Aasi ◽  
Ramtin Tabatabaei ◽  
Erfan Aasi ◽  
Seyed Mohammad Jafari
Keyword(s):  
Acoustic Emission ◽  
Condition Monitoring ◽  
Time Domain ◽  
Central Moment ◽  
Rolling Element Bearings ◽  
Test Rig ◽  
Acoustic Emission Sensor ◽  
Outer Race ◽  
Common Time ◽  
Rolling Element

Inspired by previous achievements, different time-domain features for diagnosis of rolling element bearings are investigated in this study. An experimental test rig is prepared for condition monitoring of angular contact bearing by using an acoustic emission sensor for this purpose. The acoustic emission signals are acquired from defective bearing, and the sensor takes signals from defects on the inner or outer race of the bearing. By studying the literature works, different domains of features are classified, and the most common time-domain features are selected for condition monitoring. The considered features are calculated for obtained signals with different loadings, speeds, and sizes of defects on the inner and outer race of the bearing. Our results indicate that the clearance, sixth central moment, impulse, kurtosis, and crest factors are appropriate features for diagnosis purposes. Moreover, our results show that the clearance factor for small defects and sixth central moment for large defects are promising for defect diagnosis on rolling element bearings.

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